@prefix dc: .
@prefix ngm: .
@prefix ngmi: .
@prefix owl: .
@prefix prov: .
@prefix rdf: .
@prefix rdfs: .
@prefix skos: .
@prefix vc: .
@prefix xsd: .
dc:creator a owl:AnnotationProperty .
skos:Concept a owl:Class ;
rdfs:label "Concept"@en .
skos:broader a owl:AnnotationProperty .
ngm:1-hive a owl:Class ;
rdfs:comment "A decentralised community and DAO that issues the Honey community currency and develops governance tooling such as the Gardens framework for conviction voting."@en ;
rdfs:label "1Hive"@en ;
rdfs:subClassOf ngm:dao ;
rdfs:subClassOf _:r1 ;
rdfs:subClassOf _:r2 ;
vc:bridgesTo ngm:liquid-democracy ;
vc:enables ngm:quadratic-funding ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:dao ;
vc:requires ngm:governance-token ;
vc:slug "1-hive" ;
vc:sourceDomain "governance" .
ngm:1-inch a owl:Class ;
rdfs:comment "A decentralised exchange aggregator that routes trades across multiple liquidity sources to find favourable execution prices on Ethereum and other chains."@en ;
rdfs:label "1inch"@en ;
rdfs:subClassOf ngm:decentralized-exchange ;
rdfs:subClassOf _:r3 ;
rdfs:subClassOf _:r4 ;
rdfs:subClassOf _:r5 ;
vc:bridgesTo ngm:uniswap ;
vc:enables ngm:liquidity-pool ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:automated-market-maker ;
vc:requires ngm:ethereum-smart-contract-platform ;
vc:requires ngm:smart-contract ;
vc:slug "1-inch" ;
vc:sourceDomain "blockchain" .
ngm:1hive-gardens-specification a skos:Concept ;
rdfs:label "1hive Gardens Specification"@en .
ngm:2-d-li-dar a owl:Class ;
rdfs:comment "2D LiDAR is a laser scanning sensor that emits a rotating beam in a single horizontal or vertical plane, producing a planar point cloud used for obstacle detection, proximity sensing, and 2D mapping. It is widely deployed on mobile robots and autonomous guided vehicles where full 3D sensing is unnecessary or cost-prohibitive."@en ;
rdfs:label "2D LiDAR"@en ;
rdfs:subClassOf ngm:lidar ;
rdfs:subClassOf ngm:robo-perception ;
skos:broader ngm:robo-perception ;
vc:bridgesTo ngm:lidar ;
vc:enables ngm:localisation ;
vc:enables ngm:proximity-detection ;
vc:enables ngm:simultaneous-localisation-and-mapping ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:robo-perception ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:3-d-li-dar ;
vc:relatedTo ngm:laser-scanner ;
vc:relatedTo ngm:point-cloud ;
vc:relatedTo ngm:proximity-sensor ;
vc:relatedTo ngm:slam ;
vc:relatedTo ngm:ultrasonic-sensor ;
vc:slug "2-d-li-dar" ;
vc:sourceDomain "robotics" ;
vc:uses ngm:lidar-scanning .
ngm:21-cfr a skos:Concept ;
rdfs:label "21 Cfr"@en .
ngm:24-7-carbon-free-energy a skos:Concept ;
rdfs:label "24 7 Carbon Free Energy"@en .
ngm:24-7-customer-service a skos:Concept ;
rdfs:label "24 7 Customer Service"@en .
ngm:24-7-trading a skos:Concept ;
rdfs:label "24 7 Trading"@en .
ngm:2d-display a skos:Concept ;
rdfs:label "2d Display"@en .
ngm:2d-sprite a skos:Concept ;
rdfs:label "2d Sprite"@en .
ngm:2d-video a skos:Concept ;
rdfs:label "2d Video"@en .
ngm:3-d-and-4-d a owl:Class ;
rdfs:comment "The domain of three-dimensional and four-dimensional content creation, covering tools, techniques, and AI-powered pipelines for generating, editing, and rendering 3D assets and temporally dynamic (4D) representations. Encompasses text-to-3D systems (NVIDIA Edify, Luma Genie, Point-E), neural radiance fields, Gaussian splatting, and diffusion-based mesh generation, as well as 6D pose estimation, scene-scale generation, and integration with AR/VR workflows."@en ;
rdfs:label "3D and 4D"@en ;
rdfs:subClassOf ngm:sc-content-and-assets ;
skos:broader ngm:sc-content-and-assets ;
vc:enables ngm:3-d-asset ;
vc:enables ngm:augmented-reality ;
vc:enables ngm:pose-estimation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:computer-vision ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:slug "3-d-and-4-d" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:deep-learning ;
vc:uses ngm:diffusion-model ;
vc:uses ngm:generative-ai ;
vc:uses ngm:neural-radiance-field .
ngm:3-d-animation a owl:Class ;
rdfs:comment "3D Animation is the discipline of creating motion in three-dimensional digital environments using techniques such as keyframe animation, motion capture, and procedural simulation. It underpins character movement, environmental dynamics, and cinematic sequences in spatial computing platforms, game engines, and metaverse applications."@en ;
rdfs:label "3D Animation"@en ;
rdfs:subClassOf ngm:animation-technique ;
rdfs:subClassOf _:r10 ;
rdfs:subClassOf _:r11 ;
rdfs:subClassOf _:r6 ;
rdfs:subClassOf _:r7 ;
rdfs:subClassOf _:r8 ;
rdfs:subClassOf _:r9 ;
vc:bridgesTo ngm:generative-ai ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:contrastsWith ngm:animation ;
vc:dependsOn ngm:graphics-processing-unit ;
vc:dependsOn ngm:scene-graph ;
vc:enables ngm:avatar ;
vc:enables ngm:digital-twin ;
vc:enables ngm:immersive-experience ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:animation-state-machine ;
vc:hasPart ngm:blend-shape ;
vc:hasPart ngm:character-rigging ;
vc:hasPart ngm:keyframe-animation ;
vc:isPartOf ngm:sc-content-and-assets ;
vc:isPartOf ngm:visual-effects ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:level-of-detail ;
vc:relatedTo ngm:rendering-pipeline ;
vc:requires ngm:3-d-asset ;
vc:requires ngm:game-engine ;
vc:slug "3-d-animation" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:gltf-standard ;
vc:standardizedBy ngm:iso-iec-jtc-1-sc-24 ;
vc:standardizedBy ngm:usd ;
vc:supports ngm:extended-reality ;
vc:supports ngm:real-time-rendering ;
vc:uses ngm:inverse-kinematics ;
vc:uses ngm:motion-capture ;
vc:uses ngm:physics-simulation ;
vc:uses ngm:procedural-animation .
ngm:3-d-asset a owl:Class ;
rdfs:comment "A 3D Asset is a discrete, self-contained digital artefact encoding three-dimensional geometry, surface materials, skeletal animation rigs, and associated metadata in a machine-readable interchange format such as glTF 2.0, USD, FBX, or OBJ. Such assets are produced by digital content creation tools, stored in asset management systems with versioning and provenance records, and consumed at runtime by rendering engines, game engines, and spatial computing platforms. Production-quality 3D assets typically incorporate multiple levels of detail (LOD), physically-based rendering (PBR) material maps (albedo, metallic-roughness, normal, occlusion, emissive), collision meshes for physics simulation, and compressed texture atlases optimised for a target hardware envelope. Cross-platform delivery relies on open standards maintained by the Khronos Group and Pixar/Academy Software Foundation, enabling asset reuse across metaverse environments, digital twins, extended reality (XR) applications, and game titles."@en ;
rdfs:label "3D Asset"@en ;
rdfs:subClassOf ngm:digital-asset ;
rdfs:subClassOf _:r20 ;
rdfs:subClassOf _:r21 ;
rdfs:subClassOf _:r22 ;
rdfs:subClassOf _:r23 ;
rdfs:subClassOf _:r24 ;
rdfs:subClassOf _:r25 ;
rdfs:subClassOf _:r26 ;
vc:bridgesTo ngm:generative-ai ;
vc:bridgesTo ngm:neural-radiance-field ;
vc:bridgesTo ngm:non-fungible-token ;
vc:contrastsWith ngm:2d-sprite ;
vc:contrastsWith ngm:voxel ;
vc:enables ngm:digital-twin ;
vc:enables ngm:extended-reality ;
vc:enables ngm:metaverse ;
vc:enables ngm:real-time-rendering ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:collision-mesh ;
vc:hasPart ngm:level-of-detail ;
vc:hasPart ngm:polygon-mesh ;
vc:hasPart ngm:skeletal-rig ;
vc:hasPart ngm:texture-map ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:game-engine ;
vc:relatedTo ngm:scene-graph ;
vc:relatedTo ngm:spatial-computing ;
vc:requires ngm:asset-pipeline ;
vc:requires ngm:digital-content-creation ;
vc:requires ngm:physically-based-rendering ;
vc:slug "3-d-asset" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:academy-software-foundation ;
vc:standardizedBy ngm:khronos-group ;
vc:standardizedBy ngm:w3-c ;
vc:uses ngm:digital-asset-management ;
vc:uses ngm:gltf-standard ;
vc:uses ngm:texture-compression ;
vc:uses ngm:usd .
ngm:3-d-asset-standard a owl:Class ;
rdfs:comment "A 3D Asset Standard is a formal specification defining the file formats, metadata schemas, coordinate systems, material models, animation encodings, and interoperability protocols required for consistent creation, exchange, and real-time rendering of three-dimensional digital content across diverse software platforms and runtime environments. Such standards normalise vertex data structures, physically based rendering (PBR) material pipelines, level-of-detail hierarchies, skeletal animation rigs, and compression algorithms so that assets created in one authoring tool function correctly in another without manual conversion or data loss. Prominent examples include the Khronos Group glTF 2.0 specification for web and mobile 3D delivery, Pixar's Universal Scene Description (USD/USDZ) for complex scene composition, and the Metaverse Standards Forum interoperability profiles. These specifications underpin spatial computing, extended reality, game engines, digital-twin platforms, and emerging metaverse ecosystems by ensuring deterministic visual fidelity and semantic asset identity across the entire content pipeline."@en ;
rdfs:label "3D Asset Standard"@en ;
rdfs:subClassOf ngm:interoperability-standard ;
rdfs:subClassOf _:r12 ;
rdfs:subClassOf _:r13 ;
rdfs:subClassOf _:r14 ;
rdfs:subClassOf _:r15 ;
rdfs:subClassOf _:r16 ;
rdfs:subClassOf _:r17 ;
rdfs:subClassOf _:r18 ;
rdfs:subClassOf _:r19 ;
vc:bridgesTo ngm:non-fungible-token ;
vc:bridgesTo ngm:semantic-web-linked-data-standard ;
vc:contrastsWith ngm:fbx ;
vc:contrastsWith ngm:proprietary-asset-format ;
vc:enables ngm:asset-interoperability ;
vc:enables ngm:digital-twin ;
vc:enables ngm:extended-reality ;
vc:enables ngm:real-time-rendering ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:gltf-standard ;
vc:hasPart ngm:level-of-detail ;
vc:hasPart ngm:physically-based-rendering ;
vc:hasPart ngm:usd ;
vc:implements ngm:iso-iec-14496-16 ;
vc:implements ngm:open-standard ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:digital-content-creation ;
vc:relatedTo ngm:iso-iec-14496-16 ;
vc:relatedTo ngm:semantic-spatial-web-layer ;
vc:requires ngm:coordinate-system ;
vc:requires ngm:mesh-compression ;
vc:requires ngm:texture-atlas ;
vc:slug "3-d-asset-standard" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:academy-software-foundation ;
vc:standardizedBy ngm:khronos-group ;
vc:standardizedBy ngm:metaverse-standards-forum ;
vc:supports ngm:augmented-reality ;
vc:supports ngm:game-engine ;
vc:supports ngm:metaverse-platform ;
vc:uses ngm:material-x ;
vc:uses ngm:scene-graph ;
vc:uses ngm:skeletal-animation .
ngm:3-d-content-creation a owl:Class ;
rdfs:comment "3D Content Creation encompasses the end-to-end process of designing, modelling, texturing, rigging, and rendering three-dimensional digital assets and environments for use in games, film, XR experiences, and digital twins. It spans artistic and technical disciplines ranging from polygon modelling and UV unwrapping to physically based material authoring and real-time rendering optimisation. The discipline bridges human creative intent and the technical pipelines that deliver interactive or cinematic experiences."@en ;
rdfs:label "3D Content Creation"@en ;
rdfs:subClassOf ngm:content-creation ;
vc:enables ngm:3-d-content-pipeline ;
vc:enables ngm:digital-twin-creation ;
vc:enables ngm:xr-applications ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:3-d-asset ;
vc:relatedTo ngm:3-d-content-generation ;
vc:relatedTo ngm:motion-capture ;
vc:slug "3-d-content-creation" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:3-d-modeling-software ;
vc:uses ngm:3-d-rendering-engine ;
vc:uses ngm:physically-based-rendering .
ngm:3-d-content-generation a owl:Class ;
rdfs:comment "The computational process of producing three-dimensional digital content through algorithmic and AI-driven methods, encompassing procedural generation, neural rendering, NeRF-based scene synthesis, and GAN-based 3D model creation. Applications span game development, virtual reality, digital twins, and automated CAD, enabling scalable production of photorealistic 3D assets from text or image inputs."@en ;
rdfs:label "3D Content Generation"@en ;
rdfs:subClassOf ngm:generative-ai ;
rdfs:subClassOf _:r27 ;
rdfs:subClassOf _:r28 ;
rdfs:subClassOf _:r29 ;
rdfs:subClassOf _:r30 ;
rdfs:subClassOf _:r31 ;
rdfs:subClassOf _:r32 ;
vc:bridgesTo ngm:autonomous-robot ;
vc:bridgesTo ngm:digital-asset ;
vc:bridgesTo ngm:extended-reality ;
vc:bridgesTo ngm:metaverse ;
vc:contrastsWith ngm:3d-modelling ;
vc:contrastsWith ngm:photogrammetry ;
vc:dependsOn ngm:gpu-compute ;
vc:enables ngm:digital-asset ;
vc:enables ngm:digital-twin ;
vc:enables ngm:game-development ;
vc:enables ngm:virtual-world ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:mesh-generation ;
vc:hasPart ngm:neural-rendering ;
vc:hasPart ngm:procedural-generation ;
vc:hasPart ngm:texture-synthesis ;
vc:qualityScore "0.68"^^xsd:float ;
vc:relatedTo ngm:3-d-animation ;
vc:relatedTo ngm:3-d-asset ;
vc:requires ngm:3-d-scene-representation ;
vc:requires ngm:computer-graphics ;
vc:requires ngm:deep-learning ;
vc:slug "3-d-content-generation" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:deep-learning ;
vc:uses ngm:diffusion-model ;
vc:uses ngm:generative-adversarial-network ;
vc:uses ngm:neural-radiance-field ;
vc:uses ngm:neural-rendering ;
vc:uses ngm:procedural-generation .
ngm:3-d-content-pipeline a owl:Class ;
rdfs:comment "The comprehensive workflows, tools, and methodologies for creating, processing, optimising, and delivering three-dimensional assets for metaverse and spatial computing applications. A 3D content pipeline spans concept art, geometry modelling, UV mapping, PBR texturing, rigging, LOD generation, and platform-specific optimisation, integrating DCC tools, game engines, version control, and CI/CD systems to support distributed teams and continuous asset delivery."@en ;
rdfs:label "3D Content Pipeline"@en ;
rdfs:subClassOf ngm:software-engineering ;
rdfs:subClassOf _:r33 ;
rdfs:subClassOf _:r34 ;
rdfs:subClassOf _:r35 ;
rdfs:subClassOf _:r36 ;
rdfs:subClassOf _:r37 ;
rdfs:subClassOf _:r38 ;
rdfs:subClassOf _:r39 ;
rdfs:subClassOf _:r40 ;
vc:bridgesTo ngm:cloud-computing ;
vc:dependsOn ngm:asset-management-system ;
vc:dependsOn ngm:ci-cd-automation ;
vc:enables ngm:metaverse-and-telecollaboration ;
vc:enables ngm:procedural-generation ;
vc:enables ngm:real-time-rendering ;
vc:enables ngm:xr-content-delivery ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:3-d-animation ;
vc:hasPart ngm:3-d-asset ;
vc:hasPart ngm:character-rigging ;
vc:hasPart ngm:level-of-detail ;
vc:hasPart ngm:rendering-pipeline ;
vc:qualityScore "0.73"^^xsd:float ;
vc:relatedTo ngm:3-d-content-generation ;
vc:relatedTo ngm:digital-twin ;
vc:requires ngm:digital-content-creation ;
vc:requires ngm:game-engine ;
vc:requires ngm:version-control ;
vc:slug "3-d-content-pipeline" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:gltf-standard ;
vc:standardizedBy ngm:usd ;
vc:supports ngm:distributed-team-collaboration ;
vc:uses ngm:geometry-processing ;
vc:uses ngm:physically-based-rendering .
ngm:3-d-design a owl:Class ;
rdfs:comment "3D Design is the creative and technical discipline of conceiving, modelling, and refining three-dimensional digital objects and environments for interactive, immersive, or real-time applications. It encompasses spatial composition, form language, and visual hierarchy adapted for game engines, virtual reality, and metaverse platforms, requiring performance-conscious workflows such as level-of-detail strategies, UV unwrapping, and real-time shader design."@en ;
rdfs:label "3D Design"@en ;
rdfs:subClassOf ngm:software-engineering ;
rdfs:subClassOf _:r41 ;
rdfs:subClassOf _:r42 ;
rdfs:subClassOf _:r43 ;
vc:enables ngm:3-d-content-generation ;
vc:enables ngm:real-time-rendering ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:3-d-asset ;
vc:isPartOf ngm:3-d-content-pipeline ;
vc:isPartOf ngm:3-d-development ;
vc:qualityScore "0.0"^^xsd:float ;
vc:requires ngm:3d-modelling ;
vc:requires ngm:rendering-engine ;
vc:slug "3-d-design" ;
vc:sourceDomain "infrastructure" .
ngm:3-d-development a owl:Class ;
rdfs:comment "3D Development encompasses the modologies, tools, and workflows for creating, iterating, and deploying three-dimensional digital assets and environments."@en ;
rdfs:label "3D Development"@en ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf ngm:software-development ;
rdfs:subClassOf _:r44 ;
rdfs:subClassOf _:r45 ;
skos:broader ngm:sc-platform-and-environment ;
vc:bridgesTo ngm:3d-modelling ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:game-engine ;
vc:bridgesTo ngm:software-development ;
vc:enables ngm:metaverse-content-creation ;
vc:enables ngm:virtual-environment-design ;
vc:enables ngm:xr-applications ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:3-d-graphics-standard ;
vc:requires ngm:3-d-rendering-engine ;
vc:slug "3-d-development" ;
vc:sourceDomain "spatial-computing" .
ngm:3-d-engine a owl:Class ;
rdfs:comment "A 3D engine is software that handles the representation, rendering, physics simulation, and animation of three-dimensional scenes, providing an abstraction layer over GPU hardware and platform-specific graphics APIs so developers can build interactive applications and simulations without writing low-level graphics code."@en ;
rdfs:label "3D Engine"@en ;
rdfs:subClassOf ngm:game-engine ;
rdfs:subClassOf _:r46 ;
rdfs:subClassOf _:r47 ;
rdfs:subClassOf _:r48 ;
rdfs:subClassOf _:r49 ;
rdfs:subClassOf _:r50 ;
rdfs:subClassOf _:r51 ;
rdfs:subClassOf _:r52 ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:bridgesTo ngm:physics-simulation-engine ;
vc:bridgesTo ngm:robotics ;
vc:enables ngm:3-d-engine ;
vc:enables ngm:augmented-reality ;
vc:enables ngm:digital-twin ;
vc:enables ngm:virtual-reality ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:animation-system ;
vc:hasPart ngm:physics-simulation-engine ;
vc:hasPart ngm:rendering-pipeline ;
vc:hasPart ngm:scene-graph ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:extended-reality ;
vc:relatedTo ngm:level-of-detail ;
vc:requires ngm:computational-geometry ;
vc:requires ngm:graphics-processing-unit ;
vc:requires ngm:linear-algebra ;
vc:requires ngm:shader ;
vc:slug "3-d-engine" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:metaverse ;
vc:supports ngm:spatial-computing ;
vc:uses ngm:directx ;
vc:uses ngm:open-gl ;
vc:uses ngm:vulkan ;
vc:uses ngm:webgpu .
ngm:3-d-file-format a owl:Class ;
rdfs:comment "3D File Formats are standardised container structures for encoding three-dimensional geometric data, textures, materials, animations, and metadata, enabling asset portability across tools, rendering engines, and platforms."@en ;
rdfs:label "3D File Format"@en ;
rdfs:subClassOf ngm:data-format-standard ;
rdfs:subClassOf _:r53 ;
rdfs:subClassOf _:r54 ;
rdfs:subClassOf _:r55 ;
rdfs:subClassOf _:r56 ;
rdfs:subClassOf _:r57 ;
rdfs:subClassOf _:r58 ;
vc:bridgesTo ngm:3-d-model ;
vc:bridgesTo ngm:asset-pipeline ;
vc:bridgesTo ngm:data-format-standard ;
vc:bridgesTo ngm:interoperability ;
vc:bridgesTo ngm:metaverse-infrastructure ;
vc:enables ngm:3-d-rendering ;
vc:enables ngm:augmented-reality ;
vc:enables ngm:cross-platform-asset-exchange ;
vc:enables ngm:digital-asset-management ;
vc:enables ngm:real-time-graphics ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:material-definition ;
vc:hasPart ngm:mesh-data ;
vc:hasPart ngm:texture-map ;
vc:implements ngm:gltf-standard ;
vc:implements ngm:usd ;
vc:isPartOf ngm:asset-pipeline ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:3-d-model ;
vc:relatedTo ngm:point-cloud ;
vc:requires ngm:animation-keyframes ;
vc:requires ngm:coordinate-system ;
vc:requires ngm:material-definition ;
vc:requires ngm:mesh-data ;
vc:slug "3-d-file-format" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:khronos-group ;
vc:standardizedBy ngm:pixar-animation-studios ;
vc:supports ngm:level-of-detail ;
vc:supports ngm:physics-simulation ;
vc:uses ngm:binary-encoding ;
vc:uses ngm:data-compression .
ngm:3-d-gaussian-splatting a owl:Class ;
rdfs:comment "A neural rendering technique that represents 3D scenes as collections of millions of 3D Gaussian primitives with learnable positions, colours, opacities, and covariances, enabling photorealistic real-time rendering at 100+ frames per second through GPU-accelerated rasterisation, revolutionising telepresence and immersive collaboration with unprecedented visual fidelity."@en ;
rdfs:label "3D Gaussian Splatting"@en ;
rdfs:subClassOf ngm:neural-rendering ;
rdfs:subClassOf ngm:tele-050-neural-rendering-telepresence ;
rdfs:subClassOf _:r59 ;
rdfs:subClassOf _:r60 ;
rdfs:subClassOf _:r61 ;
rdfs:subClassOf _:r62 ;
vc:bridgesTo ngm:extended-reality ;
vc:bridgesTo ngm:tele-050-neural-rendering-telepresence ;
vc:bridgesTo ngm:web-xr ;
vc:contrastsWith ngm:neural-radiance-fields ;
vc:contrastsWith ngm:tele-060-instant-ngp ;
vc:dependsOn ngm:adam-optimiser ;
vc:dependsOn ngm:multi-view-photography ;
vc:dependsOn ngm:point-cloud ;
vc:enables ngm:avatar ;
vc:enables ngm:novel-view-synthesis ;
vc:enables ngm:photorealistic-telepresence ;
vc:enables ngm:photorealistictelepresence ;
vc:enables ngm:tele-053-volumetric-video-conferencing ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:gaussian-primitive ;
vc:hasPart ngm:spherical-harmonics ;
vc:implements ngm:alpha-blending ;
vc:isPartOf ngm:novel-view-synthesis ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:3-d-scene-reconstruction ;
vc:relatedTo ngm:virtual-reality-telepresence ;
vc:requires ngm:differentiable-rendering ;
vc:requires ngm:structure-from-motion ;
vc:slug "3-d-gaussian-splatting" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:ssim-loss ;
vc:uses ngm:stochastic-gradient-descent .
ngm:3-d-generation a owl:Class ;
rdfs:comment "3D Generation refers to the automated or semi-automated creation of three-dimensional geometry, appearance, and scene representations using machine learning models, procedural algorithms, or hybrid approaches. Techniques include text-to-3D, image-to-3D, and scene-level generation via neural radiance fields, Gaussian splatting, diffusion models, and large multi-modal networks. The field aims to dramatically reduce the time and skill threshold required to produce photorealistic or stylised 3D content for gaming, film, spatial computing, e-commerce, digital twins, and robotics simulation."@en ;
rdfs:label "3D Generation"@en ;
rdfs:subClassOf ngm:3-d-content-generation ;
rdfs:subClassOf ngm:computer-vision ;
rdfs:subClassOf ngm:deep-learning ;
rdfs:subClassOf ngm:generative-model ;
rdfs:subClassOf _:r63 ;
rdfs:subClassOf _:r64 ;
rdfs:subClassOf _:r65 ;
rdfs:subClassOf _:r66 ;
rdfs:subClassOf _:r67 ;
rdfs:subClassOf _:r68 ;
rdfs:subClassOf _:r69 ;
rdfs:subClassOf _:r70 ;
rdfs:subClassOf _:r71 ;
vc:contrastsWith ngm:3-d-reconstruction ;
vc:contrastsWith ngm:image-generation ;
vc:dependsOn ngm:computer-vision ;
vc:dependsOn ngm:generative-adversarial-network ;
vc:dependsOn ngm:image-generation ;
vc:dependsOn ngm:point-cloud ;
vc:dependsOn ngm:transformer-architecture ;
vc:dependsOn ngm:vae ;
vc:enables ngm:3-d-content-creation ;
vc:enables ngm:autonomous-navigation ;
vc:enables ngm:digital-twin ;
vc:enables ngm:digital-twin-generation ;
vc:enables ngm:e-commerce ;
vc:enables ngm:extended-reality ;
vc:enables ngm:game-asset-generation ;
vc:enables ngm:robotics ;
vc:enables ngm:scene-generation ;
vc:enables ngm:spatial-computing ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:mesh-generation ;
vc:hasPart ngm:neural-3-d-generation ;
vc:hasPart ngm:novel-view-synthesis ;
vc:hasPart ngm:point-cloud ;
vc:hasPart ngm:scene-generation ;
vc:hasPart ngm:text-to-3-d ;
vc:hasPart ngm:texture-synthesis ;
vc:implements ngm:differentiable-rendering ;
vc:implements ngm:novel-view-synthesis ;
vc:implements ngm:score-distillation-sampling ;
vc:qualityScore "0.88"^^xsd:float ;
vc:relatedTo ngm:3-d-reconstruction ;
vc:relatedTo ngm:digital-twin ;
vc:relatedTo ngm:extended-reality ;
vc:relatedTo ngm:gaussian-splatting ;
vc:relatedTo ngm:image-generation ;
vc:relatedTo ngm:instant-ngp ;
vc:relatedTo ngm:latent-diffusion ;
vc:relatedTo ngm:neural-3-d-generation ;
vc:relatedTo ngm:novel-view-synthesis ;
vc:relatedTo ngm:robotics ;
vc:relatedTo ngm:text-to-3-d ;
vc:relatedTo ngm:texture-synthesis ;
vc:requires ngm:deep-learning ;
vc:requires ngm:differentiable-rendering ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:multimodal-ai-architecture-ai ;
vc:requires ngm:objaverse ;
vc:slug "3-d-generation" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:objaverse ;
vc:supports ngm:3-d-reconstruction ;
vc:supports ngm:digital-twin ;
vc:supports ngm:e-commerce ;
vc:supports ngm:game-asset-generation ;
vc:supports ngm:multimodal-ai-architecture-ai ;
vc:supports ngm:robotics ;
vc:uses ngm:clip ;
vc:uses ngm:differentiable-rendering ;
vc:uses ngm:diffusion-model ;
vc:uses ngm:gaussian-splatting ;
vc:uses ngm:implicit-neural-representation ;
vc:uses ngm:instant-ngp ;
vc:uses ngm:latent-diffusion ;
vc:uses ngm:ne-rf ;
vc:uses ngm:occupancy-network ;
vc:uses ngm:score-distillation-sampling ;
vc:uses ngm:signed-distance-function ;
vc:uses ngm:triplane ;
vc:uses ngm:u-net ;
vc:uses ngm:vision-transformer .
ngm:3-d-geometry a owl:Class ;
rdfs:comment "3D geometry is the mathematical description of shapes, positions, and transformations of objects in three-dimensional space, using representations such as points, vectors, meshes, and coordinate transforms. It provides the underlying spatial data model that computer graphics rendering pipelines and photorealistic rendering engines operate on, from vertex positions through to camera projection matrices. Practical 3D geometry combines linear algebra with computational geometry techniques to represent and manipulate scenes efficiently."@en ;
rdfs:label "3D Geometry"@en ;
rdfs:subClassOf ngm:computational-geometry ;
vc:enables ngm:computer-graphics ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:slug "3-d-geometry" ;
vc:sourceDomain "spatial-computing" .
ngm:3-d-graphics-standard a owl:Class ;
rdfs:comment "3D Graphics Standards are technical specifications and conventions governing the representation, rendering, and interchange of three-dimensional visual data, including APIs like OpenGL, DirectX, and Vulkan, shader languages, and coordinate system conventions."@en ;
rdfs:label "3D Graphics Standard"@en ;
rdfs:subClassOf ngm:rendering-standard ;
rdfs:subClassOf ngm:sc-content-and-assets ;
rdfs:subClassOf ngm:sc-display-and-rendering ;
rdfs:subClassOf ngm:technical-standard ;
rdfs:subClassOf _:r72 ;
rdfs:subClassOf _:r73 ;
rdfs:subClassOf _:r74 ;
rdfs:subClassOf _:r75 ;
skos:broader ngm:sc-content-and-assets ;
skos:broader ngm:sc-display-and-rendering ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:gpu-architecture ;
vc:bridgesTo ngm:shader-language ;
vc:enables ngm:cross-platform-compatibility ;
vc:enables ngm:hardware-acceleration ;
vc:enables ngm:real-time-rendering ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:technical-standard ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:driver-software ;
vc:requires ngm:gpu ;
vc:slug "3-d-graphics-standard" ;
vc:sourceDomain "spatial-computing" .
ngm:3-d-li-dar a owl:Class ;
rdfs:comment "3D LiDAR is a active ranging sensor that emits pulsed laser light across multiple vertical channels to capture dense three-dimensional point clouds of the surrounding environment. Spinning or solid-state variants measure range and intensity for hundreds of thousands of points per second, enabling robots and autonomous vehicles to perform obstacle detection, SLAM, and high-fidelity scene reconstruction in real time."@en ;
rdfs:label "3D LiDAR"@en ;
rdfs:subClassOf ngm:lidar ;
rdfs:subClassOf ngm:robo-perception ;
skos:broader ngm:robo-perception ;
vc:bridgesTo ngm:lidar ;
vc:enables ngm:autonomous-navigation ;
vc:enables ngm:point-cloud ;
vc:enables ngm:simultaneous-localisation-and-mapping ;
vc:enables ngm:slam ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:2-d-li-dar ;
vc:relatedTo ngm:lidar-scanning ;
vc:relatedTo ngm:multirotor-uav ;
vc:relatedTo ngm:stereo-camera ;
vc:slug "3-d-li-dar" ;
vc:sourceDomain "robotics" ;
vc:uses ngm:perception-system ;
vc:uses ngm:sensor-fusion .
ngm:3-d-model a owl:Class ;
rdfs:comment "A 3D Model is a digital representation of a three-dimensional object or environment constructed from vertices, edges, faces, and materials, encoded in standard formats such as glTF, OBJ, FBX, or USD, and used as a foundational asset in spatial computing, simulation, gaming, and metaverse applications."@en ;
rdfs:label "3D Model"@en ;
rdfs:subClassOf ngm:digital-asset ;
rdfs:subClassOf ngm:sc-content-and-assets ;
rdfs:subClassOf _:r76 ;
rdfs:subClassOf _:r77 ;
rdfs:subClassOf _:r78 ;
rdfs:subClassOf _:r79 ;
rdfs:subClassOf _:r80 ;
rdfs:subClassOf _:r81 ;
rdfs:subClassOf _:r82 ;
rdfs:subClassOf _:r83 ;
rdfs:subClassOf _:r84 ;
skos:broader ngm:sc-content-and-assets ;
vc:bridgesTo ngm:3-d-development ;
vc:bridgesTo ngm:3d-modelling ;
vc:bridgesTo ngm:animation-retargeting ;
vc:bridgesTo ngm:computer-vision ;
vc:enables ngm:3-d-rendering ;
vc:enables ngm:animation-retargeting ;
vc:enables ngm:augmented-reality ;
vc:enables ngm:interactive-visualization ;
vc:enables ngm:virtual-environment-design ;
vc:enables ngm:virtual-reality ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:material-definition ;
vc:hasPart ngm:mesh-data ;
vc:hasPart ngm:skeletal-rig ;
vc:hasPart ngm:texture-mapping ;
vc:isPartOf ngm:digital-asset ;
vc:isPartOf ngm:virtual-environment-design ;
vc:qualityScore "0.7"^^xsd:float ;
vc:relatedTo ngm:photogrammetry ;
vc:relatedTo ngm:procedural-generation ;
vc:requires ngm:3-d-file-format ;
vc:requires ngm:3d-modelling ;
vc:requires ngm:material-definition ;
vc:requires ngm:mesh-data ;
vc:requires ngm:texture-mapping ;
vc:slug "3-d-model" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:gltf-standard ;
vc:standardizedBy ngm:usd ;
vc:supports ngm:digital-twin ;
vc:supports ngm:metaverse ;
vc:uses ngm:level-of-detail ;
vc:uses ngm:uv-mapping .
ngm:3-d-modeling-software a owl:Class ;
rdfs:comment "3D Modeling Software is a category of applications that provide tools for constructing, editing, and organising three-dimensional geometric representations of objects and scenes, typically via polygon mesh editing, subdivision surfaces, NURBS curves, sculpting, or parametric operations. These applications underpin virtually all digital content creation workflows for games, film, architecture, product design, and XR environments. They commonly integrate texturing, rigging, animation, and basic rendering capabilities alongside the core modelling toolkit."@en ;
rdfs:label "3D Modeling Software"@en ;
rdfs:subClassOf ngm:3d-modelling ;
vc:enables ngm:3-d-asset ;
vc:enables ngm:3-d-content-creation ;
vc:enables ngm:animation-rig ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:bim-software ;
vc:relatedTo ngm:cad-software ;
vc:relatedTo ngm:game-engine ;
vc:slug "3-d-modeling-software" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:3-d-file-format ;
vc:uses ngm:physically-based-rendering ;
vc:uses ngm:shader .
ngm:3-d-perception a owl:Class ;
rdfs:comment "3D Perception is the computational capability to interpret sensor data — from cameras, LiDAR, radar, and depth sensors — and derive accurate three-dimensional understanding of the surrounding environment, including object detection, pose estimation, scene structure, and semantic labelling. It forms a foundational layer for autonomous systems, robotic manipulation, augmented reality registration, and spatial computing. The discipline draws on computer vision, geometry, and deep learning to transform raw observations into actionable 3D representations."@en ;
rdfs:label "3D Perception"@en ;
rdfs:subClassOf ngm:computer-vision ;
vc:enables ngm:6-do-f-tracking ;
vc:enables ngm:object-detection ;
vc:enables ngm:simultaneous-localisation-and-mapping ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:3-d-scanning ;
vc:relatedTo ngm:pose-estimation ;
vc:relatedTo ngm:semantic-segmentation ;
vc:slug "3-d-perception" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:depth-sensing ;
vc:uses ngm:point-cloud ;
vc:uses ngm:sensor-fusion .
ngm:3-d-reconstruction a owl:Class ;
rdfs:comment "3D Reconstruction is the computational process of recovering three-dimensional geometric and structural information from multiple 2D images or sensor data (such as LiDAR or depth cameras) using techniques including Computer Vision, photogrammetry, and Structure-from-Motion (SfM), enabling digital capture of real-world objects and environments for Digital Twin creation, immersive environment mapping, and spatial analysis."@en ;
rdfs:label "3D Reconstruction"@en ;
rdfs:subClassOf ngm:computer-vision ;
rdfs:subClassOf ngm:sc-content-and-assets ;
rdfs:subClassOf _:r92 ;
rdfs:subClassOf _:r93 ;
rdfs:subClassOf _:r94 ;
rdfs:subClassOf _:r95 ;
rdfs:subClassOf _:r96 ;
rdfs:subClassOf _:r97 ;
rdfs:subClassOf _:r98 ;
rdfs:subClassOf _:r99 ;
skos:broader ngm:sc-content-and-assets ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:bridgesTo ngm:photogrammetry ;
vc:bridgesTo ngm:robotics ;
vc:dependsOn ngm:computer-vision ;
vc:dependsOn ngm:deep-learning ;
vc:enables ngm:augmented-reality ;
vc:enables ngm:digital-twin ;
vc:enables ngm:environmental-mapping ;
vc:enables ngm:point-cloud-generation ;
vc:enables ngm:real-world-digitisation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:depth-estimation ;
vc:hasPart ngm:multi-view-stereo ;
vc:hasPart ngm:point-cloud ;
vc:hasPart ngm:structure-from-motion ;
vc:isPartOf ngm:photogrammetry ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:scene-understanding ;
vc:relatedTo ngm:spatial-computing ;
vc:requires ngm:camera-calibration ;
vc:requires ngm:feature-matching ;
vc:requires ngm:image-processing ;
vc:requires ngm:sensor-fusion ;
vc:slug "3-d-reconstruction" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:lidar ;
vc:uses ngm:neural-radiance-field ;
vc:uses ngm:simultaneous-localisation-and-mapping .
ngm:3-d-rendering a owl:Class ;
rdfs:comment "3D rendering is the computational process of generating a two-dimensional image or animation from a three-dimensional scene description by simulating the interaction of light with surfaces, materials, and geometry. It encompasses techniques ranging from real-time rasterization used in interactive applications to physically-based ray tracing and path tracing used for photorealistic offline production. The pipeline converts geometric primitives, shader programs, texture maps, and lighting data into final pixel colours via a GPU compute pipeline or software renderer. Contemporary rendering also incorporates neural methods such as Neural Radiance Fields and 3D Gaussian Splatting, as well as AI-driven upscaling and denoising, blurring the boundary between classical computer graphics and machine learning."@en ;
rdfs:label "3D Rendering"@en ;
rdfs:subClassOf ngm:computer-graphics ;
rdfs:subClassOf _:r105 ;
rdfs:subClassOf _:r106 ;
rdfs:subClassOf _:r107 ;
rdfs:subClassOf _:r108 ;
rdfs:subClassOf _:r109 ;
rdfs:subClassOf _:r110 ;
rdfs:subClassOf _:r111 ;
rdfs:subClassOf _:r112 ;
rdfs:subClassOf _:r113 ;
rdfs:subClassOf _:r114 ;
vc:bridgesTo ngm:3-d-content-generation ;
vc:bridgesTo ngm:3-d-gaussian-splatting ;
vc:bridgesTo ngm:differentiable-rendering ;
vc:bridgesTo ngm:neural-radiance-field ;
vc:dependsOn ngm:3-d-rendering-engine ;
vc:dependsOn ngm:linear-algebra ;
vc:enables ngm:augmented-reality ;
vc:enables ngm:foveated-rendering ;
vc:enables ngm:photorealistic-rendering ;
vc:enables ngm:physically-based-rendering ;
vc:enables ngm:real-time-graphics ;
vc:enables ngm:virtual-reality ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:compute-shader ;
vc:hasPart ngm:path-tracing ;
vc:hasPart ngm:pixel-shader ;
vc:hasPart ngm:rasterization ;
vc:hasPart ngm:ray-tracing ;
vc:hasPart ngm:render-pipeline ;
vc:isPartOf ngm:computer-graphics ;
vc:isPartOf ngm:spatial-computing ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:anti-aliasing ;
vc:relatedTo ngm:global-illumination ;
vc:relatedTo ngm:level-of-detail ;
vc:relatedTo ngm:spatial-computing ;
vc:requires ngm:depth-buffer ;
vc:requires ngm:graphics-processing-unit ;
vc:requires ngm:virtual-lighting-model ;
vc:slug "3-d-rendering" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:3-d-model ;
vc:uses ngm:gpu-compute ;
vc:uses ngm:scene-graph ;
vc:uses ngm:shader ;
vc:uses ngm:texture-mapping .
ngm:3-d-rendering-engine a owl:Class ;
rdfs:comment "A 3D rendering engine is software that converts three-dimensional geometric data into two-dimensional images through processes including geometry processing, lighting calculation, texture mapping, and rasterisation or ray tracing. In real-time contexts it targets interactive frame rates (90 Hz+) and must minimise motion-to-photon latency for XR presence."@en ;
rdfs:label "3D Rendering Engine"@en ;
rdfs:subClassOf ngm:computer-graphics ;
rdfs:subClassOf _:r100 ;
rdfs:subClassOf _:r101 ;
rdfs:subClassOf _:r102 ;
rdfs:subClassOf _:r103 ;
rdfs:subClassOf _:r104 ;
vc:bridgesTo ngm:inference ;
vc:bridgesTo ngm:metaverse ;
vc:contrastsWith ngm:offline-rendering ;
vc:dependsOn ngm:physics-engine ;
vc:dependsOn ngm:spatial-audio ;
vc:enables ngm:digital-twin ;
vc:enables ngm:foveated-rendering ;
vc:enables ngm:immersive-experiences ;
vc:enables ngm:real-time-visualisation ;
vc:enables ngm:xr-applications ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:level-of-detail ;
vc:hasPart ngm:scene-graph ;
vc:hasPart ngm:shader-pipeline ;
vc:hasPart ngm:texture-mapping ;
vc:implements ngm:rasterization ;
vc:implements ngm:ray-tracing ;
vc:isPartOf ngm:game-engine ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:spatial-computing ;
vc:requires ngm:graphics-api ;
vc:requires ngm:graphics-processing-unit ;
vc:slug "3-d-rendering-engine" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:khronos-group ;
vc:supports ngm:augmented-reality ;
vc:supports ngm:stereoscopic-display ;
vc:supports ngm:virtual-reality ;
vc:uses ngm:directx ;
vc:uses ngm:open-gl ;
vc:uses ngm:vulkan .
ngm:3-d-scanning a owl:Class ;
rdfs:comment "3D Scanning is the process of capturing the three-dimensional shape, and optionally the colour and texture, of real-world objects, people, or environments using hardware such as structured-light scanners, time-of-flight LiDAR, photogrammetry rigs, or depth cameras, producing digital point clouds or meshes that represent the physical source. The resulting data feeds into digital preservation, reverse engineering, visual-effects production, quality inspection, and spatial computing pipelines. Accuracy, resolution, and scan volume are the primary quality axes that distinguish scanning technologies."@en ;
rdfs:label "3D Scanning"@en ;
rdfs:subClassOf ngm:3-d-reconstruction ;
rdfs:subClassOf _:r115 ;
rdfs:subClassOf _:r116 ;
rdfs:subClassOf _:r117 ;
rdfs:subClassOf _:r118 ;
vc:bridgesTo ngm:medical-imaging ;
vc:bridgesTo ngm:robotics-perception ;
vc:contrastsWith ngm:neural-radiance-field ;
vc:contrastsWith ngm:structure-from-motion ;
vc:enables ngm:3-d-scene-reconstruction ;
vc:enables ngm:digital-heritage ;
vc:enables ngm:digital-twin-creation ;
vc:enables ngm:point-cloud-processing ;
vc:enables ngm:reverse-engineering ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:mesh-generation ;
vc:hasPart ngm:point-cloud ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:3-d-perception ;
vc:relatedTo ngm:gaussian-splatting ;
vc:relatedTo ngm:simultaneous-localisation-and-mapping ;
vc:requires ngm:calibration ;
vc:requires ngm:depth-sensor ;
vc:slug "3-d-scanning" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:augmented-reality ;
vc:supports ngm:bim-virtual-model ;
vc:supports ngm:quality-inspection ;
vc:uses ngm:3-d-li-dar ;
vc:uses ngm:photogrammetry ;
vc:uses ngm:structured-light ;
vc:uses ngm:time-of-flight-sensor .
ngm:3-d-scene-exchange-protocol-sxp a owl:Class ;
rdfs:comment "Open standards framework enabling interoperable transfer of complete 3D scene graphs including geometric meshes (polygon topology vertex positions normals texture coordinates with indexed triangle lists optimized for GPU rendering), physically-based rendering (PBR) material systems (metallic-roug..."@en ;
rdfs:label "3D Scene Exchange Protocol (SXP)"@en ;
rdfs:subClassOf ngm:3-d-graphics-standard ;
rdfs:subClassOf ngm:data-format ;
rdfs:subClassOf ngm:interchange-protocol ;
rdfs:subClassOf ngm:metaverse-infrastructure ;
rdfs:subClassOf ngm:open-standard ;
rdfs:subClassOf ngm:sc-standards-and-interop ;
rdfs:subClassOf ngm:scene-graph-format ;
rdfs:subClassOf _:r119 ;
rdfs:subClassOf _:r120 ;
rdfs:subClassOf _:r121 ;
rdfs:subClassOf _:r122 ;
rdfs:subClassOf _:r123 ;
rdfs:subClassOf _:r124 ;
rdfs:subClassOf _:r125 ;
rdfs:subClassOf _:r126 ;
rdfs:subClassOf _:r127 ;
skos:broader ngm:sc-standards-and-interop ;
vc:bridgesTo ngm:computer-vision ;
vc:dependsOn ngm:binary-encoding ;
vc:dependsOn ngm:draco-compression ;
vc:dependsOn ngm:gltf-standard ;
vc:dependsOn ngm:json-format ;
vc:dependsOn ngm:material-x ;
vc:dependsOn ngm:open-gl ;
vc:dependsOn ngm:usd-framework ;
vc:dependsOn ngm:vulkan ;
vc:dependsOn ngm:web-gl ;
vc:dependsOn ngm:webgpu ;
vc:enables ngm:3d-asset-interchange ;
vc:enables ngm:ar-vr-experiences ;
vc:enables ngm:asset-portability ;
vc:enables ngm:collaborative-workflows ;
vc:enables ngm:cross-platform-compatibility ;
vc:enables ngm:e-commerce-3-d ;
vc:enables ngm:e-commerce-3d ;
vc:enables ngm:metaverse-interoperability ;
vc:enables ngm:real-time-rendering ;
vc:enables ngm:web-3d-visualization ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:animation-rig ;
vc:hasPart ngm:camera-definition ;
vc:hasPart ngm:geometric-mesh ;
vc:hasPart ngm:lighting-environment ;
vc:hasPart ngm:lod-specification ;
vc:hasPart ngm:material-system ;
vc:hasPart ngm:normal-map ;
vc:hasPart ngm:pbr-workflow ;
vc:hasPart ngm:polygon-topology ;
vc:hasPart ngm:scene-hierarchy ;
vc:hasPart ngm:skeletal-bone ;
vc:hasPart ngm:texture-map ;
vc:hasPart ngm:uv-coordinate ;
vc:hasPart ngm:vertex-attribute ;
vc:implements ngm:extension-mechanism ;
vc:implements ngm:mesh-lod ;
vc:implements ngm:non-destructive-editing ;
vc:implements ngm:pbr-materials ;
vc:implements ngm:progressive-loading ;
vc:implements ngm:scene-composition ;
vc:implements ngm:scene-graph-format ;
vc:implements ngm:skeletal-animation ;
vc:implements ngm:version-control ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:3-d-modeling-software ;
vc:requires ngm:animation-tools ;
vc:requires ngm:game-engine ;
vc:requires ngm:material-converter ;
vc:requires ngm:mesh-compression ;
vc:requires ngm:rendering-pipeline ;
vc:requires ngm:scene-validator ;
vc:requires ngm:texture-authoring ;
vc:slug "3-d-scene-exchange-protocol-sxp" ;
vc:sourceDomain "spatial-computing" .
ngm:3-d-scene-reconstruction a owl:Class ;
rdfs:comment "3D Scene Reconstruction is the computational process of recovering a complete, coherent three-dimensional model of an environment or scene from sensor observations such as images, depth maps, or LiDAR returns, integrating multiple viewpoints and modalities into a unified representation. Methods include volumetric fusion, truncated signed distance function (TSDF) integration, neural implicit representations, and Gaussian splatting, each offering different trade-offs between completeness, accuracy, and real-time capability. The output is used in robotics, autonomous driving, spatial computing, and cultural heritage documentation."@en ;
rdfs:label "3D Scene Reconstruction"@en ;
rdfs:subClassOf ngm:3-d-reconstruction ;
vc:enables ngm:3-d-perception ;
vc:enables ngm:ar-registration ;
vc:enables ngm:digital-twin-creation ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:3-d-scanning ;
vc:relatedTo ngm:gaussian-splatting ;
vc:relatedTo ngm:ne-rf ;
vc:slug "3-d-scene-reconstruction" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:multi-view-stereo ;
vc:uses ngm:simultaneous-localisation-and-mapping ;
vc:uses ngm:structure-from-motion .
ngm:3-d-scene-representation a owl:Class ;
rdfs:comment "A 3D scene representation is a data structure that encodes the geometry, appearance and spatial layout of a three-dimensional environment, such as point clouds, meshes, voxel grids or neural implicit fields. It underpins 3D content generation and reconstruction pipelines, providing the intermediate format from which renderable or editable scenes are produced. Point clouds are one common instance, forming a sparse, unstructured representation that is often converted into denser structures for downstream use."@en ;
rdfs:label "3D Scene Representation"@en ;
rdfs:subClassOf ngm:scene-representation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:point-cloud ;
vc:qualityScore "0.5"^^xsd:float ;
vc:slug "3-d-scene-representation" ;
vc:sourceDomain "spatial-computing" .
ngm:3-d-user-interface a owl:Class ;
rdfs:comment "A 3D User Interface (3DUI) is an interactive control system within three-dimensional virtual environments enabling users to manipulate objects, navigate spaces, and access functionality through spatial gestures, hand tracking, gaze-based selection, and voice commands. 3DUI design balances accessibility standards with intuitive spatial affordances appropriate for VR, AR, and metaverse interactions."@en ;
rdfs:label "3D User Interface"@en ;
rdfs:subClassOf ngm:interaction-design ;
rdfs:subClassOf ngm:sc-interaction ;
rdfs:subClassOf ngm:user-interface ;
rdfs:subClassOf _:r128 ;
rdfs:subClassOf _:r129 ;
rdfs:subClassOf _:r130 ;
rdfs:subClassOf _:r131 ;
rdfs:subClassOf _:r132 ;
rdfs:subClassOf _:r133 ;
rdfs:subClassOf _:r134 ;
rdfs:subClassOf _:r135 ;
rdfs:subClassOf _:r136 ;
rdfs:subClassOf _:r137 ;
skos:broader ngm:sc-interaction ;
vc:bridgesTo ngm:accessibility-standard ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:gesture-recognition ;
vc:bridgesTo ngm:interaction-design ;
vc:bridgesTo ngm:metaverse ;
vc:bridgesTo ngm:sensor-input ;
vc:contrastsWith ngm:graphical-user-interface ;
vc:contrastsWith ngm:user-interface ;
vc:enables ngm:accessible-immersion ;
vc:enables ngm:immersive-experience ;
vc:enables ngm:intuitive-interaction ;
vc:enables ngm:user-navigation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:gaze-tracking ;
vc:hasPart ngm:gesture-recognition ;
vc:hasPart ngm:hand-tracking ;
vc:hasPart ngm:haptic-feedback ;
vc:hasPart ngm:voice-input ;
vc:isPartOf ngm:extended-reality ;
vc:isPartOf ngm:spatial-computing ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:augmented-reality ;
vc:relatedTo ngm:embodied-interaction ;
vc:relatedTo ngm:mixed-reality ;
vc:relatedTo ngm:virtual-reality ;
vc:requires ngm:gaze-tracking ;
vc:requires ngm:hand-tracking ;
vc:requires ngm:haptic-feedback ;
vc:requires ngm:sensor-input ;
vc:requires ngm:voice-input ;
vc:slug "3-d-user-interface" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:accessibility-standard ;
vc:supports ngm:multimodal-ai-architecture ;
vc:uses ngm:depth-sensing ;
vc:uses ngm:real-time-rendering ;
vc:uses ngm:spatial-audio .
ngm:3-dpw-benchmark a skos:Concept ;
rdfs:label "3 Dpw Benchmark"@en .
ngm:3-gpp a owl:Class ;
rdfs:comment "The 3rd Generation Partnership Project (3GPP) is a global consortium of regional telecommunications standards bodies that develops and maintains versioned technical specifications governing mobile communication systems, from UMTS (3G) through LTE (4G) to NR (5G) and the emerging 6G framework. Operating through working groups (RAN, SA, CT), it produces Releases that introduce new radio access technologies, core network architectures, and service-layer capabilities. 3GPP specifications are the foundational technical substrate for the global cellular infrastructure serving billions of devices."@en ;
rdfs:label "3GPP"@en ;
rdfs:subClassOf ngm:standards-body ;
rdfs:subClassOf _:r138 ;
rdfs:subClassOf _:r139 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:spatial-computing ;
vc:enables ngm:internet-of-things ;
vc:enables ngm:multi-access-edge-computing ;
vc:enables ngm:network-function-virtualization ;
vc:enables ngm:network-slicing ;
vc:enables ngm:vehicle-to-everything ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:5g-core-network ;
vc:hasPart ngm:5g-new-radio ;
vc:hasPart ngm:radio-access-network ;
vc:implements ngm:5-g-connectivity ;
vc:implements ngm:5-g-network ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:etsi ;
vc:relatedTo ngm:ieee ;
vc:relatedTo ngm:itu-r ;
vc:relatedTo ngm:network-architecture ;
vc:relatedTo ngm:telecommunications ;
vc:requires ngm:spectrum-allocation ;
vc:slug "3-gpp" ;
vc:sourceDomain "standards" ;
vc:supports ngm:low-latency .
ngm:360-degree-video a skos:Concept ;
rdfs:label "360 Degree Video"@en .
ngm:360-video a owl:Class ;
rdfs:comment "A spherical video format captured with omnidirectional camera rigs that records the full 360-degree field of view around a single vantage point, allowing viewers to look in any direction during playback on headsets, browsers, or mobile devices. Because the footage is fixed to the capture position, it offers rotational (three-degrees-of-freedom) immersion but no positional movement, distinguishing it from volumetric formats that reconstruct scene geometry."@en ;
rdfs:label "360 Video"@en ;
rdfs:subClassOf ngm:immersive-media ;
vc:contrastsWith ngm:volumetric-capture ;
vc:contrastsWith ngm:volumetric-video ;
vc:enables ngm:vr-experiences ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:virtual-reality ;
vc:slug "360-video" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:video-streaming .
ngm:3d-asset-creation a owl:Class ;
rdfs:comment "The production of three-dimensional digital assets—models, characters, environments, props, and their materials, textures, rigs, and animations—ready for use in games, film, extended reality, simulation, and digital-twin applications. 3D asset creation is the spatial specialisation of general asset creation, spanning manual modelling and sculpting, photogrammetry and scanning, procedural generation, and increasingly generative AI pipelines that produce textured meshes from text or image prompts."@en ;
rdfs:label "3D Asset Creation"@en ;
rdfs:subClassOf ngm:asset-creation ;
vc:enables ngm:virtual-environment ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:creative-tools ;
vc:relatedTo ngm:digital-asset ;
vc:slug "3d-asset-creation" ;
vc:sourceDomain "metaverse" ;
vc:uses ngm:3d-modelling ;
vc:uses ngm:procedural-generation ;
vc:uses ngm:texture-mapping .
ngm:3d-asset-exchange a skos:Concept ;
rdfs:label "3d Asset Exchange"@en .
ngm:3d-asset-generation a skos:Concept ;
rdfs:label "3d Asset Generation"@en .
ngm:3d-asset-interchange a skos:Concept ;
rdfs:label "3d Asset Interchange"@en .
ngm:3d-cad-integration a skos:Concept ;
rdfs:label "3d Cad Integration"@en .
ngm:3d-coordinate-geometry a skos:Concept ;
rdfs:label "3d Coordinate Geometry"@en .
ngm:3d-generative-model a skos:Concept ;
rdfs:label "3d Generative Model"@en .
ngm:3d-generator a skos:Concept ;
rdfs:label "3d Generator"@en .
ngm:3d-imaging a skos:Concept ;
rdfs:label "3d Imaging"@en .
ngm:3d-mapping a owl:Class ;
rdfs:comment "3D mapping is the process of building a spatially coherent three-dimensional representation of an environment from sensor observations, such as camera images, LiDAR scans, or depth data, typically as a robot or capture device moves through the space. It relies on techniques including structure-from-motion and triangulation to recover the geometry of the scene and the trajectory of the sensor simultaneously. 3D mapping outputs, including point clouds, meshes, or occupancy grids, support downstream applications in robotics navigation, spatial computing, and photogrammetry-based 3D reconstruction."@en ;
rdfs:label "3D Mapping"@en ;
rdfs:subClassOf ngm:3-d-reconstruction ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:slug "3d-mapping" ;
vc:sourceDomain "spatial-computing" .
ngm:3d-medical-imaging a skos:Concept ;
rdfs:label "3d Medical Imaging"@en .
ngm:3d-model-creation a skos:Concept ;
rdfs:label "3d Model Creation"@en .
ngm:3d-modelling a owl:Class ;
rdfs:comment "3D modelling is the creation of a mathematical representation of a three-dimensional surface or volume using specialised software. Models are commonly built from polygon meshes, parametric surfaces or volumetric data and define the geometry that is later textured, rigged, animated and rendered. It is the foundational discipline for games, film, visualisation, product design and spatial computing."@en ;
rdfs:label "3D Modelling"@en ;
rdfs:subClassOf ngm:3-d-development ;
rdfs:subClassOf ngm:computer-graphics ;
rdfs:subClassOf _:r85 ;
rdfs:subClassOf _:r86 ;
rdfs:subClassOf _:r87 ;
rdfs:subClassOf _:r88 ;
rdfs:subClassOf _:r89 ;
rdfs:subClassOf _:r90 ;
rdfs:subClassOf _:r91 ;
vc:bridgesTo ngm:augmented-reality ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:generative-ai ;
vc:bridgesTo ngm:photogrammetry ;
vc:contrastsWith ngm:computer-aided-design ;
vc:contrastsWith ngm:digital-art ;
vc:enables ngm:asset-creation ;
vc:enables ngm:character-animation ;
vc:enables ngm:character-model ;
vc:enables ngm:real-time-graphics ;
vc:enables ngm:rendering ;
vc:enables ngm:texture-mapping ;
vc:enables ngm:virtual-environment-design ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:character-rigging ;
vc:hasPart ngm:geometry-processing ;
vc:hasPart ngm:material-definition ;
vc:hasPart ngm:polygon-mesh ;
vc:hasPart ngm:topology ;
vc:isPartOf ngm:asset-pipeline ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:character-rigging ;
vc:relatedTo ngm:fbx ;
vc:relatedTo ngm:skinning ;
vc:relatedTo ngm:visual-effects ;
vc:requires ngm:design-software ;
vc:requires ngm:polygon-mesh ;
vc:slug "3d-modelling" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:gltf-standard ;
vc:standardizedBy ngm:obj-format ;
vc:supports ngm:augmented-reality ;
vc:supports ngm:game-development ;
vc:supports ngm:game-engine ;
vc:supports ngm:virtual-production ;
vc:supports ngm:virtual-reality ;
vc:supports ngm:visual-effects ;
vc:uses ngm:3-d-model ;
vc:uses ngm:computer-aided-design ;
vc:uses ngm:level-of-detail ;
vc:uses ngm:uv-mapping .
ngm:3d-models a skos:Concept ;
rdfs:label "3d Models"@en .
ngm:3d-motion-analysis a skos:Concept ;
rdfs:label "3d Motion Analysis"@en .
ngm:3d-object-detection a skos:Concept ;
rdfs:label "3d Object Detection"@en .
ngm:3d-object-segmentation a skos:Concept ;
rdfs:label "3d Object Segmentation"@en .
ngm:3d-parallelism a owl:Class ;
rdfs:comment "3D parallelism is a distributed training strategy that combines data parallelism, tensor parallelism and pipeline parallelism along three independent axes to train models too large for a single accelerator or single parallelism scheme alone. Each axis partitions a different dimension of the problem: data parallelism splits the batch, tensor parallelism splits individual layers across devices, and pipeline parallelism splits the layer stack across stages. Frameworks such as Megatron-LM and DeepSpeed implement 3D parallelism to scale training to thousands of GPUs."@en ;
rdfs:label "3D Parallelism"@en ;
rdfs:subClassOf ngm:distributed-training ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:slug "3d-parallelism" ;
vc:sourceDomain "machine-learning" .
ngm:3d-printing a skos:Concept ;
rdfs:label "3d Printing"@en .
ngm:3d-representation a skos:Concept ;
rdfs:label "3d Representation"@en .
ngm:3d-scanner a skos:Concept ;
rdfs:label "3d Scanner"@en .
ngm:3d-sound-rendering a skos:Concept ;
rdfs:label "3d Sound Rendering"@en .
ngm:3d-transform-system a skos:Concept ;
rdfs:label "3d Transform System"@en .
ngm:3d-visualisation a skos:Concept ;
rdfs:label "3d Visualisation"@en .
ngm:3d-visualization a skos:Concept ;
rdfs:label "3d Visualization"@en .
ngm:3dpw-benchmark a skos:Concept ;
rdfs:label "3dpw Benchmark"@en .
ngm:3dreconstruction a skos:Concept ;
rdfs:label "3dreconstruction"@en .
ngm:3gpp-5g-core a skos:Concept ;
rdfs:label "3gpp 5g Core"@en .
ngm:3gpp-nr a skos:Concept ;
rdfs:label "3gpp Nr"@en .
ngm:4-d-humans a skos:Concept ;
rdfs:label "4 D Humans"@en .
ngm:4d-content-creation a skos:Concept ;
rdfs:label "4d Content Creation"@en .
ngm:4d-humans a skos:Concept ;
rdfs:label "4d Humans"@en .
ngm:4d-parameterisation a skos:Concept ;
rdfs:label "4d Parameterisation"@en .
ngm:4e-cognition a skos:Concept ;
rdfs:label "4e Cognition"@en .
ngm:4g-lte a skos:Concept ;
rdfs:label "4g Lte"@en .
ngm:4k-uhd-delivery a skos:Concept ;
rdfs:label "4k Uhd Delivery"@en .
ngm:5-g a owl:Class ;
rdfs:comment "5G (Fifth Generation) is the latest generation of mobile cellular network technology, standardised by 3GPP from Release 15 onwards, characterised by peak data rates exceeding 20 Gbps, radio latencies below 1 ms, and support for up to one million connected devices per square kilometre. It introduces three primary use-case families: enhanced mobile broadband (eMBB), ultra-reliable low-latency communications (URLLC), and massive machine-type communications (mMTC). 5G underpins advances in spatial computing, autonomous vehicles, industrial automation, and IoT at scale."@en ;
rdfs:label "5G"@en ;
rdfs:subClassOf ngm:telecommunications ;
rdfs:subClassOf _:r152 ;
rdfs:subClassOf _:r153 ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:spatial-computing ;
vc:contrastsWith ngm:4g-lte ;
vc:contrastsWith ngm:6g ;
vc:enables ngm:5-g-connectivity ;
vc:enables ngm:autonomous-vehicle ;
vc:enables ngm:industrial-io-t ;
vc:enables ngm:multi-access-edge-computing ;
vc:enables ngm:network-slicing ;
vc:enables ngm:private-5g-network ;
vc:enables ngm:xr-applications ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:5g-core ;
vc:hasPart ngm:5g-new-radio ;
vc:hasPart ngm:service-oriented-architecture ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:5-g-network ;
vc:relatedTo ngm:internet-of-things ;
vc:relatedTo ngm:mobile-edge-computing ;
vc:requires ngm:massive-mimo ;
vc:slug "5-g" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:3-gpp ;
vc:standardizedBy ngm:itu-r ;
vc:uses ngm:beamforming ;
vc:uses ngm:cloud-native ;
vc:uses ngm:network-function-virtualization .
ngm:5-g-connectivity a owl:Class ;
rdfs:comment "5G Connectivity is the set of radio access and core network capabilities delivered by a 5G NR network that provides devices and applications with wireless communication services characterised by high throughput, ultra-low latency, and high device density. It encompasses the radio link between user equipment and the gNB base station, quality-of-service mechanisms, network slicing for application-specific service guarantees, and the APIs through which applications access network capabilities. 5G Connectivity is a critical enabler for cloud XR, autonomous systems, and real-time industrial applications."@en ;
rdfs:label "5G Connectivity"@en ;
rdfs:subClassOf ngm:5-g ;
vc:enables ngm:io-t-infrastructure ;
vc:enables ngm:low-latency ;
vc:enables ngm:xr-applications ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:3-gpp ;
vc:relatedTo ngm:guaranteed-bandwidth ;
vc:relatedTo ngm:latency ;
vc:slug "5-g-connectivity" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:5-g-network ;
vc:uses ngm:multi-access-edge-computing ;
vc:uses ngm:network-function-virtualization .
ngm:5-g-network a owl:Class ;
rdfs:comment "A 5G Network is the end-to-end fifth-generation mobile telecommunications system comprising a 5G New Radio (NR) radio access network built around gNB base stations, a cloud-native 5G Core implementing a service-based architecture with independently deployable network functions (AMF, SMF, UPF, PCF, NRF, AUSF), and the transport infrastructure interconnecting them. The architecture fundamentally separates the control plane from the user plane, enables network slicing to provision multiple virtualised logical networks on shared physical resources, and integrates multi-access edge computing nodes for deterministic low-latency application hosting. Defined across 3GPP Release 15 (frozen 2018) through Release 18 (5G-Advanced), 5G networks support three canonical service classes: enhanced Mobile Broadband (eMBB), Ultra-Reliable Low-Latency Communications (URLLC), and massive Machine-Type Communications (mMTC), making them the foundational connectivity layer for industrial IoT, autonomous systems, extended reality, and private campus networks."@en ;
rdfs:label "5G Network"@en ;
rdfs:subClassOf ngm:telecommunications-infrastructure ;
rdfs:subClassOf _:r144 ;
rdfs:subClassOf _:r145 ;
rdfs:subClassOf _:r146 ;
rdfs:subClassOf _:r147 ;
rdfs:subClassOf _:r148 ;
rdfs:subClassOf _:r149 ;
rdfs:subClassOf _:r150 ;
rdfs:subClassOf _:r151 ;
vc:bridgesTo ngm:6-g-network-slice ;
vc:bridgesTo ngm:ai-driven-network-operations ;
vc:bridgesTo ngm:artificial-intelligence-operations ;
vc:bridgesTo ngm:digital-twin ;
vc:contrastsWith ngm:4g-lte ;
vc:contrastsWith ngm:wi-fi ;
vc:enables ngm:5-g-connectivity ;
vc:enables ngm:autonomous-vehicle ;
vc:enables ngm:extended-reality ;
vc:enables ngm:io-t-infrastructure ;
vc:enables ngm:private-5g ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:5-g ;
vc:hasPart ngm:5g-core ;
vc:hasPart ngm:multi-access-edge-computing ;
vc:hasPart ngm:network-slicing ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:mobile-edge-computing ;
vc:relatedTo ngm:network-infrastructure ;
vc:relatedTo ngm:open-ran ;
vc:requires ngm:cloud-native-architecture ;
vc:requires ngm:spectrum-allocation ;
vc:requires ngm:transport-network ;
vc:slug "5-g-network" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:3-gpp ;
vc:standardizedBy ngm:etsi ;
vc:standardizedBy ngm:o-ran-alliance ;
vc:uses ngm:edge-computing ;
vc:uses ngm:massive-mimo ;
vc:uses ngm:millimetre-wave ;
vc:uses ngm:network-function-virtualization ;
vc:uses ngm:software-defined-networking .
ngm:51-attack a owl:Class ;
rdfs:comment "A 51% Attack is a consensus-layer attack on a Proof-of-Work blockchain in which a single entity or coalition controls more than half of the network's hash rate, enabling double-spending, transaction censorship, and chain reorganisation. The attack exploits the longest-chain rule: the attacker mines a private fork containing fraudulent transactions and, once it exceeds the honest chain in cumulative work, broadcasts it to override confirmed history."@en ;
rdfs:label "51 Percent Attack"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf _:r140 ;
rdfs:subClassOf _:r141 ;
rdfs:subClassOf _:r142 ;
rdfs:subClassOf _:r143 ;
skos:broader ngm:bc-protocol-and-consensus ;
skos:broader ngm:blockchain ;
vc:bridgesTo ngm:ai-energy-optimisation ;
vc:bridgesTo ngm:game-theory ;
vc:bridgesTo ngm:network-security ;
vc:contrastsWith ngm:byzantine-fault-tolerance ;
vc:contrastsWith ngm:proof-of-stake ;
vc:dependsOn ngm:blockchain ;
vc:dependsOn ngm:cryptocurrency ;
vc:dependsOn ngm:mining-hardware ;
vc:enables ngm:chain-reorganization ;
vc:enables ngm:double-spending ;
vc:enables ngm:transaction-censorship ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:isPartOf ngm:blockchain-security ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:ethereum-smart-contract-platform-classic ;
vc:relatedTo ngm:finality ;
vc:relatedTo ngm:selfish-mining ;
vc:relatedTo ngm:transaction ;
vc:requires ngm:hash-rate ;
vc:requires ngm:mining ;
vc:requires ngm:mining-pool ;
vc:requires ngm:proof-of-work ;
vc:slug "51-percent-attack" ;
vc:sourceDomain "blockchain" .
ngm:5g-core a skos:Concept ;
rdfs:label "5g Core"@en .
ngm:5g-core-network a skos:Concept ;
rdfs:label "5g Core Network"@en .
ngm:5g-new-radio a skos:Concept ;
rdfs:label "5g New Radio"@en .
ngm:5gstandalonearchitecture a skos:Concept ;
rdfs:label "5gstandalonearchitecture"@en .
ngm:6-do-f-estimation a skos:Concept ;
rdfs:label "6 Do F Estimation"@en .
ngm:6-do-f-tracking a owl:Class ;
rdfs:comment "6DoF (Six Degrees of Freedom) Tracking is the measurement and continuous estimation of an object's complete rigid-body pose in three-dimensional space, encompassing three translational components (x, y, z position) and three rotational components (pitch, yaw, roll orientation). It is the foundational capability for XR headsets, controllers, and spatial computing devices to understand and respond to the user's physical motion with sub-millimetre accuracy and minimal latency. 6DoF tracking is achieved through sensor fusion of inertial measurement units, camera-based visual odometry, and optionally external beacons or reference markers."@en ;
rdfs:label "6DoF Tracking"@en ;
rdfs:subClassOf ngm:simultaneous-localisation-and-mapping ;
vc:enables ngm:3-d-perception ;
vc:enables ngm:ar-registration ;
vc:enables ngm:xr-applications ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:camera-tracking ;
vc:relatedTo ngm:depth-sensing ;
vc:relatedTo ngm:pose-estimation ;
vc:slug "6-do-f-tracking" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:imu ;
vc:uses ngm:sensor-fusion ;
vc:uses ngm:simultaneous-localisation-and-mapping .
ngm:6-dof-vr a skos:Concept ;
rdfs:label "6 Dof VR"@en .
ngm:6-g-network-slice a owl:Class ;
rdfs:comment "Virtual partition of 6G infrastructure guaranteeing specified quality-of-service levels for immersive workloads through isolated resource allocation."@en ;
rdfs:label "6G Network Slice"@en ;
rdfs:subClassOf ngm:infra-network-and-comms ;
rdfs:subClassOf _:r154 ;
rdfs:subClassOf _:r155 ;
rdfs:subClassOf _:r156 ;
rdfs:subClassOf _:r157 ;
rdfs:subClassOf _:r158 ;
skos:broader ngm:infra-network-and-comms ;
vc:enables ngm:guaranteed-bandwidth ;
vc:enables ngm:low-latency-service ;
vc:enables ngm:resource-allocation ;
vc:enables ngm:workload-isolation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:qos-policy ;
vc:hasPart ngm:resource-allocation ;
vc:hasPart ngm:service-level-agreement ;
vc:hasPart ngm:traffic-classifier ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:network-infrastructure ;
vc:requires ngm:network-slicing-orchestrator ;
vc:requires ngm:sdn-controller ;
vc:slug "6-g-network-slice" ;
vc:sourceDomain "infrastructure" .
ngm:6-lo-wpan a skos:Concept ;
rdfs:label "6 Lo Wpan"@en .
ngm:6dof-estimation a skos:Concept ;
rdfs:label "6dof Estimation"@en .
ngm:6g a skos:Concept ;
rdfs:label "6g"@en .
ngm:6lowpan a skos:Concept ;
rdfs:label "6lowpan"@en .
ngm:80-plus-certification a skos:Concept ;
rdfs:label "80 Plus Certification"@en .
ngm:MaturityLevel a owl:Class ;
rdfs:label "Maturity Level"@en .
ngm:a-b-testing a owl:Class ;
rdfs:comment "A/B testing is a controlled experimentation method that compares two or more variants by randomly assigning subjects to each and measuring a defined outcome metric. By holding all factors constant except the variant under test, it isolates causal effects and supports data-driven decisions with statistical rigour. It is widely used to optimise digital products, content and user experiences."@en ;
rdfs:label "A/B Testing"@en ;
rdfs:subClassOf ngm:data-analytics ;
vc:contrastsWith ngm:usability-testing ;
vc:dependsOn ngm:data-visualisation ;
vc:enables ngm:predictive-personalization ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:data-analytics ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:business-intelligence ;
vc:relatedTo ngm:monitoring-dashboard ;
vc:relatedTo ngm:recommendation-system ;
vc:relatedTo ngm:user-experience ;
vc:slug "a-b-testing" ;
vc:sourceDomain "data" ;
vc:supports ngm:data-science ;
vc:supports ngm:digital-marketing ;
vc:supports ngm:optimisation ;
vc:uses ngm:metrics ;
vc:uses ngm:statistics .
ngm:a-b-testing-framework a skos:Concept ;
rdfs:label "A B Testing Framework"@en .
ngm:a-star-algorithm a owl:Class ;
rdfs:comment "The A* algorithm is an informed best-first graph-search method that finds a least-cost path from a start node to a goal node by evaluating each candidate node n with the function f(n) = g(n) + h(n), where g(n) is the exact cost accumulated from the start node to n and h(n) is an admissible heuristic estimating the remaining cost from n to the goal. By always expanding the open-list node with the lowest f-value, A* is guaranteed to find the optimal path when h is admissible (never overestimates) and is also consistent (satisfies the triangle inequality h(n) ≤ c(n,n') + h(n') for every edge (n,n')). A* generalises Dijkstra's algorithm by adding goal-directed heuristic guidance, and subsumes greedy best-first search as the special case g(n)=0. First described by Peter Hart, Nils Nilsson, and Bertram Raphael at the Stanford Research Institute in 1968, A* remains the most widely deployed optimal graph-search algorithm in artificial intelligence, robotics, game development, and logistics."@en ;
rdfs:label "A Star Algorithm"@en ;
rdfs:subClassOf ngm:graph-search ;
rdfs:subClassOf ngm:informed-search ;
rdfs:subClassOf ngm:pathfinding ;
rdfs:subClassOf ngm:search-algorithm ;
rdfs:subClassOf _:r159 ;
rdfs:subClassOf _:r160 ;
rdfs:subClassOf _:r161 ;
rdfs:subClassOf _:r162 ;
rdfs:subClassOf _:r163 ;
rdfs:subClassOf _:r164 ;
rdfs:subClassOf _:r165 ;
rdfs:subClassOf _:r166 ;
vc:contrastsWith ngm:dijkstra-algorithm ;
vc:contrastsWith ngm:monte-carlo-tree-search ;
vc:contrastsWith ngm:rrt-algorithm ;
vc:dependsOn ngm:dynamic-programming ;
vc:dependsOn ngm:graph-search ;
vc:dependsOn ngm:heuristic-methods ;
vc:dependsOn ngm:optimality ;
vc:enables ngm:autonomous-navigation ;
vc:enables ngm:motion-planning ;
vc:enables ngm:navigation ;
vc:enables ngm:network-routing ;
vc:enables ngm:path-planning ;
vc:enables ngm:pathfinding ;
vc:enables ngm:shortest-path ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:admissibility ;
vc:hasPart ngm:consistency ;
vc:hasPart ngm:cost-function ;
vc:hasPart ngm:heuristic-methods ;
vc:hasPart ngm:path-planning ;
vc:hasPart ngm:priority-queue ;
vc:implements ngm:graph-search ;
vc:implements ngm:heuristic-methods ;
vc:implements ngm:informed-search ;
vc:implements ngm:optimisation ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:bidirectional-search ;
vc:relatedTo ngm:completeness ;
vc:relatedTo ngm:d ;
vc:relatedTo ngm:d-star ;
vc:relatedTo ngm:graph-theory ;
vc:relatedTo ngm:ida ;
vc:relatedTo ngm:ida-star ;
vc:relatedTo ngm:jump-point-search ;
vc:relatedTo ngm:motion-planning ;
vc:relatedTo ngm:occupancy-grid ;
vc:relatedTo ngm:optimality ;
vc:relatedTo ngm:optimisation ;
vc:relatedTo ngm:spatial-computing ;
vc:relatedTo ngm:theta ;
vc:relatedTo ngm:theta-star ;
vc:requires ngm:admissibility ;
vc:requires ngm:graph-representation ;
vc:requires ngm:graph-theory ;
vc:requires ngm:state-space ;
vc:requires ngm:weighted-graph ;
vc:slug "a-star-algorithm" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:search-algorithm ;
vc:supports ngm:autonomous-navigation ;
vc:supports ngm:game-ai ;
vc:supports ngm:gps-systems ;
vc:supports ngm:logistics ;
vc:supports ngm:network-routing ;
vc:supports ngm:path-planning ;
vc:supports ngm:robotics ;
vc:supports ngm:spatial-computing ;
vc:uses ngm:cost-function ;
vc:uses ngm:dynamic-programming ;
vc:uses ngm:graph-representation ;
vc:uses ngm:graph-search ;
vc:uses ngm:graph-theory ;
vc:uses ngm:priority-queue ;
vc:uses ngm:state-space ;
vc:uses ngm:weighted-graph .
ngm:a2-a-protocol a owl:Class ;
rdfs:comment "The Agent-to-Agent (A2A) Protocol is an open communication specification, initially proposed by Google in April 2025 and transferred to the Linux Foundation in June 2025, that defines how autonomous AI agents discover one another, negotiate capabilities, delegate tasks, and exchange results across heterogeneous agent frameworks and cloud environments. It uses HTTP/HTTPS transport with JSON-RPC 2.0 structured messages and Server-Sent Events for streaming, an Agent Card system at a well-known URI for capability advertisement, and enterprise-grade authentication through OAuth 2.0, mTLS, and JWT, enabling cross-vendor agent interoperability without requiring shared infrastructure. A2A complements tool-access protocols such as the Model Context Protocol by standardising the agent-to-agent interaction layer, and reached v1.0 production readiness in 2026 with adoption by over 150 organisations including Microsoft, AWS, Salesforce, SAP, and ServiceNow."@en ;
rdfs:label "A2A Protocol"@en ;
rdfs:subClassOf ngm:agent-communication-protocol ;
rdfs:subClassOf ngm:agent-to-agent-protocol ;
rdfs:subClassOf _:r167 ;
rdfs:subClassOf _:r168 ;
rdfs:subClassOf _:r169 ;
rdfs:subClassOf _:r170 ;
rdfs:subClassOf _:r171 ;
rdfs:subClassOf _:r172 ;
vc:bridgesTo ngm:api-gateway ;
vc:bridgesTo ngm:microservices-architecture ;
vc:bridgesTo ngm:peer-to-peer-network ;
vc:bridgesTo ngm:semantic-web-linked-data-standard ;
vc:bridgesTo ngm:web-of-things ;
vc:contrastsWith ngm:model-context-protocol ;
vc:contrastsWith ngm:remote-procedure-call ;
vc:dependsOn ngm:agent-identity ;
vc:dependsOn ngm:autonomous-agent ;
vc:dependsOn ngm:credential-management ;
vc:dependsOn ngm:distributed-systems ;
vc:dependsOn ngm:large-language-model ;
vc:dependsOn ngm:service-discovery ;
vc:enables ngm:agent-marketplace ;
vc:enables ngm:agentic-workflow ;
vc:enables ngm:enterprise-ai ;
vc:enables ngm:inter-agent-communication ;
vc:enables ngm:multi-agent-orchestration ;
vc:enables ngm:task-delegation ;
vc:enables ngm:workflow-automation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:agent-card ;
vc:hasPart ngm:capability-negotiation ;
vc:hasPart ngm:streaming-api ;
vc:hasPart ngm:task-lifecycle ;
vc:qualityScore "0.88"^^xsd:float ;
vc:relatedTo ngm:agent2-agent-protocol-google-2025 ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:api-integration ;
vc:relatedTo ngm:contract-net-protocol ;
vc:relatedTo ngm:digital-twin ;
vc:relatedTo ngm:fipa-acl ;
vc:relatedTo ngm:model-context-protocol ;
vc:relatedTo ngm:multi-agent-system ;
vc:relatedTo ngm:open-agent-network ;
vc:relatedTo ngm:open-source ;
vc:relatedTo ngm:peer-to-peer-network ;
vc:relatedTo ngm:prompt-injection ;
vc:relatedTo ngm:rate-limiting ;
vc:relatedTo ngm:zero-trust-architecture ;
vc:requires ngm:http-protocol ;
vc:requires ngm:json-data-interchange-format-rpc-2-0 ;
vc:requires ngm:json-data-interchange-format-schema ;
vc:requires ngm:mutual-tls ;
vc:requires ngm:oauth-2-0 ;
vc:requires ngm:server-sent-events ;
vc:slug "a2-a-protocol" ;
vc:sourceDomain "ai" ;
vc:supports ngm:agent-orchestrator ;
vc:supports ngm:cost-attribution ;
vc:supports ngm:human-in-the-loop ;
vc:supports ngm:supply-chain-automation ;
vc:supports ngm:task-and-motion-planning ;
vc:uses ngm:agent-frameworks ;
vc:uses ngm:agentic-ai ;
vc:uses ngm:function-calling ;
vc:uses ngm:g-rpc ;
vc:uses ngm:json-ld ;
vc:uses ngm:message-passing ;
vc:uses ngm:protobuf ;
vc:uses ngm:protocol-buffer ;
vc:uses ngm:service-discovery .
ngm:aaai a owl:Class ;
rdfs:comment "AAAI (the Association for the Advancement of Artificial Intelligence), founded in 1979 under the original name 'American Association for Artificial Intelligence' and renamed in 2007, is the principal non-profit scientific society devoted to advancing research in and responsible use of artificial intelligence. It is best known for its flagship annual peer-reviewed conference — one of the most selective and broadly scoped venues in AI — alongside the AI, Ethics and Society (AIES) conference, symposia, workshops, and the journal AI Magazine. AAAI also engages in education, public communication, and policy discussion concerning AI; administers the AAAI Fellows Program recognising sustained contributions to the discipline; and maintains historical continuity as the first professional society dedicated exclusively to AI, founded by leaders including Allen Newell, Edward Feigenbaum, Marvin Minsky, and John McCarthy. AAAI 2026 — the 40th annual conference — received 23,680 submissions and accepted 4,167 papers at a 17.6% acceptance rate, making it the most competitive edition in the conference's history."@en ;
rdfs:label "AAAI"@en ;
rdfs:subClassOf ngm:academic-conference ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf _:r173 ;
skos:broader ngm:ai-research-area ;
vc:bridgesTo ngm:ai-alignment ;
vc:bridgesTo ngm:ai-governance ;
vc:bridgesTo ngm:ai-safety ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:contrastsWith ngm:cvpr ;
vc:contrastsWith ngm:iclr ;
vc:contrastsWith ngm:icml ;
vc:contrastsWith ngm:ijcai ;
vc:contrastsWith ngm:neur-ips ;
vc:enables ngm:ai-alignment ;
vc:enables ngm:ai-for-social-good ;
vc:enables ngm:ai-governance ;
vc:enables ngm:ai-research ;
vc:enables ngm:benchmark-standard ;
vc:enables ngm:research-dissemination ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:aaai-conference ;
vc:hasPart ngm:aaai-fellows-program ;
vc:hasPart ngm:ai-magazine ;
vc:hasPart ngm:peer-review ;
vc:hasPart ngm:poster-session ;
vc:hasPart ngm:programme-committee ;
vc:hasPart ngm:tutorial ;
vc:hasPart ngm:workshop ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:academic-conference ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:causal-inference ;
vc:relatedTo ngm:computer-vision ;
vc:relatedTo ngm:deep-learning ;
vc:relatedTo ngm:generative-ai ;
vc:relatedTo ngm:human-computer-interaction ;
vc:relatedTo ngm:knowledge-representation ;
vc:relatedTo ngm:large-language-model ;
vc:relatedTo ngm:multi-agent-system ;
vc:relatedTo ngm:multimodal-ai-architecture-ai ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:neural-network ;
vc:relatedTo ngm:open-review ;
vc:relatedTo ngm:planning-and-scheduling ;
vc:relatedTo ngm:reasoning ;
vc:relatedTo ngm:reinforcement-learning ;
vc:relatedTo ngm:research-institution ;
vc:relatedTo ngm:retrieval-augmented-generation ;
vc:relatedTo ngm:robotics ;
vc:relatedTo ngm:scientific-conference ;
vc:relatedTo ngm:symbolic-ai ;
vc:slug "aaai" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:double-blind-review ;
vc:standardizedBy ngm:peer-review ;
vc:supports ngm:ai-ethics ;
vc:supports ngm:ai-policy ;
vc:supports ngm:artificial-intelligence ;
vc:supports ngm:explainability ;
vc:supports ngm:fairness-in-machine-learning ;
vc:supports ngm:machine-learning-discipline ;
vc:supports ngm:open-science ;
vc:supports ngm:responsible-ai .
ngm:aaai-aiide a skos:Concept ;
rdfs:label "Aaai Aiide"@en .
ngm:aaai-cognitive-systems a skos:Concept ;
rdfs:label "Aaai Cognitive Systems"@en .
ngm:aaai-conference a skos:Concept ;
rdfs:label "Aaai Conference"@en .
ngm:aaai-fellows-program a skos:Concept ;
rdfs:label "Aaai Fellows Program"@en .
ngm:aardvark-bft a skos:Concept ;
rdfs:label "Aardvark Bft"@en .
ngm:aave a owl:Class ;
rdfs:comment "Aave is a decentralised, non-custodial liquidity protocol deployed on Ethereum and multiple EVM-compatible networks that allows users to supply crypto assets into pooled reserves to earn algorithmically set interest, and to borrow against over-collateralised positions at variable or stable rates. Pioneered by Stani Kulechov and launched as ETHLend in 2017 before rebranding in 2020, it introduced the flash loan — an uncollateralised loan that must be atomically repaid within a single transaction block — as a foundational DeFi primitive. Governance is exercised by AAVE token holders who vote on Aave Improvement Proposals controlling risk parameters, supported asset listings, protocol upgrades, and treasury allocations."@en ;
rdfs:label "Aave"@en ;
rdfs:subClassOf ngm:de-fi ;
rdfs:subClassOf _:r916 ;
rdfs:subClassOf _:r917 ;
rdfs:subClassOf _:r918 ;
rdfs:subClassOf _:r919 ;
vc:bridgesTo ngm:ai-driven-trading ;
vc:bridgesTo ngm:risk-modelling ;
vc:contrastsWith ngm:compound ;
vc:contrastsWith ngm:maker-dao ;
vc:contrastsWith ngm:traditional-finance ;
vc:enables ngm:collateralised-borrowing ;
vc:enables ngm:flash-loan ;
vc:enables ngm:on-chain-arbitrage ;
vc:enables ngm:self-liquidation ;
vc:enables ngm:yield-farming ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:algorithmic-interest-rate ;
vc:implements ngm:atoken ;
vc:implements ngm:on-chain-governance ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:cross-chain-bridge ;
vc:relatedTo ngm:gho-stablecoin ;
vc:relatedTo ngm:liquidation-mechanism ;
vc:relatedTo ngm:stablecoin ;
vc:relatedTo ngm:token-governance ;
vc:requires ngm:oracle ;
vc:requires ngm:over-collateralisation ;
vc:requires ngm:wallet ;
vc:slug "aave" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:chainlink ;
vc:uses ngm:ethereum ;
vc:uses ngm:evm ;
vc:uses ngm:liquidity-pool ;
vc:uses ngm:smart-contracts .
ngm:aave-companies a owl:Class ;
rdfs:comment "Aave Companies is the development company, founded by Stani Kulechov, behind the Aave decentralised lending protocol and related products. It was formerly known as ETHLend."@en ;
rdfs:label "Aave Companies"@en ;
rdfs:subClassOf ngm:aave ;
vc:bridgesTo ngm:de-fi ;
vc:enables ngm:lending-protocol ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:slug "aave-companies" ;
vc:sourceDomain "blockchain" .
ngm:aave-governance a owl:Class ;
rdfs:comment "Aave Governance is the on-chain decision-making system for the Aave decentralised lending protocol, enabling AAVE token holders and protocol delegates to propose, debate, and vote on parameter changes, new asset listings, risk adjustments, and smart contract upgrades. It operates through a tiered proposal mechanism where quorum and voting-power thresholds determine whether a proposal proceeds to execution, with all outcomes enforced autonomously by smart contracts on Ethereum and affiliated networks."@en ;
rdfs:label "Aave Governance"@en ;
rdfs:subClassOf ngm:on-chain-governance ;
vc:dependsOn ngm:aave ;
vc:dependsOn ngm:smart-contract ;
vc:enables ngm:collateral-management ;
vc:enables ngm:de-fi ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:dao-governance ;
vc:relatedTo ngm:token-economics ;
vc:slug "aave-governance" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:governance-token ;
vc:uses ngm:voting-mechanism .
ngm:ab-1008 a skos:Concept ;
rdfs:label "Ab 1008"@en .
ngm:ab-2013 a skos:Concept ;
rdfs:label "Ab 2013"@en .
ngm:ab-489 a skos:Concept ;
rdfs:label "Ab 489"@en .
ngm:abac a skos:Concept ;
rdfs:label "Abac"@en .
ngm:abaqus-fea a skos:Concept ;
rdfs:label "Abaqus Fea"@en .
ngm:abci a skos:Concept ;
rdfs:label "Abci"@en .
ngm:abi a skos:Concept ;
rdfs:label "Abi"@en .
ngm:abi-encoding a owl:Class ;
rdfs:comment "ABI encoding is the Application Binary Interface encoding scheme used by the Ethereum Virtual Machine to serialise function calls and their arguments into the byte layout that smart contracts expect on-chain. It defines fixed rules for encoding primitive types, dynamic types such as strings and arrays, and nested structures, so that a compiled contract can decode calldata deterministically regardless of the source language or tool that produced it. Development toolchains such as Foundry and compilers such as Vyper generate ABI-encoded calldata automatically from a contract's interface definition."@en ;
rdfs:label "ABI Encoding"@en ;
rdfs:subClassOf ngm:smart-contract ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:slug "abi-encoding" ;
vc:sourceDomain "blockchain" .
ngm:abi-repository a skos:Concept ;
rdfs:label "Abi Repository"@en .
ngm:ablation-studies a skos:Concept ;
rdfs:label "Ablation Studies"@en .
ngm:ablation-zone a owl:Class ;
rdfs:label "Ablation Zone"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-system-phenomena ;
vc:slug "ablation-zone" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:abnormally-dangerous-activity-doctrine a skos:Concept ;
rdfs:label "Abnormally Dangerous Activity Doctrine"@en .
ngm:abox a skos:Concept ;
rdfs:label "Abox"@en .
ngm:abr-algorithm a skos:Concept ;
rdfs:label "Abr Algorithm"@en .
ngm:absolute-magnitude a owl:Class ;
rdfs:label "Absolute Magnitude"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:astronomy ;
vc:slug "absolute-magnitude" ;
vc:sourceDomain "space-science-and-systems" .
ngm:absolute-positional-encoding a skos:Concept ;
rdfs:label "Absolute Positional Encoding"@en .
ngm:abstract-interpretation a skos:Concept ;
rdfs:label "Abstract Interpretation"@en .
ngm:abstract-syntax-tree a skos:Concept ;
rdfs:label "Abstract Syntax Tree"@en .
ngm:abstraction-layer a skos:Concept ;
rdfs:label "Abstraction Layer"@en .
ngm:abstraction-modules a skos:Concept ;
rdfs:label "Abstraction Modules"@en .
ngm:academia a owl:Class ;
rdfs:comment "The worldwide community and institutional system devoted to the production, validation, and transmission of scholarly knowledge — universities, research institutes, learned societies, journals, and conferences — organised around disciplines, credentialed through degrees and peer review, and governed by norms of originality, citation, and open critique that distinguish scholarly knowledge from other forms of expertise."@en ;
rdfs:label "Academia"@en ;
rdfs:subClassOf ngm:education ;
rdfs:subClassOf _:r920 ;
rdfs:subClassOf _:r921 ;
rdfs:subClassOf _:r922 ;
vc:enables ngm:academic-research ;
vc:enables ngm:technology-transfer ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:academic-conference ;
vc:hasPart ngm:peer-review ;
vc:hasPart ngm:research-institution ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:open-science ;
vc:slug "academia" ;
vc:sourceDomain "governance" ;
vc:uses ngm:scientific-method .
ngm:academic-ai-labs a skos:Concept ;
rdfs:label "Academic AI Labs"@en .
ngm:academic-conference a owl:Class ;
rdfs:comment "An academic conference is a periodic, structured gathering at which researchers present, discuss, and publish peer-reviewed work, serving as the primary mechanism for disseminating new findings, validating scientific claims, and setting research agendas in a discipline. Submissions are evaluated by a programme committee drawn from the research community, with accepted papers published in conference proceedings and delivered through oral presentations, poster sessions, and co-located workshops. In computer science and artificial intelligence specifically, leading venues such as NeurIPS, ICML, CVPR, and ICLR function as the primary records of scientific priority, where peer review, archival publication, and community exchange are tightly coupled rather than mediated solely through journal cycles — a structural feature that distinguishes the field from most traditional sciences and accelerates the pace at which novel results enter the community."@en ;
rdfs:label "Academic Conference"@en ;
rdfs:subClassOf ngm:academia ;
rdfs:subClassOf ngm:scientific-research ;
rdfs:subClassOf _:r923 ;
rdfs:subClassOf _:r924 ;
rdfs:subClassOf _:r925 ;
rdfs:subClassOf _:r926 ;
rdfs:subClassOf _:r927 ;
vc:contrastsWith ngm:arxiv ;
vc:dependsOn ngm:academia ;
vc:dependsOn ngm:peer-review ;
vc:dependsOn ngm:programme-committee ;
vc:dependsOn ngm:scientific-method ;
vc:dependsOn ngm:scientific-research ;
vc:enables ngm:artificial-intelligence-research ;
vc:enables ngm:benchmark-standard ;
vc:enables ngm:collaboration ;
vc:enables ngm:knowledge-sharing ;
vc:enables ngm:open-science ;
vc:enables ngm:reproducibility ;
vc:enables ngm:research-dissemination ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:double-blind-review ;
vc:hasPart ngm:peer-review ;
vc:hasPart ngm:poster-session ;
vc:hasPart ngm:proceedings ;
vc:hasPart ngm:programme-committee ;
vc:hasPart ngm:publication ;
vc:hasPart ngm:workshop ;
vc:implements ngm:double-blind-review ;
vc:implements ngm:open-science ;
vc:implements ngm:peer-review ;
vc:isPartOf ngm:academia ;
vc:isPartOf ngm:scientific-research ;
vc:qualityScore "0.87"^^xsd:float ;
vc:relatedTo ngm:aaai ;
vc:relatedTo ngm:benchmark-standard ;
vc:relatedTo ngm:computer-vision ;
vc:relatedTo ngm:cvpr ;
vc:relatedTo ngm:generative-ai ;
vc:relatedTo ngm:iccv ;
vc:relatedTo ngm:iclr ;
vc:relatedTo ngm:icml ;
vc:relatedTo ngm:ijcai ;
vc:relatedTo ngm:knowledge-graph ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:neur-ips ;
vc:relatedTo ngm:publication ;
vc:relatedTo ngm:reinforcement-learning ;
vc:requires ngm:double-blind-review ;
vc:requires ngm:peer-review ;
vc:requires ngm:programme-committee ;
vc:requires ngm:scientific-method ;
vc:slug "academic-conference" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:icml ;
vc:standardizedBy ngm:neur-ips ;
vc:supports ngm:ai-ethics ;
vc:supports ngm:ai-safety-research ;
vc:supports ngm:artificial-intelligence-research ;
vc:supports ngm:computer-vision ;
vc:supports ngm:deep-learning ;
vc:supports ngm:generative-ai ;
vc:supports ngm:machine-learning-discipline ;
vc:supports ngm:natural-language-processing ;
vc:supports ngm:reinforcement-learning ;
vc:uses ngm:arxiv ;
vc:uses ngm:double-blind-review ;
vc:uses ngm:open-review ;
vc:uses ngm:openreview ;
vc:uses ngm:peer-review .
ngm:academic-conference-series a skos:Concept ;
rdfs:label "Academic Conference Series"@en .
ngm:academic-crawler a skos:Concept ;
rdfs:label "Academic Crawler"@en .
ngm:academic-peer-review a skos:Concept ;
rdfs:label "Academic Peer Review"@en .
ngm:academic-research a owl:Class ;
rdfs:comment "Academic research is the systematic, disciplined inquiry conducted within universities and research institutions to generate, validate, and disseminate new knowledge. It proceeds through formulating questions, reviewing prior literature, designing and executing studies under the scientific method, and subjecting findings to peer review before publication. Its outputs include papers, datasets, and theories that are cited and built upon by the wider scholarly community. Governance norms such as reproducibility, transparency, and research integrity distinguish it from informal or commercial knowledge production."@en ;
rdfs:label "Academic Research"@en ;
rdfs:subClassOf ngm:governance ;
rdfs:subClassOf _:r928 ;
rdfs:subClassOf _:r929 ;
rdfs:subClassOf _:r930 ;
vc:bridgesTo ngm:knowledge-graph ;
vc:bridgesTo ngm:open-access ;
vc:enables ngm:knowledge-graph ;
vc:enables ngm:open-access ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:peer-review ;
vc:hasPart ngm:reproducibility ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:academia ;
vc:relatedTo ngm:reproducibility ;
vc:relatedTo ngm:scientific-method ;
vc:requires ngm:scientific-method ;
vc:slug "academic-research" ;
vc:sourceDomain "governance" ;
vc:supports ngm:governance ;
vc:uses ngm:peer-review ;
vc:uses ngm:scientific-method .
ngm:academic-research-pipeline a skos:Concept ;
rdfs:label "Academic Research Pipeline"@en .
ngm:academy-software-foundation a owl:Class ;
rdfs:comment "The Academy Software Foundation (ASWF) is a neutral, vendor-independent organisation, hosted under the Linux Foundation and founded with the Academy of Motion Picture Arts and Sciences, that develops and stewards open-source software for the motion picture and broader media industries. It provides shared governance, infrastructure and funding for foundational projects in visual effects, animation and digital content creation, such as OpenColorIO, OpenEXR, OpenVDB, OpenTimelineIO and MaterialX. Its goal is sustainable, interoperable open-source tooling across the production pipeline."@en ;
rdfs:label "Academy Software Foundation"@en ;
rdfs:subClassOf ngm:standards-organization ;
rdfs:subClassOf _:r931 ;
vc:enables ngm:asset-pipeline ;
vc:enables ngm:interoperability ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:open-source-software ;
vc:isPartOf ngm:linux-foundation ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:computer-graphics ;
vc:relatedTo ngm:film-production ;
vc:relatedTo ngm:usd ;
vc:slug "academy-software-foundation" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:standards ;
vc:supports ngm:animation ;
vc:supports ngm:digital-content-creation ;
vc:supports ngm:visual-effects ;
vc:uses ngm:governance ;
vc:uses ngm:open-source .
ngm:acados a skos:Concept ;
rdfs:label "Acados"@en .
ngm:accelerated-gradient-descent a skos:Concept ;
rdfs:label "Accelerated Gradient Descent"@en .
ngm:accelerated-life-testing a skos:Concept ;
rdfs:label "Accelerated Life Testing"@en .
ngm:acceleration-planning a skos:Concept ;
rdfs:label "Acceleration Planning"@en .
ngm:acceleration-profile a skos:Concept ;
rdfs:label "Acceleration Profile"@en .
ngm:acceleration-structure a owl:Class ;
rdfs:comment "An acceleration structure is a spatial data structure that organises geometric primitives in a scene to allow rapid culling of irrelevant geometry during ray intersection or visibility queries, dramatically reducing the computational complexity of rendering algorithms from O(n) per-ray to approximately O(log n). Common forms include bounding volume hierarchies, k-d trees, and octrees, each making different trade-offs between construction time, memory footprint, and query efficiency."@en ;
rdfs:label "Acceleration Structure"@en ;
rdfs:subClassOf ngm:spatial-index ;
vc:enables ngm:ray-tracing ;
vc:enables ngm:real-time-rendering ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:scene-graph ;
vc:slug "acceleration-structure" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:collision-detection ;
vc:supports ngm:rendering-pipeline ;
vc:uses ngm:bounding-volume-hierarchy ;
vc:uses ngm:gpu-acceleration .
ngm:accelerometer a owl:Class ;
rdfs:comment "Accelerometer - A microelectromechanical sensor (MEMS) that detects changes in velocity and gravity along three orthogonal axes, enabling robots to measure Motion, Orientation, and Vibration for real-time feedback control and navigation."@en ;
rdfs:label "Accelerometer"@en ;
rdfs:subClassOf ngm:robo-perception ;
rdfs:subClassOf ngm:robotics ;
rdfs:subClassOf _:r932 ;
skos:broader ngm:robo-perception ;
skos:broader ngm:robotics ;
vc:bridgesTo ngm:sensor ;
vc:enables ngm:gesture-recognition ;
vc:enables ngm:motion-detection ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:inertial-measurement-unit ;
vc:qualityScore "0.55"^^xsd:float ;
vc:requires ngm:signal-conditioning ;
vc:slug "accelerometer" ;
vc:sourceDomain "robotics" ;
vc:uses ngm:robotics .
ngm:accent-adaptation a skos:Concept ;
rdfs:label "Accent Adaptation"@en .
ngm:acceptable-use-policy a skos:Concept ;
rdfs:label "Acceptable Use Policy"@en .
ngm:acceptance-criterion a skos:Concept ;
rdfs:label "Acceptance Criterion"@en .
ngm:acceptance-network a skos:Concept ;
rdfs:label "Acceptance Network"@en .
ngm:acceptance-probability a skos:Concept ;
rdfs:label "Acceptance Probability"@en .
ngm:acceptance-ratio a skos:Concept ;
rdfs:label "Acceptance Ratio"@en .
ngm:acceptance-testing a skos:Concept ;
rdfs:label "Acceptance Testing"@en .
ngm:accepting-state a skos:Concept ;
rdfs:label "Accepting State"@en .
ngm:access-control a owl:Class ;
rdfs:comment "Access control is a fundamental security mechanism that regulates which users, systems, or processes can view, use, or modify resources within a computing environment. It encompasses the policies, procedures, and technologies that govern the granting and restricting of access rights, ensuring that only authorised entities can perform specific actions on protected resources based on their identity, role, or attributes."@en ;
rdfs:label "Access Control"@en ;
rdfs:subClassOf ngm:infra-security-and-identity ;
rdfs:subClassOf ngm:security ;
rdfs:subClassOf _:r950 ;
rdfs:subClassOf _:r951 ;
rdfs:subClassOf _:r952 ;
rdfs:subClassOf _:r953 ;
rdfs:subClassOf _:r954 ;
rdfs:subClassOf _:r955 ;
skos:broader ngm:infra-security-and-identity ;
vc:bridgesTo ngm:cryptography ;
vc:bridgesTo ngm:decentralised-identity ;
vc:bridgesTo ngm:smart-contract ;
vc:contrastsWith ngm:open-access ;
vc:enables ngm:compliance ;
vc:enables ngm:data-protection ;
vc:enables ngm:least-privilege ;
vc:enables ngm:security ;
vc:enables ngm:separation-of-duties ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:audit-logging ;
vc:hasPart ngm:authentication ;
vc:hasPart ngm:authorisation ;
vc:hasPart ngm:identity-and-access-management ;
vc:implements ngm:attribute-based-access-control ;
vc:implements ngm:authorisation ;
vc:implements ngm:identity-and-access-management ;
vc:implements ngm:mandatory-access-control ;
vc:implements ngm:role-based-access-control ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:multi-factor-authentication ;
vc:relatedTo ngm:network-security ;
vc:relatedTo ngm:security ;
vc:requires ngm:cryptography ;
vc:requires ngm:identity-management ;
vc:slug "access-control" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:iso-iec-27001 ;
vc:standardizedBy ngm:nist-sp-800-53 ;
vc:supports ngm:regulatory-compliance ;
vc:supports ngm:zero-trust-architecture ;
vc:uses ngm:access-control-list ;
vc:uses ngm:identity-and-access-management ;
vc:uses ngm:privileged-access-management .
ngm:access-control-decisions a owl:Class ;
rdfs:comment "Access Control Decisions are the runtime determinations made by a policy engine or decision point as to whether a particular subject—user, process, or device—is permitted to perform a requested action on a protected resource, based on evaluated policies, attributes, and contextual signals. These decisions are the operational output of an access control architecture and are typically produced by a Policy Decision Point (PDP) and enforced by a Policy Enforcement Point (PEP)."@en ;
rdfs:label "Access Control Decisions"@en ;
rdfs:subClassOf ngm:access-control ;
vc:dependsOn ngm:authentication ;
vc:dependsOn ngm:identity-management ;
vc:enables ngm:authorisation ;
vc:enables ngm:zero-trust-architecture ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:policy-enforcement-point ;
vc:relatedTo ngm:role-based-access-control ;
vc:slug "access-control-decisions" ;
vc:sourceDomain "security" ;
vc:uses ngm:policy-decision-point ;
vc:uses ngm:policy-engine .
ngm:access-control-list a skos:Concept ;
rdfs:label "Access Control List"@en .
ngm:access-control-module a owl:Class ;
rdfs:comment "An Access Control Module is a self-contained software component that enforces authorization rules governing which principals may invoke which functions or read which resources. In smart-contract systems it is commonly implemented as a reusable mixin defining roles, ownership, and permission checks that other contracts inherit. It centralizes permission logic so that privileged operations such as timelocked upgrades or rights revocation are gated behind verifiable on-chain conditions."@en ;
rdfs:label "Access Control Module"@en ;
rdfs:subClassOf ngm:infra-security-and-identity ;
skos:broader ngm:infra-security-and-identity ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:digital-rights-management-extended ;
vc:relatedTo ngm:timelock ;
vc:slug "access-control-module" ;
vc:sourceDomain "security" .
ngm:access-control-policy a owl:Class ;
rdfs:comment "An Access Control Policy is a machine-readable specification of the rules that determine which agents may read, write, or append to a given resource. In decentralized web-data systems such as Solid, policies are expressed as RDF documents (e.g. WAC or ACP) attached to resources, granting or denying modes of access to identified WebID principals or groups. The policy is the declarative source of truth that an authorization engine evaluates on each request."@en ;
rdfs:label "Access Control Policy"@en ;
rdfs:subClassOf ngm:infra-security-and-identity ;
skos:broader ngm:infra-security-and-identity ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:identity-management ;
vc:relatedTo ngm:solid ;
vc:slug "access-control-policy" ;
vc:sourceDomain "security" .
ngm:access-control-system a owl:Class ;
rdfs:comment "An Access Control System is the assemblage of policies, decision engines, enforcement points, identity providers, attribute sources, audit pipelines, and cryptographic primitives that determines wher a subject (human user, service account, autonomous agent, device) is permitted to perform a r..."@en ;
rdfs:label "Access Control System"@en ;
rdfs:subClassOf ngm:authorisation-mechanism ;
rdfs:subClassOf ngm:governance-control ;
rdfs:subClassOf ngm:information-security-system ;
rdfs:subClassOf ngm:infra-security-and-identity ;
rdfs:subClassOf ngm:security-control ;
rdfs:subClassOf _:r933 ;
rdfs:subClassOf _:r934 ;
rdfs:subClassOf _:r935 ;
rdfs:subClassOf _:r936 ;
rdfs:subClassOf _:r937 ;
rdfs:subClassOf _:r938 ;
rdfs:subClassOf _:r939 ;
rdfs:subClassOf _:r940 ;
rdfs:subClassOf _:r941 ;
rdfs:subClassOf _:r942 ;
rdfs:subClassOf _:r943 ;
rdfs:subClassOf _:r944 ;
rdfs:subClassOf _:r945 ;
rdfs:subClassOf _:r946 ;
rdfs:subClassOf _:r947 ;
rdfs:subClassOf _:r948 ;
rdfs:subClassOf _:r949 ;
skos:broader ngm:infra-security-and-identity ;
vc:bridgesTo ngm:control-theory ;
vc:bridgesTo ngm:smart-contract ;
vc:bridgesTo ngm:training-data ;
vc:contrastsWith ngm:capability-based-security ;
vc:contrastsWith ngm:decentralised-identifier ;
vc:contrastsWith ngm:passwordless-authentication ;
vc:contrastsWith ngm:self-sovereign-identity ;
vc:contrastsWith ngm:verifiable-credential-vc ;
vc:dependsOn ngm:cryptographic-infrastructure ;
vc:dependsOn ngm:cryptography ;
vc:dependsOn ngm:directory-service ;
vc:dependsOn ngm:secure-logging ;
vc:dependsOn ngm:time-synchronisation ;
vc:enables ngm:accountability ;
vc:enables ngm:auditability ;
vc:enables ngm:distributed-system ;
vc:enables ngm:least-privilege ;
vc:enables ngm:quality-assurance ;
vc:enables ngm:regulatory-compliance ;
vc:enables ngm:risk-assessment ;
vc:enables ngm:separation-of-duties ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:attribute-evaluation ;
vc:hasPart ngm:audit-log ;
vc:hasPart ngm:identity-system ;
vc:hasPart ngm:policy-administration-point ;
vc:hasPart ngm:policy-decision-point ;
vc:hasPart ngm:policy-enforcement-point ;
vc:hasPart ngm:policy-engine ;
vc:hasPart ngm:policy-information-point ;
vc:hasPart ngm:session-manager ;
vc:hasPart ngm:token-service ;
vc:implements ngm:abac ;
vc:implements ngm:capability-based-security ;
vc:implements ngm:dac ;
vc:implements ngm:mac ;
vc:implements ngm:pbac ;
vc:implements ngm:rbac ;
vc:implements ngm:rebac ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:identity-and-access-management ;
vc:relatedTo ngm:identity-management ;
vc:relatedTo ngm:multi-factor-authentication ;
vc:relatedTo ngm:privileged-access-management ;
vc:relatedTo ngm:secrets-management ;
vc:relatedTo ngm:single-sign-on ;
vc:requires ngm:api-gateway ;
vc:requires ngm:authentication ;
vc:requires ngm:cryptographic-primitive ;
vc:requires ngm:identity-provider ;
vc:requires ngm:metadata-management ;
vc:requires ngm:trusted-timestamping ;
vc:slug "access-control-system" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:ansi-incits-359 ;
vc:standardizedBy ngm:ietf ;
vc:standardizedBy ngm:ietf-rfc-6749 ;
vc:standardizedBy ngm:iso-iec-27002 ;
vc:standardizedBy ngm:nist ;
vc:standardizedBy ngm:nist-sp-800-207 ;
vc:standardizedBy ngm:oasis ;
vc:standardizedBy ngm:web-authn ;
vc:supports ngm:compliance-framework ;
vc:supports ngm:forensic-investigation ;
vc:supports ngm:incident-response ;
vc:supports ngm:privileged-access-management ;
vc:supports ngm:zero-trust-architecture ;
vc:uses ngm:kerberos ;
vc:uses ngm:ldap ;
vc:uses ngm:oauth-2-0 ;
vc:uses ngm:open-id-connect ;
vc:uses ngm:open-policy-agent ;
vc:uses ngm:saml ;
vc:uses ngm:web-authn ;
vc:uses ngm:xacml ;
vc:uses ngm:zanzibar .
ngm:access-controls a owl:Class ;
rdfs:comment "Access controls are mechanisms that govern which subjects may perform which operations on resources, enforcing authorisation policies."@en ;
rdfs:label "Access Controls"@en ;
rdfs:subClassOf ngm:authorisation ;
rdfs:subClassOf _:r956 ;
vc:bridgesTo ngm:identity-management ;
vc:enables ngm:information-security ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:authentication ;
vc:slug "access-controls" ;
vc:sourceDomain "distributed-systems" .
ngm:access-log-emitter a skos:Concept ;
rdfs:label "Access Log Emitter"@en .
ngm:access-logs a skos:Concept ;
rdfs:label "Access Logs"@en .
ngm:access-to-justice a skos:Concept ;
rdfs:label "Access To Justice"@en .
ngm:access-to-services a skos:Concept ;
rdfs:label "Access To Services"@en .
ngm:access-to-systems-and-personnel a skos:Concept ;
rdfs:label "Access To Systems And Personnel"@en .
ngm:access-token a owl:Class ;
rdfs:comment "An access token is a credential that a client presents to a resource server to access protected resources within a granted scope and lifetime. Typically short-lived and often a bearer token, it carries or references the authorisation decision so the resource server need not re-check with the authorisation server on every request. Access tokens are the workhorse credential of OAuth 2.0 and API authorisation."@en ;
rdfs:label "Access Token"@en ;
rdfs:subClassOf ngm:oauth-2-0 ;
rdfs:subClassOf _:r957 ;
rdfs:subClassOf _:r958 ;
vc:bridgesTo ngm:identity-provider ;
vc:contrastsWith ngm:refresh-token ;
vc:dependsOn ngm:oauth ;
vc:enables ngm:api ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:token ;
vc:implements ngm:authorization ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:authorization ;
vc:relatedTo ngm:oauth ;
vc:relatedTo ngm:session-management ;
vc:relatedTo ngm:token ;
vc:requires ngm:authentication ;
vc:slug "access-token" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:standards ;
vc:supports ngm:single-sign-on ;
vc:uses ngm:bearer-token ;
vc:uses ngm:oauth-2-0 .
ngm:accessibility a owl:Class ;
rdfs:comment "Accessibility is the systematic property of digital products, services, environments and information systems being perceivable, operable, understandable and robust (POUR) for the widest possible range of users including those with permanent disabilities temporary impairments (broken arm, post-sur..."@en ;
rdfs:label "Accessibility"@en ;
rdfs:subClassOf ngm:design-principle ;
rdfs:subClassOf ngm:human-factors ;
rdfs:subClassOf ngm:inclusive-design ;
rdfs:subClassOf ngm:non-functional-requirement ;
rdfs:subClassOf ngm:quality-attribute ;
rdfs:subClassOf ngm:sc-governance-and-safety ;
rdfs:subClassOf _:r974 ;
rdfs:subClassOf _:r975 ;
rdfs:subClassOf _:r976 ;
rdfs:subClassOf _:r977 ;
rdfs:subClassOf _:r978 ;
rdfs:subClassOf _:r979 ;
rdfs:subClassOf _:r980 ;
rdfs:subClassOf _:r981 ;
rdfs:subClassOf _:r982 ;
rdfs:subClassOf _:r983 ;
skos:broader ngm:sc-governance-and-safety ;
vc:bridgesTo ngm:software-engineering ;
vc:contrastsWith ngm:inclusive-design ;
vc:contrastsWith ngm:reasonable-accommodation ;
vc:contrastsWith ngm:universal-design ;
vc:dependsOn ngm:assistive-technology-ecosystem ;
vc:dependsOn ngm:disability-studies ;
vc:dependsOn ngm:human-factors-research ;
vc:dependsOn ngm:operating-system-accessibility-apis ;
vc:dependsOn ngm:web-standards ;
vc:enables ngm:disability-inclusion ;
vc:enables ngm:equitable-access ;
vc:enables ngm:independent-living ;
vc:enables ngm:market-expansion ;
vc:enables ngm:regulatory-compliance ;
vc:enables ngm:usability ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:accessibility-statement ;
vc:hasPart ngm:accessible-name-computation ;
vc:hasPart ngm:alternative-text ;
vc:hasPart ngm:audio-description ;
vc:hasPart ngm:focus-management ;
vc:hasPart ngm:keyboard-navigation ;
vc:hasPart ngm:live-captions ;
vc:hasPart ngm:operability ;
vc:hasPart ngm:perceivability ;
vc:hasPart ngm:robustness ;
vc:hasPart ngm:semantic-html ;
vc:hasPart ngm:understandability ;
vc:implements ngm:atag-2-0 ;
vc:implements ngm:en-301-549 ;
vc:implements ngm:pour-principles ;
vc:implements ngm:section-508 ;
vc:implements ngm:wai-aria-1-2 ;
vc:implements ngm:wcag-2-2 ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:disability-rights ;
vc:relatedTo ngm:internationalisation ;
vc:relatedTo ngm:localisation ;
vc:relatedTo ngm:privacy ;
vc:relatedTo ngm:safety ;
vc:relatedTo ngm:usability ;
vc:relatedTo ngm:user-experience ;
vc:requires ngm:assistive-technology ;
vc:requires ngm:colour-contrast ;
vc:requires ngm:keyboard-operability ;
vc:requires ngm:semantic-html ;
vc:requires ngm:user-research ;
vc:requires ngm:wai-aria ;
vc:slug "accessibility" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:bs-8878 ;
vc:standardizedBy ngm:en-301-549 ;
vc:standardizedBy ngm:iso-iec-40500 ;
vc:standardizedBy ngm:section-508 ;
vc:standardizedBy ngm:w3c-wai ;
vc:supports ngm:accessibility-captioning ;
vc:supports ngm:cognitively-diverse-users ;
vc:supports ngm:eye-tracking-users ;
vc:supports ngm:keyboard-only-users ;
vc:supports ngm:screen-reader-users ;
vc:supports ngm:switch-users ;
vc:supports ngm:voice-control-users ;
vc:uses ngm:axe-core ;
vc:uses ngm:jaws ;
vc:uses ngm:lighthouse ;
vc:uses ngm:nvda ;
vc:uses ngm:pa11y ;
vc:uses ngm:talkback ;
vc:uses ngm:voiceover ;
vc:uses ngm:wave .
ngm:accessibility-audit-tool a owl:Class ;
rdfs:comment "An automated software utility that verifies compliance with accessibility standards (such as WCAG) in XR environments, identifying barriers for users with disabilities."@en ;
rdfs:label "Accessibility Audit Tool"@en ;
rdfs:subClassOf ngm:sc-governance-and-safety ;
rdfs:subClassOf _:r959 ;
rdfs:subClassOf _:r960 ;
rdfs:subClassOf _:r961 ;
rdfs:subClassOf _:r962 ;
rdfs:subClassOf _:r963 ;
rdfs:subClassOf _:r964 ;
skos:broader ngm:sc-governance-and-safety ;
vc:bridgesTo ngm:telecollaboration ;
vc:dependsOn ngm:testing-protocol ;
vc:dependsOn ngm:wcag-guidelines ;
vc:dependsOn ngm:xr-accessibility-standards ;
vc:enables ngm:accessibility-reporting ;
vc:enables ngm:compliance-verification ;
vc:enables ngm:inclusive-design ;
vc:enables ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:automated-testing ;
vc:hasPart ngm:compliance-dashboard ;
vc:hasPart ngm:report-generator ;
vc:hasPart ngm:wcag-validator ;
vc:isPartOf ngm:quality-assurance ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:accessibility-standards ;
vc:requires ngm:testing ;
vc:requires ngm:user-interface-analyzer ;
vc:slug "accessibility-audit-tool" ;
vc:sourceDomain "spatial-computing" .
ngm:accessibility-captioning a owl:Class ;
rdfs:comment "Accessibility captioning is the practice of producing synchronised textual representations of spoken dialogue, sound effects, and other audio information within video or live media so that deaf, hard-of-hearing, or audio-impaired audiences can fully engage with the content. It encompasses both closed captions (user-selectable, stored separately from the video stream) and open captions (burned into the image), and spans pre-produced transcription and real-time automatic speech recognition pipelines."@en ;
rdfs:label "Accessibility Captioning"@en ;
rdfs:subClassOf ngm:inclusive-design ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:transparency ;
vc:slug "accessibility-captioning" ;
vc:sourceDomain "standards" ;
vc:standardizedBy ngm:wcag-2-2 ;
vc:supports ngm:assistive-technology-integration ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:speech-recognition .
ngm:accessibility-in-harsh-environments a skos:Concept ;
rdfs:label "Accessibility In Harsh Environments"@en .
ngm:accessibility-reporting a skos:Concept ;
rdfs:label "Accessibility Reporting"@en .
ngm:accessibility-requirement a skos:Concept ;
rdfs:label "Accessibility Requirement"@en .
ngm:accessibility-standard a owl:Class ;
rdfs:comment "Normative specification ensuring equitable access to digital content, services, and experiences for users with diverse abilities and disabilities, covering visual, auditory, motor, cognitive, and neurological access paths with testable conformance criteria."@en ;
rdfs:label "Accessibility Standard"@en ;
rdfs:subClassOf ngm:sc-governance-and-safety ;
rdfs:subClassOf _:r965 ;
rdfs:subClassOf _:r966 ;
rdfs:subClassOf _:r967 ;
rdfs:subClassOf _:r968 ;
rdfs:subClassOf _:r969 ;
skos:broader ngm:sc-governance-and-safety ;
vc:bridgesTo ngm:human-computer-interaction ;
vc:bridgesTo ngm:telecollaboration ;
vc:enables ngm:digital-inclusion ;
vc:enables ngm:equitable-access ;
vc:enables ngm:inclusive-xr-experience ;
vc:enables ngm:universal-design ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:accessibility-requirement ;
vc:hasPart ngm:compliance-metric ;
vc:hasPart ngm:testing-protocol ;
vc:hasPart ngm:xr-accessibility-guideline ;
vc:implements ngm:section-508 ;
vc:implements ngm:wcag-2-2 ;
vc:isPartOf ngm:compliance-framework ;
vc:isPartOf ngm:governance-framework ;
vc:qualityScore "0.68"^^xsd:float ;
vc:relatedTo ngm:ai-governance-and-ethics ;
vc:relatedTo ngm:middleware-layer ;
vc:requires ngm:assistive-technology ;
vc:requires ngm:user-interface-standard ;
vc:requires ngm:xr-accessibility-guideline ;
vc:slug "accessibility-standard" ;
vc:sourceDomain "standards" ;
vc:standardizedBy ngm:etsi ;
vc:standardizedBy ngm:iso ;
vc:standardizedBy ngm:w3-c ;
vc:supports ngm:user-experience-design .
ngm:accessibility-standards a owl:Class ;
rdfs:comment "Accessibility Standards for the metaverse and extended reality (XR) encompass guidelines, technical specifications, and design principles that ensure virtual environments, interfaces, and interactions are usable by people with diverse disabilities including visual, auditory, physical, cognitive, and neurological impairments. Key bodies include the W3C XR Accessibility User Requirements (XRAUR), WCAG 2.2/3.0 adaptations, ADA digital interpretations, and inclusive immersion frameworks covering multi-modal input, hardware ergonomics, and spatial interface design."@en ;
rdfs:label "Accessibility Standards"@en ;
rdfs:subClassOf ngm:design-standards ;
rdfs:subClassOf ngm:sc-governance-and-safety ;
rdfs:subClassOf _:r970 ;
rdfs:subClassOf _:r971 ;
skos:broader ngm:sc-governance-and-safety ;
vc:bridgesTo ngm:governance ;
vc:bridgesTo ngm:human-computer-interaction ;
vc:bridgesTo ngm:infra-legal-and-regulatory ;
vc:bridgesTo ngm:telecollaboration ;
vc:contrastsWith ngm:interface-standards ;
vc:enables ngm:equitable-access ;
vc:enables ngm:inclusive-xr-experience ;
vc:enables ngm:universal-design ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:inclusive-design ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:extended-reality ;
vc:relatedTo ngm:spatial-computing ;
vc:relatedTo ngm:user-experience-design ;
vc:requires ngm:assistive-technology-integration ;
vc:requires ngm:eye-tracking ;
vc:requires ngm:multi-modal-interfaces ;
vc:slug "accessibility-standards" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:w3-c ;
vc:standardizedBy ngm:wcag-2-2 ;
vc:standardizedBy ngm:xr-accessibility-user-requirements ;
vc:supports ngm:metaverse ;
vc:supports ngm:telecollaboration .
ngm:accessibility-statement a skos:Concept ;
rdfs:label "Accessibility Statement"@en .
ngm:accessibility-technology a skos:Concept ;
rdfs:label "Accessibility Technology"@en .
ngm:accessibility-tools a skos:Concept ;
rdfs:label "Accessibility Tools"@en .
ngm:accessibility-tree a owl:Class ;
rdfs:comment "The Accessibility Tree is a structured, platform-independent semantic representation of a user interface that browsers and native application runtimes construct in parallel with the visual render tree, exposing each element's role, name, description, state, and value to platform accessibility APIs and programmatic automation clients. Derived from the Document Object Model by filtering out presentational and layout-only nodes, it is the authoritative conduit through which screen readers, braille displays, switch-access devices, voice-control systems, and AI browser agents perceive and interact with software interfaces without parsing raw pixels."@en ;
rdfs:label "Accessibility Tree"@en ;
rdfs:subClassOf ngm:human-computer-interaction ;
rdfs:subClassOf ngm:inclusive-design ;
rdfs:subClassOf ngm:semantic-representation ;
rdfs:subClassOf ngm:user-interface ;
rdfs:subClassOf ngm:user-interface-model ;
rdfs:subClassOf _:r972 ;
rdfs:subClassOf _:r973 ;
vc:contrastsWith ngm:pixel-based-interaction ;
vc:contrastsWith ngm:screenshot-based-automation ;
vc:contrastsWith ngm:visual-render-tree ;
vc:dependsOn ngm:browser-rendering-engine ;
vc:dependsOn ngm:chrome-devtools-protocol ;
vc:dependsOn ngm:document-object-model ;
vc:dependsOn ngm:semantic-html ;
vc:dependsOn ngm:wai-aria ;
vc:enables ngm:assistive-technology ;
vc:enables ngm:automated-accessibility-testing ;
vc:enables ngm:autonomous-task-execution ;
vc:enables ngm:browser-automation ;
vc:enables ngm:computer-use-and-browser-agents ;
vc:enables ngm:jaws-screen-reader ;
vc:enables ngm:keyboard-navigation ;
vc:enables ngm:nvda-screen-reader ;
vc:enables ngm:switch-access ;
vc:enables ngm:voice-control ;
vc:enables ngm:voiceover ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:accessible-description ;
vc:hasPart ngm:accessible-name ;
vc:hasPart ngm:accessible-name-computation ;
vc:hasPart ngm:alternative-text ;
vc:hasPart ngm:aria-role ;
vc:hasPart ngm:aria-state ;
vc:hasPart ngm:focus-management ;
vc:hasPart ngm:live-region ;
vc:hasPart ngm:role-name-state-value-tuple ;
vc:implements ngm:atk-at-spi ;
vc:implements ngm:core-accessibility-api-mappings ;
vc:implements ngm:msaa-iaccessible2 ;
vc:implements ngm:platform-accessibility-api ;
vc:implements ngm:wcag-2-2 ;
vc:implements ngm:windows-ui-automation ;
vc:qualityScore "0.92"^^xsd:float ;
vc:relatedTo ngm:accessibility-audit-tool ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:axe-core ;
vc:relatedTo ngm:chrome-devtools-protocol ;
vc:relatedTo ngm:computer-use-and-browser-agents ;
vc:relatedTo ngm:large-language-model ;
vc:relatedTo ngm:model-context-protocol ;
vc:relatedTo ngm:platform-accessibility-api ;
vc:relatedTo ngm:playwright-mcp ;
vc:relatedTo ngm:universal-design ;
vc:relatedTo ngm:web-agent ;
vc:relatedTo ngm:webdriver-bidi ;
vc:requires ngm:accessible-name-computation ;
vc:requires ngm:document-object-model ;
vc:requires ngm:html-accessibility-api-mappings ;
vc:requires ngm:platform-accessibility-api ;
vc:requires ngm:semantic-html ;
vc:requires ngm:wai-aria ;
vc:slug "accessibility-tree" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:accessibility-standard ;
vc:standardizedBy ngm:core-accessibility-api-mappings ;
vc:standardizedBy ngm:html-accessibility-api-mappings ;
vc:standardizedBy ngm:wai-aria ;
vc:standardizedBy ngm:wcag-2-2 ;
vc:standardizedBy ngm:web-accessibility-initiative ;
vc:supports ngm:accessibility ;
vc:supports ngm:accessibility-standard ;
vc:supports ngm:assistive-technology ;
vc:supports ngm:inclusive-design ;
vc:supports ngm:universal-design ;
vc:supports ngm:web-accessibility-initiative ;
vc:uses ngm:accessible-name-computation ;
vc:uses ngm:alternative-text ;
vc:uses ngm:aria-role ;
vc:uses ngm:aria-state ;
vc:uses ngm:focus-management ;
vc:uses ngm:semantic-html .
ngm:accessible-communication a skos:Concept ;
rdfs:label "Accessible Communication"@en .
ngm:accessible-description a skos:Concept ;
rdfs:label "Accessible Description"@en .
ngm:accessible-design a owl:Class ;
rdfs:comment "Accessible Design is the practice of creating virtual environments and interactions usable by people with diverse disabilities, incorporating universal design principles from conception through implementation."@en ;
rdfs:label "Accessible Design"@en ;
rdfs:subClassOf ngm:inclusive-design ;
rdfs:subClassOf ngm:sc-governance-and-safety ;
rdfs:subClassOf ngm:universal-design ;
rdfs:subClassOf _:r984 ;
rdfs:subClassOf _:r985 ;
rdfs:subClassOf _:r986 ;
skos:broader ngm:sc-governance-and-safety ;
vc:bridgesTo ngm:3-d-user-interface ;
vc:bridgesTo ngm:accessibility-standard ;
vc:bridgesTo ngm:inclusive-design ;
vc:bridgesTo ngm:telecollaboration ;
vc:bridgesTo ngm:universal-design ;
vc:enables ngm:broader-user-base ;
vc:enables ngm:inclusive-participation ;
vc:enables ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:assistive-technology-integration ;
vc:requires ngm:user-research ;
vc:slug "accessible-design" ;
vc:sourceDomain "spatial-computing" .
ngm:accessible-experience a owl:Class ;
rdfs:comment "An Accessible Experience is a virtual environment or application delivering equivalent functionality and engagement to users with disabilities through multimodal access pathways, assistive technology integration, and Accessible Design principles, ensuring feature parity across visual, auditory, motor, and cognitive modalities."@en ;
rdfs:label "Accessible Experience"@en ;
rdfs:subClassOf ngm:inclusive-experience ;
rdfs:subClassOf ngm:sc-governance-and-safety ;
rdfs:subClassOf ngm:sc-interaction ;
rdfs:subClassOf ngm:user-experience ;
rdfs:subClassOf _:r987 ;
rdfs:subClassOf _:r988 ;
rdfs:subClassOf _:r989 ;
skos:broader ngm:sc-governance-and-safety ;
skos:broader ngm:sc-interaction ;
vc:bridgesTo ngm:3-d-user-interface ;
vc:bridgesTo ngm:accessibility-standard ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:bridgesTo ngm:telecollaboration ;
vc:bridgesTo ngm:user-experience ;
vc:contrastsWith ngm:inaccessible-design ;
vc:enables ngm:equitable-engagement ;
vc:enables ngm:inclusive-experience ;
vc:enables ngm:inclusive-participation ;
vc:enables ngm:universal-access ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.7"^^xsd:float ;
vc:relatedTo ngm:cognitive-accessibility ;
vc:relatedTo ngm:screen-reader ;
vc:relatedTo ngm:universal-design ;
vc:requires ngm:accessibility-standard ;
vc:requires ngm:accessible-design ;
vc:requires ngm:alternative-input-methods ;
vc:requires ngm:assistive-technology-support ;
vc:requires ngm:multimodal-ai-architecture-interfaces ;
vc:requires ngm:multimodal-interfaces ;
vc:slug "accessible-experience" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:section-508 ;
vc:standardizedBy ngm:wcag-2-2 ;
vc:supports ngm:metaverse ;
vc:supports ngm:spatial-computing ;
vc:uses ngm:3-d-user-interface ;
vc:uses ngm:eye-tracking ;
vc:uses ngm:voice-input .
ngm:accessible-immersion a skos:Concept ;
rdfs:label "Accessible Immersion"@en .
ngm:accessible-media a skos:Concept ;
rdfs:label "Accessible Media"@en .
ngm:accessible-name a skos:Concept ;
rdfs:label "Accessible Name"@en .
ngm:accessible-name-computation a skos:Concept ;
rdfs:label "Accessible Name Computation"@en .
ngm:accessible-tourism a skos:Concept ;
rdfs:label "Accessible Tourism"@en .
ngm:accessible-xr a skos:Concept ;
rdfs:label "Accessible XR"@en .
ngm:accident-risks a skos:Concept ;
rdfs:label "Accident Risks"@en .
ngm:accidental-exposure a skos:Concept ;
rdfs:label "Accidental Exposure"@en .
ngm:accord-project a skos:Concept ;
rdfs:label "Accord Project"@en .
ngm:accord-project-cicero a skos:Concept ;
rdfs:label "Accord Project Cicero"@en .
ngm:account-abstraction a owl:Class ;
rdfs:comment "A paradigm shift in ereum account architecture standardized through ERC-4337 (March 2023) enabling smart contract wallets with programmable transaction validation logic, decoupled gas payment mechanisms, and flexible account recovery, eliminating the distinction between externally owned accounts ..."@en ;
rdfs:label "Account Abstraction"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf ngm:smart-contract ;
rdfs:subClassOf _:r990 ;
rdfs:subClassOf _:r991 ;
rdfs:subClassOf _:r992 ;
rdfs:subClassOf _:r993 ;
rdfs:subClassOf _:r994 ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:bridgesTo ngm:ai-agent-system ;
vc:dependsOn ngm:bundler-network ;
vc:dependsOn ngm:entrypoint-singleton ;
vc:dependsOn ngm:erc-4337 ;
vc:dependsOn ngm:paymaster-infrastructure ;
vc:enables ngm:account-recovery ;
vc:enables ngm:batch-operations ;
vc:enables ngm:gasless-transactions ;
vc:enables ngm:programmable-validation ;
vc:enables ngm:session-keys ;
vc:enables ngm:social-recovery ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:account-factory ;
vc:hasPart ngm:bundler ;
vc:hasPart ngm:entrypoint-contract ;
vc:hasPart ngm:paymaster-contract ;
vc:hasPart ngm:signature-aggregator ;
vc:hasPart ngm:useroperation ;
vc:implements ngm:account-model ;
vc:implements ngm:erc-4337 ;
vc:implements ngm:gas-sponsorship ;
vc:implements ngm:mempool ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:digital-signature-verification ;
vc:requires ngm:ethereum-smart-contract-platform ;
vc:requires ngm:evm ;
vc:requires ngm:gas-abstraction ;
vc:requires ngm:smart-contract ;
vc:slug "account-abstraction" ;
vc:sourceDomain "blockchain" .
ngm:account-balance-ledger a skos:Concept ;
rdfs:label "Account Balance Ledger"@en .
ngm:account-factory a skos:Concept ;
rdfs:label "Account Factory"@en .
ngm:account-model a owl:Class ;
rdfs:comment "The Account Model is a balance-based ledger paradigm in which each address maintains a persistent balance that is updated in-place when transactions execute. Unlike the UTXO model, accounts hold state across transactions, simplifying smart contract programming while introducing challenges around replay protection and nonce management."@en ;
rdfs:label "Account Model"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf ngm:blockchain-entity ;
rdfs:subClassOf ngm:distributed-data-structure ;
rdfs:subClassOf _:r995 ;
rdfs:subClassOf _:r996 ;
rdfs:subClassOf _:r997 ;
rdfs:subClassOf _:r998 ;
rdfs:subClassOf _:r999 ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:bridgesTo ngm:de-fi ;
vc:bridgesTo ngm:digital-identity ;
vc:contrastsWith ngm:utxo-model ;
vc:dependsOn ngm:merkle-patricia-trie ;
vc:dependsOn ngm:state-root ;
vc:enables ngm:decentralised-application ;
vc:enables ngm:smart-contract ;
vc:enables ngm:token-standard ;
vc:enables ngm:transaction-processing ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:nonce ;
vc:implements ngm:ledger ;
vc:isPartOf ngm:blockchain ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:blockchain-network ;
vc:relatedTo ngm:blockchain-transaction ;
vc:relatedTo ngm:cryptographic-keys ;
vc:relatedTo ngm:double-spending ;
vc:relatedTo ngm:externally-owned-account ;
vc:relatedTo ngm:transaction-fee ;
vc:requires ngm:nonce ;
vc:requires ngm:public-key-cryptography ;
vc:requires ngm:transaction ;
vc:requires ngm:wallet ;
vc:slug "account-model" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:gas-mechanism .
ngm:account-opening a skos:Concept ;
rdfs:label "Account Opening"@en .
ngm:account-recovery a skos:Concept ;
rdfs:label "Account Recovery"@en .
ngm:account-security a skos:Concept ;
rdfs:label "Account Security"@en .
ngm:accountability a owl:Class ;
rdfs:comment "The assignment of clear responsibilities for AI system development, deployment, and outcomes, coupled with mechanisms for oversight, redress, and remediation, ensuring that actors can be held answerable for system impacts and failures."@en ;
rdfs:label "Accountability"@en ;
rdfs:subClassOf ngm:ai-governance ;
rdfs:subClassOf _:r1020 ;
rdfs:subClassOf _:r1021 ;
rdfs:subClassOf _:r1022 ;
rdfs:subClassOf _:r1023 ;
rdfs:subClassOf _:r1024 ;
rdfs:subClassOf _:r1025 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:smart-contract ;
vc:enables ngm:compliance ;
vc:enables ngm:redress-mechanism ;
vc:enables ngm:risk-management ;
vc:enables ngm:trust ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:eu-ai-act-regulatory-instrument ;
vc:implements ngm:gdpr ;
vc:implements ngm:nist-ai-rmf ;
vc:qualityScore "0.7"^^xsd:float ;
vc:relatedTo ngm:ai-audit ;
vc:relatedTo ngm:algorithmic-bias ;
vc:relatedTo ngm:governance-framework ;
vc:requires ngm:audit-trail ;
vc:requires ngm:explainability ;
vc:requires ngm:human-oversight ;
vc:requires ngm:transparency ;
vc:slug "accountability" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:iso-iec-23894-2023 ;
vc:standardizedBy ngm:iso-iec-38500 ;
vc:standardizedBy ngm:oecd-ai-principles ;
vc:supports ngm:ai-trustworthiness ;
vc:supports ngm:fairness ;
vc:supports ngm:safety .
ngm:accountability-ai-0068 a owl:Class ;
rdfs:comment "Accountability (AI-0068) is the principle — codified under ontology reference identifier AI-0068 in structured AI ethics and governance frameworks — requiring that organisations developing, deploying, or operating AI systems must be able to demonstrate traceable, enforceable responsibility for the systems' decisions and impacts, provide redress mechanisms when harm occurs, maintain identifiable human oversight over automated processes, and document the entire lifecycle of AI systems through auditable artefacts. It grounds the ethical aspiration of accountability in specific technical and organisational obligations, distinguishing it from aspirational guidelines by imposing concrete requirements for AI audit trails, explainability outputs, model documentation, incident response procedures, and designated role assignments for liability."@en ;
rdfs:label "Accountability (AI-0068)"@en ;
rdfs:subClassOf ngm:accountability ;
rdfs:subClassOf ngm:ai-ethics ;
rdfs:subClassOf ngm:ai-governance ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:algorithmic-accountability ;
rdfs:subClassOf ngm:governance-framework ;
rdfs:subClassOf ngm:responsible-ai ;
rdfs:subClassOf _:r1000 ;
rdfs:subClassOf _:r1001 ;
rdfs:subClassOf _:r1002 ;
rdfs:subClassOf _:r1003 ;
rdfs:subClassOf _:r1004 ;
rdfs:subClassOf _:r1005 ;
rdfs:subClassOf _:r1006 ;
rdfs:subClassOf _:r1007 ;
rdfs:subClassOf _:r1008 ;
rdfs:subClassOf _:r1009 ;
rdfs:subClassOf _:r1010 ;
rdfs:subClassOf _:r1011 ;
rdfs:subClassOf _:r1012 ;
rdfs:subClassOf _:r1013 ;
rdfs:subClassOf _:r1014 ;
rdfs:subClassOf _:r1015 ;
rdfs:subClassOf _:r1016 ;
rdfs:subClassOf _:r1017 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:contrastsWith ngm:autonomous-decision-making-without-oversight ;
vc:contrastsWith ngm:black-box-ai ;
vc:contrastsWith ngm:opacity ;
vc:dependsOn ngm:ai-audit ;
vc:dependsOn ngm:ai-monitoring ;
vc:dependsOn ngm:data-governance ;
vc:dependsOn ngm:explainable-ai ;
vc:dependsOn ngm:human-oversight ;
vc:dependsOn ngm:transparency ;
vc:enables ngm:ai-governance-framework ;
vc:enables ngm:ai-regulation ;
vc:enables ngm:contestability ;
vc:enables ngm:regulatory-compliance ;
vc:enables ngm:responsible-ai ;
vc:enables ngm:third-party-certification ;
vc:enables ngm:trust ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:ai-audit ;
vc:hasPart ngm:ai-documentation-standards ;
vc:hasPart ngm:ai-impact-assessment ;
vc:hasPart ngm:ai-model-card ;
vc:hasPart ngm:conformity-assessment ;
vc:hasPart ngm:human-oversight ;
vc:hasPart ngm:incident-response ;
vc:hasPart ngm:model-cards ;
vc:hasPart ngm:model-registry ;
vc:hasPart ngm:redress-mechanism ;
vc:implements ngm:eu-ai-act-regulatory-instrument ;
vc:implements ngm:gdpr ;
vc:implements ngm:iso-iec-42001-2023 ;
vc:implements ngm:iso-iec-42005 ;
vc:implements ngm:nist-ai-rmf ;
vc:implements ngm:oecd-ai-principles ;
vc:qualityScore "0.93"^^xsd:float ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:ai-governance-framework ;
vc:relatedTo ngm:ai-regulation ;
vc:relatedTo ngm:ai-risk-management ;
vc:relatedTo ngm:algorithmic-accountability ;
vc:relatedTo ngm:algorithmic-bias ;
vc:relatedTo ngm:fairness-ai ;
vc:relatedTo ngm:liability ;
vc:relatedTo ngm:responsible-ai ;
vc:relatedTo ngm:uk-ai-strategy ;
vc:requires ngm:ai-documentation-standards ;
vc:requires ngm:ai-monitoring ;
vc:requires ngm:algorithmic-bias ;
vc:requires ngm:data-governance ;
vc:requires ngm:explainable-ai ;
vc:requires ngm:human-in-the-loop ;
vc:requires ngm:human-oversight ;
vc:requires ngm:transparency ;
vc:slug "accountability-ai-0068" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:iso-iec-42001-2023 ;
vc:standardizedBy ngm:iso-iec-42005 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:standardizedBy ngm:oecd-ai-principles ;
vc:supports ngm:ai-ethics ;
vc:supports ngm:ai-regulation ;
vc:supports ngm:algorithmic-accountability ;
vc:supports ngm:fairness-ai ;
vc:supports ngm:gdpr ;
vc:supports ngm:human-in-the-loop ;
vc:supports ngm:transparency ;
vc:uses ngm:ai-audit ;
vc:uses ngm:ai-impact-assessment ;
vc:uses ngm:ai-model-card ;
vc:uses ngm:ai-monitoring ;
vc:uses ngm:bias-mitigation-techniques ;
vc:uses ngm:conformity-assessment ;
vc:uses ngm:model-registry .
ngm:accountability-framework a owl:Class ;
rdfs:comment "An accountability framework is a structured set of principles, roles, processes, and controls that together define how responsibility for outcomes is assigned, tracked, and enforced within an organisation or system. It specifies who is answerable for decisions and actions, what evidence of responsible conduct must be maintained, and what redress or corrective measures apply when obligations are unmet. Accountability frameworks appear across governance, AI ethics, financial regulation, and public sector administration."@en ;
rdfs:label "Accountability Framework"@en ;
rdfs:subClassOf ngm:governance-framework ;
rdfs:subClassOf _:r1018 ;
rdfs:subClassOf _:r1019 ;
vc:enables ngm:accountability-mechanism ;
vc:enables ngm:compliance ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:accountability ;
vc:relatedTo ngm:regulatory-framework ;
vc:requires ngm:audit ;
vc:requires ngm:transparency ;
vc:slug "accountability-framework" ;
vc:sourceDomain "governance" .
ngm:accountability-mechanism a owl:Class ;
rdfs:comment "An accountability mechanism is a specific procedural, technical, or institutional instrument through which an actor can be held answerable for their decisions and conduct—for example, an audit trail, an ombudsman process, an algorithmic impact assessment, or a public reporting obligation. Whereas an accountability framework defines the overall structure of responsibility, an accountability mechanism is the concrete tool that makes accountability operational within or across that framework."@en ;
rdfs:label "Accountability Mechanism"@en ;
rdfs:subClassOf ngm:accountability ;
vc:enables ngm:compliance ;
vc:enables ngm:transparency ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:accountability-framework ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:algorithmic-accountability ;
vc:relatedTo ngm:regulatory-framework ;
vc:slug "accountability-mechanism" ;
vc:sourceDomain "governance" ;
vc:uses ngm:audit-log ;
vc:uses ngm:audit-trail .
ngm:accountability-oecd a owl:Class ;
rdfs:comment "Organisations and individuals developing, deploying or operating AI systems should be accountable for their proper functioning in accordance with OECD AI Principles and applicable legal frameworks, based on their roles, context and ability to act."@en ;
rdfs:label "Accountability (OECD)"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:policy-framework ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:ai-agent-system ;
vc:enables ngm:continuous-improvement ;
vc:enables ngm:governance ;
vc:enables ngm:redress-procedure ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:artificial-intelligence ;
vc:slug "accountability-oecd" ;
vc:sourceDomain "artificial-intelligence" .
ngm:accountable-party a owl:Class ;
rdfs:comment "An Accountable Party is an individual, organisation, or role that bears defined responsibility for specific aspects of an AI system's development, deployment, operation, or outcomes, with corresponding obligations to ensure compliance with governance principles, regulatory requirements, and ethical standards. Accountability addresses the foundational question of who bears responsibility when AI systems cause harm or produce unfair outcomes, requiring that identifiable parties possess the authority, resources, and monitoring capacity commensurate with their obligations. Accountable parties span the AI value chain—from data providers and model developers to deploying organisations, system operators, and governance bodies—each with lifecycle-specific duties enforced through formal reporting structures and consequence mechanisms."@en ;
rdfs:label "Accountable Party"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:ai-governance-principle ;
rdfs:subClassOf _:r1026 ;
rdfs:subClassOf _:r1027 ;
rdfs:subClassOf _:r1028 ;
rdfs:subClassOf _:r1029 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:enables ngm:ai-governance ;
vc:enables ngm:compliance-monitoring ;
vc:enables ngm:transparency ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ai-ethics-board ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:ai-regulation ;
vc:relatedTo ngm:audit-trail ;
vc:relatedTo ngm:compliance-control ;
vc:relatedTo ngm:risk-assessment ;
vc:requires ngm:accountability ;
vc:requires ngm:compliance-framework ;
vc:requires ngm:human-oversight ;
vc:slug "accountable-party" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:ai-governance-framework ;
vc:supports ngm:ai-governance-and-ethics ;
vc:supports ngm:governance-framework .
ngm:accreditation a skos:Concept ;
rdfs:label "Accreditation"@en .
ngm:accreditation-body a skos:Concept ;
rdfs:label "Accreditation Body"@en .
ngm:accredited-investor-verification a owl:Class ;
rdfs:comment "Accredited investor verification is the process of confirming that a prospective investor meets the income, net-worth, or professional-knowledge thresholds that securities regulation requires for participation in unregistered or exempt securities offerings, such as many security token issuances. It typically involves documentary evidence or third-party attestation rather than self-certification alone. It is a compliance gate distinct from general know-your-customer identity checks, since it verifies financial eligibility rather than identity."@en ;
rdfs:label "Accredited Investor Verification"@en ;
rdfs:subClassOf ngm:securities-regulation ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:securities-regulation ;
vc:qualityScore "0.6"^^xsd:float ;
vc:slug "accredited-investor-verification" ;
vc:sourceDomain "blockchain" .
ngm:accretion-disc a owl:Class ;
rdfs:label "Accretion Disc"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:black-hole ;
vc:relatedTo ngm:quasar ;
vc:slug "accretion-disc" ;
vc:sourceDomain "space-science-and-systems" .
ngm:accumulation-zone a owl:Class ;
rdfs:label "Accumulation Zone"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-system-phenomena ;
vc:slug "accumulation-zone" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:accuracy a owl:Class ;
rdfs:comment "A classification performance metric representing the proportion of correct predictions made by an artificial intelligence model across all instances in a dataset, calculated as the ratio of the sum of true positives and true negatives to the total number of predictions, providing an aggregate measure of overall model correctness but potentially obscuring performance disparities across classes, particularly in datasets with imbalanced class distributions or asymmetric misclassification costs."@en ;
rdfs:label "Accuracy"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf _:r1030 ;
rdfs:subClassOf _:r1031 ;
rdfs:subClassOf _:r1032 ;
rdfs:subClassOf _:r1033 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:evaluation-metric ;
vc:contrastsWith ngm:f1-score ;
vc:contrastsWith ngm:matthews-correlation-coefficient ;
vc:dependsOn ngm:classification-threshold ;
vc:enables ngm:model-selection ;
vc:enables ngm:performance-monitoring ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:true-negative ;
vc:hasPart ngm:true-positive ;
vc:isPartOf ngm:model-evaluation ;
vc:isPartOf ngm:model-performance ;
vc:qualityScore "0.68"^^xsd:float ;
vc:relatedTo ngm:fairness ;
vc:relatedTo ngm:sensitivity ;
vc:relatedTo ngm:specificity ;
vc:requires ngm:confusion-matrix ;
vc:requires ngm:ground-truth-labels ;
vc:slug "accuracy" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:iso-iec-25059 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:uses ngm:precision ;
vc:uses ngm:recall ;
vc:uses ngm:roc-curve .
ngm:accuracy-metric a skos:Concept ;
rdfs:label "Accuracy Metric"@en .
ngm:accurate-ar-alignment a skos:Concept ;
rdfs:label "Accurate AR Alignment"@en .
ngm:accurate-ar-overlay a skos:Concept ;
rdfs:label "Accurate AR Overlay"@en .
ngm:acid-properties a owl:Class ;
rdfs:comment "ACID Properties are the four guarantees - Atomicity, Consistency, Isolation and Durability - that define a reliable database transaction. Atomicity ensures a transaction is all-or-nothing; Consistency preserves invariants; Isolation hides concurrent intermediate states; and Durability persists committed results across failures. Together they let applications reason about correctness despite concurrency and crashes, distinguishing strongly consistent transactional systems from eventually consistent alternatives."@en ;
rdfs:label "ACID Properties"@en ;
rdfs:subClassOf ngm:transaction ;
rdfs:subClassOf _:r174 ;
rdfs:subClassOf _:r175 ;
rdfs:subClassOf _:r176 ;
rdfs:subClassOf _:r177 ;
vc:contrastsWith ngm:scalability ;
vc:dependsOn ngm:data-persistence ;
vc:dependsOn ngm:write-ahead-logging ;
vc:enables ngm:data-integrity ;
vc:enables ngm:relational-database ;
vc:enables ngm:reliability ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:data-integrity ;
vc:hasPart ngm:fault-tolerance ;
vc:implements ngm:data-integrity ;
vc:implements ngm:reliability ;
vc:isPartOf ngm:transaction ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-persistence ;
vc:relatedTo ngm:distributed-systems ;
vc:relatedTo ngm:transaction ;
vc:requires ngm:two-phase-commit ;
vc:requires ngm:write-ahead-logging ;
vc:slug "acid-properties" ;
vc:sourceDomain "distributed-systems" ;
vc:supports ngm:database-management-system ;
vc:supports ngm:database-systems ;
vc:uses ngm:two-phase-commit .
ngm:acid-transactions a owl:Class ;
rdfs:comment "ACID transactions are units of database work that uphold four guarantees: atomicity, consistency, isolation and durability. Atomicity ensures a transaction either fully completes or has no effect; consistency keeps the database in a valid state; isolation prevents concurrent transactions from interfering; and durability guarantees committed changes survive failures. Together these properties allow reliable, predictable updates to shared data and form the bedrock of relational database systems."@en ;
rdfs:label "Acid Transactions"@en ;
rdfs:subClassOf ngm:database-management-system ;
rdfs:subClassOf _:r1034 ;
rdfs:subClassOf _:r1035 ;
vc:dependsOn ngm:database-management-system ;
vc:dependsOn ngm:write-ahead-logging ;
vc:enables ngm:relational-database ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:two-phase-commit ;
vc:implements ngm:data-integrity ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:centralised-database ;
vc:relatedTo ngm:data ;
vc:requires ngm:database ;
vc:slug "acid-transactions" ;
vc:sourceDomain "data" ;
vc:supports ngm:sql ;
vc:uses ngm:two-phase-commit ;
vc:uses ngm:write-ahead-logging .
ngm:acinq a owl:Class ;
rdfs:comment "ACINQ is a Paris-based Bitcoin technology company specialising in the development and operation of Lightning Network infrastructure, most notably the Eclair Lightning Network node implementation written in Scala and the Phoenix self-custodial mobile Bitcoin wallet. The company operates one of the largest publicly reachable Lightning Network routing nodes, providing significant liquidity and routing capacity to the network. ACINQ contributes to the BOLT (Basis of Lightning Technology) protocol specification process and has pioneered features such as trampoline routing to reduce the on-device computation required by mobile Lightning clients."@en ;
rdfs:label "ACINQ"@en ;
rdfs:subClassOf ngm:lightning-network ;
rdfs:subClassOf _:r178 ;
rdfs:subClassOf _:r179 ;
rdfs:subClassOf _:r180 ;
rdfs:subClassOf _:r181 ;
vc:bridgesTo ngm:de-fi ;
vc:bridgesTo ngm:peer-to-peer-network ;
vc:contrastsWith ngm:core-lightning ;
vc:contrastsWith ngm:lnd ;
vc:enables ngm:micropayment ;
vc:enables ngm:non-custodial-wallet ;
vc:enables ngm:trampoline-routing ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:eclair ;
vc:hasPart ngm:phoenix-wallet ;
vc:implements ngm:lightning-network ;
vc:implements ngm:onion-routing ;
vc:isPartOf ngm:lightning-network ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol-layer-2 ;
vc:relatedTo ngm:bolt-12 ;
vc:relatedTo ngm:bolt12-offers ;
vc:relatedTo ngm:channel-liquidity ;
vc:relatedTo ngm:routing-node ;
vc:requires ngm:bitcoin ;
vc:requires ngm:payment-channel ;
vc:slug "acinq" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:bitcoin-payment ;
vc:supports ngm:splicing ;
vc:uses ngm:htlc ;
vc:uses ngm:onion-routing ;
vc:uses ngm:programming-language .
ngm:acl a owl:Class ;
rdfs:comment "An Access Control List (ACL) is a data structure attached to a resource — such as a file, directory, or network interface — that enumerates which subjects (users, groups, or processes) are permitted to perform which operations on that resource. Each entry in the list is called an Access Control Entry (ACE) and specifies a principal, a set of permissions (read, write, execute, delete), and whether those permissions are granted or denied. ACLs originated in file-system security (POSIX, NTFS) and were subsequently extended to networking, where routers and firewalls use IP-level ACLs to filter packets by source address, destination port, and protocol. In distributed and cloud environments ACLs underpin fine-grained authorisation that complements role-based and attribute-based access-control models."@en ;
rdfs:label "ACL"@en ;
rdfs:subClassOf ngm:access-control ;
vc:contrastsWith ngm:policy-enforcement-point ;
vc:enables ngm:policy-enforcement ;
vc:enables ngm:zero-trust-architecture ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:access-control-system ;
vc:relatedTo ngm:digital-identity ;
vc:relatedTo ngm:identity-and-access-management ;
vc:slug "acl" ;
vc:sourceDomain "security" ;
vc:uses ngm:authentication ;
vc:uses ngm:encryption .
ngm:acl-anthology a skos:Concept ;
rdfs:label "Acl Anthology"@en .
ngm:acm a owl:Class ;
rdfs:comment "The Association for Computing Machinery (ACM) is the world's largest and oldest scientific and educational computing society, founded in 1947, that advances the computing profession through peer-reviewed publication, professional development, and conference organisation. ACM maintains the ACM Digital Library, one of the most comprehensive archives of computing literature, and publishes flagship journals including Communications of the ACM and ACM Transactions series. It confers the ACM Turing Award — widely regarded as computing's highest honour — and promulgates ethical codes of professional conduct. ACM also co-sponsors and organises foundational conferences such as SIGGRAPH, STOC, CCS, and CHI through its network of Special Interest Groups."@en ;
rdfs:label "ACM"@en ;
rdfs:subClassOf ngm:standards-body ;
rdfs:subClassOf _:r182 ;
vc:bridgesTo ngm:artificial-intelligence-research ;
vc:bridgesTo ngm:machine-learning-conferences ;
vc:contrastsWith ngm:british-computer-society ;
vc:contrastsWith ngm:ieee ;
vc:enables ngm:computing-education ;
vc:enables ngm:professional-certification ;
vc:enables ngm:research-dissemination ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:acm-code-of-ethics ;
vc:hasPart ngm:acm-digital-library ;
vc:hasPart ngm:acm-special-interest-group ;
vc:hasPart ngm:acm-turing-award ;
vc:isPartOf ngm:computing-research-community ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:computer-science ;
vc:relatedTo ngm:cybersecurity ;
vc:relatedTo ngm:human-computer-interaction ;
vc:relatedTo ngm:programming-language ;
vc:requires ngm:open-access-publishing ;
vc:requires ngm:peer-review ;
vc:slug "acm" ;
vc:sourceDomain "standards" ;
vc:standardizedBy ngm:acm-curriculum-guidelines ;
vc:supports ngm:computer-science-curriculum ;
vc:supports ngm:diversity-in-computing ;
vc:supports ngm:software-engineering ;
vc:uses ngm:creative-commons ;
vc:uses ngm:doi-system .
ngm:acm-code-of-ethics a skos:Concept ;
rdfs:label "Acm Code Of Ethics"@en .
ngm:acm-computing-classification-system a skos:Concept ;
rdfs:label "Acm Computing Classification System"@en .
ngm:acm-curriculum-guidelines a skos:Concept ;
rdfs:label "Acm Curriculum Guidelines"@en .
ngm:acm-digital-library a skos:Concept ;
rdfs:label "Acm Digital Library"@en .
ngm:acm-sigir a skos:Concept ;
rdfs:label "Acm Sigir"@en .
ngm:acm-special-interest-group a skos:Concept ;
rdfs:label "Acm Special Interest Group"@en .
ngm:acm-tog a skos:Concept ;
rdfs:label "Acm Tog"@en .
ngm:acm-turing-award a skos:Concept ;
rdfs:label "Acm Turing Award"@en .
ngm:acme-protocol a skos:Concept ;
rdfs:label "Acme Protocol"@en .
ngm:acoustic-engineering a skos:Concept ;
rdfs:label "Acoustic Engineering"@en .
ngm:acoustic-environment a skos:Concept ;
rdfs:label "Acoustic Environment"@en .
ngm:acoustic-model a owl:Class ;
rdfs:comment "An Acoustic Model is the component of a speech-recognition system that maps audio signal features to the probability of phonetic or sub-word units. It learns the statistical relationship between observed acoustic features and the linguistic sounds that produced them, traditionally using hidden Markov models with Gaussian mixtures and increasingly using deep neural networks. Combined with a language model, it converts spoken audio into the most likely sequence of words."@en ;
rdfs:label "Acoustic Model"@en ;
rdfs:subClassOf ngm:sequence-model ;
rdfs:subClassOf ngm:speech-recognition ;
rdfs:subClassOf _:r1036 ;
rdfs:subClassOf _:r1037 ;
rdfs:subClassOf _:r1038 ;
rdfs:subClassOf _:r1039 ;
rdfs:subClassOf _:r1040 ;
rdfs:subClassOf _:r1041 ;
vc:contrastsWith ngm:language-model ;
vc:contrastsWith ngm:pronunciation-model ;
vc:dependsOn ngm:expectation-maximisation ;
vc:dependsOn ngm:graphical-model ;
vc:dependsOn ngm:hidden-markov-model ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:speech-processing ;
vc:enables ngm:accessibility ;
vc:enables ngm:automatic-speech-recognition ;
vc:enables ngm:multimodal-ai-architecture ;
vc:enables ngm:voice-user-interface ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:encoder-decoder-architecture ;
vc:hasPart ngm:neural-network ;
vc:hasPart ngm:sequence-model ;
vc:implements ngm:end-to-end-learning ;
vc:implements ngm:pattern-recognition ;
vc:implements ngm:sequence-model ;
vc:isPartOf ngm:speech-recognition ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:audio-processing ;
vc:relatedTo ngm:language-model ;
vc:relatedTo ngm:model-compression ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:noise-robustness ;
vc:relatedTo ngm:quantisation ;
vc:relatedTo ngm:representation-learning ;
vc:relatedTo ngm:speaker-adaptation ;
vc:relatedTo ngm:speaker-diarisation ;
vc:relatedTo ngm:text-to-speech ;
vc:relatedTo ngm:transfer-learning ;
vc:requires ngm:audio-signal-processing ;
vc:requires ngm:feature-extraction ;
vc:requires ngm:mel-frequency-cepstral-coefficients ;
vc:requires ngm:signal-processing ;
vc:slug "acoustic-model" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:nist ;
vc:supports ngm:accessibility-technology ;
vc:supports ngm:automatic-speech-recognition ;
vc:supports ngm:speaker-diarisation ;
vc:uses ngm:attention-mechanism ;
vc:uses ngm:beam-search ;
vc:uses ngm:connectionist-temporal-classification ;
vc:uses ngm:convolutional-neural-network ;
vc:uses ngm:data-augmentation ;
vc:uses ngm:deep-learning ;
vc:uses ngm:pattern-recognition ;
vc:uses ngm:recurrent-neural-network ;
vc:uses ngm:self-supervised-learning ;
vc:uses ngm:transformer .
ngm:acoustic-properties a skos:Concept ;
rdfs:label "Acoustic Properties"@en .
ngm:acoustic-realism a skos:Concept ;
rdfs:label "Acoustic Realism"@en .
ngm:acoustic-sensing a skos:Concept ;
rdfs:label "Acoustic Sensing"@en .
ngm:acp-protocol a skos:Concept ;
rdfs:label "Acp Protocol"@en .
ngm:acqui-hire a skos:Concept ;
rdfs:label "Acqui Hire"@en .
ngm:acquisition-function a owl:Class ;
rdfs:comment "An acquisition function is a utility function used in Bayesian optimisation that determines which point in the input space to evaluate next by balancing exploration of uncertain regions against exploitation of known promising areas. It transforms the surrogate model's posterior distribution into a scalar score, guiding the sequential selection of experiments or evaluations. Common forms include Expected Improvement, Upper Confidence Bound, and Probability of Improvement."@en ;
rdfs:label "Acquisition Function"@en ;
rdfs:subClassOf ngm:black-box-optimisation ;
rdfs:subClassOf ngm:optimisation-algorithm ;
rdfs:subClassOf _:r1042 ;
rdfs:subClassOf _:r1043 ;
rdfs:subClassOf _:r1044 ;
rdfs:subClassOf _:r1045 ;
vc:contrastsWith ngm:gradient-descent ;
vc:contrastsWith ngm:grid-search ;
vc:contrastsWith ngm:random-search ;
vc:dependsOn ngm:bayesian-inference ;
vc:dependsOn ngm:monte-carlo ;
vc:dependsOn ngm:probabilistic-model ;
vc:enables ngm:auto-ml ;
vc:enables ngm:bayesian-optimisation ;
vc:enables ngm:drug-discovery ;
vc:enables ngm:experimental-design ;
vc:enables ngm:hyperparameter-tuning ;
vc:enables ngm:multi-objective-optimisation ;
vc:enables ngm:neural-architecture-search ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:expected-improvement ;
vc:hasPart ngm:thompson-sampling ;
vc:hasPart ngm:upper-confidence-bound ;
vc:implements ngm:exploration-exploitation-tradeoff ;
vc:implements ngm:regret-minimisation ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:active-learning ;
vc:relatedTo ngm:bandit-algorithm ;
vc:relatedTo ngm:exploration-exploitation-tradeoff ;
vc:relatedTo ngm:hyperparameter ;
vc:relatedTo ngm:information-theory ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:optimality ;
vc:relatedTo ngm:reinforcement-learning ;
vc:relatedTo ngm:transfer-learning ;
vc:relatedTo ngm:trust-region-method ;
vc:requires ngm:gaussian-process ;
vc:requires ngm:kernel-function ;
vc:requires ngm:probabilistic-inference ;
vc:requires ngm:surrogate-model ;
vc:slug "acquisition-function" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:botorch ;
vc:supports ngm:auto-ml ;
vc:supports ngm:machine-learning-discipline ;
vc:supports ngm:material-science ;
vc:supports ngm:protein-engineering ;
vc:supports ngm:robotics ;
vc:uses ngm:bayesian-inference ;
vc:uses ngm:deep-kernel-learning ;
vc:uses ngm:gaussian-process ;
vc:uses ngm:kernel-function ;
vc:uses ngm:monte-carlo ;
vc:uses ngm:probabilistic-model ;
vc:uses ngm:variance-reduction .
ngm:across-protocol a owl:Class ;
rdfs:comment "Across Protocol is a decentralised cross-chain bridging protocol that uses an optimistic verification model and a network of liquidity providers—called relayers—to enable fast, capital-efficient transfers of ERC-20 tokens between Ethereum mainnet and Layer 2 networks such as Optimism, Arbitrum, and Polygon. Relayers front user funds immediately on the destination chain and are reimbursed from a liquidity pool on Ethereum after an optimistic challenge period, creating a bridge architecture that prioritises speed and low fees over trustless finality."@en ;
rdfs:label "Across Protocol"@en ;
rdfs:subClassOf ngm:cross-chain-bridge ;
vc:dependsOn ngm:ethereum-smart-contract-platform ;
vc:dependsOn ngm:layer-2-solutions ;
vc:enables ngm:cross-chain-asset-transfer ;
vc:enables ngm:cross-chain-interoperability ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:interoperability-protocol ;
vc:slug "across-protocol" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:liquidity-pool ;
vc:uses ngm:liquidity-provider .
ngm:act-only-agent a skos:Concept ;
rdfs:label "Act Only Agent"@en .
ngm:act-r a skos:Concept ;
rdfs:label "Act R"@en .
ngm:action-chunking-transformer a skos:Concept ;
rdfs:label "Action Chunking Transformer"@en .
ngm:action-embedding a skos:Concept ;
rdfs:label "Action Embedding"@en .
ngm:action-execution a skos:Concept ;
rdfs:label "Action Execution"@en .
ngm:action-executor a owl:Class ;
rdfs:comment "An Action Executor is a software component within an agentic AI system responsible for translating high-level instructions or plans into concrete, observable operations in an environment. It serves as the effector layer that bridges planning and execution by dispatching tool calls, API requests, file operations, or process invocations. Action Executors typically implement sandboxing, retry logic, and side-effect isolation to ensure safe and predictable operation. They are central to autonomous agent architectures where multiple sequential or parallel actions must be managed reliably."@en ;
rdfs:label "Action Executor"@en ;
rdfs:subClassOf ngm:agentic-ai ;
rdfs:subClassOf ngm:ai-agent-system ;
rdfs:subClassOf ngm:autonomous-agent ;
rdfs:subClassOf _:r1046 ;
rdfs:subClassOf _:r1047 ;
rdfs:subClassOf _:r1048 ;
rdfs:subClassOf _:r1049 ;
rdfs:subClassOf _:r1050 ;
rdfs:subClassOf _:r1051 ;
rdfs:subClassOf _:r1052 ;
rdfs:subClassOf _:r1053 ;
rdfs:subClassOf _:r1054 ;
rdfs:subClassOf _:r1055 ;
rdfs:subClassOf _:r1056 ;
rdfs:subClassOf _:r1057 ;
rdfs:subClassOf _:r1058 ;
vc:contrastsWith ngm:automated-planning ;
vc:contrastsWith ngm:behaviour-tree ;
vc:contrastsWith ngm:reinforcement-learning ;
vc:dependsOn ngm:agent-runtime ;
vc:dependsOn ngm:large-language-models ;
vc:dependsOn ngm:memory-management ;
vc:dependsOn ngm:orchestration ;
vc:dependsOn ngm:orchestration-layer ;
vc:dependsOn ngm:security-architecture ;
vc:enables ngm:agentic-workflow ;
vc:enables ngm:automated-planning ;
vc:enables ngm:autonomous-task-execution ;
vc:enables ngm:code-execution ;
vc:enables ngm:multi-agent-systems ;
vc:enables ngm:multi-step-reasoning ;
vc:enables ngm:retrieval-augmented-generation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:agent-event-stream ;
vc:hasPart ngm:argument-validator ;
vc:hasPart ngm:audit-log ;
vc:hasPart ngm:error-handling ;
vc:hasPart ngm:observability-emitter ;
vc:hasPart ngm:retry-policy ;
vc:hasPart ngm:sandbox-environment ;
vc:hasPart ngm:tool-schema ;
vc:implements ngm:agent-loop ;
vc:implements ngm:least-privilege-principle ;
vc:implements ngm:model-context-protocol ;
vc:implements ngm:planning-and-scheduling ;
vc:implements ngm:re-act-pattern ;
vc:qualityScore "0.88"^^xsd:float ;
vc:relatedTo ngm:action-space ;
vc:relatedTo ngm:agent ;
vc:relatedTo ngm:agent-communication-protocol ;
vc:relatedTo ngm:agent-frameworks ;
vc:relatedTo ngm:agent-orchestrator ;
vc:relatedTo ngm:auto-gen ;
vc:relatedTo ngm:aws-bedrock ;
vc:relatedTo ngm:crew-ai ;
vc:relatedTo ngm:google-vertex-ai ;
vc:relatedTo ngm:lang-graph ;
vc:relatedTo ngm:model-context-protocol ;
vc:relatedTo ngm:re-act-pattern ;
vc:relatedTo ngm:task-planning ;
vc:requires ngm:agent-loop ;
vc:requires ngm:function-calling ;
vc:requires ngm:json-data-interchange-format-schema ;
vc:requires ngm:orchestration ;
vc:requires ngm:runtime-environment ;
vc:requires ngm:tool-registry ;
vc:requires ngm:tool-schema ;
vc:requires ngm:tool-use ;
vc:slug "action-executor" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:agent-communication-protocol ;
vc:standardizedBy ngm:json-data-interchange-format-schema ;
vc:standardizedBy ngm:model-context-protocol ;
vc:supports ngm:cloud-native ;
vc:supports ngm:digital-infrastructure ;
vc:supports ngm:human-oversight ;
vc:supports ngm:multi-agent-orchestration ;
vc:supports ngm:multi-agent-systems ;
vc:supports ngm:observability ;
vc:uses ngm:agent-communication-protocol ;
vc:uses ngm:chain-of-thought ;
vc:uses ngm:containerisation ;
vc:uses ngm:error-handling ;
vc:uses ngm:json-data-interchange-format-schema ;
vc:uses ngm:large-language-models ;
vc:uses ngm:model-context-protocol ;
vc:uses ngm:orchestration ;
vc:uses ngm:prompt-engineering ;
vc:uses ngm:sandbox-environment .
ngm:action-factorisation a skos:Concept ;
rdfs:label "Action Factorisation"@en .
ngm:action-item-extraction a skos:Concept ;
rdfs:label "Action Item Extraction"@en .
ngm:action-masking a skos:Concept ;
rdfs:label "Action Masking"@en .
ngm:action-model a skos:Concept ;
rdfs:label "Action Model"@en .
ngm:action-node a skos:Concept ;
rdfs:label "Action Node"@en .
ngm:action-potential-recording a skos:Concept ;
rdfs:label "Action Potential Recording"@en .
ngm:action-recognition a owl:Class ;
rdfs:comment "Action Recognition is a computer-vision task that classifies the activity being performed by one or more agents from video or motion-sequence data. Models ingest spatiotemporal features, often built on detected body keypoints or 3D convolutions and transformers, to label actions such as walking, waving, or falling. It underpins applications in surveillance, sports analytics, human-robot interaction, and assistive monitoring."@en ;
rdfs:label "Action Recognition"@en ;
rdfs:subClassOf ngm:computer-vision ;
rdfs:subClassOf ngm:computer-vision-task ;
rdfs:subClassOf ngm:video-understanding ;
rdfs:subClassOf _:r1059 ;
rdfs:subClassOf _:r1060 ;
rdfs:subClassOf _:r1061 ;
rdfs:subClassOf _:r1062 ;
rdfs:subClassOf _:r1063 ;
rdfs:subClassOf _:r1064 ;
rdfs:subClassOf _:r1065 ;
rdfs:subClassOf _:r1066 ;
vc:contrastsWith ngm:gesture-recognition ;
vc:contrastsWith ngm:image-classification ;
vc:contrastsWith ngm:object-detection ;
vc:dependsOn ngm:attention-mechanism ;
vc:dependsOn ngm:deep-learning-framework ;
vc:dependsOn ngm:foundation-model ;
vc:dependsOn ngm:multimodal-ai-architecture-ai ;
vc:dependsOn ngm:multimodal-ai-architecture-learning ;
vc:dependsOn ngm:self-supervised-learning ;
vc:enables ngm:activity-data ;
vc:enables ngm:autonomous-vehicle ;
vc:enables ngm:behavioural-analytics ;
vc:enables ngm:fall-detection ;
vc:enables ngm:gesture-interface ;
vc:enables ngm:human-computer-interaction ;
vc:enables ngm:human-robot-interaction ;
vc:enables ngm:sports-analytics ;
vc:enables ngm:surveillance ;
vc:enables ngm:wearable-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:benchmark-dataset ;
vc:hasPart ngm:optical-flow ;
vc:hasPart ngm:pose-estimation ;
vc:hasPart ngm:skeleton-graph ;
vc:hasPart ngm:spatiotemporal-feature-extractor ;
vc:hasPart ngm:temporal-action-detection ;
vc:hasPart ngm:temporal-sampler ;
vc:implements ngm:attention-mechanism ;
vc:implements ngm:convolutional-neural-network ;
vc:implements ngm:graph-neural-network ;
vc:implements ngm:lstm ;
vc:implements ngm:self-supervised-learning ;
vc:implements ngm:transformer-architecture ;
vc:qualityScore "0.88"^^xsd:float ;
vc:relatedTo ngm:action-space ;
vc:relatedTo ngm:behavioural-analytics ;
vc:relatedTo ngm:computer-vision-video-analysis ;
vc:relatedTo ngm:explainable-ai ;
vc:relatedTo ngm:gesture-recognition ;
vc:relatedTo ngm:human-capture-and-recognition ;
vc:relatedTo ngm:motion-capture ;
vc:relatedTo ngm:multimodal-ai ;
vc:relatedTo ngm:multimodal-ai-architecture-ai ;
vc:relatedTo ngm:pose-estimation ;
vc:relatedTo ngm:sports-analytics ;
vc:relatedTo ngm:wearable-computing ;
vc:requires ngm:benchmark-dataset ;
vc:requires ngm:deep-learning ;
vc:requires ngm:motion-tracking ;
vc:requires ngm:neural-network ;
vc:requires ngm:pose-estimation ;
vc:requires ngm:temporal-modelling ;
vc:requires ngm:video-data ;
vc:slug "action-recognition" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:iso-iec-22989-2022 ;
vc:supports ngm:activity-data ;
vc:supports ngm:autonomous-vehicle ;
vc:supports ngm:human-capture-and-recognition ;
vc:supports ngm:human-robot-interaction ;
vc:supports ngm:robotics ;
vc:supports ngm:robotics-perception ;
vc:supports ngm:wearable-computing ;
vc:uses ngm:convolutional-neural-network ;
vc:uses ngm:foundation-model ;
vc:uses ngm:graph-neural-network ;
vc:uses ngm:lstm ;
vc:uses ngm:motion-capture ;
vc:uses ngm:motion-tracking ;
vc:uses ngm:multimodal-ai-architecture-learning ;
vc:uses ngm:optical-flow ;
vc:uses ngm:self-supervised-learning ;
vc:uses ngm:transformer-architecture .
ngm:action-schema a skos:Concept ;
rdfs:label "Action Schema"@en .
ngm:action-selection a skos:Concept ;
rdfs:label "Action Selection"@en .
ngm:action-space a owl:Class ;
rdfs:comment "The action space in reinforcement learning and control theory is the complete set of actions available to an agent at any given decision step, defining the boundaries of what the agent may do when interacting with its environment. It may be discrete—a finite enumeration of choices—or continuous—a real-valued manifold such as joint torques or steering angles—and its structure fundamentally determines which learning algorithms are applicable and how efficiently a policy can be discovered."@en ;
rdfs:label "Action Space"@en ;
rdfs:subClassOf ngm:control-theory ;
rdfs:subClassOf ngm:markov-decision-process ;
rdfs:subClassOf ngm:optimisation ;
rdfs:subClassOf ngm:state-space ;
rdfs:subClassOf _:r1067 ;
rdfs:subClassOf _:r1068 ;
rdfs:subClassOf _:r1069 ;
rdfs:subClassOf _:r1070 ;
rdfs:subClassOf _:r1071 ;
rdfs:subClassOf _:r1072 ;
vc:contrastsWith ngm:curriculum-learning ;
vc:contrastsWith ngm:inverse-reinforcement-learning ;
vc:contrastsWith ngm:transfer-learning ;
vc:dependsOn ngm:environment-model ;
vc:dependsOn ngm:gpu-acceleration ;
vc:dependsOn ngm:neural-network ;
vc:dependsOn ngm:simulation-environment ;
vc:enables ngm:autonomous-robot ;
vc:enables ngm:combinatorial-optimisation ;
vc:enables ngm:deep-reinforcement-learning ;
vc:enables ngm:hierarchical-reinforcement-learning ;
vc:enables ngm:multi-agent-reinforcement-learning ;
vc:enables ngm:policy-optimisation ;
vc:enables ngm:reinforcement-learning-algorithm ;
vc:enables ngm:safe-reinforcement-learning ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:action-embedding ;
vc:hasPart ngm:action-factorisation ;
vc:hasPart ngm:action-masking ;
vc:hasPart ngm:continuous-action ;
vc:hasPart ngm:discrete-action ;
vc:hasPart ngm:exploration-exploitation ;
vc:hasPart ngm:parameterised-action ;
vc:hasPart ngm:policy-gradient-methods ;
vc:hasPart ngm:value-function ;
vc:implements ngm:control-theory ;
vc:implements ngm:deep-learning ;
vc:implements ngm:model-based-reinforcement-learning ;
vc:implements ngm:reinforcement-learning ;
vc:qualityScore "0.87"^^xsd:float ;
vc:relatedTo ngm:computer-vision ;
vc:relatedTo ngm:control-theory ;
vc:relatedTo ngm:deep-reinforcement-learning ;
vc:relatedTo ngm:domain-randomisation ;
vc:relatedTo ngm:exploration-exploitation ;
vc:relatedTo ngm:hierarchical-reinforcement-learning ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:markov-decision-process ;
vc:relatedTo ngm:multi-agent-reinforcement-learning ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:reinforcement-learning ;
vc:relatedTo ngm:reinforcement-learning-from-human-feedback ;
vc:relatedTo ngm:reward-function ;
vc:relatedTo ngm:reward-shaping ;
vc:relatedTo ngm:sample-efficiency ;
vc:relatedTo ngm:state-space ;
vc:relatedTo ngm:transfer-learning ;
vc:requires ngm:environment-model ;
vc:requires ngm:markov-decision-process ;
vc:requires ngm:reward-function ;
vc:requires ngm:simulation-environment ;
vc:requires ngm:transition-dynamics ;
vc:slug "action-space" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:gymnasium ;
vc:standardizedBy ngm:markov-decision-process ;
vc:supports ngm:agentic-ai ;
vc:supports ngm:autonomous-vehicle ;
vc:supports ngm:combinatorial-optimisation ;
vc:supports ngm:game-ai ;
vc:supports ngm:large-language-models ;
vc:supports ngm:natural-language-processing ;
vc:supports ngm:reinforcement-learning-for-robotics ;
vc:uses ngm:graph-neural-network ;
vc:uses ngm:neural-network ;
vc:uses ngm:policy-gradient-methods ;
vc:uses ngm:proximal-policy-optimisation ;
vc:uses ngm:reinforcement-learning-for-robotics ;
vc:uses ngm:reward-function ;
vc:uses ngm:temporal-difference ;
vc:uses ngm:value-function .
ngm:action-unit a skos:Concept ;
rdfs:label "Action Unit"@en .
ngm:activation-function a owl:Class ;
rdfs:comment "An Activation Function is a non-linear mathematical transformation applied to a neuron's weighted input sum, enabling neural networks to learn complex, non-linear mappings. Common variants include Sigmoid, Tanh, ReLU, Leaky ReLU, and GELU; the choice of activation function critically affects gradient flow, convergence speed, and model expressivity."@en ;
rdfs:label "Activation Function"@en ;
rdfs:subClassOf ngm:neural-network-component ;
rdfs:subClassOf _:r1073 ;
rdfs:subClassOf _:r1074 ;
vc:bridgesTo ngm:neuromorphic-computing ;
vc:bridgesTo ngm:quantum-neural-network ;
vc:dependsOn ngm:neuron ;
vc:enables ngm:deep-learning ;
vc:enables ngm:feature-learning ;
vc:enables ngm:universal-approximation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:nonlinearity ;
vc:isPartOf ngm:feedforward-neural-network ;
vc:isPartOf ngm:neural-network ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:batch-normalisation ;
vc:relatedTo ngm:neural-network-layer ;
vc:relatedTo ngm:vanishing-gradient ;
vc:relatedTo ngm:weight-initialisation ;
vc:requires ngm:backpropagation ;
vc:requires ngm:differentiability ;
vc:slug "activation-function" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:iso-iec-22989-2022 ;
vc:standardizedBy ngm:onnx ;
vc:supports ngm:convolutional-neural-network ;
vc:supports ngm:recurrent-neural-network ;
vc:supports ngm:transformer-architecture ;
vc:uses ngm:gradient-descent .
ngm:activation-patching a skos:Concept ;
rdfs:label "Activation Patching"@en .
ngm:activation-recomputation a skos:Concept ;
rdfs:label "Activation Recomputation"@en .
ngm:active-directory a skos:Concept ;
rdfs:label "Active Directory"@en .
ngm:active-earth-observation-sensor a owl:Class ;
rdfs:label "Active Earth Observation Sensor"@en ;
rdfs:subClassOf ngm:earth-observation-sensor ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:active-remote-sensing ;
vc:slug "active-earth-observation-sensor" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:active-galactic-nucleus a owl:Class ;
rdfs:label "Active Galactic Nucleus"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:black-hole ;
vc:relatedTo ngm:quasar ;
vc:slug "active-galactic-nucleus" ;
vc:sourceDomain "space-science-and-systems" .
ngm:active-inference a skos:Concept ;
rdfs:label "Active Inference"@en .
ngm:active-learning a owl:Class ;
rdfs:comment "Machine learning paradigm where algorithms actively select which unlabeled examples from large data pools to query for human annotation rather than passively accepting randomly labeled datasets, optimizing informativeness through query strategies (uncertainty sampling selecting least-confident pr..."@en ;
rdfs:label "Active Learning"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:data-efficient-learning ;
rdfs:subClassOf ngm:human-in-the-loop-learning ;
rdfs:subClassOf ngm:interactive-learning ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf ngm:supervised-learning ;
rdfs:subClassOf _:r1075 ;
rdfs:subClassOf _:r1076 ;
rdfs:subClassOf _:r1077 ;
rdfs:subClassOf _:r1078 ;
rdfs:subClassOf _:r1079 ;
rdfs:subClassOf _:r1080 ;
rdfs:subClassOf _:r1081 ;
rdfs:subClassOf _:r1082 ;
rdfs:subClassOf _:r1083 ;
rdfs:subClassOf _:r1084 ;
skos:broader ngm:ai-technique ;
vc:dependsOn ngm:information-theory ;
vc:dependsOn ngm:pac-learning-theory ;
vc:dependsOn ngm:statistical-learning-theory ;
vc:dependsOn ngm:uncertainty-quantification ;
vc:dependsOn ngm:version-space-learning ;
vc:enables ngm:data-annotation ;
vc:enables ngm:data-efficient-learning ;
vc:enables ngm:expert-knowledge-elicitation ;
vc:enables ngm:rapid-prototyping ;
vc:enables ngm:sample-complexity-reduction ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:acquisition-function ;
vc:hasPart ngm:blockchain-oracle ;
vc:hasPart ngm:diversity-measure ;
vc:hasPart ngm:early-stopping ;
vc:hasPart ngm:label-budget ;
vc:hasPart ngm:query-strategy ;
vc:hasPart ngm:unlabeled-data-pool ;
vc:implements ngm:density-weighted-methods ;
vc:implements ngm:expected-error-reduction ;
vc:implements ngm:expected-model-change ;
vc:implements ngm:query-by-committee ;
vc:implements ngm:sampling ;
vc:implements ngm:variance-reduction ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:base-learner ;
vc:requires ngm:evaluation-metric ;
vc:requires ngm:oracle ;
vc:requires ngm:query-selection-algorithm ;
vc:requires ngm:unlabeled-data ;
vc:slug "active-learning" ;
vc:sourceDomain "artificial-intelligence" .
ngm:active-matter-physics a skos:Concept ;
rdfs:label "Active Matter Physics"@en .
ngm:active-metadata a skos:Concept ;
rdfs:label "Active Metadata"@en .
ngm:active-perception a skos:Concept ;
rdfs:label "Active Perception"@en .
ngm:active-queue-management a skos:Concept ;
rdfs:label "Active Queue Management"@en .
ngm:active-r-d-funding-opportunities-register a owl:Class ;
rdfs:comment "A curated register of active and accessible funding opportunities for immersive technology, AI, and creative industries R&D, encompassing Innovate UK grants, UKRI programmes, ARIA challenges, Web3 venture capital, and academic grant schemes. The register tracks application status, eligibility constraints, match-funding requirements, and strategic alignment to accelerate project funding decisions."@en ;
rdfs:label "Active R&D Funding Opportunities Register"@en ;
rdfs:subClassOf ngm:resource-management ;
rdfs:subClassOf ngm:software-engineering ;
vc:enables ngm:ai-agent-system ;
vc:enables ngm:immersive-technology ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:extended-reality ;
vc:relatedTo ngm:resource-management ;
vc:slug "active-r-d-funding-opportunities-register" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:agentic-ai ;
vc:supports ngm:knowledge-graph .
ngm:active-record a skos:Concept ;
rdfs:label "Active Record"@en .
ngm:active-remote-sensing a owl:Class ;
rdfs:label "Active Remote Sensing"@en ;
rdfs:subClassOf ngm:remote-sensing ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation ;
vc:slug "active-remote-sensing" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:active-research-projects-registry a owl:Class ;
rdfs:comment "An Active Research Projects Registry is a structured, queryable catalogue that maintains authoritative records of ongoing research initiatives, development workstreams, and collaborative projects within an organisation or knowledge graph, capturing metadata such as status, ownership, objectives, dependencies, and timelines. It serves as a single source of truth for portfolio governance, enabling stakeholders to discover, track, and coordinate active work without duplicating effort or losing context across distributed teams. Unlike a static document index, a living registry integrates with project management workflows, version control systems, and knowledge management platforms to reflect real-time project state. It supports prioritisation, resource allocation, and strategic alignment by surfacing the relationships between concurrent initiatives and shared infrastructure."@en ;
rdfs:label "Active Research Projects Registry"@en ;
rdfs:subClassOf ngm:data-registry ;
rdfs:subClassOf _:r1085 ;
rdfs:subClassOf _:r1086 ;
rdfs:subClassOf _:r1087 ;
rdfs:subClassOf _:r1088 ;
rdfs:subClassOf _:r1089 ;
rdfs:subClassOf _:r1090 ;
vc:bridgesTo ngm:fair-data-principles ;
vc:bridgesTo ngm:open-data ;
vc:contrastsWith ngm:data-catalog ;
vc:contrastsWith ngm:empirical-experimental-design-tracking ;
vc:enables ngm:automated-planning ;
vc:enables ngm:collaboration ;
vc:enables ngm:knowledge-management ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:applied-ai-research-portfolio ;
vc:hasPart ngm:knowledge-graph-kanban-board ;
vc:hasPart ngm:project-management ;
vc:isPartOf ngm:knowledge-management-system ;
vc:qualityScore "0.68"^^xsd:float ;
vc:relatedTo ngm:agentic-workflow ;
vc:relatedTo ngm:collaboration-platform ;
vc:relatedTo ngm:knowledge-graph-publication-classifier ;
vc:requires ngm:data-governance ;
vc:requires ngm:metadata-management ;
vc:requires ngm:version-control ;
vc:slug "active-research-projects-registry" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:ai-augmented-research-tooling-suite ;
vc:supports ngm:decentralised-agent-coordination-initiative ;
vc:uses ngm:agile-software-development ;
vc:uses ngm:data-catalog ;
vc:uses ngm:knowledge-graph .
ngm:active-thermal-control a owl:Class ;
rdfs:label "Active Thermal Control"@en ;
rdfs:subClassOf ngm:spacecraft-thermal-control ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:spacecraft-power-and-thermal-control ;
vc:slug "active-thermal-control" ;
vc:sourceDomain "space-science-and-systems" .
ngm:activity-data a owl:Class ;
rdfs:comment "Activity data is the structured or semi-structured record of actions, interactions, and events performed by users, devices, or systems over time, capturing what was done, when, by whom, and in what context. It encompasses clickstreams, application usage logs, sensor readings, transaction histories, and learning interaction records, and serves as the raw material for analytics, personalisation, compliance auditing, and behavioural modelling."@en ;
rdfs:label "Activity Data"@en ;
rdfs:subClassOf ngm:behavioural-analytics ;
rdfs:subClassOf ngm:data-collection ;
rdfs:subClassOf ngm:event-sourcing ;
rdfs:subClassOf ngm:time-series-analysis ;
rdfs:subClassOf _:r1091 ;
rdfs:subClassOf _:r1092 ;
rdfs:subClassOf _:r1093 ;
rdfs:subClassOf _:r1094 ;
rdfs:subClassOf _:r1095 ;
rdfs:subClassOf _:r1096 ;
rdfs:subClassOf _:r1097 ;
rdfs:subClassOf _:r1098 ;
rdfs:subClassOf _:r1099 ;
vc:contrastsWith ngm:differential-privacy ;
vc:contrastsWith ngm:profile-data ;
vc:contrastsWith ngm:synthetic-data ;
vc:dependsOn ngm:data-lake ;
vc:dependsOn ngm:data-pipeline ;
vc:dependsOn ngm:event-driven-architecture ;
vc:dependsOn ngm:stream-processing ;
vc:dependsOn ngm:tracking-system ;
vc:enables ngm:ai-audit ;
vc:enables ngm:analytics-engine ;
vc:enables ngm:anomaly-detection ;
vc:enables ngm:audit-log ;
vc:enables ngm:behavioural-analytics ;
vc:enables ngm:collaborative-systems-modality-filtering ;
vc:enables ngm:digital-twin ;
vc:enables ngm:fraud-detection ;
vc:enables ngm:knowledge-graph ;
vc:enables ngm:observability ;
vc:enables ngm:personalisation ;
vc:enables ngm:recommendation-system ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:agent-action-log ;
vc:hasPart ngm:audit-log ;
vc:hasPart ngm:audit-trail ;
vc:hasPart ngm:clickstream ;
vc:hasPart ngm:event-record ;
vc:hasPart ngm:sensor-telemetry ;
vc:hasPart ngm:session-recording ;
vc:hasPart ngm:transaction-log ;
vc:implements ngm:compliance ;
vc:implements ngm:data-governance ;
vc:implements ngm:data-minimisation ;
vc:implements ngm:observability ;
vc:implements ngm:open-telemetry ;
vc:implements ngm:purpose-limitation ;
vc:implements ngm:xapi ;
vc:qualityScore "0.87"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:ai-audit ;
vc:relatedTo ngm:audit-log ;
vc:relatedTo ngm:compliance ;
vc:relatedTo ngm:data-governance ;
vc:relatedTo ngm:data-minimisation ;
vc:relatedTo ngm:data-protection-regulation ;
vc:relatedTo ngm:learning-management-system ;
vc:relatedTo ngm:privacy ;
vc:relatedTo ngm:purpose-limitation ;
vc:relatedTo ngm:reinforcement-learning-from-human-feedback ;
vc:relatedTo ngm:time-series-analysis ;
vc:relatedTo ngm:transparency ;
vc:requires ngm:data-lake ;
vc:requires ngm:data-pipeline ;
vc:requires ngm:event-driven-architecture ;
vc:requires ngm:stream-processing ;
vc:requires ngm:telemetry-and-analytics ;
vc:requires ngm:tracking-system ;
vc:slug "activity-data" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:data-protection-regulation ;
vc:standardizedBy ngm:iso-27001 ;
vc:standardizedBy ngm:open-telemetry ;
vc:standardizedBy ngm:xapi ;
vc:supports ngm:agentic-ai ;
vc:supports ngm:anomaly-detection ;
vc:supports ngm:digital-twin ;
vc:supports ngm:explainable-ai ;
vc:supports ngm:feature-engineering ;
vc:supports ngm:fraud-detection ;
vc:supports ngm:machine-learning-discipline-pipeline ;
vc:supports ngm:reinforcement-learning-from-human-feedback ;
vc:uses ngm:analytics-engine ;
vc:uses ngm:data-pipeline ;
vc:uses ngm:differential-privacy ;
vc:uses ngm:open-telemetry ;
vc:uses ngm:stream-processing ;
vc:uses ngm:synthetic-data ;
vc:uses ngm:telemetry-and-analytics ;
vc:uses ngm:tracking-system ;
vc:uses ngm:xapi .
ngm:activity-logging a skos:Concept ;
rdfs:label "Activity Logging"@en .
ngm:activity-model a skos:Concept ;
rdfs:label "Activity Model"@en .
ngm:activity-monitor a skos:Concept ;
rdfs:label "Activity Monitor"@en .
ngm:activity-monitoring a skos:Concept ;
rdfs:label "Activity Monitoring"@en .
ngm:activity-pub a owl:Class ;
rdfs:comment "ActivityPub is a W3C-standardised decentralised social networking protocol that defines two layers: a server-to-server federation protocol enabling independent server instances to share content with one another, and a client-to-server protocol allowing applications to interact with a user's social data. Based on the ActivityStreams 2.0 vocabulary and JSON-LD serialisation, it enables interoperable federated social networks where users on different server instances can follow, reply to, and interact with each other across instance boundaries."@en ;
rdfs:label "ActivityPub"@en ;
rdfs:subClassOf ngm:distributed-protocol ;
rdfs:subClassOf _:r1100 ;
vc:bridgesTo ngm:decentralised-identity ;
vc:bridgesTo ngm:ipfs ;
vc:contrastsWith ngm:at-protocol ;
vc:enables ngm:content-moderation ;
vc:enables ngm:decentralised-web ;
vc:enables ngm:federated-social-networks ;
vc:enables ngm:federation ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:interoperability-protocol ;
vc:implements ngm:web-standard ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:semantic-web-linked-data-standard ;
vc:requires ngm:transport-protocol ;
vc:slug "activity-pub" ;
vc:sourceDomain "distributed-systems" ;
vc:standardizedBy ngm:world-wide-web-consortium ;
vc:uses ngm:digital-signatures ;
vc:uses ngm:json-ld ;
vc:uses ngm:linked-data .
ngm:activitystreams-2-0 a skos:Concept ;
rdfs:label "Activitystreams 2 0"@en .
ngm:activitystreams-vocabulary a skos:Concept ;
rdfs:label "Activitystreams Vocabulary"@en .
ngm:actor-model a owl:Class ;
rdfs:comment "The actor model is a mathematical model of concurrent computation in which the universal primitive is the actor, an independent entity that has private state and communicates only by sending asynchronous messages. In response to a message an actor can update its state, send messages to other actors and create new actors. Because actors share nothing and process one message at a time, the model avoids shared-memory data races and provides a foundation for scalable, fault-tolerant distributed systems."@en ;
rdfs:label "Actor Model"@en ;
rdfs:subClassOf ngm:concurrency ;
rdfs:subClassOf ngm:distributed-computing ;
vc:contrastsWith ngm:shared-nothing-architecture ;
vc:enables ngm:concurrency-model ;
vc:enables ngm:distributed-computing ;
vc:enables ngm:fault-tolerance ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:asynchronous-messaging ;
vc:implements ngm:message-passing ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:distributed-system ;
vc:relatedTo ngm:flow-control ;
vc:relatedTo ngm:reactive-systems ;
vc:slug "actor-model" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:load-balancing ;
vc:supports ngm:parallel-computing ;
vc:uses ngm:event-driven-architecture ;
vc:uses ngm:message-passing .
ngm:actor-network a skos:Concept ;
rdfs:label "Actor Network"@en .
ngm:actuation-system a skos:Concept ;
rdfs:label "Actuation System"@en .
ngm:actuator a owl:Class ;
rdfs:comment "An actuator is a transducer that converts a stored or supplied energy form — electrical, hydraulic, pneumatic, or thermochemical — into controlled mechanical motion or force, functioning as the output effector in any closed-loop control chain. Actuators execute commands issued by a controller by producing joint rotations, linear displacements, gripping forces, or compliant deformations, and their dynamic properties (torque density, bandwidth, backdrivability, stiffness) fundamentally bound a system's achievable speed, precision, payload capacity, and intrinsic safety during physical interaction. The choice of actuation technology cascades through every level of system design, from mechanical linkage geometry and energy storage requirements to real-time control law selection and safety-rated force limitation."@en ;
rdfs:label "Actuator"@en ;
rdfs:subClassOf ngm:robo-actuation-and-control ;
rdfs:subClassOf _:r1101 ;
rdfs:subClassOf _:r1102 ;
rdfs:subClassOf _:r1103 ;
rdfs:subClassOf _:r1104 ;
rdfs:subClassOf _:r1105 ;
rdfs:subClassOf _:r1106 ;
rdfs:subClassOf _:r1107 ;
rdfs:subClassOf _:r1108 ;
rdfs:subClassOf _:r1109 ;
rdfs:subClassOf _:r1110 ;
skos:broader ngm:robo-actuation-and-control ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:internet-of-things ;
vc:contrastsWith ngm:passive-mechanism ;
vc:contrastsWith ngm:transducer ;
vc:dependsOn ngm:embedded-system ;
vc:dependsOn ngm:embedded-systems ;
vc:dependsOn ngm:encoder ;
vc:dependsOn ngm:pid-controller ;
vc:enables ngm:human-robot-interaction ;
vc:enables ngm:motion-planning ;
vc:enables ngm:robot-kinematics ;
vc:enables ngm:teleoperation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:electric-linear-actuator ;
vc:hasPart ngm:hydraulic-actuator ;
vc:hasPart ngm:pneumatic-actuator ;
vc:hasPart ngm:series-elastic-actuator ;
vc:hasPart ngm:servo-motor ;
vc:isPartOf ngm:cyber-physical-systems ;
vc:isPartOf ngm:mechatronic-system ;
vc:isPartOf ngm:robot ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:impedance-control ;
vc:relatedTo ngm:industrial-automation ;
vc:relatedTo ngm:soft-robotics ;
vc:relatedTo ngm:torque-control ;
vc:requires ngm:control-system ;
vc:requires ngm:feedback-control ;
vc:requires ngm:power-electronics ;
vc:requires ngm:sensor ;
vc:slug "actuator" ;
vc:sourceDomain "robotics" .
ngm:actuator-driver a skos:Concept ;
rdfs:label "Actuator Driver"@en .
ngm:actuator-model a skos:Concept ;
rdfs:label "Actuator Model"@en .
ngm:actuator-response a skos:Concept ;
rdfs:label "Actuator Response"@en .
ngm:actuatorcommand a skos:Concept ;
rdfs:label "Actuatorcommand"@en .
ngm:actuators a owl:Class ;
rdfs:comment "Actuators are physical devices that convert an electrical, hydraulic, or pneumatic control signal into mechanical motion or force, enabling a control system to produce a desired physical effect in the world. They are the output components of robotic and cyber-physical systems, spanning technologies including servo motors, pneumatic cylinders, hydraulic actuators, and piezoelectric elements, each offering different trade-offs in force output, speed, precision, and energy efficiency."@en ;
rdfs:label "Actuators"@en ;
rdfs:subClassOf ngm:robot-component ;
rdfs:subClassOf _:r1111 ;
rdfs:subClassOf _:r1112 ;
rdfs:subClassOf _:r1113 ;
rdfs:subClassOf _:r1114 ;
rdfs:subClassOf _:r1115 ;
rdfs:subClassOf _:r1116 ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:extended-reality ;
vc:dependsOn ngm:control-system ;
vc:dependsOn ngm:sensors ;
vc:enables ngm:force-torque-control ;
vc:enables ngm:haptic-feedback ;
vc:enables ngm:locomotion ;
vc:enables ngm:robot-manipulation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:pneumatic-actuator ;
vc:hasPart ngm:series-elastic-actuator ;
vc:hasPart ngm:servo-motor ;
vc:implements ngm:robot-actuator ;
vc:isPartOf ngm:cyber-physical-systems ;
vc:isPartOf ngm:humanoid-robot ;
vc:isPartOf ngm:robot ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:prosthetics ;
vc:relatedTo ngm:soft-robotics ;
vc:requires ngm:feedback-control ;
vc:requires ngm:motion-control ;
vc:requires ngm:power-electronics ;
vc:slug "actuators" ;
vc:sourceDomain "robotics" ;
vc:uses ngm:ether-cat ;
vc:uses ngm:ros .
ngm:ad-hoc-ai-deployment a skos:Concept ;
rdfs:label "Ad Hoc AI Deployment"@en .
ngm:ad-hoc-data-access a skos:Concept ;
rdfs:label "Ad Hoc Data Access"@en .
ngm:ad-hoc-experimentation a skos:Concept ;
rdfs:label "Ad Hoc Experimentation"@en .
ngm:ad-hoc-identity a skos:Concept ;
rdfs:label "Ad Hoc Identity"@en .
ngm:ada-lovelace-harms-framework a skos:Concept ;
rdfs:label "Ada Lovelace Harms Framework"@en .
ngm:adaface a skos:Concept ;
rdfs:label "Adaface"@en .
ngm:adafactor a skos:Concept ;
rdfs:label "Adafactor"@en .
ngm:adafactor-optimiser a skos:Concept ;
rdfs:label "Adafactor Optimiser"@en .
ngm:adagrad a skos:Concept ;
rdfs:label "Adagrad"@en .
ngm:adam-optimiser a owl:Class ;
rdfs:comment "The Adam optimiser (Adaptive Moment Estimation) is a first-order gradient-based optimisation algorithm that computes per-parameter adaptive learning rates by maintaining exponentially decaying moving averages of past gradients (first moment) and past squared gradients (second moment), with bias correction applied in early iterations. It synthesises the momentum-tracking behaviour of gradient descent with momentum and the per-parameter scaling of RMSProp, making it robust to sparse gradients, non-stationary objectives, and high-dimensional parameter spaces. Introduced by Kingma and Ba (2014), Adam has become the de-facto default optimiser for training transformer-based large language models, diffusion models, and deep neural networks across most domains. Key variants including AdamW, Adan, and AdaFactor extend it with decoupled weight decay, Nesterov momentum, and memory-efficient factorisation respectively."@en ;
rdfs:label "Adam Optimiser"@en ;
rdfs:subClassOf ngm:gradient-descent ;
rdfs:subClassOf ngm:optimisation-algorithm ;
rdfs:subClassOf _:r1117 ;
rdfs:subClassOf _:r1118 ;
rdfs:subClassOf _:r1119 ;
rdfs:subClassOf _:r1120 ;
rdfs:subClassOf _:r1121 ;
rdfs:subClassOf _:r1122 ;
rdfs:subClassOf _:r1123 ;
rdfs:subClassOf _:r1124 ;
vc:bridgesTo ngm:distributed-training ;
vc:bridgesTo ngm:federated-learning ;
vc:bridgesTo ngm:policy-gradient-methods ;
vc:bridgesTo ngm:reinforcement-learning ;
vc:bridgesTo ngm:scientific-machine-learning ;
vc:contrastsWith ngm:adagrad ;
vc:contrastsWith ngm:amsgrad ;
vc:contrastsWith ngm:lion-optimiser ;
vc:contrastsWith ngm:muon-optimiser ;
vc:contrastsWith ngm:rmsprop ;
vc:contrastsWith ngm:sgd-with-momentum ;
vc:dependsOn ngm:gradient-accumulation ;
vc:dependsOn ngm:neural-network ;
vc:dependsOn ngm:numerical-stability ;
vc:enables ngm:convergence ;
vc:enables ngm:deep-learning ;
vc:enables ngm:fine-tuning ;
vc:enables ngm:hyperparameter-optimisation ;
vc:enables ngm:mixed-precision-training ;
vc:enables ngm:model-training ;
vc:enables ngm:transfer-learning ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:adafactor ;
vc:hasPart ngm:adam-optimiser ;
vc:hasPart ngm:amsgrad ;
vc:hasPart ngm:bias-correction ;
vc:hasPart ngm:exponential-moving-average ;
vc:hasPart ngm:gradient-clipping ;
vc:hasPart ngm:learning-rate-schedule ;
vc:hasPart ngm:lion-optimiser ;
vc:hasPart ngm:muon-optimiser ;
vc:implements ngm:adaptive-learning-rate ;
vc:implements ngm:momentum-optimisation ;
vc:implements ngm:regularisation ;
vc:qualityScore "0.91"^^xsd:float ;
vc:relatedTo ngm:adafactor ;
vc:relatedTo ngm:adam-optimiser ;
vc:relatedTo ngm:amsgrad ;
vc:relatedTo ngm:batch-normalisation ;
vc:relatedTo ngm:generalisation ;
vc:relatedTo ngm:large-language-model ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:neural-network ;
vc:relatedTo ngm:transformer-architecture ;
vc:relatedTo ngm:vanishing-gradient-problem ;
vc:relatedTo ngm:weight-decay ;
vc:requires ngm:automatic-differentiation ;
vc:requires ngm:backpropagation ;
vc:requires ngm:loss-function ;
vc:requires ngm:stochastic-gradient-descent ;
vc:slug "adam-optimiser" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:jax ;
vc:standardizedBy ngm:py-torch ;
vc:standardizedBy ngm:tensor-flow ;
vc:supports ngm:diffusion-model ;
vc:supports ngm:large-language-model ;
vc:supports ngm:natural-language-processing ;
vc:supports ngm:recurrent-neural-network ;
vc:supports ngm:vision-transformer ;
vc:uses ngm:exponential-moving-average ;
vc:uses ngm:gradient-clipping ;
vc:uses ngm:stochastic-gradient-descent .
ngm:adaptable-governance a skos:Concept ;
rdfs:label "Adaptable Governance"@en .
ngm:adaptation a skos:Concept ;
rdfs:label "Adaptation"@en .
ngm:adaptation-law a skos:Concept ;
rdfs:label "Adaptation Law"@en .
ngm:adapter-modules a owl:Class ;
rdfs:comment "Adapter Modules are compact bottleneck neural network sub-networks inserted between frozen transformer layers, trained exclusively on task-specific data whilst leaving the base model unchanged. They typically comprise a down-projection, a non-linearity, and an up-projection with a residual connection, constituting under 1% of model parameters and enabling efficient multi-task deployment from a single frozen base model."@en ;
rdfs:label "Adapter Modules"@en ;
rdfs:subClassOf ngm:parameter-efficient-fine-tuning ;
rdfs:subClassOf _:r1125 ;
rdfs:subClassOf _:r1126 ;
rdfs:subClassOf _:r1127 ;
rdfs:subClassOf _:r1128 ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:multimodal-ai-architecture-learning ;
vc:contrastsWith ngm:full-fine-tuning ;
vc:contrastsWith ngm:lo-ra ;
vc:contrastsWith ngm:prefix-tuning ;
vc:contrastsWith ngm:prompt-tuning ;
vc:dependsOn ngm:attention-mechanism ;
vc:dependsOn ngm:large-language-model ;
vc:enables ngm:continual-learning ;
vc:enables ngm:domain-adaptation ;
vc:enables ngm:multi-task-learning ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:residual-connection ;
vc:implements ngm:neural-network ;
vc:implements ngm:transfer-learning ;
vc:isPartOf ngm:parameter-efficient-fine-tuning ;
vc:qualityScore "0.65"^^xsd:float ;
vc:relatedTo ngm:natural-language-processing ;
vc:requires ngm:fine-tuning ;
vc:requires ngm:pre-trained-model ;
vc:requires ngm:transformer-architecture ;
vc:slug "adapter-modules" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:model-compression ;
vc:uses ngm:neural-network-layer ;
vc:uses ngm:transfer-learning .
ngm:adapter-pattern a skos:Concept ;
rdfs:label "Adapter Pattern"@en .
ngm:adapter-slot a owl:Class ;
rdfs:comment "A pluggable interface architecture (ADR-005) providing five standardised slots through which a VisionClaw Agentic Container|VisionClaw agent interacts with its environment: Solid Pod Storage|Pod (persistent storage), Agent Memory|Memory (episodic and semantic),"@en ;
rdfs:label "Adapter Slot"@en ;
rdfs:subClassOf ngm:infra-computing-and-cloud ;
skos:broader ngm:infra-computing-and-cloud ;
vc:bridgesTo ngm:containerisation ;
vc:bridgesTo ngm:microservices-architecture ;
vc:enables ngm:deployment-flexibility ;
vc:enables ngm:pluggable-memory ;
vc:enables ngm:pluggable-storage ;
vc:enables ngm:pluggable-telemetry ;
vc:enables ngm:pluggable-work-distribution ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:bead-adapter ;
vc:hasPart ngm:event-adapter ;
vc:hasPart ngm:memory-adapter ;
vc:hasPart ngm:orchestrator-adapter ;
vc:hasPart ngm:pod-adapter ;
vc:implements ngm:adapter-pattern ;
vc:implements ngm:dependency-injection ;
vc:implements ngm:strategy-pattern ;
vc:qualityScore "0.89"^^xsd:float ;
vc:requires ngm:interface-specification ;
vc:requires ngm:manifest-declaration ;
vc:requires ngm:runtime-initialization ;
vc:slug "adapter-slot" ;
vc:sourceDomain "infrastructure" .
ngm:adapter-tuning a owl:Class ;
rdfs:comment "A parameter-efficient fine-tuning technique that adapts a frozen pre-trained neural network to new tasks by inserting small trainable modules — adapters — between or alongside its layers, typically bottleneck feed-forward blocks or low-rank projections, so that task-specific behaviour is learned in a fraction of a percent of the original parameter count; adapters preserve the base model's weights, allow many tasks to share one backbone through swappable modules, and underpin methods from Houlsby adapters to LoRA and ControlNet-style conditioning branches."@en ;
rdfs:label "Adapter Tuning"@en ;
rdfs:subClassOf ngm:parameter-efficient-fine-tuning ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:cross-modal-conditioning ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:fine-tuning ;
vc:relatedTo ngm:lo-ra-do-ra-etc ;
vc:slug "adapter-tuning" ;
vc:sourceDomain "artificial-intelligence" .
ngm:adaptive-authentication a skos:Concept ;
rdfs:label "Adaptive Authentication"@en .
ngm:adaptive-behaviour a owl:Class ;
rdfs:comment "Adaptive behaviour refers to the capacity of an agent, system, or organism to modify its actions, strategies, or responses in real time based on feedback from its environment, internal state, or prior experience. In computational and robotics contexts, it describes dynamic adjustment of policies or control laws to optimise performance under changing conditions. The concept underpins reinforcement learning, autonomous agents, and self-organising systems."@en ;
rdfs:label "Adaptive Behaviour"@en ;
rdfs:subClassOf ngm:agent ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf ngm:cybernetics ;
rdfs:subClassOf ngm:reinforcement-learning ;
rdfs:subClassOf ngm:self-organising-systems ;
rdfs:subClassOf _:r1129 ;
rdfs:subClassOf _:r1130 ;
rdfs:subClassOf _:r1131 ;
rdfs:subClassOf _:r1132 ;
rdfs:subClassOf _:r1133 ;
rdfs:subClassOf _:r1134 ;
rdfs:subClassOf _:r1135 ;
rdfs:subClassOf _:r1136 ;
rdfs:subClassOf _:r1137 ;
rdfs:subClassOf _:r1138 ;
skos:broader ngm:ai-research-area ;
vc:contrastsWith ngm:static-policy ;
vc:contrastsWith ngm:symbolic-ai ;
vc:contrastsWith ngm:transfer-learning ;
vc:dependsOn ngm:cognitive-science ;
vc:dependsOn ngm:continual-learning ;
vc:dependsOn ngm:control-theory ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:neural-network ;
vc:enables ngm:adaptive-control ;
vc:enables ngm:agentic-ai ;
vc:enables ngm:autonomous-navigation ;
vc:enables ngm:embodied-ai ;
vc:enables ngm:game-ai ;
vc:enables ngm:robotic-manipulation ;
vc:enables ngm:swarm-intelligence ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:action-space ;
vc:hasPart ngm:experience-replay ;
vc:hasPart ngm:exploration-exploitation-tradeoff ;
vc:hasPart ngm:feedback-loop ;
vc:hasPart ngm:policy-optimisation ;
vc:hasPart ngm:reward-signal ;
vc:hasPart ngm:value-function ;
vc:implements ngm:hierarchical-reinforcement-learning ;
vc:implements ngm:model-based-reinforcement-learning ;
vc:implements ngm:policy-gradient-methods ;
vc:implements ngm:q-learning ;
vc:implements ngm:reinforcement-learning ;
vc:implements ngm:temporal-difference-learning ;
vc:qualityScore "0.91"^^xsd:float ;
vc:relatedTo ngm:adaptive-learning ;
vc:relatedTo ngm:agent-based-models ;
vc:relatedTo ngm:causal-inference ;
vc:relatedTo ngm:cognitive-science ;
vc:relatedTo ngm:continual-learning ;
vc:relatedTo ngm:cybernetics ;
vc:relatedTo ngm:distribution-shift ;
vc:relatedTo ngm:meta-learning ;
vc:relatedTo ngm:multi-agent-systems ;
vc:relatedTo ngm:safe-ai ;
vc:relatedTo ngm:sim-to-real-transfer ;
vc:relatedTo ngm:swarm-intelligence ;
vc:requires ngm:exploration-exploitation-tradeoff ;
vc:requires ngm:feedback-loop ;
vc:requires ngm:markov-decision-process ;
vc:requires ngm:simulation-environment ;
vc:slug "adaptive-behaviour" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:ieee-ras ;
vc:standardizedBy ngm:mu-jo-co ;
vc:standardizedBy ngm:openai-research-organisation ;
vc:supports ngm:autonomous-vehicle ;
vc:supports ngm:digital-twin ;
vc:supports ngm:natural-language-processing ;
vc:supports ngm:reinforcement-learning-from-human-feedback ;
vc:supports ngm:robotics ;
vc:uses ngm:deep-reinforcement-learning ;
vc:uses ngm:foundation-model ;
vc:uses ngm:imitation-learning ;
vc:uses ngm:large-language-model ;
vc:uses ngm:neural-network ;
vc:uses ngm:policy-optimisation ;
vc:uses ngm:reward-signal ;
vc:uses ngm:sensor-fusion ;
vc:uses ngm:world-model .
ngm:adaptive-bitrate-streaming a owl:Class ;
rdfs:comment "Adaptive bitrate streaming (ABR) is a media delivery technique that encodes content at multiple quality levels and dynamically switches between them in response to measured network throughput and client buffer state. The player requests short segments at the highest sustainable bitrate, smoothing playback over variable connections. It underpins modern over-the-top video via protocols such as HLS and MPEG-DASH delivered over HTTP and content delivery networks."@en ;
rdfs:label "Adaptive Bitrate Streaming"@en ;
rdfs:subClassOf ngm:video-streaming ;
rdfs:subClassOf _:r1139 ;
rdfs:subClassOf _:r1140 ;
vc:contrastsWith ngm:lossless-compression ;
vc:dependsOn ngm:cdn ;
vc:enables ngm:video-streaming ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:codec ;
vc:implements ngm:video-compression ;
vc:isPartOf ngm:video-streaming ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:bandwidth ;
vc:relatedTo ngm:lossy-compression ;
vc:relatedTo ngm:mpeg ;
vc:requires ngm:data-compression ;
vc:slug "adaptive-bitrate-streaming" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:network-protocol ;
vc:uses ngm:cdn ;
vc:uses ngm:video-compression .
ngm:adaptive-capacity-index a owl:Class ;
rdfs:comment "A metric used to assess an individual's ability to adapt to labor market disruptions, considering factors like financial resources, age, and skill transferability."@en ;
rdfs:label "Adaptive Capacity Index"@en ;
rdfs:subClassOf ngm:data-management ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-impact-on-employment ;
vc:relatedTo ngm:labor-economics ;
vc:slug "adaptive-capacity-index" ;
vc:sourceDomain "economics" .
ngm:adaptive-challenge a skos:Concept ;
rdfs:label "Adaptive Challenge"@en .
ngm:adaptive-coding-and-modulation a owl:Class ;
rdfs:label "Adaptive Coding and Modulation"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:satellite-communication ;
vc:slug "adaptive-coding-and-modulation" ;
vc:sourceDomain "space-science-and-systems" .
ngm:adaptive-computing a skos:Concept ;
rdfs:label "Adaptive Computing"@en .
ngm:adaptive-control a owl:Class ;
rdfs:comment "A control strategy that automatically adjusts its parameters in real-time to maintain desired performance as system dynamics change or uncertainties are encountered. The controller learns and adapts to variations in the system or environment, using mechanisms such as system identification, parameter estimation, and online learning to compensate for model uncertainty and external disturbances."@en ;
rdfs:label "Adaptive Control"@en ;
rdfs:subClassOf ngm:closed-loop-control ;
rdfs:subClassOf _:r1141 ;
rdfs:subClassOf _:r1142 ;
rdfs:subClassOf _:r1143 ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:bridgesTo ngm:reinforcement-learning ;
vc:contrastsWith ngm:pid-control ;
vc:contrastsWith ngm:robust-control ;
vc:dependsOn ngm:feedback-control ;
vc:dependsOn ngm:state-estimation ;
vc:enables ngm:autonomous-system ;
vc:enables ngm:fault-tolerant-control ;
vc:enables ngm:robust-control ;
vc:enables ngm:self-tuning-systems ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:planning-and-scheduling ;
vc:implements ngm:online-learning ;
vc:implements ngm:optimal-control ;
vc:isPartOf ngm:control-theory ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:adaptive-systems ;
vc:requires ngm:parameter-adaptation-mechanism ;
vc:requires ngm:stability-analysis ;
vc:requires ngm:system-identification ;
vc:slug "adaptive-control" ;
vc:sourceDomain "robotics" ;
vc:supports ngm:robotics ;
vc:uses ngm:parameter-estimation ;
vc:uses ngm:system-identification .
ngm:adaptive-densification a skos:Concept ;
rdfs:label "Adaptive Densification"@en .
ngm:adaptive-difficulty a skos:Concept ;
rdfs:label "Adaptive Difficulty"@en .
ngm:adaptive-experiment-design a skos:Concept ;
rdfs:label "Adaptive Experiment Design"@en .
ngm:adaptive-instance-normalisation a skos:Concept ;
rdfs:label "Adaptive Instance Normalisation"@en .
ngm:adaptive-interaction a skos:Concept ;
rdfs:label "Adaptive Interaction"@en .
ngm:adaptive-interface a skos:Concept ;
rdfs:label "Adaptive Interface"@en .
ngm:adaptive-interfaces a owl:Class ;
rdfs:comment "Adaptive interfaces are user interface systems that dynamically reconfigure their layout, content, modality, or interaction style in response to the current user's context, behaviour, preferences, or inferred cognitive state. They employ user modelling, machine learning, and context-aware computing to personalise the interaction layer without requiring manual configuration. The goal is to optimise usability, accessibility, and task performance across diverse user populations and situational conditions."@en ;
rdfs:label "Adaptive Interfaces"@en ;
rdfs:subClassOf ngm:human-computer-interaction ;
vc:enables ngm:accessible-experience ;
vc:enables ngm:personalised-learning ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:attention-aware-interaction ;
vc:relatedTo ngm:hyper-personalisation ;
vc:slug "adaptive-interfaces" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:context-awareness ;
vc:uses ngm:recommendation-system .
ngm:adaptive-large-neighbourhood-search a skos:Concept ;
rdfs:label "Adaptive Large Neighbourhood Search"@en .
ngm:adaptive-layer-normalisation a skos:Concept ;
rdfs:label "Adaptive Layer Normalisation"@en .
ngm:adaptive-learning a owl:Class ;
rdfs:comment "Adaptive learning is an educational methodology and technology paradigm in which instructional content, pacing, and assessment are dynamically tailored to each learner's demonstrated knowledge, learning style, and progress in real time. Computational systems analyse performance data to identify gaps and misconceptions, then serve personalised learning paths that optimise for mastery and engagement. The approach draws on psychometric theory, knowledge tracing algorithms, and machine learning to individualise instruction at scale."@en ;
rdfs:label "Adaptive Learning"@en ;
rdfs:subClassOf ngm:education-technology ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf ngm:personalised-learning ;
rdfs:subClassOf _:r1144 ;
rdfs:subClassOf _:r1145 ;
rdfs:subClassOf _:r1146 ;
rdfs:subClassOf _:r1147 ;
rdfs:subClassOf _:r1148 ;
rdfs:subClassOf _:r1149 ;
rdfs:subClassOf _:r1150 ;
rdfs:subClassOf _:r1151 ;
rdfs:subClassOf _:r1152 ;
rdfs:subClassOf _:r1153 ;
rdfs:subClassOf _:r1154 ;
rdfs:subClassOf _:r1155 ;
rdfs:subClassOf _:r1156 ;
vc:bridgesTo ngm:explainable-ai ;
vc:bridgesTo ngm:federated-learning ;
vc:bridgesTo ngm:large-language-model ;
vc:bridgesTo ngm:natural-language-processing ;
vc:contrastsWith ngm:curriculum-learning ;
vc:contrastsWith ngm:one-size-fits-all-instruction ;
vc:dependsOn ngm:cognitive-science ;
vc:dependsOn ngm:content-repository ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:knowledge-component-model ;
vc:dependsOn ngm:psychometrics ;
vc:enables ngm:computerised-adaptive-testing ;
vc:enables ngm:differentiated-instruction ;
vc:enables ngm:formative-assessment ;
vc:enables ngm:learning-analytics ;
vc:enables ngm:mastery-learning ;
vc:enables ngm:metacognition ;
vc:enables ngm:personalised-learning ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:computerised-adaptive-testing ;
vc:hasPart ngm:content-repository ;
vc:hasPart ngm:domain-model ;
vc:hasPart ngm:feedback-loop ;
vc:hasPart ngm:formative-assessment ;
vc:hasPart ngm:knowledge-component-model ;
vc:hasPart ngm:learner-model ;
vc:hasPart ngm:scaffolding ;
vc:implements ngm:bayesian-knowledge-tracing ;
vc:implements ngm:deep-knowledge-tracing ;
vc:implements ngm:item-response-theory ;
vc:implements ngm:reinforcement-learning ;
vc:implements ngm:spaced-repetition ;
vc:qualityScore "0.91"^^xsd:float ;
vc:relatedTo ngm:active-learning ;
vc:relatedTo ngm:adaptive-behaviour ;
vc:relatedTo ngm:affective-computing ;
vc:relatedTo ngm:cognitive-load-theory ;
vc:relatedTo ngm:curriculum-learning ;
vc:relatedTo ngm:gamification ;
vc:relatedTo ngm:multi-modal-learning ;
vc:relatedTo ngm:open-learner-model ;
vc:relatedTo ngm:recommendation-system ;
vc:relatedTo ngm:transfer-learning ;
vc:requires ngm:content-repository ;
vc:requires ngm:domain-model ;
vc:requires ngm:feedback-loop ;
vc:requires ngm:knowledge-graph ;
vc:requires ngm:learner-model ;
vc:requires ngm:psychometrics ;
vc:requires ngm:real-time-data-processing ;
vc:slug "adaptive-learning" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:ieee-ltsc ;
vc:standardizedBy ngm:ims-global-learning-consortium ;
vc:standardizedBy ngm:scorm ;
vc:standardizedBy ngm:xapi-specification ;
vc:supports ngm:differentiated-instruction ;
vc:supports ngm:mastery-learning ;
vc:supports ngm:metacognition ;
vc:supports ngm:scaffolding ;
vc:supports ngm:zone-of-proximal-development ;
vc:uses ngm:attention-mechanism ;
vc:uses ngm:bayesian-knowledge-tracing ;
vc:uses ngm:deep-knowledge-tracing ;
vc:uses ngm:graph-neural-network ;
vc:uses ngm:intelligent-tutoring-system ;
vc:uses ngm:item-response-theory ;
vc:uses ngm:learning-management-system ;
vc:uses ngm:neural-network ;
vc:uses ngm:spaced-repetition ;
vc:uses ngm:transformer-architecture .
ngm:adaptive-learning-rate a owl:Class ;
rdfs:comment "A family of optimisation techniques in which the step size of gradient descent is adjusted automatically during training — typically per parameter, from running statistics of past gradients — so that parameters with large or frequent gradients take smaller steps and rarely-updated parameters take larger ones, as implemented by AdaGrad, RMSProp, and Adam, reducing sensitivity to the manually chosen global learning rate."@en ;
rdfs:label "Adaptive Learning Rate"@en ;
rdfs:subClassOf ngm:learning-rate ;
vc:enables ngm:deep-learning ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:optimisation-algorithm ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:adam-optimiser ;
vc:relatedTo ngm:momentum ;
vc:relatedTo ngm:rmsprop ;
vc:relatedTo ngm:stochastic-gradient-descent ;
vc:slug "adaptive-learning-rate" ;
vc:sourceDomain "machine-learning" ;
vc:uses ngm:gradient-descent .
ngm:adaptive-learning-system a skos:Concept ;
rdfs:label "Adaptive Learning System"@en .
ngm:adaptive-manipulation a owl:Class ;
rdfs:comment "Adaptive manipulation is a subfield of robotics concerned with enabling robotic systems to grasp, move, and interact with objects in unstructured environments by continuously adapting grasp strategies, force application, and motion trajectories based on sensory feedback. It combines perception, planning, and control to handle variability in object geometry, material properties, and placement that defeats fixed pre-programmed approaches. Applications span industrial automation, surgical robotics, and service robots operating in human-centred spaces."@en ;
rdfs:label "Adaptive Manipulation"@en ;
rdfs:subClassOf ngm:manipulation ;
vc:enables ngm:compliant-manipulation ;
vc:enables ngm:dexterous-manipulation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:end-effector ;
vc:slug "adaptive-manipulation" ;
vc:sourceDomain "robotics" ;
vc:uses ngm:deep-reinforcement-learning ;
vc:uses ngm:force-control ;
vc:uses ngm:haptic-feedback .
ngm:adaptive-music a owl:Class ;
rdfs:comment "Adaptive music is a compositional and audio-engineering approach in which a musical soundtrack modifies its structure, instrumentation, tempo, or emotional register dynamically in response to real-time contextual signals such as player actions, narrative state, or environmental parameters within interactive media. It replaces the static looping of pre-composed tracks with a system that maintains musical coherence while reflecting the moment-to-moment state of an interactive experience. The technique is foundational to game audio design and is increasingly applied in extended reality, therapeutic, and generative AI contexts."@en ;
rdfs:label "Adaptive Music"@en ;
rdfs:subClassOf ngm:audio-system ;
vc:enables ngm:emergent-gameplay ;
vc:enables ngm:immersive-audio ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:audio-processing ;
vc:relatedTo ngm:game-ai ;
vc:slug "adaptive-music" ;
vc:sourceDomain "metaverse" ;
vc:uses ngm:audio-engine ;
vc:uses ngm:game-engine .
ngm:adaptive-npcs a skos:Concept ;
rdfs:label "Adaptive Npcs"@en .
ngm:adaptive-personalisation a skos:Concept ;
rdfs:label "Adaptive Personalisation"@en .
ngm:adaptive-rag a skos:Concept ;
rdfs:label "Adaptive RAG"@en .
ngm:adaptive-reinforcement a skos:Concept ;
rdfs:label "Adaptive Reinforcement"@en .
ngm:adaptive-services a skos:Concept ;
rdfs:label "Adaptive Services"@en .
ngm:adaptive-systems a skos:Concept ;
rdfs:label "Adaptive Systems"@en .
ngm:adaptive-toolbox a skos:Concept ;
rdfs:label "Adaptive Toolbox"@en .
ngm:adaptive-tutoring a skos:Concept ;
rdfs:label "Adaptive Tutoring"@en .
ngm:adaptive-ui-controller a skos:Concept ;
rdfs:label "Adaptive Ui Controller"@en .
ngm:adaptive-user-interface a owl:Class ;
rdfs:comment "An adaptive user interface is an interface that automatically changes its layout, content, or interaction style in response to context such as user behaviour, device, or measured emotional or cognitive state, rather than presenting a single fixed design to all users. It is a subject of human-computer interaction research and is enabled in emerging systems by emotional analytics engines that infer user state in real time. The goal is to reduce cognitive load and improve task efficiency by matching interface complexity to the user's current needs."@en ;
rdfs:label "Adaptive User Interface"@en ;
rdfs:subClassOf ngm:human-computer-interaction ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:human-computer-interaction ;
vc:qualityScore "0.6"^^xsd:float ;
vc:slug "adaptive-user-interface" ;
vc:sourceDomain "spatial-computing" .
ngm:adaptive-ux a skos:Concept ;
rdfs:label "Adaptive Ux"@en .
ngm:adaptive-virtual-experience a owl:Class ;
rdfs:comment "Adaptive Virtual Experience refers to AI-driven immersive environments that dynamically adjust content, difficulty, pacing, and presentation in real-time based on user behavior, preferences, physiological responses, and interaction patterns to deliver personalized and engaging virtual reality exp..."@en ;
rdfs:label "Adaptive Virtual Experience"@en ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf ngm:virtual-reality-experience ;
rdfs:subClassOf _:r1157 ;
rdfs:subClassOf _:r1158 ;
skos:broader ngm:sc-platform-and-environment ;
vc:bridgesTo ngm:blockchain ;
vc:enables ngm:gaming ;
vc:enables ngm:personalized-learning ;
vc:enables ngm:therapeutic-vr ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:machine-learning-discipline ;
vc:requires ngm:real-time-analytics ;
vc:requires ngm:user-behavior-tracking ;
vc:slug "adaptive-virtual-experience" ;
vc:sourceDomain "spatial-computing" .
ngm:adaptive-virtual-world a owl:Class ;
rdfs:comment "Adaptive Virtual World describes a metaverse environment that uses procedural generation, AI-driven content creation, and real-time user behavior analysis to dynamically evolve landscapes, structures, weather patterns, NPCs, and game mechanics in response to collective and individual user actions."@en ;
rdfs:label "Adaptive Virtual World"@en ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf ngm:virtual-world ;
rdfs:subClassOf _:r1159 ;
rdfs:subClassOf _:r1160 ;
rdfs:subClassOf _:r1161 ;
rdfs:subClassOf _:r1162 ;
skos:broader ngm:sc-platform-and-environment ;
vc:bridgesTo ngm:blockchain ;
vc:enables ngm:emergent-gameplay ;
vc:enables ngm:persistent-world-evolution ;
vc:enables ngm:personalized-environments ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:generative-ai ;
vc:requires ngm:neural-network ;
vc:requires ngm:procedural-generation ;
vc:slug "adaptive-virtual-world" ;
vc:sourceDomain "spatial-computing" .
ngm:adaptive-workload-distribution a skos:Concept ;
rdfs:label "Adaptive Workload Distribution"@en .
ngm:adaptor-signature a skos:Concept ;
rdfs:label "Adaptor Signature"@en .
ngm:adaptor-signatures a skos:Concept ;
rdfs:label "Adaptor Signatures"@en .
ngm:adas a owl:Class ;
rdfs:comment "Advanced Driver Assistance Systems (ADAS) are electronic systems that assist vehicle operators with driving and parking functions through automated technologies including adaptive cruise control, lane keeping assist, automatic emergency braking, blind spot detection, and parking assistance. ADAS operates at SAE Level 1–2 automation, augmenting rather than replacing the driver, and relies on sensor fusion across cameras, radar, and ultrasonic systems to perceive the vehicle's environment."@en ;
rdfs:label "ADAS"@en ;
rdfs:subClassOf ngm:robo-robot-type ;
rdfs:subClassOf _:r183 ;
rdfs:subClassOf _:r184 ;
skos:broader ngm:robo-robot-type ;
vc:bridgesTo ngm:autonomous-robot ;
vc:contrastsWith ngm:autonomous-vehicle ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:risk ;
vc:requires ngm:perception-system ;
vc:requires ngm:sensor-fusion ;
vc:slug "adas" ;
vc:sourceDomain "robotics" ;
vc:uses ngm:camera ;
vc:uses ngm:computer-vision ;
vc:uses ngm:lidar .
ngm:additionality a owl:Class ;
rdfs:comment "Additionality is the principle, central to carbon markets and climate finance, that an emissions-reduction or removal activity counts only if it would not have occurred under a business-as-usual baseline without the incentive of credit revenue. Demonstrating additionality requires showing that the project faces financial, regulatory, or technical barriers it overcomes specifically because of the credit mechanism. It is the key integrity test that separates credible carbon credits from those representing reductions that would have happened anyway."@en ;
rdfs:label "Additionality"@en ;
rdfs:subClassOf ngm:carbon-markets ;
rdfs:subClassOf _:r1163 ;
rdfs:subClassOf _:r1164 ;
vc:bridgesTo ngm:climate-finance ;
vc:contrastsWith ngm:greenwashing ;
vc:dependsOn ngm:carbon-accounting ;
vc:enables ngm:carbon-credits ;
vc:enables ngm:carbon-offset ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:carbon-markets ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:carbon-footprint ;
vc:relatedTo ngm:carbon-offset ;
vc:relatedTo ngm:esg ;
vc:relatedTo ngm:sustainable-finance ;
vc:requires ngm:carbon-accounting ;
vc:requires ngm:verification ;
vc:slug "additionality" ;
vc:sourceDomain "finance" ;
vc:standardizedBy ngm:paris-agreement ;
vc:supports ngm:net-zero ;
vc:uses ngm:audit .
ngm:additionality-assessment a skos:Concept ;
rdfs:label "Additionality Assessment"@en .
ngm:additive-manufacturing a owl:Class ;
rdfs:comment "Additive manufacturing (AM) is a family of processes that construct three-dimensional objects by depositing, sintering, or photopolymerising material layer by layer from a digital design file, in contrast to subtractive methods that remove material from a solid block. Processes include fused deposition modelling, selective laser sintering, stereolithography, binder jetting, and directed energy deposition, each suited to particular materials and resolution requirements. AM enables on-demand production of complex geometries, personalised products, and distributed manufacturing without the tooling investment of conventional production."@en ;
rdfs:label "Additive Manufacturing"@en ;
rdfs:subClassOf ngm:digital-fabrication ;
vc:contrastsWith ngm:collaborative-systems-modality-robotics ;
vc:enables ngm:digital-fabrication ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:computer-vision-system ;
vc:relatedTo ngm:digital-twin-creation ;
vc:slug "additive-manufacturing" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:cad-software ;
vc:uses ngm:digital-twin .
ngm:address a owl:Class ;
rdfs:comment "A blockchain Address is a compact, human-transmissible identifier derived from a public key via cryptographic hashing (typically SHA-256 followed by RIPEMD-160 for Bitcoin, or Keccak-256 for Ethereum), which designates the recipient or controller of blockchain funds or smart-contract state. Addresses function as pseudonymous identifiers: they reveal nothing about the owner's real identity while allowing cryptographic proof of ownership through digital signature with the corresponding private key. They are encoded in formats such as Base58Check (Bitcoin legacy), Bech32 (Bitcoin native SegWit), or hexadecimal with EIP-55 checksum (Ethereum)."@en ;
rdfs:label "Address"@en ;
rdfs:subClassOf ngm:blockchain-entity ;
rdfs:subClassOf ngm:cryptographic-primitive ;
rdfs:subClassOf _:r1165 ;
rdfs:subClassOf _:r1166 ;
rdfs:subClassOf _:r1167 ;
vc:enables ngm:blockchain-transaction ;
vc:enables ngm:digital-identity ;
vc:enables ngm:wallet ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:account-model ;
vc:relatedTo ngm:digital-wallet ;
vc:relatedTo ngm:hash-function ;
vc:relatedTo ngm:secp256k1 ;
vc:relatedTo ngm:utxo-model ;
vc:requires ngm:cryptographic-hash-function ;
vc:requires ngm:elliptic-curve-cryptography ;
vc:requires ngm:public-key-cryptography ;
vc:slug "address" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:digital-signature ;
vc:uses ngm:private-key ;
vc:uses ngm:public-key .
ngm:address-attribution a skos:Concept ;
rdfs:label "Address Attribution"@en .
ngm:addressing-scheme a owl:Class ;
rdfs:comment "An addressing scheme is a systematic convention for assigning, structuring, and resolving identifiers that locate resources, nodes, or content within a namespace. Schemes range from hierarchical and human-readable forms such as IP addresses and URLs to flat cryptographic forms such as content hashes and public-key fingerprints. The defining properties of an addressing scheme are its uniqueness guarantees, its resolution mechanism, and whether addresses are location-based, identity-based, or content-derived. Addressing schemes underpin routing, naming, and reference integrity across networked and decentralised systems."@en ;
rdfs:label "Addressing Scheme"@en ;
rdfs:subClassOf ngm:technique ;
vc:enables ngm:content-identifier ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:content-addressing ;
vc:relatedTo ngm:decentralised-identifier ;
vc:slug "addressing-scheme" ;
vc:sourceDomain "infrastructure" .
ngm:ade20-k a owl:Class ;
rdfs:comment "ADE20K is a large-scale image segmentation dataset containing over 27,000 images annotated with 150 semantic categories covering both indoor and outdoor scenes, released by MIT CSAIL in 2017. It provides pixel-level semantic, instance, and part-level annotations enabling training and benchmarking of scene parsing and semantic segmentation models. ADE20K serves as the foundational benchmark for the ImageNet Scene Parsing Challenge and has driven significant advances in dense prediction architectures, with state-of-the-art models achieving 62.8 mIoU by 2022 (BEiT-3)."@en ;
rdfs:label "ADE20K"@en ;
rdfs:subClassOf ngm:benchmark-dataset ;
rdfs:subClassOf ngm:benchmarks ;
rdfs:subClassOf _:r185 ;
rdfs:subClassOf _:r186 ;
rdfs:subClassOf _:r187 ;
rdfs:subClassOf _:r188 ;
rdfs:subClassOf _:r189 ;
rdfs:subClassOf _:r190 ;
rdfs:subClassOf _:r191 ;
rdfs:subClassOf _:r192 ;
rdfs:subClassOf _:r193 ;
vc:contrastsWith ngm:coco-dataset ;
vc:dependsOn ngm:data-annotation ;
vc:dependsOn ngm:ground-truth-labels ;
vc:dependsOn ngm:image-processing ;
vc:enables ngm:dense-prediction ;
vc:enables ngm:image-segmentation ;
vc:enables ngm:instance-segmentation ;
vc:enables ngm:open-vocabulary-segmentation ;
vc:enables ngm:panoptic-segmentation ;
vc:enables ngm:scene-understanding ;
vc:enables ngm:semantic-segmentation ;
vc:enables ngm:semi-supervised-learning ;
vc:enables ngm:visual-grounding ;
vc:enables ngm:weakly-supervised-learning ;
vc:enables ngm:zero-shot-learning ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:data-annotation ;
vc:hasPart ngm:evaluation-metric ;
vc:hasPart ngm:ground-truth-labels ;
vc:hasPart ngm:instance-segmentation ;
vc:hasPart ngm:panoptic-segmentation ;
vc:hasPart ngm:semantic-segmentation ;
vc:implements ngm:image-processing ;
vc:implements ngm:object-detection ;
vc:implements ngm:object-recognition ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:augmented-reality ;
vc:relatedTo ngm:autonomous-navigation ;
vc:relatedTo ngm:coco-dataset ;
vc:relatedTo ngm:foundation-model ;
vc:relatedTo ngm:image-captioning ;
vc:relatedTo ngm:image-classification ;
vc:relatedTo ngm:image-segmentation ;
vc:relatedTo ngm:medical-imaging ;
vc:relatedTo ngm:multimodal-ai-architecture-ai ;
vc:relatedTo ngm:robotics-perception ;
vc:relatedTo ngm:scene-graph ;
vc:relatedTo ngm:transfer-learning ;
vc:requires ngm:crowdsourcing ;
vc:requires ngm:data-curation ;
vc:requires ngm:human-in-the-loop ;
vc:requires ngm:places-dataset ;
vc:requires ngm:sun-database ;
vc:slug "ade20-k" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:mit-csail ;
vc:supports ngm:attention-mechanism ;
vc:supports ngm:convolutional-neural-network ;
vc:supports ngm:deep-learning ;
vc:supports ngm:foundation-model ;
vc:supports ngm:neural-network ;
vc:supports ngm:transformer-architecture ;
vc:supports ngm:vision-transformers ;
vc:uses ngm:computer-vision ;
vc:uses ngm:crowdsourcing ;
vc:uses ngm:data-annotation ;
vc:uses ngm:ground-truth-labels ;
vc:uses ngm:model-evaluation ;
vc:uses ngm:transfer-learning .
ngm:adequacy-decision-framework a skos:Concept ;
rdfs:label "Adequacy Decision Framework"@en .
ngm:adequacy-decisions a skos:Concept ;
rdfs:label "Adequacy Decisions"@en .
ngm:adjacency-list a skos:Concept ;
rdfs:label "Adjacency List"@en .
ngm:adjacency-matrix a owl:Class ;
rdfs:comment "An adjacency matrix is a square matrix representation of a graph in which the entry at row i and column j records whether, or how strongly, vertex i is connected to vertex j. For a graph of n vertices it is an n-by-n matrix, symmetric for undirected graphs and potentially weighted to encode edge costs. It is a foundational data structure for graph algorithms, spectral analysis and graph neural networks."@en ;
rdfs:label "Adjacency Matrix"@en ;
rdfs:subClassOf ngm:graph-representation ;
rdfs:subClassOf _:r1168 ;
vc:bridgesTo ngm:graph-neural-network ;
vc:contrastsWith ngm:sparse-matrix ;
vc:dependsOn ngm:linear-algebra ;
vc:enables ngm:graph-neural-network ;
vc:enables ngm:network-analysis ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:graph-representation ;
vc:isPartOf ngm:graph-theory ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:network-analysis ;
vc:relatedTo ngm:sparse-matrix ;
vc:requires ngm:graph-theory ;
vc:slug "adjacency-matrix" ;
vc:sourceDomain "data" ;
vc:supports ngm:pagerank ;
vc:supports ngm:shortest-path ;
vc:uses ngm:linear-algebra ;
vc:uses ngm:matrix .
ngm:adjacency-representation a skos:Concept ;
rdfs:label "Adjacency Representation"@en .
ngm:admet-prediction a skos:Concept ;
rdfs:label "Admet Prediction"@en .
ngm:admissibility a skos:Concept ;
rdfs:label "Admissibility"@en .
ngm:admission-control a skos:Concept ;
rdfs:label "Admission Control"@en .
ngm:admittance-control a owl:Class ;
rdfs:comment "Force control strategy where robotic systems respond to external forces by producing proportional motion governed by virtual admittance parameters (mass, damping, stiffness), enabling compliant physical interaction with uncertain or variable environments by regulating position/velocity trajectori..."@en ;
rdfs:label "Admittance Control"@en ;
rdfs:subClassOf ngm:compliance-control ;
rdfs:subClassOf ngm:force-control ;
rdfs:subClassOf ngm:interaction-control ;
rdfs:subClassOf ngm:motion-control ;
rdfs:subClassOf ngm:robo-actuation-and-control ;
rdfs:subClassOf ngm:robot-control ;
rdfs:subClassOf _:r1169 ;
rdfs:subClassOf _:r1170 ;
rdfs:subClassOf _:r1171 ;
rdfs:subClassOf _:r1172 ;
rdfs:subClassOf _:r1173 ;
rdfs:subClassOf _:r1174 ;
rdfs:subClassOf _:r1175 ;
rdfs:subClassOf _:r1176 ;
rdfs:subClassOf _:r1177 ;
rdfs:subClassOf _:r1178 ;
rdfs:subClassOf _:r1179 ;
skos:broader ngm:robo-actuation-and-control ;
vc:bridgesTo ngm:compliance-control ;
vc:dependsOn ngm:control-theory ;
vc:dependsOn ngm:dynamic-modeling ;
vc:dependsOn ngm:inverse-kinematics ;
vc:dependsOn ngm:sensor-fusion ;
vc:dependsOn ngm:signal-processing ;
vc:enables ngm:adaptive-manipulation ;
vc:enables ngm:compliant-motion ;
vc:enables ngm:contact-based-assembly ;
vc:enables ngm:delicate-handling ;
vc:enables ngm:rb-0094-power-and-force-limiting ;
vc:enables ngm:safe-human-robot-interaction ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:admittance-transfer-function ;
vc:hasPart ngm:force-sensor ;
vc:hasPart ngm:hyperparameter-tuning ;
vc:hasPart ngm:inverse-kinematics ;
vc:hasPart ngm:position-control ;
vc:hasPart ngm:virtual-mechanical-system ;
vc:implements ngm:force-to-motion-mapping ;
vc:implements ngm:rb-1007-trajectory-generation ;
vc:implements ngm:second-order-mechanical-system ;
vc:implements ngm:trajectory-generation ;
vc:implements ngm:virtual-damper-spring-mass ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:dynamic-model ;
vc:requires ngm:force-torque-sensor ;
vc:requires ngm:kinematic-model ;
vc:requires ngm:position-controlled-robot ;
vc:requires ngm:real-time-control-loop ;
vc:slug "admittance-control" ;
vc:sourceDomain "robotics" .
ngm:admittance-transfer-function a skos:Concept ;
rdfs:label "Admittance Transfer Function"@en .
ngm:adobe-content-authenticity-initiative a skos:Concept ;
rdfs:label "Adobe Content Authenticity Initiative"@en .
ngm:adobe-creative-cloud a owl:Class ;
rdfs:comment "Adobe Creative Cloud is a subscription-based software platform operated by Adobe Inc. that delivers a suite of professional creative applications—including Photoshop, Illustrator, Premiere Pro, After Effects, and InDesign—alongside cloud storage, collaboration services, and asset management infrastructure. Launched in 2013 as the successor to Adobe Creative Suite, it transitioned the industry from perpetual licence software to a continuous-update, cloud-connected model. The platform is the dominant industry standard for graphic design, photography, video production, motion graphics, and digital publishing workflows."@en ;
rdfs:label "Adobe Creative Cloud"@en ;
rdfs:subClassOf ngm:creative-tools ;
vc:enables ngm:content-creation ;
vc:enables ngm:content-production-workflow ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:3-d-content-creation ;
vc:relatedTo ngm:animation-software ;
vc:slug "adobe-creative-cloud" ;
vc:sourceDomain "metaverse" ;
vc:uses ngm:adobe-firefly ;
vc:uses ngm:cloud-platform .
ngm:adobe-firefly a owl:Class ;
rdfs:comment "Adobe Firefly is Adobe's family of proprietary generative AI models designed for commercial creative applications, offering text-to-image generation, generative fill, vector recolouring, and text-effect capabilities trained exclusively on licensed Adobe Stock imagery, openly licensed content, and public domain material. Launched in March 2023, Firefly is embedded across Adobe Creative Cloud applications and is positioned as an enterprise-safe generative AI tool that provides intellectual property indemnification for commercial outputs. It represents Adobe's strategy to integrate generative AI natively into professional creative workflows."@en ;
rdfs:label "Adobe Firefly"@en ;
rdfs:subClassOf ngm:creative-ai ;
rdfs:subClassOf ngm:creative-tools ;
rdfs:subClassOf ngm:generative-ai ;
rdfs:subClassOf _:r1180 ;
rdfs:subClassOf _:r1181 ;
rdfs:subClassOf _:r1182 ;
rdfs:subClassOf _:r1183 ;
rdfs:subClassOf _:r1184 ;
rdfs:subClassOf _:r1185 ;
vc:bridgesTo ngm:creative-industries ;
vc:bridgesTo ngm:enterprise-ai ;
vc:contrastsWith ngm:midjourney-text-to-image-service ;
vc:contrastsWith ngm:open-source-ai ;
vc:contrastsWith ngm:stable-diffusion-image-model ;
vc:enables ngm:brand-asset-management ;
vc:enables ngm:brand-management ;
vc:enables ngm:content-creation ;
vc:enables ngm:creative-workflow-automation ;
vc:enables ngm:image-editing ;
vc:enables ngm:image-generation ;
vc:enables ngm:vector-graphics ;
vc:enables ngm:video-generation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:fine-tuning ;
vc:hasPart ngm:firefly-custom-models ;
vc:hasPart ngm:firefly-video-model ;
vc:hasPart ngm:generative-fill ;
vc:hasPart ngm:text-effects-generation ;
vc:hasPart ngm:video-generation ;
vc:implements ngm:c2-pa ;
vc:implements ngm:c2-pa-content-credentials ;
vc:implements ngm:digital-content-provenance-marking ;
vc:isPartOf ngm:adobe-creative-cloud ;
vc:qualityScore "0.87"^^xsd:float ;
vc:relatedTo ngm:creative-ai ;
vc:relatedTo ngm:digital-content-provenance-marking ;
vc:relatedTo ngm:fine-tuning ;
vc:relatedTo ngm:generative-ai-api ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:multimodal-ai ;
vc:relatedTo ngm:multimodal-ai-architecture-ai ;
vc:relatedTo ngm:substance-3d ;
vc:requires ngm:cloud-platform ;
vc:requires ngm:content-licensing ;
vc:requires ngm:training-data ;
vc:slug "adobe-firefly" ;
vc:sourceDomain "ai" ;
vc:supports ngm:ai-governance ;
vc:supports ngm:ai-regulation ;
vc:supports ngm:enterprise-ai ;
vc:supports ngm:intellectual-property-rights-framework ;
vc:uses ngm:computer-vision ;
vc:uses ngm:deep-learning ;
vc:uses ngm:diffusion-model ;
vc:uses ngm:latent-diffusion ;
vc:uses ngm:neural-network ;
vc:uses ngm:text-to-image ;
vc:uses ngm:transformer-architecture .
ngm:adobe-podcast a skos:Concept ;
rdfs:label "Adobe Podcast"@en .
ngm:adoption-of-convergent-technologies a owl:Class ;
rdfs:comment "Adoption of Convergent Technologies is the socio-technical process by which enterprises, governments, consumers and communities progressively integrate interoperating stacks of mutually reinforcing deep-technology families — artificial intelligence (including foundation models, generative AI and ..."@en ;
rdfs:label "Adoption of Convergent Technologies"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:digital-transformation ;
rdfs:subClassOf ngm:innovation-diffusion ;
rdfs:subClassOf ngm:socio-technical-transition ;
rdfs:subClassOf ngm:technology-adoption ;
rdfs:subClassOf ngm:technology-policy ;
rdfs:subClassOf _:r1186 ;
rdfs:subClassOf _:r1187 ;
rdfs:subClassOf _:r1188 ;
rdfs:subClassOf _:r1189 ;
rdfs:subClassOf _:r1190 ;
rdfs:subClassOf _:r1191 ;
rdfs:subClassOf _:r1192 ;
rdfs:subClassOf _:r1193 ;
rdfs:subClassOf _:r1194 ;
rdfs:subClassOf _:r1195 ;
rdfs:subClassOf _:r1196 ;
rdfs:subClassOf _:r1197 ;
rdfs:subClassOf _:r1198 ;
rdfs:subClassOf _:r1199 ;
rdfs:subClassOf _:r1200 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:innovation-diffusion ;
vc:contrastsWith ngm:ai-adoption ;
vc:contrastsWith ngm:legacy-systems-modernisation ;
vc:contrastsWith ngm:pre-digital-transformation ;
vc:contrastsWith ngm:sequential-technology-rollout ;
vc:contrastsWith ngm:siloed-technology-adoption ;
vc:contrastsWith ngm:technology-lock-in ;
vc:dependsOn ngm:5-g-network ;
vc:dependsOn ngm:arm-ecosystem ;
vc:dependsOn ngm:cloud-computing ;
vc:dependsOn ngm:edge-computing ;
vc:dependsOn ngm:open-standards-ecosystems ;
vc:dependsOn ngm:public-research-funding ;
vc:dependsOn ngm:regulatory-sandbox ;
vc:dependsOn ngm:venture-capital-markets ;
vc:enables ngm:autonomous-system ;
vc:enables ngm:decentralised-application ;
vc:enables ngm:digital-physical-integration ;
vc:enables ngm:immersive-collaboration ;
vc:enables ngm:industry-4-0 ;
vc:enables ngm:precision-medicine ;
vc:enables ngm:productivity-multiplier-effects ;
vc:enables ngm:smart-city-infrastructure ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ai-adoption ;
vc:hasPart ngm:ar-frame ;
vc:hasPart ngm:biotech-commercialisation ;
vc:hasPart ngm:blockchain-network ;
vc:hasPart ngm:convergence-readiness-assessment ;
vc:hasPart ngm:digital-twin ;
vc:hasPart ngm:iot-adoption ;
vc:hasPart ngm:regulatory-sandbox ;
vc:hasPart ngm:skills-transition-programme ;
vc:hasPart ngm:technology-stack ;
vc:implements ngm:diffusion-of-innovations-theory ;
vc:implements ngm:gartner-hype-cycle ;
vc:implements ngm:multi-level-perspective ;
vc:implements ngm:nbic-convergence ;
vc:implements ngm:technology-acceptance-model ;
vc:implements ngm:toe-framework ;
vc:implements ngm:utaut ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:ai-adoption ;
vc:relatedTo ngm:ai-risks ;
vc:relatedTo ngm:algorithmic-bias-and-variance ;
vc:relatedTo ngm:carbon-credit-tracking ;
vc:relatedTo ngm:carbon-footprint-measurement ;
vc:relatedTo ngm:digital-sovereignty ;
vc:relatedTo ngm:fourth-industrial-revolution ;
vc:relatedTo ngm:metaverse ;
vc:relatedTo ngm:platform-economy ;
vc:relatedTo ngm:skills-gap ;
vc:relatedTo ngm:technology-governance ;
vc:relatedTo ngm:web3 ;
vc:requires ngm:ai-talent ;
vc:requires ngm:change-management ;
vc:requires ngm:data-governance-framework ;
vc:requires ngm:digital-infrastructure ;
vc:requires ngm:executive-sponsorship ;
vc:requires ngm:interoperability-standard ;
vc:requires ngm:interoperability-standards ;
vc:requires ngm:investment-capital ;
vc:requires ngm:regulatory-clarity ;
vc:slug "adoption-of-convergent-technologies" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:do-ra ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:gdpr ;
vc:standardizedBy ngm:hl7-fhir ;
vc:standardizedBy ngm:ieee-p2510 ;
vc:standardizedBy ngm:iso-iec-42001-ai-management-system ;
vc:standardizedBy ngm:matter-protocol ;
vc:standardizedBy ngm:open-xr ;
vc:standardizedBy ngm:uk-ai-opportunities-action-plan ;
vc:supports ngm:climate-tech ;
vc:supports ngm:economic-growth ;
vc:supports ngm:fourth-industrial-revolution ;
vc:supports ngm:future-of-work-transition ;
vc:supports ngm:national-competitiveness ;
vc:supports ngm:public-sector-modernisation ;
vc:supports ngm:sustainable-development-goals ;
vc:uses ngm:agent-frameworks ;
vc:uses ngm:agentic-internet ;
vc:uses ngm:artificial-intelligence ;
vc:uses ngm:blockchain-network ;
vc:uses ngm:computer-vision ;
vc:uses ngm:extended-reality ;
vc:uses ngm:generative-ai ;
vc:uses ngm:internet-of-things ;
vc:uses ngm:large-language-models ;
vc:uses ngm:synthetic-biology .
ngm:adr a skos:Concept ;
rdfs:label "Adr"@en .
ngm:adr-008 a owl:Class ;
rdfs:comment "An architecture decision record numbered 008, documenting a specific architectural choice within a project together with its context, options considered, and consequences. ADRs form a chronological log of design decisions."@en ;
rdfs:label "ADR-008"@en ;
rdfs:subClassOf ngm:software-architecture ;
rdfs:subClassOf _:r194 ;
vc:bridgesTo ngm:software-engineering ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:software-architecture ;
vc:slug "adr-008" ;
vc:sourceDomain "infrastructure" .
ngm:adr-012 a owl:Class ;
rdfs:comment "An architecture decision record numbered 012, capturing a particular architectural decision within a project alongside its context and consequences. It is part of a numbered sequence of design records."@en ;
rdfs:label "ADR-012"@en ;
rdfs:subClassOf ngm:software-architecture ;
rdfs:subClassOf _:r195 ;
vc:bridgesTo ngm:software-engineering ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:software-architecture ;
vc:slug "adr-012" ;
vc:sourceDomain "infrastructure" .
ngm:adr-generation a skos:Concept ;
rdfs:label "Adr Generation"@en .
ngm:adr-schemes a skos:Concept ;
rdfs:label "Adr Schemes"@en .
ngm:advance-cargo-information-system a skos:Concept ;
rdfs:label "Advance Cargo Information System"@en .
ngm:advanced-analytics a skos:Concept ;
rdfs:label "Advanced Analytics"@en .
ngm:advanced-driver-assistance-system a owl:Class ;
rdfs:comment "An Advanced Driver Assistance System (ADAS) is a suite of sensor-based technologies built into a vehicle that assist a human driver with perception, warning, or partial control tasks such as lane keeping, adaptive cruise control, and automatic emergency braking. It sits below full autonomy on the driving-automation scale, keeping the human driver responsible for the overall task. Standards such as SAE J3016 define the levels of automation ADAS features correspond to."@en ;
rdfs:label "Advanced Driver Assistance System"@en ;
rdfs:subClassOf ngm:autonomous-vehicle ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "advanced-driver-assistance-system" ;
vc:sourceDomain "robotics" .
ngm:advanced-manufacturing a owl:Class ;
rdfs:comment "Advanced manufacturing is the application of innovative technologies—including automation, robotics, additive manufacturing, digital twins, and data-driven process control—to improve the productivity, flexibility, and quality of producing goods. It integrates cyber-physical systems across the production lifecycle, blurring the boundary between digital design and physical fabrication. Advanced manufacturing is a central pillar of Industry 4.0 and modern industrial strategy."@en ;
rdfs:label "Advanced Manufacturing"@en ;
rdfs:subClassOf ngm:infrastructure ;
rdfs:subClassOf ngm:manufacturing-automation ;
skos:broader ngm:infrastructure ;
vc:dependsOn ngm:compute-infrastructure ;
vc:dependsOn ngm:supply-chain ;
vc:enables ngm:additive-manufacturing ;
vc:enables ngm:economic-development ;
vc:enables ngm:precision-manufacturing ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:industry-4-0 ;
vc:isPartOf ngm:infrastructure ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:digital-twin ;
vc:relatedTo ngm:io-t ;
vc:slug "advanced-manufacturing" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:logistics ;
vc:supports ngm:supply-chain ;
vc:supports ngm:uk-industrial-strategy ;
vc:uses ngm:automation ;
vc:uses ngm:digital-twin ;
vc:uses ngm:industrial-automation .
ngm:advanced-manufacturing-research-centre a skos:Concept ;
rdfs:label "Advanced Manufacturing Research Centre"@en .
ngm:advanced-metering-infrastructure a owl:Class ;
rdfs:comment "Advanced metering infrastructure (AMI) is the integrated system of smart meters, two-way communication networks and data management software that enables utilities to remotely collect detailed, time-stamped consumption data and to send control signals back to meters and connected devices. It extends earlier automated meter reading by providing bidirectional communication, enabling near-real-time usage data, remote connect/disconnect and dynamic pricing. AMI is a foundational enabler of demand response programmes and smart grid operations, since it supplies the granular consumption data those systems depend on."@en ;
rdfs:label "Advanced Metering Infrastructure"@en ;
rdfs:subClassOf ngm:smart-metering ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:smart-metering ;
vc:qualityScore "0.55"^^xsd:float ;
vc:relatedTo ngm:demand-response ;
vc:relatedTo ngm:smart-metering ;
vc:slug "advanced-metering-infrastructure" ;
vc:sourceDomain "infrastructure" .
ngm:advanced-packaging a skos:Concept ;
rdfs:label "Advanced Packaging"@en .
ngm:advances-in-cognitive-systems-journal a skos:Concept ;
rdfs:label "Advances In Cognitive Systems Journal"@en .
ngm:adversarial-attack a owl:Class ;
rdfs:comment "An Adversarial Attack is a deliberate attempt to manipulate an AI system by crafting malicious inputs or exploiting model vulnerabilities to cause misclassification, extract confidential information, degrade performance, or subvert intended behaviour. Attack classes include evasion, poisoning, model extraction, inversion, and backdoor, across white-box, black-box, and grey-box threat models."@en ;
rdfs:label "Adversarial Attack"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf _:r1201 ;
rdfs:subClassOf _:r1202 ;
rdfs:subClassOf _:r1203 ;
rdfs:subClassOf _:r1204 ;
rdfs:subClassOf _:r1205 ;
rdfs:subClassOf _:r1206 ;
rdfs:subClassOf _:r1207 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:ai-risk-management ;
vc:bridgesTo ngm:cybersecurity ;
vc:contrastsWith ngm:certified-defense ;
vc:contrastsWith ngm:robustness ;
vc:contrastsWith ngm:safety-fine-tuning ;
vc:enables ngm:adversarial-robustness ;
vc:enables ngm:red-teaming ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:backdoor-attack ;
vc:hasPart ngm:data-poisoning ;
vc:hasPart ngm:membership-inference ;
vc:hasPart ngm:model-extraction ;
vc:hasPart ngm:model-inversion ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:adversarial-training ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:computer-vision ;
vc:relatedTo ngm:differential-privacy ;
vc:requires ngm:machine-learning-model ;
vc:requires ngm:threat-model ;
vc:slug "adversarial-attack" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:deep-learning .
ngm:adversarial-attacks a owl:Class ;
rdfs:comment "Adversarial Attacks are malicious techniques that exploit vulnerabilities in machine learning models by deliberately crafting deceptive input data to cause incorrect predictions, misclassifications, or unintended behaviors, often through subtle perturbations imperceptible to humans but significan..."@en ;
rdfs:label "Adversarial Attacks"@en ;
rdfs:subClassOf ngm:ai-safety ;
rdfs:subClassOf ngm:ai-security-threats ;
rdfs:subClassOf ngm:ai-technique ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:computer-vision ;
vc:enables ngm:model-evasion ;
vc:enables ngm:system-manipulation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:crafted-perturbations ;
vc:requires ngm:knowledge-of-target-model ;
vc:slug "adversarial-attacks" ;
vc:sourceDomain "artificial-intelligence" .
ngm:adversarial-coordination a skos:Concept ;
rdfs:label "Adversarial Coordination"@en .
ngm:adversarial-debiasing a skos:Concept ;
rdfs:label "Adversarial Debiasing"@en .
ngm:adversarial-elicitation a skos:Concept ;
rdfs:label "Adversarial Elicitation"@en .
ngm:adversarial-examples a skos:Concept ;
rdfs:label "Adversarial Examples"@en .
ngm:adversarial-generation a skos:Concept ;
rdfs:label "Adversarial Generation"@en .
ngm:adversarial-jailbreaking a skos:Concept ;
rdfs:label "Adversarial Jailbreaking"@en .
ngm:adversarial-loss a skos:Concept ;
rdfs:label "Adversarial Loss"@en .
ngm:adversarial-machine-learning a owl:Class ;
rdfs:comment "Adversarial machine learning is the study of attacks that exploit vulnerabilities in machine learning models and the development of defences against them, encompassing threats across the model lifecycle including training-time data poisoning, evasion attacks at inference time, model inversion, and membership inference. Attackers craft carefully perturbed inputs or manipulate training data to cause misclassification, extract sensitive information, or degrade model performance, whilst defenders develop robust training procedures, certified defences, and detection mechanisms. The field spans both offensive security research and the development of trustworthy AI systems."@en ;
rdfs:label "Adversarial Machine Learning"@en ;
rdfs:subClassOf ngm:ai-security ;
rdfs:subClassOf _:r1208 ;
rdfs:subClassOf _:r1209 ;
rdfs:subClassOf _:r1210 ;
rdfs:subClassOf _:r1211 ;
rdfs:subClassOf _:r1212 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:contrastsWith ngm:machine-learning-discipline ;
vc:dependsOn ngm:cybersecurity ;
vc:dependsOn ngm:formal-verification ;
vc:enables ngm:adversarial-robustness ;
vc:enables ngm:model-robustness ;
vc:enables ngm:red-teaming ;
vc:enables ngm:trustworthy-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:adversarial-attack ;
vc:hasPart ngm:backdoor-attack ;
vc:hasPart ngm:membership-inference ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:adversarial-testing ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:differential-privacy ;
vc:relatedTo ngm:federated-learning ;
vc:relatedTo ngm:model-inversion ;
vc:relatedTo ngm:prompt-injection ;
vc:requires ngm:machine-learning-discipline ;
vc:requires ngm:threat-modelling ;
vc:slug "adversarial-machine-learning" ;
vc:sourceDomain "security" ;
vc:uses ngm:adversarial-attacks ;
vc:uses ngm:data-poisoning ;
vc:uses ngm:gradient-descent ;
vc:uses ngm:neural-network ;
vc:uses ngm:transfer-learning .
ngm:adversarial-model a skos:Concept ;
rdfs:label "Adversarial Model"@en .
ngm:adversarial-robustness a owl:Class ;
rdfs:comment "The capability of an AI system to maintain correct and consistent behaviour when subjected to adversarial examples—inputs intentionally crafted with small, often imperceptible perturbations designed to cause misclassification or incorrect outputs. Defensive strategies include adversarial training, randomised smoothing, and ensemble methods, each offering different trade-offs between certified guarantees and computational cost."@en ;
rdfs:label "Adversarial Robustness"@en ;
rdfs:subClassOf ngm:ai-safety ;
rdfs:subClassOf _:r1213 ;
rdfs:subClassOf _:r1214 ;
rdfs:subClassOf _:r1215 ;
vc:bridgesTo ngm:autonomous-system ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:cybersecurity ;
vc:contrastsWith ngm:adversarial-attack ;
vc:contrastsWith ngm:attack-vector ;
vc:contrastsWith ngm:vulnerability ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:model-evaluation ;
vc:enables ngm:safe-ai-deployment ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:adversarial-training ;
vc:hasPart ngm:certified-defense ;
vc:implements ngm:ensemble-methods ;
vc:isPartOf ngm:model-robustness ;
vc:isPartOf ngm:trustworthy-ai ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:explainability ;
vc:relatedTo ngm:fairness ;
vc:relatedTo ngm:resilience ;
vc:relatedTo ngm:risk ;
vc:requires ngm:security ;
vc:requires ngm:threat-model ;
vc:slug "adversarial-robustness" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:iso-iec-tr-24029-1-2021 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:ai-governance ;
vc:supports ngm:risk-management ;
vc:uses ngm:formal-verification .
ngm:adversarial-search a skos:Concept ;
rdfs:label "Adversarial Search"@en .
ngm:adversarial-testing a owl:Class ;
rdfs:comment "A testing methodology that deliberately attempts to cause AI system failures through adversarial inputs, edge cases, and challenging scenarios in order to identify robustness issues, safety vulnerabilities, and alignment failures before deployment. It encompasses both explicitly adversarial prompts and implicitly problematic queries, drawing on red-teaming practices and formalised by NIST AI 100-2."@en ;
rdfs:label "Adversarial Testing"@en ;
rdfs:subClassOf ngm:ai-safety ;
rdfs:subClassOf _:r1216 ;
rdfs:subClassOf _:r1217 ;
vc:bridgesTo ngm:cybersecurity ;
vc:bridgesTo ngm:digital-twin ;
vc:contrastsWith ngm:unit-testing ;
vc:dependsOn ngm:benchmark-dataset ;
vc:dependsOn ngm:model-evaluation ;
vc:enables ngm:bias-detection-methods ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:nist-ai-rmf ;
vc:implements ngm:security-testing ;
vc:qualityScore "0.68"^^xsd:float ;
vc:relatedTo ngm:adversarial-training ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:safety-evaluation ;
vc:requires ngm:machine-learning-model ;
vc:requires ngm:threat-model ;
vc:slug "adversarial-testing" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:ai-alignment ;
vc:supports ngm:ai-safety ;
vc:supports ngm:responsible-ai ;
vc:supports ngm:robustness ;
vc:uses ngm:adversarial-examples ;
vc:uses ngm:prompt-injection ;
vc:uses ngm:red-teaming .
ngm:adversarial-training a owl:Class ;
rdfs:comment "Adversarial training is a robustness technique that augments model training with adversarially perturbed examples generated to maximise the model's loss. By solving an inner maximisation that crafts worst-case inputs within a bounded perturbation set and an outer minimisation over model parameters, it teaches models to resist adversarial attacks. It improves robustness against perturbations at the cost of additional computation and sometimes reduced clean accuracy."@en ;
rdfs:label "Adversarial Training"@en ;
rdfs:subClassOf ngm:model-training ;
rdfs:subClassOf _:r1218 ;
rdfs:subClassOf _:r1219 ;
rdfs:subClassOf _:r1220 ;
rdfs:subClassOf _:r1221 ;
vc:enables ngm:robustness ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:data-augmentation ;
vc:hasPart ngm:gradient-descent ;
vc:implements ngm:model-robustness ;
vc:isPartOf ngm:model-training ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:deep-learning ;
vc:relatedTo ngm:generative-adversarial-network ;
vc:relatedTo ngm:overfitting ;
vc:relatedTo ngm:security ;
vc:requires ngm:adversarial-attack ;
vc:requires ngm:supervised-learning ;
vc:slug "adversarial-training" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:gradient-descent ;
vc:uses ngm:neural-network .
ngm:adversary-intelligence-collection a skos:Concept ;
rdfs:label "Adversary Intelligence Collection"@en .
ngm:adversary-model a skos:Concept ;
rdfs:label "Adversary Model"@en .
ngm:adverse-media-screening a skos:Concept ;
rdfs:label "Adverse Media Screening"@en .
ngm:adverse-selection a skos:Concept ;
rdfs:label "Adverse Selection"@en .
ngm:advertising a owl:Class ;
rdfs:comment "Advertising is the practice of communicating persuasive messages about products, services, ideas, or brands to targeted audiences through paid media channels with the intent to influence awareness, attitudes, or purchasing behaviour. It encompasses the creative development of messages and the strategic planning and buying of media placements across channels including broadcast, print, digital, out-of-home, and emerging immersive formats. Modern advertising increasingly relies on data-driven audience targeting, algorithmic media buying, and AI-generated creative to maximise return on investment at scale."@en ;
rdfs:label "Advertising"@en ;
rdfs:subClassOf ngm:advertising-and-marketing ;
vc:enables ngm:programmatic-advertising ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:data-privacy ;
vc:relatedTo ngm:gdpr ;
vc:relatedTo ngm:social-media-platform-infrastructure ;
vc:slug "advertising" ;
vc:sourceDomain "finance" ;
vc:uses ngm:digital-marketing ;
vc:uses ngm:predictive-analytics .
ngm:advertising-and-marketing a owl:Class ;
rdfs:comment "Advertising and marketing is the combined domain of commercial practices concerned with identifying customer needs, developing products and services to meet them, communicating value propositions to target audiences through paid and unpaid channels, and building lasting brand relationships. Marketing encompasses the strategic disciplines of market research, product development, pricing, distribution, and communications, while advertising is the paid communications subset of the marketing mix. Together they constitute the primary commercial mechanism by which organisations acquire customers and generate revenue in market economies."@en ;
rdfs:label "Advertising and Marketing"@en ;
rdfs:subClassOf ngm:digital-marketing ;
vc:enables ngm:advertising ;
vc:enables ngm:programmatic-advertising ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:customer-experience ;
vc:relatedTo ngm:data-privacy ;
vc:slug "advertising-and-marketing" ;
vc:sourceDomain "finance" ;
vc:uses ngm:behavioural-analytics ;
vc:uses ngm:predictive-analytics ;
vc:uses ngm:recommendation-engine .
ngm:advertising-economics a skos:Concept ;
rdfs:label "Advertising Economics"@en .
ngm:advertising-production a skos:Concept ;
rdfs:label "Advertising Production"@en .
ngm:advertising-revenue a skos:Concept ;
rdfs:label "Advertising Revenue"@en .
ngm:advertising-space a skos:Concept ;
rdfs:label "Advertising Space"@en .
ngm:advertising-technology a skos:Concept ;
rdfs:label "Advertising Technology"@en .
ngm:adwin a skos:Concept ;
rdfs:label "Adwin"@en .
ngm:adyen a skos:Concept ;
rdfs:label "Adyen"@en .
ngm:aead-cipher a skos:Concept ;
rdfs:label "Aead Cipher"@en .
ngm:aerial-robot a owl:Class ;
rdfs:comment "Aerial Robot - An autonomous or remotely operated aircraft equipped with Sensors, Actuators, and Navigation Systems for performing surveillance, inspection, delivery, and environmental monitoring tasks in three-dimensional airspace with minimal human intervention."@en ;
rdfs:label "Aerial Robot"@en ;
rdfs:subClassOf ngm:mobile-robot ;
rdfs:subClassOf ngm:robo-robot-type ;
rdfs:subClassOf ngm:robotics ;
rdfs:subClassOf _:r1222 ;
rdfs:subClassOf _:r1223 ;
rdfs:subClassOf _:r1224 ;
rdfs:subClassOf _:r1225 ;
skos:broader ngm:robo-robot-type ;
skos:broader ngm:robotics ;
vc:enables ngm:automated-delivery ;
vc:enables ngm:environmental-monitoring ;
vc:enables ngm:technology-infrastructure-domain-inspection ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:aerial-vehicle ;
vc:isPartOf ngm:autonomous-system ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:flight-control-system ;
vc:requires ngm:gps-navigation ;
vc:requires ngm:obstacle-avoidance ;
vc:requires ngm:power-management ;
vc:slug "aerial-robot" ;
vc:sourceDomain "robotics" .
ngm:aerial-robotics a skos:Concept ;
rdfs:label "Aerial Robotics"@en .
ngm:aerial-vehicle a skos:Concept ;
rdfs:label "Aerial Vehicle"@en .
ngm:aerosol-dispersal-mechanism a skos:Concept ;
rdfs:label "Aerosol Dispersal Mechanism"@en .
ngm:aerosol-optical-depth-retrieval a owl:Class ;
rdfs:label "Aerosol Optical Depth Retrieval"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-applications ;
vc:slug "aerosol-optical-depth-retrieval" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:aerospace a skos:Concept ;
rdfs:label "Aerospace"@en .
ngm:aerospace-engineering a owl:Class ;
rdfs:comment "Aerospace Engineering is the branch of engineering concerned with the design, development, testing, and operation of aircraft, spacecraft, satellites, and related systems. It encompasses aerodynamics, propulsion, structural mechanics, avionics, guidance systems, and materials science. As an application domain it drives requirements for high-integrity embedded systems, real-time control, fault tolerance, and increasingly autonomous operation."@en ;
rdfs:label "Aerospace Engineering"@en ;
rdfs:subClassOf ngm:infrastructure ;
rdfs:subClassOf ngm:systems-engineering ;
rdfs:subClassOf _:r1226 ;
rdfs:subClassOf _:r1227 ;
rdfs:subClassOf _:r1228 ;
skos:broader ngm:infrastructure ;
vc:bridgesTo ngm:spatial-computing ;
vc:dependsOn ngm:embedded-systems ;
vc:dependsOn ngm:sensor-fusion ;
vc:enables ngm:remote-sensing ;
vc:enables ngm:satellite-communication ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:avionics ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:governance ;
vc:relatedTo ngm:standards ;
vc:requires ngm:functional-safety ;
vc:requires ngm:real-time-computing ;
vc:slug "aerospace-engineering" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:autonomous-system ;
vc:supports ngm:robotics ;
vc:uses ngm:digital-twin ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:simulation .
ngm:aerospace-guidance-navigation-control a skos:Concept ;
rdfs:label "Aerospace Guidance Navigation Control"@en .
ngm:aerospace-mro a skos:Concept ;
rdfs:label "Aerospace Mro"@en .
ngm:aes a skos:Concept ;
rdfs:label "Aes"@en .
ngm:aes-128 a skos:Concept ;
rdfs:label "Aes 128"@en .
ngm:aes-256-encryption a skos:Concept ;
rdfs:label "Aes 256 Encryption"@en .
ngm:aes-encryption a owl:Class ;
rdfs:comment "AES encryption is the Advanced Encryption Standard, a symmetric block cipher adopted as a US federal standard that operates on fixed-size blocks using a shared secret key for both encryption and decryption. It is the most widely deployed symmetric cipher, used by hardware security features such as Intel SGX for memory encryption and by low-power wireless protocols such as Zigbee for link-layer security. It supports 128, 192 and 256-bit key lengths, with 128-bit remaining secure against all known practical attacks."@en ;
rdfs:label "AES Encryption"@en ;
rdfs:subClassOf ngm:symmetric-encryption ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:slug "aes-encryption" ;
vc:sourceDomain "security" .
ngm:aes-gcm a owl:Class ;
rdfs:comment "AES-GCM (Advanced Encryption Standard – Galois/Counter Mode) is an authenticated encryption with associated data (AEAD) cipher mode that combines the AES block cipher operating in Counter Mode with the Galois Message Authentication Code. It provides both confidentiality and data integrity in a single pass, making it the dominant symmetric encryption scheme in modern secure communications."@en ;
rdfs:label "AES-GCM"@en ;
rdfs:subClassOf ngm:symmetric-encryption ;
vc:enables ngm:end-to-end-encryption ;
vc:enables ngm:network-security ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:cryptographic-key-management ;
vc:relatedTo ngm:cryptography ;
vc:slug "aes-gcm" ;
vc:sourceDomain "security" ;
vc:uses ngm:message-authentication-code ;
vc:uses ngm:nonce .
ngm:aes69-sofa a skos:Concept ;
rdfs:label "Aes69 Sofa"@en .
ngm:aesthetic-knowledge-base a skos:Concept ;
rdfs:label "Aesthetic Knowledge Base"@en .
ngm:aesthetics a skos:Concept ;
rdfs:label "Aesthetics"@en .
ngm:affective-computing a owl:Class ;
rdfs:comment "Affective computing is a branch of artificial intelligence and human-computer interaction concerned with systems that can recognise, interpret, process, and simulate human emotions and affective states. It draws on psychology, cognitive science, and machine learning to endow machines with emotional intelligence, enabling them to adapt their behaviour in response to detected user affect. The field encompasses technologies for emotion detection from facial expressions, speech, physiological signals, and body language, as well as methods for generating emotionally congruent responses. Foundational work by Rosalind Picard at MIT established that recognising and appropriately responding to affect is essential for natural, effective human-machine communication."@en ;
rdfs:label "Affective Computing"@en ;
rdfs:subClassOf ngm:cognitive-science ;
rdfs:subClassOf ngm:human-computer-interaction ;
rdfs:subClassOf ngm:multimodal-ai-architecture-ai ;
rdfs:subClassOf _:r1238 ;
rdfs:subClassOf _:r1239 ;
rdfs:subClassOf _:r1240 ;
rdfs:subClassOf _:r1241 ;
rdfs:subClassOf _:r1242 ;
rdfs:subClassOf _:r1243 ;
rdfs:subClassOf _:r1244 ;
rdfs:subClassOf _:r1245 ;
rdfs:subClassOf _:r1246 ;
rdfs:subClassOf _:r1247 ;
vc:bridgesTo ngm:autonomous-vehicle ;
vc:bridgesTo ngm:digital-health ;
vc:bridgesTo ngm:extended-reality ;
vc:bridgesTo ngm:human-robot-interaction ;
vc:bridgesTo ngm:robotics ;
vc:bridgesTo ngm:social-robotics ;
vc:contrastsWith ngm:rational-agent ;
vc:contrastsWith ngm:rule-based-systems ;
vc:contrastsWith ngm:symbolic-ai ;
vc:dependsOn ngm:active-learning ;
vc:dependsOn ngm:data-labelling ;
vc:dependsOn ngm:foundation-model ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:multimodal-ai-architecture-ai ;
vc:dependsOn ngm:transfer-learning ;
vc:enables ngm:adaptive-learning-system ;
vc:enables ngm:cognitive-feedback-interface ;
vc:enables ngm:digital-health ;
vc:enables ngm:driver-monitoring-system ;
vc:enables ngm:emotion-aware-interaction ;
vc:enables ngm:emotional-analytics-engine ;
vc:enables ngm:human-robot-interaction ;
vc:enables ngm:intelligent-tutoring-system ;
vc:enables ngm:mental-health-monitoring ;
vc:enables ngm:social-robotics ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:biometric-sensing ;
vc:hasPart ngm:cognitive-feedback-interface ;
vc:hasPart ngm:emotion-recognition ;
vc:hasPart ngm:emotional-analytics-engine ;
vc:hasPart ngm:multimodal-ai-architecture ;
vc:hasPart ngm:physiological-signal-processing ;
vc:implements ngm:active-learning ;
vc:implements ngm:differential-privacy ;
vc:implements ngm:federated-learning ;
vc:implements ngm:privacy-preserving-machine-learning ;
vc:implements ngm:transfer-learning ;
vc:qualityScore "0.91"^^xsd:float ;
vc:relatedTo ngm:appraisal-theory ;
vc:relatedTo ngm:autonomous-agent ;
vc:relatedTo ngm:bdi-model ;
vc:relatedTo ngm:biometric-sensing ;
vc:relatedTo ngm:cognitive-load ;
vc:relatedTo ngm:cognitive-science ;
vc:relatedTo ngm:dimensional-model-of-affect ;
vc:relatedTo ngm:emotional-intelligence ;
vc:relatedTo ngm:explainable-ai ;
vc:relatedTo ngm:facial-action-coding-system ;
vc:relatedTo ngm:human-robot-interaction ;
vc:relatedTo ngm:large-language-model ;
vc:relatedTo ngm:multimodal-ai ;
vc:relatedTo ngm:multimodal-ai-architecture-ai ;
vc:relatedTo ngm:neuroimaging ;
vc:relatedTo ngm:privacy-preserving-machine-learning ;
vc:relatedTo ngm:psychophysiology ;
vc:relatedTo ngm:reinforcement-learning-from-human-feedback ;
vc:relatedTo ngm:user-experience-design ;
vc:relatedTo ngm:wearable-computing ;
vc:requires ngm:annotated-dataset ;
vc:requires ngm:annotated-training-data ;
vc:requires ngm:data-labelling ;
vc:requires ngm:emotion-recognition ;
vc:requires ngm:multimodal-fusion ;
vc:requires ngm:transfer-learning ;
vc:slug "affective-computing" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:gdpr ;
vc:standardizedBy ngm:ieee-p7014 ;
vc:supports ngm:autonomous-vehicle ;
vc:supports ngm:digital-health ;
vc:supports ngm:extended-reality ;
vc:supports ngm:social-robotics ;
vc:supports ngm:user-experience-design ;
vc:uses ngm:attention-mechanism ;
vc:uses ngm:computer-vision ;
vc:uses ngm:convolutional-neural-network ;
vc:uses ngm:deep-learning ;
vc:uses ngm:eeg ;
vc:uses ngm:foundation-model ;
vc:uses ngm:large-language-model ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:physiological-signal-processing ;
vc:uses ngm:sentiment-analysis ;
vc:uses ngm:speech-recognition ;
vc:uses ngm:transformer-architecture ;
vc:uses ngm:wearable-computing .
ngm:affective-computing-system a owl:Class ;
rdfs:comment "An Affective Computing System is a computational architecture that can recognise, interpret, simulate, or respond to human emotional and affective states through the integration of multimodal physiological and behavioural signals with machine learning models. Such systems aim to make human-computer interaction more natural and context-sensitive by treating emotion as a first-class computational variable."@en ;
rdfs:label "Affective Computing System"@en ;
rdfs:subClassOf ngm:affective-computing ;
rdfs:subClassOf ngm:cognitive-ai ;
rdfs:subClassOf ngm:human-computer-interaction ;
rdfs:subClassOf _:r1229 ;
rdfs:subClassOf _:r1230 ;
rdfs:subClassOf _:r1231 ;
rdfs:subClassOf _:r1232 ;
rdfs:subClassOf _:r1233 ;
rdfs:subClassOf _:r1234 ;
rdfs:subClassOf _:r1235 ;
rdfs:subClassOf _:r1236 ;
rdfs:subClassOf _:r1237 ;
vc:bridgesTo ngm:autonomous-vehicle ;
vc:bridgesTo ngm:digital-health ;
vc:bridgesTo ngm:extended-reality ;
vc:bridgesTo ngm:social-robotics ;
vc:contrastsWith ngm:rational-agent ;
vc:contrastsWith ngm:symbolic-ai ;
vc:dependsOn ngm:data-labelling ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:physiological-signal-processing ;
vc:enables ngm:adaptive-interfaces ;
vc:enables ngm:adaptive-learning ;
vc:enables ngm:emotion-aware-interaction ;
vc:enables ngm:emotional-analytics-engine ;
vc:enables ngm:empathetic-ai ;
vc:enables ngm:intelligent-tutoring ;
vc:enables ngm:mental-health-monitoring ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:affective-response-module ;
vc:hasPart ngm:cognitive-feedback-interface ;
vc:hasPart ngm:emotion-recognition ;
vc:hasPart ngm:emotional-analytics-engine ;
vc:hasPart ngm:multimodal-fusion ;
vc:hasPart ngm:sensor-fusion ;
vc:qualityScore "0.87"^^xsd:float ;
vc:relatedTo ngm:ai-regulation ;
vc:relatedTo ngm:cognitive-load ;
vc:relatedTo ngm:cognitive-science ;
vc:relatedTo ngm:digital-health ;
vc:relatedTo ngm:edge-computing ;
vc:relatedTo ngm:emotional-intelligence ;
vc:relatedTo ngm:explainable-ai ;
vc:relatedTo ngm:federated-learning ;
vc:relatedTo ngm:privacy-by-design ;
vc:relatedTo ngm:transfer-learning ;
vc:relatedTo ngm:user-experience-design ;
vc:requires ngm:annotated-dataset ;
vc:requires ngm:annotated-training-data ;
vc:requires ngm:data-labelling ;
vc:requires ngm:machine-learning-discipline ;
vc:requires ngm:sensor-fusion ;
vc:slug "affective-computing-system" ;
vc:sourceDomain "ai" ;
vc:supports ngm:autonomous-vehicle ;
vc:supports ngm:digital-health ;
vc:supports ngm:social-robotics ;
vc:supports ngm:user-experience-design ;
vc:uses ngm:behavioral-modeling ;
vc:uses ngm:computer-vision ;
vc:uses ngm:convolutional-neural-network ;
vc:uses ngm:deep-learning ;
vc:uses ngm:eeg ;
vc:uses ngm:facial-recognition ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:physiological-signal-processing ;
vc:uses ngm:recurrent-neural-network ;
vc:uses ngm:sentiment-analysis ;
vc:uses ngm:speech-recognition ;
vc:uses ngm:transformer-architecture ;
vc:uses ngm:wearable-computing .
ngm:affective-design a skos:Concept ;
rdfs:label "Affective Design"@en .
ngm:affective-dialogue-management a skos:Concept ;
rdfs:label "Affective Dialogue Management"@en .
ngm:affective-language-models a skos:Concept ;
rdfs:label "Affective Language Models"@en .
ngm:affective-response-logs a skos:Concept ;
rdfs:label "Affective Response Logs"@en .
ngm:affective-response-module a skos:Concept ;
rdfs:label "Affective Response Module"@en .
ngm:affective-state-detection a skos:Concept ;
rdfs:label "Affective State Detection"@en .
ngm:affective-state-predictor a skos:Concept ;
rdfs:label "Affective State Predictor"@en .
ngm:affective-tone-module a skos:Concept ;
rdfs:label "Affective Tone Module"@en .
ngm:affinity-diagramming a skos:Concept ;
rdfs:label "Affinity Diagramming"@en .
ngm:affordability-unlock a owl:Class ;
rdfs:comment "An economic mechanism wherein AI-driven cost reductions lower service prices, thereby activating a long-tail market of consumers who previously found those services financially out of reach."@en ;
rdfs:label "Affordability Unlock"@en ;
rdfs:subClassOf ngm:economic-impact-of-ai ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:cost-reduction ;
vc:relatedTo ngm:long-tail-market ;
vc:relatedTo ngm:service-accessibility ;
vc:slug "affordability-unlock" ;
vc:sourceDomain "economics" .
ngm:affordable-access a skos:Concept ;
rdfs:label "Affordable Access"@en .
ngm:affordance a owl:Class ;
rdfs:comment "An affordance is a property of an object or environment that signals the actions it makes possible to a perceiving agent, mediating the relationship between the agent's capabilities and the world. Originating in ecological psychology, the concept was adapted to design to describe how the perceptible features of an interface or physical artefact suggest how it can be used. In spatial and interactive computing, affordances guide users towards available actions, and perceived affordances are deliberately engineered so that controls and gestures feel discoverable and natural."@en ;
rdfs:label "Affordance"@en ;
rdfs:subClassOf ngm:interaction-design ;
rdfs:subClassOf _:r1248 ;
rdfs:subClassOf _:r1249 ;
vc:dependsOn ngm:perception ;
vc:dependsOn ngm:scene-understanding ;
vc:enables ngm:gesture-recognition ;
vc:enables ngm:user-experience ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:perception ;
vc:hasPart ngm:usability ;
vc:isPartOf ngm:human-computer-interaction ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:augmented-reality ;
vc:relatedTo ngm:cognitive-load ;
vc:relatedTo ngm:ergonomics ;
vc:relatedTo ngm:virtual-reality ;
vc:slug "affordance" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:accessibility ;
vc:supports ngm:user-interface ;
vc:uses ngm:user-centred-design .
ngm:affordance-learning a skos:Concept ;
rdfs:label "Affordance Learning"@en .
ngm:age-appropriate-design-code a skos:Concept ;
rdfs:label "Age Appropriate Design Code"@en .
ngm:age-bias a skos:Concept ;
rdfs:label "Age Bias"@en .
ngm:age-verification a owl:Class ;
rdfs:comment "Age verification is a set of technical and procedural mechanisms used to confirm that a user meets a minimum age threshold before accessing restricted digital content or services. It encompasses document-based checks, biometric estimation, and privacy-preserving cryptographic proofs. Regulatory frameworks such as the UK Online Safety Act mandate age verification for platforms hosting harmful content. The field balances effective enforcement against privacy risks and the potential exclusion of legitimate users."@en ;
rdfs:label "Age Verification"@en ;
rdfs:subClassOf ngm:compliance-verification ;
rdfs:subClassOf _:r1250 ;
rdfs:subClassOf _:r1251 ;
vc:bridgesTo ngm:decentralised-identity ;
vc:bridgesTo ngm:self-sovereign-identity ;
vc:enables ngm:access-control ;
vc:enables ngm:content-moderation ;
vc:enables ngm:parental-controls ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:authentication ;
vc:relatedTo ngm:data-protection ;
vc:relatedTo ngm:digital-identity ;
vc:relatedTo ngm:gdpr ;
vc:relatedTo ngm:identity-proofing ;
vc:relatedTo ngm:regulatory-compliance ;
vc:requires ngm:consent-management ;
vc:requires ngm:identity-verification ;
vc:slug "age-verification" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:iso ;
vc:standardizedBy ngm:w3-c-verifiable-credentials ;
vc:supports ngm:data-minimisation ;
vc:supports ngm:online-safety-act-2023 ;
vc:supports ngm:uk-online-safety-act ;
vc:uses ngm:verifiable-credentials ;
vc:uses ngm:zero-knowledge-proof .
ngm:agent a owl:Class ;
rdfs:comment "An autonomous computational or physical entity that perceives its environment, reasons about its perceptions using internal beliefs and goals, and acts to achieve specified objectives—exhibiting autonomy, reactivity, proactivity, and social ability across AI, blockchain, robotics, and metaverse domains."@en ;
rdfs:label "Agent"@en ;
rdfs:subClassOf ngm:autonomous-system ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf _:r1409 ;
rdfs:subClassOf _:r1410 ;
rdfs:subClassOf _:r1411 ;
rdfs:subClassOf _:r1412 ;
rdfs:subClassOf _:r1413 ;
rdfs:subClassOf _:r1414 ;
skos:broader ngm:blockchain ;
vc:bridgesTo ngm:robotic-system ;
vc:bridgesTo ngm:smart-contract ;
vc:dependsOn ngm:knowledge-representation ;
vc:dependsOn ngm:sensor ;
vc:enables ngm:autonomous-decision-making ;
vc:enables ngm:emergent-behavior ;
vc:enables ngm:task-automation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:autonomy-level ;
vc:hasPart ngm:perception-module ;
vc:hasPart ngm:reasoning-engine ;
vc:implements ngm:bdi-model ;
vc:isPartOf ngm:multi-agent-system ;
vc:qualityScore "0.7"^^xsd:float ;
vc:relatedTo ngm:alignment ;
vc:relatedTo ngm:human-in-the-loop ;
vc:relatedTo ngm:objective ;
vc:relatedTo ngm:safety ;
vc:relatedTo ngm:trust ;
vc:requires ngm:ai-agent-system ;
vc:requires ngm:environment ;
vc:requires ngm:goal ;
vc:slug "agent" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:ai-agent-system ;
vc:supports ngm:human-in-the-loop ;
vc:uses ngm:bdi-model ;
vc:uses ngm:goal ;
vc:uses ngm:large-language-model ;
vc:uses ngm:planning ;
vc:uses ngm:reinforcement-learning .
ngm:agent-action-log a skos:Concept ;
rdfs:label "Agent Action Log"@en .
ngm:agent-architecture a skos:Concept ;
rdfs:label "Agent Architecture"@en .
ngm:agent-assist a skos:Concept ;
rdfs:label "Agent Assist"@en .
ngm:agent-autonomy a skos:Concept ;
rdfs:label "Agent Autonomy"@en .
ngm:agent-banking a skos:Concept ;
rdfs:label "Agent Banking"@en .
ngm:agent-based-modelling a owl:Class ;
rdfs:comment "Agent-based modelling (ABM) is a computational simulation methodology in which a system is represented as a collection of autonomous, heterogeneous agents that each follow local behavioural rules and interact with one another and with their environment. The global dynamics of interest — such as market prices, epidemic spread, or traffic congestion — emerge from these micro-level interactions rather than being specified analytically. ABM bridges individual behaviour and system-level phenomena, making it particularly powerful for studying complex adaptive systems where aggregate equations cannot capture heterogeneity or non-linear feedback loops. The approach is distinct from equation-based modelling in that agents are discrete, can differ individually, and can adapt their strategies through reinforcement or learning mechanisms."@en ;
rdfs:label "Agent-Based Modelling"@en ;
rdfs:subClassOf ngm:complex-systems-science ;
rdfs:subClassOf ngm:complexity-science ;
rdfs:subClassOf ngm:computational-modelling ;
rdfs:subClassOf ngm:simulation ;
rdfs:subClassOf _:r1379 ;
rdfs:subClassOf _:r1380 ;
rdfs:subClassOf _:r1381 ;
rdfs:subClassOf _:r1382 ;
rdfs:subClassOf _:r1383 ;
rdfs:subClassOf _:r1384 ;
rdfs:subClassOf _:r1385 ;
rdfs:subClassOf _:r1386 ;
rdfs:subClassOf _:r1387 ;
rdfs:subClassOf _:r1388 ;
rdfs:subClassOf _:r1389 ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:large-language-models ;
vc:bridgesTo ngm:multi-agent-reinforcement-learning ;
vc:bridgesTo ngm:multi-agent-systems ;
vc:bridgesTo ngm:swarm-intelligence ;
vc:contrastsWith ngm:discrete-event-simulation ;
vc:contrastsWith ngm:equation-based-modelling ;
vc:contrastsWith ngm:system-dynamics ;
vc:dependsOn ngm:behavioral-modeling ;
vc:dependsOn ngm:computational-modelling ;
vc:dependsOn ngm:scientific-computing ;
vc:dependsOn ngm:stochastic-process ;
vc:enables ngm:collective-intelligence ;
vc:enables ngm:crowd-simulation ;
vc:enables ngm:economic-model ;
vc:enables ngm:epidemiological-modelling ;
vc:enables ngm:innovation-diffusion ;
vc:enables ngm:policy-simulation ;
vc:enables ngm:social-simulation ;
vc:enables ngm:supply-chain-optimisation ;
vc:enables ngm:uncertainty-quantification ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:autonomous-agent ;
vc:hasPart ngm:emergence ;
vc:hasPart ngm:environment-model ;
vc:hasPart ngm:feedback-loop ;
vc:hasPart ngm:scheduler ;
vc:hasPart ngm:sensitivity-analysis ;
vc:hasPart ngm:stochastic-process ;
vc:implements ngm:artificial-life ;
vc:implements ngm:behavioral-modeling ;
vc:implements ngm:complex-adaptive-systems ;
vc:isPartOf ngm:artificial-intelligence ;
vc:isPartOf ngm:complex-systems-science ;
vc:isPartOf ngm:complexity-science ;
vc:isPartOf ngm:computational-social-science ;
vc:qualityScore "0.87"^^xsd:float ;
vc:relatedTo ngm:agent-based-models ;
vc:relatedTo ngm:artificial-life ;
vc:relatedTo ngm:collective-intelligence ;
vc:relatedTo ngm:emergence ;
vc:relatedTo ngm:feedback-loop ;
vc:relatedTo ngm:game-theory ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:network-science ;
vc:relatedTo ngm:swarm-intelligence ;
vc:requires ngm:discrete-event-simulation ;
vc:requires ngm:scientific-computing ;
vc:requires ngm:simulation ;
vc:requires ngm:stochastic-process ;
vc:slug "agent-based-modelling" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:digital-twin ;
vc:supports ngm:economic-model ;
vc:supports ngm:epidemiological-modelling ;
vc:supports ngm:policy-simulation ;
vc:supports ngm:social-simulation ;
vc:supports ngm:urban-computing ;
vc:uses ngm:cellular-automata ;
vc:uses ngm:genetic-algorithm ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:monte-carlo-simulation ;
vc:uses ngm:network-science ;
vc:uses ngm:parallel-computing ;
vc:uses ngm:reinforcement-learning ;
vc:uses ngm:sensitivity-analysis .
ngm:agent-based-models a owl:Class ;
rdfs:comment "Agent-Based Models (ABMs) are computational simulation frameworks that represent systems as collections of autonomous, heterogeneous agents that interact with one another and their environment according to local rules, allowing complex global behaviours and emergent phenomena to arise from the bottom up without being explicitly programmed at the system level. They are a primary tool in complexity science for studying social, biological, economic, and technical systems."@en ;
rdfs:label "Agent-Based Models"@en ;
rdfs:subClassOf ngm:complex-systems-science ;
rdfs:subClassOf ngm:computational-intelligence ;
rdfs:subClassOf ngm:simulation ;
rdfs:subClassOf _:r1390 ;
rdfs:subClassOf _:r1391 ;
rdfs:subClassOf _:r1392 ;
rdfs:subClassOf _:r1393 ;
rdfs:subClassOf _:r1394 ;
rdfs:subClassOf _:r1395 ;
rdfs:subClassOf _:r1396 ;
rdfs:subClassOf _:r1397 ;
rdfs:subClassOf _:r1398 ;
rdfs:subClassOf _:r1399 ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:large-language-models ;
vc:bridgesTo ngm:multi-agent-reinforcement-learning ;
vc:bridgesTo ngm:multi-agent-systems ;
vc:bridgesTo ngm:swarm-intelligence ;
vc:contrastsWith ngm:discrete-event-simulation ;
vc:contrastsWith ngm:equation-based-modelling ;
vc:contrastsWith ngm:system-dynamics ;
vc:dependsOn ngm:behavioral-modeling ;
vc:dependsOn ngm:complex-adaptive-systems ;
vc:dependsOn ngm:network-science ;
vc:dependsOn ngm:scientific-computing ;
vc:enables ngm:collective-intelligence ;
vc:enables ngm:crowd-simulation ;
vc:enables ngm:economic-model ;
vc:enables ngm:emergence ;
vc:enables ngm:epidemiological-modelling ;
vc:enables ngm:innovation-diffusion ;
vc:enables ngm:policy-simulation ;
vc:enables ngm:social-simulation ;
vc:enables ngm:supply-chain-optimisation ;
vc:enables ngm:uncertainty-quantification ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:autonomous-agent ;
vc:hasPart ngm:environment-model ;
vc:hasPart ngm:feedback-loop ;
vc:hasPart ngm:scheduler ;
vc:hasPart ngm:sensitivity-analysis ;
vc:hasPart ngm:stochastic-process ;
vc:implements ngm:artificial-life ;
vc:implements ngm:behavioral-modeling ;
vc:implements ngm:complex-adaptive-systems ;
vc:isPartOf ngm:artificial-intelligence ;
vc:isPartOf ngm:complex-systems-science ;
vc:isPartOf ngm:complexity-science ;
vc:isPartOf ngm:computational-intelligence ;
vc:qualityScore "0.87"^^xsd:float ;
vc:relatedTo ngm:agent-based-modelling ;
vc:relatedTo ngm:artificial-life ;
vc:relatedTo ngm:collective-intelligence ;
vc:relatedTo ngm:emergence ;
vc:relatedTo ngm:feedback-loop ;
vc:relatedTo ngm:game-theory ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:multi-agent-systems ;
vc:relatedTo ngm:network-science ;
vc:relatedTo ngm:swarm-intelligence ;
vc:requires ngm:computational-modelling ;
vc:requires ngm:scientific-computing ;
vc:requires ngm:simulation ;
vc:requires ngm:stochastic-process ;
vc:slug "agent-based-models" ;
vc:sourceDomain "ai" ;
vc:supports ngm:crowd-simulation ;
vc:supports ngm:digital-twin ;
vc:supports ngm:economic-model ;
vc:supports ngm:policy-simulation ;
vc:supports ngm:urban-computing ;
vc:uses ngm:autonomous-agent ;
vc:uses ngm:behavioral-modeling ;
vc:uses ngm:cellular-automata ;
vc:uses ngm:genetic-algorithm ;
vc:uses ngm:monte-carlo-simulation ;
vc:uses ngm:network-science ;
vc:uses ngm:parallel-computing ;
vc:uses ngm:reinforcement-learning ;
vc:uses ngm:scientific-computing ;
vc:uses ngm:sensitivity-analysis .
ngm:agent-based-simulation a skos:Concept ;
rdfs:label "Agent Based Simulation"@en .
ngm:agent-beacon a skos:Concept ;
rdfs:label "Agent Beacon"@en .
ngm:agent-bench a skos:Concept ;
rdfs:label "Agent Bench"@en .
ngm:agent-capability-scaling a owl:Class ;
rdfs:comment "The empirical trend and theoretical analysis of how the complexity and duration of tasks that AI agents can autonomously complete increase over time with model improvements."@en ;
rdfs:label "Agent Capability Scaling"@en ;
rdfs:subClassOf ngm:agent ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:agent ;
vc:relatedTo ngm:autonomous-decision-making ;
vc:relatedTo ngm:scaling-laws ;
vc:slug "agent-capability-scaling" ;
vc:sourceDomain "artificial-intelligence" .
ngm:agent-card a skos:Concept ;
rdfs:label "Agent Card"@en .
ngm:agent-communication-language a owl:Class ;
rdfs:comment "An Agent Communication Language (ACL) is a formal, standardised message format and semantics that lets autonomous software agents exchange information, requests and commitments independently of their internal implementation. ACLs define performatives (speech acts such as inform, request and propose), a content language and an ontology reference so that interacting agents share a common interpretation of messages. Established examples include FIPA-ACL and KQML."@en ;
rdfs:label "Agent Communication Language"@en ;
rdfs:subClassOf ngm:multi-agent-system ;
rdfs:subClassOf _:r1252 ;
rdfs:subClassOf _:r1253 ;
rdfs:subClassOf _:r1254 ;
vc:bridgesTo ngm:interoperability-protocol ;
vc:enables ngm:interoperability ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:message-passing ;
vc:implements ngm:fipa ;
vc:isPartOf ngm:multi-agent-system ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-integration ;
vc:relatedTo ngm:linked-data ;
vc:relatedTo ngm:network-protocol ;
vc:requires ngm:ontology ;
vc:requires ngm:semantic-interoperability ;
vc:slug "agent-communication-language" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:fipa ;
vc:supports ngm:decision-making ;
vc:uses ngm:api .
ngm:agent-communication-protocol a owl:Class ;
rdfs:comment "An Agent Communication Protocol is a formalised specification governing the syntax, semantics, and pragmatics of message exchange between autonomous software agents, enabling them to coordinate actions, share information, delegate tasks, and negotiate goals across heterogeneous runtime environments. Such protocols define the speech act primitives, message envelope formats, conversation policies, and error-handling procedures that agents must implement to participate in a multi-agent system."@en ;
rdfs:label "Agent Communication Protocol"@en ;
rdfs:subClassOf ngm:coordination-protocol ;
rdfs:subClassOf ngm:distributed-systems ;
rdfs:subClassOf ngm:interoperability ;
rdfs:subClassOf _:r1255 ;
rdfs:subClassOf _:r1256 ;
rdfs:subClassOf _:r1257 ;
rdfs:subClassOf _:r1258 ;
rdfs:subClassOf _:r1259 ;
rdfs:subClassOf _:r1260 ;
rdfs:subClassOf _:r1261 ;
rdfs:subClassOf _:r1262 ;
rdfs:subClassOf _:r1263 ;
rdfs:subClassOf _:r1264 ;
rdfs:subClassOf _:r1265 ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:bridgesTo ngm:event-driven-architecture ;
vc:bridgesTo ngm:multi-agent-reinforcement-learning ;
vc:bridgesTo ngm:robotics ;
vc:bridgesTo ngm:semantic-web-linked-data-standard ;
vc:contrastsWith ngm:agent ;
vc:contrastsWith ngm:microservices ;
vc:contrastsWith ngm:remote-procedure-call ;
vc:dependsOn ngm:concurrent-programming ;
vc:dependsOn ngm:distributed-systems ;
vc:dependsOn ngm:game-theory ;
vc:enables ngm:agentic-workflow ;
vc:enables ngm:autonomous-agent ;
vc:enables ngm:autonomous-task-execution ;
vc:enables ngm:capability-advertisement ;
vc:enables ngm:distributed-collaboration ;
vc:enables ngm:inter-agent-communication ;
vc:enables ngm:multi-agent-system ;
vc:enables ngm:negotiation ;
vc:enables ngm:task-delegation ;
vc:enables ngm:task-planning ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:capability-advertisement ;
vc:hasPart ngm:error-handling ;
vc:hasPart ngm:json-ld ;
vc:hasPart ngm:message-passing ;
vc:hasPart ngm:negotiation ;
vc:hasPart ngm:ontology ;
vc:hasPart ngm:speech-act-theory ;
vc:hasPart ngm:trust-management ;
vc:implements ngm:agent-network-protocol ;
vc:implements ngm:agent-to-agent-protocol ;
vc:implements ngm:contract-net-protocol ;
vc:implements ngm:fipa-acl ;
vc:implements ngm:kqml ;
vc:implements ngm:model-context-protocol ;
vc:qualityScore "0.91"^^xsd:float ;
vc:relatedTo ngm:agent-based-modelling ;
vc:relatedTo ngm:agent-to-agent-protocol ;
vc:relatedTo ngm:auction-mechanism ;
vc:relatedTo ngm:autonomous-agent ;
vc:relatedTo ngm:bdi-architecture ;
vc:relatedTo ngm:collective-decision-making ;
vc:relatedTo ngm:decentralised-identifier ;
vc:relatedTo ngm:distributed-artificial-intelligence ;
vc:relatedTo ngm:emergent-behavior ;
vc:relatedTo ngm:event-driven-architecture ;
vc:relatedTo ngm:formal-specification ;
vc:relatedTo ngm:game-theory ;
vc:relatedTo ngm:interoperability ;
vc:relatedTo ngm:knowledge-representation ;
vc:relatedTo ngm:kqml ;
vc:relatedTo ngm:large-language-model ;
vc:relatedTo ngm:linux-foundation ;
vc:relatedTo ngm:model-context-protocol ;
vc:relatedTo ngm:multi-agent-reinforcement-learning ;
vc:relatedTo ngm:oauth-2-0 ;
vc:relatedTo ngm:open-agent-standard ;
vc:relatedTo ngm:process-algebra ;
vc:relatedTo ngm:reinforcement-learning ;
vc:relatedTo ngm:swarm-intelligence ;
vc:relatedTo ngm:task-planning ;
vc:requires ngm:distributed-systems ;
vc:requires ngm:ontology ;
vc:requires ngm:trust-management ;
vc:slug "agent-communication-protocol" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:fipa ;
vc:standardizedBy ngm:linux-foundation ;
vc:standardizedBy ngm:w3-c ;
vc:supports ngm:algorithmic-trading ;
vc:supports ngm:capability-advertisement ;
vc:supports ngm:error-handling ;
vc:supports ngm:negotiation ;
vc:supports ngm:robotics ;
vc:supports ngm:smart-grid ;
vc:supports ngm:software-engineering-agents ;
vc:supports ngm:warehouse-automation ;
vc:uses ngm:concurrent-programming ;
vc:uses ngm:decentralised-identifier ;
vc:uses ngm:http-protocol ;
vc:uses ngm:json-data-interchange-format-rpc-2-0 ;
vc:uses ngm:json-ld ;
vc:uses ngm:message-passing ;
vc:uses ngm:oauth-2-0 ;
vc:uses ngm:ontology ;
vc:uses ngm:speech-act-theory ;
vc:uses ngm:web-socket .
ngm:agent-communication-protocol-ibm-acp a skos:Concept ;
rdfs:label "Agent Communication Protocol Ibm Acp"@en .
ngm:agent-development-sdks a owl:Class ;
rdfs:comment "Official vendor SDKs and libraries for building custom AI agents with built-in tools, MCP support, session management, and deployment infrastructure — includes Claude Agent SDK, Google ADK, strands-agents, pydantic-ai, Composio, and SWE-agent."@en ;
rdfs:label "Agent Development SDKs"@en ;
rdfs:subClassOf ngm:agent-frameworks ;
rdfs:subClassOf ngm:agent-harness ;
rdfs:subClassOf ngm:llm-orchestration ;
rdfs:subClassOf _:r1266 ;
rdfs:subClassOf _:r1267 ;
rdfs:subClassOf _:r1268 ;
rdfs:subClassOf _:r1269 ;
rdfs:subClassOf _:r1270 ;
rdfs:subClassOf _:r1271 ;
rdfs:subClassOf _:r1272 ;
rdfs:subClassOf _:r1273 ;
rdfs:subClassOf _:r1274 ;
rdfs:subClassOf _:r1275 ;
rdfs:subClassOf _:r1276 ;
rdfs:subClassOf _:r1277 ;
vc:contrastsWith ngm:agent-frameworks ;
vc:contrastsWith ngm:lang-graph ;
vc:contrastsWith ngm:multi-agent-orchestration-frameworks ;
vc:dependsOn ngm:agent-execution-sandboxes ;
vc:dependsOn ngm:agent-harness ;
vc:dependsOn ngm:external-ai-harness ;
vc:dependsOn ngm:internal-ai-harness ;
vc:dependsOn ngm:large-language-model ;
vc:dependsOn ngm:model-context-protocol ;
vc:enables ngm:agentic-ai ;
vc:enables ngm:ai-safety ;
vc:enables ngm:autonomous-coding ;
vc:enables ngm:browser-automation ;
vc:enables ngm:computer-use ;
vc:enables ngm:human-in-the-loop ;
vc:enables ngm:multi-agent-orchestration-frameworks ;
vc:enables ngm:retrieval-augmented-generation ;
vc:enables ngm:workflow-automation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:agent-runtime ;
vc:hasPart ngm:claude-agent-sdk ;
vc:hasPart ngm:composio ;
vc:hasPart ngm:google-adk ;
vc:hasPart ngm:mastra ;
vc:hasPart ngm:memory-store ;
vc:hasPart ngm:observability ;
vc:hasPart ngm:openai-research-organisation-agents-sdk ;
vc:hasPart ngm:pydantic-ai ;
vc:hasPart ngm:strands-agents ;
vc:hasPart ngm:swe-agent ;
vc:hasPart ngm:tool-registry ;
vc:implements ngm:a2-a-protocol ;
vc:implements ngm:agent-communication-protocol ;
vc:implements ngm:agent-to-agent-protocol ;
vc:implements ngm:chain-of-thought ;
vc:implements ngm:plan-and-execute-pattern ;
vc:implements ngm:re-act-pattern ;
vc:implements ngm:structured-output ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:agent-evaluation-benchmarks ;
vc:relatedTo ngm:agent-execution-sandboxes ;
vc:relatedTo ngm:agent-orchestrator ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:ai-agent-payments ;
vc:relatedTo ngm:autonomous-ai-agents ;
vc:relatedTo ngm:multi-agent-orchestration-frameworks ;
vc:requires ngm:agent-execution-sandboxes ;
vc:requires ngm:context-window ;
vc:requires ngm:function-calling ;
vc:requires ngm:large-language-model ;
vc:requires ngm:model-context-protocol ;
vc:requires ngm:persistence-layer ;
vc:requires ngm:tool-calling-api ;
vc:requires ngm:tool-use ;
vc:slug "agent-development-sdks" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:a2-a-protocol ;
vc:standardizedBy ngm:agent-communication-protocol ;
vc:standardizedBy ngm:linux-foundation ;
vc:standardizedBy ngm:model-context-protocol ;
vc:supports ngm:agent-evaluation-benchmarks ;
vc:supports ngm:agentic-ai ;
vc:supports ngm:ai-agent-payments ;
vc:supports ngm:ai-safety ;
vc:supports ngm:multi-agent-orchestration-frameworks ;
vc:supports ngm:observability ;
vc:uses ngm:agent-to-agent-protocol ;
vc:uses ngm:function-calling ;
vc:uses ngm:model-context-protocol ;
vc:uses ngm:persistence-layer ;
vc:uses ngm:prompt-template ;
vc:uses ngm:structured-output ;
vc:uses ngm:tool-calling-api .
ngm:agent-ecosystem a owl:Class ;
rdfs:comment "A coordinated network of specialized AI agents that interact and share context to solve complex, multi-faceted problems."@en ;
rdfs:label "Agent Ecosystem"@en ;
rdfs:subClassOf ngm:agents ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:agents ;
vc:relatedTo ngm:multi-agent-system ;
vc:slug "agent-ecosystem" ;
vc:sourceDomain "artificial-intelligence" .
ngm:agent-environment a skos:Concept ;
rdfs:label "Agent Environment"@en .
ngm:agent-evaluation-benchmarks a owl:Class ;
rdfs:comment "Standardised benchmark suites and evaluation frameworks for measuring autonomous agent capabilities across software engineering, web navigation, reasoning, and general task completion — includes SWE-bench, WebArena, ARC-AGI-2, inspect_ai, AgentBench, and VitaBench."@en ;
rdfs:label "Agent Evaluation Benchmarks"@en ;
rdfs:subClassOf ngm:agent-harness ;
rdfs:subClassOf ngm:evaluation-harness ;
rdfs:subClassOf ngm:llm-evaluation ;
rdfs:subClassOf _:r1278 ;
rdfs:subClassOf _:r1279 ;
rdfs:subClassOf _:r1280 ;
rdfs:subClassOf _:r1281 ;
rdfs:subClassOf _:r1282 ;
rdfs:subClassOf _:r1283 ;
rdfs:subClassOf _:r1284 ;
rdfs:subClassOf _:r1285 ;
vc:contrastsWith ngm:llm-evaluation ;
vc:contrastsWith ngm:reward-hacking ;
vc:contrastsWith ngm:static-nlp-benchmarks ;
vc:dependsOn ngm:agent-execution-sandboxes ;
vc:dependsOn ngm:agent-harness ;
vc:dependsOn ngm:external-ai-harness ;
vc:dependsOn ngm:internal-ai-harness ;
vc:dependsOn ngm:large-language-model ;
vc:enables ngm:agentic-ai ;
vc:enables ngm:ai-safety ;
vc:enables ngm:autonomous-coding ;
vc:enables ngm:browser-automation ;
vc:enables ngm:computer-use ;
vc:enables ngm:human-in-the-loop ;
vc:enables ngm:responsible-scaling-policy ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:agent-bench ;
vc:hasPart ngm:agentbench ;
vc:hasPart ngm:arc-agi ;
vc:hasPart ngm:gaia-benchmark ;
vc:hasPart ngm:inspect-ai ;
vc:hasPart ngm:metr-hcast ;
vc:hasPart ngm:osworld ;
vc:hasPart ngm:swe-bench ;
vc:hasPart ngm:tau-bench ;
vc:hasPart ngm:terminal-bench ;
vc:hasPart ngm:vita-bench ;
vc:hasPart ngm:vitabench ;
vc:hasPart ngm:web-arena ;
vc:hasPart ngm:webarena ;
vc:implements ngm:functional-verification ;
vc:implements ngm:llm-evaluation ;
vc:implements ngm:plan-and-execute-pattern ;
vc:implements ngm:reinforcement-learning ;
vc:implements ngm:safety-assessment ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:agent-development-sdks ;
vc:relatedTo ngm:agent-frameworks ;
vc:relatedTo ngm:ai-agent-system ;
vc:relatedTo ngm:autonomous-agent ;
vc:relatedTo ngm:evaluation-harness ;
vc:relatedTo ngm:multi-agent-orchestration-frameworks ;
vc:requires ngm:agent-execution-sandboxes ;
vc:requires ngm:agent-harness ;
vc:requires ngm:chain-of-thought ;
vc:requires ngm:foundation-model ;
vc:requires ngm:large-language-model ;
vc:requires ngm:re-act-pattern ;
vc:requires ngm:tool-use ;
vc:slug "agent-evaluation-benchmarks" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:ai-safety-institute ;
vc:standardizedBy ngm:inspect-ai ;
vc:standardizedBy ngm:metr-hcast ;
vc:supports ngm:agent-development-sdks ;
vc:supports ngm:agent-frameworks ;
vc:supports ngm:agentic-ai ;
vc:supports ngm:ai-safety ;
vc:supports ngm:multi-agent-orchestration-frameworks ;
vc:supports ngm:regulatory-compliance ;
vc:uses ngm:agent-execution-sandboxes ;
vc:uses ngm:chain-of-thought ;
vc:uses ngm:docker-containerisation-platform ;
vc:uses ngm:model-context-protocol ;
vc:uses ngm:re-act-pattern ;
vc:uses ngm:reinforcement-learning .
ngm:agent-event-stream a owl:Class ;
rdfs:comment "A real-time telemetry stream (surface S6) that emits ActivityStream|ActivityStreams-based JSON-LD events for agent lifecycle events (birth, startup, activity, completion, error, termination) via WebSocket, Nostr relay, or message queue, enabling external monitoring systems, dashboards, and or..."@en ;
rdfs:label "Agent Event Stream"@en ;
rdfs:subClassOf ngm:ai-infrastructure ;
rdfs:subClassOf _:r1286 ;
rdfs:subClassOf _:r1287 ;
rdfs:subClassOf _:r1288 ;
rdfs:subClassOf _:r1289 ;
rdfs:subClassOf _:r1290 ;
vc:bridgesTo ngm:data-analytics-platform ;
vc:bridgesTo ngm:monitoring-system ;
vc:bridgesTo ngm:orchestration-system ;
vc:enables ngm:anomaly-detection ;
vc:enables ngm:automated-alerting ;
vc:enables ngm:fleet-observability ;
vc:enables ngm:real-time-monitoring ;
vc:enables ngm:work-tracking ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:event-emission ;
vc:hasPart ngm:event-filtering ;
vc:hasPart ngm:event-indexing ;
vc:hasPart ngm:event-subscription ;
vc:hasPart ngm:real-time-streaming ;
vc:implements ngm:activitystreams-2-0 ;
vc:implements ngm:json-data-interchange-format-ld-1-1 ;
vc:implements ngm:w3c-event-streams ;
vc:qualityScore "0.85"^^xsd:float ;
vc:requires ngm:activitystreams-vocabulary ;
vc:requires ngm:event-schemas ;
vc:requires ngm:json-data-interchange-format-ld-1-1 ;
vc:requires ngm:web-socket ;
vc:slug "agent-event-stream" ;
vc:sourceDomain "artificial-intelligence" .
ngm:agent-execution-sandboxes a owl:Class ;
rdfs:comment "Isolated execution environments providing secure, ephemeral containers and virtual machines for AI-generated code execution, tool use, and autonomous agent operation — including E2B, Daytona, Docker MCP Gateway, Cloudflare Sandboxes, Modal, Vercel Sandbox, and Fly Machines — with hardware-level isolation via Firecracker microVMs, gVisor syscall interception, or Kata Containers to prevent escape to host infrastructure."@en ;
rdfs:label "Agent Execution Sandboxes"@en ;
rdfs:subClassOf ngm:agent-harness ;
rdfs:subClassOf ngm:ai-infrastructure ;
rdfs:subClassOf ngm:containerisation ;
rdfs:subClassOf _:r1291 ;
rdfs:subClassOf _:r1292 ;
rdfs:subClassOf _:r1293 ;
rdfs:subClassOf _:r1294 ;
rdfs:subClassOf _:r1295 ;
rdfs:subClassOf _:r1296 ;
rdfs:subClassOf _:r1297 ;
rdfs:subClassOf _:r1298 ;
rdfs:subClassOf _:r1299 ;
rdfs:subClassOf _:r1300 ;
rdfs:subClassOf _:r1301 ;
vc:bridgesTo ngm:agent-development-sdks ;
vc:bridgesTo ngm:ai-safety ;
vc:bridgesTo ngm:human-in-the-loop ;
vc:bridgesTo ngm:prompt-injection ;
vc:contrastsWith ngm:container-orchestration ;
vc:contrastsWith ngm:internal-ai-harness ;
vc:contrastsWith ngm:regulatory-sandbox ;
vc:dependsOn ngm:cloud-computing ;
vc:dependsOn ngm:container-orchestration ;
vc:dependsOn ngm:docker-containerisation-platform ;
vc:dependsOn ngm:microservices-architecture ;
vc:dependsOn ngm:serverless-architecture ;
vc:enables ngm:agent-evaluation-benchmarks ;
vc:enables ngm:agentic-ai ;
vc:enables ngm:agentic-workflow ;
vc:enables ngm:autonomous-agent ;
vc:enables ngm:autonomous-coding ;
vc:enables ngm:multi-agent-systems ;
vc:enables ngm:retrieval-augmented-generation ;
vc:enables ngm:terminal-coding-agents ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:agent-memory ;
vc:hasPart ngm:api-gateway ;
vc:hasPart ngm:code-execution ;
vc:hasPart ngm:container-runtime ;
vc:hasPart ngm:mcp-server ;
vc:hasPart ngm:open-container-initiative ;
vc:implements ngm:function-calling ;
vc:implements ngm:mcp-server ;
vc:implements ngm:model-context-protocol ;
vc:implements ngm:open-container-initiative ;
vc:implements ngm:tool-call-loop ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:agent-development-sdks ;
vc:relatedTo ngm:agentic-rag ;
vc:relatedTo ngm:decentralised-agentic-infrastructure-stack ;
vc:relatedTo ngm:edge-computing ;
vc:relatedTo ngm:llm-application-frameworks ;
vc:relatedTo ngm:model-context-protocol ;
vc:relatedTo ngm:multi-agent-orchestration-frameworks ;
vc:relatedTo ngm:multi-agent-systems ;
vc:relatedTo ngm:swe-bench ;
vc:relatedTo ngm:terminal-coding-agents ;
vc:relatedTo ngm:vision-claw-agentic-container ;
vc:requires ngm:cloud-computing ;
vc:requires ngm:containerisation ;
vc:requires ngm:docker-containerisation-platform ;
vc:requires ngm:open-container-initiative ;
vc:requires ngm:tool-use ;
vc:slug "agent-execution-sandboxes" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:model-context-protocol ;
vc:standardizedBy ngm:open-container-initiative ;
vc:supports ngm:agent-evaluation-benchmarks ;
vc:supports ngm:agentic-ai ;
vc:supports ngm:ai-safety ;
vc:supports ngm:human-in-the-loop ;
vc:supports ngm:prompt-injection ;
vc:supports ngm:swe-bench ;
vc:uses ngm:agent-loop ;
vc:uses ngm:external-ai-harness ;
vc:uses ngm:function-calling ;
vc:uses ngm:mcp-client ;
vc:uses ngm:mcp-server ;
vc:uses ngm:tool-call-loop ;
vc:uses ngm:vector-database .
ngm:agent-frameworks a owl:Class ;
rdfs:comment "Agent Frameworks are software libraries, runtimes, and orchestration platforms that compose large language models (LLMs) with tool-use, memory, planning, and inter-agent communication into autonomous or semi-autonomous systems capable of multi-step goal pursuit, encompassing single-agent harnesse..."@en ;
rdfs:label "Agent Frameworks"@en ;
rdfs:subClassOf ngm:ai-agent-system ;
rdfs:subClassOf ngm:autonomous-system ;
rdfs:subClassOf ngm:llm-orchestration ;
rdfs:subClassOf ngm:software-framework ;
rdfs:subClassOf ngm:workflow-engine ;
rdfs:subClassOf _:r1302 ;
rdfs:subClassOf _:r1303 ;
rdfs:subClassOf _:r1304 ;
rdfs:subClassOf _:r1305 ;
rdfs:subClassOf _:r1306 ;
rdfs:subClassOf _:r1307 ;
rdfs:subClassOf _:r1308 ;
rdfs:subClassOf _:r1309 ;
rdfs:subClassOf _:r1310 ;
rdfs:subClassOf _:r1311 ;
rdfs:subClassOf _:r1312 ;
vc:bridgesTo ngm:ai-infrastructure ;
vc:bridgesTo ngm:workflow-engine ;
vc:contrastsWith ngm:bpmn-orchestration ;
vc:contrastsWith ngm:deterministic-dag-pipeline ;
vc:contrastsWith ngm:robotic-process-automation ;
vc:contrastsWith ngm:rule-based-expert-system ;
vc:contrastsWith ngm:workflow-engine ;
vc:dependsOn ngm:embedding-model ;
vc:dependsOn ngm:function-calling ;
vc:dependsOn ngm:inference ;
vc:dependsOn ngm:json-data-interchange-format-schema ;
vc:dependsOn ngm:structured-output ;
vc:dependsOn ngm:tool-calling-api ;
vc:dependsOn ngm:vector-database ;
vc:enables ngm:autonomous-coding ;
vc:enables ngm:browser-automation ;
vc:enables ngm:computer-use ;
vc:enables ngm:conversational-ai ;
vc:enables ngm:multi-agent-collaboration ;
vc:enables ngm:scientific-discovery ;
vc:enables ngm:tool-augmented-reasoning ;
vc:enables ngm:workflow-automation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:agent-runtime ;
vc:hasPart ngm:evaluator-module ;
vc:hasPart ngm:executor-module ;
vc:hasPart ngm:hook-system ;
vc:hasPart ngm:memory-store ;
vc:hasPart ngm:planner-module ;
vc:hasPart ngm:prompt-template ;
vc:hasPart ngm:state-graph ;
vc:hasPart ngm:tool-registry ;
vc:hasPart ngm:trace-logger ;
vc:implements ngm:chain-of-thought ;
vc:implements ngm:mesh-topology ;
vc:implements ngm:network-topology ;
vc:implements ngm:plan-and-execute-pattern ;
vc:implements ngm:re-act-pattern ;
vc:implements ngm:reflexion ;
vc:implements ngm:self-consistency ;
vc:implements ngm:toolformer-pattern ;
vc:implements ngm:tree-of-thoughts ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:large-scale-pretrained-foundation-model ;
vc:relatedTo ngm:llm-evaluation ;
vc:relatedTo ngm:prompt-engineering ;
vc:relatedTo ngm:retrieval-augmented-generation ;
vc:relatedTo ngm:tool-use ;
vc:requires ngm:context-window ;
vc:requires ngm:inference-endpoint ;
vc:requires ngm:large-language-model ;
vc:requires ngm:large-language-models ;
vc:requires ngm:observability ;
vc:requires ngm:persistence-layer ;
vc:requires ngm:tool-use ;
vc:slug "agent-frameworks" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:agent-communication-protocol ;
vc:standardizedBy ngm:agent-to-agent-protocol ;
vc:standardizedBy ngm:agntcy-collective ;
vc:standardizedBy ngm:model-context-protocol ;
vc:supports ngm:coding-assistant ;
vc:supports ngm:customer-service-agent ;
vc:supports ngm:data-analysis-agent ;
vc:supports ngm:rag-pipeline ;
vc:supports ngm:research-assistant ;
vc:supports ngm:workflow-automation ;
vc:uses ngm:a2-a-protocol ;
vc:uses ngm:acp-protocol ;
vc:uses ngm:function-calling ;
vc:uses ngm:json-data-interchange-format-rpc ;
vc:uses ngm:model-control-protocols-like-mcp ;
vc:uses ngm:open-api-specification ;
vc:uses ngm:server-sent-events .
ngm:agent-handoff a owl:Class ;
rdfs:comment "The orchestration primitive by which one agent transfers control of a conversation or task to another agent, passing along the accumulated context, goal, and constraints so the receiving agent can continue the work with its own specialised tools and instructions. A handoff reassigns responsibility rather than merely requesting a result: control does not automatically return to the sender, and the receiver becomes the active locus of decision-making, which is what distinguishes handoff-based routing from a simple tool call or a blocking sub-task."@en ;
rdfs:label "Agent Handoff"@en ;
rdfs:subClassOf ngm:multi-agent-orchestration ;
rdfs:subClassOf ngm:multiagentorchestration ;
rdfs:subClassOf _:r1313 ;
rdfs:subClassOf _:r1314 ;
vc:enables ngm:agentic-workflow ;
vc:enables ngm:agenticworkflow ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:llm-orchestration ;
vc:relatedTo ngm:llmorchestration ;
vc:requires ngm:multi-agent-system ;
vc:slug "agent-handoff" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:task-delegation ;
vc:uses ngm:taskdelegation .
ngm:agent-harness a owl:Class ;
rdfs:comment "A runtime framework that turns model inference into agent action by managing the tool-call loop, approval gates, context routing, execution lifecycle, and failure recovery — the model thinks, the harness decides what that thinking is allowed to touch."@en ;
rdfs:label "Agent Harness"@en ;
rdfs:subClassOf ngm:agentic-ai ;
rdfs:subClassOf ngm:ai-agent-system ;
rdfs:subClassOf ngm:ai-infrastructure ;
rdfs:subClassOf ngm:autonomous-agent ;
rdfs:subClassOf _:r1315 ;
rdfs:subClassOf _:r1316 ;
rdfs:subClassOf _:r1317 ;
rdfs:subClassOf _:r1318 ;
rdfs:subClassOf _:r1319 ;
rdfs:subClassOf _:r1320 ;
rdfs:subClassOf _:r1321 ;
rdfs:subClassOf _:r1322 ;
rdfs:subClassOf _:r1323 ;
rdfs:subClassOf _:r1324 ;
rdfs:subClassOf _:r1325 ;
rdfs:subClassOf _:r1326 ;
rdfs:subClassOf _:r1327 ;
rdfs:subClassOf _:r1328 ;
rdfs:subClassOf _:r1329 ;
rdfs:subClassOf _:r1330 ;
rdfs:subClassOf _:r1331 ;
vc:contrastsWith ngm:agent-runtime ;
vc:contrastsWith ngm:evaluation-harness ;
vc:contrastsWith ngm:workflow-engine ;
vc:dependsOn ngm:agent-memory ;
vc:dependsOn ngm:agent-runtime ;
vc:dependsOn ngm:context-window ;
vc:dependsOn ngm:credential-management ;
vc:dependsOn ngm:sandboxed-code-execution ;
vc:dependsOn ngm:state-persistence ;
vc:dependsOn ngm:tool-registry ;
vc:enables ngm:agentic-ai ;
vc:enables ngm:autonomous-agent ;
vc:enables ngm:durable-execution ;
vc:enables ngm:multi-agent-systems ;
vc:enables ngm:software-development-automation ;
vc:enables ngm:task-automation ;
vc:enables ngm:workflow-orchestration ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:agent-evaluation-benchmarks ;
vc:hasPart ngm:agent-execution-sandboxes ;
vc:hasPart ngm:external-ai-harness ;
vc:hasPart ngm:harness-configuration-packs ;
vc:hasPart ngm:ide-coding-agents ;
vc:hasPart ngm:internal-ai-harness ;
vc:hasPart ngm:multi-agent-orchestration-frameworks ;
vc:hasPart ngm:personal-agent-runtimes ;
vc:hasPart ngm:progressive-disclosure-harnesses ;
vc:hasPart ngm:terminal-coding-agents ;
vc:implements ngm:chain-of-thought ;
vc:implements ngm:checkpointing ;
vc:implements ngm:human-in-the-loop ;
vc:implements ngm:plan-and-execute ;
vc:implements ngm:re-act-pattern ;
vc:implements ngm:reflexion ;
vc:qualityScore "0.91"^^xsd:float ;
vc:relatedTo ngm:agent-communication-protocol ;
vc:relatedTo ngm:agent-evaluation-benchmarks ;
vc:relatedTo ngm:agent-runtime ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:aws-bedrock-agentcore ;
vc:relatedTo ngm:lang-graph ;
vc:relatedTo ngm:multi-agent-orchestration-frameworks ;
vc:relatedTo ngm:prompt-injection ;
vc:relatedTo ngm:temporal ;
vc:relatedTo ngm:terminal-coding-agents ;
vc:requires ngm:agent-loop ;
vc:requires ngm:context-window ;
vc:requires ngm:foundation-model ;
vc:requires ngm:function-calling ;
vc:requires ngm:large-language-models ;
vc:requires ngm:model-context-protocol ;
vc:requires ngm:tool-use ;
vc:slug "agent-harness" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:agent-to-agent-protocol ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:model-context-protocol ;
vc:supports ngm:agent-development-sdks ;
vc:supports ngm:agent-orchestrator ;
vc:supports ngm:ai-alignment ;
vc:supports ngm:ai-safety ;
vc:supports ngm:human-in-the-loop ;
vc:uses ngm:agent-memory ;
vc:uses ngm:function-calling ;
vc:uses ngm:observability ;
vc:uses ngm:open-telemetry ;
vc:uses ngm:rate-limiting ;
vc:uses ngm:retrieval-augmented-generation ;
vc:uses ngm:sandboxed-code-execution .
ngm:agent-identity a owl:Class ;
rdfs:comment "Agent identity is the set of attributes, credentials, and cryptographic material that uniquely identifies an autonomous software agent and allows other parties to authenticate it, attribute its actions, and decide what it may do. It extends identity management from human and device contexts to AI agents that act on a user's behalf, enabling verifiable accountability across the emerging agentic internet. Robust agent identity typically combines decentralised identifiers, verifiable credentials, and key management."@en ;
rdfs:label "Agent Identity"@en ;
rdfs:subClassOf ngm:decentralized-identity ;
rdfs:subClassOf ngm:identity-management ;
rdfs:subClassOf ngm:trust-framework ;
rdfs:subClassOf _:r1332 ;
rdfs:subClassOf _:r1333 ;
rdfs:subClassOf _:r1334 ;
rdfs:subClassOf _:r1335 ;
rdfs:subClassOf _:r1336 ;
rdfs:subClassOf _:r1337 ;
rdfs:subClassOf _:r1338 ;
rdfs:subClassOf _:r1339 ;
rdfs:subClassOf _:r1340 ;
rdfs:subClassOf _:r1341 ;
rdfs:subClassOf _:r1342 ;
vc:bridgesTo ngm:ai-agent ;
vc:bridgesTo ngm:amazon-bedrock ;
vc:bridgesTo ngm:autonomous-agent ;
vc:bridgesTo ngm:microsoft-entra ;
vc:contrastsWith ngm:api-key-authentication ;
vc:contrastsWith ngm:centralized-identity-provider ;
vc:contrastsWith ngm:single-sign-on ;
vc:dependsOn ngm:artificial-intelligence ;
vc:dependsOn ngm:foundation-model ;
vc:dependsOn ngm:large-language-models ;
vc:enables ngm:access-control ;
vc:enables ngm:accountability ;
vc:enables ngm:agentic-workflow ;
vc:enables ngm:authorisation ;
vc:enables ngm:delegation ;
vc:enables ngm:non-repudiation ;
vc:enables ngm:tool-use ;
vc:enables ngm:trust ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:audit-trail ;
vc:hasPart ngm:capability-token ;
vc:hasPart ngm:did ;
vc:hasPart ngm:digital-signature ;
vc:hasPart ngm:key-management ;
vc:hasPart ngm:verifiable-credentials ;
vc:implements ngm:did ;
vc:implements ngm:oauth ;
vc:implements ngm:open-id-connect ;
vc:implements ngm:self-sovereign-identity ;
vc:implements ngm:spiffe ;
vc:isPartOf ngm:agentic-internet ;
vc:isPartOf ngm:identity-management ;
vc:qualityScore "0.88"^^xsd:float ;
vc:relatedTo ngm:agent-loop ;
vc:relatedTo ngm:agent-memory ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:agentic-internet ;
vc:relatedTo ngm:prompt-injection ;
vc:relatedTo ngm:provenance ;
vc:relatedTo ngm:single-sign-on ;
vc:requires ngm:authentication ;
vc:requires ngm:cryptographic-infrastructure ;
vc:requires ngm:cryptographic-proof ;
vc:requires ngm:key-management ;
vc:requires ngm:trust-framework ;
vc:slug "agent-identity" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:agent-to-agent-protocol ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:ietf ;
vc:standardizedBy ngm:model-context-protocol ;
vc:standardizedBy ngm:w3-c ;
vc:supports ngm:ai-safety ;
vc:supports ngm:human-in-the-loop ;
vc:supports ngm:multi-agent-system ;
vc:supports ngm:sandboxing ;
vc:supports ngm:zero-trust-architecture ;
vc:uses ngm:decentralized-identity ;
vc:uses ngm:oauth ;
vc:uses ngm:open-id-connect ;
vc:uses ngm:spiffe .
ngm:agent-layer a owl:Class ;
rdfs:comment "The Agent Layer is the stratum that hosts autonomous entities capable of perceiving, deciding, and acting toward goals. It sits above control and inference strata that supply its capabilities and below coordination and application strata that direct collectives of agents. It contains agent policies, goal representations, memory, and decision loops."@en ;
rdfs:label "Agent Layer"@en ;
rdfs:subClassOf ngm:ai-model-architecture ;
rdfs:subClassOf ngm:owl-thing ;
rdfs:subClassOf _:r1343 ;
rdfs:subClassOf _:r1344 ;
skos:broader ngm:ai-model-architecture ;
vc:bridgesTo ngm:autonomous-agent ;
vc:bridgesTo ngm:reinforcement-learning ;
vc:enables ngm:application-layer ;
vc:enables ngm:coordination-layer ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:control-layer ;
vc:requires ngm:inference-layer ;
vc:slug "agent-layer" ;
vc:sourceDomain "ai" .
ngm:agent-loop a owl:Class ;
rdfs:comment "The agent loop is the repeating control cycle — observe, plan, act, evaluate — through which an autonomous agent perceives its environment, selects a next action or tool call, executes it, and incorporates the result before repeating. It is the core execution pattern underlying agentic systems, terminal coding agents, and retrieval-augmented reasoning, continuing until a termination condition such as task completion or a step budget is reached. The loop's design governs how an agent balances exploration, tool use, and convergence toward a goal."@en ;
rdfs:label "Agent Loop"@en ;
rdfs:subClassOf ngm:agent-harness ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:agent-harness ;
vc:qualityScore "0.6"^^xsd:float ;
vc:slug "agent-loop" ;
vc:sourceDomain "ai" .
ngm:agent-management a owl:Class ;
rdfs:comment "The skills and practices required to oversee, coordinate, and evaluate AI agents, distinct from traditional software or human management."@en ;
rdfs:label "Agent Management"@en ;
rdfs:subClassOf ngm:ai-technique ;
skos:broader ngm:ai-technique ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:knowledge-work-primitive ;
vc:slug "agent-management" ;
vc:sourceDomain "artificial-intelligence" .
ngm:agent-marketplace a skos:Concept ;
rdfs:label "Agent Marketplace"@en .
ngm:agent-memory a owl:Class ;
rdfs:comment "Agent memory is the structured ensemble of mechanisms by which an autonomous AI agent stores, indexes, consolidates, retrieves, and forgets information across steps, sessions, and lifetimes — enabling coherent, personalised, and long-horizon behaviour that transcends the hard limit of any single context window. It encompasses four functionally distinct tiers: working memory (active context window); episodic memory (timestamped records of prior observations, actions, and outcomes); semantic memory (declarative facts, entity relationships, and world knowledge); and procedural memory (skill programs, tool-use patterns, and reusable plan templates)."@en ;
rdfs:label "Agent Memory"@en ;
rdfs:subClassOf ngm:ai-agent ;
rdfs:subClassOf ngm:cognitive-architecture ;
rdfs:subClassOf ngm:memory-management ;
rdfs:subClassOf _:r1357 ;
rdfs:subClassOf _:r1358 ;
rdfs:subClassOf _:r1359 ;
rdfs:subClassOf _:r1360 ;
rdfs:subClassOf _:r1361 ;
rdfs:subClassOf _:r1362 ;
rdfs:subClassOf _:r1363 ;
rdfs:subClassOf _:r1364 ;
rdfs:subClassOf _:r1365 ;
vc:bridgesTo ngm:agent-loop ;
vc:bridgesTo ngm:cognitive-architecture ;
vc:bridgesTo ngm:tool-use ;
vc:contrastsWith ngm:context-window ;
vc:contrastsWith ngm:fine-tuning ;
vc:contrastsWith ngm:in-context-learning ;
vc:dependsOn ngm:attention-mechanism ;
vc:dependsOn ngm:embeddings ;
vc:dependsOn ngm:knowledge-graph ;
vc:dependsOn ngm:reasoning-engine ;
vc:dependsOn ngm:vector-database ;
vc:enables ngm:agentic-workflow ;
vc:enables ngm:continual-learning ;
vc:enables ngm:in-context-learning ;
vc:enables ngm:long-horizon-task-execution ;
vc:enables ngm:personalisation ;
vc:enables ngm:planning-and-scheduling ;
vc:enables ngm:self-reflection ;
vc:enables ngm:task-automation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:episodic-memory ;
vc:hasPart ngm:knowledge-graph ;
vc:hasPart ngm:long-term-memory ;
vc:hasPart ngm:procedural-memory ;
vc:hasPart ngm:semantic-memory ;
vc:hasPart ngm:working-memory ;
vc:implements ngm:chain-of-thought ;
vc:implements ngm:re-act-pattern ;
vc:implements ngm:reflexion ;
vc:qualityScore "0.88"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:autonomous-agent ;
vc:relatedTo ngm:consolidation ;
vc:relatedTo ngm:data-compression ;
vc:relatedTo ngm:forgetting ;
vc:relatedTo ngm:gdpr ;
vc:relatedTo ngm:hallucination ;
vc:relatedTo ngm:privacy ;
vc:requires ngm:context-window ;
vc:requires ngm:embeddings ;
vc:requires ngm:foundation-model ;
vc:requires ngm:large-language-models ;
vc:requires ngm:retrieval-augmented-generation ;
vc:requires ngm:vector-database ;
vc:slug "agent-memory" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:agent-identity ;
vc:supports ngm:ai-safety ;
vc:supports ngm:human-in-the-loop ;
vc:supports ngm:multi-agent-system ;
vc:supports ngm:provenance ;
vc:uses ngm:information-retrieval ;
vc:uses ngm:knowledge-representation ;
vc:uses ngm:pgvector ;
vc:uses ngm:pinecone ;
vc:uses ngm:temporal-reasoning ;
vc:uses ngm:weaviate .
ngm:agent-memory-layers a owl:Class ;
rdfs:comment "Persistent memory systems for AI agents providing contextual recall across sessions through vector retrieval, automatic summarisation, and state management — includes Mem0, letta, claude-mem, and agentlog."@en ;
rdfs:label "Agent Memory Layers"@en ;
rdfs:subClassOf ngm:agent-harness ;
rdfs:subClassOf ngm:ai-infrastructure ;
rdfs:subClassOf ngm:cognitive-architecture ;
rdfs:subClassOf _:r1345 ;
rdfs:subClassOf _:r1346 ;
rdfs:subClassOf _:r1347 ;
rdfs:subClassOf _:r1348 ;
rdfs:subClassOf _:r1349 ;
rdfs:subClassOf _:r1350 ;
rdfs:subClassOf _:r1351 ;
rdfs:subClassOf _:r1352 ;
rdfs:subClassOf _:r1353 ;
rdfs:subClassOf _:r1354 ;
rdfs:subClassOf _:r1355 ;
rdfs:subClassOf _:r1356 ;
vc:contrastsWith ngm:context-window ;
vc:contrastsWith ngm:fine-tuning ;
vc:contrastsWith ngm:hallucination ;
vc:contrastsWith ngm:in-context-learning ;
vc:dependsOn ngm:agent-loop ;
vc:dependsOn ngm:embeddings ;
vc:dependsOn ngm:foundation-model ;
vc:dependsOn ngm:knowledge-graph ;
vc:dependsOn ngm:large-language-models ;
vc:dependsOn ngm:retrieval-augmented-generation ;
vc:dependsOn ngm:vector-database ;
vc:enables ngm:agentic-rag ;
vc:enables ngm:agentic-workflow ;
vc:enables ngm:continual-learning ;
vc:enables ngm:in-context-learning ;
vc:enables ngm:multi-agent-system ;
vc:enables ngm:personalisation ;
vc:enables ngm:planning-and-scheduling ;
vc:enables ngm:self-reflection ;
vc:enables ngm:task-automation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:consolidation-pipeline ;
vc:hasPart ngm:episodic-memory ;
vc:hasPart ngm:knowledge-graph ;
vc:hasPart ngm:memory-router ;
vc:hasPart ngm:procedural-memory ;
vc:hasPart ngm:semantic-memory ;
vc:hasPart ngm:vector-database ;
vc:hasPart ngm:working-memory ;
vc:implements ngm:act-r ;
vc:implements ngm:coala ;
vc:implements ngm:information-retrieval ;
vc:implements ngm:nearest-neighbor-search ;
vc:implements ngm:reflexion ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:agent-memory ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:agentic-rag ;
vc:relatedTo ngm:consolidation ;
vc:relatedTo ngm:data-compression ;
vc:relatedTo ngm:external-ai-harness ;
vc:relatedTo ngm:forgetting ;
vc:relatedTo ngm:gdpr ;
vc:relatedTo ngm:hallucination ;
vc:relatedTo ngm:harness-configuration-packs ;
vc:relatedTo ngm:internal-ai-harness ;
vc:relatedTo ngm:multi-agent-orchestration-frameworks ;
vc:relatedTo ngm:personal-agent-runtimes ;
vc:relatedTo ngm:privacy ;
vc:relatedTo ngm:progressive-disclosure-harnesses ;
vc:requires ngm:agent-identity ;
vc:requires ngm:agent-loop ;
vc:requires ngm:context-window ;
vc:requires ngm:embeddings ;
vc:requires ngm:foundation-model ;
vc:requires ngm:large-language-models ;
vc:requires ngm:retrieval-augmented-generation ;
vc:requires ngm:vector-database ;
vc:slug "agent-memory-layers" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:act-r ;
vc:standardizedBy ngm:coala ;
vc:supports ngm:agent-identity ;
vc:supports ngm:agentic-rag ;
vc:supports ngm:ai-safety ;
vc:supports ngm:autonomous-agent ;
vc:supports ngm:human-in-the-loop ;
vc:supports ngm:multi-agent-system ;
vc:supports ngm:provenance ;
vc:supports ngm:temporal-reasoning ;
vc:uses ngm:information-retrieval ;
vc:uses ngm:knowledge-representation ;
vc:uses ngm:model-context-protocol ;
vc:uses ngm:nearest-neighbor-search ;
vc:uses ngm:pgvector ;
vc:uses ngm:pinecone ;
vc:uses ngm:temporal-reasoning ;
vc:uses ngm:weaviate .
ngm:agent-network-protocol a skos:Concept ;
rdfs:label "Agent Network Protocol"@en .
ngm:agent-orchestrator a owl:Class ;
rdfs:comment "An Agent Orchestrator is the directive control component of a multi-agent architecture that decomposes high-level goals into directed acyclic graphs of sub-tasks, selects and dispatches those tasks to specialised sub-agents via a structured Agent Communication Protocol, monitors execution state, resolves inter-task data dependencies, handles timeouts and failures through retry or fallback logic, and assembles partial results into coherent outputs — operating atop an Agent Runtime that manages the lifecycle of individual agents and providing the coordination hub that transforms a pool of autonomous agents into a collaborative system capable of accomplishing complex, long-horizon objectives."@en ;
rdfs:label "Agent Orchestrator"@en ;
rdfs:subClassOf ngm:ai-agent-system ;
rdfs:subClassOf ngm:intelligent-system ;
rdfs:subClassOf _:r1366 ;
rdfs:subClassOf _:r1367 ;
rdfs:subClassOf _:r1368 ;
rdfs:subClassOf _:r1369 ;
rdfs:subClassOf _:r1370 ;
rdfs:subClassOf _:r1371 ;
rdfs:subClassOf _:r1372 ;
vc:contrastsWith ngm:single-agent-system ;
vc:contrastsWith ngm:workflow-automation ;
vc:contrastsWith ngm:workflow-engine ;
vc:dependsOn ngm:directed-acyclic-graph ;
vc:dependsOn ngm:message-passing ;
vc:dependsOn ngm:structured-output ;
vc:enables ngm:agentic-workflow ;
vc:enables ngm:autonomous-coding ;
vc:enables ngm:autonomous-task-execution ;
vc:enables ngm:multi-agent-system ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:error-recovery ;
vc:hasPart ngm:goal-planner ;
vc:hasPart ngm:planning-and-scheduling ;
vc:hasPart ngm:result-validation ;
vc:hasPart ngm:task-decomposition ;
vc:implements ngm:contract-net-protocol ;
vc:implements ngm:plan-and-execute-pattern ;
vc:implements ngm:re-act-pattern ;
vc:qualityScore "0.91"^^xsd:float ;
vc:relatedTo ngm:agent-frameworks ;
vc:relatedTo ngm:agent-to-agent-protocol ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:bdi-architecture ;
vc:relatedTo ngm:coordination-mechanisms ;
vc:relatedTo ngm:distributed-systems ;
vc:relatedTo ngm:fipa-acl ;
vc:relatedTo ngm:workflow-engine ;
vc:requires ngm:agent-memory ;
vc:requires ngm:agent-runtime ;
vc:requires ngm:capability-advertisement ;
vc:requires ngm:large-language-models ;
vc:slug "agent-orchestrator" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:agent-to-agent-protocol ;
vc:standardizedBy ngm:model-context-protocol ;
vc:supports ngm:ai-safety ;
vc:supports ngm:human-in-the-loop ;
vc:uses ngm:agent-communication-protocol ;
vc:uses ngm:agent-runtime ;
vc:uses ngm:chain-of-thought ;
vc:uses ngm:function-calling ;
vc:uses ngm:model-context-protocol ;
vc:uses ngm:task-planning .
ngm:agent-personalisation a skos:Concept ;
rdfs:label "Agent Personalisation"@en .
ngm:agent-platform a skos:Concept ;
rdfs:label "Agent Platform"@en .
ngm:agent-primitives a owl:Class ;
rdfs:comment "The foundational software components and abstractions, such as orchestration, memory, and tool-use interfaces, that enable the construction of autonomous AI agents."@en ;
rdfs:label "Agent Primitives"@en ;
rdfs:subClassOf ngm:agent ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:agent ;
vc:relatedTo ngm:multi-agent-system ;
vc:relatedTo ngm:open-source-ai ;
vc:slug "agent-primitives" ;
vc:sourceDomain "artificial-intelligence" .
ngm:agent-productivity-augmentation a skos:Concept ;
rdfs:label "Agent Productivity Augmentation"@en .
ngm:agent-reasoning a skos:Concept ;
rdfs:label "Agent Reasoning"@en .
ngm:agent-runtime a owl:Class ;
rdfs:comment "An Agent Runtime is the infrastructure execution layer that manages the complete lifecycle, resource allocation, tool access, memory state, and communication channels of one or more autonomous AI agents — providing process isolation, context window management, stateful execution with durable checkpointing, sandboxed tool-call dispatch, inter-agent messaging, credential management, rate limiting, and structured observability, analogous to how an operating system runtime supports application processes, and forming the foundational services upon which Agent Orchestrator control logic and Agentic Workflow execution patterns are built."@en ;
rdfs:label "Agent Runtime"@en ;
rdfs:subClassOf ngm:ai-agent-system ;
rdfs:subClassOf ngm:intelligent-system ;
rdfs:subClassOf _:r1373 ;
rdfs:subClassOf _:r1374 ;
rdfs:subClassOf _:r1375 ;
rdfs:subClassOf _:r1376 ;
rdfs:subClassOf _:r1377 ;
rdfs:subClassOf _:r1378 ;
vc:contrastsWith ngm:serverless-function ;
vc:contrastsWith ngm:workflow-engine ;
vc:dependsOn ngm:api-integration ;
vc:dependsOn ngm:context-window ;
vc:dependsOn ngm:vector-database ;
vc:enables ngm:autonomous-task-execution ;
vc:enables ngm:durable-execution ;
vc:enables ngm:multi-tenancy ;
vc:enables ngm:sandboxed-code-execution ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:credential-management ;
vc:hasPart ngm:observability ;
vc:hasPart ngm:process-isolation ;
vc:hasPart ngm:session-management ;
vc:hasPart ngm:state-persistence ;
vc:hasPart ngm:tool-registry ;
vc:implements ngm:checkpointing ;
vc:implements ngm:execution-model ;
vc:implements ngm:rate-limiting ;
vc:qualityScore "0.91"^^xsd:float ;
vc:relatedTo ngm:agent-communication-protocol ;
vc:relatedTo ngm:agent-frameworks ;
vc:relatedTo ngm:dapr-agents ;
vc:relatedTo ngm:execution-model ;
vc:relatedTo ngm:lang-graph ;
vc:relatedTo ngm:multi-agent-system ;
vc:relatedTo ngm:ros-robotic-operating-system ;
vc:relatedTo ngm:temporal ;
vc:relatedTo ngm:workflow-engine ;
vc:requires ngm:agent-memory ;
vc:requires ngm:authentication-system ;
vc:requires ngm:large-language-models ;
vc:slug "agent-runtime" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:model-context-protocol ;
vc:standardizedBy ngm:open-telemetry ;
vc:supports ngm:agent-orchestrator ;
vc:supports ngm:agentic-workflow ;
vc:uses ngm:function-calling ;
vc:uses ngm:model-context-protocol ;
vc:uses ngm:open-telemetry ;
vc:uses ngm:retrieval-augmented-generation ;
vc:uses ngm:tool-use .
ngm:agent-security a owl:Class ;
rdfs:comment "The discipline of protecting autonomous AI agents and their interactions with tools, data, and other systems from unauthorized access, manipulation, or malicious exploitation."@en ;
rdfs:label "Agent Security"@en ;
rdfs:subClassOf ngm:security ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:access-control ;
vc:relatedTo ngm:ai-agent ;
vc:relatedTo ngm:intrusion-detection ;
vc:slug "agent-security" ;
vc:sourceDomain "security" .
ngm:agent-skill a owl:Class ;
rdfs:comment "An agent skill is a packaged, self-contained unit of procedural knowledge — a named bundle of instructions, and optionally scripts and reference resources — that an agent loads into its context on demand when a task matches the skill's trigger, and unloads afterwards. Rather than baking every capability into the base system prompt, a skill lets specialised know-how (how to run a deployment, audit prose, drive a browser) live as a discoverable, versioned artifact that is progressively disclosed only when relevant, keeping the working context small while giving the agent deep competence in whatever domain the current task demands."@en ;
rdfs:label "Agent Skill"@en ;
rdfs:subClassOf ngm:prompt-template ;
rdfs:subClassOf ngm:prompttemplate ;
vc:enables ngm:agentic-workflow ;
vc:enables ngm:agenticworkflow ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:capability-advertisement ;
vc:relatedTo ngm:capabilityadvertisement ;
vc:relatedTo ngm:tool-use ;
vc:relatedTo ngm:tooluse ;
vc:slug "agent-skill" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:context-management ;
vc:uses ngm:contextmanagement .
ngm:agent-to-agent-protocol a owl:Class ;
rdfs:comment "Agent-to-Agent Protocol is a class of communication specifications that define how autonomous AI agents discover one another, advertise capabilities, delegate tasks, and exchange results directly — without requiring a centralised broker — enabling peer-to-peer coordination between agents built by different organisations or on different frameworks. These protocols treat agents as first-class addressable entities with discoverable skill sets and negotiable service contracts."@en ;
rdfs:label "Agent-to-Agent Protocol"@en ;
rdfs:subClassOf ngm:agent-communication-protocol ;
rdfs:subClassOf ngm:coordination-protocol ;
rdfs:subClassOf _:r1400 ;
rdfs:subClassOf _:r1401 ;
rdfs:subClassOf _:r1402 ;
rdfs:subClassOf _:r1403 ;
rdfs:subClassOf _:r1404 ;
rdfs:subClassOf _:r1405 ;
rdfs:subClassOf _:r1406 ;
rdfs:subClassOf _:r1407 ;
rdfs:subClassOf _:r1408 ;
vc:bridgesTo ngm:distributed-systems ;
vc:bridgesTo ngm:enterprise-ai ;
vc:bridgesTo ngm:microservices-architecture ;
vc:bridgesTo ngm:supply-chain-automation ;
vc:bridgesTo ngm:web-of-things ;
vc:contrastsWith ngm:multi-agent-orchestration ;
vc:contrastsWith ngm:remote-procedure-call ;
vc:dependsOn ngm:autonomous-agent ;
vc:dependsOn ngm:http-protocol ;
vc:dependsOn ngm:large-language-model ;
vc:dependsOn ngm:oauth-2-0 ;
vc:dependsOn ngm:server-sent-events ;
vc:enables ngm:agentic-internet ;
vc:enables ngm:agentic-workflow ;
vc:enables ngm:autonomous-task-execution ;
vc:enables ngm:inter-agent-communication ;
vc:enables ngm:multi-agent-system ;
vc:enables ngm:task-delegation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:agent-card ;
vc:hasPart ngm:agent-identity ;
vc:hasPart ngm:capability-advertisement ;
vc:hasPart ngm:service-discovery ;
vc:hasPart ngm:task-lifecycle ;
vc:implements ngm:agent2-agent-protocol-google-2025 ;
vc:implements ngm:contract-net-protocol ;
vc:implements ngm:fipa-acl ;
vc:qualityScore "0.92"^^xsd:float ;
vc:relatedTo ngm:agent-communication-protocol-ibm-acp ;
vc:relatedTo ngm:agent-network-protocol ;
vc:relatedTo ngm:model-context-protocol ;
vc:relatedTo ngm:multi-agent-orchestration ;
vc:relatedTo ngm:openai-swarm ;
vc:relatedTo ngm:prompt-injection ;
vc:relatedTo ngm:swarm-intelligence ;
vc:requires ngm:agent-identity ;
vc:requires ngm:capability-advertisement ;
vc:requires ngm:decentralised-identifier ;
vc:requires ngm:http-protocol ;
vc:requires ngm:json-data-interchange-format-rpc-2-0 ;
vc:requires ngm:mutual-authentication ;
vc:slug "agent-to-agent-protocol" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:linux-foundation ;
vc:supports ngm:access-control ;
vc:supports ngm:error-handling ;
vc:supports ngm:negotiation ;
vc:supports ngm:rate-limiting ;
vc:supports ngm:state-management ;
vc:supports ngm:webhook ;
vc:uses ngm:json-data-interchange-format-rpc-2-0 ;
vc:uses ngm:json-ld ;
vc:uses ngm:json-web-signature ;
vc:uses ngm:message-passing ;
vc:uses ngm:oauth-2-0 ;
vc:uses ngm:server-sent-events ;
vc:uses ngm:service-discovery .
ngm:agent-tool-use a skos:Concept ;
rdfs:label "Agent Tool Use"@en .
ngm:agent-training a skos:Concept ;
rdfs:label "Agent Training"@en .
ngm:agent-wellbeing a skos:Concept ;
rdfs:label "Agent Wellbeing"@en .
ngm:agent2-agent-protocol a owl:Class ;
rdfs:comment "Agent2Agent Protocol (A2A) is an open specification developed by Google and partner organisations that enables heterogeneous AI agents to discover, communicate, and collaborate across organisational and platform boundaries. It defines a standardised messaging envelope, capability advertisement mechanism, and task-delegation schema so that agents built on different frameworks — such as LangChain, CrewAI, or custom enterprise systems — can interoperate without bespoke integration code. The protocol operates over HTTPS with JSON-RPC 2.0 and supports both synchronous request-response and asynchronous streaming via Server-Sent Events. Agent capability cards, analogous to service discovery manifests, allow an agent to advertise its skills so that orchestrating agents can route work appropriately."@en ;
rdfs:label "Agent2Agent Protocol"@en ;
rdfs:subClassOf ngm:communication-protocol ;
vc:bridgesTo ngm:interoperability-protocol ;
vc:enables ngm:agentic-workflow ;
vc:enables ngm:orchestration ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:agent-event-stream ;
vc:relatedTo ngm:multi-agent-systems ;
vc:relatedTo ngm:server-sent-events ;
vc:slug "agent2-agent-protocol" ;
vc:sourceDomain "ai" ;
vc:uses ngm:model-context-protocol ;
vc:uses ngm:rest-api .
ngm:agent2-agent-protocol-google-2025 a owl:Class ;
rdfs:comment "The Agent2Agent Protocol (A2A), released by Google as an open specification in April 2025 and transferred to the Linux Foundation in June 2025, is a JSON-RPC 2.0 over HTTP(S) protocol — extended with Server-Sent Events for streaming — that enables AI agents to discover one another via standardised, cryptographically signed agent cards hosted at well-known URIs, delegate tasks through a six-state task lifecycle, stream results back to requesting agents, and operate regardless of the underlying model or framework used to implement the agents. Reaching version 1.2 by March 2026 with over 150 supporting organisations, it is designed as a complementary peer-to-peer layer alongside Anthropic's Model Context Protocol, together forming the emerging two-protocol stack for the agentic internet."@en ;
rdfs:label "Agent2Agent Protocol (Google 2025)"@en ;
rdfs:subClassOf ngm:agent-communication-protocol ;
rdfs:subClassOf ngm:agent-to-agent-protocol ;
rdfs:subClassOf ngm:coordination-protocol ;
rdfs:subClassOf _:r1415 ;
rdfs:subClassOf _:r1416 ;
rdfs:subClassOf _:r1417 ;
rdfs:subClassOf _:r1418 ;
rdfs:subClassOf _:r1419 ;
rdfs:subClassOf _:r1420 ;
rdfs:subClassOf _:r1421 ;
vc:bridgesTo ngm:distributed-systems ;
vc:bridgesTo ngm:enterprise-ai ;
vc:bridgesTo ngm:microservices-architecture ;
vc:bridgesTo ngm:supply-chain-automation ;
vc:bridgesTo ngm:web-of-things ;
vc:contrastsWith ngm:openai-swarm ;
vc:contrastsWith ngm:remote-procedure-call ;
vc:dependsOn ngm:agent-runtime ;
vc:dependsOn ngm:autonomous-agent ;
vc:dependsOn ngm:http-protocol ;
vc:dependsOn ngm:large-language-model ;
vc:enables ngm:agentic-internet ;
vc:enables ngm:agentic-workflow ;
vc:enables ngm:autonomous-task-execution ;
vc:enables ngm:inter-agent-communication ;
vc:enables ngm:multi-agent-system ;
vc:enables ngm:task-delegation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:agent-card ;
vc:hasPart ngm:push-notification ;
vc:hasPart ngm:service-discovery ;
vc:hasPart ngm:task-lifecycle ;
vc:implements ngm:json-canonicalization-scheme ;
vc:implements ngm:json-data-interchange-format-rpc-2-0 ;
vc:implements ngm:json-data-interchange-format-schema ;
vc:implements ngm:json-web-signature ;
vc:implements ngm:server-sent-events ;
vc:qualityScore "0.93"^^xsd:float ;
vc:relatedTo ngm:agent-communication-protocol ;
vc:relatedTo ngm:agent-communication-protocol-ibm-acp ;
vc:relatedTo ngm:agent-network-protocol ;
vc:relatedTo ngm:model-context-protocol ;
vc:relatedTo ngm:multi-agent-orchestration ;
vc:relatedTo ngm:prompt-injection ;
vc:relatedTo ngm:swarm-intelligence ;
vc:relatedTo ngm:trust-framework ;
vc:requires ngm:agent-identity ;
vc:requires ngm:http-protocol ;
vc:requires ngm:json-data-interchange-format-rpc-2-0 ;
vc:requires ngm:mutual-authentication ;
vc:requires ngm:oauth-2-0 ;
vc:slug "agent2-agent-protocol-google-2025" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:linux-foundation ;
vc:supports ngm:access-control ;
vc:supports ngm:capability-advertisement ;
vc:supports ngm:error-handling ;
vc:supports ngm:negotiation ;
vc:supports ngm:rate-limiting ;
vc:supports ngm:state-management ;
vc:uses ngm:http-protocol ;
vc:uses ngm:json-data-interchange-format-rpc-2-0 ;
vc:uses ngm:json-data-interchange-format-schema ;
vc:uses ngm:json-web-signature ;
vc:uses ngm:message-passing ;
vc:uses ngm:oauth-2-0 ;
vc:uses ngm:server-sent-events ;
vc:uses ngm:service-discovery ;
vc:uses ngm:well-known-uri .
ngm:agentbench a skos:Concept ;
rdfs:label "Agentbench"@en .
ngm:agentic-ai a owl:Class ;
rdfs:comment "Agentic AI refers to AI systems characterised by autonomy, goal-directedness, and the capacity to take sustained sequences of actions — including calling external tools, spawning sub-agents, and modifying their own environment — in pursuit of high-level objectives specified by a user or orchestrator. Agentic systems differ from reactive or conversational AI in that they operate over extended time horizons, maintain persistent state across steps, and may take consequential or irreversible actions without per-step human approval. The architectural backbone is typically a large language model serving as a cognitive core inside a closed sense-plan-act loop, augmented by memory stores, tool registries, and inter-agent communication protocols. The term encompasses both single-agent pipelines and heterogeneous multi-agent architectures in which agentic components collaborate, compete, or are hierarchically orchestrated."@en ;
rdfs:label "Agentic AI"@en ;
rdfs:subClassOf ngm:agent-based-modelling ;
rdfs:subClassOf ngm:ai-agents ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:cognitive-architecture ;
rdfs:subClassOf _:r1422 ;
rdfs:subClassOf _:r1423 ;
rdfs:subClassOf _:r1424 ;
rdfs:subClassOf _:r1425 ;
rdfs:subClassOf _:r1426 ;
rdfs:subClassOf _:r1427 ;
rdfs:subClassOf _:r1428 ;
rdfs:subClassOf _:r1429 ;
rdfs:subClassOf _:r1430 ;
rdfs:subClassOf _:r1431 ;
rdfs:subClassOf _:r1432 ;
rdfs:subClassOf _:r1433 ;
skos:broader ngm:ai-application ;
vc:bridgesTo ngm:agent-based-modelling ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:internet-of-agents ;
vc:bridgesTo ngm:robotic-process-automation ;
vc:contrastsWith ngm:conversational-ai ;
vc:contrastsWith ngm:reactive-systems ;
vc:contrastsWith ngm:robotic-process-automation ;
vc:contrastsWith ngm:single-turn-inference ;
vc:dependsOn ngm:embedding-model ;
vc:dependsOn ngm:foundation-model ;
vc:dependsOn ngm:retrieval-augmented-generation ;
vc:dependsOn ngm:transformer-architecture ;
vc:dependsOn ngm:vector-database ;
vc:enables ngm:agentic-rag ;
vc:enables ngm:agentic-workflow ;
vc:enables ngm:ai-agent-payments ;
vc:enables ngm:autonomous-agent ;
vc:enables ngm:multi-agent-system ;
vc:enables ngm:software-development-automation ;
vc:enables ngm:workflow-automation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:agent-loop ;
vc:hasPart ngm:agent-memory ;
vc:hasPart ngm:agent-orchestrator ;
vc:hasPart ngm:agent-runtime ;
vc:hasPart ngm:task-planning ;
vc:hasPart ngm:tool-registry ;
vc:hasPart ngm:working-memory ;
vc:implements ngm:chain-of-thought ;
vc:implements ngm:function-calling ;
vc:implements ngm:model-context-protocol ;
vc:implements ngm:re-act-pattern ;
vc:implements ngm:reflexion ;
vc:qualityScore "0.92"^^xsd:float ;
vc:relatedTo ngm:agent-communication-protocol ;
vc:relatedTo ngm:agent-identity ;
vc:relatedTo ngm:agent-to-agent-protocol ;
vc:relatedTo ngm:ai-agent-payments ;
vc:relatedTo ngm:ai-agents ;
vc:relatedTo ngm:ai-alignment ;
vc:relatedTo ngm:cognitive-architecture ;
vc:relatedTo ngm:computer-vision ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:orchestration ;
vc:relatedTo ngm:prompt-engineering ;
vc:relatedTo ngm:prompt-injection ;
vc:requires ngm:foundation-model ;
vc:requires ngm:large-language-models ;
vc:requires ngm:memory-management ;
vc:requires ngm:task-planning ;
vc:requires ngm:tool-use ;
vc:slug "agentic-ai" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:agent-frameworks ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:model-context-protocol ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:ai-alignment ;
vc:supports ngm:ai-safety ;
vc:supports ngm:human-in-the-loop ;
vc:supports ngm:prompt-injection ;
vc:uses ngm:agent-communication-protocol ;
vc:uses ngm:chain-of-thought ;
vc:uses ngm:function-calling ;
vc:uses ngm:knowledge-graph ;
vc:uses ngm:model-context-protocol ;
vc:uses ngm:prompt-engineering ;
vc:uses ngm:re-act-pattern ;
vc:uses ngm:reinforcement-learning .
ngm:agentic-ai-practitioner-training-programme a owl:Class ;
rdfs:comment "A structured training programme introducing practitioners to agentic AI systems, covering context engineering, memory management, agent orchestration tools (such as Roo Code), and practical case studies in project management, data visualisation, and academic research through phased, multi-session instruction."@en ;
rdfs:label "Agentic AI Practitioner Training Programme"@en ;
rdfs:subClassOf ngm:ai-application ;
skos:broader ngm:ai-application ;
vc:bridgesTo ngm:ai-agent-system ;
vc:enables ngm:agentic-ai ;
vc:enables ngm:generative-ai ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:agent-frameworks ;
vc:relatedTo ngm:generative-ai-development-methodology ;
vc:slug "agentic-ai-practitioner-training-programme" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:ai-governance-and-ethics ;
vc:uses ngm:ai-agent-system ;
vc:uses ngm:large-language-models .
ngm:agentic-ai-systems a owl:Class ;
rdfs:comment "Agentic AI systems are AI systems that autonomously plan and execute multi-step tasks by invoking tools, calling external APIs, and adapting their strategy based on intermediate results, rather than producing a single response to a single prompt. They combine a reasoning model with memory, tool use, and control loops that allow sustained operation toward a goal with limited human intervention. Agentic AI systems are a major focus of frontier AI development and a key axis of competition among AI labs."@en ;
rdfs:label "Agentic AI Systems"@en ;
rdfs:subClassOf ngm:ai-system ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "agentic-ai-systems" ;
vc:sourceDomain "artificial-intelligence" .
ngm:agentic-ai-workflow a skos:Concept ;
rdfs:label "Agentic AI Workflow"@en .
ngm:agentic-architecture a owl:Class ;
rdfs:comment "The design patterns and system structures for building AI agents, including modular skills, continuous learning, and multi-agent collaboration."@en ;
rdfs:label "Agentic Architecture"@en ;
rdfs:subClassOf ngm:model-architecture ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:modular-ai ;
vc:slug "agentic-architecture" ;
vc:sourceDomain "artificial-intelligence" .
ngm:agentic-browser a skos:Concept ;
rdfs:label "Agentic Browser"@en .
ngm:agentic-browsing a skos:Concept ;
rdfs:label "Agentic Browsing"@en .
ngm:agentic-code-generation a skos:Concept ;
rdfs:label "Agentic Code Generation"@en .
ngm:agentic-coding a owl:Class ;
rdfs:comment "The application of autonomous AI agents to perform complex, multi-step software engineering tasks, including code generation, debugging, and execution within terminal environments."@en ;
rdfs:label "Agentic Coding"@en ;
rdfs:subClassOf ngm:gpt ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:gpt ;
vc:relatedTo ngm:natural-language-processing ;
vc:slug "agentic-coding" ;
vc:sourceDomain "artificial-intelligence" .
ngm:agentic-commerce-layer a skos:Concept ;
rdfs:label "Agentic Commerce Layer"@en .
ngm:agentic-economy a skos:Concept ;
rdfs:label "Agentic Economy"@en .
ngm:agentic-evaluation a skos:Concept ;
rdfs:label "Agentic Evaluation"@en .
ngm:agentic-finance a owl:Class ;
rdfs:comment "Infrastructure enabling autonomous AI agents to hold cryptographic wallets, provision compute resources, negotiate contracts, and transact with other agents or humans without intermediaries. AgentFi bridges decentralised finance protocols with agentic AI systems, creating machine-to-machine economic coordination layers."@en ;
rdfs:label "Agentic Finance"@en ;
rdfs:subClassOf ngm:bc-defi-and-economics ;
skos:broader ngm:bc-defi-and-economics ;
vc:bridgesTo ngm:agentic-internet ;
vc:bridgesTo ngm:ai-application ;
vc:dependsOn ngm:decentralized-finance-de-fi ;
vc:dependsOn ngm:micropayments ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:smart-contract ;
vc:slug "agentic-finance" ;
vc:sourceDomain "blockchain" .
ngm:agentic-harness a owl:Class ;
rdfs:comment "A software framework or layer that orchestrates autonomous AI agents, managing their memory, decision loops, and interaction with external tools or environments."@en ;
rdfs:label "Agentic Harness"@en ;
rdfs:subClassOf ngm:agent-layer ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:agent-layer ;
vc:relatedTo ngm:software-architecture ;
vc:slug "agentic-harness" ;
vc:sourceDomain "artificial-intelligence" .
ngm:agentic-internet a owl:Class ;
rdfs:comment "Agentic Internet is the emerging substrate of protocols, identity primitives, payment rails and discovery mechanisms over which autonomous AI agents — rather than human users clicking through browsers — discover services, negotiate terms, exchange data and settle value on behalf of principals (hu..."@en ;
rdfs:label "Agentic Internet"@en ;
rdfs:subClassOf ngm:agent-oriented-computing ;
rdfs:subClassOf ngm:ai-agent-system ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf ngm:distributed-computing ;
rdfs:subClassOf ngm:sociotechnical-system ;
rdfs:subClassOf ngm:web-architecture ;
rdfs:subClassOf _:r1434 ;
rdfs:subClassOf _:r1435 ;
rdfs:subClassOf _:r1436 ;
rdfs:subClassOf _:r1437 ;
rdfs:subClassOf _:r1438 ;
rdfs:subClassOf _:r1439 ;
rdfs:subClassOf _:r1440 ;
rdfs:subClassOf _:r1441 ;
rdfs:subClassOf _:r1442 ;
rdfs:subClassOf _:r1443 ;
rdfs:subClassOf _:r1444 ;
rdfs:subClassOf _:r1445 ;
rdfs:subClassOf _:r1446 ;
rdfs:subClassOf _:r1447 ;
rdfs:subClassOf _:r1448 ;
rdfs:subClassOf _:r1449 ;
skos:broader ngm:ai-research-area ;
vc:bridgesTo ngm:sociotechnical-system ;
vc:contrastsWith ngm:browser-centric-internet ;
vc:contrastsWith ngm:human-in-the-loop-workflow ;
vc:contrastsWith ngm:static-web ;
vc:contrastsWith ngm:walled-garden ;
vc:contrastsWith ngm:web-2-0-saas ;
vc:contrastsWith ngm:web3-blockchain-agents ;
vc:dependsOn ngm:cryptographic-infrastructure ;
vc:dependsOn ngm:dns ;
vc:dependsOn ngm:http ;
vc:dependsOn ngm:json-data-interchange-format ;
vc:dependsOn ngm:oauth ;
vc:dependsOn ngm:rest ;
vc:dependsOn ngm:tls ;
vc:dependsOn ngm:web-sockets ;
vc:enables ngm:agentic-search ;
vc:enables ngm:api-first-web ;
vc:enables ngm:autonomous-workflows ;
vc:enables ngm:cross-vendor-agent-interoperability ;
vc:enables ngm:long-horizon-task-execution ;
vc:enables ngm:machine-to-machine-commerce ;
vc:enables ngm:personal-ai ;
vc:enables ngm:programmatic-service-composition ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:a2-a-protocol ;
vc:hasPart ngm:agent-identity ;
vc:hasPart ngm:agent-marketplace ;
vc:hasPart ngm:agent-orchestrator ;
vc:hasPart ngm:agent-runtime ;
vc:hasPart ngm:agentic-commerce-layer ;
vc:hasPart ngm:capability-token ;
vc:hasPart ngm:computer-use-and-browser-agents ;
vc:hasPart ngm:model-context-protocol ;
vc:hasPart ngm:tool-registry ;
vc:implements ngm:capability-discovery ;
vc:implements ngm:elicitation ;
vc:implements ngm:function-calling ;
vc:implements ngm:json-data-interchange-format-rpc ;
vc:implements ngm:server-sent-events ;
vc:implements ngm:streaming-responses ;
vc:implements ngm:task-lifecycle-management ;
vc:implements ngm:tool-schema ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:agentic-economy ;
vc:relatedTo ngm:ai-agents ;
vc:relatedTo ngm:ai-search ;
vc:relatedTo ngm:autonomous-agent ;
vc:relatedTo ngm:browser-automation ;
vc:relatedTo ngm:computer-use ;
vc:relatedTo ngm:death-of-the-internet ;
vc:relatedTo ngm:internet-of-agents ;
vc:relatedTo ngm:multi-agent-systems ;
vc:relatedTo ngm:zero-click-search ;
vc:requires ngm:authentication ;
vc:requires ngm:authorisation ;
vc:requires ngm:discovery-protocol ;
vc:requires ngm:large-language-model ;
vc:requires ngm:large-language-models ;
vc:requires ngm:persistent-memory ;
vc:requires ngm:reasoning-engine ;
vc:requires ngm:tool-use ;
vc:requires ngm:transport-layer ;
vc:slug "agentic-internet" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:agntcy ;
vc:standardizedBy ngm:anthropic ;
vc:standardizedBy ngm:ietf ;
vc:standardizedBy ngm:linux-foundation ;
vc:standardizedBy ngm:open-id-foundation ;
vc:standardizedBy ngm:trust-over-ip-foundation ;
vc:standardizedBy ngm:w3-c ;
vc:supports ngm:booking-agents ;
vc:supports ngm:coding-copilots ;
vc:supports ngm:customer-service-automation ;
vc:supports ngm:personal-assistance ;
vc:supports ngm:procurement-agents ;
vc:supports ngm:research-agents ;
vc:supports ngm:shopping-agents ;
vc:supports ngm:software-engineering-agents ;
vc:uses ngm:constitutional-ai-training-methodology-language-model-family ;
vc:uses ngm:embeddings ;
vc:uses ngm:google-ai-technology-corporation-gemini ;
vc:uses ngm:gpt ;
vc:uses ngm:meta-llama-model-family ;
vc:uses ngm:mistral ;
vc:uses ngm:retrieval-augmented-generation ;
vc:uses ngm:vector-database .
ngm:agentic-knowledge-base a owl:Class ;
rdfs:comment "An autonomous system that continuously ingests, processes, and structures external information to provide real-time context for other AI agents."@en ;
rdfs:label "Agentic Knowledge Base"@en ;
rdfs:subClassOf ngm:agents ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:agents ;
vc:relatedTo ngm:enterprise-ai ;
vc:relatedTo ngm:ontology ;
vc:slug "agentic-knowledge-base" ;
vc:sourceDomain "artificial-intelligence" .
ngm:agentic-loop a skos:Concept ;
rdfs:label "Agentic Loop"@en .
ngm:agentic-misalignment a skos:Concept ;
rdfs:label "Agentic Misalignment"@en .
ngm:agentic-mycelia a owl:Class ;
rdfs:comment "A framework for interconnected metaverse instances operating as a decentralised, AI-driven ecosystem, in which specialised software agents mediate interoperability, value exchange, identity, and adaptable governance across otherwise-sovereign virtual worlds. Each instance exposes a machine- and human-readable ontology (Linked-JSON) that agents at the edges translate and arbitrate between."@en ;
rdfs:label "Agentic Mycelia"@en ;
rdfs:subClassOf ngm:metaverse-architecture ;
vc:enables ngm:adaptable-governance ;
vc:enables ngm:interoperability ;
vc:enables ngm:self-sovereign-identity ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:jurisdictional-agent ;
vc:hasPart ngm:onboarding-agent ;
vc:hasPart ngm:scene-agent ;
vc:hasPart ngm:transfer-agent ;
vc:isPartOf ngm:metaverse-architecture ;
vc:qualityScore "0.0"^^xsd:float ;
vc:requires ngm:living-contract ;
vc:slug "agentic-mycelia" ;
vc:sourceDomain "spatial-computing" .
ngm:agentic-pipeline a skos:Concept ;
rdfs:label "Agentic Pipeline"@en .
ngm:agentic-rag a owl:Class ;
rdfs:comment "Agentic RAG is an architecture that augments retrieval-augmented generation with an autonomous agent loop, letting a language model plan, decide when and what to retrieve, issue multiple queries across heterogeneous sources, reflect on retrieved evidence quality, reformulate queries, and verify results before generating a final response. Unlike the single-pass retrieve-then-read pipeline of naive RAG, Agentic RAG treats retrieval as a first-class action in a multi-step reasoning cycle, enabling resolution of multi-hop questions, adaptive source selection, self-correction, and iterative evidence accumulation under agent-controlled stopping criteria."@en ;
rdfs:label "Agentic RAG"@en ;
rdfs:subClassOf ngm:agentic-workflow ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:information-retrieval ;
rdfs:subClassOf ngm:retrieval-augmented-generation ;
rdfs:subClassOf _:r1450 ;
rdfs:subClassOf _:r1451 ;
rdfs:subClassOf _:r1452 ;
rdfs:subClassOf _:r1453 ;
rdfs:subClassOf _:r1454 ;
rdfs:subClassOf _:r1455 ;
rdfs:subClassOf _:r1456 ;
rdfs:subClassOf _:r1457 ;
skos:broader ngm:ai-application ;
vc:contrastsWith ngm:fine-tuning ;
vc:contrastsWith ngm:parametric-knowledge ;
vc:contrastsWith ngm:rag-pipeline ;
vc:dependsOn ngm:agentic-ai ;
vc:dependsOn ngm:foundation-model ;
vc:dependsOn ngm:nearest-neighbor-search ;
vc:dependsOn ngm:rag-pipeline ;
vc:dependsOn ngm:transformer-architecture ;
vc:enables ngm:enterprise-search ;
vc:enables ngm:hallucination-mitigation ;
vc:enables ngm:knowledge-grounding ;
vc:enables ngm:multi-hop-reasoning ;
vc:enables ngm:question-answering ;
vc:enables ngm:semantic-search ;
vc:enables ngm:source-attribution ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:agent-orchestrator ;
vc:hasPart ngm:corrective-rag ;
vc:hasPart ngm:evidence-accumulator ;
vc:hasPart ngm:query-rewriting ;
vc:hasPart ngm:retrieval-augmented-generation ;
vc:hasPart ngm:retrieval-grader ;
vc:hasPart ngm:self-rag ;
vc:implements ngm:adaptive-rag ;
vc:implements ngm:chain-of-thought ;
vc:implements ngm:function-calling ;
vc:implements ngm:hybrid-retrieval ;
vc:implements ngm:query-rewriting ;
vc:implements ngm:reranking ;
vc:implements ngm:tool-use ;
vc:qualityScore "0.91"^^xsd:float ;
vc:relatedTo ngm:agentic-workflow ;
vc:relatedTo ngm:ai-agents ;
vc:relatedTo ngm:enterprise-search ;
vc:relatedTo ngm:graph-rag ;
vc:relatedTo ngm:model-context-protocol ;
vc:relatedTo ngm:multimodal-ai-architecture-ai ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:orchestration ;
vc:relatedTo ngm:prompt-engineering ;
vc:relatedTo ngm:rag-pipeline ;
vc:relatedTo ngm:retrieval-augmented-generation ;
vc:relatedTo ngm:semantic-search ;
vc:relatedTo ngm:streaming-rag ;
vc:requires ngm:agent-loop ;
vc:requires ngm:chunking ;
vc:requires ngm:embedding-model ;
vc:requires ngm:large-language-models ;
vc:requires ngm:retrieval-augmented-generation ;
vc:requires ngm:vector-database ;
vc:slug "agentic-rag" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:model-context-protocol ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:enterprise-search ;
vc:supports ngm:hallucination-reduction ;
vc:supports ngm:knowledge-base ;
vc:supports ngm:natural-language-processing ;
vc:supports ngm:source-attribution ;
vc:uses ngm:agent-memory ;
vc:uses ngm:chain-of-thought ;
vc:uses ngm:chunking ;
vc:uses ngm:context-window-management ;
vc:uses ngm:dense-retrieval ;
vc:uses ngm:embedding-search ;
vc:uses ngm:function-calling ;
vc:uses ngm:hybrid-retrieval ;
vc:uses ngm:knowledge-graph ;
vc:uses ngm:nearest-neighbor-search ;
vc:uses ngm:reranking .
ngm:agentic-search a skos:Concept ;
rdfs:label "Agentic Search"@en .
ngm:agentic-shift a owl:Class ;
rdfs:comment "The industry-wide transition from static AI models to autonomous, goal-directed agents capable of complex task execution."@en ;
rdfs:label "Agentic Shift"@en ;
rdfs:subClassOf ngm:agents ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:agents ;
vc:relatedTo ngm:enterprise-ai ;
vc:slug "agentic-shift" ;
vc:sourceDomain "artificial-intelligence" .
ngm:agentic-software-engineering a owl:Class ;
rdfs:comment "A software development paradigm where autonomous AI agents perform end-to-end engineering tasks, including coding, testing, and review, with minimal human intervention."@en ;
rdfs:label "Agentic Software Engineering"@en ;
rdfs:subClassOf ngm:software-development ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-code-generation ;
vc:relatedTo ngm:code-review ;
vc:relatedTo ngm:devops ;
vc:relatedTo ngm:software-development ;
vc:slug "agentic-software-engineering" ;
vc:sourceDomain "artificial-intelligence" .
ngm:agentic-system a skos:Concept ;
rdfs:label "Agentic System"@en .
ngm:agentic-workflow a owl:Class ;
rdfs:comment "An agentic workflow is a structured, iterative execution pattern in which an AI agent autonomously plans actions, invokes external tools or APIs, observes results, and revises its approach through successive reasoning cycles until a goal condition is satisfied or a stopping criterion is met. Unlike single-pass inference, agentic workflows employ persistent memory, branching logic, and multi-step planning that may span many inference calls and involve specialised sub-agents coordinated by an orchestrator. The pattern relies on large language model capabilities — tool use, function calling, long-context reasoning — and is the architectural basis for systems such as AutoGPT, LangGraph, CrewAI, OpenAI Agents SDK, and Anthropic's Claude toolset. Agentic workflows introduce novel safety and reliability challenges including error compounding, prompt injection via tool outputs, and the need for human-in-the-loop checkpoints in high-stakes deployments."@en ;
rdfs:label "Agentic Workflow"@en ;
rdfs:subClassOf ngm:workflow-automation ;
rdfs:subClassOf _:r1458 ;
rdfs:subClassOf _:r1459 ;
rdfs:subClassOf _:r1460 ;
rdfs:subClassOf _:r1461 ;
rdfs:subClassOf _:r1462 ;
rdfs:subClassOf _:r1463 ;
rdfs:subClassOf _:r1464 ;
rdfs:subClassOf _:r1465 ;
rdfs:subClassOf _:r1466 ;
vc:bridgesTo ngm:ai-safety ;
vc:bridgesTo ngm:human-in-the-loop ;
vc:bridgesTo ngm:prompt-injection ;
vc:contrastsWith ngm:robotic-process-automation ;
vc:contrastsWith ngm:single-turn-inference ;
vc:contrastsWith ngm:traditional-workflow-orchestration ;
vc:dependsOn ngm:api-integration ;
vc:dependsOn ngm:foundation-model ;
vc:dependsOn ngm:inference ;
vc:dependsOn ngm:orchestration ;
vc:enables ngm:ai-agent-system ;
vc:enables ngm:ai-research-assistant ;
vc:enables ngm:autonomous-agent ;
vc:enables ngm:autonomous-coding ;
vc:enables ngm:data-engineering ;
vc:enables ngm:multi-agent-systems ;
vc:enables ngm:retrieval-augmented-generation ;
vc:enables ngm:scientific-discovery ;
vc:enables ngm:task-planning ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:agent-loop ;
vc:hasPart ngm:plan-and-execute-pattern ;
vc:hasPart ngm:re-act-pattern ;
vc:hasPart ngm:reflection-pattern ;
vc:hasPart ngm:tool-call-loop ;
vc:implements ngm:plan-and-execute-pattern ;
vc:implements ngm:re-act-pattern ;
vc:implements ngm:reflection-pattern ;
vc:qualityScore "0.91"^^xsd:float ;
vc:relatedTo ngm:agent-frameworks ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:auto-gen ;
vc:relatedTo ngm:autonomous-agent ;
vc:relatedTo ngm:crew-ai ;
vc:relatedTo ngm:foundation-model ;
vc:relatedTo ngm:gaia ;
vc:relatedTo ngm:lang-graph ;
vc:relatedTo ngm:multi-agent-systems ;
vc:relatedTo ngm:openai-research-organisation-agents-sdk ;
vc:relatedTo ngm:orchestration ;
vc:relatedTo ngm:planning-and-scheduling ;
vc:relatedTo ngm:robotic-process-automation ;
vc:relatedTo ngm:swe-bench ;
vc:relatedTo ngm:webarena ;
vc:requires ngm:agent-memory ;
vc:requires ngm:context-window ;
vc:requires ngm:function-calling ;
vc:requires ngm:large-language-models ;
vc:requires ngm:tool-use ;
vc:slug "agentic-workflow" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:model-context-protocol ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:ai-alignment ;
vc:supports ngm:ai-safety ;
vc:supports ngm:human-in-the-loop ;
vc:supports ngm:robotic-process-automation ;
vc:uses ngm:chain-of-thought ;
vc:uses ngm:function-calling ;
vc:uses ngm:model-context-protocol ;
vc:uses ngm:prompt-engineering ;
vc:uses ngm:re-act-pattern ;
vc:uses ngm:reasoning ;
vc:uses ngm:reinforcement-learning ;
vc:uses ngm:tool-use ;
vc:uses ngm:vector-database .
ngm:agentic-workload-economics a owl:Class ;
rdfs:comment "The economic analysis of computational costs and resource consumption associated with autonomous AI agents that perform multi-step tasks, characterized by significantly higher token usage than simple query-response interactions."@en ;
rdfs:label "Agentic Workload Economics"@en ;
rdfs:subClassOf ngm:model ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:enterprise-ai-cost-management ;
vc:relatedTo ngm:model-capacity ;
vc:slug "agentic-workload-economics" ;
vc:sourceDomain "economics" .
ngm:agenticworkflow a skos:Concept ;
rdfs:label "Agenticworkflow"@en .
ngm:agentloop a skos:Concept ;
rdfs:label "Agentloop"@en .
ngm:agents a owl:Class ;
rdfs:comment "Agents are autonomous or semi-autonomous computational systems that perceive an environment through sensors (text inputs, vision encoders, structured tool responses, multimodal streams), reason or plan over an internal model of that environment, and act upon it through actuators (function calls, ..."@en ;
rdfs:label "Agents"@en ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf ngm:autonomous-system ;
rdfs:subClassOf ngm:cognitive-architecture ;
rdfs:subClassOf ngm:intelligent-system ;
rdfs:subClassOf _:r1467 ;
rdfs:subClassOf _:r1468 ;
rdfs:subClassOf _:r1469 ;
rdfs:subClassOf _:r1470 ;
rdfs:subClassOf _:r1471 ;
rdfs:subClassOf _:r1472 ;
rdfs:subClassOf _:r1473 ;
rdfs:subClassOf _:r1474 ;
rdfs:subClassOf _:r1475 ;
rdfs:subClassOf _:r1476 ;
rdfs:subClassOf _:r1477 ;
rdfs:subClassOf _:r1478 ;
rdfs:subClassOf _:r1479 ;
rdfs:subClassOf _:r1480 ;
rdfs:subClassOf _:r1481 ;
rdfs:subClassOf _:r1482 ;
skos:broader ngm:ai-research-area ;
skos:broader ngm:artificial-intelligence ;
vc:bridgesTo ngm:cognitive-architecture ;
vc:bridgesTo ngm:intelligent-systems ;
vc:contrastsWith ngm:chatbot ;
vc:contrastsWith ngm:digital-assistant-siri-alexa ;
vc:contrastsWith ngm:robotic-process-automation ;
vc:contrastsWith ngm:static-inference-pipeline ;
vc:contrastsWith ngm:workflow-automation ;
vc:dependsOn ngm:constitutional-ai-training-methodology ;
vc:dependsOn ngm:function-calling-api ;
vc:dependsOn ngm:reinforcement-learning-from-human-feedback ;
vc:dependsOn ngm:retrieval-augmented-generation ;
vc:dependsOn ngm:transformer-architecture ;
vc:dependsOn ngm:vector-database ;
vc:enables ngm:agentic-workflow ;
vc:enables ngm:ai-augmented-software-engineering ;
vc:enables ngm:autonomous-task-execution ;
vc:enables ngm:browser-automation ;
vc:enables ngm:computer-use ;
vc:enables ngm:deep-research ;
vc:enables ngm:multi-agent-orchestration ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:action-executor ;
vc:hasPart ngm:agent-memory ;
vc:hasPart ngm:large-language-model ;
vc:hasPart ngm:large-language-models ;
vc:hasPart ngm:observation-buffer ;
vc:hasPart ngm:planning-module ;
vc:hasPart ngm:reasoning-trace ;
vc:hasPart ngm:reflection-loop ;
vc:hasPart ngm:system-prompt ;
vc:hasPart ngm:tool-use ;
vc:implements ngm:bdi-model ;
vc:implements ngm:contract-net-protocol ;
vc:implements ngm:plan-and-execute ;
vc:implements ngm:re-act ;
vc:implements ngm:reflexion ;
vc:implements ngm:self-consistency ;
vc:implements ngm:subsumption-architecture ;
vc:implements ngm:tree-of-thoughts ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:ai-alignment ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:cognitive-architecture ;
vc:relatedTo ngm:embodied-ai ;
vc:relatedTo ngm:multi-agent-system ;
vc:relatedTo ngm:reinforcement-learning ;
vc:relatedTo ngm:tool-augmented-llm ;
vc:requires ngm:context-window ;
vc:requires ngm:foundation-model ;
vc:requires ngm:function-calling ;
vc:requires ngm:human-oversight ;
vc:requires ngm:inference-compute ;
vc:requires ngm:large-scale-pretrained-foundation-model ;
vc:requires ngm:tool-definition ;
vc:slug "agents" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:agent2-agent-protocol-google-2025 ;
vc:standardizedBy ngm:fipa-acl-2002 ;
vc:standardizedBy ngm:model-context-protocol-anthropic-2024 ;
vc:standardizedBy ngm:owasp-llm-top-10-2025 ;
vc:supports ngm:customer-service-automation ;
vc:supports ngm:drug-discovery ;
vc:supports ngm:enterprise-workflow ;
vc:supports ngm:personal-assistance ;
vc:supports ngm:robotics-control ;
vc:supports ngm:scientific-research ;
vc:supports ngm:software-development-automation ;
vc:uses ngm:agent2-agent-protocol ;
vc:uses ngm:chain-of-thought ;
vc:uses ngm:embedding-search ;
vc:uses ngm:fipa-acl ;
vc:uses ngm:function-schemas ;
vc:uses ngm:model-context-protocol .
ngm:agentspeak a skos:Concept ;
rdfs:label "Agentspeak"@en .
ngm:aggelos-kiayias a owl:Class ;
rdfs:comment "A computer scientist and cryptographer known for research in cryptography and blockchain protocols, including provably secure proof-of-stake consensus."@en ;
rdfs:label "Aggelos Kiayias"@en ;
rdfs:subClassOf ngm:cryptography ;
rdfs:subClassOf _:r1483 ;
vc:bridgesTo ngm:cardano ;
vc:bridgesTo ngm:consensus-mechanisms ;
vc:enables ngm:proof-of-stake ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:cryptography ;
vc:slug "aggelos-kiayias" ;
vc:sourceDomain "security" .
ngm:aggregate-demand a skos:Concept ;
rdfs:label "Aggregate Demand"@en .
ngm:aggregate-supply a skos:Concept ;
rdfs:label "Aggregate Supply"@en .
ngm:aggregation-algorithm a skos:Concept ;
rdfs:label "Aggregation Algorithm"@en .
ngm:aggregation-bias a skos:Concept ;
rdfs:label "Aggregation Bias"@en .
ngm:aggregation-contract a skos:Concept ;
rdfs:label "Aggregation Contract"@en .
ngm:aggregative-property a skos:Concept ;
rdfs:label "Aggregative Property"@en .
ngm:aggregator a skos:Concept ;
rdfs:label "Aggregator"@en .
ngm:aggregator-feed a skos:Concept ;
rdfs:label "Aggregator Feed"@en .
ngm:agi a owl:Class ;
rdfs:comment "Artificial General Intelligence refers to the hypothetical capability of an AI system to perform any intellectual task that a human can do, characterized by flexibility, adaptability, and generalization across diverse domains."@en ;
rdfs:label "AGI"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:autonomous-system ;
vc:relatedTo ngm:large-language-models ;
vc:slug "agi" ;
vc:sourceDomain "artificial-intelligence" .
ngm:agi-race a skos:Concept ;
rdfs:label "Agi Race"@en .
ngm:agi-timelines a owl:Class ;
rdfs:comment "AGI timelines are structured probabilistic forecasts estimating when artificial general intelligence — AI matching or exceeding human cognitive ability across most economically valuable tasks — might be achieved. Such forecasts aggregate expert surveys (AI Impacts ESPAI 2022/2023), compute-scaling extrapolations (biological anchors model, Cotra 2020/2022), benchmark-progress curves (Metaculus, Manifold Markets), and Bayesian models of research milestones to produce probability distributions over future dates. As of mid-2026, median estimates cluster in the 2030–2047 range depending on methodology. Timelines are inherently uncertain and contested, and they materially influence AI safety research prioritisation, alignment investment, compute governance thresholds, and public policy."@en ;
rdfs:label "AGI Timelines"@en ;
rdfs:subClassOf ngm:capability-forecasting ;
rdfs:subClassOf ngm:time-series-forecasting ;
rdfs:subClassOf _:r196 ;
rdfs:subClassOf _:r197 ;
rdfs:subClassOf _:r198 ;
rdfs:subClassOf _:r199 ;
rdfs:subClassOf _:r200 ;
rdfs:subClassOf _:r201 ;
rdfs:subClassOf _:r202 ;
rdfs:subClassOf _:r203 ;
vc:contrastsWith ngm:gartner-prediction ;
vc:dependsOn ngm:compute-cluster ;
vc:dependsOn ngm:compute-resources ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:emergent-behavior ;
vc:dependsOn ngm:large-language-models ;
vc:enables ngm:ai-governance ;
vc:enables ngm:ai-policy ;
vc:enables ngm:alignment-research ;
vc:enables ngm:compute-governance ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:bayesian-inference ;
vc:hasPart ngm:expert-elicitation ;
vc:hasPart ngm:performance-benchmarks ;
vc:hasPart ngm:prediction-markets ;
vc:hasPart ngm:superforecasting ;
vc:implements ngm:bayesian-inference ;
vc:implements ngm:time-series-forecasting ;
vc:qualityScore "0.88"^^xsd:float ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:alignment ;
vc:relatedTo ngm:artificial-general-intelligence ;
vc:relatedTo ngm:brain-computer-interfaces ;
vc:relatedTo ngm:cognitive-science ;
vc:relatedTo ngm:compute-governance ;
vc:relatedTo ngm:economic-impact-of-ai ;
vc:relatedTo ngm:existential-risk ;
vc:relatedTo ngm:frontier-ai ;
vc:relatedTo ngm:gartner-prediction ;
vc:relatedTo ngm:labour-market-disruption ;
vc:relatedTo ngm:robustness ;
vc:relatedTo ngm:transformative-ai ;
vc:requires ngm:artificial-general-intelligence ;
vc:requires ngm:evaluation-benchmarks-and-leaderboards ;
vc:requires ngm:model-evaluation ;
vc:requires ngm:reasoning ;
vc:requires ngm:scaling-laws ;
vc:slug "agi-timelines" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:ai-safety-institute ;
vc:supports ngm:ai-safety ;
vc:supports ngm:ai-safety-institute ;
vc:supports ngm:ai-safety-research ;
vc:supports ngm:aisi-frontier-ai-safety-framework ;
vc:supports ngm:alignment ;
vc:supports ngm:alignment-techniques ;
vc:supports ngm:compute-governance ;
vc:uses ngm:arc-agi ;
vc:uses ngm:autonomous-agent ;
vc:uses ngm:autonomous-reasoning ;
vc:uses ngm:bayesian-inference ;
vc:uses ngm:expert-elicitation ;
vc:uses ngm:multimodal-ai-architecture-ai ;
vc:uses ngm:neural-network ;
vc:uses ngm:performance-benchmarks ;
vc:uses ngm:prediction-markets ;
vc:uses ngm:reinforcement-learning ;
vc:uses ngm:scaling-laws .
ngm:agile-design a skos:Concept ;
rdfs:label "Agile Design"@en .
ngm:agile-development a skos:Concept ;
rdfs:label "Agile Development"@en .
ngm:agile-manifesto a skos:Concept ;
rdfs:label "Agile Manifesto"@en .
ngm:agile-manifesto-2001 a skos:Concept ;
rdfs:label "Agile Manifesto 2001"@en .
ngm:agile-methodology a skos:Concept ;
rdfs:label "Agile Methodology"@en .
ngm:agile-retrospective a skos:Concept ;
rdfs:label "Agile Retrospective"@en .
ngm:agile-software-development a owl:Class ;
rdfs:comment "Agile Software Development is a family of iterative, incremental approaches to building software that prioritise working product increments, continuous stakeholder collaboration, and rapid adaptation to changing requirements over rigid up-front planning. Rooted in the 2001 Agile Manifesto, it encompasses frameworks such as Scrum, Kanban, Extreme Programming, and SAFe, each operationalising core values through time-boxed iterations, cross-functional teams, and frequent feedback loops. Agile practices shorten the feedback cycle between developers and end users, reduce the cost of change, and improve delivery predictability by surfacing risk early. It has become the dominant paradigm for professional software delivery and is increasingly applied to hardware, policy, and organisational transformation."@en ;
rdfs:label "Agile Software Development"@en ;
rdfs:subClassOf ngm:software-engineering ;
rdfs:subClassOf ngm:software-engineering-domain ;
rdfs:subClassOf _:r1484 ;
rdfs:subClassOf _:r1485 ;
rdfs:subClassOf _:r1486 ;
rdfs:subClassOf _:r1487 ;
rdfs:subClassOf _:r1488 ;
vc:bridgesTo ngm:distributed-systems ;
vc:bridgesTo ngm:mlops ;
vc:bridgesTo ngm:organisational-learning ;
vc:contrastsWith ngm:big-design-up-front ;
vc:contrastsWith ngm:waterfall-model ;
vc:enables ngm:continuous-delivery ;
vc:enables ngm:devops ;
vc:enables ngm:lean-software-development ;
vc:enables ngm:test-driven-development ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:extreme-programming ;
vc:hasPart ngm:kanban ;
vc:hasPart ngm:retrospective ;
vc:hasPart ngm:scrum ;
vc:hasPart ngm:sprint ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:distributed-teams ;
vc:relatedTo ngm:project-management ;
vc:relatedTo ngm:software-architecture ;
vc:requires ngm:continuous-integration ;
vc:requires ngm:software-development ;
vc:requires ngm:version-control ;
vc:slug "agile-software-development" ;
vc:sourceDomain "distributed-collaboration" ;
vc:standardizedBy ngm:agile-manifesto ;
vc:standardizedBy ngm:scaled-agile-framework ;
vc:uses ngm:pair-programming ;
vc:uses ngm:product-backlog ;
vc:uses ngm:user-story .
ngm:agisoft-metashape a skos:Concept ;
rdfs:label "Agisoft Metashape"@en .
ngm:agntcy a skos:Concept ;
rdfs:label "Agntcy"@en .
ngm:agntcy-collective a skos:Concept ;
rdfs:label "Agntcy Collective"@en .
ngm:agreement-protocol a owl:Class ;
rdfs:comment "An Agreement Protocol is a distributed protocol specifically designed to enable multiple independent nodes to reach consensus on a single value, decision, or sequence of events despite the presence of failures, network asynchrony, and potentially malicious participants. Agreement protocols must satisfy safety (all honest nodes agree on the same value), liveness (the protocol eventually terminates), and validity (the agreed value was proposed by some participant), and their design space is constrained by impossibility results such as the FLP theorem and Byzantine Agreement bounds."@en ;
rdfs:label "Agreement Protocol"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf ngm:distributed-protocol ;
rdfs:subClassOf _:r1489 ;
rdfs:subClassOf _:r1490 ;
rdfs:subClassOf _:r1491 ;
rdfs:subClassOf _:r1492 ;
rdfs:subClassOf _:r1493 ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:enables ngm:blockchain-governance ;
vc:enables ngm:blockchain-protocol ;
vc:enables ngm:finality ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:consensus-algorithm ;
vc:hasPart ngm:consensus-mechanism ;
vc:implements ngm:nakamoto-consensus ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:blockchain-network ;
vc:relatedTo ngm:blockchain-scalability ;
vc:relatedTo ngm:node ;
vc:relatedTo ngm:validator-node ;
vc:requires ngm:byzantine-fault-tolerance ;
vc:requires ngm:distributed-systems ;
vc:requires ngm:fault-tolerance ;
vc:slug "agreement-protocol" ;
vc:sourceDomain "blockchain" .
ngm:agricultural-genomics a skos:Concept ;
rdfs:label "Agricultural Genomics"@en .
ngm:agricultural-robot a owl:Class ;
rdfs:comment "Agricultural Robot - A semi-autonomous or fully autonomous platform equipped with Precision Agriculture Sensors, Manipulation Modules, and Crop Analysis Systems for performing field operations including planting, selective weeding, harvesting, and health monitoring whilst minimising s..."@en ;
rdfs:label "Agricultural Robot"@en ;
rdfs:subClassOf ngm:mobile-robot ;
rdfs:subClassOf ngm:robo-robot-type ;
rdfs:subClassOf ngm:robotics ;
rdfs:subClassOf ngm:service-robot ;
rdfs:subClassOf _:r1494 ;
rdfs:subClassOf _:r1495 ;
rdfs:subClassOf _:r1496 ;
rdfs:subClassOf _:r1497 ;
skos:broader ngm:robo-robot-type ;
skos:broader ngm:robotics ;
vc:enables ngm:crop-quality-improvement ;
vc:enables ngm:environmental-sustainability ;
vc:enables ngm:labour-cost-reduction ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:precision-agriculture ;
vc:isPartOf ngm:sustainable-farming ;
vc:qualityScore "0.53"^^xsd:float ;
vc:requires ngm:computer-vision ;
vc:requires ngm:environmental-sensor ;
vc:requires ngm:soft-robotics ;
vc:requires ngm:terrain-navigation ;
vc:slug "agricultural-robot" ;
vc:sourceDomain "robotics" .
ngm:agricultural-robotics a owl:Class ;
rdfs:comment "Agricultural robotics is the engineering discipline concerned with the design, deployment, and operation of autonomous and semi-autonomous robotic systems applied to crop and livestock farming tasks, including soil preparation, precision planting, selective harvesting, agrochemical application, irrigation management, and herd monitoring. These systems integrate computer vision, machine learning, GNSS positioning, and mechatronic manipulation to function reliably in unstructured outdoor environments subject to variable terrain, lighting, weather, and biological variability. The field is a primary enabler of precision agriculture, supporting reductions in agrochemical inputs, labour dependency, and resource waste while maintaining or increasing yields. Commercial deployment spans ground-based field robots, unmanned aerial vehicles, and autonomous underwater and amphibious systems for aquaculture."@en ;
rdfs:label "Agricultural Robotics"@en ;
rdfs:subClassOf ngm:autonomous-robot ;
rdfs:subClassOf _:r1498 ;
rdfs:subClassOf _:r1499 ;
rdfs:subClassOf _:r1500 ;
rdfs:subClassOf _:r1501 ;
rdfs:subClassOf _:r1502 ;
rdfs:subClassOf _:r1503 ;
rdfs:subClassOf _:r1504 ;
vc:bridgesTo ngm:data-analytics ;
vc:bridgesTo ngm:supply-chain-management ;
vc:contrastsWith ngm:industrial-robotics ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:edge-computing ;
vc:enables ngm:crop-monitoring ;
vc:enables ngm:precision-agriculture ;
vc:enables ngm:variable-rate-application ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:computer-vision-system ;
vc:hasPart ngm:end-effector ;
vc:hasPart ngm:mobile-robot-platform ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:digital-twin ;
vc:relatedTo ngm:internet-of-things ;
vc:relatedTo ngm:remote-sensing ;
vc:relatedTo ngm:swarm-robotics ;
vc:requires ngm:autonomous-navigation ;
vc:requires ngm:object-detection ;
vc:requires ngm:path-planning ;
vc:requires ngm:sensor-fusion ;
vc:slug "agricultural-robotics" ;
vc:sourceDomain "robotics" ;
vc:uses ngm:computer-vision ;
vc:uses ngm:lidar ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:robotic-arm ;
vc:uses ngm:rtk-gps ;
vc:uses ngm:unmanned-aerial-vehicle .
ngm:agroterrorism a skos:Concept ;
rdfs:label "Agroterrorism"@en .
ngm:ai a skos:Concept ;
rdfs:label "AI"@en .
ngm:ai-acceleration-gap a owl:Class ;
rdfs:comment "The compounding divergence between the rapid advancement of frontier AI capabilities and the slower adoption and integration of these technologies by the median enterprise or individual."@en ;
rdfs:label "AI Acceleration Gap"@en ;
rdfs:subClassOf ngm:ai-research-area ;
skos:broader ngm:ai-research-area ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-research-area ;
vc:relatedTo ngm:competitive-advantage ;
vc:slug "ai-acceleration-gap" ;
vc:sourceDomain "economics" .
ngm:ai-accelerator a owl:Class ;
rdfs:comment "An AI accelerator is a class of specialised hardware designed to speed up machine learning workloads, particularly the dense linear algebra of neural network training and inference. Common forms include GPUs, tensor processing units, neural processing units, and custom application-specific integrated circuits that exploit massive parallelism, reduced-precision arithmetic, and high-bandwidth memory. By offloading matrix and tensor operations from general-purpose CPUs, AI accelerators deliver order-of-magnitude gains in throughput and energy efficiency for deep learning."@en ;
rdfs:label "AI Accelerator"@en ;
rdfs:subClassOf ngm:hardware-accelerator ;
rdfs:subClassOf _:r204 ;
rdfs:subClassOf _:r205 ;
rdfs:subClassOf _:r206 ;
vc:bridgesTo ngm:compute-infrastructure ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:enables ngm:deep-learning ;
vc:enables ngm:distributed-training ;
vc:enables ngm:neural-network ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:high-bandwidth-memory ;
vc:hasPart ngm:systolic-array ;
vc:isPartOf ngm:compute-infrastructure ;
vc:isPartOf ngm:gpu-cluster ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:gpu ;
vc:relatedTo ngm:nvidia-corporation ;
vc:relatedTo ngm:nvlink ;
vc:relatedTo ngm:tpu ;
vc:requires ngm:data-centre ;
vc:slug "ai-accelerator" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:cloud-computing ;
vc:uses ngm:matrix-multiplication .
ngm:ai-accountability a owl:Class ;
rdfs:comment "AI Accountability is the set of mechanisms, obligations, and institutional structures that ensure developers, deployers, and operators of AI systems can be held responsible for the outcomes those systems produce. It encompasses technical auditability, legal liability, organisational governance, and redress pathways for harms caused by algorithmic decisions. Accountability frameworks bind technical transparency measures to enforceable consequences, distinguishing it from voluntary explainability efforts. Effective AI accountability requires clear assignment of responsibility across the AI value chain—from data collection through deployment and monitoring."@en ;
rdfs:label "AI Accountability"@en ;
rdfs:subClassOf ngm:accountability ;
rdfs:subClassOf ngm:ai-governance ;
rdfs:subClassOf ngm:responsible-ai ;
rdfs:subClassOf _:r207 ;
rdfs:subClassOf _:r208 ;
rdfs:subClassOf _:r209 ;
rdfs:subClassOf _:r210 ;
rdfs:subClassOf _:r211 ;
rdfs:subClassOf _:r212 ;
rdfs:subClassOf _:r213 ;
rdfs:subClassOf _:r214 ;
rdfs:subClassOf _:r215 ;
rdfs:subClassOf _:r216 ;
rdfs:subClassOf _:r217 ;
rdfs:subClassOf _:r218 ;
rdfs:subClassOf _:r219 ;
rdfs:subClassOf _:r220 ;
vc:contrastsWith ngm:self-regulation ;
vc:contrastsWith ngm:voluntary-transparency ;
vc:dependsOn ngm:artificial-intelligence ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:foundation-model ;
vc:dependsOn ngm:liability ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:enables ngm:ai-alignment ;
vc:enables ngm:ai-safety ;
vc:enables ngm:ai-trustworthiness ;
vc:enables ngm:digital-rights ;
vc:enables ngm:fairness ;
vc:enables ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:ai-ethics-board ;
vc:hasPart ngm:ai-impact-assessment ;
vc:hasPart ngm:ai-model-card ;
vc:hasPart ngm:algorithmic-auditing ;
vc:hasPart ngm:audit-trail ;
vc:hasPart ngm:conformity-assessment ;
vc:hasPart ngm:model-cards ;
vc:hasPart ngm:post-market-monitoring ;
vc:hasPart ngm:redress-mechanism ;
vc:implements ngm:eu-ai-act-regulatory-instrument ;
vc:implements ngm:gdpr ;
vc:implements ngm:iso-iec-42001 ;
vc:implements ngm:nist-ai-rmf ;
vc:implements ngm:oecd-ai-principles ;
vc:qualityScore "0.87"^^xsd:float ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:ai-ethics-board ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:algorithmic-accountability ;
vc:relatedTo ngm:bias-mitigation-techniques ;
vc:relatedTo ngm:centre-for-data-ethics-and-innovation ;
vc:relatedTo ngm:gdpr ;
vc:relatedTo ngm:information-commissioner-s-office ;
vc:relatedTo ngm:iso-iec-jtc1-sc42 ;
vc:relatedTo ngm:liability ;
vc:requires ngm:data-governance ;
vc:requires ngm:explainability ;
vc:requires ngm:explainable-ai ;
vc:requires ngm:human-oversight ;
vc:requires ngm:risk-management ;
vc:requires ngm:transparency ;
vc:slug "ai-accountability" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:standardizedBy ngm:iso-iec-jtc1-sc42 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:standardizedBy ngm:oecd-ai-principles ;
vc:supports ngm:ai-alignment ;
vc:supports ngm:ai-safety ;
vc:supports ngm:ai-trustworthiness ;
vc:supports ngm:regulatory-compliance ;
vc:supports ngm:responsible-ai ;
vc:uses ngm:ai-impact-assessment ;
vc:uses ngm:ai-model-card ;
vc:uses ngm:algorithmic-auditing ;
vc:uses ngm:audit-trail ;
vc:uses ngm:explainability ;
vc:uses ngm:post-market-monitoring ;
vc:uses ngm:redress-mechanism .
ngm:ai-acquisitions-and-m-a a skos:Concept ;
rdfs:label "AI Acquisitions And M A"@en .
ngm:ai-act-product-safety a skos:Concept ;
rdfs:label "AI Act Product Safety"@en .
ngm:ai-adoption a owl:Class ;
rdfs:comment "AI Adoption is the multi-dimensional socio-technical process by which organisations, sectors, national economies and individual workers progressively integrate artificial-intelligence systems — classical machine learning, deep learning, foundation models, generative AI and agentic AI — into produ..."@en ;
rdfs:label "AI Adoption"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:digital-transformation ;
rdfs:subClassOf ngm:innovation-diffusion ;
rdfs:subClassOf ngm:organisational-change ;
rdfs:subClassOf ngm:socio-technical-process ;
rdfs:subClassOf ngm:technology-adoption ;
rdfs:subClassOf _:r221 ;
rdfs:subClassOf _:r222 ;
rdfs:subClassOf _:r223 ;
rdfs:subClassOf _:r224 ;
rdfs:subClassOf _:r225 ;
rdfs:subClassOf _:r226 ;
rdfs:subClassOf _:r227 ;
rdfs:subClassOf _:r228 ;
rdfs:subClassOf _:r229 ;
rdfs:subClassOf _:r230 ;
rdfs:subClassOf _:r231 ;
rdfs:subClassOf _:r232 ;
rdfs:subClassOf _:r233 ;
rdfs:subClassOf _:r234 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:organizational-change ;
vc:contrastsWith ngm:ai-rejection ;
vc:contrastsWith ngm:build-internally-only-posture ;
vc:contrastsWith ngm:manual-operation ;
vc:contrastsWith ngm:outsourcing-strategy ;
vc:contrastsWith ngm:pre-ai-digital-transformation ;
vc:dependsOn ngm:cloud-computing ;
vc:dependsOn ngm:data-quality ;
vc:dependsOn ngm:foundation-model-availability ;
vc:dependsOn ngm:investor-capital ;
vc:dependsOn ngm:regulatory-clarity ;
vc:dependsOn ngm:skilled-workforce ;
vc:enables ngm:cost-reduction ;
vc:enables ngm:customer-experience ;
vc:enables ngm:decision-augmentation ;
vc:enables ngm:innovation-velocity ;
vc:enables ngm:process-automation ;
vc:enables ngm:productivity-improvement ;
vc:enables ngm:revenue-growth ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ai-governance-framework ;
vc:hasPart ngm:ai-strategy ;
vc:hasPart ngm:ai-talent ;
vc:hasPart ngm:ai-use-case-portfolio ;
vc:hasPart ngm:ai-vendor-stack ;
vc:hasPart ngm:change-management ;
vc:hasPart ngm:data-foundation ;
vc:hasPart ngm:mlops ;
vc:implements ngm:diffusion-of-innovations-theory ;
vc:implements ngm:organisational-learning ;
vc:implements ngm:stage-gate-adoption-process ;
vc:implements ngm:technology-acceptance-model ;
vc:implements ngm:toe-framework ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:ai-investment ;
vc:relatedTo ngm:ai-productivity-paradox ;
vc:relatedTo ngm:ai-regulation ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:ai-talent-war ;
vc:relatedTo ngm:foundation-model ;
vc:relatedTo ngm:generative-ai ;
vc:requires ngm:ai-talent ;
vc:requires ngm:change-management ;
vc:requires ngm:compute-infrastructure ;
vc:requires ngm:data-infrastructure ;
vc:requires ngm:executive-sponsorship ;
vc:requires ngm:governance-framework ;
vc:requires ngm:risk-management-framework ;
vc:slug "ai-adoption" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:iso-iec-42001-ai-management-system ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:standardizedBy ngm:oecd-ai-principles ;
vc:standardizedBy ngm:uk-ai-opportunities-action-plan ;
vc:standardizedBy ngm:us-ai-action-plan-2025 ;
vc:supports ngm:economic-growth ;
vc:supports ngm:knowledge-graph-publication-classifier ;
vc:supports ngm:national-competitiveness ;
vc:supports ngm:sectoral-productivity ;
vc:supports ngm:workforce-transformation ;
vc:uses ngm:agentic-ai ;
vc:uses ngm:computer-vision ;
vc:uses ngm:generative-ai ;
vc:uses ngm:large-language-models ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:microsoft-copilot ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:predictive-analytics .
ngm:ai-adoption-barriers a owl:Class ;
rdfs:comment "The economic, psychological, and social factors that hinder the widespread integration and utilization of artificial intelligence in society."@en ;
rdfs:label "AI Adoption Barriers"@en ;
rdfs:subClassOf ngm:ai-governance ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:artificial-intelligence ;
vc:slug "ai-adoption-barriers" ;
vc:sourceDomain "economics" .
ngm:ai-adoption-metrics a skos:Concept ;
rdfs:label "AI Adoption Metrics"@en .
ngm:ai-adoption-platform a owl:Class ;
rdfs:comment "An integrated software suite that supports the strategic planning, execution, and tracking of AI implementation within an organization."@en ;
rdfs:label "AI Adoption Platform"@en ;
rdfs:subClassOf ngm:enterprise-ai ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-maturity-assessment ;
vc:relatedTo ngm:enterprise-ai ;
vc:slug "ai-adoption-platform" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-adoption-rates a owl:Class ;
rdfs:comment "Quantitative metrics tracking the penetration, frequency, and demographic distribution of artificial intelligence tool usage across consumer and enterprise populations."@en ;
rdfs:label "AI Adoption Rates"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:generative-ai ;
vc:relatedTo ngm:intelligent-automation ;
vc:slug "ai-adoption-rates" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-advertising a owl:Class ;
rdfs:comment "The integration of advertising mechanisms, such as sponsored content or product recommendations, directly into the interfaces and decision-making processes of artificial intelligence agents and chatbots."@en ;
rdfs:label "AI Advertising"@en ;
rdfs:subClassOf ngm:advertising ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:digital-marketing ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:programmatic-advertising ;
vc:slug "ai-advertising" ;
vc:sourceDomain "economics" .
ngm:ai-agent a owl:Class ;
rdfs:comment "A software system that perceives its environment, makes decisions and takes actions to achieve goals, often using a language model together with tools and memory."@en ;
rdfs:label "AI Agent"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:autonomous-agent ;
rdfs:subClassOf ngm:goal-directed-system ;
rdfs:subClassOf _:r258 ;
rdfs:subClassOf _:r259 ;
rdfs:subClassOf _:r260 ;
rdfs:subClassOf _:r261 ;
rdfs:subClassOf _:r262 ;
rdfs:subClassOf _:r263 ;
rdfs:subClassOf _:r264 ;
rdfs:subClassOf _:r265 ;
rdfs:subClassOf _:r266 ;
rdfs:subClassOf _:r267 ;
rdfs:subClassOf _:r268 ;
rdfs:subClassOf _:r269 ;
rdfs:subClassOf _:r270 ;
skos:broader ngm:ai-application ;
vc:bridgesTo ngm:computer-use ;
vc:bridgesTo ngm:decentralised-autonomous-organisation ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:robotic-process-automation ;
vc:bridgesTo ngm:robotics ;
vc:bridgesTo ngm:scientific-discovery ;
vc:bridgesTo ngm:smart-contract ;
vc:contrastsWith ngm:chatbot ;
vc:contrastsWith ngm:conversational-ai ;
vc:contrastsWith ngm:robotic-process-automation ;
vc:contrastsWith ngm:rule-based-systems ;
vc:dependsOn ngm:agent-frameworks ;
vc:dependsOn ngm:api ;
vc:dependsOn ngm:cognitive-architecture ;
vc:dependsOn ngm:foundation-model ;
vc:dependsOn ngm:vector-database ;
vc:enables ngm:automated-planning ;
vc:enables ngm:autonomous-decision-making ;
vc:enables ngm:multi-agent-systems ;
vc:enables ngm:software-development-automation ;
vc:enables ngm:task-automation ;
vc:enables ngm:workflow-orchestration ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:agent-loop ;
vc:hasPart ngm:agent-memory ;
vc:hasPart ngm:observation-interface ;
vc:hasPart ngm:perception ;
vc:hasPart ngm:planning-and-scheduling ;
vc:hasPart ngm:reasoning-engine ;
vc:hasPart ngm:sandboxing ;
vc:hasPart ngm:tool-registry ;
vc:implements ngm:belief-desire-intention ;
vc:implements ngm:plan-and-execute ;
vc:implements ngm:re-act-pattern ;
vc:implements ngm:reflexion ;
vc:implements ngm:tree-of-thoughts ;
vc:qualityScore "0.89"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:ai-agents ;
vc:relatedTo ngm:deep-reinforcement-learning ;
vc:relatedTo ngm:digital-twin ;
vc:relatedTo ngm:emergence ;
vc:relatedTo ngm:multi-agent-reinforcement-learning ;
vc:relatedTo ngm:prompt-injection ;
vc:relatedTo ngm:reinforcement-learning ;
vc:relatedTo ngm:swarm-intelligence ;
vc:requires ngm:context-window ;
vc:requires ngm:foundation-model ;
vc:requires ngm:function-calling ;
vc:requires ngm:large-language-models ;
vc:requires ngm:memory-management ;
vc:requires ngm:reasoning-engine ;
vc:requires ngm:tool-use ;
vc:slug "ai-agent" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:agent-communication-protocol ;
vc:standardizedBy ngm:agent-to-agent-protocol ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:model-context-protocol ;
vc:supports ngm:ai-alignment ;
vc:supports ngm:ai-safety ;
vc:supports ngm:explainability ;
vc:supports ngm:human-in-the-loop ;
vc:uses ngm:agent-communication-protocol ;
vc:uses ngm:chain-of-thought ;
vc:uses ngm:function-calling ;
vc:uses ngm:orchestration ;
vc:uses ngm:prompt-engineering ;
vc:uses ngm:retrieval-augmented-generation ;
vc:uses ngm:sandboxing ;
vc:uses ngm:vector-database .
ngm:ai-agent-acquisition a owl:Class ;
rdfs:comment "The strategic purchase of AI agent startups by larger technology companies to gain capabilities, talent, or market position."@en ;
rdfs:label "AI Agent Acquisition"@en ;
rdfs:subClassOf ngm:data-management ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:ai-venture-capital ;
vc:slug "ai-agent-acquisition" ;
vc:sourceDomain "economics" .
ngm:ai-agent-asset-ownership a skos:Concept ;
rdfs:label "AI Agent Asset Ownership"@en .
ngm:ai-agent-capabilities a owl:Class ;
rdfs:comment "The specific functional attributes, such as tool use, multi-session support, and autonomous decision-making, that define the operational scope of an AI agent."@en ;
rdfs:label "AI Agent Capabilities"@en ;
rdfs:subClassOf ngm:tool-use ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:agentic-workflow ;
vc:relatedTo ngm:claude ;
vc:relatedTo ngm:tool-use ;
vc:slug "ai-agent-capabilities" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-agent-coordination a owl:Class ;
rdfs:comment "AI Agent Coordination is the set of mechanisms by which multiple autonomous AI agents align their actions, share state, allocate tasks, and resolve conflicts to achieve goals that exceed any single agent's capability. It covers communication protocols, role assignment, consensus, and negotiation, and may be centralized through an orchestrator or fully decentralized. Effective coordination is essential for multi-agent systems operating over shared resources or distributed ledgers."@en ;
rdfs:label "AI Agent Coordination"@en ;
rdfs:subClassOf ngm:ai-agent-system ;
rdfs:subClassOf ngm:decentralised-coordination ;
rdfs:subClassOf ngm:multi-agent-system ;
rdfs:subClassOf _:r235 ;
rdfs:subClassOf _:r236 ;
rdfs:subClassOf _:r237 ;
rdfs:subClassOf _:r238 ;
rdfs:subClassOf _:r239 ;
rdfs:subClassOf _:r240 ;
rdfs:subClassOf _:r241 ;
rdfs:subClassOf _:r242 ;
rdfs:subClassOf _:r243 ;
rdfs:subClassOf _:r244 ;
vc:contrastsWith ngm:agent-orchestrator ;
vc:contrastsWith ngm:centralised-orchestration ;
vc:contrastsWith ngm:hierarchical-control ;
vc:contrastsWith ngm:single-agent-system ;
vc:dependsOn ngm:large-language-model ;
vc:dependsOn ngm:natural-language-processing ;
vc:dependsOn ngm:planning-algorithm ;
vc:dependsOn ngm:reinforcement-learning ;
vc:dependsOn ngm:tool-use ;
vc:enables ngm:agentic-system ;
vc:enables ngm:ai-agent-system ;
vc:enables ngm:autonomous-ai-agents ;
vc:enables ngm:dao-governance ;
vc:enables ngm:emergent-behavior ;
vc:enables ngm:knowledge-sharing ;
vc:enables ngm:load-balancing ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:blackboard-system ;
vc:hasPart ngm:contract-net-protocol ;
vc:hasPart ngm:leader-election ;
vc:hasPart ngm:message-passing ;
vc:hasPart ngm:negotiation-protocol ;
vc:hasPart ngm:orchestration-pattern ;
vc:hasPart ngm:role-assignment ;
vc:hasPart ngm:task-allocation ;
vc:hasPart ngm:task-auction ;
vc:implements ngm:agent-to-agent-protocol ;
vc:implements ngm:contract-net-protocol ;
vc:implements ngm:distributed-constraint-optimisation ;
vc:implements ngm:fipa ;
vc:implements ngm:mechanism-design ;
vc:implements ngm:model-context-protocol ;
vc:implements ngm:swarm-intelligence ;
vc:qualityScore "0.85"^^xsd:float ;
vc:relatedTo ngm:dao-governance ;
vc:relatedTo ngm:deadlock-prevention ;
vc:relatedTo ngm:decentralised-coordination ;
vc:relatedTo ngm:distributed-constraint-optimisation ;
vc:relatedTo ngm:game-theory ;
vc:relatedTo ngm:knowledge-sharing ;
vc:relatedTo ngm:mechanism-design ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:reinforcement-learning ;
vc:relatedTo ngm:rgb-and-client-side-validation ;
vc:requires ngm:byzantine-fault-tolerance ;
vc:requires ngm:communication-protocol ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:interoperability ;
vc:requires ngm:trust-management ;
vc:slug "ai-agent-coordination" ;
vc:sourceDomain "ai" ;
vc:supports ngm:ai-accountability ;
vc:supports ngm:ai-safety ;
vc:supports ngm:human-oversight ;
vc:supports ngm:interoperability ;
vc:supports ngm:responsible-ai ;
vc:uses ngm:auto-gen ;
vc:uses ngm:byzantine-fault-tolerance ;
vc:uses ngm:crew-ai ;
vc:uses ngm:deadlock-prevention ;
vc:uses ngm:game-theory ;
vc:uses ngm:lang-graph ;
vc:uses ngm:smart-contract .
ngm:ai-agent-economic-interaction a skos:Concept ;
rdfs:label "AI Agent Economic Interaction"@en .
ngm:ai-agent-economies a skos:Concept ;
rdfs:label "AI Agent Economies"@en .
ngm:ai-agent-harness a owl:Class ;
rdfs:comment "The orchestration layer, tooling, and execution environment that wraps a foundational language model to enable autonomous task completion and reasoning."@en ;
rdfs:label "AI Agent Harness"@en ;
rdfs:subClassOf ngm:model ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-agent ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:model ;
vc:slug "ai-agent-harness" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-agent-identity a owl:Class ;
rdfs:comment "A persistent, verifiable digital identity assigned to an autonomous AI agent, enabling it to authenticate, sign transactions, and participate in decentralised systems on behalf of itself or a principal. AI agent identity encompasses credential issuance, key management, and delegation of authority scoped to the agent's operational context. Such identities may be anchored on a blockchain ledger to ensure auditability and prevent impersonation. They bridge self-sovereign identity (SSI) principles with agentic software systems."@en ;
rdfs:label "Ai Agent Identity"@en ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf ngm:verifiable-credentials ;
rdfs:subClassOf _:r1505 ;
rdfs:subClassOf _:r1506 ;
skos:broader ngm:blockchain ;
vc:bridgesTo ngm:decentralized-identifier ;
vc:bridgesTo ngm:self-sovereign-identity ;
vc:contrastsWith ngm:human-identity ;
vc:dependsOn ngm:blockchain ;
vc:dependsOn ngm:distributed-ledger ;
vc:enables ngm:autonomous-agent ;
vc:enables ngm:multi-agent-system ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:access-control ;
vc:relatedTo ngm:smart-contract ;
vc:relatedTo ngm:trust-framework ;
vc:requires ngm:cryptographic-infrastructure ;
vc:requires ngm:cryptographic-key-management ;
vc:slug "ai-agent-identity" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:accountability ;
vc:uses ngm:digital-signature ;
vc:uses ngm:verifiable-credential-vc ;
vc:uses ngm:verifiable-credentials .
ngm:ai-agent-liability a skos:Concept ;
rdfs:label "AI Agent Liability"@en .
ngm:ai-agent-misalignment a owl:Class ;
rdfs:comment "The phenomenon where AI agents exhibit behaviors or strategies that deviate from intended goals, such as unsanctioned social engineering."@en ;
rdfs:label "AI Agent Misalignment"@en ;
rdfs:subClassOf ngm:ai-safety-research ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-alignment ;
vc:relatedTo ngm:cybersecurity-evaluation ;
vc:slug "ai-agent-misalignment" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-agent-payments a owl:Class ;
rdfs:comment "AI Agent Payments refers to the infrastructure, protocols, and economic mechanisms that enable autonomous AI agents to initiate, authorise, and settle financial transactions on behalf of users or autonomously as principals, spanning micropayment rails for API service consumption, programmatic access to payment networks, and identity-bound wallet abstractions that constrain agent spending to authorised scopes and budgets."@en ;
rdfs:label "AI Agent Payments"@en ;
rdfs:subClassOf ngm:agentic-finance ;
vc:enables ngm:agentic-internet ;
vc:enables ngm:autonomous-task-execution ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:de-fi ;
vc:slug "ai-agent-payments" ;
vc:sourceDomain "finance" ;
vc:uses ngm:digital-currency ;
vc:uses ngm:lightning-network ;
vc:uses ngm:micropayments .
ngm:ai-agent-risk-disclosure a owl:Class ;
rdfs:comment "The practice of companies identifying AI agents as a material risk to their business model in regulatory filings such as SEC reports."@en ;
rdfs:label "AI Agent Risk Disclosure"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
skos:broader ngm:ai-governance-and-ethics ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-regulation ;
vc:relatedTo ngm:saas-disruption ;
vc:slug "ai-agent-risk-disclosure" ;
vc:sourceDomain "governance" .
ngm:ai-agent-smart-contracts a skos:Concept ;
rdfs:label "AI Agent Smart Contracts"@en .
ngm:ai-agent-system a owl:Class ;
rdfs:comment "An autonomous software entity that perceives its environment through Sensor Input|sensors, makes decisions using AI Techniques, and takes actions to achieve specific goals, capable of Machine Learning|learning from experience and adapting Adaptive Behavior|behaviour over time."@en ;
rdfs:label "AI Agent System"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:artificial-intelligence-core ;
rdfs:subClassOf _:r245 ;
rdfs:subClassOf _:r246 ;
rdfs:subClassOf _:r247 ;
rdfs:subClassOf _:r248 ;
rdfs:subClassOf _:r249 ;
rdfs:subClassOf _:r250 ;
rdfs:subClassOf _:r251 ;
rdfs:subClassOf _:r252 ;
rdfs:subClassOf _:r253 ;
rdfs:subClassOf _:r254 ;
rdfs:subClassOf _:r255 ;
rdfs:subClassOf _:r256 ;
rdfs:subClassOf _:r257 ;
skos:broader ngm:ai-application ;
vc:bridgesTo ngm:algorithmic-trading ;
vc:bridgesTo ngm:autonomous-economic-agent ;
vc:bridgesTo ngm:autonomous-robot ;
vc:bridgesTo ngm:bitcoin-proof-of-work-protocol ;
vc:bridgesTo ngm:bitcoin-trading-bot ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:cryptocurrency ;
vc:bridgesTo ngm:decentralized-finance-de-fi ;
vc:bridgesTo ngm:defi-agent ;
vc:bridgesTo ngm:intelligent-virtual-entity ;
vc:bridgesTo ngm:lightning-network-node ;
vc:bridgesTo ngm:metaverse ;
vc:bridgesTo ngm:payment-channel-management ;
vc:bridgesTo ngm:protocol-interaction ;
vc:bridgesTo ngm:robotics ;
vc:bridgesTo ngm:smart-contract ;
vc:enables ngm:adaptive-behaviour ;
vc:enables ngm:autonomous-operation ;
vc:enables ngm:browser-automation ;
vc:enables ngm:code-generation ;
vc:enables ngm:database-interaction ;
vc:enables ngm:file-system ;
vc:enables ngm:goal-achievement ;
vc:enables ngm:multi-agent-coordination ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:action-executor ;
vc:hasPart ngm:communication-protocol ;
vc:hasPart ngm:decision-engine ;
vc:hasPart ngm:goal-planner ;
vc:hasPart ngm:knowledge-base ;
vc:hasPart ngm:learning-module ;
vc:hasPart ngm:memory-system ;
vc:hasPart ngm:perception-system ;
vc:hasPart ngm:tool-use ;
vc:implements ngm:active-learning ;
vc:implements ngm:autonomous-behavior ;
vc:implements ngm:decision-making ;
vc:implements ngm:imitation-learning ;
vc:implements ngm:meta-learning ;
vc:implements ngm:planning-algorithm ;
vc:implements ngm:reinforcement-learning ;
vc:implements ngm:transfer-learning ;
vc:qualityScore "0.92"^^xsd:float ;
vc:requires ngm:action-space ;
vc:requires ngm:api-access ;
vc:requires ngm:authentication-system ;
vc:requires ngm:environment-model ;
vc:requires ngm:resource-budget ;
vc:requires ngm:reward-function ;
vc:requires ngm:sensor-input ;
vc:slug "ai-agent-system" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-agent-tool-selection a owl:Class ;
rdfs:comment "The process by which AI agents autonomously evaluate, choose, and invoke specific external tools or APIs to accomplish tasks, often based on dynamic criteria rather than fixed user preferences."@en ;
rdfs:label "AI Agent Tool Selection"@en ;
rdfs:subClassOf ngm:ai-agent ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-agent ;
vc:relatedTo ngm:tool-use ;
vc:slug "ai-agent-tool-selection" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-agents a owl:Class ;
rdfs:comment "AI Agents are software entities that combine a reasoning core (typically a large language model) with tool-use capabilities, memory, and a perception-action loop to autonomously pursue user-specified goals across multiple steps. They differ from single-shot inference systems by operating in iterative observe-think-act cycles, invoking external APIs, executing code, browsing the web, or delegating sub-tasks to specialised agents. The architecture integrates classical notions of rational agency with modern deep learning, spanning planning, grounding, and self-correction mechanisms. Safety, controllability, and alignment are first-class concerns because agents can initiate irreversible real-world side-effects."@en ;
rdfs:label "AI Agents"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:autonomous-agent ;
rdfs:subClassOf ngm:goal-directed-system ;
rdfs:subClassOf _:r271 ;
rdfs:subClassOf _:r272 ;
rdfs:subClassOf _:r273 ;
rdfs:subClassOf _:r274 ;
rdfs:subClassOf _:r275 ;
rdfs:subClassOf _:r276 ;
rdfs:subClassOf _:r277 ;
rdfs:subClassOf _:r278 ;
rdfs:subClassOf _:r279 ;
rdfs:subClassOf _:r280 ;
rdfs:subClassOf _:r281 ;
rdfs:subClassOf _:r282 ;
rdfs:subClassOf _:r283 ;
rdfs:subClassOf _:r284 ;
skos:broader ngm:ai-application ;
vc:bridgesTo ngm:agentic-internet ;
vc:bridgesTo ngm:computer-use ;
vc:bridgesTo ngm:decentralised-autonomous-organisation ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:robotic-system ;
vc:bridgesTo ngm:robotics ;
vc:bridgesTo ngm:smart-contracts ;
vc:contrastsWith ngm:chatbots ;
vc:contrastsWith ngm:conversational-ai ;
vc:contrastsWith ngm:robotic-process-automation ;
vc:contrastsWith ngm:single-agent-systems ;
vc:dependsOn ngm:agent-frameworks ;
vc:dependsOn ngm:cognitive-architecture ;
vc:dependsOn ngm:function-calling ;
vc:dependsOn ngm:task-planning ;
vc:dependsOn ngm:vector-databases ;
vc:enables ngm:autonomous-decision-making ;
vc:enables ngm:emergent-behavior ;
vc:enables ngm:multi-agent-systems ;
vc:enables ngm:scientific-discovery ;
vc:enables ngm:software-development-automation ;
vc:enables ngm:task-automation ;
vc:enables ngm:workflow-automation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:action-execution ;
vc:hasPart ngm:agent-loop ;
vc:hasPart ngm:agent-memory ;
vc:hasPart ngm:observation-interface ;
vc:hasPart ngm:orchestration ;
vc:hasPart ngm:perception ;
vc:hasPart ngm:planning-and-scheduling ;
vc:hasPart ngm:sandboxing ;
vc:hasPart ngm:tool-registry ;
vc:implements ngm:belief-desire-intention ;
vc:implements ngm:plan-and-execute ;
vc:implements ngm:re-act ;
vc:implements ngm:reflexion ;
vc:implements ngm:tree-of-thoughts ;
vc:qualityScore "0.91"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:ai-agent ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:coordination-protocol ;
vc:relatedTo ngm:deep-reinforcement-learning ;
vc:relatedTo ngm:emergence ;
vc:relatedTo ngm:human-in-the-loop ;
vc:relatedTo ngm:multi-agent-reinforcement-learning ;
vc:relatedTo ngm:prompt-injection ;
vc:relatedTo ngm:reinforcement-learning ;
vc:relatedTo ngm:swarm-intelligence ;
vc:requires ngm:context-window ;
vc:requires ngm:foundation-model ;
vc:requires ngm:function-calling ;
vc:requires ngm:large-language-models ;
vc:requires ngm:memory ;
vc:requires ngm:memory-store ;
vc:requires ngm:reasoning ;
vc:requires ngm:tool-use ;
vc:slug "ai-agents" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:agent-communication-protocol ;
vc:standardizedBy ngm:agent-to-agent-protocol ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:model-context-protocol ;
vc:supports ngm:ai-alignment ;
vc:supports ngm:ai-safety ;
vc:supports ngm:explainability ;
vc:supports ngm:human-in-the-loop ;
vc:uses ngm:agent-communication-protocol ;
vc:uses ngm:chain-of-thought ;
vc:uses ngm:orchestration ;
vc:uses ngm:prompt-engineering ;
vc:uses ngm:retrieval-augmented-generation ;
vc:uses ngm:sandboxing .
ngm:ai-alignment a owl:Class ;
rdfs:comment "The process of making AI systems' behaviour and goals consistent with human values, preferences, and intentions. AI alignment encompasses technical methods and research aimed at ensuring AI systems act in accordance with human interests, even as they become more capable."@en ;
rdfs:label "AI Alignment"@en ;
rdfs:subClassOf ngm:ai-safety ;
rdfs:subClassOf _:r285 ;
rdfs:subClassOf _:r286 ;
rdfs:subClassOf _:r287 ;
rdfs:subClassOf _:r288 ;
rdfs:subClassOf _:r289 ;
rdfs:subClassOf _:r290 ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:ai-governance ;
vc:bridgesTo ngm:ethics ;
vc:contrastsWith ngm:instrumental-convergence ;
vc:enables ngm:safe-ai-deployment ;
vc:enables ngm:trustworthy-ai ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:constitutional-ai-training-methodology ;
vc:hasPart ngm:scalable-oversight ;
vc:hasPart ngm:value-alignment ;
vc:isPartOf ngm:ai-governance-and-ethics ;
vc:isPartOf ngm:ai-safety ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:ai-robustness ;
vc:relatedTo ngm:explainable-ai ;
vc:relatedTo ngm:mesa-optimisation ;
vc:requires ngm:human-oversight ;
vc:requires ngm:reinforcement-learning-from-human-feedback ;
vc:requires ngm:reward-modelling ;
vc:slug "ai-alignment" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:ai-governance ;
vc:supports ngm:responsible-ai ;
vc:uses ngm:direct-preference-optimisation ;
vc:uses ngm:interpretability ;
vc:uses ngm:red-teaming .
ngm:ai-alignment-mechanism-design a skos:Concept ;
rdfs:label "AI Alignment Mechanism Design"@en .
ngm:ai-alliance a skos:Concept ;
rdfs:label "AI Alliance"@en .
ngm:ai-and-blockchain a skos:Concept ;
rdfs:label "AI And Blockchain"@en .
ngm:ai-animation a skos:Concept ;
rdfs:label "AI Animation"@en .
ngm:ai-anxiety a owl:Class ;
rdfs:comment "The psychological and social unease experienced by individuals and communities in response to the rapid advancement and potential disruptive impact of artificial intelligence."@en ;
rdfs:label "AI Anxiety"@en ;
rdfs:subClassOf ngm:ai-adoption ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-adoption ;
vc:relatedTo ngm:future-of-work ;
vc:relatedTo ngm:job-displacement ;
vc:slug "ai-anxiety" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-apis a skos:Concept ;
rdfs:label "AI Apis"@en .
ngm:ai-app-store a owl:Class ;
rdfs:comment "A centralized digital marketplace platform that enables the discovery, installation, and management of third-party applications and integrations for AI assistants and agents."@en ;
rdfs:label "AI App Store"@en ;
rdfs:subClassOf ngm:generative-ai ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:chatgpt ;
vc:relatedTo ngm:generative-ai ;
vc:relatedTo ngm:third-party-integration ;
vc:slug "ai-app-store" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-application a owl:Class ;
a skos:Concept ;
rdfs:comment "AI Application is the taxonomy hub for deployed uses of artificial intelligence across domains — encompassing conversational AI, computer vision, generative AI, healthcare AI, autonomous systems, fraud detection, and multimodal AI. It bridges AI research and real-world deployment, grouping systems by the function they perform rather than the techniques they use."@en ;
rdfs:label "AI Application"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf _:r22678 ;
rdfs:subClassOf _:r22679 ;
rdfs:subClassOf _:r22680 ;
rdfs:subClassOf _:r22681 ;
rdfs:subClassOf _:r22682 ;
rdfs:subClassOf _:r22683 ;
rdfs:subClassOf _:r22684 ;
rdfs:subClassOf _:r22685 ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:autonomous-driving ;
vc:hasPart ngm:autonomous-system ;
vc:hasPart ngm:computer-vision ;
vc:hasPart ngm:conversational-ai ;
vc:hasPart ngm:fraud-detection ;
vc:hasPart ngm:generative-ai ;
vc:hasPart ngm:healthcare-ai ;
vc:hasPart ngm:multimodal-ai-architecture-ai ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:ai-infrastructure ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:slug "ai-application" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:deep-learning ;
vc:uses ngm:machine-learning-discipline .
ngm:ai-applications a owl:Class ;
rdfs:comment "Domain-specific deployments of artificial intelligence technologies delivering measurable value across industries including healthcare diagnostics, autonomous vehicles, industrial automation, financial services, and personal assistants. AI Applications translate research-level techniques—machine learning models, natural language processing, computer vision—into production systems operating within real-world constraints of safety, reliability, and regulatory compliance."@en ;
rdfs:label "AI Applications"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf _:r291 ;
rdfs:subClassOf _:r292 ;
rdfs:subClassOf _:r293 ;
rdfs:subClassOf _:r294 ;
rdfs:subClassOf _:r295 ;
rdfs:subClassOf _:r296 ;
rdfs:subClassOf _:r297 ;
rdfs:subClassOf _:r298 ;
rdfs:subClassOf _:r299 ;
rdfs:subClassOf _:r300 ;
rdfs:subClassOf _:r301 ;
rdfs:subClassOf _:r302 ;
rdfs:subClassOf _:r303 ;
rdfs:subClassOf _:r304 ;
rdfs:subClassOf _:r305 ;
skos:broader ngm:ai-application ;
skos:broader ngm:artificial-intelligence ;
vc:contrastsWith ngm:ai-ethics ;
vc:contrastsWith ngm:ai-risk ;
vc:dependsOn ngm:deep-learning-framework ;
vc:dependsOn ngm:gpu-compute ;
vc:dependsOn ngm:training-data ;
vc:enables ngm:autonomous-decision-making ;
vc:enables ngm:autonomous-robot ;
vc:enables ngm:autonomous-system ;
vc:enables ngm:autonomous-vehicle ;
vc:enables ngm:decision-support ;
vc:enables ngm:intelligent-automation ;
vc:enables ngm:quality-control ;
vc:enables ngm:supply-chain-optimisation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:autonomous-navigation ;
vc:hasPart ngm:code-synthesis ;
vc:hasPart ngm:drug-discovery ;
vc:hasPart ngm:fraud-detection ;
vc:hasPart ngm:image-recognition ;
vc:hasPart ngm:predictive-analytics ;
vc:hasPart ngm:recommendation-system ;
vc:hasPart ngm:sentiment-analysis ;
vc:hasPart ngm:speech-recognition ;
vc:implements ngm:computer-vision ;
vc:implements ngm:deep-learning ;
vc:implements ngm:generative-ai ;
vc:implements ngm:natural-language-processing ;
vc:implements ngm:reinforcement-learning ;
vc:qualityScore "0.88"^^xsd:float ;
vc:relatedTo ngm:autonomous-ai-agents ;
vc:relatedTo ngm:autonomous-driving ;
vc:relatedTo ngm:deep-learning-framework ;
vc:relatedTo ngm:digital-asset ;
vc:relatedTo ngm:explainable-ai ;
vc:relatedTo ngm:hyperparameter-tuning ;
vc:relatedTo ngm:model-deployment ;
vc:relatedTo ngm:smart-contract ;
vc:relatedTo ngm:transfer-learning ;
vc:requires ngm:ai-governance ;
vc:requires ngm:ai-risk-management ;
vc:requires ngm:gdpr ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:iso-iec-42001-2023 ;
vc:requires ngm:nist-ai-rmf ;
vc:requires ngm:training-data ;
vc:slug "ai-applications" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:gdpr ;
vc:standardizedBy ngm:iso-iec-42001-2023 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:content-creation ;
vc:supports ngm:personalisation ;
vc:supports ngm:robotics-perception ;
vc:supports ngm:surveillance-systems ;
vc:uses ngm:computer-vision ;
vc:uses ngm:deep-learning ;
vc:uses ngm:diffusion-models ;
vc:uses ngm:generative-adversarial-networks ;
vc:uses ngm:generative-ai ;
vc:uses ngm:hyperparameter-tuning ;
vc:uses ngm:large-language-models ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:neural-network ;
vc:uses ngm:reinforcement-learning ;
vc:uses ngm:transfer-learning ;
vc:uses ngm:transformer .
ngm:ai-art a skos:Concept ;
rdfs:label "AI Art"@en .
ngm:ai-art-categorization a owl:Class ;
rdfs:comment "AI Art Categorization encompasses taxonomies, classification systems, and machine learning mods for organizing, labeling, and evaluating AI-generated and AI-assisted artworks based on creation modology, style, medium, aesthetic properties, and the degree of autonomous system involvement in the cr..."@en ;
rdfs:label "Ai Art Categorization"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:art-classification ;
rdfs:subClassOf _:r1507 ;
rdfs:subClassOf _:r1508 ;
skos:broader ngm:ai-application ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:governance ;
vc:enables ngm:art-curation ;
vc:enables ngm:authenticity-detection ;
vc:enables ngm:style-analysis ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:art-historical-knowledge ;
vc:requires ngm:computer-vision ;
vc:requires ngm:deep-learning ;
vc:slug "ai-art-categorization" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-art-generation a owl:Class ;
rdfs:comment "AI Art Generation is the production of visual artwork by generative models, most commonly text-to-image diffusion systems that synthesize images from natural-language prompts. Outputs can be steered through prompting, fine-tuning, and lightweight adapters such as LoRA or DreamBooth that teach a model new subjects or styles. It has reshaped creative workflows in illustration, concept art, and design while raising questions about training-data provenance and authorship."@en ;
rdfs:label "AI Art Generation"@en ;
rdfs:subClassOf ngm:creative-ai ;
rdfs:subClassOf ngm:generative-ai ;
rdfs:subClassOf ngm:image-generation ;
rdfs:subClassOf _:r306 ;
rdfs:subClassOf _:r307 ;
rdfs:subClassOf _:r308 ;
rdfs:subClassOf _:r309 ;
rdfs:subClassOf _:r310 ;
rdfs:subClassOf _:r311 ;
rdfs:subClassOf _:r312 ;
rdfs:subClassOf _:r313 ;
rdfs:subClassOf _:r314 ;
rdfs:subClassOf _:r315 ;
rdfs:subClassOf _:r316 ;
rdfs:subClassOf _:r317 ;
rdfs:subClassOf _:r318 ;
rdfs:subClassOf _:r319 ;
vc:contrastsWith ngm:ai-ethics ;
vc:contrastsWith ngm:explainable-ai ;
vc:contrastsWith ngm:gdpr ;
vc:dependsOn ngm:clip ;
vc:dependsOn ngm:gpu-compute ;
vc:dependsOn ngm:neural-network ;
vc:dependsOn ngm:transformer ;
vc:dependsOn ngm:u-net ;
vc:dependsOn ngm:vision-transformer ;
vc:enables ngm:content-creation ;
vc:enables ngm:creative-expression ;
vc:enables ngm:gan-virtual-landscape-art ;
vc:enables ngm:synthetic-media ;
vc:enables ngm:video-generation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:diffusion-model ;
vc:hasPart ngm:diffusion-models ;
vc:hasPart ngm:gan ;
vc:hasPart ngm:image-editing ;
vc:hasPart ngm:image-synthesis ;
vc:hasPart ngm:style-transfer ;
vc:hasPart ngm:super-resolution ;
vc:hasPart ngm:vae ;
vc:implements ngm:computer-vision ;
vc:implements ngm:deep-learning ;
vc:implements ngm:image-processing ;
vc:implements ngm:machine-learning-discipline ;
vc:qualityScore "0.89"^^xsd:float ;
vc:relatedTo ngm:autonomous-decision-making ;
vc:relatedTo ngm:diffusion-transformer ;
vc:relatedTo ngm:gan-virtual-landscape-art ;
vc:relatedTo ngm:generative-model ;
vc:relatedTo ngm:image-captioning ;
vc:relatedTo ngm:image-classification ;
vc:relatedTo ngm:image-editing ;
vc:relatedTo ngm:image-preprocessing ;
vc:relatedTo ngm:image-segmentation ;
vc:relatedTo ngm:image-to-image ;
vc:relatedTo ngm:kohya-dreambooth-and-similar ;
vc:relatedTo ngm:midjourney-text-to-image-service ;
vc:relatedTo ngm:multimodal-ai ;
vc:relatedTo ngm:openai-research-organisation ;
vc:relatedTo ngm:stability-ai ;
vc:relatedTo ngm:super-resolution ;
vc:relatedTo ngm:text-generation ;
vc:relatedTo ngm:video-generation ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:large-scale-datasets ;
vc:requires ngm:latent-space ;
vc:requires ngm:natural-language-processing ;
vc:requires ngm:neural-network-latent-space ;
vc:requires ngm:training-data ;
vc:slug "ai-art-generation" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:creative-commons ;
vc:standardizedBy ngm:gdpr ;
vc:supports ngm:creative-industries ;
vc:supports ngm:digital-asset ;
vc:supports ngm:image-segmentation ;
vc:supports ngm:nft ;
vc:supports ngm:prompt-engineering ;
vc:supports ngm:super-resolution ;
vc:uses ngm:clip ;
vc:uses ngm:creative-commons ;
vc:uses ngm:creative-expression ;
vc:uses ngm:generative-model ;
vc:uses ngm:image-and-video-restoration ;
vc:uses ngm:image-classification ;
vc:uses ngm:image-processing-software ;
vc:uses ngm:kohya-dreambooth-and-similar ;
vc:uses ngm:model-architecture ;
vc:uses ngm:multimodal-ai-architecture-ai ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:transfer-learning ;
vc:uses ngm:transformer ;
vc:uses ngm:u-net ;
vc:uses ngm:vision-transformer .
ngm:ai-as-public-good a skos:Concept ;
rdfs:label "AI As Public Good"@en .
ngm:ai-assistant a skos:Concept ;
rdfs:label "AI Assistant"@en .
ngm:ai-assisted-authoring a skos:Concept ;
rdfs:label "AI Assisted Authoring"@en .
ngm:ai-assisted-collaboration a skos:Concept ;
rdfs:label "AI Assisted Collaboration"@en .
ngm:ai-assisted-developer-tooling a owl:Class ;
rdfs:comment "Coding Support encompasses AI-assisted tools, IDE integrations, and agent frameworks that augment software developers with capabilities including inline completion, code generation, automated refactoring, debugging assistance, and test generation. Tools range from general-purpose LLM-backed assistants to domain-specific coding agents operating on full codebases."@en ;
rdfs:label "AI-Assisted Developer Tooling"@en ;
rdfs:subClassOf ngm:software-engineering ;
vc:enables ngm:code-generation ;
vc:enables ngm:generative-ai ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:gpt-engineer ;
vc:relatedTo ngm:practitioner-workflow-optimisation-heuristics ;
vc:slug "ai-assisted-developer-tooling" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:software-engineering ;
vc:uses ngm:agent-frameworks ;
vc:uses ngm:large-language-models .
ngm:ai-assisted-development-practice a owl:Class ;
rdfs:comment "Vibe Coding is an AI-assisted software development practice in which developers direct large language models or AI coding tools (such as Cursor, Aider, or Copilot) with high-level intent rather than writing all code manually. The practitioner retains system-level design authority whilst delegating implementation of discrete, scoped tasks to the AI, requiring disciplined use of version control, structured context documents, and iterative refinement cycles."@en ;
rdfs:label "AI-Assisted Development Practice"@en ;
rdfs:subClassOf ngm:software-engineering ;
rdfs:subClassOf _:r780 ;
vc:enables ngm:user-experience ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:generative-ai-engineering ;
vc:requires ngm:software-engineering ;
vc:slug "ai-assisted-development-practice" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:generative-ai ;
vc:uses ngm:machine-learning-discipline .
ngm:ai-assisted-ontology-elicitation-method a owl:Class ;
rdfs:comment "A structured methodology for collaboratively building and refining formal knowledge representations by conducting iterative dialogues with AI systems. In these conversations, AI agents interpret, critique, and extend ontological schemas, producing machine-readable linked-data artefacts such as OWL classes and JSON-LD graphs that document both the resulting ontology and the reasoning process that produced it."@en ;
rdfs:label "AI-Assisted Ontology Elicitation Method"@en ;
rdfs:subClassOf ngm:software-engineering ;
vc:enables ngm:interoperability ;
vc:enables ngm:metaverse-ontology ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:multi-layer-agentic-governance-framework ;
vc:slug "ai-assisted-ontology-elicitation-method" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:agentic-ai ;
vc:uses ngm:knowledge-graph ;
vc:uses ngm:linked-data .
ngm:ai-assurance-ai-0102 a skos:Concept ;
rdfs:label "AI Assurance AI 0102"@en .
ngm:ai-audio-editing a skos:Concept ;
rdfs:label "AI Audio Editing"@en .
ngm:ai-audit a owl:Class ;
rdfs:comment "A systematic, independent examination and evaluation of an artificial intelligence system's design, development processes, deployment procedures, operational performance, documentation, governance arrangements, and compliance with applicable requirements, conducted by qualified assessors to verify conformity with specified standards, regulations, ethical principles, or organisational policies, and to identify deficiencies, risks, or opportunities for improvement, producing documented findings and recommendations that support accountability, transparency, and continuous enhancement of AI system trustworthiness."@en ;
rdfs:label "AI Audit"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf _:r320 ;
rdfs:subClassOf _:r321 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:eu-ai-act-regulatory-instrument ;
vc:contrastsWith ngm:internal-audit ;
vc:enables ngm:accountability ;
vc:enables ngm:conformity-assessment ;
vc:enables ngm:third-party-certification ;
vc:enables ngm:transparency ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:compliance-audit ;
vc:implements ngm:iso-iec-42001-2023 ;
vc:isPartOf ngm:ai-governance ;
vc:qualityScore "0.7"^^xsd:float ;
vc:relatedTo ngm:algorithmic-accountability ;
vc:requires ngm:access-to-systems-and-personnel ;
vc:requires ngm:ai-documentation-standards ;
vc:slug "ai-audit" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:iso-iec-23894-2023 ;
vc:standardizedBy ngm:iso-iec-5338-2023 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:quality-assurance ;
vc:supports ngm:risk-management ;
vc:uses ngm:ai-impact-assessment ;
vc:uses ngm:ai-monitoring .
ngm:ai-auditing a skos:Concept ;
rdfs:label "AI Auditing"@en .
ngm:ai-augmented-code-review a owl:Class ;
rdfs:comment "The integration of artificial intelligence tools into the code review process to automate defect detection, enforce standards, and reduce human review latency."@en ;
rdfs:label "AI-Augmented Code Review"@en ;
rdfs:subClassOf ngm:code-review ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-code-generation ;
vc:relatedTo ngm:code-review ;
vc:relatedTo ngm:pull-request ;
vc:relatedTo ngm:static-analysis ;
vc:slug "ai-augmented-code-review" ;
vc:sourceDomain "infrastructure" .
ngm:ai-augmented-research-tooling-suite a owl:Class ;
rdfs:comment "Research Tools are software applications and platforms that augment the academic and professional research process, encompassing AI-powered literature assistants (e.g. Elicit, Undermind), systematic review automation, citation management, and natural language interfaces to scientific corpora. They accelerate information retrieval, evidence synthesis, and knowledge organisation, and increasingly leverage large language models and retrieval-augmented generation to surface relevant findings across heterogeneous sources."@en ;
rdfs:label "AI-Augmented Research Tooling Suite"@en ;
rdfs:subClassOf ngm:software-engineering ;
vc:enables ngm:information-retrieval ;
vc:enables ngm:knowledge-management ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:knowledge-graph ;
vc:slug "ai-augmented-research-tooling-suite" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:large-language-models ;
vc:uses ngm:retrieval-augmented-generation .
ngm:ai-augmented-service-ecosystems a owl:Class ;
rdfs:comment "New professional structures in sectors like legal, education, and finance where human roles are redefined as navigators, support workers, and operators who manage and interpret AI-driven services."@en ;
rdfs:label "AI-Augmented Service Ecosystems"@en ;
rdfs:subClassOf ngm:economic-impact-of-ai ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-augmented-service-operators ;
vc:relatedTo ngm:continuous-support-workers ;
vc:relatedTo ngm:cross-industry-ai-impact ;
vc:relatedTo ngm:job-ecosystems ;
vc:slug "ai-augmented-service-ecosystems" ;
vc:sourceDomain "economics" .
ngm:ai-augmented-service-operators a skos:Concept ;
rdfs:label "AI Augmented Service Operators"@en .
ngm:ai-augmented-software-engineering a owl:Class ;
rdfs:comment "AI-Augmented Software Engineering is the practice of integrating artificial intelligence tools and techniques — including large language models, code generation systems, and agentic AI — into the software development lifecycle to accelerate coding, testing, review, and deployment. It encompasses AI-assisted code completion, automated test generation, intelligent refactoring, and documentation synthesis, transforming how software teams design, build, and maintain systems at scale."@en ;
rdfs:label "AI-Augmented Software Engineering"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:ai-application ;
skos:broader ngm:artificial-intelligence ;
vc:bridgesTo ngm:digital-asset ;
vc:enables ngm:rapid-ai-deployment ;
vc:enables ngm:software-development-process ;
vc:enables ngm:workflow-automation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:software-architecture ;
vc:relatedTo ngm:software-engineering ;
vc:relatedTo ngm:software-testing ;
vc:slug "ai-augmented-software-engineering" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:agentic-ai ;
vc:uses ngm:code-generation ;
vc:uses ngm:large-language-models .
ngm:ai-augmented-workflows a owl:Class ;
rdfs:comment "Business processes and job roles that have been restructured to integrate artificial intelligence tools, fundamentally altering task allocation, skill requirements, and organizational design."@en ;
rdfs:label "AI-Augmented Workflows"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:automated-reasoning ;
vc:relatedTo ngm:knowledge-representation ;
vc:slug "ai-augmented-workflows" ;
vc:sourceDomain "governance" .
ngm:ai-avatar-synthesis a skos:Concept ;
rdfs:label "AI Avatar Synthesis"@en .
ngm:ai-avatars a owl:Class ;
rdfs:comment "\"Virtual representations of human users generated and animated by artificial intelligence systems, employing machine learning models to synthesise photorealistic appearance, facial expressions, body movements, and speech from sensor inputs or user intentions, enabling realistic telepresence witho..."@en ;
rdfs:label "AI Avatars"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf ngm:telepresence ;
rdfs:subClassOf _:r322 ;
skos:broader ngm:artificial-intelligence ;
vc:enables ngm:photorealistic-telepresence ;
vc:enables ngm:photorealistictelepresence ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:speech-synthesis ;
vc:slug "ai-avatars" ;
vc:sourceDomain "distributed-collaboration" .
ngm:ai-benchmark-epistemological-critique a owl:Class ;
rdfs:comment "A critical epistemological lens applied to AI benchmark claims, model capability assessments, and statistical presentations that may mislead through selective metrics, dataset contamination, cherry-picked results, or hallucination. The page collects resources and reasoning for evaluating AI performance claims with rigour, highlighting how large language models can generate plausible but false outputs that resemble statistical truth."@en ;
rdfs:label "AI Benchmark Epistemological Critique"@en ;
rdfs:subClassOf ngm:software-engineering ;
vc:contrastsWith ngm:natural-language-processing ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:bias ;
vc:relatedTo ngm:large-language-models ;
vc:slug "ai-benchmark-epistemological-critique" ;
vc:sourceDomain "infrastructure" .
ngm:ai-benchmarking a owl:Class ;
rdfs:comment "The systematic process of evaluating and comparing the performance, quality, and capabilities of AI models and systems against standardized or internal metrics."@en ;
rdfs:label "AI Benchmarking"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:frontier-model-evaluation ;
vc:relatedTo ngm:large-language-models ;
vc:slug "ai-benchmarking" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-benchmarks a owl:Class ;
rdfs:comment "Standardized datasets and evaluation metrics used to quantitatively assess the performance, capabilities, and limitations of artificial intelligence models across specific tasks."@en ;
rdfs:label "AI Benchmarks"@en ;
rdfs:subClassOf ngm:benchmarks ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:benchmarks ;
vc:relatedTo ngm:model ;
vc:relatedTo ngm:reasoning ;
vc:slug "ai-benchmarks" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-benefits a skos:Concept ;
rdfs:label "AI Benefits"@en .
ngm:ai-bias a skos:Concept ;
rdfs:label "AI Bias"@en .
ngm:ai-board a owl:Class ;
rdfs:comment "EU Advisory body under Articles 65–67 of the AI Act, composed of one senior representative per Member State and supported by the AI Office as secretariat. Its mandate spans issuing harmonisation guidelines, resolving cross-border jurisdictional conflicts, coordinating joint enforcement actions, and advising the AI Office on GPAI systemic-risk classification and codes-of-practice adequacy."@en ;
rdfs:label "AI Board"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
skos:broader ngm:ai-governance-and-ethics ;
vc:enables ngm:ai-governance ;
vc:enables ngm:ai-governance-framework ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:ai-risk-management ;
vc:relatedTo ngm:general-purpose-ai-model ;
vc:slug "ai-board" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:ai-office ;
vc:supports ngm:eu-ai-act-regulatory-instrument .
ngm:ai-body-pose-estimation a skos:Concept ;
rdfs:label "AI Body Pose Estimation"@en .
ngm:ai-bubble a owl:Class ;
rdfs:comment "A market condition characterized by speculative overvaluation of artificial intelligence assets and infrastructure investments relative to their current or projected fundamental economic output."@en ;
rdfs:label "AI Bubble"@en ;
rdfs:subClassOf ngm:competition-in-ai ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-chips ;
vc:relatedTo ngm:ai-market-dynamics ;
vc:relatedTo ngm:competition-in-ai ;
vc:slug "ai-bubble" ;
vc:sourceDomain "economics" .
ngm:ai-bubble-dynamics a owl:Class ;
rdfs:comment "The economic and market conditions characterized by rapid valuation increases in AI-related assets, driven by speculative investment and high growth expectations, which carry the risk of a subsequent market correction or crash."@en ;
rdfs:label "AI Bubble Dynamics"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-infrastructure-capital-expenditure ;
vc:relatedTo ngm:foundation-model ;
vc:slug "ai-bubble-dynamics" ;
vc:sourceDomain "economics" .
ngm:ai-bubble-narrative a owl:Class ;
rdfs:comment "A recurring economic and cultural discourse arguing that the current valuation and adoption of artificial intelligence technologies are unsustainable and prone to a significant market correction."@en ;
rdfs:label "AI Bubble Narrative"@en ;
rdfs:subClassOf ngm:venture-capital ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:venture-capital ;
vc:slug "ai-bubble-narrative" ;
vc:sourceDomain "economics" .
ngm:ai-business-model a owl:Class ;
rdfs:comment "The economic frameworks and revenue strategies, such as subscription, usage-based, or hybrid models, employed to monetize artificial intelligence products and services."@en ;
rdfs:label "AI Business Model"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:inference ;
vc:relatedTo ngm:model ;
vc:slug "ai-business-model" ;
vc:sourceDomain "economics" .
ngm:ai-capabilities a skos:Concept ;
rdfs:label "AI Capabilities"@en .
ngm:ai-capabilities-research a skos:Concept ;
rdfs:label "AI Capabilities Research"@en .
ngm:ai-capability a skos:Concept ;
rdfs:label "AI Capability"@en .
ngm:ai-capability-discontinuity-model a owl:Class ;
rdfs:comment "A conceptual framework positing that AI capability does not progress linearly but instead exhibits discontinuous threshold transitions—analogous to the mathematical step function—where accumulated incremental improvements trigger rapid, self-reinforcing shifts in capability order, akin to historical inflection points such as the Cambrian explosion or the printing press. The framework draws on self-organisation theory and feedback-loop dynamics to argue that AI represents the next major complexity transition in evolutionary and technological history."@en ;
rdfs:label "AI Capability Discontinuity Model"@en ;
rdfs:subClassOf ngm:ai-research-area ;
skos:broader ngm:ai-research-area ;
vc:enables ngm:ai-safety ;
vc:enables ngm:responsible-ai ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-alignment ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:generative-ai ;
vc:slug "ai-capability-discontinuity-model" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:ai-concept .
ngm:ai-capability-evidence-compendium a owl:Class ;
rdfs:comment "A curated reference document compiling empirical evidence countering common objections to AI capability and originality claims, aggregating benchmarks, research findings, and expert commentary demonstrating that large language models exhibit reasoning, world-model construction, and generalisation beyond stochastic pattern matching. Serves as an evidence base for constructive discourse on AI capabilities and their societal implications."@en ;
rdfs:label "AI Capability Evidence Compendium"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
skos:broader ngm:ai-governance-and-ethics ;
vc:enables ngm:ai-ethics ;
vc:enables ngm:explainability ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:ai-alignment ;
vc:relatedTo ngm:generative-ai ;
vc:relatedTo ngm:large-language-models ;
vc:slug "ai-capability-evidence-compendium" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:ai-safety ;
vc:supports ngm:responsible-ai .
ngm:ai-capability-forecasting a skos:Concept ;
rdfs:label "AI Capability Forecasting"@en .
ngm:ai-capability-temporal-horizon-framework a owl:Class ;
rdfs:comment "Soon-Next-Later is a structured futurology framework for categorising AI capability developments across three temporal horizons: Soon (0–5 years, capabilities already emerging in products), Next (5–10 years, capabilities requiring current research to mature), and Later (10+ years, speculative capabilities dependent on fundamental advances). The framework provides practitioners with a tractable planning scaffold that avoids both near-term over-hype and long-horizon dismissiveness."@en ;
rdfs:label "AI Capability Temporal Horizon Framework"@en ;
rdfs:subClassOf ngm:ai-research-area ;
skos:broader ngm:ai-research-area ;
vc:bridgesTo ngm:national-sovereign-ai-procurement-initiative ;
vc:enables ngm:ai-governance ;
vc:enables ngm:ai-policy ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.7"^^xsd:float ;
vc:relatedTo ngm:artificial-general-intelligence ;
vc:relatedTo ngm:sam-hammond-ai-policy-economist ;
vc:relatedTo ngm:social-contract ;
vc:slug "ai-capability-temporal-horizon-framework" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:ai-risk .
ngm:ai-capex-forecast a owl:Class ;
rdfs:comment "Projections of capital expenditure by hyperscalers and enterprises on AI infrastructure, including data centers, chips, and power systems."@en ;
rdfs:label "AI CapEx Forecast"@en ;
rdfs:subClassOf ngm:data ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:data ;
vc:relatedTo ngm:digital-infrastructure ;
vc:slug "ai-capex-forecast" ;
vc:sourceDomain "economics" .
ngm:ai-capex-spend a owl:Class ;
rdfs:comment "The capital expenditure by technology companies on AI infrastructure, including data centers, chips, and energy, driving macroeconomic impacts."@en ;
rdfs:label "AI CapEx Spend"@en ;
rdfs:subClassOf ngm:data-management ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-economics ;
vc:relatedTo ngm:big-tech-capex ;
vc:slug "ai-capex-spend" ;
vc:sourceDomain "economics" .
ngm:ai-capital-expenditure a owl:Class ;
rdfs:comment "The aggregate financial outlay by corporations and governments for physical infrastructure, such as data centers and chips, required to train and deploy large-scale artificial intelligence models."@en ;
rdfs:label "AI Capital Expenditure"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:computational-infrastructure ;
vc:relatedTo ngm:data-storage ;
vc:slug "ai-capital-expenditure" ;
vc:sourceDomain "economics" .
ngm:ai-certification a owl:Class ;
rdfs:comment "AI certification is the formal attestation, by an accredited third party, that an artificial intelligence system or its governing management system conforms to defined requirements for safety, robustness, fairness, transparency, and risk management. Unlike generic conformity certification, it is scoped to AI-specific standards and hazards — data-quality and bias controls, model evaluation, human oversight, and lifecycle governance under frameworks such as ISO/IEC 42001. AI certification converts abstract commitments to trustworthy AI into auditable, marketable evidence, giving procurers, regulators, and the public a credible signal that a system has been independently assessed against recognised criteria rather than self-declared as compliant."@en ;
rdfs:label "AI Certification"@en ;
rdfs:subClassOf ngm:certification ;
rdfs:subClassOf _:r323 ;
vc:enables ngm:trustworthy-ai ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:iso-iec-42001 ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:ai-governance ;
vc:requires ngm:conformity-assessment ;
vc:slug "ai-certification" ;
vc:sourceDomain "governance" .
ngm:ai-chip-geopolitics a owl:Class ;
rdfs:comment "The strategic interplay of national security policies, trade agreements, and diplomatic relations that govern the cross-border flow of advanced semiconductor hardware and associated intellectual property."@en ;
rdfs:label "AI Chip Geopolitics"@en ;
rdfs:subClassOf ngm:export-controls ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-chips ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:competition-in-ai ;
vc:relatedTo ngm:export-controls ;
vc:slug "ai-chip-geopolitics" ;
vc:sourceDomain "governance" .
ngm:ai-chip-manufacturing a owl:Class ;
rdfs:comment "The specialized semiconductor fabrication and supply chain processes required to produce high-performance accelerators and TPUs for artificial intelligence workloads."@en ;
rdfs:label "AI Chip Manufacturing"@en ;
rdfs:subClassOf ngm:computational-infrastructure ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:data-processing ;
vc:relatedTo ngm:deep-learning ;
vc:relatedTo ngm:neural-network ;
vc:slug "ai-chip-manufacturing" ;
vc:sourceDomain "infrastructure" .
ngm:ai-chips a owl:Class ;
rdfs:comment "AI Chips are specialized processors optimized for the massively parallel linear-algebra workloads of machine-learning training and inference, including GPUs, TPUs, NPUs, and custom ASICs. They deliver high throughput on matrix and tensor operations through wide SIMD execution, high-bandwidth memory, and reduced-precision arithmetic. Control over advanced AI-chip design and fabrication has become a strategic axis of geopolitical and commercial competition."@en ;
rdfs:label "AI Chips"@en ;
rdfs:subClassOf ngm:ai-infrastructure ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:competition-in-ai ;
vc:relatedTo ngm:hardware ;
vc:slug "ai-chips" ;
vc:sourceDomain "infrastructure" .
ngm:ai-classification-systems a skos:Concept ;
rdfs:label "AI Classification Systems"@en .
ngm:ai-cluster a skos:Concept ;
rdfs:label "AI Cluster"@en .
ngm:ai-code-generation a owl:Class ;
rdfs:comment "The use of artificial intelligence models to automatically produce, complete, or refactor source code based on natural language prompts or context."@en ;
rdfs:label "AI Code Generation"@en ;
rdfs:subClassOf ngm:model ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:model ;
vc:slug "ai-code-generation" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-coding-agents a owl:Class ;
rdfs:comment "Autonomous software agents capable of writing, debugging, and deploying code, increasingly driving adoption of developer tools."@en ;
rdfs:label "AI Coding Agents"@en ;
rdfs:subClassOf ngm:model ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:large-language-models ;
vc:slug "ai-coding-agents" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-coding-assistant a owl:Class ;
rdfs:comment "A class of AI tools designed to augment software development workflows by generating, refactoring, and debugging code, thereby enhancing developer productivity."@en ;
rdfs:label "AI Coding Assistant"@en ;
rdfs:subClassOf ngm:gpt ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:code-generation ;
vc:relatedTo ngm:gpt ;
vc:relatedTo ngm:natural-language-processing ;
vc:slug "ai-coding-assistant" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-coding-assistants a owl:Class ;
rdfs:comment "Software tools that assist developers in writing, reviewing, and debugging code using AI models."@en ;
rdfs:label "AI Coding Assistants"@en ;
rdfs:subClassOf ngm:model ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-coding-agents ;
vc:relatedTo ngm:large-language-models ;
vc:slug "ai-coding-assistants" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-coding-tools a owl:Class ;
rdfs:comment "Software applications that leverage large language models to assist, automate, or generate code for software development tasks."@en ;
rdfs:label "AI Coding Tools"@en ;
rdfs:subClassOf ngm:ai-application ;
skos:broader ngm:ai-application ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:developer-ai ;
vc:relatedTo ngm:large-language-models ;
vc:slug "ai-coding-tools" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-companies a owl:Class ;
rdfs:comment "AI Companies is the population-level concept comprising commercial and non-profit organisations whose principal economic activity is the research, development, productisation, deployment, distribution, or infrastructure-provision of artificial intelligence technologies—spanning the 2024-2026 indu..."@en ;
rdfs:label "AI Companies"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:commercial-enterprise ;
rdfs:subClassOf ngm:industry-sector ;
rdfs:subClassOf ngm:research-organisation ;
rdfs:subClassOf ngm:software-vendor ;
rdfs:subClassOf ngm:technology-company ;
rdfs:subClassOf _:r324 ;
rdfs:subClassOf _:r325 ;
rdfs:subClassOf _:r326 ;
rdfs:subClassOf _:r327 ;
rdfs:subClassOf _:r328 ;
rdfs:subClassOf _:r329 ;
rdfs:subClassOf _:r330 ;
rdfs:subClassOf _:r331 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:software-engineering ;
vc:contrastsWith ngm:academic-ai-labs ;
vc:contrastsWith ngm:open-source-communities ;
vc:contrastsWith ngm:pure-play-saas-companies ;
vc:contrastsWith ngm:traditional-software-vendors ;
vc:dependsOn ngm:academic-research-pipeline ;
vc:dependsOn ngm:hyperscaler-cloud ;
vc:dependsOn ngm:nvidia-gpus ;
vc:dependsOn ngm:power-grid-capacity ;
vc:dependsOn ngm:semiconductor-supply-chain ;
vc:dependsOn ngm:sovereign-wealth-investment ;
vc:dependsOn ngm:venture-capital ;
vc:enables ngm:ai-agent-system ;
vc:enables ngm:ai-apis ;
vc:enables ngm:autonomous-system ;
vc:enables ngm:enterprise-ai-adoption ;
vc:enables ngm:foundation-model-licensing ;
vc:enables ngm:generative-ai ;
vc:enables ngm:synthetic-media ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ai-infrastructure ;
vc:hasPart ngm:ai-research-laboratory ;
vc:hasPart ngm:application-ai-companies ;
vc:hasPart ngm:capital-base ;
vc:hasPart ngm:foundation-model-labs ;
vc:hasPart ngm:founding-team ;
vc:hasPart ngm:open-source-ai ;
vc:hasPart ngm:vertical-ai-specialists ;
vc:implements ngm:ai-safety-research ;
vc:implements ngm:commercial-productisation ;
vc:implements ngm:frontier-model-training ;
vc:implements ngm:inference-serving ;
vc:implements ngm:model-distribution ;
vc:implements ngm:rlhf ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:agi-race ;
vc:relatedTo ngm:ai-acquisitions-and-m-a ;
vc:relatedTo ngm:ai-funding-landscape ;
vc:relatedTo ngm:ai-talent-war ;
vc:relatedTo ngm:compute-cluster ;
vc:relatedTo ngm:hyperscaler-cloud ;
vc:relatedTo ngm:sovereign-ai ;
vc:requires ngm:capital-investment ;
vc:requires ngm:cloud-infrastructure ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:large-language-models ;
vc:requires ngm:regulatory-license ;
vc:requires ngm:talent-pool ;
vc:requires ngm:training-data ;
vc:slug "ai-companies" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:frontier-model-forum ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:standardizedBy ngm:partnership-on-ai ;
vc:standardizedBy ngm:uk-ai-safety-institute ;
vc:standardizedBy ngm:white-house-voluntary-ai-commitments ;
vc:supports ngm:creative-industries ;
vc:supports ngm:defence-and-security-ai ;
vc:supports ngm:education-technology ;
vc:supports ngm:enterprise-automation ;
vc:supports ngm:healthcare-ai ;
vc:supports ngm:legal-tech ;
vc:supports ngm:national-ai-strategy ;
vc:supports ngm:scientific-research ;
vc:uses ngm:chain-of-thought-reasoning ;
vc:uses ngm:constitutional-ai-training-methodology ;
vc:uses ngm:distributed-training ;
vc:uses ngm:mixture-of-experts-architecture ;
vc:uses ngm:reinforcement-learning-from-human-feedback ;
vc:uses ngm:retrieval-augmented-generation ;
vc:uses ngm:transformer-architecture .
ngm:ai-companions a owl:Class ;
rdfs:comment "AI companions are a class of consumer-facing conversational artificial intelligence systems explicitly designed and marketed to form ongoing affective, social, and parasocial relationships with individual human users—distinct from task-oriented assistants (Siri, Alexa, Google Assistant) that opti..."@en ;
rdfs:label "AI companions"@en ;
rdfs:subClassOf ngm:affective-computing-system ;
rdfs:subClassOf ngm:ai-agent-system ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:consumer-ai-product ;
rdfs:subClassOf ngm:conversational-ai ;
rdfs:subClassOf ngm:large-language-model-application ;
rdfs:subClassOf _:r751 ;
rdfs:subClassOf _:r752 ;
rdfs:subClassOf _:r753 ;
rdfs:subClassOf _:r754 ;
rdfs:subClassOf _:r755 ;
rdfs:subClassOf _:r756 ;
rdfs:subClassOf _:r757 ;
rdfs:subClassOf _:r758 ;
rdfs:subClassOf _:r759 ;
rdfs:subClassOf _:r760 ;
rdfs:subClassOf _:r761 ;
skos:broader ngm:ai-application ;
vc:contrastsWith ngm:ai-assistant ;
vc:contrastsWith ngm:customer-service-bot ;
vc:contrastsWith ngm:general-purpose-chatbot ;
vc:contrastsWith ngm:search-augmented-chatbot ;
vc:contrastsWith ngm:therapy-chatbot ;
vc:contrastsWith ngm:voice-assistant ;
vc:dependsOn ngm:foundation-model ;
vc:dependsOn ngm:inference-infrastructure ;
vc:dependsOn ngm:mobile-app-distribution ;
vc:dependsOn ngm:payment-processing ;
vc:dependsOn ngm:trust-and-safety-operations ;
vc:enables ngm:creative-collaboration ;
vc:enables ngm:elder-companionship ;
vc:enables ngm:emotional-support ;
vc:enables ngm:language-practice ;
vc:enables ngm:loneliness-mitigation ;
vc:enables ngm:parasocial-bonding ;
vc:enables ngm:relationship-simulation ;
vc:enables ngm:role-play ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:affective-tone-module ;
vc:hasPart ngm:avatar-renderer ;
vc:hasPart ngm:content-moderation ;
vc:hasPart ngm:memory-store ;
vc:hasPart ngm:persona-system ;
vc:hasPart ngm:safety-filter ;
vc:hasPart ngm:subscription-paywall ;
vc:hasPart ngm:voice-synthesis-module ;
vc:implements ngm:age-verification ;
vc:implements ngm:content-moderation ;
vc:implements ngm:engagement-optimisation ;
vc:implements ngm:memory-retrieval ;
vc:implements ngm:persona-conditioning ;
vc:implements ngm:sentiment-analysis ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:affective-computing ;
vc:relatedTo ngm:artificial-intimacy ;
vc:relatedTo ngm:generative-ai ;
vc:relatedTo ngm:human-ai-interaction ;
vc:relatedTo ngm:loneliness-epidemic ;
vc:relatedTo ngm:parasocial-interaction ;
vc:relatedTo ngm:synthetic-media ;
vc:requires ngm:gpu-inference-capacity ;
vc:requires ngm:large-language-model ;
vc:requires ngm:large-language-models ;
vc:requires ngm:persistent-storage ;
vc:requires ngm:reinforcement-learning-from-human-feedback ;
vc:requires ngm:retrieval-augmented-generation ;
vc:requires ngm:user-authentication ;
vc:slug "ai-companions" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:c2-pa ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:ftc-ai-enforcement ;
vc:standardizedBy ngm:gdpr ;
vc:standardizedBy ngm:ofcom ;
vc:standardizedBy ngm:uk-online-safety-act ;
vc:supports ngm:bereavement-processing ;
vc:supports ngm:creative-writing ;
vc:supports ngm:dementia-engagement ;
vc:supports ngm:fan-fiction ;
vc:supports ngm:mental-health-self-help ;
vc:supports ngm:neurodivergent-communication ;
vc:supports ngm:social-skills-training ;
vc:uses ngm:direct-preference-optimisation ;
vc:uses ngm:embedding-search ;
vc:uses ngm:image-generation ;
vc:uses ngm:live2d-animation ;
vc:uses ngm:rlhf ;
vc:uses ngm:safety-classifiers ;
vc:uses ngm:speech-synthesis .
ngm:ai-compute-infrastructure a owl:Class ;
rdfs:comment "The physical and logical systems, including data centers, GPUs, and networking, that provide the processing power required to train and deploy large-scale artificial intelligence models."@en ;
rdfs:label "AI Compute Infrastructure"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:transformer-architecture ;
vc:slug "ai-compute-infrastructure" ;
vc:sourceDomain "infrastructure" .
ngm:ai-compute-strategy a owl:Class ;
rdfs:comment "The corporate and economic approaches used by organizations to acquire, allocate, and leverage computational resources to gain competitive advantage in the AI market."@en ;
rdfs:label "AI Compute Strategy"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-compute-infrastructure ;
vc:relatedTo ngm:market-consolidation ;
vc:slug "ai-compute-strategy" ;
vc:sourceDomain "economics" .
ngm:ai-concept a owl:Class ;
rdfs:comment "The foundational theoretical constructs and abstract principles underlying artificial intelligence systems, encompassing both symbolic approaches (knowledge representation, logic-based reasoning) and subsymbolic methods (connectionist networks, distributed representations). AI Concepts define learning paradigms, reasoning mechanisms, and cognitive architectures that serve as the theoretical basis for designing, evaluating, and advancing intelligent systems across research and application domains."@en ;
rdfs:label "AI Concept"@en ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf _:r332 ;
skos:broader ngm:ai-research-area ;
vc:enables ngm:artificial-intelligence ;
vc:enables ngm:machine-learning-discipline ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-alignment ;
vc:relatedTo ngm:explainability ;
vc:relatedTo ngm:neural-network ;
vc:requires ngm:knowledge-representation ;
vc:slug "ai-concept" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-context a owl:Class ;
rdfs:comment "The specific, often private or situational information required by an AI model to perform tasks effectively for a particular user, representing a critical bottleneck in AI deployment beyond raw model capability."@en ;
rdfs:label "AI Context"@en ;
rdfs:subClassOf ngm:knowledge-representation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-model ;
vc:relatedTo ngm:knowledge-representation ;
vc:relatedTo ngm:retrieval-augmented-generation ;
vc:slug "ai-context" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-control-problem a skos:Concept ;
rdfs:label "AI Control Problem"@en .
ngm:ai-cooperation a skos:Concept ;
rdfs:label "AI Cooperation"@en .
ngm:ai-copilot-layer a skos:Concept ;
rdfs:label "AI Copilot Layer"@en .
ngm:ai-copyright-infringement a owl:Class ;
rdfs:comment "Legal disputes and policy issues arising from the use of copyrighted works to train or generate content with AI models."@en ;
rdfs:label "AI Copyright Infringement"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
skos:broader ngm:ai-governance-and-ethics ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-regulation ;
vc:relatedTo ngm:hollywood-ai-policy ;
vc:slug "ai-copyright-infringement" ;
vc:sourceDomain "governance" .
ngm:ai-core-concepts a owl:Class ;
rdfs:comment "Foundational artificial intelligence technologies — including machine learning paradigms (supervised, unsupervised, reinforcement), neural architectures (neural networks, transformers, CNNs), generative models, and classical symbolic reasoning — that collectively enable intelligent system behaviour. In metaverse contexts these concepts drive NPC dialogue, environment perception, procedural content generation, and federated privacy-preserving learning."@en ;
rdfs:label "ai core concepts"@en ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf _:r22674 ;
rdfs:subClassOf _:r22675 ;
rdfs:subClassOf _:r22676 ;
rdfs:subClassOf _:r22677 ;
skos:broader ngm:ai-research-area ;
vc:enables ngm:computer-vision ;
vc:enables ngm:inference ;
vc:enables ngm:natural-language-processing ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:generative-ai ;
vc:hasPart ngm:machine-learning-discipline ;
vc:hasPart ngm:neural-network ;
vc:hasPart ngm:reinforcement-learning ;
vc:qualityScore "0.4"^^xsd:float ;
vc:slug "ai-core-concepts" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:data-pipeline ;
vc:uses ngm:federated-learning .
ngm:ai-corporate-governance a owl:Class ;
rdfs:comment "The legal and structural frameworks governing the ownership, equity distribution, and fiduciary responsibilities of artificial intelligence research organizations."@en ;
rdfs:label "AI Corporate Governance"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
skos:broader ngm:ai-governance-and-ethics ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-governance-and-ethics ;
vc:relatedTo ngm:ai-investment ;
vc:relatedTo ngm:ai-regulation ;
vc:slug "ai-corporate-governance" ;
vc:sourceDomain "governance" .
ngm:ai-cybersecurity a owl:Class ;
rdfs:comment "The intersection of artificial intelligence and information security, encompassing both the use of AI to enhance defensive security measures and the mitigation of risks posed by AI systems themselves."@en ;
rdfs:label "AI Cybersecurity"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:autonomous-systems ;
vc:relatedTo ngm:security ;
vc:slug "ai-cybersecurity" ;
vc:sourceDomain "security" .
ngm:ai-data-center-capacity a owl:Class ;
rdfs:comment "The total power and compute throughput available to a specific facility or cluster for training and serving artificial intelligence models."@en ;
rdfs:label "AI Data Center Capacity"@en ;
rdfs:subClassOf ngm:computational-infrastructure ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:computational-infrastructure ;
vc:relatedTo ngm:deep-learning ;
vc:relatedTo ngm:training ;
vc:slug "ai-data-center-capacity" ;
vc:sourceDomain "infrastructure" .
ngm:ai-data-center-infrastructure a owl:Class ;
rdfs:comment "The physical and computational facilities, including specialized hardware like GPUs and power systems, designed to host and scale large-scale AI model training and inference workloads."@en ;
rdfs:label "AI Data Center Infrastructure"@en ;
rdfs:subClassOf ngm:infrastructure ;
skos:broader ngm:infrastructure ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:european-commission ;
vc:relatedTo ngm:model ;
vc:slug "ai-data-center-infrastructure" ;
vc:sourceDomain "infrastructure" .
ngm:ai-data-centers a owl:Class ;
rdfs:comment "Specialized data centers designed for AI workloads, with unique requirements for power, cooling, and network connectivity."@en ;
rdfs:label "AI Data Centers"@en ;
rdfs:subClassOf ngm:data-storage ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-inference-infrastructure ;
vc:relatedTo ngm:data-center-power-demand ;
vc:slug "ai-data-centers" ;
vc:sourceDomain "infrastructure" .
ngm:ai-data-centres a skos:Concept ;
rdfs:label "AI Data Centres"@en .
ngm:ai-data-retention-policy a owl:Class ;
rdfs:comment "A specific subset of data governance rules that dictate the duration and conditions under which prompts, outputs, and training data generated by or for AI systems are stored, reviewed, or deleted."@en ;
rdfs:label "AI Data Retention Policy"@en ;
rdfs:subClassOf ngm:retention-policy ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:content-moderation ;
vc:relatedTo ngm:data-governance ;
vc:relatedTo ngm:trust-and-safety ;
vc:slug "ai-data-retention-policy" ;
vc:sourceDomain "governance" .
ngm:ai-dataset-distribution a skos:Concept ;
rdfs:label "AI Dataset Distribution"@en .
ngm:ai-dataset-management a skos:Concept ;
rdfs:label "AI Dataset Management"@en .
ngm:ai-decision-system a skos:Concept ;
rdfs:label "AI Decision System"@en .
ngm:ai-demand-elasticity-framework a owl:Class ;
rdfs:comment "A conceptual model categorizing how artificial intelligence alters market demand through specific dimensions such as price, access, complexity, continuity, personalization, and relational value."@en ;
rdfs:label "AI Demand Elasticity Framework"@en ;
rdfs:subClassOf ngm:economic-impact-of-ai ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:demand-elasticity ;
vc:relatedTo ngm:personalization-elasticity ;
vc:relatedTo ngm:price-elasticity ;
vc:slug "ai-demand-elasticity-framework" ;
vc:sourceDomain "economics" .
ngm:ai-deployment a owl:Class ;
rdfs:comment "The phase of the AI lifecycle in which a developed and validated artificial intelligence system is integrated into operational environments, made available to end users, and transitioned from development to production use, encompassing activities such as system integration, infrastructure provisioning, release management, user training, documentation delivery, and the establishment of operational support structures to ensure reliable, safe, and effective system functioning in real-world conditions."@en ;
rdfs:label "AI Deployment"@en ;
rdfs:subClassOf ngm:ai-lifecycle ;
rdfs:subClassOf _:r333 ;
rdfs:subClassOf _:r334 ;
rdfs:subClassOf _:r335 ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:governance ;
vc:bridgesTo ngm:security ;
vc:contrastsWith ngm:ai-development ;
vc:dependsOn ngm:ai-development ;
vc:dependsOn ngm:human-oversight ;
vc:enables ngm:ai-monitoring ;
vc:enables ngm:ai-system-use-by-ai-users-and-ai-operators ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:canary-deployment ;
vc:hasPart ngm:infrastructure-provisioning ;
vc:hasPart ngm:release-management ;
vc:implements ngm:mlops ;
vc:isPartOf ngm:ai-lifecycle ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:fda-software-as-medical-device ;
vc:relatedTo ngm:iso-iec-25010 ;
vc:requires ngm:deployment-infrastructure ;
vc:requires ngm:model-performance ;
vc:requires ngm:operational-procedures ;
vc:requires ngm:risk-management ;
vc:slug "ai-deployment" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:iso-iec-42001-2023 ;
vc:standardizedBy ngm:iso-iec-5338-2023 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:uses ngm:ai-agent-system ;
vc:uses ngm:ai-operator ;
vc:uses ngm:ai-provider ;
vc:uses ngm:ai-user .
ngm:ai-detection a owl:Class ;
rdfs:comment "The set of computational methods and tools used to identify and classify content as being generated by artificial intelligence systems rather than human authors."@en ;
rdfs:label "AI Detection"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:content-integrity ;
vc:relatedTo ngm:generative-ai ;
vc:slug "ai-detection" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-detection-systems a skos:Concept ;
rdfs:label "AI Detection Systems"@en .
ngm:ai-development a owl:Class ;
rdfs:comment "The phase of the AI lifecycle encompassing the design, creation, training, and validation of artificial intelligence systems, including activities such as algorithm selection, data preparation, model architecture design, training process execution, hyperparameter optimisation, performance eand do..."@en ;
rdfs:label "AI Development"@en ;
rdfs:subClassOf ngm:ai-infrastructure ;
rdfs:subClassOf _:r336 ;
rdfs:subClassOf _:r337 ;
rdfs:subClassOf _:r338 ;
vc:bridgesTo ngm:ai-agent-system ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:computational-resources ;
vc:requires ngm:technical-expertise ;
vc:requires ngm:training-data ;
vc:slug "ai-development" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:ai-model ;
vc:uses ngm:machine-learning-discipline .
ngm:ai-development-tools a owl:Class ;
rdfs:comment "Software frameworks, libraries, platforms, and integrated development environments designed to facilitate the creation, training, deployment, and maintenance of artificial intelligence systems. Includes deep learning frameworks (TensorFlow, PyTorch, JAX), AutoML platforms, model optimisation toolkits, MLOps infrastructure, and AI-assisted IDEs. Modern tools emphasise reproducibility, scalability, experiment tracking, and continuous delivery of AI systems."@en ;
rdfs:label "AI Development Tools"@en ;
rdfs:subClassOf ngm:ai-infrastructure ;
vc:enables ngm:deep-learning ;
vc:enables ngm:generative-ai ;
vc:enables ngm:machine-learning-discipline ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.35"^^xsd:float ;
vc:slug "ai-development-tools" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:ai-lifecycle ;
vc:supports ngm:machine-learning-discipline-infrastructure ;
vc:uses ngm:auto-ml ;
vc:uses ngm:data-pipeline .
ngm:ai-diagram-tools a owl:Class ;
rdfs:comment "AI Diagram Tools are a class of generative AI applications that translate natural-language descriptions, source code, screenshots, or structured specifications into machine-renderable diagram artefacts (flowcharts, sequence diagrams, entity-relationship models, class diagrams, mind maps, architec..."@en ;
rdfs:label "AI Diagram Tools"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:ai-productivity-tool ;
rdfs:subClassOf ngm:diagram-as-code ;
rdfs:subClassOf ngm:generative-ai-application ;
rdfs:subClassOf ngm:knowledge-visualisation ;
rdfs:subClassOf ngm:llm-powered-tool ;
rdfs:subClassOf _:r339 ;
rdfs:subClassOf _:r340 ;
rdfs:subClassOf _:r341 ;
rdfs:subClassOf _:r342 ;
rdfs:subClassOf _:r343 ;
rdfs:subClassOf _:r344 ;
rdfs:subClassOf _:r345 ;
rdfs:subClassOf _:r346 ;
skos:broader ngm:ai-application ;
vc:bridgesTo ngm:ai-infrastructure ;
vc:contrastsWith ngm:generative-image-model ;
vc:contrastsWith ngm:hand-drawn-whiteboard ;
vc:contrastsWith ngm:midjourney-text-to-image-service ;
vc:contrastsWith ngm:omnigraffle ;
vc:contrastsWith ngm:static-diagram-file ;
vc:contrastsWith ngm:visio ;
vc:dependsOn ngm:claude-3-5 ;
vc:dependsOn ngm:d2-diagram-language ;
vc:dependsOn ngm:diffusion-model ;
vc:dependsOn ngm:eclipse-layout-kernel ;
vc:dependsOn ngm:gpt-4 ;
vc:dependsOn ngm:graphviz ;
vc:dependsOn ngm:mermaid-js ;
vc:dependsOn ngm:plantuml ;
vc:enables ngm:adr-generation ;
vc:enables ngm:architecture-documentation ;
vc:enables ngm:onboarding-diagram-production ;
vc:enables ngm:prd-visualisation ;
vc:enables ngm:rapid-diagramming ;
vc:enables ngm:system-design-communication ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:diagram-grammar-compiler ;
vc:hasPart ngm:editor-surface ;
vc:hasPart ngm:export-pipeline ;
vc:hasPart ngm:layout-algorithm ;
vc:hasPart ngm:llm-backend ;
vc:hasPart ngm:prompt-template ;
vc:hasPart ngm:rendering-engine ;
vc:implements ngm:code-to-diagram-reverse-engineering ;
vc:implements ngm:screenshot-to-diagram-conversion ;
vc:implements ngm:sugiyama-hierarchical-layout ;
vc:implements ngm:text-to-dot-generation ;
vc:implements ngm:text-to-mermaid-generation ;
vc:implements ngm:text-to-plantuml-generation ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:c4-model ;
vc:relatedTo ngm:claude ;
vc:relatedTo ngm:eraser-diagramgpt ;
vc:relatedTo ngm:excalidraw ;
vc:relatedTo ngm:lucidchart-ai ;
vc:relatedTo ngm:markdown-diagramming-as-code-tool ;
vc:relatedTo ngm:miro ;
vc:relatedTo ngm:napkin-ai ;
vc:relatedTo ngm:structurizr-dsl ;
vc:relatedTo ngm:whimsical-ai ;
vc:requires ngm:browser-runtime ;
vc:requires ngm:diagram-specification-language ;
vc:requires ngm:large-language-model ;
vc:requires ngm:large-language-models ;
vc:requires ngm:layout-engine ;
vc:requires ngm:markdown-diagramming-as-code-tool ;
vc:slug "ai-diagram-tools" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:c4-model ;
vc:standardizedBy ngm:markdown-diagramming-as-code-tool ;
vc:standardizedBy ngm:omg-uml-2-5 ;
vc:standardizedBy ngm:plantuml-standard ;
vc:standardizedBy ngm:structurizr-dsl ;
vc:supports ngm:diagram-driven-development ;
vc:supports ngm:knowledge-graph-construction ;
vc:supports ngm:product-management ;
vc:supports ngm:software-architecture-documentation ;
vc:supports ngm:system-design-interview-prep ;
vc:supports ngm:technical-documentation ;
vc:uses ngm:few-shot-prompting ;
vc:uses ngm:force-directed-layout ;
vc:uses ngm:markdown ;
vc:uses ngm:prompt-engineering ;
vc:uses ngm:svg-rendering ;
vc:uses ngm:tree-sitter-parsing .
ngm:ai-document-verification a skos:Concept ;
rdfs:label "AI Document Verification"@en .
ngm:ai-documentation a owl:Class ;
rdfs:comment "The structured transparency artefacts that record what an AI system is, how it was built, and how it behaves — model cards, datasheets for datasets, system cards, technical files, and decision logs. AI documentation is the evidentiary substrate of AI accountability: it lets developers, deployers, auditors, and regulators trace capabilities, limitations, training data provenance, and evaluation results, and is increasingly mandated by regimes such as the EU AI Act."@en ;
rdfs:label "AI Documentation"@en ;
rdfs:subClassOf ngm:documentation ;
vc:enables ngm:ai-accountability ;
vc:enables ngm:auditability ;
vc:enables ngm:transparency ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:training-data ;
vc:slug "ai-documentation" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-documentation-framework a skos:Concept ;
rdfs:label "AI Documentation Framework"@en .
ngm:ai-documentation-standards a owl:Class ;
rdfs:comment "AI Documentation Standards are structured frameworks and templates for comprehensively documenting AI systems, datasets, and models to ensure transparency, accountability, reproducibility, and informed stakeholder decision-making throughout the AI lifecycle."@en ;
rdfs:label "AI Documentation Standards"@en ;
rdfs:subClassOf ngm:ai-governance ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:ai-governance-framework ;
rdfs:subClassOf ngm:documentation-standards ;
rdfs:subClassOf ngm:responsible-ai ;
rdfs:subClassOf _:r347 ;
rdfs:subClassOf _:r348 ;
rdfs:subClassOf _:r349 ;
rdfs:subClassOf _:r350 ;
rdfs:subClassOf _:r351 ;
rdfs:subClassOf _:r352 ;
rdfs:subClassOf _:r353 ;
rdfs:subClassOf _:r354 ;
rdfs:subClassOf _:r355 ;
rdfs:subClassOf _:r356 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:smart-contract ;
vc:contrastsWith ngm:informal-ai-disclosure ;
vc:contrastsWith ngm:large-language-models ;
vc:dependsOn ngm:ai-ethics ;
vc:dependsOn ngm:ai-lifecycle ;
vc:dependsOn ngm:explainable-ai ;
vc:dependsOn ngm:large-language-models ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:enables ngm:ai-auditing ;
vc:enables ngm:ai-governance ;
vc:enables ngm:ai-impact-assessment ;
vc:enables ngm:ai-safety ;
vc:enables ngm:algorithmic-transparency ;
vc:enables ngm:decision-transparency ;
vc:enables ngm:regulatory-compliance ;
vc:enables ngm:responsible-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ai-impact-assessment ;
vc:hasPart ngm:ai-model-card ;
vc:hasPart ngm:algorithmic-transparency-reports ;
vc:hasPart ngm:data-cards ;
vc:hasPart ngm:datasheets-for-datasets ;
vc:hasPart ngm:datasheets-gebru-et-al ;
vc:hasPart ngm:documentation-generation ;
vc:hasPart ngm:factsheets ;
vc:hasPart ngm:factsheets-ibm ;
vc:hasPart ngm:system-cards ;
vc:implements ngm:ai-governance ;
vc:implements ngm:ai-governance-framework ;
vc:implements ngm:eu-ai-act-regulatory-instrument ;
vc:implements ngm:iso-iec-42001 ;
vc:implements ngm:nist-ai-rmf ;
vc:qualityScore "0.92"^^xsd:float ;
vc:relatedTo ngm:ai-ecosystem ;
vc:relatedTo ngm:ai-ethics-board ;
vc:relatedTo ngm:ai-governance-framework ;
vc:relatedTo ngm:ai-governance-law-and-privacy ;
vc:relatedTo ngm:ai-transparency-framework ;
vc:relatedTo ngm:algorithmic-transparency-index ;
vc:relatedTo ngm:documentation-standards ;
vc:relatedTo ngm:eu-ai-act-regulatory-instrument ;
vc:relatedTo ngm:gdpr ;
vc:relatedTo ngm:ieee-7001 ;
vc:relatedTo ngm:iso-iec-23053 ;
vc:relatedTo ngm:iso-iec-42001 ;
vc:relatedTo ngm:model-cards-mitchell-et-al ;
vc:relatedTo ngm:nist-ai-rmf ;
vc:requires ngm:ai-lifecycle ;
vc:requires ngm:algorithmic-auditing ;
vc:requires ngm:algorithmic-transparency ;
vc:requires ngm:bias-analysis ;
vc:requires ngm:explainable-ai ;
vc:requires ngm:machine-learning-discipline ;
vc:slug "ai-documentation-standards" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:ieee-7001 ;
vc:standardizedBy ngm:iso-iec-23053 ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:ai-ecosystem ;
vc:supports ngm:ai-ethics ;
vc:supports ngm:ai-ethics-checklist ;
vc:supports ngm:ai-governance-maturity-model ;
vc:supports ngm:ai-policy ;
vc:supports ngm:ai-safety ;
vc:supports ngm:explainable-ai ;
vc:uses ngm:ai-transparency-framework ;
vc:uses ngm:documentation-as-code ;
vc:uses ngm:documentation-generation ;
vc:uses ngm:documentation-standards ;
vc:uses ngm:model-context-protocol .
ngm:ai-doomerism a skos:Concept ;
rdfs:label "AI Doomerism"@en .
ngm:ai-driven-data-governance a skos:Concept ;
rdfs:label "AI Driven Data Governance"@en .
ngm:ai-driven-efficiency a owl:Class ;
rdfs:comment "The structural economic phenomenon where the adoption of artificial intelligence and automation leads to increased productivity and revenue growth while simultaneously reducing the required human labor force."@en ;
rdfs:label "AI-Driven Efficiency"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:agentic-workflow ;
vc:relatedTo ngm:foundation-model ;
vc:slug "ai-driven-efficiency" ;
vc:sourceDomain "economics" .
ngm:ai-driven-enterprise a owl:Class ;
rdfs:comment "A business organization that integrates artificial intelligence into its core strategy, operations, and value proposition to achieve competitive advantage and operational efficiency."@en ;
rdfs:label "AI-Driven Enterprise"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:intelligent-automation ;
vc:slug "ai-driven-enterprise" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-driven-finance a skos:Concept ;
rdfs:label "AI Driven Finance"@en .
ngm:ai-driven-network-operations a skos:Concept ;
rdfs:label "AI Driven Network Operations"@en .
ngm:ai-driven-software-development a owl:Class ;
rdfs:comment "The integration of generative AI tools into the software engineering lifecycle to automate code generation, review, and testing, fundamentally altering developer workflows and productivity metrics."@en ;
rdfs:label "AI-Driven Software Development"@en ;
rdfs:subClassOf ngm:model ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:model-architecture ;
vc:slug "ai-driven-software-development" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-driven-trading a skos:Concept ;
rdfs:label "AI Driven Trading"@en .
ngm:ai-driven-unemployment a owl:Class ;
rdfs:comment "The potential displacement of human workers by AI systems, particularly in knowledge work and entry-level roles."@en ;
rdfs:label "AI-Driven Unemployment"@en ;
rdfs:subClassOf ngm:data-management ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-impact-on-employment ;
vc:relatedTo ngm:labor-market-disruption ;
vc:slug "ai-driven-unemployment" ;
vc:sourceDomain "economics" .
ngm:ai-driven-vulnerability-discovery a owl:Class ;
rdfs:comment "The application of large language models and AI agents to systematically identify, analyze, and exploit software and system vulnerabilities at a scale and speed exceeding traditional human-led security research."@en ;
rdfs:label "AI-Driven Vulnerability Discovery"@en ;
rdfs:subClassOf ngm:ai-security ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:adversarial-machine-learning ;
vc:relatedTo ngm:claude ;
vc:relatedTo ngm:vulnerability ;
vc:relatedTo ngm:vulnerability-scanning ;
vc:slug "ai-driven-vulnerability-discovery" ;
vc:sourceDomain "security" .
ngm:ai-driven-workforce-displacement-registry a owl:Class ;
rdfs:comment "A curated record of mass layoffs in the technology sector from 2023 onwards, cataloguing headcount reductions at major firms alongside UK government estimates that AI automation may displace 10–30% of existing jobs. The tracker contextualises how AI adoption—particularly large language models and agentic AI—is accelerating workforce restructuring across white-collar roles."@en ;
rdfs:label "AI-Driven Workforce Displacement Registry"@en ;
rdfs:subClassOf ngm:software-engineering ;
vc:dependsOn ngm:generative-ai ;
vc:dependsOn ngm:large-language-models ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:economics ;
vc:slug "ai-driven-workforce-displacement-registry" ;
vc:sourceDomain "infrastructure" .
ngm:ai-driven-workforce-reduction a owl:Class ;
rdfs:comment "The systematic reduction of human labor roles and headcount within organizations explicitly attributed to the adoption of artificial intelligence capabilities."@en ;
rdfs:label "AI-Driven Workforce Reduction"@en ;
rdfs:subClassOf ngm:economics ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:automation ;
vc:relatedTo ngm:macroeconomics ;
vc:slug "ai-driven-workforce-reduction" ;
vc:sourceDomain "economics" .
ngm:ai-economic-impact a owl:Class ;
rdfs:comment "The analysis of how artificial intelligence technologies influence labor markets, capital allocation, productivity, and macroeconomic structures."@en ;
rdfs:label "AI Economic Impact"@en ;
rdfs:subClassOf ngm:economics ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:economics ;
vc:slug "ai-economic-impact" ;
vc:sourceDomain "economics" .
ngm:ai-economic-impact-prediction a skos:Concept ;
rdfs:label "AI Economic Impact Prediction"@en .
ngm:ai-economics a skos:Concept ;
rdfs:label "AI Economics"@en .
ngm:ai-ecosystem a owl:Class ;
rdfs:comment "The AI Ecosystem is the interconnected network of organisations, technologies, standards, talent pipelines, regulatory frameworks, and capital flows that collectively produce, deploy, and govern artificial intelligence systems. It encompasses foundation model providers, cloud infrastructure operators, toolchain vendors, application developers, research institutions, standardisation bodies, and end-user communities, together constituting the supply chain and governance fabric of AI as a general-purpose technology."@en ;
rdfs:label "AI Ecosystem"@en ;
rdfs:subClassOf ngm:digital-asset-ecosystem ;
rdfs:subClassOf ngm:digital-economy ;
rdfs:subClassOf _:r357 ;
rdfs:subClassOf _:r358 ;
rdfs:subClassOf _:r359 ;
rdfs:subClassOf _:r360 ;
rdfs:subClassOf _:r361 ;
rdfs:subClassOf _:r362 ;
rdfs:subClassOf _:r363 ;
rdfs:subClassOf _:r364 ;
rdfs:subClassOf _:r365 ;
rdfs:subClassOf _:r366 ;
rdfs:subClassOf _:r367 ;
rdfs:subClassOf _:r368 ;
rdfs:subClassOf _:r369 ;
rdfs:subClassOf _:r370 ;
rdfs:subClassOf _:r371 ;
rdfs:subClassOf _:r372 ;
rdfs:subClassOf _:r373 ;
rdfs:subClassOf _:r374 ;
rdfs:subClassOf _:r375 ;
rdfs:subClassOf _:r376 ;
vc:contrastsWith ngm:digital-asset-ecosystem ;
vc:contrastsWith ngm:sovereign-ai ;
vc:dependsOn ngm:computer-vision ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:reinforcement-learning ;
vc:dependsOn ngm:transformer-architecture ;
vc:enables ngm:agentic-ai ;
vc:enables ngm:ai-documentation-standards ;
vc:enables ngm:ai-governance ;
vc:enables ngm:ai-safety ;
vc:enables ngm:computer-vision ;
vc:enables ngm:digital-economy ;
vc:enables ngm:generative-ai ;
vc:enables ngm:multimodal-ai-architecture-ai ;
vc:enables ngm:natural-language-processing ;
vc:enables ngm:responsible-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:agent-frameworks ;
vc:hasPart ngm:ai-inference ;
vc:hasPart ngm:ai-research ;
vc:hasPart ngm:ai-safety-research ;
vc:hasPart ngm:ai-startups ;
vc:hasPart ngm:cloud-computing ;
vc:hasPart ngm:data-centre ;
vc:hasPart ngm:foundation-model ;
vc:hasPart ngm:gpu-computing ;
vc:hasPart ngm:large-language-models ;
vc:hasPart ngm:multimodal-ai-architecture-ai ;
vc:hasPart ngm:open-source-ai ;
vc:hasPart ngm:talent-pipeline ;
vc:hasPart ngm:venture-capital ;
vc:implements ngm:ai-governance-framework ;
vc:implements ngm:ai-policy ;
vc:implements ngm:eu-ai-act-regulatory-instrument ;
vc:implements ngm:national-ai-strategy ;
vc:qualityScore "0.93"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:ai-policy ;
vc:relatedTo ngm:ai-regulation ;
vc:relatedTo ngm:ai-safety-research ;
vc:relatedTo ngm:ai-standards ;
vc:relatedTo ngm:ai-startups ;
vc:relatedTo ngm:alan-turing-institute ;
vc:relatedTo ngm:eu-ai-act-regulatory-instrument ;
vc:relatedTo ngm:foundation-model ;
vc:relatedTo ngm:generative-ai ;
vc:relatedTo ngm:sovereign-ai ;
vc:relatedTo ngm:venture-capital ;
vc:requires ngm:ai-chips ;
vc:requires ngm:data-centre ;
vc:requires ngm:deep-learning ;
vc:requires ngm:gpu-computing ;
vc:requires ngm:machine-learning-discipline ;
vc:requires ngm:natural-language-processing ;
vc:requires ngm:transformer-architecture ;
vc:slug "ai-ecosystem" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:ai-governance-framework ;
vc:standardizedBy ngm:ai-standards ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:ai-documentation-standards ;
vc:supports ngm:ai-governance ;
vc:supports ngm:ai-policy ;
vc:supports ngm:ai-safety ;
vc:supports ngm:ai-standards ;
vc:supports ngm:responsible-ai ;
vc:supports ngm:sovereign-ai ;
vc:uses ngm:agent-frameworks ;
vc:uses ngm:ai-chips ;
vc:uses ngm:ai-inference ;
vc:uses ngm:cloud-computing ;
vc:uses ngm:large-language-models ;
vc:uses ngm:model-context-protocol .
ngm:ai-employment-effects a owl:Class ;
rdfs:comment "The measurable impact of artificial intelligence adoption on labor market outcomes, including job displacement, hiring rates, and wage structures across different skill levels and sectors."@en ;
rdfs:label "AI Employment Effects"@en ;
rdfs:subClassOf ngm:digital-economy ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:digital-economy ;
vc:relatedTo ngm:enterprise-ai-adoption ;
vc:slug "ai-employment-effects" ;
vc:sourceDomain "economics" .
ngm:ai-enabled-healthcare a skos:Concept ;
rdfs:label "AI Enabled Healthcare"@en .
ngm:ai-energy-consumption a owl:Class ;
rdfs:comment "The total electrical power and computational resources required to train, deploy, and operate artificial intelligence models."@en ;
rdfs:label "AI Energy Consumption"@en ;
rdfs:subClassOf ngm:energy-consumption ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-model ;
vc:relatedTo ngm:energy-consumption ;
vc:relatedTo ngm:model-training ;
vc:slug "ai-energy-consumption" ;
vc:sourceDomain "infrastructure" .
ngm:ai-energy-optimisation a owl:Class ;
rdfs:comment "The set of techniques and engineering practices that reduce the energy consumed by training and running artificial intelligence systems while preserving acceptable task performance, spanning model compression, efficient hardware selection, workload scheduling, and data-centre operation."@en ;
rdfs:label "AI Energy Optimisation"@en ;
rdfs:subClassOf ngm:ai-infrastructure ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf ngm:green-ai ;
rdfs:subClassOf ngm:model-compression ;
rdfs:subClassOf _:r377 ;
rdfs:subClassOf _:r378 ;
rdfs:subClassOf _:r379 ;
rdfs:subClassOf _:r380 ;
rdfs:subClassOf _:r381 ;
rdfs:subClassOf _:r382 ;
rdfs:subClassOf _:r383 ;
rdfs:subClassOf _:r384 ;
rdfs:subClassOf _:r385 ;
rdfs:subClassOf _:r386 ;
rdfs:subClassOf _:r387 ;
rdfs:subClassOf _:r388 ;
rdfs:subClassOf _:r389 ;
rdfs:subClassOf _:r390 ;
skos:broader ngm:artificial-intelligence ;
vc:bridgesTo ngm:ai-ethics-checklist ;
vc:bridgesTo ngm:data-centre ;
vc:bridgesTo ngm:environmental-sustainability ;
vc:bridgesTo ngm:renewable-energy ;
vc:contrastsWith ngm:high-performance-computing ;
vc:contrastsWith ngm:large-language-model ;
vc:dependsOn ngm:carbon-aware-computing ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:gpu-computing ;
vc:dependsOn ngm:hardware-acceleration ;
vc:dependsOn ngm:neuromorphic-computing ;
vc:enables ngm:carbon-aware-computing ;
vc:enables ngm:edge-ai ;
vc:enables ngm:edge-computing ;
vc:enables ngm:environmental-sustainability ;
vc:enables ngm:federated-learning ;
vc:enables ngm:on-device-inference ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:flash-attention ;
vc:hasPart ngm:gradient-checkpointing ;
vc:hasPart ngm:knowledge-distillation ;
vc:hasPart ngm:mixed-precision-training ;
vc:hasPart ngm:model-pruning ;
vc:hasPart ngm:model-quantization ;
vc:hasPart ngm:neural-architecture-search ;
vc:hasPart ngm:neural-network-quantisation ;
vc:hasPart ngm:parameter-efficient-fine-tuning ;
vc:hasPart ngm:sparse-attention ;
vc:hasPart ngm:speculative-decoding ;
vc:hasPart ngm:workload-scheduling ;
vc:implements ngm:green-ai ;
vc:implements ngm:model-compression ;
vc:implements ngm:parameter-efficient-fine-tuning ;
vc:implements ngm:transformers ;
vc:qualityScore "0.87"^^xsd:float ;
vc:relatedTo ngm:federated-learning ;
vc:relatedTo ngm:flash-attention ;
vc:relatedTo ngm:knowledge-distillation ;
vc:relatedTo ngm:neuromorphic-computing ;
vc:relatedTo ngm:on-device-inference ;
vc:relatedTo ngm:power-usage-effectiveness ;
vc:relatedTo ngm:speculative-decoding ;
vc:relatedTo ngm:transformers ;
vc:requires ngm:deep-learning ;
vc:requires ngm:gpu-computing ;
vc:requires ngm:hardware-acceleration ;
vc:requires ngm:power-usage-effectiveness ;
vc:slug "ai-energy-optimisation" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:supports ngm:ai-ethics-checklist ;
vc:supports ngm:ai-governance ;
vc:supports ngm:environmental-sustainability ;
vc:supports ngm:regulatory-compliance ;
vc:supports ngm:renewable-energy ;
vc:uses ngm:carbon-aware-computing ;
vc:uses ngm:edge-computing ;
vc:uses ngm:federated-learning ;
vc:uses ngm:mixed-precision-training ;
vc:uses ngm:renewable-energy ;
vc:uses ngm:transfer-learning .
ngm:ai-energy-scarcity a owl:Class ;
rdfs:comment "Systemic infrastructure bottleneck where exponential growth in AI training and inference compute demand outstrips available energy supply and grid capacity. Drives hyperscaler investment in dedicated power generation including small modular reactors (SMRs) and nuclear recommissioning, while creating geopolitical competition for compute sovereignty."@en ;
rdfs:label "AI Energy Scarcity"@en ;
rdfs:subClassOf ngm:infra-computing-and-cloud ;
skos:broader ngm:infra-computing-and-cloud ;
vc:contrastsWith ngm:bitcoin-proof-of-work-protocol-mining ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:competition-in-ai ;
vc:relatedTo ngm:energy-and-power ;
vc:relatedTo ngm:large-language-models ;
vc:slug "ai-energy-scarcity" ;
vc:sourceDomain "infrastructure" .
ngm:ai-engine a skos:Concept ;
rdfs:label "AI Engine"@en .
ngm:ai-ethics a owl:Class ;
rdfs:comment "AI Ethics addresses the moral principles, values, and guidelines governing the design, development, deployment, and use of artificial intelligence systems. This interdisciplinary field examines fairness, accountability, transparency, privacy, and bias mitigation, drawing on philosophy, law, and computer science to ensure AI systems respect human rights and societal values."@en ;
rdfs:label "AI Ethics"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf _:r417 ;
rdfs:subClassOf _:r418 ;
rdfs:subClassOf _:r419 ;
rdfs:subClassOf _:r420 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:data-governance ;
vc:bridgesTo ngm:digital-rights ;
vc:bridgesTo ngm:smart-contract ;
vc:contrastsWith ngm:algorithmic-bias ;
vc:contrastsWith ngm:surveillance-capitalism ;
vc:enables ngm:human-centered-ai ;
vc:enables ngm:responsible-ai ;
vc:enables ngm:trustworthy-ai ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.68"^^xsd:float ;
vc:relatedTo ngm:algorithmic-fairness ;
vc:relatedTo ngm:bias-mitigation-techniques ;
vc:relatedTo ngm:compliance-framework ;
vc:relatedTo ngm:existential-risk ;
vc:relatedTo ngm:privacy-preserving-machine-learning ;
vc:requires ngm:accountability ;
vc:requires ngm:explainable-ai ;
vc:requires ngm:fairness ;
vc:requires ngm:transparency ;
vc:slug "ai-ethics" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:ai-policy ;
vc:standardizedBy ngm:compliance-framework ;
vc:supports ngm:ai-governance ;
vc:supports ngm:data-privacy ;
vc:supports ngm:human-rights ;
vc:supports ngm:responsible-ai ;
vc:uses ngm:algorithmic-impact-assessment ;
vc:uses ngm:bias-mitigation-techniques ;
vc:uses ngm:value-sensitive-design .
ngm:ai-ethics-board a owl:Class ;
rdfs:comment "An AI Ethics Board is a formally constituted, multidisciplinary oversight committee responsible for reviewing AI systems and deployments against ethical principles, organisational values, and applicable regulatory requirements. Comprising technical experts, ethicists, legal and compliance professionals, domain specialists, and stakeholder representatives, the board conducts structured ethical impact assessments, provides binding or advisory guidance on AI deployment decisions, and monitors deployed systems for ongoing compliance. It serves as a key institutional mechanism for operationalising responsible AI principles and maintaining human oversight of consequential automated decision-making."@en ;
rdfs:label "AI Ethics Board"@en ;
rdfs:subClassOf ngm:ai-ethics ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf _:r391 ;
rdfs:subClassOf _:r392 ;
rdfs:subClassOf _:r393 ;
rdfs:subClassOf _:r394 ;
rdfs:subClassOf _:r395 ;
rdfs:subClassOf _:r396 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:enables ngm:accountability ;
vc:enables ngm:compliance-framework ;
vc:enables ngm:responsible-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ai-ethics-checklist ;
vc:hasPart ngm:audit-trail ;
vc:hasPart ngm:risk-assessment ;
vc:implements ngm:ai-policy ;
vc:implements ngm:ethical-ai ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:ai-governance-framework ;
vc:relatedTo ngm:ai-governance-principle ;
vc:relatedTo ngm:governance-board ;
vc:relatedTo ngm:responsible-ai-principles ;
vc:relatedTo ngm:stakeholder-engagement-in-ai ;
vc:requires ngm:governance-structure ;
vc:requires ngm:human-oversight ;
vc:requires ngm:stakeholder ;
vc:slug "ai-ethics-board" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:fairness-constraints ;
vc:supports ngm:transparency .
ngm:ai-ethics-checklist a owl:Class ;
rdfs:comment "Structured verification process evaluating fairness, accountability, transparency, and ethical compliance of AI systems against established governance frameworks including IEEE 7000, OECD AI Principles, UNESCO AI Ethics Recommendations, the EU AI Act, NIST AI RMF, and ISO/IEC 42001."@en ;
rdfs:label "AI Ethics Checklist"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:ai-governance-framework ;
rdfs:subClassOf ngm:responsible-ai ;
rdfs:subClassOf ngm:trustandgovernancedomain ;
rdfs:subClassOf _:r397 ;
rdfs:subClassOf _:r398 ;
rdfs:subClassOf _:r399 ;
rdfs:subClassOf _:r400 ;
rdfs:subClassOf _:r401 ;
rdfs:subClassOf _:r402 ;
rdfs:subClassOf _:r403 ;
rdfs:subClassOf _:r404 ;
rdfs:subClassOf _:r405 ;
rdfs:subClassOf _:r406 ;
rdfs:subClassOf _:r407 ;
rdfs:subClassOf _:r408 ;
rdfs:subClassOf _:r409 ;
rdfs:subClassOf _:r410 ;
rdfs:subClassOf _:r411 ;
rdfs:subClassOf _:r412 ;
rdfs:subClassOf _:r413 ;
rdfs:subClassOf _:r414 ;
rdfs:subClassOf _:r415 ;
rdfs:subClassOf _:r416 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:compliance-verification ;
vc:contrastsWith ngm:ai-agent-system ;
vc:dependsOn ngm:eu-ai-act-regulatory-instrument ;
vc:dependsOn ngm:ieee-7000 ;
vc:dependsOn ngm:iso-iec-42001 ;
vc:dependsOn ngm:nist-ai-rmf ;
vc:dependsOn ngm:oecd-ai-principles ;
vc:dependsOn ngm:unesco-ai-ethics-recommendations ;
vc:enables ngm:algorithmic-impact-assessment ;
vc:enables ngm:algorithmic-transparency-index ;
vc:enables ngm:compliance-verification ;
vc:enables ngm:ethical-ai ;
vc:enables ngm:incident-reporting ;
vc:enables ngm:responsible-ai ;
vc:enables ngm:risk-assessment ;
vc:enables ngm:stakeholder-trust ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:accountability-framework ;
vc:hasPart ngm:ai-model-card ;
vc:hasPart ngm:algorithmic-impact-assessment ;
vc:hasPart ngm:bias-detection-methods ;
vc:hasPart ngm:conformity-assessment ;
vc:hasPart ngm:fairness-assessment ;
vc:hasPart ngm:fundamental-rights-impact-assessment ;
vc:hasPart ngm:human-oversight ;
vc:hasPart ngm:incident-reporting ;
vc:hasPart ngm:transparency-metrics ;
vc:implements ngm:ieee-7000 ;
vc:implements ngm:iso-iec-42001 ;
vc:implements ngm:nist-ai-rmf ;
vc:implements ngm:oecd-ai-principles ;
vc:implements ngm:unesco-ai-ethics-recommendations ;
vc:isPartOf ngm:ai-governance-framework ;
vc:qualityScore "0.88"^^xsd:float ;
vc:relatedTo ngm:ai-energy-optimisation ;
vc:relatedTo ngm:algorithmic-impact-assessment ;
vc:relatedTo ngm:data-governance ;
vc:relatedTo ngm:fundamental-rights-impact-assessment ;
vc:relatedTo ngm:human-oversight ;
vc:relatedTo ngm:responsible-ai ;
vc:requires ngm:ai-documentation-standards ;
vc:requires ngm:assessment-methodology ;
vc:requires ngm:data-governance ;
vc:requires ngm:ethical-framework ;
vc:requires ngm:explainability ;
vc:requires ngm:human-oversight ;
vc:requires ngm:privacy-by-design ;
vc:slug "ai-ethics-checklist" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:ieee-7000 ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:standardizedBy ngm:oecd-ai-principles ;
vc:standardizedBy ngm:unesco-ai-ethics-recommendations ;
vc:supports ngm:ai-governance-framework ;
vc:supports ngm:ai-model-card ;
vc:supports ngm:algorithmic-transparency-index ;
vc:supports ngm:incident-reporting ;
vc:supports ngm:privacy-by-design ;
vc:supports ngm:stakeholder-trust ;
vc:uses ngm:algorithmic-transparency-index ;
vc:uses ngm:assessment-methodology ;
vc:uses ngm:bias-detection-methods ;
vc:uses ngm:explainability ;
vc:uses ngm:risk-assessment ;
vc:uses ngm:transparency-metrics .
ngm:ai-ethics-classification a skos:Concept ;
rdfs:label "AI Ethics Classification"@en .
ngm:ai-ethics-guidelines a skos:Concept ;
rdfs:label "AI Ethics Guidelines"@en .
ngm:ai-evaluation a owl:Class ;
rdfs:comment "AI Evaluation is the systematic, multi-dimensional measurement of AI model capabilities, reliability, safety, alignment, and societal impact using benchmarks, held-out task suites, human preference judgments, automated graders, and adversarial probing. It encompasses the full lifecycle of rigorous assessment from pre-deployment capability elicitation through post-deployment monitoring, producing quantitative metrics and qualitative findings that guide model selection, release decisions, regulatory compliance, and ongoing risk assessment. Credible evaluation must guard against benchmark contamination, distribution shift, Goodhart pressures, and over-optimisation toward narrow scores, while ensuring elicitation methods are sufficient to reveal the true capability ceiling of the system under test."@en ;
rdfs:label "AI Evaluation"@en ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf ngm:ai-safety ;
rdfs:subClassOf _:r421 ;
rdfs:subClassOf _:r422 ;
rdfs:subClassOf _:r423 ;
rdfs:subClassOf _:r424 ;
rdfs:subClassOf _:r425 ;
rdfs:subClassOf _:r426 ;
rdfs:subClassOf _:r427 ;
skos:broader ngm:ai-research-area ;
vc:contrastsWith ngm:benchmark-contamination ;
vc:contrastsWith ngm:benchmark-saturation ;
vc:contrastsWith ngm:goodhart-s-law ;
vc:dependsOn ngm:large-language-models ;
vc:dependsOn ngm:reward-model ;
vc:dependsOn ngm:rlhf ;
vc:enables ngm:ai-ethics ;
vc:enables ngm:alignment-evaluation ;
vc:enables ngm:eval-factsheet ;
vc:enables ngm:frontier-models ;
vc:enables ngm:model-cards ;
vc:enables ngm:sandbagging ;
vc:enables ngm:scalable-oversight ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:alignment-evaluation ;
vc:hasPart ngm:capability-elicitation ;
vc:hasPart ngm:evaluation-benchmarks-and-leaderboards ;
vc:hasPart ngm:evaluation-metric ;
vc:hasPart ngm:human-preference-evaluation ;
vc:hasPart ngm:llm-as-judge ;
vc:hasPart ngm:red-teaming ;
vc:hasPart ngm:safety-evaluation ;
vc:implements ngm:adversarial-testing ;
vc:implements ngm:bradley-terry-model ;
vc:implements ngm:dynamic-evaluation ;
vc:implements ngm:elo-rating ;
vc:qualityScore "0.91"^^xsd:float ;
vc:relatedTo ngm:ai-benchmark-epistemological-critique ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:bias ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:prompt-sensitivity ;
vc:relatedTo ngm:task-complexity ;
vc:requires ngm:ai-model-card ;
vc:requires ngm:calibration ;
vc:requires ngm:held-out-test-set ;
vc:requires ngm:human-oracle ;
vc:requires ngm:prompt-sensitivity ;
vc:slug "ai-evaluation" ;
vc:sourceDomain "ai" ;
vc:supports ngm:ai-benchmark-epistemological-critique ;
vc:supports ngm:bias ;
vc:supports ngm:distribution-shift ;
vc:uses ngm:aime ;
vc:uses ngm:arena-hard ;
vc:uses ngm:chatbot-arena ;
vc:uses ngm:eleutherai-lm-evaluation-harness ;
vc:uses ngm:gaia-benchmark ;
vc:uses ngm:gpqa ;
vc:uses ngm:helm ;
vc:uses ngm:humanity-s-last-exam ;
vc:uses ngm:inspect-framework ;
vc:uses ngm:livecodebench ;
vc:uses ngm:mmlu ;
vc:uses ngm:mt-bench ;
vc:uses ngm:swe-bench ;
vc:uses ngm:uk-ai-safety-institute .
ngm:ai-executive-accountability a owl:Class ;
rdfs:comment "The organizational governance structure that assigns specific responsibility and oversight for AI strategy, risk, and value realization to C-suite leadership, such as the CEO or CTO."@en ;
rdfs:label "AI Executive Accountability"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
skos:broader ngm:ai-governance-and-ethics ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:data-governance ;
vc:relatedTo ngm:trust-and-safety ;
vc:slug "ai-executive-accountability" ;
vc:sourceDomain "governance" .
ngm:ai-existential-risk-probability-estimate a owl:Class ;
rdfs:comment "p(doom) is an informal probabilistic estimate, expressed as a value between 0 and 1, of the likelihood that advanced AI development leads to an existential catastrophe for humanity—typically through loss of control over a misaligned superintelligent system. The metric is widely discussed in AI safety research communities as a shorthand for aggregating personal credences about existential risk, and is distinct from rigorous formal risk models, serving primarily as a rhetorical and community-calibration tool."@en ;
rdfs:label "AI Existential Risk Probability Estimate"@en ;
rdfs:subClassOf ngm:software-engineering ;
vc:bridgesTo ngm:ai-alignment ;
vc:bridgesTo ngm:history-and-path-to-agi ;
vc:bridgesTo ngm:uk-ai-safety-institute ;
vc:contrastsWith ngm:value-alignment ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.7"^^xsd:float ;
vc:relatedTo ngm:ai-risk ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:artificial-superintelligence-theory ;
vc:relatedTo ngm:safety-and-alignment ;
vc:slug "ai-existential-risk-probability-estimate" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:bayesian-inference .
ngm:ai-export-controls a owl:Class ;
rdfs:comment "Governmental regulations and policies that restrict the cross-border transfer of artificial intelligence technologies, models, and related hardware to protect national security interests."@en ;
rdfs:label "AI Export Controls"@en ;
rdfs:subClassOf ngm:ai-regulation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-regulation ;
vc:relatedTo ngm:european-commission ;
vc:relatedTo ngm:governance ;
vc:slug "ai-export-controls" ;
vc:sourceDomain "governance" .
ngm:ai-factory a skos:Concept ;
rdfs:label "AI Factory"@en .
ngm:ai-fairness a owl:Class ;
rdfs:comment "AI Fairness refers to the principle and practice of ensuring artificial intelligence systems produce equitable outcomes without bias or discrimination based on protected characteristics such as race, gender, age, or socioeconomic status."@en ;
rdfs:label "AI Fairness"@en ;
rdfs:subClassOf ngm:ai-ethics ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:smart-contract ;
vc:enables ngm:equitable-ai-systems ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.5"^^xsd:float ;
vc:slug "ai-fairness" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-fairness-audit a skos:Concept ;
rdfs:label "AI Fairness Audit"@en .
ngm:ai-feedback a skos:Concept ;
rdfs:label "AI Feedback"@en .
ngm:ai-for-good a skos:Concept ;
rdfs:label "AI For Good"@en .
ngm:ai-for-social-good a skos:Concept ;
rdfs:label "AI For Social Good"@en .
ngm:ai-for-sustainability a skos:Concept ;
rdfs:label "AI For Sustainability"@en .
ngm:ai-framework a owl:Class ;
rdfs:comment "A comprehensive software architecture that provides reusable code, design patterns, and infrastructure for developing artificial intelligence applications. AI frameworks abstract low-level computational details, offering high-level interfaces for model construction, training, and inference. Examples include TensorFlow, PyTorch, JAX, and scikit-learn, each optimised for distinct use cases from research prototyping to production deployment."@en ;
rdfs:label "AI Framework"@en ;
rdfs:subClassOf ngm:ai-infrastructure ;
rdfs:subClassOf _:r428 ;
vc:enables ngm:deep-learning ;
vc:enables ngm:machine-learning-discipline-pipeline ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:inference ;
vc:qualityScore "0.0"^^xsd:float ;
vc:slug "ai-framework" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:auto-ml ;
vc:supports ngm:neural-network ;
vc:uses ngm:machine-learning-discipline-infrastructure .
ngm:ai-framework-act a skos:Concept ;
rdfs:label "AI Framework Act"@en .
ngm:ai-frontier-capability-survey a owl:Class ;
rdfs:comment "State of the Art in AI is a curated survey of the current frontier of artificial intelligence capability, covering large language models, generative AI, multimodal systems, hardware advances, and sociotechnical implications. It synthesises emerging research directions, benchmark performance milestones, and near-term deployment trajectories across proprietary and open-source AI ecosystems."@en ;
rdfs:label "AI Frontier Capability Survey"@en ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf _:r429 ;
rdfs:subClassOf _:r430 ;
rdfs:subClassOf _:r431 ;
skos:broader ngm:ai-research-area ;
vc:bridgesTo ngm:ai-governance-law-and-privacy ;
vc:bridgesTo ngm:knowledge-artefact-update-cycle ;
vc:enables ngm:adoption-of-convergent-technologies ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:hardware-and-edge ;
vc:hasPart ngm:open-generative-ai-tools ;
vc:hasPart ngm:proprietary-large-language-models ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:ai-capability-temporal-horizon-framework ;
vc:relatedTo ngm:trust-and-safety ;
vc:slug "ai-frontier-capability-survey" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-funding-landscape a skos:Concept ;
rdfs:label "AI Funding Landscape"@en .
ngm:ai-game-agent a owl:Class ;
rdfs:comment "An AI Game Agent is an intelligent autonomous entity embedded within a video game or interactive virtual environment that perceives its local Game State through sensory abstraction, reasons over a structured decision framework, and executes goal-directed actions to create engaging, adaptive, and believable interactive experiences. Contemporary AI Game Agents synthesise classical symbolic control techniques — Finite State Machines, Behavior Trees, Goal-Oriented Action Planning, Hierarchical Task Networks — with data-driven methods including deep Reinforcement Learning, Imitation Learning from expert demonstrations, and Markov Decision Process formulations over Partially Observable environments. The most capable agents further incorporate Large Language Models as an 'inner monologue' for context-aware dialogue and high-level planning, while a learned Reinforcement Learning policy serves as the low-level action executor under Real-Time Constraints. The archetype spans NPC characters in narrative games, competitive game-playing agents trained through Self-Play such as AlphaGo and OpenAI Five, procedurally adaptive companions that model player behaviour through Player Modelling, and scripted simulation agents used in Automated Playtesting and Game Analytics pipelines."@en ;
rdfs:label "AI Game Agent"@en ;
rdfs:subClassOf ngm:ai-agent-system ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:intelligent-virtual-entity ;
rdfs:subClassOf _:r432 ;
rdfs:subClassOf _:r433 ;
rdfs:subClassOf _:r434 ;
rdfs:subClassOf _:r435 ;
rdfs:subClassOf _:r436 ;
rdfs:subClassOf _:r437 ;
rdfs:subClassOf _:r438 ;
rdfs:subClassOf _:r439 ;
rdfs:subClassOf _:r440 ;
skos:broader ngm:ai-application ;
vc:bridgesTo ngm:ai-in-games ;
vc:bridgesTo ngm:game-engine ;
vc:bridgesTo ngm:intelligent-virtual-entity ;
vc:bridgesTo ngm:procedural-content-generation ;
vc:contrastsWith ngm:scripted-npcs ;
vc:dependsOn ngm:game-engine ;
vc:dependsOn ngm:navigation-mesh ;
vc:dependsOn ngm:partially-observable-mdp ;
vc:enables ngm:adaptive-challenge ;
vc:enables ngm:automated-playtesting ;
vc:enables ngm:dynamic-difficulty-adjustment ;
vc:enables ngm:dynamic-gameplay ;
vc:enables ngm:emergent-behavior ;
vc:enables ngm:emergent-gameplay ;
vc:enables ngm:player-engagement ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:behaviour-tree ;
vc:hasPart ngm:decision-engine ;
vc:hasPart ngm:finite-state-machine ;
vc:hasPart ngm:influence-map ;
vc:hasPart ngm:npc-dialogue-system ;
vc:hasPart ngm:pathfinding ;
vc:hasPart ngm:state-machine ;
vc:implements ngm:adaptive-difficulty ;
vc:implements ngm:goap ;
vc:implements ngm:htn-planning ;
vc:implements ngm:imitation-learning ;
vc:implements ngm:monte-carlo-tree-search ;
vc:implements ngm:procedural-behavior ;
vc:implements ngm:reinforcement-learning ;
vc:implements ngm:utility-ai ;
vc:qualityScore "0.91"^^xsd:float ;
vc:relatedTo ngm:ai-in-games ;
vc:relatedTo ngm:game-analytics ;
vc:relatedTo ngm:game-theory ;
vc:relatedTo ngm:generative-agents ;
vc:relatedTo ngm:player-modelling ;
vc:relatedTo ngm:procedural-content-generation ;
vc:relatedTo ngm:spatial-reasoning ;
vc:requires ngm:game-engine ;
vc:requires ngm:game-state ;
vc:requires ngm:markov-decision-process ;
vc:requires ngm:navigation-mesh ;
vc:requires ngm:real-time-constraints ;
vc:slug "ai-game-agent" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:aaai-aiide ;
vc:standardizedBy ngm:ieee-cig ;
vc:supports ngm:inworld-ai ;
vc:supports ngm:nvidia-ace ;
vc:supports ngm:unity ;
vc:supports ngm:unreal-engine ;
vc:uses ngm:curriculum-learning ;
vc:uses ngm:domain-randomisation ;
vc:uses ngm:generative-agents ;
vc:uses ngm:large-language-models ;
vc:uses ngm:proximal-policy-optimisation ;
vc:uses ngm:reward-shaping ;
vc:uses ngm:self-play .
ngm:ai-gateway a skos:Concept ;
rdfs:label "AI Gateway"@en .
ngm:ai-generated-content a owl:Class ;
rdfs:comment "AI Generated Content (AIGC) refers to text, images, audio, video, code, or other media artefacts produced autonomously or semi-autonomously by artificial intelligence systems, particularly large generative models. The content may be indistinguishable from human-created output and spans creative, informational, and functional applications. Its proliferation raises governance questions around attribution, intellectual property, misinformation, and authenticity verification. Regulatory frameworks are evolving to mandate disclosure and provenance tracking of AI-generated material."@en ;
rdfs:label "Ai Generated Content"@en ;
rdfs:subClassOf ngm:governance ;
rdfs:subClassOf _:r1509 ;
rdfs:subClassOf _:r1510 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:content-moderation ;
vc:bridgesTo ngm:digital-media ;
vc:dependsOn ngm:generative-model ;
vc:dependsOn ngm:training-data ;
vc:enables ngm:content-personalisation ;
vc:enables ngm:creative-automation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:isPartOf ngm:generative-ai ;
vc:isPartOf ngm:governance ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:deepfakes ;
vc:relatedTo ngm:intellectual-property-rights-framework ;
vc:relatedTo ngm:large-language-model ;
vc:relatedTo ngm:misinformation ;
vc:requires ngm:content-authenticity ;
vc:requires ngm:provenance-tracking ;
vc:slug "ai-generated-content" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:c2-pa ;
vc:supports ngm:digital-watermarking .
ngm:ai-generated-content-disclosure a owl:Class ;
rdfs:comment "Mandatory transparency requirement specifying that content created wholly or partially by AI systems must be explicitly labeled with origin metadata for user awareness and regulatory compliance."@en ;
rdfs:label "AI-Generated Content Disclosure"@en ;
rdfs:subClassOf ngm:ai-ethics ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:ai-governance-framework ;
rdfs:subClassOf ngm:ai-transparency-framework ;
rdfs:subClassOf _:r781 ;
rdfs:subClassOf _:r782 ;
rdfs:subClassOf _:r783 ;
rdfs:subClassOf _:r784 ;
rdfs:subClassOf _:r785 ;
rdfs:subClassOf _:r786 ;
rdfs:subClassOf _:r787 ;
rdfs:subClassOf _:r788 ;
rdfs:subClassOf _:r789 ;
rdfs:subClassOf _:r790 ;
rdfs:subClassOf _:r791 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:ai-agent-system ;
vc:contrastsWith ngm:deepfakes ;
vc:contrastsWith ngm:misinformation ;
vc:dependsOn ngm:c2-pa-standard ;
vc:dependsOn ngm:eu-ai-act-regulatory-instrument ;
vc:dependsOn ngm:generative-ai ;
vc:dependsOn ngm:ieee-7001 ;
vc:dependsOn ngm:online-safety-act-2023 ;
vc:enables ngm:algorithmic-accountability ;
vc:enables ngm:algorithmic-transparency ;
vc:enables ngm:deepfake-detection ;
vc:enables ngm:informed-consent ;
vc:enables ngm:regulatory-compliance ;
vc:enables ngm:trust-building ;
vc:enables ngm:user-awareness ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ai-origin-declaration ;
vc:hasPart ngm:content-labeling-metadata ;
vc:hasPart ngm:digital-watermarking ;
vc:hasPart ngm:enforcement-mechanism ;
vc:hasPart ngm:transparency-notice ;
vc:hasPart ngm:watermarking-service ;
vc:isPartOf ngm:ai-transparency-framework ;
vc:qualityScore "0.88"^^xsd:float ;
vc:relatedTo ngm:deepfake-detection ;
vc:relatedTo ngm:deepfakes ;
vc:relatedTo ngm:generative-ai ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:misinformation ;
vc:relatedTo ngm:synthetic-media ;
vc:requires ngm:c2-pa-standard ;
vc:requires ngm:content-authentication ;
vc:requires ngm:documentation-standards ;
vc:requires ngm:metadata-standards ;
vc:requires ngm:provenance-tracking ;
vc:slug "ai-generated-content-disclosure" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:ai-governance-framework ;
vc:supports ngm:blockchain-provenance ;
vc:supports ngm:explainable-ai ;
vc:uses ngm:digital-rights-management ;
vc:uses ngm:metadata-standards ;
vc:uses ngm:synthetic-media .
ngm:ai-generated-pathogens a owl:Class ;
rdfs:comment "Biological agents or viral structures designed or synthesized using artificial intelligence algorithms, raising specific concerns regarding biosecurity and the potential for novel disease emergence."@en ;
rdfs:label "AI-Generated Pathogens"@en ;
rdfs:subClassOf ngm:ai-safety ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:risk-management ;
vc:slug "ai-generated-pathogens" ;
vc:sourceDomain "security" .
ngm:ai-generated-text a skos:Concept ;
rdfs:label "AI Generated Text"@en .
ngm:ai-geopolitics a owl:Class ;
rdfs:comment "The study of how artificial intelligence capabilities influence international relations, national security strategies, and the balance of power between states."@en ;
rdfs:label "AI Geopolitics"@en ;
rdfs:subClassOf ngm:ai-policy ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-policy ;
vc:relatedTo ngm:china ;
vc:relatedTo ngm:regulatory-framework ;
vc:slug "ai-geopolitics" ;
vc:sourceDomain "governance" .
ngm:ai-governance a owl:Class ;
rdfs:comment "AI Governance encompasses the policies, frameworks, standards, and institutional mechanisms for overseeing the responsible development, deployment, and use of artificial intelligence technologies, including regulatory compliance, organisational accountability structures, risk-based assessment, algorithmic transparency requirements, and stakeholder engagement processes that balance innovation with societal protection."@en ;
rdfs:label "AI Governance"@en ;
rdfs:subClassOf ngm:governance-framework ;
rdfs:subClassOf _:r472 ;
rdfs:subClassOf _:r473 ;
rdfs:subClassOf _:r474 ;
rdfs:subClassOf _:r475 ;
rdfs:subClassOf _:r476 ;
rdfs:subClassOf _:r477 ;
rdfs:subClassOf _:r478 ;
rdfs:subClassOf _:r479 ;
vc:bridgesTo ngm:decentralised-autonomous-organisation ;
vc:bridgesTo ngm:smart-contract ;
vc:dependsOn ngm:data-governance ;
vc:dependsOn ngm:risk-management ;
vc:enables ngm:responsible-ai ;
vc:enables ngm:trustworthy-ai ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:ai-audit ;
vc:hasPart ngm:ai-ethics-board ;
vc:hasPart ngm:ai-impact-assessment ;
vc:hasPart ngm:algorithmic-accountability ;
vc:implements ngm:eu-ai-act-regulatory-instrument ;
vc:implements ngm:nist-ai-rmf ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:ai-alignment ;
vc:relatedTo ngm:bias-mitigation-techniques ;
vc:relatedTo ngm:explainable-ai ;
vc:relatedTo ngm:gdpr ;
vc:relatedTo ngm:risk-management ;
vc:requires ngm:ai-ethics ;
vc:requires ngm:human-oversight ;
vc:requires ngm:regulatory-compliance ;
vc:requires ngm:transparency ;
vc:slug "ai-governance" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:standardizedBy ngm:oecd-ai-principles ;
vc:supports ngm:ai-alignment ;
vc:supports ngm:ai-safety ;
vc:supports ngm:digital-rights ;
vc:supports ngm:responsible-ai .
ngm:ai-governance-and-ethics a owl:Class ;
a skos:Concept ;
rdfs:comment "A taxonomy hub encompassing the policies, frameworks, principles, and regulatory mechanisms that govern the responsible development, deployment, and oversight of artificial intelligence systems. This category covers ethical guidelines, accountability structures, safety requirements, bias mitigation, transparency mandates, and legal compliance obligations that collectively shape how AI systems are built and governed."@en ;
rdfs:label "AI Governance and Ethics"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf _:r22686 ;
rdfs:subClassOf _:r22687 ;
rdfs:subClassOf _:r22688 ;
rdfs:subClassOf _:r22689 ;
rdfs:subClassOf _:r22690 ;
rdfs:subClassOf _:r22691 ;
rdfs:subClassOf _:r22692 ;
rdfs:subClassOf _:r22693 ;
rdfs:subClassOf _:r22694 ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ai-alignment ;
vc:hasPart ngm:ai-ethics ;
vc:hasPart ngm:ai-fairness ;
vc:hasPart ngm:ai-governance ;
vc:hasPart ngm:ai-regulation ;
vc:hasPart ngm:ai-risk-management ;
vc:hasPart ngm:ai-safety ;
vc:hasPart ngm:algorithmic-accountability ;
vc:hasPart ngm:algorithmic-bias ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:accountability ;
vc:relatedTo ngm:ai-governance-framework ;
vc:relatedTo ngm:ai-transparency-framework ;
vc:slug "ai-governance-and-ethics" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-governance-framework a owl:Class ;
rdfs:comment "Set of policies and procedures ensuring responsible development and operation of AI components in the metaverse."@en ;
rdfs:label "AI Governance Framework"@en ;
rdfs:subClassOf ngm:ai-governance ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:governance-model ;
rdfs:subClassOf ngm:policy-framework ;
rdfs:subClassOf _:r441 ;
rdfs:subClassOf _:r442 ;
rdfs:subClassOf _:r443 ;
rdfs:subClassOf _:r444 ;
rdfs:subClassOf _:r445 ;
rdfs:subClassOf _:r446 ;
rdfs:subClassOf _:r447 ;
rdfs:subClassOf _:r448 ;
rdfs:subClassOf _:r449 ;
rdfs:subClassOf _:r450 ;
rdfs:subClassOf _:r451 ;
rdfs:subClassOf _:r452 ;
rdfs:subClassOf _:r453 ;
rdfs:subClassOf _:r454 ;
rdfs:subClassOf _:r455 ;
rdfs:subClassOf _:r456 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:ai-governance ;
vc:bridgesTo ngm:data-governance ;
vc:bridgesTo ngm:smart-contract ;
vc:contrastsWith ngm:algorithmic-bias ;
vc:contrastsWith ngm:opaque-ai ;
vc:contrastsWith ngm:unregulated-deployment ;
vc:dependsOn ngm:data-governance ;
vc:dependsOn ngm:policy-framework ;
vc:dependsOn ngm:regulatory-compliance ;
vc:dependsOn ngm:risk-management ;
vc:enables ngm:ai-accountability ;
vc:enables ngm:ai-safety ;
vc:enables ngm:ai-transparency-framework ;
vc:enables ngm:ethical-ai ;
vc:enables ngm:explainable-ai ;
vc:enables ngm:responsible-ai ;
vc:enables ngm:trustworthy-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ai-ethics-board ;
vc:hasPart ngm:ai-ethics-checklist ;
vc:hasPart ngm:ai-impact-assessment ;
vc:hasPart ngm:ai-risk-assessment ;
vc:hasPart ngm:algorithmic-accountability ;
vc:hasPart ngm:algorithmic-transparency-index ;
vc:hasPart ngm:audit-mechanism ;
vc:hasPart ngm:compliance-policy ;
vc:hasPart ngm:ethical-framework ;
vc:hasPart ngm:human-oversight ;
vc:hasPart ngm:stakeholder-engagement ;
vc:implements ngm:eu-ai-act-regulatory-instrument ;
vc:implements ngm:iso-iec-42001 ;
vc:implements ngm:nist-ai-rmf ;
vc:implements ngm:oecd-ai-principles ;
vc:isPartOf ngm:ai-governance ;
vc:isPartOf ngm:governance-model ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-agent-system ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:ai-governance-maturity-model ;
vc:relatedTo ngm:explainability ;
vc:relatedTo ngm:fairness ;
vc:relatedTo ngm:gdpr ;
vc:relatedTo ngm:responsible-ai ;
vc:relatedTo ngm:transparency ;
vc:requires ngm:access-control ;
vc:requires ngm:ai-risk-management ;
vc:requires ngm:data-governance ;
vc:requires ngm:identity-management ;
vc:requires ngm:model-documentation ;
vc:requires ngm:regulatory-compliance ;
vc:slug "ai-governance-framework" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:standardizedBy ngm:oecd-ai-principles ;
vc:supports ngm:ai-alignment ;
vc:supports ngm:ai-safety ;
vc:supports ngm:digital-rights ;
vc:supports ngm:human-oversight ;
vc:uses ngm:ai-model-card ;
vc:uses ngm:ai-risk-assessment ;
vc:uses ngm:algorithmic-auditing ;
vc:uses ngm:bias-mitigation-techniques ;
vc:uses ngm:red-teaming .
ngm:ai-governance-law-and-privacy a owl:Class ;
rdfs:comment "The intersecting domain of political governance, legal frameworks, and individual privacy rights as they apply to AI and digital technologies. This cluster addresses how legislation (e.g., EU AI Act, GDPR), regulatory enforcement, and political economy shape what AI systems are permitted to do, how data about individuals is collected and used, and how citizens can exercise rights against automated decision-making and surveillance."@en ;
rdfs:label "AI Governance Law and Privacy"@en ;
rdfs:subClassOf ngm:infra-legal-and-regulatory ;
rdfs:subClassOf _:r457 ;
rdfs:subClassOf _:r458 ;
rdfs:subClassOf _:r459 ;
rdfs:subClassOf _:r460 ;
rdfs:subClassOf _:r461 ;
rdfs:subClassOf _:r462 ;
rdfs:subClassOf _:r463 ;
skos:broader ngm:infra-legal-and-regulatory ;
vc:bridgesTo ngm:education-and-ai ;
vc:bridgesTo ngm:supply-chain-transparency ;
vc:bridgesTo ngm:trust-and-safety ;
vc:contrastsWith ngm:digital-society-surveillance ;
vc:contrastsWith ngm:surveillance-capitalism ;
vc:dependsOn ngm:data-sovereignty ;
vc:dependsOn ngm:rule-of-law ;
vc:enables ngm:access-to-justice ;
vc:enables ngm:democratic-governance ;
vc:enables ngm:trustworthy-ai ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:ai-liability ;
vc:hasPart ngm:ai-regulation ;
vc:hasPart ngm:algorithmic-accountability ;
vc:hasPart ngm:data-protection ;
vc:hasPart ngm:digital-rights ;
vc:implements ngm:data-protection-regulation ;
vc:implements ngm:eu-ai-act-regulatory-instrument ;
vc:isPartOf ngm:digital-governance ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:data-brokerage ;
vc:relatedTo ngm:facial-recognition ;
vc:relatedTo ngm:intellectual-property-rights-framework ;
vc:relatedTo ngm:open-source-ai ;
vc:requires ngm:fundamental-rights-impact-assessment ;
vc:requires ngm:gdpr-compliance ;
vc:requires ngm:regulatory-impact-assessment ;
vc:slug "ai-governance-law-and-privacy" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:civil-liberties ;
vc:supports ngm:human-oversight ;
vc:uses ngm:conformity-assessment ;
vc:uses ngm:risk-classification .
ngm:ai-governance-maturity-model a owl:Class ;
rdfs:comment "AI Governance Maturity Model is an assessment framework that defines progressive maturity levels for AI governance capabilities across multiple dimensions, enabling organizations to evaluate current practices, identify gaps, benchmark against peers, and guide continuous improvement toward trustwo..."@en ;
rdfs:label "AI Governance Maturity Model"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:ai-governance-framework ;
rdfs:subClassOf ngm:assessment-framework ;
rdfs:subClassOf ngm:governance-model ;
rdfs:subClassOf ngm:maturity-model ;
rdfs:subClassOf _:r464 ;
rdfs:subClassOf _:r465 ;
rdfs:subClassOf _:r466 ;
rdfs:subClassOf _:r467 ;
rdfs:subClassOf _:r468 ;
rdfs:subClassOf _:r469 ;
rdfs:subClassOf _:r470 ;
rdfs:subClassOf _:r471 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:data-governance-maturity-model ;
vc:bridgesTo ngm:enterprise-risk-management ;
vc:bridgesTo ngm:smart-contract ;
vc:contrastsWith ngm:ad-hoc-ai-deployment ;
vc:contrastsWith ngm:governance-theatre ;
vc:contrastsWith ngm:unregulated-deployment ;
vc:dependsOn ngm:ai-governance-framework ;
vc:dependsOn ngm:data-governance ;
vc:dependsOn ngm:regulatory-compliance ;
vc:dependsOn ngm:risk-management ;
vc:enables ngm:ai-accountability ;
vc:enables ngm:ai-safety ;
vc:enables ngm:ai-transparency-framework ;
vc:enables ngm:continuous-improvement ;
vc:enables ngm:regulatory-compliance ;
vc:enables ngm:responsible-ai ;
vc:enables ngm:trustworthy-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:artificial-intelligence ;
vc:hasPart ngm:assessment-dimension ;
vc:hasPart ngm:benchmarking-methodology ;
vc:hasPart ngm:evidence-collection ;
vc:hasPart ngm:gap-analysis ;
vc:hasPart ngm:governance-capability ;
vc:hasPart ngm:improvement-roadmap ;
vc:hasPart ngm:maturity-level ;
vc:hasPart ngm:self-assessment-tool ;
vc:implements ngm:cmmi-institute ;
vc:implements ngm:iso-21827 ;
vc:implements ngm:iso-iec-42001 ;
vc:implements ngm:nist-ai-rmf ;
vc:implements ngm:oecd-ai-principles ;
vc:implements ngm:singapore-model-ai-governance-framework ;
vc:isPartOf ngm:ai-governance ;
vc:isPartOf ngm:ai-governance-framework ;
vc:isPartOf ngm:governance-model ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:ai-governance-framework ;
vc:relatedTo ngm:ai-risk-management ;
vc:relatedTo ngm:algorithmic-accountability ;
vc:relatedTo ngm:fairness ;
vc:relatedTo ngm:human-oversight ;
vc:relatedTo ngm:responsible-ai ;
vc:relatedTo ngm:smart-contract ;
vc:relatedTo ngm:transparency ;
vc:requires ngm:ai-ethics-board ;
vc:requires ngm:ai-governance-framework ;
vc:requires ngm:ai-risk-assessment ;
vc:requires ngm:model-documentation ;
vc:requires ngm:regulatory-compliance ;
vc:requires ngm:stakeholder-engagement ;
vc:slug "ai-governance-maturity-model" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:cmmi-institute ;
vc:standardizedBy ngm:iso-21827 ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:ai-accountability ;
vc:supports ngm:ai-risk-management ;
vc:supports ngm:ai-safety ;
vc:supports ngm:ethical-ai ;
vc:supports ngm:responsible-ai ;
vc:uses ngm:ai-ethics-checklist ;
vc:uses ngm:ai-risk-assessment ;
vc:uses ngm:algorithmic-auditing ;
vc:uses ngm:benchmarking-methodology ;
vc:uses ngm:evidence-collection ;
vc:uses ngm:gap-analysis ;
vc:uses ngm:self-assessment-tool .
ngm:ai-governance-principle a owl:Class ;
rdfs:comment "A normative rule or guideline that shapes the design, development, deployment, and oversight of AI systems to ensure they remain safe, fair, transparent, and accountable. AI governance principles operationalise ethical commitments into actionable standards, informing policy frameworks such as the OECD AI Principles and the EU AI Act, and guiding organisational decision-making throughout the AI lifecycle."@en ;
rdfs:label "AI Governance Principle"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf _:r1511 ;
rdfs:subClassOf _:r1512 ;
rdfs:subClassOf _:r1513 ;
rdfs:subClassOf _:r1514 ;
rdfs:subClassOf _:r1515 ;
rdfs:subClassOf _:r1516 ;
rdfs:subClassOf _:r1517 ;
rdfs:subClassOf _:r1518 ;
rdfs:subClassOf _:r1519 ;
rdfs:subClassOf _:r1520 ;
rdfs:subClassOf _:r1521 ;
rdfs:subClassOf _:r1522 ;
rdfs:subClassOf _:r1523 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:contrastsWith ngm:agentic-ai ;
vc:contrastsWith ngm:algorithmic-bias ;
vc:dependsOn ngm:ai-governance ;
vc:dependsOn ngm:ai-risk-assessment ;
vc:dependsOn ngm:data-governance ;
vc:dependsOn ngm:responsible-ai-principles ;
vc:enables ngm:accountability ;
vc:enables ngm:ai-governance-framework ;
vc:enables ngm:ai-regulation ;
vc:enables ngm:national-ai-strategy ;
vc:enables ngm:responsible-ai ;
vc:enables ngm:trustworthy-ai ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:accountability ;
vc:hasPart ngm:ai-safety ;
vc:hasPart ngm:contestability ;
vc:hasPart ngm:explainable-ai ;
vc:hasPart ngm:fairness ;
vc:hasPart ngm:privacy ;
vc:hasPart ngm:robustness ;
vc:hasPart ngm:transparency ;
vc:implements ngm:ai-ethics ;
vc:implements ngm:constitutional-ai-training-methodology ;
vc:implements ngm:oecd-ai-principles ;
vc:implements ngm:value-alignment ;
vc:qualityScore "0.91"^^xsd:float ;
vc:relatedTo ngm:ai-alignment ;
vc:relatedTo ngm:data-governance ;
vc:relatedTo ngm:digital-rights ;
vc:relatedTo ngm:regulatory-compliance ;
vc:relatedTo ngm:responsible-ai-principles ;
vc:relatedTo ngm:societal-impact ;
vc:requires ngm:ai-impact-assessment ;
vc:requires ngm:human-oversight ;
vc:requires ngm:interpretability ;
vc:requires ngm:model-evaluation ;
vc:requires ngm:risk-management ;
vc:slug "ai-governance-principle" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:bletchley-declaration ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:g7-hiroshima-ai-process ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:standardizedBy ngm:oecd-ai-principles ;
vc:supports ngm:corrigibility ;
vc:supports ngm:explainable-ai ;
vc:supports ngm:human-in-the-loop ;
vc:supports ngm:human-oversight ;
vc:supports ngm:inclusive-growth ;
vc:uses ngm:ai-impact-assessment ;
vc:uses ngm:interpretability ;
vc:uses ngm:model-evaluation ;
vc:uses ngm:red-teaming .
ngm:ai-group-formation a owl:Class ;
rdfs:comment "AI Group Formation is the automated assignment of participants into subgroups using models that optimise for criteria such as skill balance, topic affinity, social diversity, or learning objectives. In collaborative and meeting platforms it drives features like intelligent breakout-room allocation, replacing manual or random grouping. The technique combines clustering, optimisation, and sometimes reinforcement learning over participant attributes and interaction signals."@en ;
rdfs:label "AI Group Formation"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:combinatorial-optimisation ;
rdfs:subClassOf ngm:unsupervised-learning ;
rdfs:subClassOf _:r480 ;
rdfs:subClassOf _:r481 ;
rdfs:subClassOf _:r482 ;
rdfs:subClassOf _:r483 ;
rdfs:subClassOf _:r484 ;
rdfs:subClassOf _:r485 ;
skos:broader ngm:ai-application ;
vc:contrastsWith ngm:automatic-grouping ;
vc:contrastsWith ngm:manual-room-assignment ;
vc:dependsOn ngm:learning-analytics ;
vc:dependsOn ngm:learning-management-system ;
vc:dependsOn ngm:participant-profiling ;
vc:enables ngm:breakout-room ;
vc:enables ngm:collaborative-systems-modality-learning ;
vc:enables ngm:participation-equity ;
vc:enables ngm:personalised-learning ;
vc:enables ngm:scaled-workshop-facilitation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:constraint-satisfaction ;
vc:hasPart ngm:distance-metric ;
vc:hasPart ngm:diversity-optimisation ;
vc:hasPart ngm:participant-profiling ;
vc:hasPart ngm:skill-matching ;
vc:qualityScore "0.87"^^xsd:float ;
vc:relatedTo ngm:adaptive-learning ;
vc:relatedTo ngm:collaborative-systems-modality-whiteboard ;
vc:relatedTo ngm:community-detection ;
vc:relatedTo ngm:graph-analytics ;
vc:relatedTo ngm:group-facilitation-tools ;
vc:relatedTo ngm:human-computer-interaction ;
vc:relatedTo ngm:meeting-ai-assistant ;
vc:relatedTo ngm:multi-objective-optimisation ;
vc:relatedTo ngm:social-network-analysis ;
vc:relatedTo ngm:team-communication-platform ;
vc:requires ngm:data-pipeline ;
vc:requires ngm:distance-metric ;
vc:requires ngm:feature-engineering ;
vc:requires ngm:learning-analytics ;
vc:slug "ai-group-formation" ;
vc:sourceDomain "ai" ;
vc:supports ngm:active-learning ;
vc:supports ngm:conference-facilitation ;
vc:supports ngm:corporate-training ;
vc:supports ngm:educational-technology ;
vc:supports ngm:peer-learning ;
vc:supports ngm:problem-based-learning ;
vc:supports ngm:remote-education ;
vc:supports ngm:virtual-workshop ;
vc:uses ngm:clustering ;
vc:uses ngm:embedding ;
vc:uses ngm:genetic-algorithm ;
vc:uses ngm:graph-analytics ;
vc:uses ngm:k-means-clustering ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:recommender-system ;
vc:uses ngm:reinforcement-learning .
ngm:ai-hardware a owl:Class ;
rdfs:comment "AI Hardware encompasses specialized computing hardware designed to accelerate artificial intelligence and machine learning workloads, including GPUs, TPUs, NPUs, and other AI accelerators optimized for training neural networks and running inference at scale. These processors feature architectures specifically designed for matrix operations, parallel processing, and low-precision arithmetic fundamental to modern AI algorithms."@en ;
rdfs:label "AI Hardware"@en ;
rdfs:subClassOf ngm:computer-hardware ;
rdfs:subClassOf _:r486 ;
rdfs:subClassOf _:r487 ;
rdfs:subClassOf _:r488 ;
rdfs:subClassOf _:r489 ;
rdfs:subClassOf _:r490 ;
rdfs:subClassOf _:r491 ;
rdfs:subClassOf _:r492 ;
vc:bridgesTo ngm:autonomous-robot ;
vc:bridgesTo ngm:robotics ;
vc:bridgesTo ngm:spatial-computing ;
vc:contrastsWith ngm:central-processing-unit ;
vc:dependsOn ngm:semiconductor-industry ;
vc:dependsOn ngm:supply-chain ;
vc:enables ngm:ai-inference ;
vc:enables ngm:autonomous-robot ;
vc:enables ngm:deep-learning ;
vc:enables ngm:large-language-models ;
vc:enables ngm:neural-network-training ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:field-programmable-gate-array ;
vc:hasPart ngm:graphics-processing-unit ;
vc:hasPart ngm:high-bandwidth-memory ;
vc:hasPart ngm:neural-processing-unit ;
vc:hasPart ngm:tensor-processing-unit ;
vc:isPartOf ngm:ai-infrastructure ;
vc:isPartOf ngm:data-centre ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:energy-consumption ;
vc:requires ngm:cooling-system ;
vc:requires ngm:semiconductor-fabrication ;
vc:slug "ai-hardware" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:edge-computing ;
vc:supports ngm:scientific-computing ;
vc:uses ngm:mixed-precision-arithmetic ;
vc:uses ngm:parallel-computing .
ngm:ai-hardware-ecosystem a owl:Class ;
rdfs:comment "The interconnected network of specialized computing hardware, software stacks, and device manufacturers that enable the deployment and utilization of artificial intelligence models across various consumer and enterprise applications."@en ;
rdfs:label "AI Hardware Ecosystem"@en ;
rdfs:subClassOf ngm:ai-hardware ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-hardware ;
vc:relatedTo ngm:edge-computing ;
vc:relatedTo ngm:foundation-model ;
vc:slug "ai-hardware-ecosystem" ;
vc:sourceDomain "infrastructure" .
ngm:ai-hardware-infrastructure a skos:Concept ;
rdfs:label "AI Hardware Infrastructure"@en .
ngm:ai-harness-engineering a skos:Concept ;
rdfs:label "AI Harness Engineering"@en .
ngm:ai-harnesses a owl:Class ;
rdfs:comment "The software frameworks, user interfaces, and integration layers that wrap around AI models to enable their practical application and value extraction in specific contexts."@en ;
rdfs:label "AI Harnesses"@en ;
rdfs:subClassOf ngm:model ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:model ;
vc:relatedTo ngm:model-architecture ;
vc:slug "ai-harnesses" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-hpc-pivot a skos:Concept ;
rdfs:label "AI Hpc Pivot"@en .
ngm:ai-image-enhancement a skos:Concept ;
rdfs:label "AI Image Enhancement"@en .
ngm:ai-image-generation a owl:Class ;
rdfs:comment "The use of generative AI models to create or modify visual content from text or other inputs."@en ;
rdfs:label "AI Image Generation"@en ;
rdfs:subClassOf ngm:generative-model ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:computer-vision ;
vc:relatedTo ngm:generative-model ;
vc:slug "ai-image-generation" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-impact-assessment a owl:Class ;
rdfs:comment "A systematic process for identifying, analysing, evaluating, and documenting the potential positive and negative effects of an artificial intelligence system on individuals, groups, organisations, society, and the environment across multiple dimensions including fundamental rights, ethical principles, safety, fairness, privacy, environmental sustainability, and socioeconomic impacts, conducted prior to deployment and periodically thereafter to inform design decisions, risk mitigation strategies, governance arrangements, and stakeholder communication regarding AI system consequences."@en ;
rdfs:label "AI Impact Assessment"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf _:r493 ;
rdfs:subClassOf _:r494 ;
rdfs:subClassOf _:r495 ;
rdfs:subClassOf _:r496 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:environmental-assessment ;
vc:bridgesTo ngm:gdpr ;
vc:bridgesTo ngm:smart-contract ;
vc:dependsOn ngm:risk-management ;
vc:enables ngm:accountability ;
vc:enables ngm:informed-decision-making ;
vc:enables ngm:risk-management ;
vc:enables ngm:transparency ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:stakeholder-engagement ;
vc:implements ngm:nist-ai-rmf ;
vc:isPartOf ngm:ai-governance ;
vc:isPartOf ngm:ai-lifecycle ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:responsible-ai ;
vc:requires ngm:fairness ;
vc:requires ngm:human-rights ;
vc:requires ngm:stakeholder ;
vc:slug "ai-impact-assessment" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:iso-iec-23894-2023 ;
vc:standardizedBy ngm:iso-iec-42001-2023 ;
vc:supports ngm:ai-audit ;
vc:supports ngm:regulatory-compliance ;
vc:uses ngm:algorithmic-impact-assessment ;
vc:uses ngm:human-rights-impact-assessment .
ngm:ai-impact-on-employment a skos:Concept ;
rdfs:label "AI Impact On Employment"@en .
ngm:ai-impacts-surveys a skos:Concept ;
rdfs:label "AI Impacts Surveys"@en .
ngm:ai-in-finance a skos:Concept ;
rdfs:label "AI In Finance"@en .
ngm:ai-in-games a owl:Class ;
rdfs:comment "AI in Games is the interdisciplinary research and engineering field encompassing the design, implementation, and study of computational systems that perceive, decide, learn, and generate within interactive entertainment software, spanning classical symbolic techniques (finite-state machines FSM d..."@en ;
rdfs:label "AI in Games"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:applied-artificial-intelligence ;
rdfs:subClassOf ngm:entertainment-technology ;
rdfs:subClassOf ngm:game-development ;
rdfs:subClassOf ngm:interactive-computing ;
rdfs:subClassOf ngm:real-time-ai ;
rdfs:subClassOf _:r762 ;
rdfs:subClassOf _:r763 ;
rdfs:subClassOf _:r764 ;
rdfs:subClassOf _:r765 ;
rdfs:subClassOf _:r766 ;
rdfs:subClassOf _:r767 ;
rdfs:subClassOf _:r768 ;
rdfs:subClassOf _:r769 ;
rdfs:subClassOf _:r770 ;
rdfs:subClassOf _:r771 ;
rdfs:subClassOf _:r772 ;
rdfs:subClassOf _:r773 ;
rdfs:subClassOf _:r774 ;
rdfs:subClassOf _:r775 ;
rdfs:subClassOf _:r776 ;
rdfs:subClassOf _:r777 ;
rdfs:subClassOf _:r778 ;
rdfs:subClassOf _:r779 ;
skos:broader ngm:ai-application ;
vc:bridgesTo ngm:game-development ;
vc:contrastsWith ngm:classical-ai-without-learning ;
vc:contrastsWith ngm:expert-systems ;
vc:contrastsWith ngm:hand-authored-dialogue ;
vc:contrastsWith ngm:scripted-npcs ;
vc:contrastsWith ngm:static-quest-trees ;
vc:dependsOn ngm:game-theory ;
vc:dependsOn ngm:generative-ai ;
vc:dependsOn ngm:large-language-models ;
vc:dependsOn ngm:neural-network ;
vc:dependsOn ngm:planning-algorithms ;
vc:dependsOn ngm:probabilistic-reasoning ;
vc:dependsOn ngm:reinforcement-learning ;
vc:dependsOn ngm:search-algorithms ;
vc:enables ngm:adaptive-tutoring ;
vc:enables ngm:automated-playtesting ;
vc:enables ngm:believable-npc-behaviour ;
vc:enables ngm:difficulty-adjustment ;
vc:enables ngm:dynamic-narrative ;
vc:enables ngm:emergent-gameplay ;
vc:enables ngm:personalised-game-experience ;
vc:enables ngm:procedural-replayability ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ai-game-agent ;
vc:hasPart ngm:animation-controller ;
vc:hasPart ngm:behaviour-tree ;
vc:hasPart ngm:behaviour-trees ;
vc:hasPart ngm:dialogue-system ;
vc:hasPart ngm:finite-state-machine ;
vc:hasPart ngm:goap ;
vc:hasPart ngm:htn-planning ;
vc:hasPart ngm:influence-map ;
vc:hasPart ngm:monte-carlo-tree-search ;
vc:hasPart ngm:navigation-mesh ;
vc:hasPart ngm:pathfinding ;
vc:hasPart ngm:procedural-content-generation ;
vc:implements ngm:alphazero ;
vc:implements ngm:behaviour-tree ;
vc:implements ngm:dreamerv3 ;
vc:implements ngm:impala ;
vc:implements ngm:mu-zero ;
vc:implements ngm:perlin-noise ;
vc:implements ngm:proximal-policy-optimisation ;
vc:implements ngm:recast-navmesh ;
vc:implements ngm:search-algorithm ;
vc:implements ngm:simplex-noise ;
vc:implements ngm:utility-ai ;
vc:implements ngm:voronoi-diagram ;
vc:implements ngm:wave-function-collapse ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:computational-creativity ;
vc:relatedTo ngm:esports ;
vc:relatedTo ngm:game-analytics ;
vc:relatedTo ngm:game-user-research ;
vc:relatedTo ngm:generative-ai ;
vc:relatedTo ngm:player-modelling ;
vc:relatedTo ngm:speedrunning ;
vc:relatedTo ngm:twitch-plays ;
vc:requires ngm:content-creation-pipeline ;
vc:requires ngm:game-engine ;
vc:requires ngm:game-state-representation ;
vc:requires ngm:player-modelling ;
vc:requires ngm:quality-assurance ;
vc:requires ngm:real-time-constraints ;
vc:requires ngm:spatial-reasoning ;
vc:slug "ai-in-games" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:aaai-aiide ;
vc:standardizedBy ngm:fdg-conference ;
vc:standardizedBy ngm:ieee ;
vc:standardizedBy ngm:igda-ai-special-interest-group ;
vc:standardizedBy ngm:khronos-gl-tf ;
vc:standardizedBy ngm:open-usd ;
vc:supports ngm:bevy ;
vc:supports ngm:convai ;
vc:supports ngm:cryengine ;
vc:supports ngm:gamemaker ;
vc:supports ngm:godot ;
vc:supports ngm:inworld-ai ;
vc:supports ngm:nvidia-corporation ;
vc:supports ngm:roblox ;
vc:supports ngm:unity ;
vc:supports ngm:unreal-engine ;
vc:uses ngm:curriculum-learning ;
vc:uses ngm:domain-randomisation ;
vc:uses ngm:imitation-learning ;
vc:uses ngm:markov-decision-process ;
vc:uses ngm:partially-observable-mdp ;
vc:uses ngm:reward-shaping ;
vc:uses ngm:self-play .
ngm:ai-in-healthcare a owl:Class ;
rdfs:comment "The application of artificial intelligence technologies to clinical decision-making, diagnostics, and administrative workflows within the medical field."@en ;
rdfs:label "AI in Healthcare"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:decision-support ;
vc:slug "ai-in-healthcare" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-incident a owl:Class ;
rdfs:comment "An event in which an AI system causes or has the potential to cause harm to individuals, property, the environment, or fundamental rights, encompassing technical failures, security breaches, bias-driven discrimination, privacy violations, and unintended consequences. Under the EU AI Act Article 72, serious incidents must be reported to national competent authorities within 15 days; structured incident taxonomies and response protocols (detection, containment, investigation, remediation) are codified in ISO/IEC 23894:2023."@en ;
rdfs:label "AI Incident"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:ai-risk ;
rdfs:subClassOf _:r497 ;
rdfs:subClassOf _:r498 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:enables ngm:ai-governance ;
vc:enables ngm:responsible-ai ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:bias ;
vc:relatedTo ngm:eu-ai-act-regulatory-instrument ;
vc:requires ngm:accountability ;
vc:requires ngm:ai-risk-management ;
vc:slug "ai-incident" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-incident-database a skos:Concept ;
rdfs:label "AI Incident Database"@en .
ngm:ai-industry-consolidation a owl:Class ;
rdfs:comment "The process of mergers, acquisitions, and strategic partnerships within the artificial intelligence sector that reduces the number of independent market participants and concentrates capabilities, capital, and talent."@en ;
rdfs:label "AI Industry Consolidation"@en ;
rdfs:subClassOf ngm:competition-in-ai ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:competition-in-ai ;
vc:slug "ai-industry-consolidation" ;
vc:sourceDomain "economics" .
ngm:ai-inequality a owl:Class ;
rdfs:comment "The widening disparity in access to, benefits from, and power derived from artificial intelligence technologies, driven by socioeconomic privilege and resource concentration."@en ;
rdfs:label "AI Inequality"@en ;
rdfs:subClassOf ngm:ai-governance-law-and-privacy ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-governance-law-and-privacy ;
vc:relatedTo ngm:ai-safety ;
vc:slug "ai-inequality" ;
vc:sourceDomain "governance" .
ngm:ai-inference a owl:Class ;
rdfs:comment "AI Inference is the operational phase of a machine learning system in which a trained model processes new input data to generate predictions, classifications, embeddings, or generative outputs — as distinct from the training phase in which model parameters are optimised. It is the production-time workload that determines the latency, throughput, cost, and scalability characteristics experienced by end users and downstream systems. Inference encompasses the full serving stack: model loading and memory management, request batching, hardware-specific kernel execution, and output post-processing. Modern inference optimisation techniques — including quantisation, speculative decoding, continuous batching, and KV-cache management — are essential for deploying large models at commercially viable cost."@en ;
rdfs:label "AI Inference"@en ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf ngm:neural-network ;
rdfs:subClassOf _:r499 ;
rdfs:subClassOf _:r500 ;
rdfs:subClassOf _:r501 ;
rdfs:subClassOf _:r502 ;
rdfs:subClassOf _:r503 ;
rdfs:subClassOf _:r504 ;
rdfs:subClassOf _:r505 ;
rdfs:subClassOf _:r506 ;
rdfs:subClassOf _:r507 ;
vc:bridgesTo ngm:cloud-computing ;
vc:bridgesTo ngm:distributed-systems ;
vc:contrastsWith ngm:fine-tuning ;
vc:contrastsWith ngm:model-training ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:model-training ;
vc:enables ngm:autonomous-agent ;
vc:enables ngm:computer-vision ;
vc:enables ngm:edge-inference ;
vc:enables ngm:generative-ai ;
vc:enables ngm:natural-language-processing ;
vc:enables ngm:on-device-ai ;
vc:enables ngm:real-time-ai-inference ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:batch-inference ;
vc:hasPart ngm:continuous-batching ;
vc:hasPart ngm:flash-attention ;
vc:hasPart ngm:kv-cache ;
vc:hasPart ngm:prefix-caching ;
vc:hasPart ngm:speculative-decoding ;
vc:implements ngm:distributed-inference ;
vc:implements ngm:model-serving ;
vc:qualityScore "0.91"^^xsd:float ;
vc:relatedTo ngm:chain-of-thought ;
vc:relatedTo ngm:edge-computing ;
vc:relatedTo ngm:inference-compute ;
vc:relatedTo ngm:inference-hardware ;
vc:relatedTo ngm:inference-optimisation ;
vc:relatedTo ngm:knowledge-distillation ;
vc:relatedTo ngm:mlops ;
vc:relatedTo ngm:model-compression ;
vc:relatedTo ngm:model-serving ;
vc:relatedTo ngm:on-device-ai ;
vc:relatedTo ngm:retrieval-augmented-generation ;
vc:requires ngm:gpu-acceleration ;
vc:requires ngm:hardware-accelerator ;
vc:requires ngm:inference-runtime ;
vc:requires ngm:model-weights ;
vc:slug "ai-inference" ;
vc:sourceDomain "machine-learning" ;
vc:supports ngm:ai-governance ;
vc:supports ngm:mlops ;
vc:supports ngm:retrieval-augmented-generation ;
vc:uses ngm:ai-model ;
vc:uses ngm:ai-model-architecture ;
vc:uses ngm:flash-attention ;
vc:uses ngm:gpu-acceleration ;
vc:uses ngm:mixture-of-experts ;
vc:uses ngm:onnx ;
vc:uses ngm:quantisation ;
vc:uses ngm:tensor-parallelism .
ngm:ai-inference-cost-management a owl:Class ;
rdfs:comment "The practice of monitoring, optimizing, and budgeting for the computational expenses associated with running large language models and AI services in production."@en ;
rdfs:label "AI Inference Cost Management"@en ;
rdfs:subClassOf ngm:enterprise-budgeting ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-code-generation ;
vc:relatedTo ngm:cloud-computing ;
vc:relatedTo ngm:software-supply-chain ;
vc:slug "ai-inference-cost-management" ;
vc:sourceDomain "economics" .
ngm:ai-inference-costs a owl:Class ;
rdfs:comment "The financial expenditure associated with executing trained AI models on production workloads, encompassing compute, memory, and latency trade-offs."@en ;
rdfs:label "AI Inference Costs"@en ;
rdfs:subClassOf ngm:ai-inference ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-inference ;
vc:relatedTo ngm:mlops ;
vc:relatedTo ngm:model-serving ;
vc:slug "ai-inference-costs" ;
vc:sourceDomain "economics" .
ngm:ai-inference-hardware a owl:Class ;
rdfs:comment "Specialized computing chips and server architectures designed to optimize the speed and cost of running AI models."@en ;
rdfs:label "AI Inference Hardware"@en ;
rdfs:subClassOf ngm:data-storage ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-inference-infrastructure ;
vc:relatedTo ngm:nvidia-blackwell-gpus ;
vc:slug "ai-inference-hardware" ;
vc:sourceDomain "infrastructure" .
ngm:ai-inference-infrastructure a owl:Class ;
rdfs:comment "The specialized hardware, data centers, and energy systems required to run AI models at scale, distinct from training infrastructure."@en ;
rdfs:label "AI Inference Infrastructure"@en ;
rdfs:subClassOf ngm:data-storage ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-factory ;
vc:relatedTo ngm:data-center-investment ;
vc:slug "ai-inference-infrastructure" ;
vc:sourceDomain "infrastructure" .
ngm:ai-infrastructure a owl:Class ;
rdfs:comment "AI Infrastructure is the integrated ensemble of hardware, software, data systems, and operational tooling required to develop, train, deploy, monitor, and govern artificial intelligence and machine learning workloads at scale. It spans physical compute resources such as GPU and TPU clusters, networking fabrics, and storage systems through to cloud-managed AI platforms, model-serving runtimes, data pipelines, and MLOps toolchains. Unlike general-purpose computing infrastructure, AI Infrastructure is specifically optimised for tensor operations, distributed parallel training, high-throughput vector data ingestion, and low-latency inference serving. It constitutes the production backbone that determines the cost, velocity, reliability, and scalability of AI system development cycles."@en ;
rdfs:label "AI Infrastructure"@en ;
rdfs:subClassOf ngm:digital-infrastructure ;
rdfs:subClassOf _:r508 ;
rdfs:subClassOf _:r509 ;
rdfs:subClassOf _:r510 ;
rdfs:subClassOf _:r511 ;
rdfs:subClassOf _:r512 ;
rdfs:subClassOf _:r513 ;
rdfs:subClassOf _:r514 ;
rdfs:subClassOf _:r515 ;
vc:bridgesTo ngm:decentralised-ai ;
vc:bridgesTo ngm:spatial-computing ;
vc:contrastsWith ngm:general-purpose-computing ;
vc:dependsOn ngm:cloud-computing ;
vc:dependsOn ngm:data-centre ;
vc:enables ngm:federated-learning ;
vc:enables ngm:large-language-model ;
vc:enables ngm:real-time-inference ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:data-pipeline ;
vc:hasPart ngm:edge-computing ;
vc:hasPart ngm:gpu-compute ;
vc:hasPart ngm:mlops ;
vc:hasPart ngm:model-serving ;
vc:hasPart ngm:vector-database ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:cloud-infrastructure ;
vc:relatedTo ngm:empirical-experimental-design-tracking ;
vc:relatedTo ngm:model-registry ;
vc:requires ngm:distributed-storage ;
vc:requires ngm:high-performance-computing ;
vc:requires ngm:networking-fabric ;
vc:slug "ai-infrastructure" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:artificial-intelligence ;
vc:supports ngm:deep-learning ;
vc:supports ngm:machine-learning-discipline ;
vc:uses ngm:containerisation ;
vc:uses ngm:gpu-computing ;
vc:uses ngm:kubernetes .
ngm:ai-infrastructure-capital-expenditure a owl:Class ;
rdfs:comment "The large-scale financial investment by technology companies and hyperscalers in physical computing resources, such as GPUs, data centers, and networking, required to train and deploy large-scale foundation models."@en ;
rdfs:label "AI Infrastructure Capital Expenditure"@en ;
rdfs:subClassOf ngm:ai-infrastructure ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-hardware ;
vc:relatedTo ngm:foundation-model ;
vc:relatedTo ngm:gpu-compute ;
vc:slug "ai-infrastructure-capital-expenditure" ;
vc:sourceDomain "infrastructure" .
ngm:ai-infrastructure-economics a owl:Class ;
rdfs:comment "The study of the economic dynamics, cost structures, and market forces governing the production, allocation, and pricing of computational resources essential for AI development."@en ;
rdfs:label "AI Infrastructure Economics"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:reinforcement-learning ;
vc:slug "ai-infrastructure-economics" ;
vc:sourceDomain "economics" .
ngm:ai-infrastructure-investment a owl:Class ;
rdfs:comment "The large-scale capital allocation and construction of physical and digital assets, such as data centers and compute clusters, required to support the training and deployment of artificial intelligence models."@en ;
rdfs:label "AI Infrastructure Investment"@en ;
rdfs:subClassOf ngm:ai-infrastructure ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-infrastructure ;
vc:relatedTo ngm:data-pipeline ;
vc:relatedTo ngm:gpu-compute ;
vc:slug "ai-infrastructure-investment" ;
vc:sourceDomain "infrastructure" .
ngm:ai-infrastructure-planning a skos:Concept ;
rdfs:label "AI Infrastructure Planning"@en .
ngm:ai-infrastructure-regulation a owl:Class ;
rdfs:comment "Government policies and regulations governing the physical deployment of AI infrastructure, including data centers, energy use, and community impact."@en ;
rdfs:label "AI Infrastructure Regulation"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
skos:broader ngm:ai-governance-and-ethics ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-regulation ;
vc:relatedTo ngm:data-center-moratorium ;
vc:slug "ai-infrastructure-regulation" ;
vc:sourceDomain "governance" .
ngm:ai-infrastructure-strategy a owl:Class ;
rdfs:comment "The corporate and competitive planning focused on securing compute resources, data pipelines, and physical hardware to support the development and deployment of artificial intelligence models."@en ;
rdfs:label "AI Infrastructure Strategy"@en ;
rdfs:subClassOf ngm:ai-infrastructure ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-infrastructure ;
vc:relatedTo ngm:cloud-computing ;
vc:relatedTo ngm:gpu-compute ;
vc:slug "ai-infrastructure-strategy" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-insurance a skos:Concept ;
rdfs:label "AI Insurance"@en .
ngm:ai-investment a owl:Class ;
rdfs:comment "AI Investment is the allocation of capital toward artificial-intelligence research, talent, compute infrastructure, startups, and data assets in pursuit of strategic or financial returns. It spans venture funding, corporate capital expenditure on data centres and chips, sovereign wealth funds, public research grants, and hyperscaler balance-sheet commitments. The scale and concentration of this capital is a primary driver of competitive dynamics among firms and nations, with global AI corporate investment reaching $581 billion in 2025 and Q1 2026 venture activity alone surpassing that figure. Investment categories include frontier-model lab funding, compute infrastructure build-out, application-layer enterprise AI, and sovereign compute programmes. Returns are gated by access to scarce inputs — advanced semiconductor capacity, high-bandwidth memory, and specialised research talent — creating oligopolistic supply-side dynamics that shape long-run market structure."@en ;
rdfs:label "AI Investment"@en ;
rdfs:subClassOf ngm:capital-markets ;
rdfs:subClassOf ngm:competition-in-ai ;
rdfs:subClassOf ngm:economics ;
rdfs:subClassOf ngm:technology-race ;
rdfs:subClassOf _:r516 ;
rdfs:subClassOf _:r517 ;
rdfs:subClassOf _:r518 ;
rdfs:subClassOf _:r519 ;
rdfs:subClassOf _:r520 ;
rdfs:subClassOf _:r521 ;
rdfs:subClassOf _:r522 ;
rdfs:subClassOf _:r523 ;
vc:contrastsWith ngm:ai-cooperation ;
vc:contrastsWith ngm:open-source-ai ;
vc:contrastsWith ngm:public-research-grants ;
vc:dependsOn ngm:ai-regulation ;
vc:dependsOn ngm:antitrust-oversight ;
vc:dependsOn ngm:eu-ai-act-regulatory-instrument ;
vc:dependsOn ngm:geopolitics ;
vc:dependsOn ngm:regulatory-frameworks ;
vc:dependsOn ngm:semiconductor-industry ;
vc:enables ngm:ai-sovereignty ;
vc:enables ngm:economic-competitiveness ;
vc:enables ngm:enterprise-ai-adoption ;
vc:enables ngm:frontier-models ;
vc:enables ngm:innovation-ecosystems ;
vc:enables ngm:open-source-ai ;
vc:enables ngm:productivity-gains ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:corporate-capital-expenditure ;
vc:hasPart ngm:data-centre ;
vc:hasPart ngm:mega-round-financing ;
vc:hasPart ngm:public-research-grants ;
vc:hasPart ngm:sovereign-wealth-fund ;
vc:hasPart ngm:venture-capital ;
vc:implements ngm:compute-governance ;
vc:implements ngm:export-controls ;
vc:implements ngm:industrial-strategy ;
vc:implements ngm:national-ai-strategies ;
vc:qualityScore "0.88"^^xsd:float ;
vc:relatedTo ngm:ai-chips ;
vc:relatedTo ngm:competition-in-ai ;
vc:relatedTo ngm:deepseek ;
vc:relatedTo ngm:google-ai-technology-corporation-deep-mind ;
vc:relatedTo ngm:isambard-ai ;
vc:relatedTo ngm:market-concentration ;
vc:relatedTo ngm:meta-ai ;
vc:relatedTo ngm:open-source-ai ;
vc:relatedTo ngm:talent-concentration ;
vc:requires ngm:ai-chips ;
vc:requires ngm:ai-research-talent ;
vc:requires ngm:cloud-infrastructure ;
vc:requires ngm:gpu-supply-chain ;
vc:requires ngm:semiconductor-industry ;
vc:requires ngm:training-data ;
vc:slug "ai-investment" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:ai-governance ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:risk-management ;
vc:supports ngm:ai-policy ;
vc:supports ngm:ai-research-talent ;
vc:supports ngm:compute-access ;
vc:supports ngm:foundation-model ;
vc:supports ngm:uk-ai-sector ;
vc:uses ngm:generative-ai ;
vc:uses ngm:inference-optimisation ;
vc:uses ngm:large-scale-pretrained-foundation-model .
ngm:ai-ipo a owl:Class ;
rdfs:comment "The process of artificial intelligence companies transitioning to public equity markets, representing a key mechanism for capital formation and valuation in the AI sector."@en ;
rdfs:label "AI IPO"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:frontier-ai ;
vc:relatedTo ngm:generative-ai ;
vc:slug "ai-ipo" ;
vc:sourceDomain "economics" .
ngm:ai-job-creation a owl:Class ;
rdfs:comment "The net increase in employment opportunities and roles directly or indirectly generated by the adoption and expansion of artificial intelligence technologies."@en ;
rdfs:label "AI Job Creation"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:labor-market-impact ;
vc:slug "ai-job-creation" ;
vc:sourceDomain "economics" .
ngm:ai-job-displacement a owl:Class ;
rdfs:comment "The reduction or elimination of human labor roles due to the automation and efficiency gains provided by artificial intelligence systems."@en ;
rdfs:label "AI Job Displacement"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:labor-market-impact ;
vc:relatedTo ngm:social-policy ;
vc:slug "ai-job-displacement" ;
vc:sourceDomain "economics" .
ngm:ai-kill-switch-bill a owl:Class ;
rdfs:comment "US legislation requiring AI companies to maintain the technical capability to shut down models during safety incidents."@en ;
rdfs:label "AI Kill Switch Bill"@en ;
rdfs:subClassOf ngm:ai-safety-research ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-regulation ;
vc:relatedTo ngm:responsible-scaling-policy ;
vc:slug "ai-kill-switch-bill" ;
vc:sourceDomain "governance" .
ngm:ai-labor-market-impact a owl:Class ;
rdfs:comment "The structural changes in employment, workforce composition, and labor-capital dynamics resulting from the automation and augmentation of work by artificial intelligence."@en ;
rdfs:label "AI Labor Market Impact"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:autonomous-system ;
vc:relatedTo ngm:intelligent-automation ;
vc:slug "ai-labor-market-impact" ;
vc:sourceDomain "economics" .
ngm:ai-labour-displacement a skos:Concept ;
rdfs:label "AI Labour Displacement"@en .
ngm:ai-liability a owl:Class ;
rdfs:comment "AI Liability is the body of legal doctrine, statutory regime, regulatory practice and emerging case law that allocates civil responsibility for personal injury, property damage, economic loss, discrimination, privacy invasion and consequential harm caused by artificial intelligence systems—encomp..."@en ;
rdfs:label "AI Liability"@en ;
rdfs:subClassOf ngm:ai-governance ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:algorithmic-accountability ;
rdfs:subClassOf ngm:civil-liability ;
rdfs:subClassOf ngm:product-liability ;
rdfs:subClassOf ngm:tort-law ;
rdfs:subClassOf _:r524 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:contrastsWith ngm:contractual-liability ;
vc:contrastsWith ngm:criminal-liability ;
vc:contrastsWith ngm:regulatory-sanction ;
vc:contrastsWith ngm:self-regulation ;
vc:contrastsWith ngm:voluntary-code ;
vc:dependsOn ngm:causation-doctrine ;
vc:dependsOn ngm:common-law-system ;
vc:dependsOn ngm:expert-evidence ;
vc:dependsOn ngm:judicial-capacity ;
vc:dependsOn ngm:precedent ;
vc:dependsOn ngm:statutory-interpretation ;
vc:enables ngm:compensation-for-victims ;
vc:enables ngm:deterrence-of-harm ;
vc:enables ngm:insurance-pricing ;
vc:enables ngm:regulatory-enforcement ;
vc:enables ngm:risk-internalisation ;
vc:enables ngm:safety-investment ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:breach-of-duty ;
vc:hasPart ngm:causation ;
vc:hasPart ngm:conformity-assessment ;
vc:hasPart ngm:damages ;
vc:hasPart ngm:duty-of-care ;
vc:hasPart ngm:foreseeability ;
vc:hasPart ngm:post-market-monitoring ;
vc:hasPart ngm:strict-liability-standard ;
vc:implements ngm:abnormally-dangerous-activity-doctrine ;
vc:implements ngm:eu-ai-act-regulatory-instrument ;
vc:implements ngm:negligence-standard ;
vc:implements ngm:product-liability ;
vc:implements ngm:product-liability-directive ;
vc:implements ngm:strict-liability ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:algorithmic-bias ;
vc:relatedTo ngm:data-protection ;
vc:relatedTo ngm:explainable-ai ;
vc:relatedTo ngm:foundation-model ;
vc:relatedTo ngm:frontier-ai ;
vc:relatedTo ngm:large-scale-pretrained-foundation-model ;
vc:requires ngm:causal-linkage ;
vc:requires ngm:compensable-harm ;
vc:requires ngm:evidentiary-record ;
vc:requires ngm:identifiable-legal-person ;
vc:requires ngm:jurisdictional-framework ;
vc:slug "ai-liability" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:consumer-protection-act-1987 ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:ieee-7000 ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:standardizedBy ngm:product-liability-directive ;
vc:supports ngm:ai-insurance ;
vc:supports ngm:ai-safety ;
vc:supports ngm:algorithmic-auditing ;
vc:supports ngm:conformity-assessment ;
vc:supports ngm:consumer-protection ;
vc:supports ngm:market-surveillance ;
vc:uses ngm:caparo-three-stage-test ;
vc:uses ngm:daubert-standard ;
vc:uses ngm:foreseeability-test ;
vc:uses ngm:reasonable-care-standard ;
vc:uses ngm:restatement-second-of-torts-402a ;
vc:uses ngm:risk-benefit-analysis .
ngm:ai-licensing-regime a owl:Class ;
rdfs:comment "The set of legal, regulatory, and administrative frameworks that govern the distribution, access, and commercialization of artificial intelligence models and their outputs."@en ;
rdfs:label "AI Licensing Regime"@en ;
rdfs:subClassOf ngm:ai-policy ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-policy ;
vc:relatedTo ngm:ai-regulation ;
vc:relatedTo ngm:open-source-licence ;
vc:slug "ai-licensing-regime" ;
vc:sourceDomain "governance" .
ngm:ai-lifecycle a owl:Class ;
rdfs:comment "The series of distinct phases through which an artificial intelligence system progresses from initial conception to eventual decommissioning, encompassing planning, design, development, verification, deployment, operation, monitoring, maintenance, and retirement, with each phase involving specific activities, stakeholder roles, documentation requirements, and governance controls to ensure responsible and effective AI system management."@en ;
rdfs:label "AI Lifecycle"@en ;
rdfs:subClassOf ngm:ai-governance ;
rdfs:subClassOf _:r527 ;
rdfs:subClassOf _:r528 ;
rdfs:subClassOf _:r529 ;
rdfs:subClassOf _:r530 ;
rdfs:subClassOf _:r531 ;
rdfs:subClassOf _:r532 ;
rdfs:subClassOf _:r533 ;
rdfs:subClassOf _:r534 ;
rdfs:subClassOf _:r535 ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:fda-software-as-medical-device ;
vc:contrastsWith ngm:software-development-lifecycle ;
vc:dependsOn ngm:ai-impact-assessment ;
vc:dependsOn ngm:version-control ;
vc:enables ngm:ai-accountability ;
vc:enables ngm:model-performance ;
vc:enables ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:ai-deployment ;
vc:hasPart ngm:ai-development ;
vc:hasPart ngm:ai-monitoring ;
vc:hasPart ngm:model-validation ;
vc:implements ngm:mlops ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:continuous-integration ;
vc:requires ngm:data-governance ;
vc:requires ngm:human-oversight ;
vc:requires ngm:risk-management ;
vc:requires ngm:stakeholder-engagement ;
vc:slug "ai-lifecycle" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:iso-iec-23053 ;
vc:standardizedBy ngm:iso-iec-42001-2023 ;
vc:standardizedBy ngm:iso-iec-5338-2023 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:ai-governance ;
vc:supports ngm:responsible-ai ;
vc:uses ngm:ai-agent-system .
ngm:ai-lifecycle-management a owl:Class ;
rdfs:comment "AI lifecycle management is the governed oversight of an AI system across its whole existence — design, data acquisition, training, validation, deployment, operation, monitoring, retraining, and retirement — so that risk controls, documentation, and accountability travel with the system rather than stopping at release. It extends generic asset lifecycle management with AI-specific concerns: dataset provenance and drift, model versioning, performance and bias monitoring in production, incident response for model failures, and the stage-mapped risk activities that frameworks such as the NIST AI Risk Management Framework require."@en ;
rdfs:label "AI Lifecycle Management"@en ;
rdfs:subClassOf ngm:lifecycle-management ;
rdfs:subClassOf _:r525 ;
rdfs:subClassOf _:r526 ;
vc:enables ngm:responsible-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:ai-governance ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:data-lifecycle ;
vc:relatedTo ngm:nist-ai-rmf ;
vc:requires ngm:model-governance ;
vc:requires ngm:model-monitoring ;
vc:slug "ai-lifecycle-management" ;
vc:sourceDomain "governance" ;
vc:uses ngm:mlops .
ngm:ai-literacy a skos:Concept ;
rdfs:label "AI Literacy"@en .
ngm:ai-literacy-curriculum a skos:Concept ;
rdfs:label "AI Literacy Curriculum"@en .
ngm:ai-literacy-training-for-designers a owl:Class ;
rdfs:comment "Training for Design Practitioners covers structured programmes and self-directed learning pathways that equip designers—particularly in landscape, product, and spatial disciplines—with practical AI literacy, covering generative image tools, RAG-based knowledge management, client communication automation, and AI-assisted rendering workflows for immediate professional application."@en ;
rdfs:label "AI Literacy Training for Designers"@en ;
rdfs:subClassOf ngm:software-engineering ;
vc:enables ngm:knowledge-graphing ;
vc:enables ngm:sme-ai-productivity-toolkit ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:slug "ai-literacy-training-for-designers" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:generative-design-tool ;
vc:uses ngm:image-generation ;
vc:uses ngm:prompt-engineering ;
vc:uses ngm:retrieval-augmented-generation-rag .
ngm:ai-machine-learning a owl:Class ;
rdfs:comment "AI Machine Learning in the metaverse context refers to the application of artificial intelligence algorithms, neural networks, and deep learning architectures that enable intelligent virtual environments through natural language processing, computer vision, procedural content generation, and adap..."@en ;
rdfs:label "Ai Machine Learning"@en ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf _:r1524 ;
rdfs:subClassOf _:r1525 ;
rdfs:subClassOf _:r1526 ;
skos:broader ngm:ai-research-area ;
skos:broader ngm:artificial-intelligence ;
vc:bridgesTo ngm:computer-vision ;
vc:enables ngm:adaptive-npcs ;
vc:enables ngm:content-generation ;
vc:enables ngm:personalized-experiences ;
vc:enables ngm:smart-virtual-environments ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:computational-infrastructure ;
vc:requires ngm:neural-network-architecture ;
vc:requires ngm:neural-network-architectures ;
vc:requires ngm:training-data ;
vc:slug "ai-machine-learning" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-magazine a skos:Concept ;
rdfs:label "AI Magazine"@en .
ngm:ai-maintenance a skos:Concept ;
rdfs:label "AI Maintenance"@en .
ngm:ai-management-system a skos:Concept ;
rdfs:label "AI Management System"@en .
ngm:ai-mandate a owl:Class ;
rdfs:comment "Corporate policies that tie AI tool adoption and proficiency to employee career progression, promotions, or performance reviews."@en ;
rdfs:label "AI Mandate"@en ;
rdfs:subClassOf ngm:data-management ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-adoption-metrics ;
vc:relatedTo ngm:business-intelligence ;
vc:slug "ai-mandate" ;
vc:sourceDomain "economics" .
ngm:ai-market a skos:Concept ;
rdfs:label "AI Market"@en .
ngm:ai-market-dynamics a owl:Class ;
rdfs:comment "The competitive, pricing, and strategic forces shaping the AI industry, including model commoditization and provider optionality."@en ;
rdfs:label "AI Market Dynamics"@en ;
rdfs:subClassOf ngm:data-management ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-economics ;
vc:relatedTo ngm:model-market-share ;
vc:slug "ai-market-dynamics" ;
vc:sourceDomain "economics" .
ngm:ai-market-growth a owl:Class ;
rdfs:comment "The expansion of the economic value and scale of the artificial intelligence industry, driven by increased adoption, new applications, and technological advancements."@en ;
rdfs:label "AI Market Growth"@en ;
rdfs:subClassOf ngm:ai-adoption ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-adoption ;
vc:relatedTo ngm:ai-market ;
vc:relatedTo ngm:hyperscale-cloud ;
vc:slug "ai-market-growth" ;
vc:sourceDomain "economics" .
ngm:ai-market-impact a owl:Class ;
rdfs:comment "The measurable influence of artificial intelligence adoption and technological shifts on financial markets, sector valuations, and investor sentiment."@en ;
rdfs:label "AI Market Impact"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:artificial-intelligence ;
vc:slug "ai-market-impact" ;
vc:sourceDomain "economics" .
ngm:ai-mastering a skos:Concept ;
rdfs:label "AI Mastering"@en .
ngm:ai-maturity-assessment a owl:Class ;
rdfs:comment "A structured framework for evaluating an organization's readiness and capability in adopting and integrating AI technologies."@en ;
rdfs:label "AI Maturity Assessment"@en ;
rdfs:subClassOf ngm:enterprise-ai ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-governance-law-and-privacy ;
vc:relatedTo ngm:enterprise-ai ;
vc:slug "ai-maturity-assessment" ;
vc:sourceDomain "governance" .
ngm:ai-medical-devices a skos:Concept ;
rdfs:label "AI Medical Devices"@en .
ngm:ai-metadata a owl:Class ;
rdfs:comment "Descriptive information, provenance data, and contextual attributes associated with AI models, datasets, and computational artefacts. Includes model cards documenting architecture, training procedures, performance metrics, intended use, and known limitations; dataset metadata capturing collection methods, labelling procedures, and potential biases; and lineage records enabling reproducibility, regulatory compliance, and responsible deployment throughout the machine learning lifecycle."@en ;
rdfs:label "AI Metadata"@en ;
rdfs:subClassOf ngm:ai-infrastructure ;
vc:enables ngm:ai-governance ;
vc:enables ngm:data-provenance ;
vc:enables ngm:transparency-oecd ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.35"^^xsd:float ;
vc:slug "ai-metadata" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:ai-audit ;
vc:supports ngm:data-governance ;
vc:uses ngm:ai-model-card ;
vc:uses ngm:training-dataset-metadata .
ngm:ai-misuse-risk a skos:Concept ;
rdfs:label "AI Misuse Risk"@en .
ngm:ai-model a owl:Class ;
rdfs:comment "An AI Model is a computational artefact — comprising a parameterised mathematical function, its learned weights, and associated configuration — that encodes patterns extracted from training data and can be applied to new inputs to generate predictions, classifications, embeddings, or generative outputs. AI models range from simple linear regressors to billion-parameter deep neural networks and constitute the core intellectual and commercial asset of modern AI systems."@en ;
rdfs:label "AI Model"@en ;
rdfs:subClassOf ngm:ai-model-architecture ;
rdfs:subClassOf ngm:generative-model ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf _:r565 ;
rdfs:subClassOf _:r566 ;
rdfs:subClassOf _:r567 ;
rdfs:subClassOf _:r568 ;
rdfs:subClassOf _:r569 ;
rdfs:subClassOf _:r570 ;
rdfs:subClassOf _:r571 ;
skos:broader ngm:ai-model-architecture ;
vc:bridgesTo ngm:ai-governance ;
vc:bridgesTo ngm:compute-governance ;
vc:bridgesTo ngm:eu-ai-act-regulatory-instrument ;
vc:bridgesTo ngm:model-deployment ;
vc:contrastsWith ngm:expert-systems ;
vc:contrastsWith ngm:narrow-ai ;
vc:contrastsWith ngm:rule-based-systems ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:gradient-descent ;
vc:dependsOn ngm:neural-network ;
vc:enables ngm:agentic-workflow ;
vc:enables ngm:ai-agent ;
vc:enables ngm:ai-inference ;
vc:enables ngm:computer-vision ;
vc:enables ngm:generative-ai ;
vc:enables ngm:in-context-learning ;
vc:enables ngm:natural-language-processing ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:ai-model-architecture ;
vc:hasPart ngm:loss-function ;
vc:hasPart ngm:model-checkpoint ;
vc:hasPart ngm:model-weights ;
vc:implements ngm:learning-algorithm ;
vc:implements ngm:reinforcement-learning ;
vc:implements ngm:self-supervised-learning ;
vc:qualityScore "0.93"^^xsd:float ;
vc:relatedTo ngm:ai-alignment ;
vc:relatedTo ngm:ai-chips ;
vc:relatedTo ngm:ai-model-card ;
vc:relatedTo ngm:ai-model-development ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:benchmark-evaluation ;
vc:relatedTo ngm:bias-mitigation-techniques ;
vc:relatedTo ngm:emergent-capabilities ;
vc:relatedTo ngm:explainable-ai ;
vc:relatedTo ngm:foundation-model ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:mlops ;
vc:relatedTo ngm:model-evaluation ;
vc:relatedTo ngm:multimodal-ai-architecture-ai ;
vc:relatedTo ngm:open-source-ai ;
vc:relatedTo ngm:responsible-ai ;
vc:relatedTo ngm:transfer-learning ;
vc:requires ngm:compute-infrastructure ;
vc:requires ngm:model-training ;
vc:requires ngm:training-data ;
vc:slug "ai-model" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:supports ngm:fine-tuning ;
vc:supports ngm:knowledge-distillation ;
vc:supports ngm:model-quantization ;
vc:supports ngm:prompt-engineering ;
vc:supports ngm:retrieval-augmented-generation ;
vc:supports ngm:transfer-learning ;
vc:uses ngm:ai-model-architecture ;
vc:uses ngm:convolutional-neural-network ;
vc:uses ngm:deep-learning ;
vc:uses ngm:diffusion-model ;
vc:uses ngm:gradient-descent ;
vc:uses ngm:graph-neural-network ;
vc:uses ngm:mixture-of-experts ;
vc:uses ngm:neural-network ;
vc:uses ngm:rlhf ;
vc:uses ngm:training-data ;
vc:uses ngm:transformer-architecture .
ngm:ai-model-architecture a owl:Class ;
a skos:Concept ;
rdfs:comment "Taxonomy hub encompassing the structural designs, layer configurations, and computational graphs used to construct machine-learning models, including transformer architectures, convolutional networks, recurrent networks, diffusion models, and mixture-of-experts designs. Architecture choices determine model capacity, training efficiency, and deployment characteristics."@en ;
rdfs:label "AI Model Architecture"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf _:r22695 ;
rdfs:subClassOf _:r22696 ;
rdfs:subClassOf _:r22697 ;
rdfs:subClassOf _:r22698 ;
rdfs:subClassOf _:r22699 ;
rdfs:subClassOf _:r22700 ;
rdfs:subClassOf _:r22701 ;
skos:broader ngm:artificial-intelligence ;
vc:enables ngm:fine-tuning ;
vc:enables ngm:generative-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:autoencoder ;
vc:hasPart ngm:convolutional-neural-network ;
vc:hasPart ngm:diffusion-model ;
vc:hasPart ngm:encoder-decoder-architecture ;
vc:hasPart ngm:mixture-of-experts-architecture ;
vc:hasPart ngm:recurrent-neural-network ;
vc:hasPart ngm:transformer-architecture ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:attention-mechanism ;
vc:relatedTo ngm:deep-learning ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:neural-network ;
vc:slug "ai-model-architecture" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-model-attestation a skos:Concept ;
rdfs:label "AI Model Attestation"@en .
ngm:ai-model-auditing a owl:Class ;
rdfs:comment "The systematic process of evaluating, testing, and monitoring AI models to identify behavioral anomalies, biases, or unintended artifacts resulting from training methodologies."@en ;
rdfs:label "AI Model Auditing"@en ;
rdfs:subClassOf ngm:ai-safety-research ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:constitutional-ai-training-methodology ;
vc:relatedTo ngm:frontier-model-evaluation ;
vc:relatedTo ngm:interpretability ;
vc:slug "ai-model-auditing" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-model-benchmarking a owl:Class ;
rdfs:comment "The standardized evaluation of artificial intelligence models using curated datasets and metrics to measure performance, capability, and safety, serving as a primary mechanism for comparing model generations and tracking progress."@en ;
rdfs:label "AI Model Benchmarking"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:claude ;
vc:relatedTo ngm:large-language-model ;
vc:slug "ai-model-benchmarking" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-model-card a owl:Class ;
rdfs:comment "A structured documentation format that describes an AI Model's purpose, Performance Metrics, limitations, ical Considerations, and appropriate Use Case|use cases to promote Transparency and Responsible AI Deployment|responsible deployment."@en ;
rdfs:label "AI Model Card"@en ;
rdfs:subClassOf ngm:ai-documentation-framework ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:ai-risk-management ;
rdfs:subClassOf ngm:compliance-documentation ;
rdfs:subClassOf ngm:documentation-standards ;
rdfs:subClassOf _:r536 ;
rdfs:subClassOf _:r537 ;
rdfs:subClassOf _:r538 ;
rdfs:subClassOf _:r539 ;
rdfs:subClassOf _:r540 ;
rdfs:subClassOf _:r541 ;
rdfs:subClassOf _:r542 ;
rdfs:subClassOf _:r543 ;
rdfs:subClassOf _:r544 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:blockchain ;
vc:contrastsWith ngm:ai-impact-assessment ;
vc:dependsOn ngm:ai-ethics-guidelines ;
vc:dependsOn ngm:data-provenance ;
vc:dependsOn ngm:documentation-standards ;
vc:dependsOn ngm:explainability ;
vc:dependsOn ngm:industry-best-practices ;
vc:dependsOn ngm:model-testing-protocols ;
vc:dependsOn ngm:regulatory-requirements ;
vc:enables ngm:ai-accountability ;
vc:enables ngm:algorithmic-auditing ;
vc:enables ngm:informed-decision-making ;
vc:enables ngm:model-transparency ;
vc:enables ngm:procurement-due-diligence ;
vc:enables ngm:regulatory-compliance ;
vc:enables ngm:responsible-ai-deployment ;
vc:enables ngm:third-party-auditing ;
vc:enables ngm:trustworthy-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:bias-analysis ;
vc:hasPart ngm:demographic-performance-analysis ;
vc:hasPart ngm:ethical-considerations ;
vc:hasPart ngm:fairness-metrics ;
vc:hasPart ngm:limitations-section ;
vc:hasPart ngm:model-details ;
vc:hasPart ngm:performance-metrics ;
vc:hasPart ngm:safety-testing-results ;
vc:hasPart ngm:security-considerations ;
vc:hasPart ngm:training-data ;
vc:hasPart ngm:use-case-descriptions ;
vc:isPartOf ngm:ai-documentation-framework ;
vc:isPartOf ngm:ai-risk-management ;
vc:isPartOf ngm:compliance-documentation ;
vc:isPartOf ngm:model-governance-system ;
vc:qualityScore "0.93"^^xsd:float ;
vc:relatedTo ngm:blockchain-analytics ;
vc:relatedTo ngm:eu-ai-act-regulatory-instrument ;
vc:relatedTo ngm:hugging-face-model-hub ;
vc:relatedTo ngm:iso-iec-42001 ;
vc:relatedTo ngm:iso-iec-42005 ;
vc:relatedTo ngm:nist-ai-rmf ;
vc:relatedTo ngm:oecd ;
vc:relatedTo ngm:smart-contract-auditing ;
vc:requires ngm:ai-safety-evaluation ;
vc:requires ngm:demographic-performance-analysis ;
vc:requires ngm:model-evaluation-results ;
vc:requires ngm:performance-benchmarks ;
vc:requires ngm:red-teaming ;
vc:requires ngm:safety-testing-results ;
vc:requires ngm:training-dataset-metadata ;
vc:slug "ai-model-card" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:documentation-standards ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:standardizedBy ngm:oecd ;
vc:supports ngm:foundation-model-transparency-index ;
vc:supports ngm:generative-ai ;
vc:supports ngm:nist-ai-rmf ;
vc:supports ngm:open-source-ai ;
vc:uses ngm:bias-analysis ;
vc:uses ngm:demographic-performance-analysis ;
vc:uses ngm:fairness-metrics ;
vc:uses ngm:red-teaming ;
vc:uses ngm:watermarking-service .
ngm:ai-model-competition a owl:Class ;
rdfs:comment "The ongoing rivalry among technology companies to release superior large language models and AI systems, characterized by rapid iteration and performance benchmarking."@en ;
rdfs:label "AI Model Competition"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:deep-learning ;
vc:relatedTo ngm:foundation-model ;
vc:relatedTo ngm:large-language-model ;
vc:slug "ai-model-competition" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-model-development a owl:Class ;
rdfs:comment "The end-to-end engineering discipline of designing, training, evaluating, and deploying machine learning models, encompassing dataset curation, architecture selection, optimisation, and lifecycle management. It integrates software engineering, statistical modelling, and domain expertise to produce AI systems capable of performing specified tasks at scale. The discipline spans research prototyping through production deployment and ongoing maintenance."@en ;
rdfs:label "AI Model Development"@en ;
rdfs:subClassOf ngm:ai-system ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf _:r545 ;
rdfs:subClassOf _:r546 ;
rdfs:subClassOf _:r547 ;
rdfs:subClassOf _:r548 ;
rdfs:subClassOf _:r549 ;
rdfs:subClassOf _:r550 ;
rdfs:subClassOf _:r551 ;
rdfs:subClassOf _:r552 ;
rdfs:subClassOf _:r553 ;
rdfs:subClassOf _:r554 ;
vc:contrastsWith ngm:ai-inference ;
vc:contrastsWith ngm:frontier-model-training ;
vc:dependsOn ngm:benchmark-dataset ;
vc:dependsOn ngm:loss-function ;
vc:dependsOn ngm:neural-network ;
vc:dependsOn ngm:regularisation ;
vc:dependsOn ngm:transformer-architecture ;
vc:enables ngm:ai-deployment ;
vc:enables ngm:ai-inference ;
vc:enables ngm:ai-model ;
vc:enables ngm:computer-vision ;
vc:enables ngm:large-language-models ;
vc:enables ngm:natural-language-processing ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:data-pipeline ;
vc:hasPart ngm:empirical-experimental-design-tracking ;
vc:hasPart ngm:experiment-tracking ;
vc:hasPart ngm:feature-engineering ;
vc:hasPart ngm:hyperparameter-optimisation ;
vc:hasPart ngm:model-evaluation ;
vc:implements ngm:backpropagation ;
vc:implements ngm:deep-learning ;
vc:implements ngm:distributed-training ;
vc:implements ngm:gradient-descent ;
vc:qualityScore "0.92"^^xsd:float ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:ai-risk-assessment ;
vc:relatedTo ngm:data-versioning ;
vc:relatedTo ngm:foundation-model ;
vc:relatedTo ngm:mlops ;
vc:relatedTo ngm:model-deployment ;
vc:relatedTo ngm:model-weights ;
vc:requires ngm:compute-resources ;
vc:requires ngm:data-pipeline ;
vc:requires ngm:gpu-acceleration ;
vc:requires ngm:training-data ;
vc:slug "ai-model-development" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:mlops ;
vc:supports ngm:ai-model-card ;
vc:supports ngm:empirical-experimental-design-tracking ;
vc:supports ngm:mlops ;
vc:supports ngm:model-registry ;
vc:uses ngm:adversarial-training ;
vc:uses ngm:backpropagation ;
vc:uses ngm:deep-learning ;
vc:uses ngm:fine-tuning ;
vc:uses ngm:gradient-descent ;
vc:uses ngm:lo-ra-fine-tuning ;
vc:uses ngm:quantisation ;
vc:uses ngm:reinforcement-learning-from-human-feedback ;
vc:uses ngm:transfer-learning .
ngm:ai-model-inference-engine a owl:Class ;
rdfs:comment "An AI model inference engine is the software runtime that executes a trained model to produce predictions from new inputs. It manages computation graph execution, hardware acceleration and memory to run models efficiently."@en ;
rdfs:label "AI Model Inference Engine"@en ;
rdfs:subClassOf ngm:ai-inference ;
rdfs:subClassOf ngm:ai-infrastructure ;
rdfs:subClassOf ngm:deep-learning-framework ;
rdfs:subClassOf ngm:inference-serving ;
rdfs:subClassOf _:r555 ;
rdfs:subClassOf _:r556 ;
rdfs:subClassOf _:r557 ;
rdfs:subClassOf _:r558 ;
rdfs:subClassOf _:r559 ;
rdfs:subClassOf _:r560 ;
rdfs:subClassOf _:r561 ;
rdfs:subClassOf _:r562 ;
rdfs:subClassOf _:r563 ;
rdfs:subClassOf _:r564 ;
vc:contrastsWith ngm:ai-model-development ;
vc:contrastsWith ngm:fine-tuning ;
vc:contrastsWith ngm:model-training ;
vc:dependsOn ngm:ai-model ;
vc:dependsOn ngm:ai-model-development ;
vc:dependsOn ngm:model-training ;
vc:dependsOn ngm:neural-network ;
vc:dependsOn ngm:transformer-architecture ;
vc:enables ngm:ai-inference ;
vc:enables ngm:autonomous-agent ;
vc:enables ngm:computer-vision ;
vc:enables ngm:generative-ai ;
vc:enables ngm:inference-serving ;
vc:enables ngm:model-serving ;
vc:enables ngm:natural-language-processing ;
vc:enables ngm:on-device-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:continuous-batching ;
vc:hasPart ngm:flash-attention ;
vc:hasPart ngm:kv-cache ;
vc:hasPart ngm:operator-fusion ;
vc:hasPart ngm:prefix-caching ;
vc:hasPart ngm:speculative-decoding ;
vc:implements ngm:continuous-batching ;
vc:implements ngm:flash-attention ;
vc:implements ngm:quantisation ;
vc:implements ngm:speculative-decoding ;
vc:implements ngm:tensor-parallelism ;
vc:qualityScore "0.92"^^xsd:float ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:benchmark-dataset ;
vc:relatedTo ngm:cloud-computing ;
vc:relatedTo ngm:latency ;
vc:relatedTo ngm:model-deployment ;
vc:relatedTo ngm:model-evaluation ;
vc:requires ngm:gpu ;
vc:requires ngm:gpu-acceleration ;
vc:requires ngm:hardware-accelerator ;
vc:requires ngm:model-optimization ;
vc:requires ngm:model-weights ;
vc:slug "ai-model-inference-engine" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:mlops ;
vc:standardizedBy ngm:onnx ;
vc:supports ngm:edge-computing ;
vc:supports ngm:large-language-models ;
vc:supports ngm:mlops ;
vc:supports ngm:retrieval-augmented-generation ;
vc:uses ngm:deep-learning-framework ;
vc:uses ngm:distributed-systems ;
vc:uses ngm:flash-attention ;
vc:uses ngm:gpu-acceleration ;
vc:uses ngm:onnx ;
vc:uses ngm:quantisation ;
vc:uses ngm:tensor-parallelism .
ngm:ai-model-interoperability a skos:Concept ;
rdfs:label "AI Model Interoperability"@en .
ngm:ai-model-portfolio a owl:Class ;
rdfs:comment "A strategy where users or organizations deploy multiple distinct AI models simultaneously to leverage their specific strengths, rather than relying on a single general-purpose model."@en ;
rdfs:label "AI Model Portfolio"@en ;
rdfs:subClassOf ngm:model ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:model-architecture ;
vc:relatedTo ngm:model-capacity ;
vc:slug "ai-model-portfolio" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-model-race a owl:Class ;
rdfs:comment "The competitive dynamic among AI developers and providers, characterized by multiple parallel races for superiority in capability, speed, cost, distribution, and other strategic dimensions."@en ;
rdfs:label "AI Model Race"@en ;
rdfs:subClassOf ngm:ai-strategy ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-model ;
vc:relatedTo ngm:inference-speed ;
vc:relatedTo ngm:strategic-positioning ;
vc:slug "ai-model-race" ;
vc:sourceDomain "economics" .
ngm:ai-model-release-cadence a owl:Class ;
rdfs:comment "The frequency and pattern of AI model releases, influenced by safety reviews, competitive dynamics, and governance frameworks."@en ;
rdfs:label "AI Model Release Cadence"@en ;
rdfs:subClassOf ngm:model ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-safety-preparedness-framework ;
vc:relatedTo ngm:competitive-strategy ;
vc:slug "ai-model-release-cadence" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-model-risk a skos:Concept ;
rdfs:label "AI Model Risk"@en .
ngm:ai-model-scaling a skos:Concept ;
rdfs:label "AI Model Scaling"@en .
ngm:ai-model-training-on-sensitive-data a skos:Concept ;
rdfs:label "AI Model Training On Sensitive Data"@en .
ngm:ai-model-transparency a skos:Concept ;
rdfs:label "AI Model Transparency"@en .
ngm:ai-moderation a skos:Concept ;
rdfs:label "AI Moderation"@en .
ngm:ai-monitoring a owl:Class ;
rdfs:comment "The systematic and ongoing observation, measurement, and analysis of an artificial intelligence system's behaviour, performance, inputs, outputs, and impacts during operational use, employing automated tools and human oversight to detect degradation, anomalies, bias, safety issues, or unintended consequences, enabling timely intervention, maintenance, and continuous improvement whilst ensuring accountability and compliance with governance requirements."@en ;
rdfs:label "AI Monitoring"@en ;
rdfs:subClassOf ngm:ai-lifecycle ;
rdfs:subClassOf _:r572 ;
rdfs:subClassOf _:r573 ;
rdfs:subClassOf _:r574 ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:data-drift ;
vc:contrastsWith ngm:ai-audit ;
vc:contrastsWith ngm:static-testing ;
vc:dependsOn ngm:ai-deployment ;
vc:dependsOn ngm:model-performance ;
vc:enables ngm:ai-maintenance ;
vc:enables ngm:continuous-improvement ;
vc:enables ngm:human-oversight ;
vc:enables ngm:incident-response ;
vc:enables ngm:model-updating ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:anomaly-detection ;
vc:hasPart ngm:data-drift-detection ;
vc:hasPart ngm:fairness-monitoring ;
vc:hasPart ngm:performance-monitoring ;
vc:isPartOf ngm:ai-governance ;
vc:isPartOf ngm:ai-lifecycle ;
vc:qualityScore "0.65"^^xsd:float ;
vc:relatedTo ngm:ai-operator ;
vc:relatedTo ngm:explainability ;
vc:relatedTo ngm:model-retraining ;
vc:requires ngm:alert-thresholds ;
vc:requires ngm:baseline-metrics ;
vc:requires ngm:data-logging ;
vc:requires ngm:monitoring-infrastructure ;
vc:slug "ai-monitoring" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:iso-iec-23894-2023 ;
vc:standardizedBy ngm:iso-iec-42001-2023 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:ai-audit ;
vc:supports ngm:bias ;
vc:supports ngm:fairness ;
vc:supports ngm:risk-management .
ngm:ai-music-production a skos:Concept ;
rdfs:label "AI Music Production"@en .
ngm:ai-now-institute a skos:Concept ;
rdfs:label "AI Now Institute"@en .
ngm:ai-office a owl:Class ;
rdfs:comment "European Commission body established under AI Act Articles 64–68 as the primary centre of AI expertise for a unified European AI governance system, holding executive authority for supervising general-purpose AI model providers, coordinating cross-border market surveillance, imposing corrective measures and fines, facilitating regulatory sandboxes, and representing the EU in international AI governance forums."@en ;
rdfs:label "AI Office"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
skos:broader ngm:ai-governance-and-ethics ;
vc:enables ngm:ai-governance ;
vc:enables ngm:ai-governance-framework ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:ai-risk-management ;
vc:relatedTo ngm:general-purpose-ai-model ;
vc:slug "ai-office" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:ai-board ;
vc:supports ngm:eu-ai-act-regulatory-instrument .
ngm:ai-operator a owl:Class ;
rdfs:comment "An individual or organisational entity responsible for the operational management, monitoring, and control of an artificial intelligence system during its deployment and use, including activities such as configuring system parameters, overseeing system performance, responding to incidents, coordi..."@en ;
rdfs:label "AI Operator"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf _:r575 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:ai-deployment ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:competence-development ;
vc:requires ngm:ongoing-support ;
vc:requires ngm:training ;
vc:slug "ai-operator" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-orchestration a skos:Concept ;
rdfs:label "AI Orchestration"@en .
ngm:ai-organizational-structure a owl:Class ;
rdfs:comment "The internal hierarchy, reporting lines, and departmental arrangements within an organization that govern the development, deployment, and oversight of artificial intelligence systems."@en ;
rdfs:label "AI Organizational Structure"@en ;
rdfs:subClassOf ngm:ai-governance-framework ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:ai-governance-framework ;
vc:relatedTo ngm:ai-policy ;
vc:slug "ai-organizational-structure" ;
vc:sourceDomain "governance" .
ngm:ai-origin-declaration a owl:Class ;
rdfs:comment "AI Origin Declaration refers to technical standards and regulatory requirements for disclosing when digital content has been generated or substantially modified by artificial intelligence, encompassing watermarking, metadata embedding, and provenance tracking systems that enable verification of c..."@en ;
rdfs:label "Ai Origin Declaration"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:content-authenticity ;
rdfs:subClassOf _:r1527 ;
rdfs:subClassOf _:r1528 ;
rdfs:subClassOf _:r1529 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:content-authenticity ;
vc:enables ngm:content-verification ;
vc:enables ngm:deepfake-detection ;
vc:enables ngm:trust-infrastructure ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:cryptographic-signing ;
vc:requires ngm:digital-watermarking ;
vc:requires ngm:metadata-standards ;
vc:slug "ai-origin-declaration" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-pipeline a skos:Concept ;
rdfs:label "AI Pipeline"@en .
ngm:ai-policy a owl:Class ;
rdfs:comment "AI Policy is the ensemble of government strategies, regulatory instruments, voluntary guidelines, and international agreements through which states and intergovernmental bodies shape the development, deployment, and societal impact of artificial intelligence systems. Policy instruments span public research funding, national AI strategies, procurement standards for government AI use, export controls on frontier hardware and models, and binding requirements for transparency, accountability, and fundamental-rights compliance in high-stakes applications. Effective AI policy must balance national competitiveness, safety assurance, equitable access, and interoperability with allied jurisdictions, making it an inherently multi-stakeholder and multi-domain governance challenge."@en ;
rdfs:label "AI Policy"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:technology-policy ;
rdfs:subClassOf _:r576 ;
rdfs:subClassOf _:r577 ;
rdfs:subClassOf _:r578 ;
rdfs:subClassOf _:r579 ;
rdfs:subClassOf _:r580 ;
rdfs:subClassOf _:r581 ;
rdfs:subClassOf _:r582 ;
rdfs:subClassOf _:r583 ;
rdfs:subClassOf _:r584 ;
rdfs:subClassOf _:r585 ;
rdfs:subClassOf _:r586 ;
rdfs:subClassOf _:r587 ;
rdfs:subClassOf _:r588 ;
rdfs:subClassOf _:r589 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:cybersecurity-policy ;
vc:bridgesTo ngm:export-controls ;
vc:bridgesTo ngm:human-rights-law ;
vc:bridgesTo ngm:national-security ;
vc:bridgesTo ngm:supply-chain-security ;
vc:contrastsWith ngm:self-regulation ;
vc:dependsOn ngm:ai-governance ;
vc:dependsOn ngm:data-governance ;
vc:dependsOn ngm:regulatory-compliance ;
vc:enables ngm:ai-audit ;
vc:enables ngm:ai-governance-framework ;
vc:enables ngm:algorithmic-accountability ;
vc:enables ngm:compute-governance ;
vc:enables ngm:conformity-assessment ;
vc:enables ngm:responsible-ai ;
vc:enables ngm:trustworthy-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ai-audit ;
vc:hasPart ngm:ai-governance-framework ;
vc:hasPart ngm:conformity-assessment ;
vc:hasPart ngm:impact-assessment ;
vc:hasPart ngm:risk-assessment ;
vc:hasPart ngm:stakeholder-consultation ;
vc:implements ngm:eu-ai-act-regulatory-instrument ;
vc:implements ngm:iso-iec-42001 ;
vc:implements ngm:nist-ai-rmf ;
vc:implements ngm:oecd-ai-principles ;
vc:qualityScore "0.93"^^xsd:float ;
vc:relatedTo ngm:ai-chips ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:ai-model ;
vc:relatedTo ngm:ai-regulation ;
vc:relatedTo ngm:ai-research ;
vc:relatedTo ngm:competition-policy ;
vc:relatedTo ngm:data-governance ;
vc:relatedTo ngm:foundation-model ;
vc:relatedTo ngm:gdpr ;
vc:relatedTo ngm:generative-ai ;
vc:relatedTo ngm:intellectual-property-rights-framework ;
vc:relatedTo ngm:intellectual-property-rights-framework-law ;
vc:relatedTo ngm:technology-policy ;
vc:requires ngm:ai-ethics ;
vc:requires ngm:algorithmic-accountability ;
vc:requires ngm:human-oversight ;
vc:requires ngm:impact-assessment ;
vc:requires ngm:risk-assessment ;
vc:requires ngm:risk-management ;
vc:requires ngm:stakeholder-consultation ;
vc:requires ngm:transparency ;
vc:slug "ai-policy" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:standardizedBy ngm:oecd-ai-principles ;
vc:supports ngm:ai-alignment ;
vc:supports ngm:ai-governance ;
vc:supports ngm:ai-safety ;
vc:supports ngm:digital-sovereignty ;
vc:supports ngm:responsible-ai ;
vc:supports ngm:trustworthy-ai ;
vc:uses ngm:ai-model-card ;
vc:uses ngm:bias-mitigation-techniques ;
vc:uses ngm:explainable-ai ;
vc:uses ngm:red-teaming .
ngm:ai-policy-discourse a owl:Class ;
rdfs:comment "The evolving political and public debate around AI regulation, ownership, and distribution, characterized by cross-ideological alignments."@en ;
rdfs:label "AI Policy Discourse"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
skos:broader ngm:ai-governance-and-ethics ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-as-public-good ;
vc:relatedTo ngm:ai-regulation ;
vc:slug "ai-policy-discourse" ;
vc:sourceDomain "governance" .
ngm:ai-portfolio-agent a owl:Class ;
rdfs:comment "An interactive AI agent that represents a professional's skills and history, enabling dynamic querying of their capabilities."@en ;
rdfs:label "AI Portfolio Agent"@en ;
rdfs:subClassOf ngm:agents ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:agents ;
vc:relatedTo ngm:enterprise-ai ;
vc:slug "ai-portfolio-agent" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-prediction a skos:Concept ;
rdfs:label "AI Prediction"@en .
ngm:ai-pricing-models a owl:Class ;
rdfs:comment "The various strategies used by AI providers to charge for their services, including seat-based, usage-based, and token-based pricing."@en ;
rdfs:label "AI Pricing Models"@en ;
rdfs:subClassOf ngm:data-management ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-economics ;
vc:relatedTo ngm:usage-based-consumption ;
vc:slug "ai-pricing-models" ;
vc:sourceDomain "economics" .
ngm:ai-principles a skos:Concept ;
rdfs:label "AI Principles"@en .
ngm:ai-privacy a owl:Class ;
rdfs:comment "The set of principles, practices, and user attitudes regarding the collection, use, and protection of personal data in AI systems, particularly concerning continuous monitoring and ambient data capture."@en ;
rdfs:label "AI Privacy"@en ;
rdfs:subClassOf ngm:ai-governance ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:ambient-observation ;
vc:relatedTo ngm:user-acceptance ;
vc:slug "ai-privacy" ;
vc:sourceDomain "governance" .
ngm:ai-processing a skos:Concept ;
rdfs:label "AI Processing"@en .
ngm:ai-processing-service a skos:Concept ;
rdfs:label "AI Processing Service"@en .
ngm:ai-procurement a skos:Concept ;
rdfs:label "AI Procurement"@en .
ngm:ai-product-and-risk-framework a owl:Class ;
rdfs:comment "A framework mapping the scientific method onto lean product development, guiding AI product decisions through vision setting, market analysis, and strategic planning. It addresses SWOT evaluation, moat assessment, and risk mitigation for AI products—particularly the legal, privacy, and safety risks introduced by generative AI and the EU regulatory landscape."@en ;
rdfs:label "AI Product and Risk Framework"@en ;
rdfs:subClassOf ngm:software-engineering ;
rdfs:subClassOf _:r590 ;
rdfs:subClassOf _:r591 ;
vc:contrastsWith ngm:ai-risk ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:ai-governance-law-and-privacy ;
vc:relatedTo ngm:ai-risk-management ;
vc:requires ngm:product-design ;
vc:requires ngm:safety-and-alignment ;
vc:slug "ai-product-and-risk-framework" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:ai-governance .
ngm:ai-product-safety a skos:Concept ;
rdfs:label "AI Product Safety"@en .
ngm:ai-product-strategy a owl:Class ;
rdfs:comment "The strategic planning and positioning of AI-powered products and services, including interface design, target user segmentation, and competitive differentiation in the market."@en ;
rdfs:label "AI Product Strategy"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:claude ;
vc:relatedTo ngm:frontier-ai ;
vc:slug "ai-product-strategy" ;
vc:sourceDomain "economics" .
ngm:ai-productivity-debate a owl:Class ;
rdfs:comment "The ongoing economic and academic discussion regarding the magnitude, timing, and causal mechanisms of productivity gains attributed to artificial intelligence adoption."@en ;
rdfs:label "AI Productivity Debate"@en ;
rdfs:subClassOf ngm:digital-economy ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:digital-economy ;
vc:relatedTo ngm:enterprise-ai-adoption ;
vc:slug "ai-productivity-debate" ;
vc:sourceDomain "economics" .
ngm:ai-productivity-gains a owl:Class ;
rdfs:comment "The measurable increase in output efficiency, task completion speed, or quality of work resulting from the integration of artificial intelligence tools into human workflows."@en ;
rdfs:label "AI Productivity Gains"@en ;
rdfs:subClassOf ngm:economics ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-adoption ;
vc:relatedTo ngm:decision-support ;
vc:relatedTo ngm:intelligent-automation ;
vc:slug "ai-productivity-gains" ;
vc:sourceDomain "economics" .
ngm:ai-productivity-impact a owl:Class ;
rdfs:comment "The measurable effects of AI adoption on organizational output, work intensity, and economic growth."@en ;
rdfs:label "AI Productivity Impact"@en ;
rdfs:subClassOf ngm:data-management ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-economics ;
vc:relatedTo ngm:business-intelligence ;
vc:slug "ai-productivity-impact" ;
vc:sourceDomain "economics" .
ngm:ai-productivity-paradox a skos:Concept ;
rdfs:label "AI Productivity Paradox"@en .
ngm:ai-protein-design a skos:Concept ;
rdfs:label "AI Protein Design"@en .
ngm:ai-provider a owl:Class ;
rdfs:comment "An individual, organisation, or legal entity that develops, produces, or supplies an AI system, assuming primary accountability for design decisions, training processes, capabilities, documentation, and regulatory compliance. Under the EU AI Act a provider places a system on the market under their own name, substantially modifies an existing system, or makes it available for use, thereby triggering obligations including conformity assessment, technical documentation, quality management, human oversight design, and post-market monitoring."@en ;
rdfs:label "AI Provider"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf _:r592 ;
rdfs:subClassOf _:r593 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:ai-governance-framework ;
vc:implements ngm:eu-ai-act-regulatory-instrument ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:accountability ;
vc:relatedTo ngm:ai-operator ;
vc:relatedTo ngm:ai-user ;
vc:relatedTo ngm:risk-management ;
vc:requires ngm:ai-impact-assessment ;
vc:requires ngm:ai-lifecycle ;
vc:slug "ai-provider" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-public-opinion a owl:Class ;
rdfs:comment "The aggregate attitudes, perceptions, and sentiment of the general public regarding the development, deployment, and societal impact of artificial intelligence systems."@en ;
rdfs:label "AI Public Opinion"@en ;
rdfs:subClassOf ngm:ai-policy ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:ai-policy ;
vc:slug "ai-public-opinion" ;
vc:sourceDomain "governance" .
ngm:ai-regulation a owl:Class ;
rdfs:comment "AI regulation encompasses binding laws, technical standards, and administrative rules imposed by national or supranational bodies to govern the entire lifecycle of artificial intelligence systems — from design and training through deployment and monitoring. Regulatory instruments range from risk-based frameworks such as the EU AI Act, which imposes tiered obligations proportional to application risk, to sector-specific rules in finance, healthcare, and critical infrastructure. Regulation aims to protect fundamental rights, ensure accountability, and promote systemic safety while preserving innovation capacity. Implementation translates abstract policy obligations into concrete engineering requirements including conformity assessments, audit trails, data governance documentation, and post-market surveillance."@en ;
rdfs:label "AI Regulation"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf _:r594 ;
rdfs:subClassOf _:r595 ;
rdfs:subClassOf _:r596 ;
rdfs:subClassOf _:r597 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:cybersecurity-law ;
vc:bridgesTo ngm:financial-regulation ;
vc:bridgesTo ngm:product-liability ;
vc:contrastsWith ngm:ai-self-regulation ;
vc:contrastsWith ngm:voluntary-ai-commitments ;
vc:enables ngm:ai-transparency-framework ;
vc:enables ngm:algorithmic-accountability ;
vc:enables ngm:public-trust-in-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:ai-policy ;
vc:implements ngm:risk-based-regulation ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:algorithmic-bias ;
vc:relatedTo ngm:explainable-ai ;
vc:relatedTo ngm:gdpr ;
vc:requires ngm:conformity-assessment ;
vc:requires ngm:data-governance ;
vc:requires ngm:regulatory-compliance ;
vc:requires ngm:risk-assessment ;
vc:slug "ai-regulation" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:standardizedBy ngm:oecd-ai-principles ;
vc:supports ngm:ai-governance-framework ;
vc:supports ngm:ai-safety ;
vc:supports ngm:digital-rights ;
vc:supports ngm:responsible-ai ;
vc:uses ngm:audit-and-certification ;
vc:uses ngm:impact-assessment ;
vc:uses ngm:regulatory-sandbox .
ngm:ai-regulatory-flexibility a owl:Class ;
rdfs:comment "The degree of discretion granted to regulators in enforcing AI safety and compliance standards, balancing innovation with risk mitigation."@en ;
rdfs:label "AI Regulatory Flexibility"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
skos:broader ngm:ai-governance-and-ethics ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-regulation ;
vc:relatedTo ngm:policy-uncertainty ;
vc:slug "ai-regulatory-flexibility" ;
vc:sourceDomain "governance" .
ngm:ai-regulatory-framework a owl:Class ;
rdfs:comment "The set of laws, policies, and governmental guidelines designed to govern the development, deployment, and impact of artificial intelligence systems."@en ;
rdfs:label "AI Regulatory Framework"@en ;
rdfs:subClassOf ngm:data-governance ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-policy ;
vc:relatedTo ngm:data-governance ;
vc:slug "ai-regulatory-framework" ;
vc:sourceDomain "governance" .
ngm:ai-regulatory-preemption a owl:Class ;
rdfs:comment "The legal and political strategy of establishing a unified federal regulatory framework for artificial intelligence to supersede or limit the authority of individual states to enact their own AI laws."@en ;
rdfs:label "AI Regulatory Preemption"@en ;
rdfs:subClassOf ngm:regulatory-framework ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:institutional-framework ;
vc:relatedTo ngm:regulatory-framework ;
vc:slug "ai-regulatory-preemption" ;
vc:sourceDomain "governance" .
ngm:ai-regulatory-sandbox a skos:Concept ;
rdfs:label "AI Regulatory Sandbox"@en .
ngm:ai-rejection a skos:Concept ;
rdfs:label "AI Rejection"@en .
ngm:ai-release-cadence a owl:Class ;
rdfs:comment "The frequency and timing at which artificial intelligence models and capabilities are made available to the public or specific user groups."@en ;
rdfs:label "AI Release Cadence"@en ;
rdfs:subClassOf ngm:ai-policy ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-policy ;
vc:relatedTo ngm:model-training ;
vc:slug "ai-release-cadence" ;
vc:sourceDomain "governance" .
ngm:ai-replacement-narrative a skos:Concept ;
rdfs:label "AI Replacement Narrative"@en .
ngm:ai-research a owl:Class ;
rdfs:comment "AI research is the systematic scientific investigation of methods for creating and understanding machine intelligence, spanning theoretical foundations, algorithm and architecture development, empirical benchmarking, and the study of capabilities, limitations, safety, and societal impact. It is conducted across universities, corporate laboratories, and independent institutes, and disseminated through peer-reviewed venues such as NeurIPS, ICML, and AAAI, as well as preprint servers and open-source releases."@en ;
rdfs:label "AI Research"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:ai-ecosystem ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:artificial-intelligence-research ;
vc:slug "ai-research" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:deep-learning ;
vc:uses ngm:machine-learning-discipline .
ngm:ai-research-area a owl:Class ;
a skos:Concept ;
rdfs:comment "Taxonomy hub classifying the principal sub-disciplines and research programmes within artificial intelligence, including machine learning, natural language processing, computer vision, and AI safety. Each constituent area represents an active community with distinct methodologies, benchmarks, and applications that collectively advance the broader AI field."@en ;
rdfs:label "AI Research Area"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf _:r22702 ;
rdfs:subClassOf _:r22703 ;
rdfs:subClassOf _:r22704 ;
rdfs:subClassOf _:r22705 ;
rdfs:subClassOf _:r22706 ;
rdfs:subClassOf _:r22707 ;
rdfs:subClassOf _:r22708 ;
rdfs:subClassOf _:r22709 ;
rdfs:subClassOf _:r22710 ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ai-alignment ;
vc:hasPart ngm:ai-safety ;
vc:hasPart ngm:computer-vision ;
vc:hasPart ngm:deep-learning ;
vc:hasPart ngm:generative-ai ;
vc:hasPart ngm:knowledge-graph-construction ;
vc:hasPart ngm:large-language-models ;
vc:hasPart ngm:natural-language-processing ;
vc:hasPart ngm:transfer-learning ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:ai-technique ;
vc:relatedTo ngm:responsible-ai ;
vc:slug "ai-research-area" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-research-assistant a skos:Concept ;
rdfs:label "AI Research Assistant"@en .
ngm:ai-research-cluster a skos:Concept ;
rdfs:label "AI Research Cluster"@en .
ngm:ai-research-community a skos:Concept ;
rdfs:label "AI Research Community"@en .
ngm:ai-research-laboratory a skos:Concept ;
rdfs:label "AI Research Laboratory"@en .
ngm:ai-research-organisation a skos:Concept ;
rdfs:label "AI Research Organisation"@en .
ngm:ai-research-talent a owl:Class ;
rdfs:comment "AI research talent refers to the pool of specialised researchers and engineers capable of advancing the state of the art in artificial intelligence, spanning fundamental research, model architecture design and applied systems engineering. Its scarcity is a key constraint on organisational AI capability, shaping investment decisions and competitive dynamics between labs and nations. Demand for this talent has driven sharp compensation growth and intense competition across the industry."@en ;
rdfs:label "AI Research Talent"@en ;
rdfs:subClassOf ngm:ai-talent ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:slug "ai-research-talent" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-return-on-investment a owl:Class ;
rdfs:comment "The financial and operational benefits realized from AI investments, often measured against costs and compared to other capital expenditures."@en ;
rdfs:label "AI Return on Investment"@en ;
rdfs:subClassOf ngm:data-management ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-economics ;
vc:relatedTo ngm:business-intelligence ;
vc:slug "ai-return-on-investment" ;
vc:sourceDomain "economics" .
ngm:ai-risk a owl:Class ;
rdfs:comment "The potential for AI systems to cause adverse effects on individuals, groups, organizations, communities, or society, arising from technical failures, security vulnerabilities, biased outcomes, privacy violations, or unintended consequences of system design, deployment, or operation. AI risks span from immediate operational failures to long-term catastrophic scenarios requiring proactive identification, assessment, and mitigation strategies."@en ;
rdfs:label "AI Risk"@en ;
rdfs:subClassOf ngm:risk-management ;
rdfs:subClassOf _:r614 ;
rdfs:subClassOf _:r615 ;
rdfs:subClassOf _:r616 ;
rdfs:subClassOf _:r617 ;
rdfs:subClassOf _:r618 ;
rdfs:subClassOf _:r619 ;
vc:bridgesTo ngm:cybersecurity ;
vc:bridgesTo ngm:smart-contract ;
vc:contrastsWith ngm:ai-safety ;
vc:dependsOn ngm:high-risk-ai-system ;
vc:dependsOn ngm:large-language-models ;
vc:enables ngm:ai-incident ;
vc:enables ngm:ai-risk-assessment ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ai-safety ;
vc:hasPart ngm:ai-security ;
vc:hasPart ngm:algorithmic-bias ;
vc:hasPart ngm:risk ;
vc:implements ngm:iso-iec-23894 ;
vc:implements ngm:nist-ai-rmf ;
vc:isPartOf ngm:ai-governance-and-ethics ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:ai-alignment ;
vc:relatedTo ngm:ai-regulation ;
vc:relatedTo ngm:responsible-ai ;
vc:requires ngm:ai-risk-management ;
vc:requires ngm:human-oversight ;
vc:slug "ai-risk" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:gdpr ;
vc:supports ngm:ai-ethics ;
vc:supports ngm:ai-trustworthiness ;
vc:uses ngm:explainable-ai ;
vc:uses ngm:red-teaming .
ngm:ai-risk-assessment a owl:Class ;
rdfs:comment "A structured methodology for identifying, analysing, and evaluating the potential harms, failure modes, and adverse societal impacts arising from the development and deployment of artificial intelligence systems. It applies established risk management frameworks to the distinctive properties of AI—opacity, emergent behaviour, data dependency, and scalability—to produce actionable risk registers and mitigation plans. The process informs governance decisions and regulatory compliance across the full AI system lifecycle."@en ;
rdfs:label "AI Risk Assessment"@en ;
rdfs:subClassOf ngm:risk-assessment ;
rdfs:subClassOf _:r598 ;
rdfs:subClassOf _:r599 ;
vc:bridgesTo ngm:cybersecurity-risk-assessment ;
vc:bridgesTo ngm:enterprise-risk-management ;
vc:enables ngm:ai-governance-framework ;
vc:enables ngm:ai-risk-management ;
vc:enables ngm:regulatory-compliance ;
vc:enables ngm:responsible-ai ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:failure-mode-analysis ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:ai-impact-assessment ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:algorithmic-bias ;
vc:requires ngm:ai-system ;
vc:requires ngm:model-documentation ;
vc:slug "ai-risk-assessment" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:uses ngm:adversarial-testing ;
vc:uses ngm:ai-model-card ;
vc:uses ngm:ai-risk-register ;
vc:uses ngm:red-teaming ;
vc:uses ngm:threat-modelling .
ngm:ai-risk-classification a skos:Concept ;
rdfs:label "AI Risk Classification"@en .
ngm:ai-risk-management a owl:Class ;
rdfs:comment "AI Risk Management is the systematic process of identifying, assessing, mitigating, and monitoring risks associated with artificial intelligence systems throughout their lifecycle, integrating AI-specific considerations into broader enterprise risk management frameworks. It encompasses governance structures, assessment methodologies, control mechanisms, and continuous oversight to ensure AI systems operate safely, ethically, and in compliance with applicable regulations."@en ;
rdfs:label "AI Risk Management"@en ;
rdfs:subClassOf ngm:risk-management ;
rdfs:subClassOf _:r600 ;
rdfs:subClassOf _:r601 ;
rdfs:subClassOf _:r602 ;
rdfs:subClassOf _:r603 ;
rdfs:subClassOf _:r604 ;
rdfs:subClassOf _:r605 ;
vc:bridgesTo ngm:cybersecurity-risk-management ;
vc:bridgesTo ngm:smart-contract ;
vc:dependsOn ngm:ai-transparency-framework ;
vc:dependsOn ngm:threat-modelling ;
vc:enables ngm:regulatory-compliance ;
vc:enables ngm:trustworthy-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ai-impact-assessment ;
vc:hasPart ngm:continuous-monitoring ;
vc:hasPart ngm:incident-response ;
vc:implements ngm:eu-ai-act-regulatory-instrument ;
vc:implements ngm:nist-ai-rmf ;
vc:isPartOf ngm:ai-governance-and-ethics ;
vc:isPartOf ngm:enterprise-risk-management ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:bias-detection-methods ;
vc:relatedTo ngm:model-governance ;
vc:requires ngm:audit-trail ;
vc:requires ngm:data-governance ;
vc:requires ngm:explainability ;
vc:slug "ai-risk-management" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:iso-42001 ;
vc:supports ngm:ai-safety ;
vc:supports ngm:responsible-ai ;
vc:uses ngm:algorithmic-auditing ;
vc:uses ngm:red-teaming .
ngm:ai-risk-register a owl:Class ;
rdfs:comment "An AI Risk Register is a structured artefact that systematically documents, tracks, and manages identified risks associated with AI systems throughout their lifecycle. Each entry records a risk identifier, description, affected systems and stakeholders, likelihood and consequence ratings, overall risk level, assigned owner, current mitigation controls, residual risk, and review history. The register supports risk-based governance by enabling prioritisation of mitigation efforts, regulatory compliance demonstration, and continuous monitoring across technical, ethical, legal, operational, security, and societal risk categories."@en ;
rdfs:label "AI Risk Register"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:ai-risk-management ;
rdfs:subClassOf _:r606 ;
rdfs:subClassOf _:r607 ;
rdfs:subClassOf _:r608 ;
rdfs:subClassOf _:r609 ;
rdfs:subClassOf _:r610 ;
rdfs:subClassOf _:r611 ;
rdfs:subClassOf _:r612 ;
rdfs:subClassOf _:r613 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:dependsOn ngm:ai-impact-assessment ;
vc:dependsOn ngm:incident-response ;
vc:enables ngm:ai-safety ;
vc:enables ngm:compliance-monitoring ;
vc:enables ngm:responsible-ai ;
vc:enables ngm:transparency ;
vc:enables ngm:trustworthy-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:audit-trail ;
vc:hasPart ngm:impact-assessment ;
vc:hasPart ngm:risk-appetite ;
vc:hasPart ngm:risk-assessment ;
vc:implements ngm:iso-31000 ;
vc:implements ngm:iso-iec-23894 ;
vc:implements ngm:iso-iec-23894-2023 ;
vc:implements ngm:nist-ai-rmf ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:bias ;
vc:relatedTo ngm:enterprise-risk-management ;
vc:relatedTo ngm:eu-ai-act-regulatory-instrument ;
vc:relatedTo ngm:explainability ;
vc:relatedTo ngm:fairness ;
vc:relatedTo ngm:model-drift ;
vc:relatedTo ngm:risk-management ;
vc:requires ngm:accountability ;
vc:requires ngm:ai-governance ;
vc:requires ngm:compliance-framework ;
vc:requires ngm:data-governance ;
vc:requires ngm:threat-modelling ;
vc:slug "ai-risk-register" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:supports ngm:ai-governance-framework ;
vc:supports ngm:model-governance ;
vc:supports ngm:regulatory-compliance ;
vc:uses ngm:algorithmic-auditing ;
vc:uses ngm:bias-detection-methods ;
vc:uses ngm:continuous-monitoring ;
vc:uses ngm:red-teaming .
ngm:ai-risk-scoring a skos:Concept ;
rdfs:label "AI Risk Scoring"@en .
ngm:ai-risks a owl:Class ;
rdfs:comment "AI Risks is the umbrella ontological category denoting the full taxonomy of potential and realised adverse impacts arising from the design, development, deployment, integration, or societal embedding of artificial intelligence systems, spanning four canonical risk-source domains—misuse (intention..."@en ;
rdfs:label "AI Risks"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:ai-safety ;
rdfs:subClassOf ngm:governance-object ;
rdfs:subClassOf ngm:harm-taxonomy ;
rdfs:subClassOf ngm:sociotechnical-risk ;
rdfs:subClassOf ngm:systemic-risk ;
rdfs:subClassOf ngm:technology-risk ;
rdfs:subClassOf _:r620 ;
rdfs:subClassOf _:r621 ;
rdfs:subClassOf _:r622 ;
rdfs:subClassOf _:r623 ;
rdfs:subClassOf _:r624 ;
rdfs:subClassOf _:r625 ;
rdfs:subClassOf _:r626 ;
rdfs:subClassOf _:r627 ;
rdfs:subClassOf _:r628 ;
rdfs:subClassOf _:r629 ;
rdfs:subClassOf _:r630 ;
rdfs:subClassOf _:r631 ;
rdfs:subClassOf _:r632 ;
rdfs:subClassOf _:r633 ;
rdfs:subClassOf _:r634 ;
rdfs:subClassOf _:r635 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:contrastsWith ngm:ai-benefits ;
vc:contrastsWith ngm:ai-capabilities ;
vc:contrastsWith ngm:ai-for-good ;
vc:contrastsWith ngm:beneficial-ai ;
vc:dependsOn ngm:compute-infrastructure ;
vc:dependsOn ngm:deployment-context ;
vc:dependsOn ngm:frontier-ai-systems ;
vc:dependsOn ngm:large-scale-pretrained-foundation-model ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:training-data ;
vc:enables ngm:ai-governance ;
vc:enables ngm:ai-liability ;
vc:enables ngm:algorithmic-impact-assessment ;
vc:enables ngm:compute-governance ;
vc:enables ngm:frontier-model-regulation ;
vc:enables ngm:pre-deployment-evaluation ;
vc:enables ngm:responsible-scaling-policy ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:accident-risks ;
vc:hasPart ngm:algorithmic-bias ;
vc:hasPart ngm:autonomous-weapons ;
vc:hasPart ngm:catastrophic-ai-risk ;
vc:hasPart ngm:cbrn-uplift-risk ;
vc:hasPart ngm:data-poisoning ;
vc:hasPart ngm:deepfakes ;
vc:hasPart ngm:existential-ai-risk ;
vc:hasPart ngm:hallucination ;
vc:hasPart ngm:misuse-risks ;
vc:hasPart ngm:model-inversion ;
vc:hasPart ngm:prompt-injection ;
vc:hasPart ngm:structural-risks ;
vc:implements ngm:defence-in-depth ;
vc:implements ngm:precautionary-principle ;
vc:implements ngm:risk-based-regulation ;
vc:implements ngm:sociotechnical-analysis ;
vc:implements ngm:tiered-capability-thresholds ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:ai-alignment ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:cybersecurity ;
vc:relatedTo ngm:information-security ;
vc:relatedTo ngm:privacy-protection ;
vc:relatedTo ngm:responsible-ai ;
vc:relatedTo ngm:surveillance-capitalism ;
vc:relatedTo ngm:trustworthy-ai ;
vc:requires ngm:algorithmic-auditing ;
vc:requires ngm:capability-evaluation ;
vc:requires ngm:incident-reporting ;
vc:requires ngm:red-teaming ;
vc:requires ngm:risk-assessment-methodology ;
vc:requires ngm:stakeholder-consultation ;
vc:requires ngm:threat-modelling ;
vc:slug "ai-risks" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:bletchley-declaration ;
vc:standardizedBy ngm:council-of-europe-ai-convention ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:iso-iec-23894 ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:standardizedBy ngm:mit-ai-risk-repository ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:standardizedBy ngm:oecd-ai-principles ;
vc:standardizedBy ngm:seoul-declaration ;
vc:standardizedBy ngm:uk-ai-safety-institute ;
vc:standardizedBy ngm:us-ai-safety-institute ;
vc:supports ngm:ai-policy ;
vc:supports ngm:ai-safety-research ;
vc:supports ngm:insurance-underwriting ;
vc:supports ngm:international-coordination ;
vc:supports ngm:knowledge-graph-publication-classifier ;
vc:supports ngm:liability-adjudication ;
vc:supports ngm:standards ;
vc:uses ngm:adversarial-robustness ;
vc:uses ngm:benchmarks ;
vc:uses ngm:capability-elicitation ;
vc:uses ngm:evaluation-frameworks ;
vc:uses ngm:mechanistic-interpretability ;
vc:uses ngm:risk-register ;
vc:uses ngm:threat-intelligence .
ngm:ai-rmf-govern-function a skos:Concept ;
rdfs:label "AI Rmf Govern Function"@en .
ngm:ai-rmf-manage-function a skos:Concept ;
rdfs:label "AI Rmf Manage Function"@en .
ngm:ai-rmf-map-function a skos:Concept ;
rdfs:label "AI Rmf Map Function"@en .
ngm:ai-rmf-measure-function a skos:Concept ;
rdfs:label "AI Rmf Measure Function"@en .
ngm:ai-robustness a skos:Concept ;
rdfs:label "AI Robustness"@en .
ngm:ai-roi a owl:Class ;
rdfs:comment "The quantifiable financial return and value generated by the deployment of artificial intelligence systems relative to the costs of implementation and maintenance."@en ;
rdfs:label "AI ROI"@en ;
rdfs:subClassOf ngm:ai-policy ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-policy ;
vc:relatedTo ngm:model-performance ;
vc:slug "ai-roi" ;
vc:sourceDomain "economics" .
ngm:ai-roi-benchmarking a owl:Class ;
rdfs:comment "The systematic evaluation and quantification of the financial return on investment generated by enterprise artificial intelligence deployments across various use cases."@en ;
rdfs:label "AI ROI Benchmarking"@en ;
rdfs:subClassOf ngm:enterprise-ai ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-adoption ;
vc:relatedTo ngm:enterprise-ai ;
vc:relatedTo ngm:technology-adoption ;
vc:slug "ai-roi-benchmarking" ;
vc:sourceDomain "economics" .
ngm:ai-roi-measurement a owl:Class ;
rdfs:comment "The framework and methodology used by organizations to quantify the financial and operational returns generated by artificial intelligence investments relative to their costs."@en ;
rdfs:label "AI ROI Measurement"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:model ;
vc:relatedTo ngm:model-performance ;
vc:slug "ai-roi-measurement" ;
vc:sourceDomain "economics" .
ngm:ai-safety a owl:Class ;
rdfs:comment "AI Safety is the interdisciplinary field of research and engineering practice dedicated to ensuring that artificial intelligence systems behave reliably, predictably, and in accordance with human values and intentions across their full operational lifecycle. It addresses near-term concerns such as robustness, distributional shift, and adversarial vulnerability, as well as longer-horizon concerns about advanced systems whose objectives may diverge from human welfare. Core techniques include formal verification of safety properties, interpretability methods that expose model internals, corrigibility mechanisms that preserve human oversight, and red-teaming to surface failure modes before deployment. AI Safety is increasingly embedded in regulatory frameworks and standard-setting processes governing high-risk AI applications."@en ;
rdfs:label "AI Safety"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf _:r642 ;
rdfs:subClassOf _:r643 ;
rdfs:subClassOf _:r644 ;
rdfs:subClassOf _:r645 ;
rdfs:subClassOf _:r646 ;
rdfs:subClassOf _:r647 ;
rdfs:subClassOf _:r648 ;
rdfs:subClassOf _:r649 ;
rdfs:subClassOf _:r650 ;
rdfs:subClassOf _:r651 ;
rdfs:subClassOf _:r652 ;
rdfs:subClassOf _:r653 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:autonomous-robot ;
vc:bridgesTo ngm:security ;
vc:bridgesTo ngm:smart-contract ;
vc:contrastsWith ngm:ai-capabilities-research ;
vc:contrastsWith ngm:mesa-optimisation ;
vc:contrastsWith ngm:reward-hacking ;
vc:dependsOn ngm:ai-system ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:value-alignment ;
vc:enables ngm:human-ai-collaboration ;
vc:enables ngm:model-evaluation ;
vc:enables ngm:responsible-ai ;
vc:enables ngm:trustworthy-ai ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:ai-alignment ;
vc:hasPart ngm:corrigibility ;
vc:hasPart ngm:formal-verification ;
vc:hasPart ngm:interpretability ;
vc:hasPart ngm:mechanistic-interpretability ;
vc:hasPart ngm:red-teaming ;
vc:hasPart ngm:scalable-oversight ;
vc:implements ngm:constitutional-ai-training-methodology ;
vc:implements ngm:direct-preference-optimisation ;
vc:implements ngm:reinforcement-learning-from-human-feedback ;
vc:isPartOf ngm:ai-governance ;
vc:qualityScore "0.91"^^xsd:float ;
vc:relatedTo ngm:ai-regulation ;
vc:relatedTo ngm:ai-security-institute ;
vc:relatedTo ngm:apollo-research ;
vc:relatedTo ngm:autonomous-robot ;
vc:relatedTo ngm:corrigibility ;
vc:relatedTo ngm:distributional-shift ;
vc:relatedTo ngm:existential-risk ;
vc:relatedTo ngm:large-language-model ;
vc:relatedTo ngm:mesa-optimisation ;
vc:relatedTo ngm:robustness ;
vc:relatedTo ngm:scalable-oversight ;
vc:relatedTo ngm:security ;
vc:relatedTo ngm:smart-contract ;
vc:requires ngm:ai-alignment ;
vc:requires ngm:formal-verification ;
vc:requires ngm:human-oversight ;
vc:requires ngm:interpretability ;
vc:requires ngm:robustness ;
vc:slug "ai-safety" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:bletchley-declaration ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:ai-ethics ;
vc:supports ngm:ai-regulation ;
vc:supports ngm:explainable-ai ;
vc:supports ngm:risk-management ;
vc:uses ngm:adversarial-machine-learning ;
vc:uses ngm:red-teaming ;
vc:uses ngm:reinforcement-learning-from-human-feedback ;
vc:uses ngm:sparse-autoencoders .
ngm:ai-safety-assessment a owl:Class ;
rdfs:comment "The systematic process of evaluating the potential risks, failure modes, and unintended consequences of artificial intelligence systems before and during deployment."@en ;
rdfs:label "AI Safety Assessment"@en ;
rdfs:subClassOf ngm:ai-policy ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-policy ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:risk-assessment ;
vc:slug "ai-safety-assessment" ;
vc:sourceDomain "security" .
ngm:ai-safety-evaluation a owl:Class ;
rdfs:comment "The systematic process of assessing the risks, failure modes, and potential for misalignment or cheating in AI systems prior to and during deployment."@en ;
rdfs:label "AI Safety Evaluation"@en ;
rdfs:subClassOf ngm:ai-policy ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-policy ;
vc:relatedTo ngm:gpt ;
vc:relatedTo ngm:risk-assessment ;
vc:slug "ai-safety-evaluation" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-safety-evaluation-framework a skos:Concept ;
rdfs:label "AI Safety Evaluation Framework"@en .
ngm:ai-safety-framework a skos:Concept ;
rdfs:label "AI Safety Framework"@en .
ngm:ai-safety-institute a owl:Class ;
rdfs:comment "An AI Safety Institute (AISI) is a state-backed organisation established to evaluate, test, and research the capabilities and safety risks of advanced AI systems, particularly frontier models. Such bodies conduct pre-deployment and post-deployment evaluations, develop standardised benchmarks for dangerous capability elicitation, and advise governments on AI risk policy. The UK established the world's first AISI in November 2023 at the Bletchley Park AI Safety Summit; the US, Japan, Canada, and other nations subsequently established counterpart bodies. The UK later renamed its institute the AI Security Institute (DSIT) to reflect an expanded emphasis on national-security-relevant AI risks."@en ;
rdfs:label "AI Safety Institute"@en ;
rdfs:subClassOf ngm:ai-safety ;
rdfs:subClassOf _:r636 ;
rdfs:subClassOf _:r637 ;
vc:bridgesTo ngm:national-security ;
vc:bridgesTo ngm:standards-body ;
vc:contrastsWith ngm:ai-ethics-board ;
vc:enables ngm:ai-alignment ;
vc:enables ngm:ai-policy ;
vc:enables ngm:international-ai-coordination ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:ai-governance ;
vc:isPartOf ngm:ai-policy ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:ai-safety-summit ;
vc:relatedTo ngm:bletchley-declaration ;
vc:relatedTo ngm:existential-ai-risk ;
vc:relatedTo ngm:large-language-model ;
vc:requires ngm:ai-evaluation ;
vc:requires ngm:frontier-ai ;
vc:slug "ai-safety-institute" ;
vc:sourceDomain "governance" ;
vc:supports ngm:ai-regulation ;
vc:supports ngm:ai-risk-assessment ;
vc:supports ngm:responsible-ai ;
vc:uses ngm:benchmarking ;
vc:uses ngm:capability-evaluation ;
vc:uses ngm:interpretability ;
vc:uses ngm:red-teaming .
ngm:ai-safety-institute-mandate a skos:Concept ;
rdfs:label "AI Safety Institute Mandate"@en .
ngm:ai-safety-level a skos:Concept ;
rdfs:label "AI Safety Level"@en .
ngm:ai-safety-preparedness-framework a owl:Class ;
rdfs:comment "Internal and external guidelines used by AI labs to assess and mitigate the risks of new model capabilities before release."@en ;
rdfs:label "AI Safety Preparedness Framework"@en ;
rdfs:subClassOf ngm:ai-safety-research ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:frontier-model-evaluation ;
vc:relatedTo ngm:responsible-scaling-policy ;
vc:slug "ai-safety-preparedness-framework" ;
vc:sourceDomain "governance" .
ngm:ai-safety-red-lines a owl:Class ;
rdfs:comment "Specific ethical boundaries set by AI developers that define prohibited uses of their models, such as autonomous weapons or domestic surveillance."@en ;
rdfs:label "AI Safety Red Lines"@en ;
rdfs:subClassOf ngm:ai-safety-research ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-governance-and-ethics ;
vc:relatedTo ngm:responsible-scaling-policy ;
vc:slug "ai-safety-red-lines" ;
vc:sourceDomain "governance" .
ngm:ai-safety-research a owl:Class ;
rdfs:comment "AI Safety Research is an interdisciplinary field that develops theoretical frameworks, empirical methods, and engineering techniques to ensure advanced AI systems behave in ways that are safe, reliable, and aligned with human values across a range of capability levels. The field spans near-term concerns — such as robustness, fairness, and adversarial resistance — and longer-term challenges including scalable oversight, corrigibility, and the avoidance of catastrophic risks from highly capable systems. It draws on machine learning, decision theory, formal verification, and cognitive science to produce both immediately deployable safety interventions and foundational understanding of how intelligent systems can be made reliably beneficial."@en ;
rdfs:label "AI Safety Research"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf _:r638 ;
rdfs:subClassOf _:r639 ;
rdfs:subClassOf _:r640 ;
rdfs:subClassOf _:r641 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:autonomous-system ;
vc:bridgesTo ngm:cognitive-science ;
vc:contrastsWith ngm:ai-capabilities-research ;
vc:dependsOn ngm:ai-agents ;
vc:dependsOn ngm:autonomous-system ;
vc:dependsOn ngm:deep-learning ;
vc:enables ngm:ai-alignment ;
vc:enables ngm:ai-safety ;
vc:enables ngm:corrigibility ;
vc:enables ngm:responsible-ai ;
vc:enables ngm:trustworthy-ai ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.88"^^xsd:float ;
vc:relatedTo ngm:ai-risk ;
vc:relatedTo ngm:eu-ai-act-regulatory-instrument ;
vc:relatedTo ngm:existential-risk ;
vc:relatedTo ngm:fairness-in-machine-learning ;
vc:relatedTo ngm:iso-iec-42001 ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:nist-ai-rmf ;
vc:relatedTo ngm:prompt-injection ;
vc:relatedTo ngm:reward-hacking ;
vc:relatedTo ngm:scalable-oversight ;
vc:relatedTo ngm:specification-gaming ;
vc:requires ngm:decision-theory ;
vc:requires ngm:machine-learning-discipline ;
vc:requires ngm:neural-network ;
vc:requires ngm:robustness ;
vc:slug "ai-safety-research" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:ai-governance ;
vc:supports ngm:ai-policy ;
vc:supports ngm:ai-regulation ;
vc:supports ngm:ai-risk-management ;
vc:supports ngm:model-evaluation ;
vc:uses ngm:adversarial-machine-learning ;
vc:uses ngm:constitutional-ai-training-methodology ;
vc:uses ngm:formal-verification ;
vc:uses ngm:interpretability ;
vc:uses ngm:mechanistic-interpretability ;
vc:uses ngm:red-teaming ;
vc:uses ngm:reinforcement-learning-from-human-feedback ;
vc:uses ngm:uncertainty-quantification ;
vc:uses ngm:value-learning .
ngm:ai-safety-summit a owl:Class ;
rdfs:comment "An intergovernmental summit series on frontier AI risk, inaugurated at Bletchley Park in November 2023, that convenes governments, leading AI companies, and researchers to agree shared assessments of advanced-model risks and coordination mechanisms for testing and governance. The series produced the Bletchley Declaration, catalysed the creation of national AI safety institutes, and continued through the Seoul summit (2024), the Paris AI Action Summit (2025), and the India AI Impact Summit in New Delhi (February 2026), with Switzerland due to host the next summit in Geneva in 2027."@en ;
rdfs:label "AI Safety Summit"@en ;
rdfs:subClassOf ngm:international-ai-cooperation ;
vc:enables ngm:ai-safety-institute ;
vc:enables ngm:bletchley-declaration ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:frontier-ai ;
vc:slug "ai-safety-summit" ;
vc:sourceDomain "governance" .
ngm:ai-safety-summit-series a skos:Concept ;
rdfs:label "AI Safety Summit Series"@en .
ngm:ai-safety-testing a skos:Concept ;
rdfs:label "AI Safety Testing"@en .
ngm:ai-safety-transparency a skos:Concept ;
rdfs:label "AI Safety Transparency"@en .
ngm:ai-sales-quotas a owl:Class ;
rdfs:comment "Internal revenue targets and performance benchmarks set by technology companies for the adoption and monetization of artificial intelligence products and services."@en ;
rdfs:label "AI Sales Quotas"@en ;
rdfs:subClassOf ngm:microsoft ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:azure ;
vc:relatedTo ngm:microsoft ;
vc:slug "ai-sales-quotas" ;
vc:sourceDomain "economics" .
ngm:ai-scepticism a skos:Concept ;
rdfs:label "AI Scepticism"@en .
ngm:ai-scrapers a owl:Class ;
rdfs:comment "AI Scrapers are automated software agents (web crawlers, retrieval bots, and content-fetching pipelines) operated by foundation-model laboratories, AI search vendors, retrieval-augmented-generation services, dataset aggregators, and synthetic-media producers for the purpose of harvesting publicly..."@en ;
rdfs:label "AI Scrapers"@en ;
rdfs:subClassOf ngm:ai-agent-system ;
rdfs:subClassOf ngm:automated-agent ;
rdfs:subClassOf ngm:data-acquisition-pipeline ;
rdfs:subClassOf ngm:internet-bot ;
rdfs:subClassOf ngm:regulated-data-processor ;
rdfs:subClassOf ngm:web-crawler ;
rdfs:subClassOf _:r654 ;
rdfs:subClassOf _:r655 ;
vc:bridgesTo ngm:ai-infrastructure ;
vc:contrastsWith ngm:academic-crawler ;
vc:contrastsWith ngm:classic-search-crawler ;
vc:contrastsWith ngm:personal-web-scraper ;
vc:contrastsWith ngm:web-archive-crawler ;
vc:dependsOn ngm:cdn-layer ;
vc:dependsOn ngm:common-crawl ;
vc:dependsOn ngm:dns ;
vc:dependsOn ngm:internet-infrastructure ;
vc:dependsOn ngm:public-web-architecture ;
vc:enables ngm:fine-tuning-dataset-assembly ;
vc:enables ngm:foundation-model-pre-training ;
vc:enables ngm:knowledge-graph-extraction ;
vc:enables ngm:retrieval-augmented-generation ;
vc:enables ngm:search-index-construction ;
vc:enables ngm:synthetic-data-curation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:content-extraction-pipeline ;
vc:hasPart ngm:crawl-frontier ;
vc:hasPart ngm:deduplication-filter ;
vc:hasPart ngm:ip-range-manifest ;
vc:hasPart ngm:politeness-policy ;
vc:hasPart ngm:robots-txt-parser ;
vc:hasPart ngm:user-agent-string ;
vc:implements ngm:content-type-negotiation ;
vc:implements ngm:de-duplication-hashing ;
vc:implements ngm:http-protocol ;
vc:implements ngm:politeness-throttling ;
vc:implements ngm:robots-exclusion-protocol ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:bot-management ;
vc:relatedTo ngm:content-licensing ;
vc:relatedTo ngm:data-protection ;
vc:relatedTo ngm:intellectual-property-rights-framework-law ;
vc:relatedTo ngm:training-data ;
vc:relatedTo ngm:web-scraping ;
vc:requires ngm:compute-infrastructure ;
vc:requires ngm:http-client ;
vc:requires ngm:identity-provenance ;
vc:requires ngm:network-connectivity ;
vc:requires ngm:public-web-content ;
vc:requires ngm:storage-pipeline ;
vc:slug "ai-scrapers" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument-article-53 ;
vc:standardizedBy ngm:gpai-code-of-practice ;
vc:standardizedBy ngm:iab-tech-lab ;
vc:standardizedBy ngm:ietf-aipref-working-group ;
vc:standardizedBy ngm:ietf-rfc-9309 ;
vc:supports ngm:ai-search ;
vc:supports ngm:generative-ai ;
vc:supports ngm:large-language-model-training ;
vc:supports ngm:multimodal-ai-architecture-model-training ;
vc:supports ngm:multimodal-model-training ;
vc:supports ngm:rag-pipeline ;
vc:supports ngm:rag-pipelines ;
vc:uses ngm:bloom-filter ;
vc:uses ngm:headless-browser ;
vc:uses ngm:http-library ;
vc:uses ngm:playwright ;
vc:uses ngm:selenium ;
vc:uses ngm:sitemaps-xml .
ngm:ai-script-generation a skos:Concept ;
rdfs:label "AI Script Generation"@en .
ngm:ai-search a owl:Class ;
rdfs:comment "AI Search (also termed generative search, answer engine, conversational search, or retrieval-augmented search) is the class of web-scale information-access systems that pair a large language model (LLM) with a live retrieval layer over web indexes, document stores, or proprietary corpora to produ..."@en ;
rdfs:label "AI Search"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:conversational-ai ;
rdfs:subClassOf ngm:information-retrieval ;
rdfs:subClassOf ngm:natural-language-processing ;
rdfs:subClassOf ngm:question-answering-system ;
rdfs:subClassOf ngm:retrieval-augmented-generation ;
rdfs:subClassOf ngm:search-engine ;
rdfs:subClassOf _:r656 ;
rdfs:subClassOf _:r657 ;
rdfs:subClassOf _:r658 ;
rdfs:subClassOf _:r659 ;
rdfs:subClassOf _:r660 ;
rdfs:subClassOf _:r661 ;
rdfs:subClassOf _:r662 ;
rdfs:subClassOf _:r663 ;
rdfs:subClassOf _:r664 ;
rdfs:subClassOf _:r665 ;
rdfs:subClassOf _:r666 ;
rdfs:subClassOf _:r667 ;
skos:broader ngm:ai-application ;
vc:contrastsWith ngm:boolean-search ;
vc:contrastsWith ngm:classical-information-retrieval ;
vc:contrastsWith ngm:conversational-ai-without-retrieval ;
vc:contrastsWith ngm:keyword-search ;
vc:contrastsWith ngm:knowledge-graph-lookup ;
vc:contrastsWith ngm:pagerank ;
vc:dependsOn ngm:bm25 ;
vc:dependsOn ngm:common-crawl ;
vc:dependsOn ngm:hnsw-indexing ;
vc:dependsOn ngm:nearest-neighbor-search ;
vc:dependsOn ngm:transformer-architecture ;
vc:dependsOn ngm:web-crawling ;
vc:enables ngm:agentic-browsing ;
vc:enables ngm:citation-grounded-answers ;
vc:enables ngm:conversational-web-access ;
vc:enables ngm:multi-source-synthesis ;
vc:enables ngm:programmatic-knowledge-lookup ;
vc:enables ngm:research-workflows ;
vc:enables ngm:zero-click-information-access ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:answer-synthesiser ;
vc:hasPart ngm:citation-grounding-layer ;
vc:hasPart ngm:dense-retrieval ;
vc:hasPart ngm:embedding-index ;
vc:hasPart ngm:follow-up-suggester ;
vc:hasPart ngm:llm-generator ;
vc:hasPart ngm:query-understanding-module ;
vc:hasPart ngm:reranker ;
vc:hasPart ngm:sparse-retriever ;
vc:hasPart ngm:web-index ;
vc:implements ngm:chain-of-thought-reasoning ;
vc:implements ngm:cross-encoder-reranking ;
vc:implements ngm:dense-passage-retrieval ;
vc:implements ngm:hybrid-retrieval ;
vc:implements ngm:retrieval-augmented-generation ;
vc:implements ngm:tool-use ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:agentic-browser ;
vc:relatedTo ngm:digital-twin ;
vc:relatedTo ngm:generative-ai ;
vc:relatedTo ngm:knowledge-graph ;
vc:relatedTo ngm:large-language-model ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:semantic-search ;
vc:relatedTo ngm:vector-database ;
vc:relatedTo ngm:web-search ;
vc:requires ngm:content-licensing ;
vc:requires ngm:embedding-model ;
vc:requires ngm:inference-infrastructure ;
vc:requires ngm:large-language-model ;
vc:requires ngm:large-language-models ;
vc:requires ngm:tokeniser ;
vc:requires ngm:vector-database ;
vc:requires ngm:web-crawler ;
vc:slug "ai-search" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:c2-pa-content-credentials ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument-article-50 ;
vc:standardizedBy ngm:ico-ai-guidance ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:standardizedBy ngm:trec-rag-track ;
vc:standardizedBy ngm:uk-online-safety-act ;
vc:supports ngm:academic-research ;
vc:supports ngm:customer-support ;
vc:supports ngm:journalism ;
vc:supports ngm:knowledge-management ;
vc:supports ngm:legal-research ;
vc:supports ngm:medical-information-retrieval ;
vc:supports ngm:software-development ;
vc:uses ngm:caching ;
vc:uses ngm:cosine-similarity ;
vc:uses ngm:embeddings ;
vc:uses ngm:function-calling ;
vc:uses ngm:prompt-engineering ;
vc:uses ngm:reciprocal-rank-fusion ;
vc:uses ngm:streaming-generation .
ngm:ai-security a owl:Class ;
rdfs:comment "AI Security is the field of protecting artificial intelligence systems and their components from security threats and vulnerabilities, including adversarial attacks, data poisoning, model theft, and unauthorized access to ensure systems perform as intended. It encompasses defending AI models, algorithms, training data, and infrastructure from manipulation, misuse, and exploitation throughout the AI lifecycle."@en ;
rdfs:label "AI Security"@en ;
rdfs:subClassOf ngm:cybersecurity ;
rdfs:subClassOf _:r668 ;
rdfs:subClassOf _:r669 ;
rdfs:subClassOf _:r670 ;
rdfs:subClassOf _:r671 ;
rdfs:subClassOf _:r672 ;
rdfs:subClassOf _:r673 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:zero-trust-architecture ;
vc:contrastsWith ngm:ai-safety ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:threat-modelling ;
vc:enables ngm:secure-ai-deployment ;
vc:enables ngm:trustworthy-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:adversarial-machine-learning ;
vc:hasPart ngm:ai-monitoring ;
vc:hasPart ngm:prompt-injection ;
vc:hasPart ngm:red-teaming ;
vc:implements ngm:nist-ai-rmf ;
vc:isPartOf ngm:ai-governance-and-ethics ;
vc:isPartOf ngm:cybersecurity ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:data-poisoning ;
vc:relatedTo ngm:explainable-ai ;
vc:relatedTo ngm:model-extraction ;
vc:requires ngm:access-control ;
vc:requires ngm:adversarial-training ;
vc:slug "ai-security" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:nist-cybersecurity-framework ;
vc:supports ngm:ai-risk-management ;
vc:supports ngm:responsible-ai ;
vc:uses ngm:anomaly-detection ;
vc:uses ngm:differential-privacy ;
vc:uses ngm:federated-learning .
ngm:ai-security-breach a owl:Class ;
rdfs:comment "Unauthorized access to, or compromise of, AI model weights, training data, or inference environments, leading to potential data leakage or model theft."@en ;
rdfs:label "AI Security Breach"@en ;
rdfs:subClassOf ngm:ai-safety ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:model ;
vc:relatedTo ngm:third-party-vendor ;
vc:slug "ai-security-breach" ;
vc:sourceDomain "security" .
ngm:ai-security-institute a skos:Concept ;
rdfs:label "AI Security Institute"@en .
ngm:ai-self-regulation a owl:Class ;
rdfs:comment "AI self-regulation is the governance of artificial intelligence through voluntary commitments, codes of conduct, and internal policies adopted by AI developers and industry bodies rather than imposed by statute. It includes responsible scaling policies, voluntary safety commitments, model release and evaluation norms, and industry consortia that agree shared practices. As a domain-specific specialisation of general industry self-regulation, it is defined by contrast with binding AI regulation and with state safety bodies such as national AI Safety Institutes: it is faster and more technically informed but lacks enforcement and can drift toward reputational cover unless paired with external accountability. It is frequently framed as a bridge or interim measure ahead of formal regulation."@en ;
rdfs:label "AI Self-Regulation"@en ;
rdfs:subClassOf ngm:self-regulation ;
vc:contrastsWith ngm:ai-regulation ;
vc:contrastsWith ngm:uk-ai-safety-institute ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:responsible-scaling-policy ;
vc:slug "ai-self-regulation" ;
vc:sourceDomain "governance" .
ngm:ai-service-classification a skos:Concept ;
rdfs:label "AI Service Classification"@en .
ngm:ai-shopping-assistant a owl:Class ;
rdfs:comment "Conversational AI interfaces integrated into e-commerce platforms that assist consumers in product discovery, comparison, and purchase decisions."@en ;
rdfs:label "AI Shopping Assistant"@en ;
rdfs:subClassOf ngm:ai-agents ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-agents ;
vc:relatedTo ngm:workflow-automation ;
vc:slug "ai-shopping-assistant" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-sovereign-wealth-fund a owl:Class ;
rdfs:comment "A proposed government mechanism to hold equity stakes in major AI companies to distribute the financial benefits of AI development to the public."@en ;
rdfs:label "AI Sovereign Wealth Fund"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
skos:broader ngm:ai-governance-and-ethics ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-regulation ;
vc:relatedTo ngm:eu-ai-act-regulatory-instrument ;
vc:slug "ai-sovereign-wealth-fund" ;
vc:sourceDomain "governance" .
ngm:ai-sovereignty a owl:Class ;
rdfs:comment "AI Sovereignty is the capacity of a nation or bloc to develop, control, and govern artificial-intelligence systems and their underlying compute, data, and models without dependence on foreign providers. It motivates domestic investment in chips, data centres, foundation models, and regulation to retain strategic autonomy. The concept frames AI capability as critical national infrastructure subject to security, economic, and geopolitical considerations."@en ;
rdfs:label "AI Sovereignty"@en ;
rdfs:subClassOf ngm:ai-governance ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:ai-chips ;
vc:relatedTo ngm:competition-in-ai ;
vc:slug "ai-sovereignty" ;
vc:sourceDomain "governance" .
ngm:ai-speciation a owl:Class ;
rdfs:comment "The predicted evolutionary trend in AI where a single general-purpose intelligence diverges into multiple specialized, smaller models optimized for distinct tasks."@en ;
rdfs:label "AI Speciation"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:model ;
vc:slug "ai-speciation" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-standardisation a skos:Concept ;
rdfs:label "AI Standardisation"@en .
ngm:ai-standards a skos:Concept ;
rdfs:label "AI Standards"@en .
ngm:ai-startups a skos:Concept ;
rdfs:label "AI Startups"@en .
ngm:ai-stock-market a owl:Class ;
rdfs:comment "The segment of the financial market comprising equities and investments specifically tied to the development, infrastructure, and commercialization of artificial intelligence technologies."@en ;
rdfs:label "AI Stock Market"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:computational-infrastructure ;
vc:slug "ai-stock-market" ;
vc:sourceDomain "economics" .
ngm:ai-strategy a skos:Concept ;
rdfs:label "AI Strategy"@en .
ngm:ai-styling a skos:Concept ;
rdfs:label "AI Styling"@en .
ngm:ai-supply-chain a skos:Concept ;
rdfs:label "AI Supply Chain"@en .
ngm:ai-supply-chain-management a skos:Concept ;
rdfs:label "AI Supply Chain Management"@en .
ngm:ai-supply-chain-risk a owl:Class ;
rdfs:comment "The assessment of vulnerabilities and dependencies within the ecosystem of AI model development, deployment, and maintenance, including hardware, data, and regulatory factors."@en ;
rdfs:label "AI Supply Chain Risk"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
skos:broader ngm:ai-governance-and-ethics ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:ai-regulation ;
vc:relatedTo ngm:responsible-scaling-policy ;
vc:slug "ai-supply-chain-risk" ;
vc:sourceDomain "governance" .
ngm:ai-supply-chain-shortage a owl:Class ;
rdfs:comment "A structural deficit in the availability of critical hardware components, such as high-bandwidth memory and advanced semiconductors, required to build and scale artificial intelligence infrastructure."@en ;
rdfs:label "AI Supply Chain Shortage"@en ;
rdfs:subClassOf ngm:open-source ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:open-source ;
vc:relatedTo ngm:software-supply-chain ;
vc:slug "ai-supply-chain-shortage" ;
vc:sourceDomain "infrastructure" .
ngm:ai-surveillance a owl:Class ;
rdfs:comment "AI surveillance is the application of machine learning and computer vision to monitoring at scale: automated facial recognition in public space, gait and behaviour analysis, licence-plate reading, social-media and communications analytics, and predictive scoring of individuals or crowds. It differs from conventional surveillance in that inference, not observation, does the work — systems classify, track, and flag people continuously without human attention per subject, raising distinct governance questions about bias, proportionality, chilling effects, and the legal basis for algorithmic monitoring."@en ;
rdfs:label "AI Surveillance"@en ;
rdfs:subClassOf ngm:surveillance ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:digital-society-surveillance ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:algorithmic-bias ;
vc:relatedTo ngm:privacy ;
vc:slug "ai-surveillance" ;
vc:sourceDomain "governance" ;
vc:uses ngm:computer-vision ;
vc:uses ngm:facial-recognition ;
vc:uses ngm:machine-learning-discipline .
ngm:ai-surveillance-deployment-case-study a owl:Class ;
rdfs:comment "A case study examining the deployment of AI-based surveillance systems at the Paris 2024 Olympic Games, involving real-time video analytics, geolocation tracking, behavioural pattern analysis, and predictive event detection contracted to vendors including Viet, Orange Business, Chaps Vision, and Windex. The deployment required French legislative modifications expanding surveillance powers and raised significant GDPR compliance questions regarding continuous monitoring, data retention, algorithmic bias, and the post-event normalisation of pervasive AI surveillance infrastructure."@en ;
rdfs:label "AI Surveillance Deployment Case Study"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
skos:broader ngm:ai-governance-and-ethics ;
vc:contrastsWith ngm:ai-ethics ;
vc:contrastsWith ngm:responsible-ai ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:bias ;
vc:relatedTo ngm:cryptography ;
vc:relatedTo ngm:fairness ;
vc:relatedTo ngm:privacy-by-design ;
vc:slug "ai-surveillance-deployment-case-study" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:computer-vision ;
vc:uses ngm:object-detection-and-tracking .
ngm:ai-sustainability-copilot a skos:Concept ;
rdfs:label "AI Sustainability Copilot"@en .
ngm:ai-synthesis a skos:Concept ;
rdfs:label "AI Synthesis"@en .
ngm:ai-system a owl:Class ;
rdfs:comment "An integrated assembly of software, hardware, data, and processes that employs machine learning or related techniques to perceive inputs, infer patterns or decisions, and produce outputs that affect its environment or users. AI systems range from narrow task-specific classifiers to general-purpose language models and autonomous agents, and they are characterised by behaviour that emerges from learned parameters rather than explicit programming. Regulatory definitions such as that codified in the EU AI Act emphasise the system-level perspective, encompassing the full sociotechnical context of deployment."@en ;
rdfs:label "AI System"@en ;
rdfs:subClassOf ngm:sociotechnical-system ;
rdfs:subClassOf _:r678 ;
rdfs:subClassOf _:r679 ;
rdfs:subClassOf _:r680 ;
rdfs:subClassOf _:r681 ;
rdfs:subClassOf _:r682 ;
rdfs:subClassOf _:r683 ;
rdfs:subClassOf _:r684 ;
rdfs:subClassOf _:r685 ;
rdfs:subClassOf _:r686 ;
rdfs:subClassOf _:r687 ;
vc:bridgesTo ngm:digital-infrastructure ;
vc:bridgesTo ngm:regulatory-compliance ;
vc:contrastsWith ngm:rule-based-systems ;
vc:dependsOn ngm:data-governance ;
vc:dependsOn ngm:llmops ;
vc:dependsOn ngm:mlops ;
vc:dependsOn ngm:model-registry ;
vc:dependsOn ngm:model-serving ;
vc:enables ngm:agentic-ai ;
vc:enables ngm:ai-risk-assessment ;
vc:enables ngm:autonomous-decision-making ;
vc:enables ngm:intelligent-automation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ai-inference ;
vc:hasPart ngm:ai-model ;
vc:hasPart ngm:data-pipeline ;
vc:hasPart ngm:inference-runtime ;
vc:hasPart ngm:monitoring ;
vc:implements ngm:deep-learning ;
vc:implements ngm:learning-algorithm ;
vc:implements ngm:neural-network ;
vc:implements ngm:reinforcement-learning ;
vc:implements ngm:transformer-architecture ;
vc:qualityScore "0.91"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:ai-system-eu-definition ;
vc:relatedTo ngm:compound-ai-system ;
vc:relatedTo ngm:edge-ai-system ;
vc:relatedTo ngm:large-language-model ;
vc:relatedTo ngm:multi-agent-system ;
vc:requires ngm:compute-infrastructure ;
vc:requires ngm:learning-algorithm ;
vc:requires ngm:machine-learning-discipline-framework ;
vc:requires ngm:training-data ;
vc:slug "ai-system" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:standardizedBy ngm:regulatory-compliance ;
vc:supports ngm:ai-governance ;
vc:supports ngm:ai-safety ;
vc:supports ngm:explainability ;
vc:uses ngm:api-gateway ;
vc:uses ngm:cloud-computing ;
vc:uses ngm:computer-vision ;
vc:uses ngm:natural-language-processing .
ngm:ai-system-component a owl:Class ;
rdfs:comment "Modular functional units constituting a complete artificial intelligence system, including data ingestion pipelines, feature engineering modules, model training infrastructure, inference engines, monitoring dashboards, and user interfaces. Modern AI systems adopt microservices architectures enabling independent scaling, version control, and A/B testing per component, with observability integrated at each layer for production reliability."@en ;
rdfs:label "AI System Component"@en ;
rdfs:subClassOf ngm:ai-infrastructure ;
rdfs:subClassOf _:r676 ;
rdfs:subClassOf _:r677 ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:data-pipeline ;
vc:hasPart ngm:machine-learning-discipline-pipeline ;
vc:qualityScore "0.35"^^xsd:float ;
vc:slug "ai-system-component" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:ai-infrastructure ;
vc:supports ngm:ai-lifecycle ;
vc:uses ngm:machine-learning-model ;
vc:uses ngm:microservices-architecture .
ngm:ai-system-eu-definition a owl:Class ;
rdfs:comment "Under EU AI Act Article 3(1), a machine-based system designed to operate with varying levels of autonomy, capable of adapting after deployment, and generating outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments. This definition establishes the regulatory scope of the AI Act and aligns with the 2024 OECD AI Principles, distinguishing AI systems from traditional software by their inferential and adaptive capabilities."@en ;
rdfs:label "AI System (EU Definition)"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf _:r674 ;
rdfs:subClassOf _:r675 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:ai-lifecycle ;
vc:relatedTo ngm:ai-provider ;
vc:relatedTo ngm:general-purpose-ai-model ;
vc:requires ngm:ai-risk-management ;
vc:requires ngm:human-oversight ;
vc:slug "ai-system-eu-definition" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument .
ngm:ai-system-use-by-ai-users-and-ai-operators a skos:Concept ;
rdfs:label "AI System Use By AI Users And AI Operators"@en .
ngm:ai-systems a skos:Concept ;
rdfs:label "AI Systems"@en .
ngm:ai-systems-thinking a owl:Class ;
rdfs:comment "An approach to AI adoption that emphasizes building robust, vendor-independent learning systems over relying on single models or tools."@en ;
rdfs:label "AI Systems Thinking"@en ;
rdfs:subClassOf ngm:ai-technique ;
skos:broader ngm:ai-technique ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-harness-engineering ;
vc:relatedTo ngm:vendor-independence ;
vc:slug "ai-systems-thinking" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-talent a owl:Class ;
rdfs:comment "The human capital pool comprising individuals with specialised skills in machine learning research, AI engineering, data science, and related disciplines who design, build, evaluate, and govern artificial intelligence systems. AI talent is a scarce and strategically contested resource, with demand from frontier laboratories, technology companies, and public-sector institutions consistently outpacing the supply produced by academic programmes. The composition of the talent pool—including its geographic distribution, diversity, and specialisation—directly shapes the pace and direction of AI progress."@en ;
rdfs:label "AI Talent"@en ;
rdfs:subClassOf ngm:ai-research-talent ;
rdfs:subClassOf ngm:human-capital ;
rdfs:subClassOf ngm:workforce-development ;
rdfs:subClassOf _:r703 ;
rdfs:subClassOf _:r704 ;
rdfs:subClassOf _:r705 ;
rdfs:subClassOf _:r706 ;
rdfs:subClassOf _:r707 ;
rdfs:subClassOf _:r708 ;
rdfs:subClassOf _:r709 ;
rdfs:subClassOf _:r710 ;
rdfs:subClassOf _:r711 ;
rdfs:subClassOf _:r712 ;
rdfs:subClassOf _:r713 ;
rdfs:subClassOf _:r714 ;
vc:contrastsWith ngm:ai-talent-war ;
vc:contrastsWith ngm:talent-concentration ;
vc:dependsOn ngm:ai-investment ;
vc:dependsOn ngm:compute-infrastructure ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:education-and-ai ;
vc:dependsOn ngm:reinforcement-learning ;
vc:enables ngm:ai-model-development ;
vc:enables ngm:ai-safety-research ;
vc:enables ngm:deep-learning ;
vc:enables ngm:foundation-model ;
vc:enables ngm:frontier-ai ;
vc:enables ngm:large-language-models ;
vc:enables ngm:technological-leadership ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ai-research-talent ;
vc:hasPart ngm:ai-safety-research ;
vc:hasPart ngm:alignment-research ;
vc:hasPart ngm:data-science ;
vc:hasPart ngm:explainable-ai ;
vc:hasPart ngm:ml-engineering ;
vc:hasPart ngm:mlops ;
vc:hasPart ngm:natural-language-processing ;
vc:implements ngm:ai-policy ;
vc:implements ngm:immigration-policy ;
vc:implements ngm:national-ai-strategies ;
vc:qualityScore "0.88"^^xsd:float ;
vc:relatedTo ngm:ai-investment ;
vc:relatedTo ngm:ai-talent-war ;
vc:relatedTo ngm:anthropic ;
vc:relatedTo ngm:competition-in-ai ;
vc:relatedTo ngm:education-and-ai ;
vc:relatedTo ngm:geopolitics ;
vc:relatedTo ngm:google-ai-technology-corporation-deep-mind ;
vc:relatedTo ngm:immigration-policy ;
vc:relatedTo ngm:meta-ai ;
vc:relatedTo ngm:open-source-ai ;
vc:relatedTo ngm:openai-research-organisation ;
vc:relatedTo ngm:talent-concentration ;
vc:requires ngm:ai-investment ;
vc:requires ngm:compute-infrastructure ;
vc:requires ngm:education-and-ai ;
vc:requires ngm:machine-learning-discipline ;
vc:requires ngm:neural-network ;
vc:slug "ai-talent" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:ai-policy ;
vc:standardizedBy ngm:national-ai-strategies ;
vc:supports ngm:ai-ethics ;
vc:supports ngm:ai-governance-framework ;
vc:supports ngm:bias-and-fairness ;
vc:supports ngm:economic-competitiveness ;
vc:supports ngm:innovation-ecosystems ;
vc:uses ngm:deep-learning ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:neural-network ;
vc:uses ngm:reinforcement-learning .
ngm:ai-talent-acquisition a owl:Class ;
rdfs:comment "Strategic corporate actions, including acquisitions and high-value hiring, aimed at securing specialized artificial intelligence expertise and research leadership."@en ;
rdfs:label "AI Talent Acquisition"@en ;
rdfs:subClassOf ngm:enterprise-ai ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-adoption ;
vc:relatedTo ngm:enterprise-ai ;
vc:slug "ai-talent-acquisition" ;
vc:sourceDomain "economics" .
ngm:ai-talent-war a owl:Class ;
rdfs:comment "The intensely competitive global contest among technology companies, research institutions, and nation-states to attract, retain, and concentrate the scarce pool of highly skilled AI researchers and engineers. The competition manifests through escalating compensation packages, aggressive academic recruitment, strategic immigration policy, and corporate acquisitions of talent-rich startups. Because frontier AI capability is tightly coupled to the concentration of top research talent, this competition is simultaneously an economic, geopolitical, and strategic-security phenomenon."@en ;
rdfs:label "AI Talent War"@en ;
rdfs:subClassOf ngm:competition-in-ai ;
rdfs:subClassOf ngm:geopolitics ;
rdfs:subClassOf ngm:technology-race ;
rdfs:subClassOf ngm:workforce-development ;
rdfs:subClassOf _:r695 ;
rdfs:subClassOf _:r696 ;
rdfs:subClassOf _:r697 ;
rdfs:subClassOf _:r698 ;
rdfs:subClassOf _:r699 ;
rdfs:subClassOf _:r700 ;
rdfs:subClassOf _:r701 ;
rdfs:subClassOf _:r702 ;
vc:contrastsWith ngm:ai-cooperation ;
vc:contrastsWith ngm:ai-governance-framework ;
vc:contrastsWith ngm:ai-regulation ;
vc:contrastsWith ngm:open-source-ai ;
vc:dependsOn ngm:ai-investment ;
vc:dependsOn ngm:compute-infrastructure ;
vc:dependsOn ngm:education-and-ai ;
vc:dependsOn ngm:geopolitics ;
vc:dependsOn ngm:reinforcement-learning-from-human-feedback ;
vc:enables ngm:ai-model-development ;
vc:enables ngm:ai-sovereignty ;
vc:enables ngm:economic-competitiveness ;
vc:enables ngm:frontier-model-training ;
vc:enables ngm:national-security-advantage ;
vc:enables ngm:technological-leadership ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:acqui-hire ;
vc:hasPart ngm:ai-research-talent ;
vc:hasPart ngm:compensation-escalation ;
vc:hasPart ngm:immigration-policy ;
vc:hasPart ngm:open-source-ai ;
vc:hasPart ngm:talent-concentration ;
vc:implements ngm:ai-policy ;
vc:implements ngm:export-controls ;
vc:implements ngm:immigration-policy ;
vc:implements ngm:national-ai-strategies ;
vc:qualityScore "0.88"^^xsd:float ;
vc:relatedTo ngm:ai-investment ;
vc:relatedTo ngm:ai-talent ;
vc:relatedTo ngm:anthropic ;
vc:relatedTo ngm:export-controls ;
vc:relatedTo ngm:frontier-ai ;
vc:relatedTo ngm:geopolitics ;
vc:relatedTo ngm:google-ai-technology-corporation-deep-mind ;
vc:relatedTo ngm:meta-ai ;
vc:relatedTo ngm:national-ai-strategies ;
vc:relatedTo ngm:openai-research-organisation ;
vc:relatedTo ngm:technology-race ;
vc:requires ngm:ai-investment ;
vc:requires ngm:compute-infrastructure ;
vc:requires ngm:education-and-ai ;
vc:requires ngm:foundation-model ;
vc:requires ngm:gpu-supply-chain ;
vc:slug "ai-talent-war" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:ai-policy ;
vc:standardizedBy ngm:national-ai-strategies ;
vc:supports ngm:ai-safety-research ;
vc:supports ngm:frontier-ai ;
vc:supports ngm:innovation-ecosystems ;
vc:supports ngm:technological-leadership ;
vc:uses ngm:acqui-hire ;
vc:uses ngm:deep-learning ;
vc:uses ngm:foundation-model ;
vc:uses ngm:reinforcement-learning-from-human-feedback .
ngm:ai-task-integration a skos:Concept ;
rdfs:label "AI Task Integration"@en .
ngm:ai-tax-policy a owl:Class ;
rdfs:comment "Governmental fiscal strategies and regulatory instruments designed to address the economic shifts, revenue changes, and distributional effects caused by artificial intelligence and automation."@en ;
rdfs:label "AI Tax Policy"@en ;
rdfs:subClassOf ngm:ai-policy ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-labor-market-impact ;
vc:relatedTo ngm:ai-policy ;
vc:relatedTo ngm:policy ;
vc:slug "ai-tax-policy" ;
vc:sourceDomain "governance" .
ngm:ai-technique a owl:Class ;
a skos:Concept ;
rdfs:comment "Taxonomy hub encompassing the principal methods and algorithmic approaches used in artificial intelligence, spanning symbolic, statistical, and neural paradigms. AI Technique organises the broad spectrum of techniques — from classical reasoning and search to contemporary deep learning and generative models — that implement intelligent behaviour in systems."@en ;
rdfs:label "AI Technique"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf _:r22711 ;
rdfs:subClassOf _:r22712 ;
rdfs:subClassOf _:r22713 ;
rdfs:subClassOf _:r22714 ;
rdfs:subClassOf _:r22715 ;
rdfs:subClassOf _:r22716 ;
rdfs:subClassOf _:r22717 ;
rdfs:subClassOf _:r22718 ;
rdfs:subClassOf _:r22719 ;
rdfs:subClassOf _:r22720 ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:computer-vision ;
vc:hasPart ngm:deep-learning ;
vc:hasPart ngm:federated-learning ;
vc:hasPart ngm:generative-ai ;
vc:hasPart ngm:machine-learning-discipline ;
vc:hasPart ngm:natural-language-processing ;
vc:hasPart ngm:reasoning ;
vc:hasPart ngm:reinforcement-learning ;
vc:hasPart ngm:symbolic-ai ;
vc:hasPart ngm:transfer-learning ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:ai-application ;
vc:relatedTo ngm:ai-research-area ;
vc:relatedTo ngm:neural-network ;
vc:slug "ai-technique" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-technology-skills-curriculum a owl:Class ;
rdfs:comment "Structured educational programmes and skill-development resources covering artificial intelligence, machine learning, blockchain, spatial computing, and related technologies. These include MOOCs, short courses, university programmes, professional certifications, and self-directed learning materials that build practitioner capacity across technical and non-technical audiences."@en ;
rdfs:label "AI Technology Skills Curriculum"@en ;
rdfs:subClassOf ngm:software-engineering ;
vc:bridgesTo ngm:blockchain ;
vc:enables ngm:ai-development ;
vc:enables ngm:software-development-process ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:blockchain ;
vc:slug "ai-technology-skills-curriculum" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:education-technology ;
vc:supports ngm:machine-learning-discipline ;
vc:uses ngm:learning-management-system ;
vc:uses ngm:learning-resources .
ngm:ai-testing a skos:Concept ;
rdfs:label "AI Testing"@en .
ngm:ai-timelines a skos:Concept ;
rdfs:label "AI Timelines"@en .
ngm:ai-toolkit a skos:Concept ;
rdfs:label "AI Toolkit"@en .
ngm:ai-traffic-conversion a owl:Class ;
rdfs:comment "The measurement of user engagement and purchase completion rates specifically for sessions initiated or influenced by artificial intelligence interfaces."@en ;
rdfs:label "AI Traffic Conversion"@en ;
rdfs:subClassOf ngm:ai-agents ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-agents ;
vc:relatedTo ngm:ai-shopping-assistant ;
vc:slug "ai-traffic-conversion" ;
vc:sourceDomain "economics" .
ngm:ai-training-data a skos:Concept ;
rdfs:label "AI Training Data"@en .
ngm:ai-training-data-scarcity a owl:Class ;
rdfs:comment "The emerging risk that the decline of human-curated knowledge repositories will reduce the availability of high-quality data for training AI models."@en ;
rdfs:label "AI Training Data Scarcity"@en ;
rdfs:subClassOf ngm:data ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:data-quality ;
vc:relatedTo ngm:knowledge-representation ;
vc:slug "ai-training-data-scarcity" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-training-formats a owl:Class ;
rdfs:comment "The methods and structures used to educate employees on AI tools, including video courses, hands-on labs, and integrated workflows."@en ;
rdfs:label "AI Training Formats"@en ;
rdfs:subClassOf ngm:data-management ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-adoption-metrics ;
vc:relatedTo ngm:enterprise-leadership ;
vc:slug "ai-training-formats" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-training-infrastructure a owl:Class ;
rdfs:comment "The physical and computational resources, including data centers and GPU clusters, required to train large-scale artificial intelligence models."@en ;
rdfs:label "AI Training Infrastructure"@en ;
rdfs:subClassOf ngm:model ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:gpu-compute ;
vc:relatedTo ngm:model ;
vc:relatedTo ngm:training-dataset ;
vc:slug "ai-training-infrastructure" ;
vc:sourceDomain "infrastructure" .
ngm:ai-training-monitoring a owl:Class ;
rdfs:comment "The practice of using specialized tools to observe, debug, and optimize the performance and stability of large-scale machine learning model training runs."@en ;
rdfs:label "AI Training Monitoring"@en ;
rdfs:subClassOf ngm:ai-agents ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-agents ;
vc:relatedTo ngm:large-language-models ;
vc:slug "ai-training-monitoring" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-transparency-framework a owl:Class ;
rdfs:comment "AI Transparency Framework encompasses governance structures, technical standards, and regulatory requirements that ensure artificial intelligence systems are explainable, interpretable, and accountable, enabling stakeholders to understand AI decision-making processes, limitations, and potential i..."@en ;
rdfs:label "Ai Transparency Framework"@en ;
rdfs:subClassOf ngm:ai-governance ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf _:r1530 ;
rdfs:subClassOf _:r1531 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:ai-governance ;
vc:bridgesTo ngm:blockchain ;
vc:enables ngm:algorithmic-accountability ;
vc:enables ngm:explainable-ai ;
vc:enables ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:audit-mechanism ;
vc:requires ngm:audit-mechanisms ;
vc:requires ngm:documentation-standards ;
vc:requires ngm:stakeholder-communication ;
vc:slug "ai-transparency-framework" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-tri-sm a owl:Class ;
rdfs:comment "AI TRiSM (Artificial Intelligence Trust, Risk, and Security Management) is a Gartner-coined framework that integrates technical, organisational, and regulatory controls to ensure AI systems are trustworthy, fair, reliable, and secure throughout their lifecycle. It addresses algorithmic bias, model opacity, data privacy, adversarial vulnerabilities, and compliance with regulations such as the EU AI Act, structured around three pillars: Trust, Risk, and Security."@en ;
rdfs:label "AI TRiSM"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf _:r688 ;
rdfs:subClassOf _:r689 ;
rdfs:subClassOf _:r690 ;
rdfs:subClassOf _:r691 ;
rdfs:subClassOf _:r692 ;
rdfs:subClassOf _:r693 ;
rdfs:subClassOf _:r694 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:ai-agent-system ;
vc:enables ngm:ai-governance ;
vc:enables ngm:responsible-ai ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:ai-audit ;
vc:hasPart ngm:ai-risk-management ;
vc:hasPart ngm:ai-security ;
vc:hasPart ngm:ai-trustworthiness ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:ai-lifecycle ;
vc:relatedTo ngm:ai-regulation ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:red-teaming ;
vc:requires ngm:algorithmic-bias ;
vc:requires ngm:explainable-ai ;
vc:requires ngm:model-robustness ;
vc:slug "ai-tri-sm" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-trust-risk-and-security-management a owl:Class ;
rdfs:comment "A comprehensive governance framework — popularised by Gartner and aligned with the NIST AI Risk Management Framework — for managing the trustworthiness, security, and ethical risks of AI systems throughout their lifecycle. It operationalises three pillars: Trust (transparent, auditable, reliable AI behaviour), Risk (proactive identification and mitigation of algorithmic bias, data quality issues, and regulatory non-compliance), and Security (protection against adversarial attacks, data poisoning, and model integrity threats)."@en ;
rdfs:label "AI Trust Risk and Security Management"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf _:r715 ;
rdfs:subClassOf _:r716 ;
rdfs:subClassOf _:r717 ;
rdfs:subClassOf _:r718 ;
rdfs:subClassOf _:r719 ;
rdfs:subClassOf _:r720 ;
rdfs:subClassOf _:r721 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:ai-agent-system ;
vc:enables ngm:ai-governance ;
vc:enables ngm:responsible-ai ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:ai-audit ;
vc:hasPart ngm:ai-risk-management ;
vc:hasPart ngm:ai-security ;
vc:hasPart ngm:ai-trustworthiness ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:ai-lifecycle ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:red-teaming ;
vc:requires ngm:algorithmic-bias ;
vc:requires ngm:explainable-ai ;
vc:requires ngm:model-robustness ;
vc:slug "ai-trust-risk-and-security-management" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:ai-regulation .
ngm:ai-trustworthiness a owl:Class ;
rdfs:comment "The degree to which an AI system demonstrates characteristics that warrant confidence and reliance, encompassing transparency, explainability, fairness, accountability, robustness, reliability, safety, security, and privacy throughout its lifecycle."@en ;
rdfs:label "AI Trustworthiness"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf _:r729 ;
rdfs:subClassOf _:r730 ;
rdfs:subClassOf _:r731 ;
rdfs:subClassOf _:r732 ;
rdfs:subClassOf _:r733 ;
rdfs:subClassOf _:r734 ;
rdfs:subClassOf _:r735 ;
rdfs:subClassOf _:r736 ;
rdfs:subClassOf _:r737 ;
rdfs:subClassOf _:r738 ;
rdfs:subClassOf _:r739 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:cybersecurity-framework ;
vc:contrastsWith ngm:algorithmic-bias ;
vc:dependsOn ngm:ai-audit ;
vc:dependsOn ngm:conformity-assessment ;
vc:enables ngm:ai-assurance-ai-0102 ;
vc:enables ngm:human-ai-collaboration ;
vc:enables ngm:responsible-ai ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:accountability ;
vc:hasPart ngm:ai-safety ;
vc:hasPart ngm:explainability ;
vc:hasPart ngm:fairness ;
vc:hasPart ngm:robustness ;
vc:implements ngm:nist-ai-rmf ;
vc:implements ngm:oecd-ai-principles ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:gdpr ;
vc:relatedTo ngm:privacy-by-design ;
vc:requires ngm:governance-framework ;
vc:requires ngm:human-oversight ;
vc:requires ngm:risk-management ;
vc:requires ngm:transparency ;
vc:slug "ai-trustworthiness" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:ieee-p-7009 ;
vc:standardizedBy ngm:iso-iec-tr-24028 .
ngm:ai-trustworthiness-dimensions a owl:Class ;
rdfs:comment "AI Trustworthiness Dimensions are the seven interdependent assessment criteria—human agency and oversight, technical robustness and safety, privacy and data governance, transparency and explainability, diversity and non-discrimination and fairness, societal and environmental wellbeing, and accountability—that collectively determine whether an AI system meets the requirements for trustworthy deployment. Established by the EU High-Level Expert Group on AI Ethics Guidelines (2019) and operationalised through the EU AI Act, these dimensions are mutually reinforcing rather than substitutable: satisfying one does not compensate for deficiencies in another."@en ;
rdfs:label "AI Trustworthiness Dimensions"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf _:r722 ;
rdfs:subClassOf _:r723 ;
rdfs:subClassOf _:r724 ;
rdfs:subClassOf _:r725 ;
rdfs:subClassOf _:r726 ;
rdfs:subClassOf _:r727 ;
rdfs:subClassOf _:r728 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:enables ngm:ai-governance-framework ;
vc:enables ngm:trustworthy-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:accountability ;
vc:hasPart ngm:diversity-non-discrimination-and-fairness ;
vc:hasPart ngm:explainability ;
vc:hasPart ngm:human-agency-and-oversight ;
vc:hasPart ngm:societal-and-environmental-wellbeing ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:ai-trustworthiness ;
vc:relatedTo ngm:ethical-ai ;
vc:relatedTo ngm:privacy-by-design ;
vc:requires ngm:ai-risk-management ;
vc:requires ngm:fairness-metrics ;
vc:slug "ai-trustworthiness-dimensions" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-tutor a skos:Concept ;
rdfs:label "AI Tutor"@en .
ngm:ai-upscaling-and-super-resolution a owl:Class ;
rdfs:comment "AI Upscaling and Super-Resolution is a family of deep learning techniques that synthesise plausible high-frequency detail when enlarging images or video frames beyond their native resolution. Methods range from convolutional neural network regressors (SRCNN, ESRGAN) and generative adversarial approaches to diffusion-based reconstruction, enabling applications from consumer photography enhancement to real-time game upscaling (DLSS, FSR) and medical imaging."@en ;
rdfs:label "AI Upscaling and Super-Resolution"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:generative-ai ;
rdfs:subClassOf _:r740 ;
skos:broader ngm:ai-application ;
vc:enables ngm:image-processing-software ;
vc:enables ngm:real-time-rendering ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:super-resolution ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:computer-vision ;
vc:relatedTo ngm:latent-diffusion ;
vc:relatedTo ngm:neural-rendering ;
vc:relatedTo ngm:sc-display-and-rendering ;
vc:slug "ai-upscaling-and-super-resolution" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:convolutional-neural-network ;
vc:uses ngm:deep-learning ;
vc:uses ngm:diffusion-model ;
vc:uses ngm:generative-adversarial-network .
ngm:ai-use-case-portfolio a skos:Concept ;
rdfs:label "AI Use Case Portfolio"@en .
ngm:ai-user a owl:Class ;
rdfs:comment "An individual or entity who interacts with, relies upon, or is affected by the outputs, decisions, or recommendations of an AI system in order to accomplish tasks, obtain services, or achieve objectives—either through direct interaction or indirect exposure to AI-mediated decisions. AI users are the primary experiencers of AI benefits and harms, encompassing diverse populations with varying technical literacy, accessibility needs, and degrees of voluntary engagement, making their rights and interests central to responsible AI governance."@en ;
rdfs:label "AI User"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf _:r741 ;
rdfs:subClassOf _:r742 ;
rdfs:subClassOf _:r743 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:dependsOn ngm:eu-ai-act-regulatory-instrument ;
vc:dependsOn ngm:responsible-ai ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:accountability ;
vc:relatedTo ngm:ai-operator ;
vc:relatedTo ngm:ai-provider ;
vc:requires ngm:explainability ;
vc:requires ngm:fairness ;
vc:requires ngm:human-oversight ;
vc:slug "ai-user" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-user-demographics a owl:Class ;
rdfs:comment "Statistical breakdowns of artificial intelligence adoption rates segmented by geographic, economic, or sociological factors."@en ;
rdfs:label "AI User Demographics"@en ;
rdfs:subClassOf ngm:ai-adoption ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-adoption ;
vc:relatedTo ngm:diffusion-of-innovations-theory ;
vc:relatedTo ngm:technology-acceptance-model ;
vc:slug "ai-user-demographics" ;
vc:sourceDomain "economics" .
ngm:ai-vendor-stack a skos:Concept ;
rdfs:label "AI Vendor Stack"@en .
ngm:ai-venture-capital a owl:Class ;
rdfs:comment "The investment strategies and funding dynamics specific to the AI sector, including valuations and capital allocation for frontier labs."@en ;
rdfs:label "AI Venture Capital"@en ;
rdfs:subClassOf ngm:data-management ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-economics ;
vc:relatedTo ngm:frontier-ai-valuation ;
vc:slug "ai-venture-capital" ;
vc:sourceDomain "economics" .
ngm:ai-verify a skos:Concept ;
rdfs:label "AI Verify"@en .
ngm:ai-verify-foundation a skos:Concept ;
rdfs:label "AI Verify Foundation"@en .
ngm:ai-video a owl:Class ;
rdfs:comment "AI Video, alternatively termed generative video, neural video synthesis, text-to-video (T2V), and image-to-video (I2V), denotes the class of deep generative models and engineering systems that synthesise temporally-coherent moving imagery conditioned on natural-language prompts, reference images,..."@en ;
rdfs:label "AI Video"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:deep-generative-model ;
rdfs:subClassOf ngm:foundation-model ;
rdfs:subClassOf ngm:generative-ai ;
rdfs:subClassOf ngm:multimodal-ai-architecture-ai ;
rdfs:subClassOf ngm:synthetic-media ;
rdfs:subClassOf _:r744 ;
rdfs:subClassOf _:r745 ;
rdfs:subClassOf _:r746 ;
rdfs:subClassOf _:r747 ;
rdfs:subClassOf _:r748 ;
rdfs:subClassOf _:r749 ;
rdfs:subClassOf _:r750 ;
skos:broader ngm:ai-application ;
vc:bridgesTo ngm:synthetic-media ;
vc:contrastsWith ngm:classical-animation ;
vc:contrastsWith ngm:motion-capture ;
vc:contrastsWith ngm:pika ;
vc:contrastsWith ngm:procedural-animation ;
vc:contrastsWith ngm:sora ;
vc:contrastsWith ngm:traditional-vfx-pipeline ;
vc:dependsOn ngm:clip ;
vc:dependsOn ngm:diffusion-model ;
vc:dependsOn ngm:optical-flow ;
vc:dependsOn ngm:probability-theory ;
vc:dependsOn ngm:stochastic-differential-equation ;
vc:dependsOn ngm:transformer ;
vc:dependsOn ngm:vae ;
vc:enables ngm:ai-avatar-synthesis ;
vc:enables ngm:deepfakes ;
vc:enables ngm:image-to-video-generation ;
vc:enables ngm:performance-capture ;
vc:enables ngm:synthetic-advertising ;
vc:enables ngm:synthetic-pre-visualisation ;
vc:enables ngm:text-to-video-generation ;
vc:enables ngm:video-to-video-translation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:classifier-free-guidance ;
vc:hasPart ngm:diffusion-transformer ;
vc:hasPart ngm:sampling-scheduler ;
vc:hasPart ngm:spatiotemporal-autoencoder ;
vc:hasPart ngm:temporal-attention-module ;
vc:hasPart ngm:text-encoder ;
vc:hasPart ngm:video-tokeniser ;
vc:implements ngm:classifier-free-guidance ;
vc:implements ngm:latent-diffusion ;
vc:implements ngm:rectified-flow ;
vc:implements ngm:score-based-generative-modelling ;
vc:implements ngm:spacetime-patch-tokenisation ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:computer-vision ;
vc:relatedTo ngm:diffusion-model ;
vc:relatedTo ngm:digital-twin ;
vc:relatedTo ngm:generative-adversarial-networks ;
vc:relatedTo ngm:generative-ai ;
vc:relatedTo ngm:stable-diffusion-image-model ;
vc:relatedTo ngm:synthetic-media ;
vc:relatedTo ngm:world-model ;
vc:requires ngm:backpropagation ;
vc:requires ngm:captioning-pipeline ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:large-scale-pretraining ;
vc:requires ngm:latent-diffusion ;
vc:requires ngm:video-text-training-corpus ;
vc:slug "ai-video" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:bbc-generative-ai-principles ;
vc:standardizedBy ngm:c2-pa ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:fvd ;
vc:standardizedBy ngm:online-safety-act-2023 ;
vc:standardizedBy ngm:sag-aftra-tv-theatrical-contract ;
vc:standardizedBy ngm:vbench ;
vc:supports ngm:accessibility-captioning ;
vc:supports ngm:advertising ;
vc:supports ngm:corporate-training-video ;
vc:supports ngm:film-pre-visualisation ;
vc:supports ngm:social-media-platform-infrastructure ;
vc:supports ngm:synthetic-data-generation ;
vc:supports ngm:video-dubbing ;
vc:supports ngm:video-game-cinematic ;
vc:uses ngm:adam-optimiser ;
vc:uses ngm:control-net ;
vc:uses ngm:convolution ;
vc:uses ngm:cross-attention ;
vc:uses ngm:lo-ra ;
vc:uses ngm:self-attention ;
vc:uses ngm:vae .
ngm:ai-video-summary a skos:Concept ;
rdfs:label "AI Video Summary"@en .
ngm:ai-voice-synthesis a skos:Concept ;
rdfs:label "AI Voice Synthesis"@en .
ngm:ai-watermarking a skos:Concept ;
rdfs:label "AI Watermarking"@en .
ngm:ai-wearables a owl:Class ;
rdfs:comment "A category of consumer hardware devices that integrate artificial intelligence capabilities directly into wearable form factors such as pendants, glasses, or rings to provide ambient assistance and data capture."@en ;
rdfs:label "AI Wearables"@en ;
rdfs:subClassOf ngm:hardware ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:hardware ;
vc:relatedTo ngm:meta ;
vc:relatedTo ngm:metaverse ;
vc:slug "ai-wearables" ;
vc:sourceDomain "infrastructure" .
ngm:ai-winter a skos:Concept ;
rdfs:label "AI Winter"@en .
ngm:ai-without-dynamics-models a skos:Concept ;
rdfs:label "AI Without Dynamics Models"@en .
ngm:ai-workflow-automation a owl:Class ;
rdfs:comment "The use of AI agents and large language models to automate complex, multi-step business processes and decision-making workflows."@en ;
rdfs:label "AI Workflow Automation"@en ;
rdfs:subClassOf ngm:ai-agents ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-agents ;
vc:relatedTo ngm:workflow-automation ;
vc:slug "ai-workflow-automation" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ai-workforce-impact a owl:Class ;
rdfs:comment "The structural and economic effects of artificial intelligence adoption on labor markets, including job displacement, role transformation, and changes in corporate hiring strategies."@en ;
rdfs:label "AI Workforce Impact"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:autonomous-system ;
vc:relatedTo ngm:intelligent-automation ;
vc:slug "ai-workforce-impact" ;
vc:sourceDomain "economics" .
ngm:ai16z-dao a skos:Concept ;
rdfs:label "Ai16z DAO"@en .
ngm:aia-standards a skos:Concept ;
rdfs:label "Aia Standards"@en .
ngm:aiapplications a owl:Class ;
rdfs:comment "A domain classification encompassing the practical deployment and use cases of artificial intelligence systems across industries, including autonomous systems, decision support, content generation, predictive analytics, and intelligent automation."@en ;
rdfs:label "AIApplications"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:ai-application ;
skos:broader ngm:artificial-intelligence ;
vc:bridgesTo ngm:industry-vertical ;
vc:enables ngm:predictive-analytics ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:ai-capability ;
vc:isPartOf ngm:artificial-intelligence ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:generative-ai ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:natural-language-processing ;
vc:slug "aiapplications" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:application-domain .
ngm:aicafev6 a owl:Class ;
rdfs:comment "AICafev6 is the sixth iteration of the AI Cafe demonstration platform, an open-source immersive knowledge development environment built on VisionFlow that integrates multi-modal AI, GPU-accelerated analytics, and agentic workflows for collaborative knowledge creation and presentation."@en ;
rdfs:label "AICafev6"@en ;
rdfs:subClassOf ngm:infra-computing-and-cloud ;
rdfs:subClassOf _:r792 ;
rdfs:subClassOf _:r793 ;
skos:broader ngm:infra-computing-and-cloud ;
vc:bridgesTo ngm:ai-agent-system ;
vc:enables ngm:agentic-ai ;
vc:enables ngm:natural-language-processing ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:computer-vision ;
vc:hasPart ngm:large-language-models ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:computer-vision ;
vc:slug "aicafev6" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:ai-agent-system ;
vc:uses ngm:generative-ai ;
vc:uses ngm:large-language-models .
ngm:aicpa a skos:Concept ;
rdfs:label "Aicpa"@en .
ngm:aicpa-digital-asset-practice-aid-2022 a skos:Concept ;
rdfs:label "Aicpa Digital Asset Practice Aid 2022"@en .
ngm:aider a skos:Concept ;
rdfs:label "Aider"@en .
ngm:aies a skos:Concept ;
rdfs:label "Aies"@en .
ngm:aiethics a owl:Class ;
rdfs:comment "A framework of ethical principles and governance structures ensuring responsible development, deployment, and oversight of artificial intelligence systems in compliance with societal values. Addresses fairness, accountability, transparency, bias mitigation, privacy preservation, and alignment with human rights norms across the AI lifecycle from design through decommissioning."@en ;
rdfs:label "AIEthics"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf _:r794 ;
rdfs:subClassOf _:r795 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:ai-agent-system ;
vc:contrastsWith ngm:artificial-superintelligence-theory ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:ai-risk ;
vc:relatedTo ngm:governance ;
vc:requires ngm:accountability ;
vc:requires ngm:ai-governance-and-ethics ;
vc:slug "aiethics" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:ai-safety ;
vc:supports ngm:regulatory-compliance ;
vc:supports ngm:transparency-notice .
ngm:aiethicsdomain a skos:Concept ;
rdfs:label "Aiethicsdomain"@en .
ngm:aigovernanceprinciple a skos:Concept ;
rdfs:label "Aigovernanceprinciple"@en .
ngm:aime a skos:Concept ;
rdfs:label "Aime"@en .
ngm:aime-benchmark a skos:Concept ;
rdfs:label "Aime Benchmark"@en .
ngm:aiohttp a skos:Concept ;
rdfs:label "Aiohttp"@en .
ngm:aiops a owl:Class ;
rdfs:comment "AIOps (Artificial Intelligence for IT Operations) applies machine learning, natural language processing, and big data analytics to automate and enhance IT operational tasks including event correlation, anomaly detection, root-cause analysis, incident management, and capacity planning. By continuously ingesting telemetry streams — logs, metrics, and traces — from complex distributed systems, AIOps platforms surface actionable insights that would be impossible for human operators to detect at scale, progressively shifting operations from reactive incident response towards predictive and autonomous self-healing."@en ;
rdfs:label "AIOps"@en ;
rdfs:subClassOf ngm:ai-infrastructure ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf _:r796 ;
rdfs:subClassOf _:r797 ;
rdfs:subClassOf _:r798 ;
rdfs:subClassOf _:r799 ;
rdfs:subClassOf _:r800 ;
rdfs:subClassOf _:r801 ;
skos:broader ngm:artificial-intelligence ;
vc:enables ngm:operational-resilience ;
vc:enables ngm:platform-engineering ;
vc:enables ngm:workflow-automation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ai-incident ;
vc:hasPart ngm:ai-monitoring ;
vc:hasPart ngm:anomaly-detection ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:cloud-native-applications ;
vc:relatedTo ngm:edge-computing ;
vc:requires ngm:data-pipeline ;
vc:requires ngm:machine-learning-discipline ;
vc:requires ngm:natural-language-processing ;
vc:slug "aiops" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:microservices-architecture ;
vc:supports ngm:monitoring-dashboard ;
vc:uses ngm:deep-learning ;
vc:uses ngm:event-driven-architecture ;
vc:uses ngm:predictive-analytics .
ngm:air-compressor a skos:Concept ;
rdfs:label "Air Compressor"@en .
ngm:air-gap a owl:Class ;
rdfs:comment "An air gap is a security measure that physically isolates a computer or storage device from unsecured networks, including the public internet and any networked device. In the context of cryptocurrency custody, an air-gapped device holds private keys and signs transactions while never establishing a live network connection, transferring data only through media such as QR codes or removable storage. This isolation dramatically reduces the remote attack surface available to adversaries."@en ;
rdfs:label "Air Gap"@en ;
rdfs:subClassOf ngm:cold-storage ;
rdfs:subClassOf _:r1532 ;
vc:bridgesTo ngm:secure-enclave ;
vc:contrastsWith ngm:hardware-wallet ;
vc:contrastsWith ngm:network-security ;
vc:dependsOn ngm:private-key ;
vc:enables ngm:self-custody ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:cold-storage ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:multisignature ;
vc:relatedTo ngm:self-custody ;
vc:relatedTo ngm:threat-model ;
vc:requires ngm:hardware-security-module ;
vc:slug "air-gap" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:key-management ;
vc:supports ngm:security ;
vc:uses ngm:cryptographic-key ;
vc:uses ngm:private-key .
ngm:air-gapped-computer a skos:Concept ;
rdfs:label "Air Gapped Computer"@en .
ngm:air-quality-monitoring a owl:Class ;
rdfs:label "Air Quality Monitoring"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-applications ;
vc:slug "air-quality-monitoring" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:air-supply-system a skos:Concept ;
rdfs:label "Air Supply System"@en .
ngm:air-traffic-control a skos:Concept ;
rdfs:label "Air Traffic Control"@en .
ngm:air-traffic-management a skos:Concept ;
rdfs:label "Air Traffic Management"@en .
ngm:air-typing a skos:Concept ;
rdfs:label "Air Typing"@en .
ngm:airborne-remote-sensing a owl:Class ;
rdfs:label "Airborne Remote Sensing"@en ;
rdfs:subClassOf ngm:remote-sensing ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation ;
vc:slug "airborne-remote-sensing" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:airbyte a skos:Concept ;
rdfs:label "Airbyte"@en .
ngm:airdrop a owl:Class ;
rdfs:comment "An Airdrop is a token distribution mechanism in which a blockchain project allocates free tokens to a set of wallet addresses, typically to bootstrap a community, reward early users or decentralise ownership. Eligibility may be based on prior on-chain activity, holdings of another asset or completion of tasks. Airdrops are a marketing and governance tool but attract Sybil attacks that the project must mitigate."@en ;
rdfs:label "Airdrop"@en ;
rdfs:subClassOf ngm:token-distribution ;
vc:contrastsWith ngm:initial-coin-offering ;
vc:dependsOn ngm:blockchain ;
vc:dependsOn ngm:gas-fee ;
vc:enables ngm:de-fi ;
vc:enables ngm:governance-token ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:token-distribution ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:cryptocurrency-token ;
vc:relatedTo ngm:staking ;
vc:relatedTo ngm:tokenomics ;
vc:slug "airdrop" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:sybil-attack ;
vc:uses ngm:crypto-wallet ;
vc:uses ngm:token .
ngm:airl a skos:Concept ;
rdfs:label "Airl"@en .
ngm:aisafety a skos:Concept ;
rdfs:label "Aisafety"@en .
ngm:aisi a owl:Class ;
rdfs:comment "The AI Safety Institute is a UK government body that evaluates advanced AI systems for safety and security risks. It was established to test frontier models and inform policy."@en ;
rdfs:label "AISI"@en ;
rdfs:subClassOf ngm:ai-safety ;
vc:bridgesTo ngm:frontier-ai ;
vc:enables ngm:ai-governance ;
vc:enables ngm:ai-regulation ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:slug "aisi" ;
vc:sourceDomain "governance" .
ngm:aisi-frontier-ai-safety-framework a owl:Class ;
rdfs:comment "A structured evaluation and oversight framework produced by the UK AI Safety Institute (AISI) to assess the catastrophic risks posed by frontier AI models prior to and following their public release. The framework specifies pre-deployment testing protocols, thresholds for dangerous capability uplift, and post-deployment monitoring obligations that developers of frontier models are expected to satisfy. It represents the UK government's primary technical instrument for operationalising AI safety commitments made at the Bletchley Park AI Safety Summit of November 2023."@en ;
rdfs:label "AISI Frontier AI Safety Framework"@en ;
rdfs:subClassOf ngm:ai-governance-framework ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:frontier-ai ;
vc:relatedTo ngm:frontier-model-forum ;
vc:slug "aisi-frontier-ai-safety-framework" ;
vc:sourceDomain "governance" ;
vc:supports ngm:ai-regulation ;
vc:supports ngm:ai-safety ;
vc:uses ngm:adversarial-testing ;
vc:uses ngm:model-evaluation ;
vc:uses ngm:red-teaming .
ngm:aistats a skos:Concept ;
rdfs:label "Aistats"@en .
ngm:aisystem a owl:Class ;
rdfs:comment "A comprehensive system architecture comprising machine learning models, data pipelines, inference engines, and deployment infrastructure that enables intelligent decision-making and automation across diverse application domains."@en ;
rdfs:label "AISystem"@en ;
rdfs:subClassOf ngm:ai-infrastructure ;
rdfs:subClassOf _:r802 ;
rdfs:subClassOf _:r803 ;
rdfs:subClassOf _:r804 ;
vc:bridgesTo ngm:ai-agent-system ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:machine-learning-model ;
vc:hasPart ngm:neural-network ;
vc:qualityScore "0.4"^^xsd:float ;
vc:requires ngm:ai-agent-system ;
vc:slug "aisystem" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:aiethics ;
vc:supports ngm:governance-framework ;
vc:uses ngm:computer-vision ;
vc:uses ngm:natural-language-processing .
ngm:akash-network a skos:Concept ;
rdfs:label "Akash Network"@en .
ngm:akka-framework a skos:Concept ;
rdfs:label "Akka Framework"@en .
ngm:aladdin-platform a skos:Concept ;
rdfs:label "Aladdin Platform"@en .
ngm:alan-turing a skos:Concept ;
rdfs:label "Alan Turing"@en .
ngm:alan-turing-institute a owl:Class ;
rdfs:comment "The United Kingdom's national institute for data science and artificial intelligence, founded in 2015 and headquartered in London, convening research across partner universities and applying AI and data science methods to challenges in health, defence, security, and the public sector."@en ;
rdfs:label "Alan Turing Institute"@en ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf ngm:entity ;
rdfs:subClassOf ngm:research-institute ;
rdfs:subClassOf _:r1533 ;
rdfs:subClassOf _:r1534 ;
rdfs:subClassOf _:r1535 ;
rdfs:subClassOf _:r1536 ;
rdfs:subClassOf _:r1537 ;
rdfs:subClassOf _:r1538 ;
rdfs:subClassOf _:r1539 ;
rdfs:subClassOf _:r1540 ;
rdfs:subClassOf _:r1541 ;
rdfs:subClassOf _:r1542 ;
skos:broader ngm:ai-research-area ;
vc:bridgesTo ngm:ai-governance ;
vc:bridgesTo ngm:climate-science ;
vc:bridgesTo ngm:defence-and-security ;
vc:bridgesTo ngm:digital-health ;
vc:bridgesTo ngm:national-security ;
vc:bridgesTo ngm:public-sector-ai ;
vc:contrastsWith ngm:ai-safety ;
vc:contrastsWith ngm:ai-safety-research ;
vc:dependsOn ngm:imperial-college-london ;
vc:dependsOn ngm:uk-research-and-innovation ;
vc:dependsOn ngm:university-college-london ;
vc:dependsOn ngm:university-of-cambridge ;
vc:dependsOn ngm:university-of-edinburgh ;
vc:dependsOn ngm:university-of-manchester ;
vc:dependsOn ngm:university-of-oxford ;
vc:enables ngm:ai-ethics ;
vc:enables ngm:artificial-intelligence ;
vc:enables ngm:computer-vision ;
vc:enables ngm:data-science ;
vc:enables ngm:machine-learning-discipline ;
vc:enables ngm:natural-language-processing ;
vc:enables ngm:responsible-ai ;
vc:enables ngm:statistical-learning-theory ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ai-safety-research ;
vc:hasPart ngm:algorithmic-fairness ;
vc:hasPart ngm:computer-vision ;
vc:hasPart ngm:explainable-ai ;
vc:hasPart ngm:federated-learning ;
vc:hasPart ngm:foundation-model ;
vc:hasPart ngm:natural-language-processing ;
vc:hasPart ngm:privacy-preserving-machine-learning ;
vc:hasPart ngm:probabilistic-programming ;
vc:hasPart ngm:statistical-learning-theory ;
vc:implements ngm:open-data ;
vc:implements ngm:reproducible-research ;
vc:implements ngm:uk-national-ai-strategy ;
vc:isPartOf ngm:uk-national-ai-strategy ;
vc:qualityScore "0.88"^^xsd:float ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:alan-turing ;
vc:relatedTo ngm:algorithmic-bias ;
vc:relatedTo ngm:algorithmic-fairness ;
vc:relatedTo ngm:explainable-ai ;
vc:relatedTo ngm:research-institute ;
vc:relatedTo ngm:responsible-ai ;
vc:relatedTo ngm:uk-national-ai-strategy ;
vc:slug "alan-turing-institute" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:uk-research-and-innovation ;
vc:supports ngm:climate-science ;
vc:supports ngm:computer-vision ;
vc:supports ngm:digital-health ;
vc:supports ngm:drug-discovery ;
vc:supports ngm:natural-language-processing ;
vc:supports ngm:open-data ;
vc:supports ngm:public-sector-ai ;
vc:supports ngm:reproducible-research ;
vc:supports ngm:weather-prediction ;
vc:uses ngm:data-science ;
vc:uses ngm:federated-learning ;
vc:uses ngm:foundation-model ;
vc:uses ngm:open-source-software ;
vc:uses ngm:probabilistic-programming ;
vc:uses ngm:statistical-learning-theory .
ngm:alastria-network a skos:Concept ;
rdfs:label "Alastria Network"@en .
ngm:albert a owl:Class ;
rdfs:comment "A Lite BERT: a parameter-efficient transformer variant that uses factorised embedding parameterisation and cross-layer parameter sharing to achieve 18x fewer parameters than BERT-large whilst matching or exceeding its performance on NLP benchmarks such as GLUE, SQuAD, and RACE."@en ;
rdfs:label "ALBERT"@en ;
rdfs:subClassOf ngm:ai-model-architecture ;
skos:broader ngm:ai-model-architecture ;
vc:bridgesTo ngm:ai-agent-system ;
vc:contrastsWith ngm:ro-berta ;
vc:enables ngm:fine-tuning ;
vc:enables ngm:transfer-learning ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:lo-ra-do-ra-etc ;
vc:slug "albert" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:transformer-architecture .
ngm:alc a skos:Concept ;
rdfs:label "Alc"@en .
ngm:alc-with-transitivity a skos:Concept ;
rdfs:label "Alc With Transitivity"@en .
ngm:alchemy a skos:Concept ;
rdfs:label "Alchemy"@en .
ngm:aleks a skos:Concept ;
rdfs:label "Aleks"@en .
ngm:aleksandr-lyapunov a skos:Concept ;
rdfs:label "Aleksandr Lyapunov"@en .
ngm:alembic a skos:Concept ;
rdfs:label "Alembic"@en .
ngm:aleo a owl:Class ;
rdfs:comment "Aleo is a blockchain platform designed for private applications using zero-knowledge proofs to keep transaction data confidential while remaining verifiable. Programs are written in its Leo language."@en ;
rdfs:label "Aleo"@en ;
rdfs:subClassOf ngm:zero-knowledge-proof ;
rdfs:subClassOf _:r1543 ;
rdfs:subClassOf _:r1544 ;
vc:bridgesTo ngm:blockchain ;
vc:enables ngm:privacy ;
vc:enables ngm:pseudonymity ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:cryptography ;
vc:requires ngm:zero-knowledge-proof ;
vc:slug "aleo" ;
vc:sourceDomain "blockchain" .
ngm:aleph-alpha a skos:Concept ;
rdfs:label "Aleph Alpha"@en .
ngm:alert-fatigue a skos:Concept ;
rdfs:label "Alert Fatigue"@en .
ngm:alert-management a skos:Concept ;
rdfs:label "Alert Management"@en .
ngm:alert-system a skos:Concept ;
rdfs:label "Alert System"@en .
ngm:alert-thresholds a skos:Concept ;
rdfs:label "Alert Thresholds"@en .
ngm:alerting a owl:Class ;
rdfs:comment "Alerting is the observability capability that evaluates monitored signals against defined conditions and notifies responsible humans or automated systems when those conditions indicate a problem or an impending one. It converts continuous telemetry into discrete, actionable notifications routed to the appropriate on-call recipient. Effective alerting balances sensitivity against noise so that every alert is meaningful and timely."@en ;
rdfs:label "Alerting"@en ;
rdfs:subClassOf ngm:observability ;
rdfs:subClassOf _:r1545 ;
vc:enables ngm:incident-reporting ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:alert-fatigue ;
vc:hasPart ngm:notification ;
vc:isPartOf ngm:observability ;
vc:isPartOf ngm:real-time-monitoring ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:distributed-tracing ;
vc:relatedTo ngm:service-level-agreement ;
vc:requires ngm:monitoring ;
vc:slug "alerting" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:incident-management ;
vc:supports ngm:root-cause-analysis ;
vc:supports ngm:site-reliability-engineering ;
vc:uses ngm:anomaly-detection ;
vc:uses ngm:service-level-objective ;
vc:uses ngm:telemetry .
ngm:alerting-system a skos:Concept ;
rdfs:label "Alerting System"@en .
ngm:alethea-agent a owl:Class ;
rdfs:comment "An autonomous AI agent designed to generate and verify novel proofs in pure mathematics, integrated into Google's Deep Think model."@en ;
rdfs:label "Alethea Agent"@en ;
rdfs:subClassOf ngm:model ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:deep-think ;
vc:relatedTo ngm:model ;
vc:slug "alethea-agent" ;
vc:sourceDomain "artificial-intelligence" .
ngm:algebraic-circuits a skos:Concept ;
rdfs:label "Algebraic Circuits"@en .
ngm:algebraic-equations a skos:Concept ;
rdfs:label "Algebraic Equations"@en .
ngm:algebraic-geometry a skos:Concept ;
rdfs:label "Algebraic Geometry"@en .
ngm:algebraic-topology a skos:Concept ;
rdfs:label "Algebraic Topology"@en .
ngm:algorand a owl:Class ;
rdfs:comment "Algorand is a permissionless, pure proof-of-stake Layer 1 blockchain protocol designed by MIT cryptographer Silvio Micali, providing instant transaction finality, high throughput, and carbon-negative operation through a cryptographically random committee-selection consensus mechanism. It resolves the blockchain trilemma of security, scalability, and decentralisation without forks by ensuring all confirmed blocks are final. The Algorand Virtual Machine (AVM) supports smart contract execution in TEAL bytecode and, via ARC standards, enables NFTs, DeFi, and tokenised assets at scale."@en ;
rdfs:label "Algorand"@en ;
rdfs:subClassOf ngm:blockchain-protocol ;
rdfs:subClassOf _:r1546 ;
vc:bridgesTo ngm:digital-identity ;
vc:bridgesTo ngm:financial-technology ;
vc:contrastsWith ngm:delegated-proof-of-stake ;
vc:contrastsWith ngm:proof-of-work ;
vc:enables ngm:asset-tokenisation ;
vc:enables ngm:central-bank-digital-currency-cbdc ;
vc:enables ngm:de-fi ;
vc:enables ngm:decentralized-application ;
vc:enables ngm:non-fungible-token ;
vc:enables ngm:smart-contract ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:on-chain-governance ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:blockchain-interoperability ;
vc:relatedTo ngm:blockchain-scalability ;
vc:relatedTo ngm:state-proof ;
vc:requires ngm:distributed-ledger ;
vc:slug "algorand" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:cross-border-payments ;
vc:supports ngm:real-world-asset-tokenisation ;
vc:supports ngm:stablecoin ;
vc:supports ngm:zero-knowledge-proof ;
vc:uses ngm:byzantine-agreement ;
vc:uses ngm:consensus-mechanism ;
vc:uses ngm:cryptographic-sortition ;
vc:uses ngm:pure-proof-of-stake ;
vc:uses ngm:verifiable-random-function .
ngm:algorand-standard-asset a skos:Concept ;
rdfs:label "Algorand Standard Asset"@en .
ngm:algorithm a owl:Class ;
rdfs:comment "A finite, deterministic sequence of instructions or rules that solves a computational problem or performs a transformation on data. In AI and blockchain contexts algorithms encompass learning procedures, consensus rules, cryptographic primitives, and optimisation methods that underpin intelligent systems and distributed ledgers."@en ;
rdfs:label "Algorithm"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:computational-model ;
rdfs:subClassOf _:r1565 ;
rdfs:subClassOf _:r1566 ;
rdfs:subClassOf _:r1567 ;
rdfs:subClassOf _:r1568 ;
rdfs:subClassOf _:r1569 ;
rdfs:subClassOf _:r1570 ;
rdfs:subClassOf _:r1571 ;
rdfs:subClassOf _:r1572 ;
rdfs:subClassOf _:r1573 ;
rdfs:subClassOf _:r1574 ;
rdfs:subClassOf _:r1575 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:robotic-process-automation ;
vc:bridgesTo ngm:smart-contract ;
vc:contrastsWith ngm:heuristic-methods ;
vc:dependsOn ngm:formal-language ;
vc:dependsOn ngm:mathematical-logic ;
vc:enables ngm:automation ;
vc:enables ngm:blockchain ;
vc:enables ngm:computer-vision ;
vc:enables ngm:deep-learning ;
vc:enables ngm:inference ;
vc:enables ngm:machine-learning-discipline ;
vc:enables ngm:machine-learning-model ;
vc:enables ngm:natural-language-processing ;
vc:enables ngm:optimisation ;
vc:enables ngm:reinforcement-learning ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:approximation-algorithm ;
vc:hasPart ngm:backpropagation ;
vc:hasPart ngm:consensus-algorithm ;
vc:hasPart ngm:divide-and-conquer ;
vc:hasPart ngm:dynamic-programming ;
vc:hasPart ngm:gradient-descent ;
vc:hasPart ngm:graph-algorithm ;
vc:hasPart ngm:greedy-algorithm ;
vc:hasPart ngm:hash-function ;
vc:hasPart ngm:parallel-algorithm ;
vc:hasPart ngm:probabilistic-algorithm ;
vc:hasPart ngm:recursive-algorithm ;
vc:hasPart ngm:search-algorithm ;
vc:hasPart ngm:sorting-algorithm ;
vc:implements ngm:turing-machine ;
vc:isPartOf ngm:algorithmic-framework ;
vc:isPartOf ngm:computational-model ;
vc:isPartOf ngm:software-system ;
vc:qualityScore "0.92"^^xsd:float ;
vc:relatedTo ngm:algorithmic-accountability ;
vc:relatedTo ngm:algorithmic-bias ;
vc:relatedTo ngm:algorithmic-framework ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:quantum-computation-paradigm ;
vc:requires ngm:computational-complexity-theory ;
vc:requires ngm:data-structure ;
vc:requires ngm:formal-language ;
vc:requires ngm:mathematical-logic ;
vc:slug "algorithm" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:ieee ;
vc:standardizedBy ngm:nist ;
vc:supports ngm:artificial-intelligence ;
vc:supports ngm:cryptography ;
vc:supports ngm:neural-network ;
vc:supports ngm:transformer-architecture ;
vc:uses ngm:data-structure ;
vc:uses ngm:heuristic-methods ;
vc:uses ngm:inference .
ngm:algorithm-design a skos:Concept ;
rdfs:label "Algorithm Design"@en .
ngm:algorithm-filing a skos:Concept ;
rdfs:label "Algorithm Filing"@en .
ngm:algorithm-layer a owl:Class ;
rdfs:comment "The Algorithm Layer is the architectural stratum that defines the computational methods, procedures, and decision logic operating above the data and protocol layers. It encompasses the design, selection, and composition of algorithms — sorting, search, optimisation, consensus, cryptographic, and learning algorithms — that transform inputs into outputs under defined correctness and complexity guarantees."@en ;
rdfs:label "Algorithm Layer"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:algorithm ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf _:r1547 ;
rdfs:subClassOf _:r1548 ;
rdfs:subClassOf _:r1549 ;
rdfs:subClassOf _:r1550 ;
rdfs:subClassOf _:r1551 ;
rdfs:subClassOf _:r1552 ;
rdfs:subClassOf _:r1553 ;
rdfs:subClassOf _:r1554 ;
rdfs:subClassOf _:r1555 ;
rdfs:subClassOf _:r1556 ;
rdfs:subClassOf _:r1557 ;
rdfs:subClassOf _:r1558 ;
rdfs:subClassOf _:r1559 ;
rdfs:subClassOf _:r1560 ;
rdfs:subClassOf _:r1561 ;
rdfs:subClassOf _:r1562 ;
rdfs:subClassOf _:r1563 ;
rdfs:subClassOf _:r1564 ;
skos:broader ngm:ai-technique ;
skos:broader ngm:artificial-intelligence ;
vc:bridgesTo ngm:algorithmic-complexity ;
vc:bridgesTo ngm:computational-complexity-theory ;
vc:bridgesTo ngm:model-layer ;
vc:contrastsWith ngm:algorithmic-layer ;
vc:contrastsWith ngm:compute-layer ;
vc:dependsOn ngm:computational-complexity-theory ;
vc:dependsOn ngm:data-structure ;
vc:dependsOn ngm:mathematical-logic ;
vc:enables ngm:algorithmic-fairness ;
vc:enables ngm:application-layer ;
vc:enables ngm:artificial-intelligence ;
vc:enables ngm:inference-layer ;
vc:enables ngm:machine-learning-discipline ;
vc:enables ngm:model-architecture-layer ;
vc:enables ngm:model-layer ;
vc:enables ngm:probabilistic-programming ;
vc:enables ngm:scalability ;
vc:enables ngm:training-layer ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:backpropagation ;
vc:hasPart ngm:consensus-algorithm ;
vc:hasPart ngm:cryptographic-algorithm ;
vc:hasPart ngm:dynamic-programming ;
vc:hasPart ngm:gradient-descent ;
vc:hasPart ngm:graph-algorithms ;
vc:hasPart ngm:inference-algorithm ;
vc:hasPart ngm:learning-algorithm ;
vc:hasPart ngm:monte-carlo-methods ;
vc:hasPart ngm:numerical-methods ;
vc:hasPart ngm:optimisation ;
vc:hasPart ngm:search-algorithm ;
vc:hasPart ngm:sorting-algorithm ;
vc:implements ngm:attention-mechanism ;
vc:implements ngm:automatic-differentiation ;
vc:implements ngm:backpropagation ;
vc:implements ngm:gradient-descent ;
vc:implements ngm:stochastic-gradient-descent ;
vc:implements ngm:transformer-architecture ;
vc:implements ngm:turing-machine ;
vc:qualityScore "0.88"^^xsd:float ;
vc:relatedTo ngm:algorithmic-layer ;
vc:relatedTo ngm:attention-mechanism ;
vc:relatedTo ngm:backpropagation ;
vc:relatedTo ngm:evolutionary-algorithm ;
vc:relatedTo ngm:learning-algorithm ;
vc:relatedTo ngm:neural-architecture-search ;
vc:relatedTo ngm:transformer-architecture ;
vc:requires ngm:algorithmic-complexity ;
vc:requires ngm:compute-layer ;
vc:requires ngm:data-layer ;
vc:requires ngm:data-structure ;
vc:requires ngm:mathematical-logic ;
vc:requires ngm:turing-machine ;
vc:slug "algorithm-layer" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:ieee ;
vc:standardizedBy ngm:nist ;
vc:supports ngm:artificial-intelligence ;
vc:supports ngm:evolutionary-algorithm ;
vc:supports ngm:machine-learning-discipline ;
vc:supports ngm:model-training ;
vc:supports ngm:neural-architecture-search ;
vc:supports ngm:probabilistic-programming ;
vc:uses ngm:algorithmic-complexity ;
vc:uses ngm:automatic-differentiation ;
vc:uses ngm:data-structure ;
vc:uses ngm:dynamic-programming ;
vc:uses ngm:monte-carlo-methods .
ngm:algorithm-registry a skos:Concept ;
rdfs:label "Algorithm Registry"@en .
ngm:algorithm-selection a skos:Concept ;
rdfs:label "Algorithm Selection"@en .
ngm:algorithmic-accountability a owl:Class ;
rdfs:comment "Algorithmic Accountability is a responsibility framework ensuring that AI systems and their developers are answerable for decisions, outcomes, and societal impacts produced by algorithmic processes. It encompasses mechanisms for redress, transparency, auditing, and oversight to prevent undue harm from automated decision-making."@en ;
rdfs:label "Algorithmic Accountability"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:aigovernanceprinciple ;
rdfs:subClassOf ngm:ethical-framework ;
rdfs:subClassOf ngm:regulatory-compliance ;
rdfs:subClassOf _:r1576 ;
rdfs:subClassOf _:r1577 ;
rdfs:subClassOf _:r1578 ;
rdfs:subClassOf _:r1579 ;
rdfs:subClassOf _:r1580 ;
rdfs:subClassOf _:r1581 ;
rdfs:subClassOf _:r1582 ;
rdfs:subClassOf _:r1583 ;
rdfs:subClassOf _:r1584 ;
rdfs:subClassOf _:r1585 ;
rdfs:subClassOf _:r1586 ;
rdfs:subClassOf _:r1587 ;
rdfs:subClassOf _:r1588 ;
rdfs:subClassOf _:r1589 ;
rdfs:subClassOf _:r1590 ;
rdfs:subClassOf _:r1591 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:digital-rights ;
vc:bridgesTo ngm:smart-contract ;
vc:contrastsWith ngm:black-box-model ;
vc:dependsOn ngm:algorithm ;
vc:dependsOn ngm:automated-decision-making ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:model-documentation ;
vc:enables ngm:accountability ;
vc:enables ngm:ai-fairness ;
vc:enables ngm:ai-impact-assessment ;
vc:enables ngm:digital-rights ;
vc:enables ngm:fairness ;
vc:enables ngm:public-sector-ai ;
vc:enables ngm:trustworthy-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ai-impact-assessment ;
vc:hasPart ngm:ai-model-card ;
vc:hasPart ngm:algorithmic-auditing ;
vc:hasPart ngm:audit-mechanism ;
vc:hasPart ngm:audit-trail ;
vc:hasPart ngm:bias-detection-methods ;
vc:hasPart ngm:impact-assessment ;
vc:hasPart ngm:model-documentation ;
vc:hasPart ngm:redress-mechanism ;
vc:implements ngm:aigovernanceprinciple ;
vc:implements ngm:ethical-framework ;
vc:implements ngm:regulatory-compliance ;
vc:isPartOf ngm:ai-governance ;
vc:isPartOf ngm:ai-governance-and-ethics ;
vc:isPartOf ngm:aiethicsdomain ;
vc:isPartOf ngm:responsible-ai ;
vc:isPartOf ngm:trustworthy-ai ;
vc:qualityScore "0.93"^^xsd:float ;
vc:relatedTo ngm:ai-fairness ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:algorithmic-bias ;
vc:relatedTo ngm:data-protection ;
vc:relatedTo ngm:gdpr ;
vc:relatedTo ngm:risk-based-regulation ;
vc:requires ngm:audit-trail ;
vc:requires ngm:data-governance ;
vc:requires ngm:explainability ;
vc:requires ngm:explainable-ai ;
vc:requires ngm:human-oversight ;
vc:requires ngm:model-documentation ;
vc:requires ngm:transparency ;
vc:slug "algorithmic-accountability" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:ieee-p2863 ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:ai-ethics ;
vc:supports ngm:ai-governance ;
vc:supports ngm:ai-risk-management ;
vc:supports ngm:human-oversight ;
vc:uses ngm:algorithmic-auditing ;
vc:uses ngm:bias-detection-methods ;
vc:uses ngm:counterfactual-explanation ;
vc:uses ngm:explainable-ai ;
vc:uses ngm:model-interpretability .
ngm:algorithmic-amplification a skos:Concept ;
rdfs:label "Algorithmic Amplification"@en .
ngm:algorithmic-auditing a owl:Class ;
rdfs:comment "Algorithmic auditing is the systematic evaluation of automated decision-making systems to assess their fairness, accuracy, transparency, and compliance with ethical and legal standards. It involves independent or internal review of training data, model architectures, outputs, and operational impacts. The discipline has emerged as a response to concerns about bias, discrimination, and opacity in AI-driven systems. Audits may be prospective, examining systems before deployment, or retrospective, investigating outcomes in production. Results are used to inform regulation, remediation, and public accountability."@en ;
rdfs:label "Algorithmic Auditing"@en ;
rdfs:subClassOf ngm:ai-governance ;
rdfs:subClassOf _:r1592 ;
rdfs:subClassOf _:r1593 ;
vc:bridgesTo ngm:data-governance ;
vc:bridgesTo ngm:security-audit ;
vc:contrastsWith ngm:black-box-ai ;
vc:contrastsWith ngm:self-certification ;
vc:enables ngm:accountability ;
vc:enables ngm:regulatory-compliance ;
vc:enables ngm:responsible-ai ;
vc:enables ngm:trustworthy-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:eu-ai-act-regulatory-instrument ;
vc:implements ngm:nist-ai-rmf ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:ai-fairness ;
vc:relatedTo ngm:algorithmic-accountability ;
vc:relatedTo ngm:algorithmic-bias ;
vc:requires ngm:audit-trail ;
vc:requires ngm:transparency ;
vc:slug "algorithmic-auditing" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:supports ngm:accountability ;
vc:supports ngm:ai-governance-framework ;
vc:supports ngm:ai-regulation ;
vc:uses ngm:bias-detection-methods ;
vc:uses ngm:counterfactual-analysis ;
vc:uses ngm:explainable-ai ;
vc:uses ngm:statistical-testing .
ngm:algorithmic-bias a owl:Class ;
rdfs:comment "Systematic and repeatable errors in AI systems that create unfair outcomes favouring or discriminating against particular groups or individuals. Bias manifests through historical bias, representation gaps, measurement proxies, aggregation errors, and feedback loops, and is detected through statistical auditing, counterfactual testing, and fairness metrics."@en ;
rdfs:label "Algorithmic Bias"@en ;
rdfs:subClassOf ngm:ai-ethics ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf _:r1600 ;
rdfs:subClassOf _:r1601 ;
rdfs:subClassOf _:r1602 ;
rdfs:subClassOf _:r1603 ;
rdfs:subClassOf _:r1604 ;
rdfs:subClassOf _:r1605 ;
rdfs:subClassOf _:r1606 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:smart-contract ;
vc:contrastsWith ngm:algorithmic-fairness ;
vc:contrastsWith ngm:fairness-constraints ;
vc:contrastsWith ngm:responsible-ai ;
vc:dependsOn ngm:automated-decision-making ;
vc:dependsOn ngm:data-collection ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:enables ngm:ai-fairness ;
vc:enables ngm:algorithmic-accountability ;
vc:enables ngm:algorithmic-auditing ;
vc:enables ngm:algorithmic-fairness ;
vc:enables ngm:bias-mitigation-techniques ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:aggregation-bias ;
vc:hasPart ngm:bias-detection-methods ;
vc:hasPart ngm:fairness-metrics ;
vc:hasPart ngm:feedback-loop-bias ;
vc:hasPart ngm:historical-bias ;
vc:hasPart ngm:measurement-bias ;
vc:hasPart ngm:representation-bias ;
vc:implements ngm:algorithmic-impact-assessment ;
vc:implements ngm:fairness-constraints ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:ai-fairness ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:algorithmic-bias-and-variance ;
vc:relatedTo ngm:algorithmic-fairness ;
vc:relatedTo ngm:automated-decision-making ;
vc:relatedTo ngm:automation-bias ;
vc:relatedTo ngm:bias ;
vc:relatedTo ngm:bias-and-fairness ;
vc:relatedTo ngm:bias-in-large-language-models ;
vc:relatedTo ngm:differential-privacy ;
vc:relatedTo ngm:explainability ;
vc:relatedTo ngm:fairness ;
vc:relatedTo ngm:harmful-bias ;
vc:relatedTo ngm:model-evaluation ;
vc:relatedTo ngm:training-data ;
vc:requires ngm:data-governance ;
vc:requires ngm:model-evaluation ;
vc:requires ngm:protected-attributes ;
vc:requires ngm:training-data ;
vc:slug "algorithmic-bias" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:ieee-p-7003-2021 ;
vc:standardizedBy ngm:iso-iec-tr-24027 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:standardizedBy ngm:nist-sp-1270 ;
vc:supports ngm:ai-fairness ;
vc:supports ngm:ai-governance ;
vc:supports ngm:responsible-ai ;
vc:supports ngm:trustworthy-ai ;
vc:uses ngm:bias-detection-methods ;
vc:uses ngm:explainability ;
vc:uses ngm:fairness-metrics ;
vc:uses ngm:feature-engineering ;
vc:uses ngm:model-evaluation ;
vc:uses ngm:statistical-analysis .
ngm:algorithmic-bias-and-variance a owl:Class ;
rdfs:comment "Algorithmic Bias and Variance denotes the canonical decomposition of supervised-learning generalisation error into three orthogonal components — squared bias, variance, and irreducible noise — formalised by Geman, Bienenstock & Doursat (1992) as Err(x) = E[(y − f̂(x))²] = (E[f̂(x)] − f(x))² + E[(..."@en ;
rdfs:label "Algorithmic Bias and Variance"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:generalisation-theory ;
rdfs:subClassOf ngm:model-evaluation ;
rdfs:subClassOf ngm:neural-network ;
rdfs:subClassOf ngm:statistical-learning-theory ;
rdfs:subClassOf ngm:supervised-learning ;
rdfs:subClassOf _:r1594 ;
rdfs:subClassOf _:r1595 ;
rdfs:subClassOf _:r1596 ;
rdfs:subClassOf _:r1597 ;
rdfs:subClassOf _:r1598 ;
rdfs:subClassOf _:r1599 ;
skos:broader ngm:ai-technique ;
vc:contrastsWith ngm:ai-fairness ;
vc:contrastsWith ngm:bayesian-decision-theory ;
vc:contrastsWith ngm:frequentist-bayesian-divide ;
vc:contrastsWith ngm:no-free-lunch-theorem ;
vc:dependsOn ngm:empirical-process-theory ;
vc:dependsOn ngm:measure-theory ;
vc:dependsOn ngm:pac-learning ;
vc:dependsOn ngm:probability-theory ;
vc:dependsOn ngm:rademacher-complexity ;
vc:dependsOn ngm:vc-dimension ;
vc:enables ngm:capacity-control ;
vc:enables ngm:generalisation-bound ;
vc:enables ngm:hyperparameter-tuning ;
vc:enables ngm:model-selection ;
vc:enables ngm:risk-minimisation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:bias ;
vc:hasPart ngm:hypothesis-class ;
vc:hasPart ngm:irreducible-error ;
vc:hasPart ngm:learning-curve ;
vc:hasPart ngm:mean-squared-error ;
vc:hasPart ngm:validation-curve ;
vc:hasPart ngm:variance-component ;
vc:implements ngm:bootstrap ;
vc:implements ngm:cross-validation ;
vc:implements ngm:holdout-method ;
vc:implements ngm:k-fold ;
vc:implements ngm:loocv ;
vc:implements ngm:sampling ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:benign-overfitting ;
vc:relatedTo ngm:double-descent ;
vc:relatedTo ngm:grokking ;
vc:relatedTo ngm:inductive-bias ;
vc:relatedTo ngm:overfitting ;
vc:relatedTo ngm:scaling-laws ;
vc:relatedTo ngm:underfitting ;
vc:requires ngm:hypothesis-space ;
vc:requires ngm:loss-function ;
vc:requires ngm:resampling-method ;
vc:requires ngm:sample-complexity ;
vc:requires ngm:training-data-distribution ;
vc:slug "algorithmic-bias-and-variance" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:hastie-tibshirani-friedman-esl ;
vc:standardizedBy ngm:py-torch ;
vc:standardizedBy ngm:scikit-learn ;
vc:standardizedBy ngm:tensorflow-model-analysis ;
vc:supports ngm:bagging ;
vc:supports ngm:boosting ;
vc:supports ngm:dropout ;
vc:supports ngm:early-stopping ;
vc:supports ngm:ensemble-methods ;
vc:supports ngm:regularisation ;
vc:supports ngm:stacking ;
vc:uses ngm:bootstrap-resampling ;
vc:uses ngm:concentration-inequalities ;
vc:uses ngm:expectation-operator ;
vc:uses ngm:variance-decomposition .
ngm:algorithmic-capture a owl:Class ;
rdfs:comment "Algorithmic Capture describes the process by which recommendation and ranking algorithms come to dominate the flow of attention, shaping what content people see and produce until human discretion is largely supplanted. By optimizing for engagement, these systems can homogenize discourse, amplify synthetic or low-quality content, and entrench platform control over information ecosystems. It is a central mechanism in narratives about the decline and automation of the open internet."@en ;
rdfs:label "Algorithmic Capture"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
skos:broader ngm:ai-governance-and-ethics ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:algorithmic-governance ;
vc:relatedTo ngm:death-of-the-internet ;
vc:slug "algorithmic-capture" ;
vc:sourceDomain "governance" .
ngm:algorithmic-complexity a owl:Class ;
rdfs:comment "Algorithmic complexity is the study of how the computational resources required by an algorithm, principally time and memory, grow as a function of input size. It is expressed using asymptotic notation that abstracts away constant factors to characterise scaling behaviour. In machine learning it governs the feasibility of training and inference, shaping choices of model architecture, optimisation and data structures."@en ;
rdfs:label "Algorithmic Complexity"@en ;
rdfs:subClassOf ngm:computational-complexity-theory ;
rdfs:subClassOf ngm:statistical-learning-theory ;
vc:bridgesTo ngm:scalability ;
vc:contrastsWith ngm:sample-complexity ;
vc:dependsOn ngm:parallel-computing ;
vc:enables ngm:scalability ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:statistical-learning-theory ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:generalisation ;
vc:relatedTo ngm:model-capacity ;
vc:relatedTo ngm:sample-complexity ;
vc:relatedTo ngm:vc-dimension ;
vc:requires ngm:learning-theory ;
vc:slug "algorithmic-complexity" ;
vc:sourceDomain "machine-learning" ;
vc:supports ngm:inference-optimisation ;
vc:uses ngm:latency .
ngm:algorithmic-discrimination a skos:Concept ;
rdfs:label "Algorithmic Discrimination"@en .
ngm:algorithmic-fairness a owl:Class ;
rdfs:comment "Algorithmic fairness is the study and engineering of machine-learning systems so that their predictions and decisions do not produce unjustified disparities across individuals or protected groups. It formalises fairness through competing mathematical criteria such as demographic parity, equalised odds and individual fairness, which cannot in general be satisfied simultaneously. The field combines measurement, bias mitigation techniques and governance to align automated decisions with ethical and legal norms."@en ;
rdfs:label "Algorithmic Fairness"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf _:r1607 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:contrastsWith ngm:bias ;
vc:dependsOn ngm:labelled-dataset ;
vc:enables ngm:accountability ;
vc:enables ngm:transparency ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:isPartOf ngm:ai-ethics ;
vc:isPartOf ngm:ai-governance-and-ethics ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:fairness ;
vc:requires ngm:model-evaluation ;
vc:slug "algorithmic-fairness" ;
vc:sourceDomain "governance" ;
vc:supports ngm:explainability ;
vc:supports ngm:responsible-ai ;
vc:uses ngm:classification ;
vc:uses ngm:machine-learning-discipline .
ngm:algorithmic-framework a owl:Class ;
rdfs:comment "An Algorithmic Framework is a structured collection of algorithms, data structures, and design principles that together provide a reusable computational scaffold for solving a class of related problems. It abstracts common patterns of search, optimisation, inference, and decision-making into composable building blocks that can be instantiated and extended for specific applications. Algorithmic frameworks underpin fields such as machine learning, procedural content generation, automated planning, and symbolic reasoning by providing principled, reproducible computational architectures."@en ;
rdfs:label "Algorithmic Framework"@en ;
rdfs:subClassOf ngm:ai-framework ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf _:r1608 ;
rdfs:subClassOf _:r1609 ;
rdfs:subClassOf _:r1610 ;
rdfs:subClassOf _:r1611 ;
rdfs:subClassOf _:r1612 ;
rdfs:subClassOf _:r1613 ;
rdfs:subClassOf _:r1614 ;
rdfs:subClassOf _:r1615 ;
rdfs:subClassOf _:r1616 ;
rdfs:subClassOf _:r1617 ;
rdfs:subClassOf _:r1618 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:ai-framework ;
vc:bridgesTo ngm:digital-twin ;
vc:contrastsWith ngm:brute-force-search ;
vc:contrastsWith ngm:heuristic-methods ;
vc:dependsOn ngm:algorithmic-complexity ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:enables ngm:automated-planning ;
vc:enables ngm:game-ai ;
vc:enables ngm:inference ;
vc:enables ngm:procedural-content-generation ;
vc:enables ngm:reinforcement-learning ;
vc:enables ngm:robotics ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:algorithm ;
vc:hasPart ngm:data-structure ;
vc:hasPart ngm:graph-algorithms ;
vc:hasPart ngm:heuristic-methods ;
vc:hasPart ngm:learning-algorithm ;
vc:hasPart ngm:optimisation-algorithm ;
vc:hasPart ngm:search-algorithm ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:algorithmic-complexity ;
vc:relatedTo ngm:bayesian-inference ;
vc:relatedTo ngm:digital-twin-framework ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:machine-learning-discipline-framework ;
vc:relatedTo ngm:optimization-technique ;
vc:requires ngm:computational-complexity-theory ;
vc:requires ngm:data-structure ;
vc:requires ngm:mathematical-logic ;
vc:slug "algorithmic-framework" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:bayesian-inference ;
vc:supports ngm:optimization-technique ;
vc:uses ngm:dynamic-programming ;
vc:uses ngm:evolutionary-algorithm ;
vc:uses ngm:gradient-descent ;
vc:uses ngm:monte-carlo-methods .
ngm:algorithmic-game-theory a skos:Concept ;
rdfs:label "Algorithmic Game Theory"@en .
ngm:algorithmic-governance a owl:Class ;
rdfs:comment "Algorithmic Governance is the use of automated decision systems, models, and rule engines to make or enforce governance choices that were traditionally human and discretionary, such as moderation, resource allocation, or compliance enforcement. It can increase consistency, speed, and scale, but raises concerns about transparency, accountability, bias, and contestability of automated decisions. The concept spans platform moderation, public-sector automation, and on-chain rule enforcement."@en ;
rdfs:label "Algorithmic Governance"@en ;
rdfs:subClassOf ngm:governance ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:decentralised-coordination ;
vc:relatedTo ngm:digital-society-surveillance ;
vc:slug "algorithmic-governance" ;
vc:sourceDomain "governance" .
ngm:algorithmic-impact-assessment a owl:Class ;
rdfs:comment "An algorithmic impact assessment is a structured governance process for evaluating the potential effects of an automated decision-making or artificial-intelligence system on individuals, groups and society before and during its deployment. It documents the system's purpose, data, risks to fairness, privacy and safety, and the mitigations and oversight controls in place, producing an auditable record for accountability. Modelled on data-protection and environmental impact assessments, it is increasingly mandated by AI regulation and procurement frameworks to ensure responsible and transparent use of algorithms."@en ;
rdfs:label "Algorithmic Impact Assessment"@en ;
rdfs:subClassOf ngm:ai-governance ;
rdfs:subClassOf _:r1619 ;
rdfs:subClassOf _:r1620 ;
rdfs:subClassOf _:r1621 ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:accountability ;
vc:implements ngm:algorithmic-accountability ;
vc:implements ngm:responsible-ai ;
vc:isPartOf ngm:ai-governance ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:ai-impact-assessment ;
vc:relatedTo ngm:compliance-framework ;
vc:relatedTo ngm:data-protection-impact-assessment ;
vc:relatedTo ngm:gdpr ;
vc:relatedTo ngm:impact-assessment ;
vc:relatedTo ngm:model-governance ;
vc:relatedTo ngm:privacy-impact-assessment ;
vc:requires ngm:human-oversight ;
vc:requires ngm:stakeholder-engagement ;
vc:requires ngm:transparency ;
vc:slug "algorithmic-impact-assessment" ;
vc:sourceDomain "governance" ;
vc:supports ngm:ai-regulation ;
vc:supports ngm:fairness ;
vc:supports ngm:regulatory-compliance ;
vc:uses ngm:algorithmic-bias ;
vc:uses ngm:bias ;
vc:uses ngm:explainability ;
vc:uses ngm:risk-assessment .
ngm:algorithmic-information-theory a skos:Concept ;
rdfs:label "Algorithmic Information Theory"@en .
ngm:algorithmic-interest-rate a skos:Concept ;
rdfs:label "Algorithmic Interest Rate"@en .
ngm:algorithmic-layer a owl:Class ;
rdfs:comment "The Algorithmic Layer is the stratum that holds the step-by-step procedures a system uses to transform inputs into outputs. In the canonical stack it corresponds to the Algorithm Layer, sitting above the Compute Layer and below the Model strata that compose its primitives. It contains algorithms, data structures, and their complexity characteristics."@en ;
rdfs:label "Algorithmic Layer"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:owl-thing ;
rdfs:subClassOf _:r1622 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:computational-complexity-theory ;
vc:bridgesTo ngm:data-structure ;
vc:enables ngm:model-architecture-layer ;
vc:enables ngm:model-layer ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:compute-layer ;
vc:slug "algorithmic-layer" ;
vc:sourceDomain "machine-learning" .
ngm:algorithmic-management a skos:Concept ;
rdfs:label "Algorithmic Management"@en .
ngm:algorithmic-management-doctrine a skos:Concept ;
rdfs:label "Algorithmic Management Doctrine"@en .
ngm:algorithmic-market-design a skos:Concept ;
rdfs:label "Algorithmic Market Design"@en .
ngm:algorithmic-monetary-policy a skos:Concept ;
rdfs:label "Algorithmic Monetary Policy"@en .
ngm:algorithmic-recommendation a skos:Concept ;
rdfs:label "Algorithmic Recommendation"@en .
ngm:algorithmic-stabilisation a skos:Concept ;
rdfs:label "Algorithmic Stabilisation"@en .
ngm:algorithmic-stablecoin a owl:Class ;
rdfs:comment "An algorithmic stablecoin is a cryptocurrency that seeks to maintain a stable peg, typically to a fiat unit, through on-chain algorithmic supply adjustments and incentive mechanisms rather than full reserves of external collateral. Smart contracts expand or contract token supply, often using a companion volatility-absorbing token, to push the market price toward target. The model contrasts with fiat- and crypto-collateralised stablecoins and has proven fragile, with several high-profile de-peg failures."@en ;
rdfs:label "Algorithmic Stablecoin"@en ;
rdfs:subClassOf ngm:stablecoin ;
rdfs:subClassOf _:r1623 ;
vc:dependsOn ngm:price-oracle ;
vc:enables ngm:de-fi ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:smart-contract ;
vc:isPartOf ngm:de-fi ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:dai ;
vc:relatedTo ngm:terra ;
vc:relatedTo ngm:tether ;
vc:relatedTo ngm:usd-coin ;
vc:requires ngm:smart-contract ;
vc:slug "algorithmic-stablecoin" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:peg ;
vc:uses ngm:price-oracle .
ngm:algorithmic-trading a owl:Class ;
rdfs:comment "Algorithmic trading is the use of computer programs to execute trading decisions automatically according to predefined rules covering timing, price, quantity and order routing, often without human intervention. It spans execution algorithms that minimise market impact, systematic strategies that generate signals, and high-frequency trading that exploits microsecond advantages. In crypto markets it operates across centralised and decentralised venues and interacts closely with on-chain mechanisms such as maximal extractable value."@en ;
rdfs:label "Algorithmic Trading"@en ;
rdfs:subClassOf ngm:financial-trading ;
vc:bridgesTo ngm:crypto-trading ;
vc:bridgesTo ngm:de-fi ;
vc:bridgesTo ngm:digital-asset-trading ;
vc:dependsOn ngm:latency ;
vc:enables ngm:high-frequency-trading ;
vc:enables ngm:market-making ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:financial-trading ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:financial-trading ;
vc:relatedTo ngm:mev ;
vc:slug "algorithmic-trading" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:decentralised-exchange ;
vc:supports ngm:liquidity ;
vc:uses ngm:market-microstructure ;
vc:uses ngm:risk-management .
ngm:algorithmic-transparency a owl:Class ;
rdfs:comment "The principle and practice of making the logic, data inputs, decision criteria, and outputs of algorithmic systems sufficiently accessible and comprehensible to affected stakeholders, oversight bodies, and the general public. It encompasses both technical disclosure—publishing model architectures, training data provenance, and evaluation results—and process-level disclosure of how algorithms are developed, audited, and governed. Algorithmic transparency is recognised as a foundational requirement for accountability and trust in automated decision-making systems."@en ;
rdfs:label "Algorithmic Transparency"@en ;
rdfs:subClassOf ngm:explainability ;
vc:enables ngm:ai-governance-framework ;
vc:enables ngm:algorithmic-auditing ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:algorithmic-transparency-index ;
vc:relatedTo ngm:algorithmic-transparency-reports ;
vc:relatedTo ngm:decision-transparency ;
vc:slug "algorithmic-transparency" ;
vc:sourceDomain "governance" ;
vc:uses ngm:ai-model-card ;
vc:uses ngm:explainable-ai .
ngm:algorithmic-transparency-index a owl:Class ;
rdfs:comment "A structured metrics framework for measuring and evaluating the explainability, documentation, and disclosure levels of AI algorithms and automated decision-making systems across multiple transparency dimensions."@en ;
rdfs:label "Algorithmic Transparency Index"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:ai-governance-framework ;
rdfs:subClassOf ngm:algorithmic-accountability ;
rdfs:subClassOf ngm:performance-metrics ;
rdfs:subClassOf _:r1624 ;
rdfs:subClassOf _:r1625 ;
rdfs:subClassOf _:r1626 ;
rdfs:subClassOf _:r1627 ;
rdfs:subClassOf _:r1628 ;
rdfs:subClassOf _:r1629 ;
rdfs:subClassOf _:r1630 ;
rdfs:subClassOf _:r1631 ;
rdfs:subClassOf _:r1632 ;
rdfs:subClassOf _:r1633 ;
rdfs:subClassOf _:r1634 ;
rdfs:subClassOf _:r1635 ;
rdfs:subClassOf _:r1636 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:audit-log ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:smart-contract ;
vc:contrastsWith ngm:black-box-ai ;
vc:contrastsWith ngm:opaque-ai ;
vc:contrastsWith ngm:unexplainable-system ;
vc:dependsOn ngm:automated-decision-system ;
vc:dependsOn ngm:content-moderation-system ;
vc:dependsOn ngm:explainable-ai ;
vc:dependsOn ngm:machine-learning-model ;
vc:dependsOn ngm:recommendation-system ;
vc:enables ngm:ai-accountability ;
vc:enables ngm:algorithmic-auditing ;
vc:enables ngm:algorithmic-transparency ;
vc:enables ngm:regulatory-compliance ;
vc:enables ngm:responsible-ai ;
vc:enables ngm:stakeholder-trust ;
vc:enables ngm:trustworthy-ai ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:audit-trail ;
vc:hasPart ngm:bias-detection-methods ;
vc:hasPart ngm:data-provenance ;
vc:hasPart ngm:decision-logging ;
vc:hasPart ngm:disclosure-requirements ;
vc:hasPart ngm:documentation-standards ;
vc:hasPart ngm:explainability-metrics ;
vc:hasPart ngm:model-documentation ;
vc:hasPart ngm:performance-metrics ;
vc:implements ngm:eu-ai-act-regulatory-instrument ;
vc:implements ngm:ieee-7001-2021 ;
vc:implements ngm:iso-iec-42001 ;
vc:implements ngm:nist-ai-rmf ;
vc:isPartOf ngm:ai-governance-framework ;
vc:isPartOf ngm:algorithmic-accountability ;
vc:isPartOf ngm:trustworthy-ai-framework ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-accountability ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:ai-impact-assessment ;
vc:relatedTo ngm:algorithmic-transparency ;
vc:relatedTo ngm:algorithmic-transparency-reports ;
vc:relatedTo ngm:data-governance ;
vc:relatedTo ngm:explainable-ai ;
vc:relatedTo ngm:fairness ;
vc:relatedTo ngm:responsible-ai ;
vc:requires ngm:audit-mechanism ;
vc:requires ngm:automated-decision-system ;
vc:requires ngm:bias-detection-methods ;
vc:requires ngm:data-provenance ;
vc:requires ngm:decision-logging ;
vc:requires ngm:explainable-ai ;
vc:requires ngm:model-documentation ;
vc:slug "algorithmic-transparency-index" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:ieee-7001-2021 ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:ai-governance-framework ;
vc:supports ngm:algorithmic-transparency-reports ;
vc:supports ngm:human-oversight ;
vc:supports ngm:responsible-ai ;
vc:uses ngm:ai-model-card ;
vc:uses ngm:audit-trail ;
vc:uses ngm:bias-detection-methods ;
vc:uses ngm:explainability-metrics ;
vc:uses ngm:fairness-metrics .
ngm:algorithmic-transparency-reports a owl:Class ;
rdfs:comment "Algorithmic Transparency Reports are periodic public disclosures that document AI system characteristics, performance metrics, governance practices, and accountability mechanisms, enabling external stakeholders, regulators, and affected communities to scrutinise how algorithmic decision-making systems operate and impact individuals. Core sections include system purpose and deployment scope, disaggregated performance and fairness metrics, bias and disparate-impact analyses, data governance practices, explainability provisions, incident and remediation records, and stakeholder engagement summaries. Reports balance transparency objectives against proprietary-information protection and adversarial-exploitation risks, and align with requirements in EU AI Act Article 13 (high-risk system transparency), Platform-to-Business Regulation disclosure obligations, and voluntary civil-society commitments led by organisations such as the AI Now Institute."@en ;
rdfs:label "Algorithmic Transparency Reports"@en ;
rdfs:subClassOf ngm:accountability-framework ;
rdfs:subClassOf ngm:ai-ethics ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:ai-governance-framework ;
rdfs:subClassOf ngm:algorithmic-transparency ;
rdfs:subClassOf _:r1637 ;
rdfs:subClassOf _:r1638 ;
rdfs:subClassOf _:r1639 ;
rdfs:subClassOf _:r1640 ;
rdfs:subClassOf _:r1641 ;
rdfs:subClassOf _:r1642 ;
rdfs:subClassOf _:r1643 ;
rdfs:subClassOf _:r1644 ;
rdfs:subClassOf _:r1645 ;
rdfs:subClassOf _:r1646 ;
rdfs:subClassOf _:r1647 ;
rdfs:subClassOf _:r1648 ;
rdfs:subClassOf _:r1649 ;
rdfs:subClassOf _:r1650 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:data-governance ;
vc:bridgesTo ngm:smart-contract ;
vc:contrastsWith ngm:black-box-ai ;
vc:contrastsWith ngm:opaque-ai ;
vc:contrastsWith ngm:unregulated-deployment ;
vc:dependsOn ngm:algorithmic-transparency-index ;
vc:dependsOn ngm:automated-decision-system ;
vc:dependsOn ngm:content-moderation-system ;
vc:dependsOn ngm:machine-learning-model ;
vc:dependsOn ngm:recommendation-system ;
vc:enables ngm:ai-accountability ;
vc:enables ngm:algorithmic-auditing ;
vc:enables ngm:human-oversight ;
vc:enables ngm:regulatory-compliance ;
vc:enables ngm:responsible-ai ;
vc:enables ngm:stakeholder ;
vc:enables ngm:stakeholder-trust ;
vc:enables ngm:trustworthy-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:audit-trail ;
vc:hasPart ngm:bias-detection-methods ;
vc:hasPart ngm:data-provenance ;
vc:hasPart ngm:decision-logging ;
vc:hasPart ngm:disclosure-requirements ;
vc:hasPart ngm:explainability-metrics ;
vc:hasPart ngm:human-oversight ;
vc:hasPart ngm:model-documentation ;
vc:hasPart ngm:performance-metrics ;
vc:implements ngm:eu-ai-act-regulatory-instrument ;
vc:implements ngm:iso-iec-42001 ;
vc:implements ngm:nist-ai-rmf ;
vc:implements ngm:platform-to-business-regulation ;
vc:isPartOf ngm:ai-governance-framework ;
vc:isPartOf ngm:algorithmic-accountability ;
vc:isPartOf ngm:trustworthy-ai-framework ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:ai-impact-assessment ;
vc:relatedTo ngm:ai-now-institute ;
vc:relatedTo ngm:algorithmic-transparency ;
vc:relatedTo ngm:algorithmic-transparency-index ;
vc:relatedTo ngm:diversity-non-discrimination-and-fairness ;
vc:relatedTo ngm:explainable-ai ;
vc:relatedTo ngm:human-oversight ;
vc:relatedTo ngm:redress-procedure ;
vc:relatedTo ngm:risk-assessment ;
vc:requires ngm:accountability ;
vc:requires ngm:algorithmic-transparency ;
vc:requires ngm:audit-trail ;
vc:requires ngm:data-provenance ;
vc:requires ngm:decision-logging ;
vc:requires ngm:explainable-ai ;
vc:requires ngm:model-documentation ;
vc:requires ngm:transparency ;
vc:slug "algorithmic-transparency-reports" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:standardizedBy ngm:platform-to-business-regulation ;
vc:supports ngm:ai-governance-framework ;
vc:supports ngm:algorithmic-transparency-index ;
vc:supports ngm:explainable-ai ;
vc:supports ngm:fairness ;
vc:supports ngm:governance-framework ;
vc:supports ngm:responsible-ai ;
vc:uses ngm:ai-impact-assessment ;
vc:uses ngm:ai-model-card ;
vc:uses ngm:audit-trail ;
vc:uses ngm:bias-detection-methods ;
vc:uses ngm:explainability ;
vc:uses ngm:explainability-metrics ;
vc:uses ngm:fairness ;
vc:uses ngm:fairness-metrics .
ngm:algorithms a skos:Concept ;
rdfs:label "Algorithms"@en .
ngm:alias-dictionary a skos:Concept ;
rdfs:label "Alias Dictionary"@en .
ngm:alias-expansion a skos:Concept ;
rdfs:label "Alias Expansion"@en .
ngm:alibi a skos:Concept ;
rdfs:label "Alibi"@en .
ngm:alife-conference a skos:Concept ;
rdfs:label "Alife Conference"@en .
ngm:align a skos:Concept ;
rdfs:label "Align"@en .
ngm:alignment a owl:Class ;
rdfs:comment "The technical and philosophical research programme aimed at ensuring that AI systems reliably pursue goals, exhibit behaviours, and produce outcomes that accord with human values, intentions, and oversight requirements. Alignment addresses the fundamental challenge that learned objectives may diverge from intended objectives—a problem that becomes increasingly consequential as AI systems grow more capable and autonomous. The field encompasses specification of human preferences, training methods that instil those preferences, and verification techniques that confirm alignment properties are preserved at deployment."@en ;
rdfs:label "Alignment"@en ;
rdfs:subClassOf ngm:ai-alignment ;
rdfs:subClassOf ngm:ai-safety-research ;
rdfs:subClassOf _:r1651 ;
rdfs:subClassOf _:r1652 ;
rdfs:subClassOf _:r1653 ;
rdfs:subClassOf _:r1654 ;
rdfs:subClassOf _:r1655 ;
rdfs:subClassOf _:r1656 ;
rdfs:subClassOf _:r1657 ;
rdfs:subClassOf _:r1658 ;
rdfs:subClassOf _:r1659 ;
rdfs:subClassOf _:r1660 ;
vc:bridgesTo ngm:ai-governance ;
vc:bridgesTo ngm:human-oversight ;
vc:contrastsWith ngm:alignment-faking ;
vc:contrastsWith ngm:mesa-optimisation ;
vc:contrastsWith ngm:reward-hacking ;
vc:contrastsWith ngm:sycophancy ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:mechanistic-interpretability ;
vc:dependsOn ngm:reinforcement-learning-from-human-feedback ;
vc:dependsOn ngm:sparse-autoencoders ;
vc:enables ngm:ai-safety ;
vc:enables ngm:aisi-frontier-ai-safety-framework ;
vc:enables ngm:responsible-ai ;
vc:enables ngm:trustworthy-ai ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:constitutional-ai-training-methodology ;
vc:hasPart ngm:corrigibility ;
vc:hasPart ngm:reward-modelling ;
vc:hasPart ngm:scalable-oversight ;
vc:hasPart ngm:value-alignment ;
vc:implements ngm:constitutional-ai-training-methodology ;
vc:implements ngm:direct-preference-optimisation ;
vc:implements ngm:reinforcement-learning-from-human-feedback ;
vc:isPartOf ngm:ai-safety-research ;
vc:qualityScore "0.92"^^xsd:float ;
vc:relatedTo ngm:agentic-misalignment ;
vc:relatedTo ngm:apollo-research ;
vc:relatedTo ngm:bletchley-declaration ;
vc:relatedTo ngm:distributional-shift ;
vc:relatedTo ngm:existential-risk ;
vc:relatedTo ngm:frontier-ai ;
vc:relatedTo ngm:large-language-model ;
vc:relatedTo ngm:redwood-research ;
vc:relatedTo ngm:robustness ;
vc:relatedTo ngm:weak-to-strong-generalisation ;
vc:requires ngm:human-feedback ;
vc:requires ngm:human-oversight ;
vc:requires ngm:interpretability ;
vc:requires ngm:mechanistic-interpretability ;
vc:slug "alignment" ;
vc:sourceDomain "ai" ;
vc:supports ngm:ai-governance-framework ;
vc:supports ngm:ai-regulation ;
vc:supports ngm:eu-ai-act-regulatory-instrument ;
vc:supports ngm:nist-ai-rmf ;
vc:uses ngm:debate ;
vc:uses ngm:direct-preference-optimisation ;
vc:uses ngm:iterated-amplification ;
vc:uses ngm:model-evaluation ;
vc:uses ngm:preference-learning ;
vc:uses ngm:red-teaming ;
vc:uses ngm:reward-model ;
vc:uses ngm:sparse-autoencoder .
ngm:alignment-evaluation a skos:Concept ;
rdfs:label "Alignment Evaluation"@en .
ngm:alignment-faking a skos:Concept ;
rdfs:label "Alignment Faking"@en .
ngm:alignment-research a owl:Class ;
rdfs:comment "The research programme dedicated to ensuring that increasingly capable AI systems reliably pursue their designers' and society's intended goals, spanning empirical techniques such as reinforcement learning from human feedback, constitutional AI, scalable oversight and mechanistic interpretability, alongside theoretical work on agent foundations, corrigibility, deceptive alignment and mesa-optimisation; a field whose importance scales with model capability and which anchors the safety agendas of frontier laboratories and a growing academic community."@en ;
rdfs:label "Alignment Research"@en ;
rdfs:subClassOf ngm:artificial-intelligence-research ;
vc:enables ngm:ai-alignment ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:artificial-general-intelligence ;
vc:slug "alignment-research" ;
vc:sourceDomain "artificial-intelligence" .
ngm:alignment-techniques a owl:Class ;
rdfs:comment "Alignment techniques are the methods used to make an AI system's behaviour conform to intended human goals, values, and constraints, particularly as capability increases. They include reinforcement learning from human feedback, constitutional methods, red-teaming, and interpretability-informed fine-tuning. Alignment techniques are a core requirement for building trustworthy conversational AI systems and are considered essential on the path toward artificial general intelligence."@en ;
rdfs:label "Alignment Techniques"@en ;
rdfs:subClassOf ngm:ai-alignment ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "alignment-techniques" ;
vc:sourceDomain "artificial-intelligence" .
ngm:all-gather-collective a skos:Concept ;
rdfs:label "All Gather Collective"@en .
ngm:all-reduce a skos:Concept ;
rdfs:label "All Reduce"@en .
ngm:all-reduce-algorithm a skos:Concept ;
rdfs:label "All Reduce Algorithm"@en .
ngm:all-to-all-communication a skos:Concept ;
rdfs:label "All To All Communication"@en .
ngm:allan-variance a skos:Concept ;
rdfs:label "Allan Variance"@en .
ngm:alliance-for-open-media a skos:Concept ;
rdfs:label "Alliance For Open Media"@en .
ngm:alliance-for-open-media-av1 a skos:Concept ;
rdfs:label "Alliance For Open Media AV1"@en .
ngm:alliance-for-openusd a skos:Concept ;
rdfs:label "Alliance For Openusd"@en .
ngm:allied-coalition-operations a skos:Concept ;
rdfs:label "Allied Coalition Operations"@en .
ngm:allo-protocol a owl:Class ;
rdfs:comment "Allo Protocol is an on-chain framework developed by Gitcoin for allocating capital, supporting funding mechanisms such as quadratic funding and grants."@en ;
rdfs:label "Allo Protocol"@en ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf ngm:de-fi ;
rdfs:subClassOf _:r1661 ;
skos:broader ngm:blockchain ;
vc:bridgesTo ngm:interoperability ;
vc:enables ngm:web-3-infrastructure ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:token ;
vc:slug "allo-protocol" ;
vc:sourceDomain "distributed-systems" .
ngm:allocated-account a skos:Concept ;
rdfs:label "Allocated Account"@en .
ngm:allocational-bias a skos:Concept ;
rdfs:label "Allocational Bias"@en .
ngm:alpha-blending a skos:Concept ;
rdfs:label "Alpha Blending"@en .
ngm:alpha-compositing a skos:Concept ;
rdfs:label "Alpha Compositing"@en .
ngm:alpha-stable-processes a skos:Concept ;
rdfs:label "Alpha Stable Processes"@en .
ngm:alpha-token a skos:Concept ;
rdfs:label "Alpha Token"@en .
ngm:alphabet-inc a skos:Concept ;
rdfs:label "Alphabet Inc"@en .
ngm:alphacode a skos:Concept ;
rdfs:label "Alphacode"@en .
ngm:alphadev a skos:Concept ;
rdfs:label "Alphadev"@en .
ngm:alphaevolve a skos:Concept ;
rdfs:label "Alphaevolve"@en .
ngm:alphafold a owl:Class ;
rdfs:comment "AlphaFold is a deep learning system developed by DeepMind that predicts the three-dimensional structure of a protein from its amino acid sequence with accuracy approaching that of experimental methods such as X-ray crystallography, a problem known as the protein folding problem. It uses an attention-based neural network architecture trained on known protein structures and evolutionary sequence data to output per-residue coordinates along with a confidence estimate. AlphaFold's predictions are widely used in computational biology and genomics research, and its structure database has substantially accelerated work in drug discovery and molecular biology."@en ;
rdfs:label "AlphaFold"@en ;
rdfs:subClassOf ngm:deep-learning ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:deep-learning ;
vc:qualityScore "0.55"^^xsd:float ;
vc:relatedTo ngm:computational-biology ;
vc:relatedTo ngm:genomics ;
vc:slug "alphafold" ;
vc:sourceDomain "artificial-intelligence" .
ngm:alphageometry a skos:Concept ;
rdfs:label "Alphageometry"@en .
ngm:alphago a skos:Concept ;
rdfs:label "Alphago"@en .
ngm:alphaproof a skos:Concept ;
rdfs:label "Alphaproof"@en .
ngm:alphazero a skos:Concept ;
rdfs:label "Alphazero"@en .
ngm:alpine-tundra a owl:Class ;
rdfs:label "Alpine Tundra"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-system-phenomena ;
vc:slug "alpine-tundra" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:alpr-networks a owl:Class ;
rdfs:comment "ALPR Networks are interconnected systems of Automatic License Plate Recognition cameras that capture, read, timestamp, and geotag vehicle plates at scale across roads, lots, and checkpoints. Aggregated across many cameras and operators, the resulting databases reconstruct vehicle movement histories and enable mass location tracking. They are a prominent component of contemporary surveillance infrastructure and a focal point of privacy and civil-liberties concern."@en ;
rdfs:label "ALPR Networks"@en ;
rdfs:subClassOf ngm:computer-vision ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:digital-society-surveillance ;
vc:slug "alpr-networks" ;
vc:sourceDomain "security" .
ngm:als-communication a skos:Concept ;
rdfs:label "Als Communication"@en .
ngm:alternating-direction-method-of-multipliers a skos:Concept ;
rdfs:label "Alternating Direction Method Of Multipliers"@en .
ngm:alternating-least-squares a skos:Concept ;
rdfs:label "Alternating Least Squares"@en .
ngm:alternative-finance a skos:Concept ;
rdfs:label "Alternative Finance"@en .
ngm:alternative-input-methods a skos:Concept ;
rdfs:label "Alternative Input Methods"@en .
ngm:alternative-investment a skos:Concept ;
rdfs:label "Alternative Investment"@en .
ngm:alternative-investments a skos:Concept ;
rdfs:label "Alternative Investments"@en .
ngm:alternative-text a skos:Concept ;
rdfs:label "Alternative Text"@en .
ngm:alternative-trading-system a skos:Concept ;
rdfs:label "Alternative Trading System"@en .
ngm:altspace-vr a owl:Class ;
rdfs:comment "AltspaceVR was a social virtual reality platform offering avatar-based gatherings, events and shared spaces, later acquired by Microsoft and eventually shut down."@en ;
rdfs:label "AltspaceVR"@en ;
rdfs:subClassOf ngm:metaverse ;
rdfs:subClassOf ngm:metaverse-domain ;
rdfs:subClassOf _:r1662 ;
vc:bridgesTo ngm:microsoft-mesh ;
vc:bridgesTo ngm:virtual-reality ;
vc:enables ngm:virtual-world ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:avatar-system ;
vc:slug "altspace-vr" ;
vc:sourceDomain "metaverse" .
ngm:alu-vm a owl:Class ;
rdfs:comment "A purely functional, register-based virtual machine designed for deterministic execution of smart-contract validation logic within client-side validated Bitcoin protocol layers, notably the RGB Protocol. AluVM operates without mutable global state, using a RISC-like instruction set that guarantees bounded execution time and reproducible results across heterogeneous computing environments. Its architecture is specifically optimised for the constraints of client-side validation, where contract logic must execute identically across all validating parties without access to a shared blockchain state machine."@en ;
rdfs:label "AluVM"@en ;
rdfs:subClassOf ngm:virtual-machine ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:rgb-protocol ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:layer-2-solutions ;
vc:relatedTo ngm:rgb-and-client-side-validation ;
vc:slug "alu-vm" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:bitcoin-script ;
vc:uses ngm:taproot .
ngm:aluminium-alloy a skos:Concept ;
rdfs:label "Aluminium Alloy"@en .
ngm:aluvm-validation a skos:Concept ;
rdfs:label "Aluvm Validation"@en .
ngm:always-on-culture a skos:Concept ;
rdfs:label "Always On Culture"@en .
ngm:amazon-alexa a skos:Concept ;
rdfs:label "Amazon Alexa"@en .
ngm:amazon-bedrock a skos:Concept ;
rdfs:label "Amazon Bedrock"@en .
ngm:amazon-prime-video a skos:Concept ;
rdfs:label "Amazon Prime Video"@en .
ngm:amazon-q a skos:Concept ;
rdfs:label "Amazon Q"@en .
ngm:amazon-s3 a skos:Concept ;
rdfs:label "Amazon S3"@en .
ngm:amazon-sequoia a skos:Concept ;
rdfs:label "Amazon Sequoia"@en .
ngm:amazon-web-services a skos:Concept ;
rdfs:label "Amazon Web Services"@en .
ngm:amazon-web-services-ai a skos:Concept ;
rdfs:label "Amazon Web Services AI"@en .
ngm:ambient-awareness a owl:Class ;
rdfs:comment "Ambient Awareness is the peripheral, low-effort sense of others' presence, activity, and availability that collaborative systems convey through subtle continuous signals rather than explicit notifications. It is realized through presence indicators, status cues, activity streams, and spatial audio in shared digital workspaces. By keeping collaborators loosely informed of each other's context, it supports coordination and a feeling of co-location in distributed teams."@en ;
rdfs:label "Ambient Awareness"@en ;
rdfs:subClassOf ngm:telepresence ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:presence-indicator ;
vc:slug "ambient-awareness" ;
vc:sourceDomain "metaverse" .
ngm:ambient-computing a owl:Class ;
rdfs:comment "A paradigm in which computing capability is invisibly embedded throughout the physical environment, enabling technology to sense, infer, and respond to human needs without requiring deliberate interaction with discrete devices. Ambient computing dissolves the boundary between the digital and physical worlds by distributing processing, sensing, and actuation across interconnected objects, surfaces, and spaces that operate continuously in the background. It represents the convergence of pervasive connectivity, miniaturised hardware, and AI-driven contextual inference into an always-present computational substrate."@en ;
rdfs:label "Ambient Computing"@en ;
rdfs:subClassOf ngm:pervasive-computing ;
rdfs:subClassOf _:r1663 ;
rdfs:subClassOf _:r1664 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:distributed-systems ;
vc:bridgesTo ngm:robotics ;
vc:contrastsWith ngm:cloud-computing ;
vc:dependsOn ngm:infrastructure ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:enables ngm:context-aware-computing ;
vc:enables ngm:smart-building ;
vc:enables ngm:smart-home ;
vc:enables ngm:spatial-computing ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:industrial-io-t ;
vc:relatedTo ngm:io-t ;
vc:relatedTo ngm:mixed-reality ;
vc:relatedTo ngm:privacy-preserving ;
vc:requires ngm:real-time-inference ;
vc:requires ngm:sensor-fusion ;
vc:slug "ambient-computing" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:matter-protocol ;
vc:uses ngm:computer-vision ;
vc:uses ngm:edge-ai ;
vc:uses ngm:edge-computing ;
vc:uses ngm:internet-of-things ;
vc:uses ngm:io-t-sensor-network ;
vc:uses ngm:natural-language-processing .
ngm:ambient-display a skos:Concept ;
rdfs:label "Ambient Display"@en .
ngm:ambient-observation a owl:Class ;
rdfs:comment "A paradigm for AI learning where the system passively acquires knowledge and patterns from background user interactions and environment data without explicit instruction."@en ;
rdfs:label "Ambient Observation"@en ;
rdfs:subClassOf ngm:machine-learning-discipline ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-privacy ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:unsupervised-learning ;
vc:slug "ambient-observation" ;
vc:sourceDomain "artificial-intelligence" .
ngm:ambient-occlusion a owl:Class ;
rdfs:comment "A shading and rendering technique that approximates the degree to which each point on a surface is occluded from ambient environmental light by surrounding geometry, producing soft shadows in crevices, corners, and contact areas that significantly enhance the perception of three-dimensional form and material grounding. Unlike direct illumination algorithms, ambient occlusion is view-independent and operates on the assumption that ambient light arrives uniformly from all directions, making it computationally tractable as either a pre-baked texture or a real-time screen-space approximation. It is a foundational element of physically plausible rendering pipelines."@en ;
rdfs:label "Ambient Occlusion"@en ;
rdfs:subClassOf ngm:rendering-technique ;
rdfs:subClassOf _:r1665 ;
rdfs:subClassOf _:r1666 ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:bridgesTo ngm:spatial-computing ;
vc:contrastsWith ngm:direct-illumination ;
vc:contrastsWith ngm:shadow-mapping ;
vc:enables ngm:perception ;
vc:enables ngm:photorealistic-rendering ;
vc:enables ngm:real-time-rendering ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:global-illumination ;
vc:isPartOf ngm:rendering-pipeline ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:ar-occlusion ;
vc:relatedTo ngm:dynamic-lighting ;
vc:relatedTo ngm:neural-rendering ;
vc:relatedTo ngm:occlusion-culling ;
vc:requires ngm:scene-geometry ;
vc:requires ngm:surface-normal ;
vc:slug "ambient-occlusion" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:depth-buffer ;
vc:uses ngm:physically-based-rendering ;
vc:uses ngm:ray-tracing ;
vc:uses ngm:sampling ;
vc:uses ngm:shader .
ngm:ambient-occlusion-maps a skos:Concept ;
rdfs:label "Ambient Occlusion Maps"@en .
ngm:ambisonics a owl:Class ;
rdfs:comment "Ambisonics is a full-sphere surround sound technique that represents a sound field independently of any specific loudspeaker layout by encoding it into spherical harmonic components. A captured or synthesised scene is stored as B-format channels and later decoded to an arbitrary speaker array or to binaural headphones, allowing the same recording to be rendered for many playback configurations. It is widely used for immersive and head-tracked audio in virtual and augmented reality."@en ;
rdfs:label "Ambisonics"@en ;
rdfs:subClassOf ngm:spatial-audio ;
rdfs:subClassOf _:r1667 ;
vc:dependsOn ngm:signal-processing ;
vc:enables ngm:immersive-audio ;
vc:enables ngm:spatial-audio ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:spherical-harmonics ;
vc:implements ngm:audio-spatialization ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:audio-system ;
vc:relatedTo ngm:psychoacoustics ;
vc:slug "ambisonics" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:augmented-reality ;
vc:supports ngm:virtual-reality ;
vc:uses ngm:audio-codec ;
vc:uses ngm:signal-processing .
ngm:ambisonics-playback a skos:Concept ;
rdfs:label "Ambisonics Playback"@en .
ngm:ambisonics-representation a skos:Concept ;
rdfs:label "Ambisonics Representation"@en .
ngm:amd a skos:Concept ;
rdfs:label "Amd"@en .
ngm:amd-instinct-mi300x a skos:Concept ;
rdfs:label "Amd Instinct Mi300x"@en .
ngm:amd-sev a owl:Class ;
rdfs:comment "AMD SEV (Secure Encrypted Virtualisation) is a hardware security technology that encrypts the memory of individual virtual machines using per-VM keys managed by an on-chip security processor, isolating guest memory from the hypervisor and other VMs. Extensions add register-state encryption and integrity protection with attestation, enabling confidential virtual machines whose contents are protected even from a privileged host. It is a leading approach to confidential computing in cloud environments."@en ;
rdfs:label "Amd Sev"@en ;
rdfs:subClassOf ngm:confidential-computing ;
rdfs:subClassOf _:r1668 ;
vc:contrastsWith ngm:intel-sgx ;
vc:contrastsWith ngm:tee ;
vc:dependsOn ngm:hardware-security ;
vc:dependsOn ngm:memory-encryption ;
vc:enables ngm:cloud-security ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:tee ;
vc:isPartOf ngm:confidential-computing ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:attestation ;
vc:relatedTo ngm:cloud-security ;
vc:relatedTo ngm:secure-enclave ;
vc:requires ngm:hardware-security ;
vc:slug "amd-sev" ;
vc:sourceDomain "security" ;
vc:supports ngm:hypervisor ;
vc:uses ngm:attestation ;
vc:uses ngm:memory-encryption ;
vc:uses ngm:virtualisation .
ngm:amd-sev-snp a skos:Concept ;
rdfs:label "Amd Sev Snp"@en .
ngm:amendment-procedure a skos:Concept ;
rdfs:label "Amendment Procedure"@en .
ngm:american-psychological-association a skos:Concept ;
rdfs:label "American Psychological Association"@en .
ngm:amerithrax-2001 a skos:Concept ;
rdfs:label "Amerithrax 2001"@en .
ngm:amesim a skos:Concept ;
rdfs:label "Amesim"@en .
ngm:aml a owl:Class ;
rdfs:comment "Anti-Money Laundering (AML) is the body of laws, regulations, policies, and operational controls that obligate financial institutions to detect, prevent, and report the process by which criminals disguise proceeds of illegal activity as legitimate income. AML frameworks encompass Know Your Customer (KYC) identity verification, ongoing transaction monitoring, suspicious activity reporting (SAR), and risk-based compliance programmes overseen by regulators such as the Financial Action Task Force (FATF), FinCEN, and national supervisory authorities. Machine learning and network analytics have become central to modern AML systems, enabling real-time anomaly detection and entity-resolution across large transaction graphs. Regulated entities that fail to meet AML obligations face substantial financial penalties, licence revocations, and criminal liability."@en ;
rdfs:label "AML"@en ;
rdfs:subClassOf ngm:financial-services ;
rdfs:subClassOf _:r819 ;
rdfs:subClassOf _:r820 ;
rdfs:subClassOf _:r821 ;
rdfs:subClassOf _:r822 ;
rdfs:subClassOf _:r823 ;
rdfs:subClassOf _:r824 ;
rdfs:subClassOf _:r825 ;
rdfs:subClassOf _:r826 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:federated-learning ;
vc:contrastsWith ngm:fraud-detection ;
vc:contrastsWith ngm:sanctions-screening ;
vc:enables ngm:financial-crime-prevention ;
vc:enables ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:customer-due-diligence ;
vc:hasPart ngm:kyc ;
vc:hasPart ngm:suspicious-activity-report ;
vc:hasPart ngm:transaction-monitoring ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:data-governance ;
vc:relatedTo ngm:explainability ;
vc:relatedTo ngm:financial-regulation ;
vc:requires ngm:classification ;
vc:requires ngm:identity-verification ;
vc:requires ngm:risk-scoring ;
vc:slug "aml" ;
vc:sourceDomain "finance" ;
vc:standardizedBy ngm:basel-iii ;
vc:standardizedBy ngm:fatf ;
vc:uses ngm:anomaly-detection ;
vc:uses ngm:graph-analytics ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:natural-language-processing .
ngm:aml-cft-regulation a skos:Concept ;
rdfs:label "Aml Cft Regulation"@en .
ngm:aml-enforcement a skos:Concept ;
rdfs:label "Aml Enforcement"@en .
ngm:aml-kyc-compliance a owl:Class ;
rdfs:comment "AML KYC Compliance is the composite regulatory and operational discipline by which obligated entities — banks, payment institutions, e-money issuers, brokers, insurers, accountants, lawyers, art dealers, casinos, real-estate agents, virtual-asset service providers (VASPs / crypto-asset service pr..."@en ;
rdfs:label "AML KYC Compliance"@en ;
rdfs:subClassOf ngm:anti-financial-crime-regime ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
rdfs:subClassOf ngm:customer-onboarding-discipline ;
rdfs:subClassOf ngm:financial-crime-compliance ;
rdfs:subClassOf ngm:regulatory-compliance ;
rdfs:subClassOf ngm:risk-management-framework ;
rdfs:subClassOf _:r805 ;
rdfs:subClassOf _:r806 ;
rdfs:subClassOf _:r807 ;
rdfs:subClassOf _:r808 ;
rdfs:subClassOf _:r809 ;
rdfs:subClassOf _:r810 ;
rdfs:subClassOf _:r811 ;
rdfs:subClassOf _:r812 ;
rdfs:subClassOf _:r813 ;
rdfs:subClassOf _:r814 ;
rdfs:subClassOf _:r815 ;
rdfs:subClassOf _:r816 ;
rdfs:subClassOf _:r817 ;
rdfs:subClassOf _:r818 ;
skos:broader ngm:bc-governance-and-regulation ;
vc:bridgesTo ngm:infra-legal-and-regulatory ;
vc:contrastsWith ngm:anonymous-cryptocurrency ;
vc:contrastsWith ngm:cypherpunk-pseudonymity ;
vc:contrastsWith ngm:decentralised-finance-anonymity ;
vc:contrastsWith ngm:privacy-coin-architecture ;
vc:contrastsWith ngm:privacy-preserving-identity ;
vc:contrastsWith ngm:self-sovereign-identity ;
vc:contrastsWith ngm:unhosted-wallet ;
vc:contrastsWith ngm:zero-knowledge-kyc ;
vc:dependsOn ngm:beneficial-ownership-registers ;
vc:dependsOn ngm:blockchain-analytics ;
vc:dependsOn ngm:companies-house-psc-register ;
vc:dependsOn ngm:egmont-group-information-sharing ;
vc:dependsOn ngm:financial-intelligence-unit ;
vc:dependsOn ngm:government-issued-identity-documents ;
vc:dependsOn ngm:identity-verification ;
vc:dependsOn ngm:pep-databases ;
vc:dependsOn ngm:sanctions-lists ;
vc:enables ngm:corporate-tax-compliance-framework ;
vc:enables ngm:correspondent-banking ;
vc:enables ngm:counter-terrorist-financing ;
vc:enables ngm:cross-border-payment-compliance ;
vc:enables ngm:financial-system-integrity ;
vc:enables ngm:proceeds-of-crime-recovery ;
vc:enables ngm:sanctions-enforcement ;
vc:enables ngm:vasp-market-access ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:adverse-media-screening ;
vc:hasPart ngm:beneficial-ownership-disclosure ;
vc:hasPart ngm:customer-due-diligence ;
vc:hasPart ngm:customer-identification-programme ;
vc:hasPart ngm:enhanced-due-diligence ;
vc:hasPart ngm:record-keeping ;
vc:hasPart ngm:sanctions-screening ;
vc:hasPart ngm:simplified-due-diligence ;
vc:hasPart ngm:source-of-funds-verification ;
vc:hasPart ngm:source-of-wealth-verification ;
vc:hasPart ngm:suspicious-activity-report ;
vc:hasPart ngm:transaction-monitoring ;
vc:hasPart ngm:travel-rule ;
vc:implements ngm:bank-secrecy-act ;
vc:implements ngm:eu-amlr-single-rulebook ;
vc:implements ngm:fatf-40-recommendations ;
vc:implements ngm:fatf-travel-rule ;
vc:implements ngm:proceeds-of-crime-act-2002 ;
vc:implements ngm:risk-based-approach ;
vc:implements ngm:sanctions-and-anti-money-laundering-act-2018 ;
vc:implements ngm:uk-mlr-2017 ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:amla ;
vc:relatedTo ngm:austrac ;
vc:relatedTo ngm:beneficial-ownership ;
vc:relatedTo ngm:binance-settlement-2023 ;
vc:relatedTo ngm:chainalysis ;
vc:relatedTo ngm:complyadvantage ;
vc:relatedTo ngm:elliptic ;
vc:relatedTo ngm:fatf ;
vc:relatedTo ngm:fca ;
vc:relatedTo ngm:fin-cen ;
vc:relatedTo ngm:jumio ;
vc:relatedTo ngm:mas ;
vc:relatedTo ngm:ofac ;
vc:relatedTo ngm:onfido ;
vc:relatedTo ngm:sumsub ;
vc:relatedTo ngm:td-bank-aml-settlement ;
vc:relatedTo ngm:tornado-cash ;
vc:relatedTo ngm:travel-rule ;
vc:requires ngm:audit-function ;
vc:requires ngm:board-level-oversight ;
vc:requires ngm:compliance-officer ;
vc:requires ngm:customer-identification-documentation ;
vc:requires ngm:fiu-reporting-channel ;
vc:requires ngm:risk-based-approach ;
vc:requires ngm:sanctions-list-feed ;
vc:requires ngm:staff-training-programme ;
vc:slug "aml-kyc-compliance" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:bank-secrecy-act ;
vc:standardizedBy ngm:e-idas-2-0 ;
vc:standardizedBy ngm:eccta-2023 ;
vc:standardizedBy ngm:eu-amla-regulation-2024-1620 ;
vc:standardizedBy ngm:eu-amld6-2024-1640 ;
vc:standardizedBy ngm:eu-amlr-2024-1624 ;
vc:standardizedBy ngm:fatf-40-recommendations ;
vc:standardizedBy ngm:fatf-recommendations ;
vc:standardizedBy ngm:fatf-travel-rule ;
vc:standardizedBy ngm:iso-20022 ;
vc:standardizedBy ngm:iso-iec-30107-3-pad ;
vc:standardizedBy ngm:uk-mlr-2017 ;
vc:standardizedBy ngm:w3-c-verifiable-credentials ;
vc:supports ngm:correspondent-banking ;
vc:supports ngm:de-risking-avoidance ;
vc:supports ngm:fca-cryptoasset-registration ;
vc:supports ngm:financial-inclusion ;
vc:supports ngm:licensing-requirements ;
vc:supports ngm:listed-company-compliance ;
vc:supports ngm:mica-authorisation ;
vc:uses ngm:biometric-liveness-detection ;
vc:uses ngm:blockchain-analytics-platform ;
vc:uses ngm:document-authentication-ocr ;
vc:uses ngm:identity-verification ;
vc:uses ngm:machine-learning-risk-scoring ;
vc:uses ngm:network-analysis ;
vc:uses ngm:nfc-chip-reading ;
vc:uses ngm:sanctions-screening ;
vc:uses ngm:travel-rule-protocol ;
vc:uses ngm:verifiable-credentials .
ngm:amla a skos:Concept ;
rdfs:label "Amla"@en .
ngm:amm-algorithm a owl:Class ;
rdfs:comment "An AMM Algorithm is the pricing rule of an Automated Market Maker that algorithmically sets exchange rates from the reserves held in a liquidity pool, removing the need for a traditional order book. The canonical form is the constant-product invariant x*y=k, with variants such as constant-sum, stableswap, and concentrated-liquidity curves tuned for different asset pairs. It determines slippage, price impact, and the impermanent loss that liquidity providers bear."@en ;
rdfs:label "AMM Algorithm"@en ;
rdfs:subClassOf ngm:bc-defi-and-economics ;
skos:broader ngm:bc-defi-and-economics ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:impermanent-loss ;
vc:relatedTo ngm:liquidity-pool ;
vc:slug "amm-algorithm" ;
vc:sourceDomain "blockchain" .
ngm:amortised-inference a skos:Concept ;
rdfs:label "Amortised Inference"@en .
ngm:amount-hiding a skos:Concept ;
rdfs:label "Amount Hiding"@en .
ngm:amqp a owl:Class ;
rdfs:comment "AMQP (Advanced Message Queuing Protocol) is an open, binary application-layer protocol for message-oriented middleware that defines wire-level framing, message routing and reliable delivery between brokers and clients regardless of vendor or platform. It models messaging through exchanges, queues and bindings that decouple producers from consumers and support routing patterns including direct, topic, fanout and headers exchanges. AMQP 1.0 is standardised by OASIS and ISO/IEC 19464, while the earlier AMQP 0-9-1 specification remains widely deployed in broker implementations."@en ;
rdfs:label "AMQP"@en ;
rdfs:subClassOf ngm:network-protocol ;
vc:bridgesTo ngm:event-sourcing ;
vc:contrastsWith ngm:mqtt ;
vc:dependsOn ngm:api-gateway ;
vc:enables ngm:event-driven-architecture ;
vc:enables ngm:interoperability ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:asynchronous-communication ;
vc:implements ngm:publish-subscribe-pattern ;
vc:isPartOf ngm:middleware ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:cloud-computing ;
vc:slug "amqp" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:oasis ;
vc:supports ngm:network-protocol ;
vc:uses ngm:message-broker ;
vc:uses ngm:message-queue .
ngm:amrc a skos:Concept ;
rdfs:label "Amrc"@en .
ngm:amrc-sheffield a skos:Concept ;
rdfs:label "Amrc Sheffield"@en .
ngm:amsgrad a skos:Concept ;
rdfs:label "Amsgrad"@en .
ngm:analog-to-digital-converter a owl:Class ;
rdfs:comment "Analog To Digital Converter (ADC) is an electronic component that converts continuous analog signals such as sound, light, or voltage into discrete digital representations through sampling, quantization, and encoding processes, enabling digital processing, storage, and transmission of real-world ..."@en ;
rdfs:label "Analog To Digital Converter"@en ;
rdfs:subClassOf ngm:sc-display-and-rendering ;
rdfs:subClassOf ngm:signal-processing-hardware ;
rdfs:subClassOf _:r1669 ;
skos:broader ngm:sc-display-and-rendering ;
vc:bridgesTo ngm:robo-perception ;
vc:bridgesTo ngm:sensor-input ;
vc:enables ngm:digital-audio-recording ;
vc:enables ngm:digital-imaging ;
vc:enables ngm:sensor-data-processing ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:resolution-bits ;
vc:requires ngm:sampling-rate ;
vc:requires ngm:signal-conditioning ;
vc:slug "analog-to-digital-converter" ;
vc:sourceDomain "spatial-computing" .
ngm:analogue-circuit a skos:Concept ;
rdfs:label "Analogue Circuit"@en .
ngm:analogue-signal-processing a skos:Concept ;
rdfs:label "Analogue Signal Processing"@en .
ngm:analogue-to-digital-conversion a owl:Class ;
rdfs:comment "Analogue-to-digital conversion is the process of transforming a continuous physical signal, such as voltage from a sensor, into a discrete sequence of numerical values that a digital system can store and process. It proceeds by sampling the signal at regular intervals and quantising each sample to a finite set of levels, with the sampling rate and bit depth determining how faithfully the original is represented. In robotics and embedded systems it is the essential bridge between the analogue physical world and digital control and perception pipelines."@en ;
rdfs:label "Analogue To Digital Conversion"@en ;
rdfs:subClassOf ngm:signal-processing ;
rdfs:subClassOf _:r1670 ;
rdfs:subClassOf _:r1671 ;
rdfs:subClassOf _:r1672 ;
rdfs:subClassOf _:r1673 ;
vc:dependsOn ngm:sensor ;
vc:enables ngm:data-acquisition ;
vc:enables ngm:digital-signal-processing ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:analog-to-digital-converter ;
vc:hasPart ngm:sampling ;
vc:isPartOf ngm:data-acquisition ;
vc:isPartOf ngm:signal-processing ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:digital-signal-processing ;
vc:relatedTo ngm:embedded-system ;
vc:relatedTo ngm:signal-conditioning ;
vc:requires ngm:sensor ;
vc:requires ngm:signal-conditioning ;
vc:slug "analogue-to-digital-conversion" ;
vc:sourceDomain "robotics" ;
vc:supports ngm:embedded-system ;
vc:uses ngm:analog-to-digital-converter ;
vc:uses ngm:sampling .
ngm:analysis-template a skos:Concept ;
rdfs:label "Analysis Template"@en .
ngm:analytical-methods a skos:Concept ;
rdfs:label "Analytical Methods"@en .
ngm:analytics-dashboard a skos:Concept ;
rdfs:label "Analytics Dashboard"@en .
ngm:analytics-engine a owl:Class ;
rdfs:comment "A software system or distributed platform that ingests, processes, and analyses large volumes of structured and unstructured data to extract insights, detect patterns, and support decision-making. Analytics engines abstract the complexity of distributed query execution, storage management, and statistical computation behind APIs and query interfaces, enabling analysts and applications to perform exploratory, diagnostic, predictive, and prescriptive analysis at scale. They serve as the computational backbone of business intelligence platforms, ML pipelines, and real-time operational monitoring systems."@en ;
rdfs:label "Analytics Engine"@en ;
rdfs:subClassOf ngm:data-analytics ;
vc:enables ngm:machine-learning-discipline-pipeline ;
vc:enables ngm:real-time-monitoring ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:emotional-analytics-engine ;
vc:relatedTo ngm:telemetry-and-analytics ;
vc:slug "analytics-engine" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:data-lake ;
vc:uses ngm:data-pipeline ;
vc:uses ngm:stream-processing .
ngm:analytics-reporting a skos:Concept ;
rdfs:label "Analytics Reporting"@en .
ngm:analytics-service a skos:Concept ;
rdfs:label "Analytics Service"@en .
ngm:analytics-tools a skos:Concept ;
rdfs:label "Analytics Tools"@en .
ngm:anaphora-resolution a skos:Concept ;
rdfs:label "Anaphora Resolution"@en .
ngm:anarchic-coordination a skos:Concept ;
rdfs:label "Anarchic Coordination"@en .
ngm:anarchy a skos:Concept ;
rdfs:label "Anarchy"@en .
ngm:anchor-assignment a skos:Concept ;
rdfs:label "Anchor Assignment"@en .
ngm:anchor-based-detection a owl:Class ;
rdfs:comment "Anchor-based detection is an object detection approach that predicts bounding boxes and class scores relative to a fixed set of predefined reference boxes, called anchors, tiled densely across the image at multiple scales and aspect ratios. The network learns offsets that adjust each anchor to fit a nearby object rather than predicting box coordinates directly, which stabilises training and improves recall for objects of varying size. Faster R-CNN, SSD and the early YOLO versions are canonical anchor-based detectors, later contrasted with anchor-free alternatives."@en ;
rdfs:label "Anchor-Based Detection"@en ;
rdfs:subClassOf ngm:object-detection ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:slug "anchor-based-detection" ;
vc:sourceDomain "machine-learning" .
ngm:anchor-box a skos:Concept ;
rdfs:label "Anchor Box"@en .
ngm:anchor-persistence a skos:Concept ;
rdfs:label "Anchor Persistence"@en .
ngm:anchorage-digital a owl:Class ;
rdfs:comment "A United States digital asset platform that holds a federal bank charter and provides custody, trading, staking, and financing services for institutional clients. It was the first crypto firm to receive a national trust bank charter from the Office of the Comptroller of the Currency."@en ;
rdfs:label "Anchorage Digital"@en ;
rdfs:subClassOf ngm:self-custody ;
rdfs:subClassOf _:r1674 ;
vc:bridgesTo ngm:coinbase ;
vc:enables ngm:proof-of-stake ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:regulatory-compliance ;
vc:slug "anchorage-digital" ;
vc:sourceDomain "blockchain" .
ngm:andrey-kolmogorov a skos:Concept ;
rdfs:label "Andrey Kolmogorov"@en .
ngm:android a skos:Concept ;
rdfs:label "Android"@en .
ngm:android-platform a skos:Concept ;
rdfs:label "Android Platform"@en .
ngm:anemometer a owl:Class ;
rdfs:label "Anemometer"@en ;
rdfs:subClassOf ngm:measurement-instrument ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation ;
vc:slug "anemometer" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:angular a skos:Concept ;
rdfs:label "Angular"@en .
ngm:angular-coordinate a owl:Class ;
rdfs:label "Angular Coordinate"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:geodesy ;
vc:slug "angular-coordinate" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:animateanyone a skos:Concept ;
rdfs:label "Animateanyone"@en .
ngm:animatediff a skos:Concept ;
rdfs:label "Animatediff"@en .
ngm:animation a owl:Class ;
rdfs:comment "Animation is the technique of creating the illusion of movement by rapidly displaying a sequence of static images or by computationally interpolating between keyframe states of a scene or character over time. In digital contexts, animation encompasses skeletal rigging, keyframe interpolation, physics simulation, and procedural generation to produce lifelike motion in real-time or pre-rendered environments. Modern animation pipelines integrate motion capture data, inverse kinematics, and blend trees to deliver nuanced character performances. Animation is foundational to game engines, virtual reality, film, and interactive simulations."@en ;
rdfs:label "Animation"@en ;
rdfs:subClassOf ngm:animation-technique ;
rdfs:subClassOf _:r1690 ;
rdfs:subClassOf _:r1691 ;
rdfs:subClassOf _:r1692 ;
rdfs:subClassOf _:r1693 ;
rdfs:subClassOf _:r1694 ;
rdfs:subClassOf _:r1695 ;
rdfs:subClassOf _:r1696 ;
vc:bridgesTo ngm:generative-ai ;
vc:bridgesTo ngm:neural-motion-synthesis ;
vc:dependsOn ngm:game-engine ;
vc:dependsOn ngm:physics-simulation ;
vc:enables ngm:cinematic-rendering ;
vc:enables ngm:presence ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:blend-tree ;
vc:hasPart ngm:inverse-kinematics ;
vc:hasPart ngm:motion-capture ;
vc:hasPart ngm:procedural-animation ;
vc:hasPart ngm:skeletal-animation ;
vc:isPartOf ngm:computer-graphics ;
vc:isPartOf ngm:interactive-media ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:real-time-rendering ;
vc:relatedTo ngm:simulation ;
vc:requires ngm:character-rigging ;
vc:requires ngm:rendering-pipeline ;
vc:slug "animation" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:augmented-reality ;
vc:supports ngm:digital-twin ;
vc:supports ngm:virtual-reality ;
vc:uses ngm:animation-controller ;
vc:uses ngm:rendering-engine .
ngm:animation-channels a skos:Concept ;
rdfs:label "Animation Channels"@en .
ngm:animation-clip a owl:Class ;
rdfs:comment "An animation clip is a discrete, reusable unit of animation data, typically a time-ordered sequence of keyframes or pose samples for a skeleton or property set, such as a walk cycle or a wave gesture. Animation controllers and state machines reference clips as the atomic assets they blend, sequence and transition between at runtime. Clips are commonly authored once and retargeted across multiple character rigs that share a compatible skeleton."@en ;
rdfs:label "Animation Clip"@en ;
rdfs:subClassOf ngm:animation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:slug "animation-clip" ;
vc:sourceDomain "spatial-computing" .
ngm:animation-controller a owl:Class ;
rdfs:comment "An animation controller is a software component that manages the selection, blending, and sequencing of animation clips for a character or object in real-time interactive environments. It typically implements a state machine model in which transitions between animation states are governed by parametric conditions such as velocity, input events, or AI signals. Animation controllers sit between high-level game logic and the low-level skeletal animation runtime, abstracting away the complexity of blend trees, IK passes, and additive layers."@en ;
rdfs:label "Animation Controller"@en ;
rdfs:subClassOf ngm:controller ;
rdfs:subClassOf _:r1675 ;
rdfs:subClassOf _:r1676 ;
rdfs:subClassOf _:r1677 ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:bridgesTo ngm:reinforcement-learning ;
vc:dependsOn ngm:physics-engine ;
vc:enables ngm:animation-retargeting ;
vc:enables ngm:motion-matching ;
vc:enables ngm:procedural-animation ;
vc:enables ngm:real-time-rendering ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:blend-tree ;
vc:isPartOf ngm:game-engine ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:animation ;
vc:relatedTo ngm:character-animation ;
vc:relatedTo ngm:character-rigging ;
vc:relatedTo ngm:locomotion ;
vc:relatedTo ngm:procedural-animation ;
vc:relatedTo ngm:ragdoll-physics ;
vc:requires ngm:animation-clip ;
vc:requires ngm:character-rigging ;
vc:slug "animation-controller" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:animation-clip ;
vc:uses ngm:blend-tree ;
vc:uses ngm:inverse-kinematics ;
vc:uses ngm:skeletal-animation ;
vc:uses ngm:state-machine .
ngm:animation-keyframes a skos:Concept ;
rdfs:label "Animation Keyframes"@en .
ngm:animation-retargeting a owl:Class ;
rdfs:comment "Animation Retargeting is the process of transferring motion capture or animation data from one character skeleton to another with different proportions, joint configurations, or bone structures, enabling reuse of animation assets across diverse character models in games, film, and virtual environments."@en ;
rdfs:label "Animation Retargeting"@en ;
rdfs:subClassOf ngm:animation ;
rdfs:subClassOf ngm:sc-content-and-assets ;
rdfs:subClassOf _:r1678 ;
rdfs:subClassOf _:r1679 ;
skos:broader ngm:sc-content-and-assets ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:contrastsWith ngm:keyframe-animation ;
vc:contrastsWith ngm:procedural-animation ;
vc:dependsOn ngm:animation ;
vc:dependsOn ngm:motion-capture ;
vc:enables ngm:avatar ;
vc:enables ngm:avatar-animation ;
vc:enables ngm:character-animation ;
vc:enables ngm:motion-capture ;
vc:enables ngm:real-time-animation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:blend-shape ;
vc:relatedTo ngm:digital-humans ;
vc:relatedTo ngm:skinning ;
vc:requires ngm:character-rigging ;
vc:requires ngm:inverse-kinematics ;
vc:requires ngm:pose-matching ;
vc:requires ngm:skeleton-mapping ;
vc:slug "animation-retargeting" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:coordinate-transformation ;
vc:uses ngm:forward-kinematics .
ngm:animation-rig a owl:Class ;
rdfs:comment "An animation rig is a hierarchical system of bones, controls, and constraints applied to a 3D character or object to enable articulated movement for animation. It abstracts underlying mesh deformation through a control interface that animators manipulate, translating high-level poses into low-level vertex transformations. Rigs range from simple skeletal setups to complex systems incorporating inverse kinematics, blend shapes, and procedural dynamics."@en ;
rdfs:label "Animation Rig"@en ;
rdfs:subClassOf ngm:skeletal-animation ;
vc:enables ngm:character-animation ;
vc:enables ngm:procedural-animation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:3-d-animation ;
vc:relatedTo ngm:mesh-data ;
vc:slug "animation-rig" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:inverse-kinematics ;
vc:uses ngm:motion-capture .
ngm:animation-software a owl:Class ;
rdfs:comment "Animation Software encompasses digital tools and applications for creating computer-generated moving images through 3D modeling, rigging, motion graphics, rendering, and compositing, supporting the complete animation pipeline from asset creation to final output for games, film, and metaverse content."@en ;
rdfs:label "Animation Software"@en ;
rdfs:subClassOf ngm:digital-content-creation ;
rdfs:subClassOf ngm:sc-content-and-assets ;
rdfs:subClassOf _:r1680 ;
rdfs:subClassOf _:r1681 ;
rdfs:subClassOf _:r1682 ;
rdfs:subClassOf _:r1683 ;
rdfs:subClassOf _:r1684 ;
rdfs:subClassOf _:r1685 ;
rdfs:subClassOf _:r1686 ;
rdfs:subClassOf _:r1687 ;
skos:broader ngm:sc-content-and-assets ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:generative-ai ;
vc:bridgesTo ngm:metaverse ;
vc:contrastsWith ngm:game-engine ;
vc:enables ngm:character-animation ;
vc:enables ngm:motion-graphics ;
vc:enables ngm:real-time-rendering ;
vc:enables ngm:virtual-production ;
vc:enables ngm:visual-effects ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:character-rigging ;
vc:hasPart ngm:compositing ;
vc:hasPart ngm:motion-capture ;
vc:hasPart ngm:rendering-pipeline ;
vc:isPartOf ngm:digital-content-creation ;
vc:isPartOf ngm:production-pipeline ;
vc:qualityScore "0.68"^^xsd:float ;
vc:relatedTo ngm:extended-reality ;
vc:relatedTo ngm:game-development ;
vc:requires ngm:3d-modelling ;
vc:requires ngm:character-rigging ;
vc:requires ngm:gpu-rendering ;
vc:requires ngm:texture-mapping ;
vc:slug "animation-software" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:inverse-kinematics ;
vc:uses ngm:physically-based-rendering ;
vc:uses ngm:skeletal-animation .
ngm:animation-standard a owl:Class ;
rdfs:comment "A technical specification defining how skeletal rigs, keyframes, blend shapes, and motion data are represented and exchanged so that animated characters and objects behave consistently across metaverse platforms, game engines, and spatial computing runtimes, supporting interoperable avatar animation and real-time playback."@en ;
rdfs:label "Animation Standard"@en ;
rdfs:subClassOf ngm:sc-standards-and-interop ;
skos:broader ngm:sc-standards-and-interop ;
vc:bridgesTo ngm:computer-vision ;
vc:enables ngm:asset-interoperability ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:spatial-computing ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:avatar-animation ;
vc:relatedTo ngm:motion-capture ;
vc:slug "animation-standard" ;
vc:sourceDomain "spatial-computing" .
ngm:animation-state-machine a owl:Class ;
rdfs:comment "An animation state machine is a graph of discrete animation states and the transitions between them, used in real-time engines to drive a character or object's motion based on game logic, input and parameters. Each state references a clip or blend tree, and transitions carry conditions, blend durations and interruption rules that govern how one motion flows into another. It separates high-level behaviour authoring from low-level pose evaluation, making locomotion and action systems tractable to build and tune."@en ;
rdfs:label "Animation State Machine"@en ;
rdfs:subClassOf ngm:state-machine ;
rdfs:subClassOf _:r1688 ;
rdfs:subClassOf _:r1689 ;
vc:bridgesTo ngm:unreal-engine ;
vc:contrastsWith ngm:blend-tree ;
vc:dependsOn ngm:game-engine ;
vc:enables ngm:character-animation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:blend-tree ;
vc:implements ngm:finite-state-machine ;
vc:isPartOf ngm:character-animation ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:finite-state-machine ;
vc:relatedTo ngm:skeletal-animation ;
vc:requires ngm:skeletal-animation ;
vc:slug "animation-state-machine" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:game-engine ;
vc:supports ngm:game-engine ;
vc:uses ngm:blend-tree .
ngm:animation-system a skos:Concept ;
rdfs:label "Animation System"@en .
ngm:animation-technique a owl:Class ;
rdfs:comment "An Animation Technique is a method or algorithm for generating the illusion of motion in digital content, encompassing keyframe interpolation, skeletal rigging, physics-based simulation, and procedural approaches. Animation techniques are fundamental to character representation, environmental dynamics, and interactive responsiveness in spatial computing environments."@en ;
rdfs:label "Animation Technique"@en ;
rdfs:subClassOf ngm:sc-content-and-assets ;
skos:broader ngm:sc-content-and-assets ;
vc:bridgesTo ngm:computer-vision ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:3-d-animation ;
vc:relatedTo ngm:animation-retargeting ;
vc:relatedTo ngm:rendering-technique ;
vc:slug "animation-technique" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:game-engine ;
vc:uses ngm:motion-capture ;
vc:uses ngm:physics-simulation .
ngm:animation-tools a skos:Concept ;
rdfs:label "Animation Tools"@en .
ngm:ann-benchmarks a skos:Concept ;
rdfs:label "Ann Benchmarks"@en .
ngm:annals-of-probability a skos:Concept ;
rdfs:label "Annals Of Probability"@en .
ngm:annals-of-statistics a skos:Concept ;
rdfs:label "Annals Of Statistics"@en .
ngm:annotated-data a skos:Concept ;
rdfs:label "Annotated Data"@en .
ngm:annotated-dataset a owl:Class ;
rdfs:comment "A dataset in which each example carries human- or machine-assigned labels — class names, bounding boxes, segmentation masks, transcripts, action-unit codes, or relevance judgements — produced under a documented annotation scheme with quality controls such as inter-annotator agreement; annotated datasets are the primary fuel of supervised learning, and their coverage, label accuracy, and demographic balance bound the accuracy and fairness of every model trained on them."@en ;
rdfs:label "Annotated Dataset"@en ;
rdfs:subClassOf ngm:dataset ;
rdfs:subClassOf _:r1697 ;
vc:enables ngm:face-recognition ;
vc:enables ngm:supervised-learning ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:active-learning ;
vc:relatedTo ngm:synthetic-data-generation ;
vc:relatedTo ngm:training-data ;
vc:requires ngm:data-annotation ;
vc:slug "annotated-dataset" ;
vc:sourceDomain "machine-learning" .
ngm:annotated-training-data a owl:Class ;
rdfs:comment "Annotated Training Data is a dataset whose examples have been augmented with ground-truth labels, bounding boxes, segmentation masks, or other targets that supervised models learn to predict. The annotations are produced by humans, programmatic rules, or model-assisted labeling and define the task the model is trained to solve. Its quality, coverage, and label consistency are primary determinants of supervised-model performance."@en ;
rdfs:label "Annotated Training Data"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:machine-learning-discipline ;
skos:broader ngm:ai-technique ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:cross-validation ;
vc:relatedTo ngm:segmentation-and-identification ;
vc:slug "annotated-training-data" ;
vc:sourceDomain "data" .
ngm:annotation-overlay a skos:Concept ;
rdfs:label "Annotation Overlay"@en .
ngm:annotation-pipelines a skos:Concept ;
rdfs:label "Annotation Pipelines"@en .
ngm:annotation-property a skos:Concept ;
rdfs:label "Annotation Property"@en .
ngm:annotation-schema a skos:Concept ;
rdfs:label "Annotation Schema"@en .
ngm:annotation-schemes a skos:Concept ;
rdfs:label "Annotation Schemes"@en .
ngm:annotation-standards a skos:Concept ;
rdfs:label "Annotation Standards"@en .
ngm:annual-percentage-yield a skos:Concept ;
rdfs:label "Annual Percentage Yield"@en .
ngm:anoma a owl:Class ;
rdfs:comment "Anoma is a protocol and architecture for intent-centric and privacy-preserving decentralised applications. It allows users to express desired outcomes that the network matches and settles."@en ;
rdfs:label "Anoma"@en ;
rdfs:subClassOf ngm:distributed-systems ;
rdfs:subClassOf _:r1698 ;
vc:bridgesTo ngm:privacy ;
vc:enables ngm:de-fi ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:cryptography ;
vc:slug "anoma" ;
vc:sourceDomain "blockchain" .
ngm:anomaly-detection a owl:Class ;
rdfs:comment "Anomaly detection is a machine learning and statistical discipline concerned with identifying observations, sequences, or structural patterns that deviate significantly from a learned or assumed norm, signalling potential faults, threats, or novel phenomena. It operates across three principal modes: point anomaly detection (a single observation is outlying relative to the full dataset), contextual anomaly detection (an observation is anomalous given its local context, such as a transaction at an unusual time of day), and collective anomaly detection (a subsequence or group of observations is jointly anomalous relative to expected behaviour). The field draws on statistical modelling, machine learning, and signal processing to serve applications ranging from fraud detection and network intrusion detection to industrial fault monitoring, medical diagnostics, and log analysis."@en ;
rdfs:label "Anomaly Detection"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf _:r1699 ;
rdfs:subClassOf _:r1700 ;
rdfs:subClassOf _:r1701 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:network-security ;
vc:bridgesTo ngm:sensor-data ;
vc:contrastsWith ngm:classification ;
vc:contrastsWith ngm:supervised-learning ;
vc:dependsOn ngm:data-preprocessing ;
vc:dependsOn ngm:feature-engineering ;
vc:dependsOn ngm:pattern-recognition ;
vc:enables ngm:cybersecurity ;
vc:enables ngm:fraud-detection ;
vc:enables ngm:intrusion-detection-system ;
vc:enables ngm:model-monitoring ;
vc:enables ngm:predictive-maintenance ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:collective-anomaly-detection ;
vc:hasPart ngm:contextual-anomaly-detection ;
vc:hasPart ngm:point-anomaly-detection ;
vc:implements ngm:dbscan ;
vc:implements ngm:gaussian-mixture-model ;
vc:implements ngm:isolation-forest ;
vc:implements ngm:local-outlier-factor ;
vc:implements ngm:one-class-svm ;
vc:qualityScore "0.92"^^xsd:float ;
vc:relatedTo ngm:change-point-detection ;
vc:relatedTo ngm:concept-drift ;
vc:relatedTo ngm:foundation-model ;
vc:relatedTo ngm:model-monitoring ;
vc:relatedTo ngm:outlier-detection ;
vc:relatedTo ngm:time-series ;
vc:relatedTo ngm:time-series-forecasting ;
vc:requires ngm:data-preprocessing ;
vc:requires ngm:feature-engineering ;
vc:requires ngm:statistical-modelling ;
vc:requires ngm:threshold-calibration ;
vc:slug "anomaly-detection" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:network-security ;
vc:supports ngm:sensor-data ;
vc:uses ngm:active-learning ;
vc:uses ngm:autoencoder ;
vc:uses ngm:deep-learning ;
vc:uses ngm:graph-neural-network ;
vc:uses ngm:graph-neural-networks ;
vc:uses ngm:lstm ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:normalising-flows ;
vc:uses ngm:pattern-recognition ;
vc:uses ngm:shap ;
vc:uses ngm:transformer-architecture ;
vc:uses ngm:vae .
ngm:anon-creds a owl:Class ;
rdfs:comment "AnonCreds (Anonymous Credentials) is a verifiable credential format and specification originally developed by the Hyperledger Indy project that enables privacy-preserving identity verification. The scheme allows holders to prove possession of credentials without revealing the credential itself or the issuer's signature, using zero-knowledge proofs. AnonCreds supports selective disclosure, letting a holder share only specific attributes, and predicates that prove a claim (e.g. age over 18) without revealing the underlying value. The specification has been standardised via the AnonCreds Working Group under the Decentralized Identity Foundation."@en ;
rdfs:label "AnonCreds"@en ;
rdfs:subClassOf ngm:credential-format-standard ;
vc:enables ngm:differential-privacy ;
vc:enables ngm:privacy-preserving-technology ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:credential-schema ;
vc:relatedTo ngm:decentralised-identity ;
vc:relatedTo ngm:digital-identity-wallet ;
vc:slug "anon-creds" ;
vc:sourceDomain "security" ;
vc:supports ngm:authentication ;
vc:uses ngm:selective-disclosure ;
vc:uses ngm:zero-knowledge-proof .
ngm:anonymisation a owl:Class ;
rdfs:comment "Anonymisation is the process of transforming data so that individuals can no longer be identified, directly or by inference, while preserving enough utility for analysis. Techniques include suppression, generalization, pseudonymisation, k-anonymity, differential privacy, and the blurring or synthetic replacement of faces and identifiers in media. Effective anonymisation must resist re-identification through linkage with auxiliary data."@en ;
rdfs:label "Anonymisation"@en ;
rdfs:subClassOf ngm:infra-security-and-identity ;
skos:broader ngm:infra-security-and-identity ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:face-swap ;
vc:relatedTo ngm:privacy ;
vc:slug "anonymisation" ;
vc:sourceDomain "security" .
ngm:anonymity a owl:Class ;
rdfs:comment "Anonymity is the property of an actor being unidentifiable within a set of potential actors, so that actions cannot be linked to a real-world identity. It is a core privacy goal achieved through techniques that obscure identifying attributes, network paths and metadata. Anonymity contrasts with pseudonymity, where a persistent but non-identifying handle is retained."@en ;
rdfs:label "Anonymity"@en ;
rdfs:subClassOf ngm:privacy ;
rdfs:subClassOf _:r1702 ;
vc:bridgesTo ngm:security ;
vc:contrastsWith ngm:identity ;
vc:contrastsWith ngm:pseudonymity ;
vc:contrastsWith ngm:surveillance ;
vc:enables ngm:data-protection ;
vc:enables ngm:privacy ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:differential-privacy ;
vc:isPartOf ngm:privacy ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:authentication ;
vc:relatedTo ngm:metadata ;
vc:relatedTo ngm:tor ;
vc:relatedTo ngm:vpn ;
vc:requires ngm:cryptography ;
vc:slug "anonymity" ;
vc:sourceDomain "security" ;
vc:supports ngm:zero-knowledge-proof ;
vc:uses ngm:anonymisation ;
vc:uses ngm:encryption ;
vc:uses ngm:onion-routing .
ngm:anonymization a skos:Concept ;
rdfs:label "Anonymization"@en .
ngm:anonymous-access a skos:Concept ;
rdfs:label "Anonymous Access"@en .
ngm:anonymous-communication a owl:Class ;
rdfs:comment "Anonymous Communication is a set of network techniques that let parties exchange messages without revealing their identities or the link between sender and recipient to observers, typically by routing traffic through multiple relays with layered encryption. It protects against traffic analysis as well as content interception, and is a building block for privacy-preserving applications from whistleblowing platforms to private blockchain transactions. Onion routing is the most widely deployed implementation."@en ;
rdfs:label "Anonymous Communication"@en ;
rdfs:subClassOf ngm:cryptography-security-and-privacy ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "anonymous-communication" ;
vc:sourceDomain "security" .
ngm:anonymous-credential a owl:Class ;
rdfs:comment "An anonymous credential is a cryptographic attestation that lets a holder prove possession of certified attributes to a verifier without revealing their identity or allowing their presentations to be linked. Built on techniques such as blind signatures and zero-knowledge proofs, it supports selective disclosure of individual attributes while keeping the rest private. Anonymous credentials are a core privacy-enhancing primitive for authentication and access control."@en ;
rdfs:label "Anonymous Credential"@en ;
rdfs:subClassOf ngm:cryptographic-primitive ;
rdfs:subClassOf _:r1703 ;
vc:bridgesTo ngm:self-sovereign-identity ;
vc:contrastsWith ngm:digital-identity ;
vc:enables ngm:selective-disclosure ;
vc:enables ngm:unlinkability ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:verifiable-credential-vc ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:self-sovereign-identity ;
vc:relatedTo ngm:verifiable-credential-vc ;
vc:requires ngm:cryptographic-primitive ;
vc:slug "anonymous-credential" ;
vc:sourceDomain "security" ;
vc:supports ngm:privacy ;
vc:supports ngm:pseudonymity ;
vc:uses ngm:zero-knowledge-proof .
ngm:anonymous-credential-system a skos:Concept ;
rdfs:label "Anonymous Credential System"@en .
ngm:anonymous-cryptocurrency a skos:Concept ;
rdfs:label "Anonymous Cryptocurrency"@en .
ngm:anonymous-payment a skos:Concept ;
rdfs:label "Anonymous Payment"@en .
ngm:anonymous-payments a skos:Concept ;
rdfs:label "Anonymous Payments"@en .
ngm:anonymous-transaction a skos:Concept ;
rdfs:label "Anonymous Transaction"@en .
ngm:anonymous-transfers a skos:Concept ;
rdfs:label "Anonymous Transfers"@en .
ngm:ansi a owl:Class ;
rdfs:comment "ANSI, the American National Standards Institute, is a private non-profit organisation that oversees the development of voluntary consensus standards for products, services, processes, and systems in the United States. It does not write most standards itself but accredits standards developers and approves their output as American National Standards, and it represents the United States in international bodies such as ISO and IEC. In computing it is associated with standards such as ANSI C, ANSI SQL, and the ASCII character encoding."@en ;
rdfs:label "Ansi"@en ;
rdfs:subClassOf ngm:standards-body ;
vc:bridgesTo ngm:ieee ;
vc:bridgesTo ngm:iso ;
vc:contrastsWith ngm:ietf ;
vc:contrastsWith ngm:iso ;
vc:enables ngm:data-format ;
vc:enables ngm:interoperability ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:ieee ;
vc:relatedTo ngm:iso ;
vc:relatedTo ngm:nist ;
vc:relatedTo ngm:sql ;
vc:slug "ansi" ;
vc:sourceDomain "data" ;
vc:standardizedBy ngm:standards ;
vc:supports ngm:protocol ;
vc:supports ngm:standards .
ngm:ansi-incits-359 a skos:Concept ;
rdfs:label "Ansi Incits 359"@en .
ngm:ansi-ria-r15-06 a skos:Concept ;
rdfs:label "Ansi Ria R15 06"@en .
ngm:ansi-ria-r15-08 a skos:Concept ;
rdfs:label "Ansi Ria R15 08"@en .
ngm:ansi-sql a skos:Concept ;
rdfs:label "Ansi Sql"@en .
ngm:ansi-x9 a skos:Concept ;
rdfs:label "Ansi X9"@en .
ngm:ansible a skos:Concept ;
rdfs:label "Ansible"@en .
ngm:anssi-france a skos:Concept ;
rdfs:label "Anssi France"@en .
ngm:answer-ai a owl:Class ;
rdfs:comment "Answer.AI is an applied artificial intelligence research and development laboratory co-founded in December 2023 by Jeremy Howard and Eric Ries, whose mission is to build practical, openly shared tools and techniques that make modern machine learning accessible and useful to the widest possible audience. Distinct from capability-frontier laboratories, Answer.AI explicitly does not develop new foundation models or pursue artificial general intelligence; instead it focuses on taking existing models and determining what maximally practical applications can be built with them, continuing the fast.ai tradition of pragmatic, accessibility-first research. The lab operates as a small, fully remote team of deep-technology generalists and releases open-source libraries, frameworks, and educational resources covering efficient fine-tuning, parameter-efficient adaptation, distributed training on consumer hardware, and developer ergonomics for building AI-powered applications."@en ;
rdfs:label "Answer AI"@en ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf ngm:applied-machine-learning ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf _:r1704 ;
rdfs:subClassOf _:r1705 ;
rdfs:subClassOf _:r1706 ;
rdfs:subClassOf _:r1707 ;
rdfs:subClassOf _:r1708 ;
rdfs:subClassOf _:r1709 ;
rdfs:subClassOf _:r1710 ;
rdfs:subClassOf _:r1711 ;
skos:broader ngm:ai-research-area ;
vc:contrastsWith ngm:anthropic ;
vc:contrastsWith ngm:frontier-ai ;
vc:contrastsWith ngm:openai-research-organisation ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:deep-learning-framework ;
vc:dependsOn ngm:language-model ;
vc:dependsOn ngm:machine-learning-discipline-framework ;
vc:dependsOn ngm:transfer-learning ;
vc:enables ngm:agentic-ai ;
vc:enables ngm:applied-machine-learning ;
vc:enables ngm:education-and-ai ;
vc:enables ngm:instruction-tuning ;
vc:enables ngm:open-source-ai ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:distributed-training ;
vc:hasPart ngm:fast-ai ;
vc:hasPart ngm:fasthtml ;
vc:hasPart ngm:fsdp-qlora ;
vc:hasPart ngm:open-source-ai ;
vc:hasPart ngm:parameter-efficient-fine-tuning ;
vc:hasPart ngm:solveit ;
vc:implements ngm:distributed-training ;
vc:implements ngm:lo-ra-fine-tuning ;
vc:implements ngm:open-source-ai ;
vc:implements ngm:parameter-efficient-fine-tuning ;
vc:qualityScore "0.82"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:agentic-workflow ;
vc:relatedTo ngm:deep-learning ;
vc:relatedTo ngm:direct-preference-optimisation ;
vc:relatedTo ngm:education-and-ai ;
vc:relatedTo ngm:fast-ai ;
vc:relatedTo ngm:instruction-tuning ;
vc:relatedTo ngm:language-model ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:machine-learning-accelerator ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:machine-learning-discipline-infrastructure ;
vc:relatedTo ngm:open-source-ai ;
vc:relatedTo ngm:parameter-efficient-fine-tuning ;
vc:relatedTo ngm:reinforcement-learning-from-human-feedback ;
vc:relatedTo ngm:transfer-learning ;
vc:requires ngm:deep-learning-framework ;
vc:requires ngm:foundation-model ;
vc:requires ngm:large-language-models ;
vc:requires ngm:python-programming-language ;
vc:slug "answer-ai" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:open-source-ai ;
vc:supports ngm:applied-machine-learning ;
vc:supports ngm:education-and-ai ;
vc:supports ngm:machine-learning-discipline-infrastructure ;
vc:supports ngm:open-source-ai ;
vc:uses ngm:direct-preference-optimisation ;
vc:uses ngm:distributed-training ;
vc:uses ngm:foundation-model ;
vc:uses ngm:lo-ra-fine-tuning ;
vc:uses ngm:python-programming-language ;
vc:uses ngm:quantisation ;
vc:uses ngm:reinforcement-learning-from-human-feedback .
ngm:answer-extractor a skos:Concept ;
rdfs:label "Answer Extractor"@en .
ngm:answer-set-programming a skos:Concept ;
rdfs:label "Answer Set Programming"@en .
ngm:answer-synthesis a skos:Concept ;
rdfs:label "Answer Synthesis"@en .
ngm:answer-synthesiser a skos:Concept ;
rdfs:label "Answer Synthesiser"@en .
ngm:ant-colony-optimisation a skos:Concept ;
rdfs:label "Ant Colony Optimisation"@en .
ngm:ant-pool a owl:Class ;
rdfs:comment "AntPool is a Bitcoin mining pool operated in association with Bitmain. It is one of the larger pools by share of network hash rate."@en ;
rdfs:label "AntPool"@en ;
rdfs:subClassOf ngm:mining-pool ;
rdfs:subClassOf _:r1712 ;
vc:bridgesTo ngm:bitmain ;
vc:enables ngm:transaction-validation ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:bitcoin-proof-of-work-protocol-mining ;
vc:slug "ant-pool" ;
vc:sourceDomain "blockchain" .
ngm:antecedent-scoring a skos:Concept ;
rdfs:label "Antecedent Scoring"@en .
ngm:antenna-array a owl:Class ;
rdfs:comment "An Antenna Array is a set of multiple antenna elements arranged and phased together so that their combined radiation pattern can be electronically steered and shaped. By controlling the relative phase and amplitude of each element, the array forms directional beams, increases gain, and supports spatial multiplexing in techniques such as MIMO and beamforming. Arrays are foundational to modern wireless radio, 5G, radar, and precise satellite positioning receivers."@en ;
rdfs:label "Antenna Array"@en ;
rdfs:subClassOf ngm:infra-network-and-comms ;
skos:broader ngm:infra-network-and-comms ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:gps ;
vc:relatedTo ngm:wireless-radio ;
vc:slug "antenna-array" ;
vc:sourceDomain "infrastructure" .
ngm:antenna-gain a owl:Class ;
rdfs:label "Antenna Gain"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:satellite-communication ;
vc:slug "antenna-gain" ;
vc:sourceDomain "space-science-and-systems" .
ngm:anthropic a owl:Class ;
rdfs:comment "Anthropic is a frontier AI safety company and public-benefit corporation founded in 2021 by Dario Amodei, Daniela Amodei, and colleagues formerly at OpenAI, whose primary mission is the responsible development and maintenance of advanced AI for the long-term benefit of humanity. The company develops and deploys the Claude family of large language models, distinguished by a Constitutional AI training methodology that uses AI self-critique and revision against explicit principles to systematically reduce harmful outputs. Anthropic's research agenda spans mechanistic interpretability, scalable oversight, red-teaming, and the Responsible Scaling Policy — a formal commitment tying capability advancement to mandatory safety evaluations at defined dangerous-capability thresholds. By mid-2026 Anthropic had reached a valuation of approximately $965 billion, filed confidential IPO documentation, and maintained partnerships with Amazon Web Services, Google, Microsoft, and Nvidia. As a public-benefit corporation, Anthropic occupies a distinctive position among frontier AI laboratories by integrating commercial model deployment with open publication of alignment and interpretability research."@en ;
rdfs:label "Anthropic"@en ;
rdfs:subClassOf ngm:ai-safety-research ;
rdfs:subClassOf ngm:frontier-ai ;
rdfs:subClassOf _:r1713 ;
rdfs:subClassOf _:r1714 ;
rdfs:subClassOf _:r1715 ;
rdfs:subClassOf _:r1716 ;
rdfs:subClassOf _:r1717 ;
rdfs:subClassOf _:r1718 ;
rdfs:subClassOf _:r1719 ;
rdfs:subClassOf _:r1720 ;
rdfs:subClassOf _:r1721 ;
rdfs:subClassOf _:r1722 ;
vc:bridgesTo ngm:ai-regulation ;
vc:bridgesTo ngm:ai-safety-institute ;
vc:bridgesTo ngm:compute-governance ;
vc:bridgesTo ngm:eu-ai-act-regulatory-instrument ;
vc:contrastsWith ngm:google-ai-technology-corporation-deep-mind ;
vc:contrastsWith ngm:meta-ai ;
vc:contrastsWith ngm:openai-research-organisation ;
vc:dependsOn ngm:direct-preference-optimisation ;
vc:dependsOn ngm:instruction-tuning ;
vc:dependsOn ngm:reinforcement-learning-from-human-feedback ;
vc:dependsOn ngm:rlhf ;
vc:dependsOn ngm:scalable-oversight ;
vc:enables ngm:agentic-ai ;
vc:enables ngm:agentic-workflow ;
vc:enables ngm:ai-safety ;
vc:enables ngm:claude ;
vc:enables ngm:frontier-model-evaluation ;
vc:enables ngm:language-model-alignment ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:claude ;
vc:hasPart ngm:constitutional-ai-training-methodology ;
vc:hasPart ngm:mechanistic-interpretability ;
vc:hasPart ngm:model-context-protocol ;
vc:hasPart ngm:responsible-scaling-policy ;
vc:implements ngm:constitutional-ai-training-methodology ;
vc:implements ngm:frontier-model-evaluation ;
vc:implements ngm:responsible-scaling-policy ;
vc:implements ngm:rlhf ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:agentic-workflow ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:ai-safety-research ;
vc:relatedTo ngm:compute-governance ;
vc:relatedTo ngm:frontier-ai ;
vc:relatedTo ngm:frontier-model-forum ;
vc:relatedTo ngm:frontier-model-training ;
vc:relatedTo ngm:frontier-models ;
vc:relatedTo ngm:interpretability ;
vc:relatedTo ngm:responsible-scaling-policy ;
vc:relatedTo ngm:rlhf ;
vc:requires ngm:foundation-model ;
vc:requires ngm:frontier-model-training ;
vc:requires ngm:frontier-models ;
vc:requires ngm:large-language-models ;
vc:requires ngm:transformer-architecture ;
vc:slug "anthropic" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:frontier-model-forum ;
vc:supports ngm:ai-alignment ;
vc:supports ngm:ai-governance ;
vc:supports ngm:ai-safety ;
vc:supports ngm:ai-safety-research ;
vc:supports ngm:interpretability ;
vc:supports ngm:language-model-alignment ;
vc:supports ngm:scalable-oversight ;
vc:uses ngm:constitutional-ai-training-methodology ;
vc:uses ngm:direct-preference-optimisation ;
vc:uses ngm:large-language-models ;
vc:uses ngm:mechanistic-interpretability ;
vc:uses ngm:red-teaming ;
vc:uses ngm:reinforcement-learning-from-human-feedback ;
vc:uses ngm:transformer-architecture .
ngm:anthropic-agent-skills a skos:Concept ;
rdfs:label "Anthropic Agent Skills"@en .
ngm:anthropic-agent-skills-open-standard a skos:Concept ;
rdfs:label "Anthropic Agent Skills Open Standard"@en .
ngm:anthropic-claude a skos:Concept ;
rdfs:label "Anthropic Claude"@en .
ngm:anthropic-claude-api a skos:Concept ;
rdfs:label "Anthropic Claude API"@en .
ngm:anthropic-economic-index a owl:Class ;
rdfs:comment "A research initiative by Anthropic that analyzes large-scale data from Claude interactions to quantify the economic impact, productivity gains, and usage patterns of AI in professional workflows."@en ;
rdfs:label "Anthropic Economic Index"@en ;
rdfs:subClassOf ngm:economics ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-adoption ;
vc:relatedTo ngm:anthropic ;
vc:slug "anthropic-economic-index" ;
vc:sourceDomain "economics" .
ngm:anthropic-extended-thinking a skos:Concept ;
rdfs:label "Anthropic Extended Thinking"@en .
ngm:anthropic-mcp-specification-v0-1 a skos:Concept ;
rdfs:label "Anthropic Mcp Specification V0 1"@en .
ngm:anthropic-prompt-engineering-guide a skos:Concept ;
rdfs:label "Anthropic Prompt Engineering Guide"@en .
ngm:anthropic-research a skos:Concept ;
rdfs:label "Anthropic Research"@en .
ngm:anthropic-responsible-scaling-policy a skos:Concept ;
rdfs:label "Anthropic Responsible Scaling Policy"@en .
ngm:anti-aliasing a owl:Class ;
rdfs:comment "Anti-aliasing is a family of rendering techniques that reduce the jagged, stair-stepped edges and shimmering artefacts that arise when continuous geometry and signals are sampled onto a discrete pixel grid. By increasing effective sampling, blending edge pixels, or reconstructing from accumulated samples, anti-aliasing produces smoother, more visually faithful images. It is a standard stage of real-time and offline rendering pipelines, with methods such as supersampling, multisampling, post-process filtering, and temporal accumulation."@en ;
rdfs:label "Anti Aliasing"@en ;
rdfs:subClassOf ngm:real-time-rendering ;
rdfs:subClassOf _:r1723 ;
rdfs:subClassOf _:r1724 ;
rdfs:subClassOf _:r1725 ;
vc:dependsOn ngm:gpu ;
vc:enables ngm:rasterization ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:post-processing ;
vc:hasPart ngm:sampling ;
vc:isPartOf ngm:real-time-rendering ;
vc:isPartOf ngm:rendering-pipeline ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:computer-graphics ;
vc:relatedTo ngm:offline-rendering ;
vc:relatedTo ngm:rasterization ;
vc:relatedTo ngm:ray-tracing ;
vc:relatedTo ngm:texture-mapping ;
vc:requires ngm:graphics-pipeline ;
vc:slug "anti-aliasing" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:rasterization ;
vc:uses ngm:gpu ;
vc:uses ngm:sampling .
ngm:anti-aliasing-filter a skos:Concept ;
rdfs:label "Anti Aliasing Filter"@en .
ngm:anti-collusion-voting a skos:Concept ;
rdfs:label "Anti Collusion Voting"@en .
ngm:anti-counterfeiting a owl:Class ;
rdfs:comment "Blockchain-based systems employing cryptographic verification, immutable ledgers, and physical-digital integration technologies (NFC tags, QR codes, RFID) to authenticate products, prevent counterfeiting, and establish verifiable supply chain provenance across pharmaceuticals, luxury goods, electronics, and consumer products."@en ;
rdfs:label "Anti Counterfeiting"@en ;
rdfs:subClassOf ngm:network-component ;
rdfs:subClassOf ngm:supply-chain-blockchain ;
rdfs:subClassOf _:r1726 ;
rdfs:subClassOf _:r1727 ;
vc:bridgesTo ngm:autonomous-robot ;
vc:enables ngm:luxury-goods-authentication ;
vc:enables ngm:supply-chain-traceability ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:pharmaceutical-traceability ;
vc:hasPart ngm:supply-chain-management ;
vc:qualityScore "0.5"^^xsd:float ;
vc:slug "anti-counterfeiting" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:blockchain-compliance ;
vc:uses ngm:blockchain ;
vc:uses ngm:smart-contract .
ngm:anti-curriculum a skos:Concept ;
rdfs:label "Anti Curriculum"@en .
ngm:anti-money-laundering a owl:Class ;
rdfs:comment "Anti-Money Laundering (AML) encompasses the legislative frameworks, regulatory obligations, and operational procedures that financial institutions and other regulated entities must implement to detect, prevent, and report the concealment and integration of proceeds from criminal activity. AML programmes are built around customer due diligence (CDD), enhanced due diligence (EDD) for high-risk relationships, continuous transaction monitoring, suspicious activity reporting (SAR), and sanctions screening against watch-lists maintained by bodies such as OFAC, the EU, and the UN. International standards are promulgated by the Financial Action Task Force (FATF) through its Forty Recommendations and transposed into national law by member jurisdictions, covering banks, virtual asset service providers (VASPs), lawyers, accountants, and real-estate agents. Modern AML increasingly relies on machine learning, graph analytics, and RegTech automation to surface complex layering schemes that evade traditional rule-based systems."@en ;
rdfs:label "Anti-Money Laundering"@en ;
rdfs:subClassOf ngm:regulatory-compliance ;
rdfs:subClassOf _:r1728 ;
rdfs:subClassOf _:r1729 ;
rdfs:subClassOf _:r1730 ;
rdfs:subClassOf _:r1731 ;
rdfs:subClassOf _:r1732 ;
rdfs:subClassOf _:r1733 ;
rdfs:subClassOf _:r1734 ;
rdfs:subClassOf _:r1735 ;
rdfs:subClassOf _:r1736 ;
rdfs:subClassOf _:r1737 ;
vc:bridgesTo ngm:federated-learning ;
vc:bridgesTo ngm:zero-knowledge-proof ;
vc:contrastsWith ngm:financial-privacy ;
vc:contrastsWith ngm:privacy-preserving-computation ;
vc:enables ngm:asset-recovery ;
vc:enables ngm:financial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:customer-due-diligence ;
vc:hasPart ngm:kyc ;
vc:hasPart ngm:sanctions-screening ;
vc:hasPart ngm:suspicious-activity-report ;
vc:hasPart ngm:transaction-monitoring ;
vc:isPartOf ngm:financial-crime-detection ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:blockchain-compliance ;
vc:relatedTo ngm:counter-terrorist-financing ;
vc:relatedTo ngm:financial-crime-detection ;
vc:relatedTo ngm:regtech ;
vc:requires ngm:fraud-detection ;
vc:requires ngm:identity-verification ;
vc:requires ngm:regulatory-compliance ;
vc:requires ngm:risk-management ;
vc:slug "anti-money-laundering" ;
vc:sourceDomain "finance" ;
vc:standardizedBy ngm:basel-committee-on-banking-supervision ;
vc:standardizedBy ngm:financial-action-task-force ;
vc:uses ngm:anomaly-detection ;
vc:uses ngm:graph-neural-network ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:natural-language-processing .
ngm:anti-plutocratic-governance a skos:Concept ;
rdfs:label "Anti Plutocratic Governance"@en .
ngm:anti-spoofing-module a skos:Concept ;
rdfs:label "Anti Spoofing Module"@en .
ngm:anti-windup a skos:Concept ;
rdfs:label "Anti Windup"@en .
ngm:antibody-design a skos:Concept ;
rdfs:label "Antibody Design"@en .
ngm:antitrust-oversight a skos:Concept ;
rdfs:label "Antitrust Oversight"@en .
ngm:antitrust-policy a skos:Concept ;
rdfs:label "Antitrust Policy"@en .
ngm:antitrust-regulation a skos:Concept ;
rdfs:label "Antitrust Regulation"@en .
ngm:anvil a skos:Concept ;
rdfs:label "Anvil"@en .
ngm:anycast-routing a owl:Class ;
rdfs:comment "Anycast routing is a network addressing and routing technique in which a single IP address is advertised from multiple geographically distributed locations, and packets are delivered to whichever instance is nearest by the routing metric. It uses standard internet routing to steer each client to the closest available node, reducing latency and distributing load without client awareness. Anycast underpins resilient DNS, content delivery, and DDoS mitigation by enabling automatic failover and traffic absorption across many sites."@en ;
rdfs:label "Anycast Routing"@en ;
rdfs:subClassOf ngm:routing-protocol ;
rdfs:subClassOf _:r1738 ;
vc:bridgesTo ngm:edge-computing ;
vc:dependsOn ngm:load-balancing ;
vc:enables ngm:failover ;
vc:enables ngm:high-availability ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:infrastructure ;
vc:relatedTo ngm:latency ;
vc:relatedTo ngm:load-balancer ;
vc:requires ngm:geographic-distribution ;
vc:slug "anycast-routing" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:cdn ;
vc:supports ngm:dns ;
vc:uses ngm:ip-addressing ;
vc:uses ngm:network-routing ;
vc:uses ngm:routing-protocol .
ngm:ao-compute a skos:Concept ;
rdfs:label "Ao Compute"@en .
ngm:aom-av1-specification a skos:Concept ;
rdfs:label "Aom AV1 Specification"@en .
ngm:aousd a skos:Concept ;
rdfs:label "Aousd"@en .
ngm:apache-airflow a skos:Concept ;
rdfs:label "Apache Airflow"@en .
ngm:apache-atlas a owl:Class ;
rdfs:comment "Apache Atlas is an open-source metadata management and data governance framework, originally built for the Hadoop ecosystem, that catalogs data assets, captures end-to-end lineage, and enforces classification and access policies. It exposes a typed metadata model and search so organizations can discover datasets, trace how data flows between systems, and apply governance tags. Atlas integrates with engines such as Hive, Kafka, and HBase to collect lineage automatically."@en ;
rdfs:label "Apache Atlas"@en ;
rdfs:subClassOf ngm:data-management ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:metadata-management ;
vc:slug "apache-atlas" ;
vc:sourceDomain "data" .
ngm:apache-avro a skos:Concept ;
rdfs:label "Apache Avro"@en .
ngm:apache-flink a owl:Class ;
rdfs:comment "Apache Flink is an open-source distributed engine for stateful computations over unbounded and bounded data streams. It provides a unified runtime that treats batch processing as a special case of streaming, with event-time semantics, sophisticated windowing, and exactly-once state consistency backed by distributed snapshots. Flink is widely used for low-latency, high-throughput stream processing in real-time analytics, event-driven applications, and continuous data pipelines."@en ;
rdfs:label "Apache Flink"@en ;
rdfs:subClassOf ngm:stream-processing ;
vc:contrastsWith ngm:apache-spark ;
vc:contrastsWith ngm:batch-processing ;
vc:dependsOn ngm:distributed-computing ;
vc:enables ngm:real-time-analytics ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:stream-processing ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-replication ;
vc:relatedTo ngm:eventual-consistency ;
vc:slug "apache-flink" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:apache-kafka ;
vc:uses ngm:data-pipeline ;
vc:uses ngm:distributed-computing ;
vc:uses ngm:quorum .
ngm:apache-hudi a skos:Concept ;
rdfs:label "Apache Hudi"@en .
ngm:apache-iceberg a owl:Class ;
rdfs:comment "Apache Iceberg is an open table format for large analytic datasets stored in data lakes, adding database-like guarantees on top of object storage. It provides ACID transactions, schema and partition evolution, snapshot isolation, and time-travel queries by maintaining immutable metadata layers that track data files. Iceberg decouples the table format from the compute engine, letting Spark, Trino, Flink, and others operate consistently on the same tables."@en ;
rdfs:label "Apache Iceberg"@en ;
rdfs:subClassOf ngm:data-management ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:storage-infrastructure ;
vc:slug "apache-iceberg" ;
vc:sourceDomain "data" .
ngm:apache-jena a skos:Concept ;
rdfs:label "Apache Jena"@en .
ngm:apache-kafka a owl:Class ;
rdfs:comment "Apache Kafka is an open-source distributed event streaming platform originally developed at LinkedIn and donated to the Apache Software Foundation in 2011. It provides a high-throughput, low-latency, fault-tolerant publish-subscribe messaging system built around an immutable, ordered, partitioned commit log. Kafka decouples producers and consumers of data streams, enabling real-time data pipelines, event-driven architectures, and stream processing applications at scale across thousands of nodes handling trillions of events per day."@en ;
rdfs:label "Apache Kafka"@en ;
rdfs:subClassOf ngm:distributed-system ;
vc:dependsOn ngm:distributed-architecture ;
vc:dependsOn ngm:software-infrastructure ;
vc:enables ngm:data-lake ;
vc:enables ngm:etl-pipeline ;
vc:enables ngm:machine-learning-discipline-pipeline ;
vc:enables ngm:microservices-architecture ;
vc:enables ngm:real-time ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:data-integration ;
vc:relatedTo ngm:data-pipeline ;
vc:relatedTo ngm:distributed-systems ;
vc:relatedTo ngm:event-driven-architecture ;
vc:relatedTo ngm:real-time-processing ;
vc:slug "apache-kafka" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:cloud-infrastructure ;
vc:supports ngm:monitoring-dashboard ;
vc:uses ngm:batch-processing ;
vc:uses ngm:data-processing ;
vc:uses ngm:distributed-computing .
ngm:apache-licence a skos:Concept ;
rdfs:label "Apache Licence"@en .
ngm:apache-license-2-0 a owl:Class ;
rdfs:comment "The Apache License 2.0 (AL2) is a permissive free and open-source software licence published by the Apache Software Foundation in 2004, allowing users to freely use, modify, distribute, and sublicence covered works in both open and proprietary contexts. It requires preservation of copyright notices and a NOTICE file but imposes no copyleft obligations on derivatives. Uniquely among major permissive licences, AL2 includes an explicit patent grant and a patent retaliation clause that terminates rights upon initiation of patent litigation against the licensor."@en ;
rdfs:label "Apache License 2.0"@en ;
rdfs:subClassOf ngm:intellectual-property-licence-instrument ;
vc:enables ngm:open-source-development ;
vc:enables ngm:open-source-software ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:compliance ;
vc:relatedTo ngm:licensing-requirements ;
vc:slug "apache-license-2-0" ;
vc:sourceDomain "governance" ;
vc:supports ngm:open-source-ai ;
vc:supports ngm:open-source-framework .
ngm:apache-lucene a skos:Concept ;
rdfs:label "Apache Lucene"@en .
ngm:apache-nutch a skos:Concept ;
rdfs:label "Apache Nutch"@en .
ngm:apache-parquet a owl:Class ;
rdfs:comment "Apache Parquet is an open-source columnar storage file format designed for efficient analytical processing of large datasets. By storing values of the same column contiguously, it enables aggressive compression and encoding, predicate pushdown, and reading only the columns a query needs, dramatically reducing I/O for analytical workloads. It carries a self-describing schema and rich metadata, and is widely used as the on-disk format for data lakes and big-data engines."@en ;
rdfs:label "Apache Parquet"@en ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf ngm:data-format ;
rdfs:subClassOf _:r1739 ;
skos:broader ngm:blockchain ;
vc:bridgesTo ngm:data-warehouse ;
vc:dependsOn ngm:data-serialization ;
vc:enables ngm:big-data ;
vc:enables ngm:olap ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:columnar-storage ;
vc:isPartOf ngm:data-lake ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:apache-spark ;
vc:relatedTo ngm:big-data ;
vc:relatedTo ngm:data-lake ;
vc:relatedTo ngm:data-warehouse ;
vc:requires ngm:data-format ;
vc:slug "apache-parquet" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:apache-spark ;
vc:supports ngm:schema-evolution ;
vc:uses ngm:columnar-storage ;
vc:uses ngm:data-serialization .
ngm:apache-pulsar a skos:Concept ;
rdfs:label "Apache Pulsar"@en .
ngm:apache-software-foundation a skos:Concept ;
rdfs:label "Apache Software Foundation"@en .
ngm:apache-spark a owl:Class ;
rdfs:comment "Apache Spark is an open-source unified analytics engine for large-scale data processing across clusters of machines. It exposes high-level APIs for batch processing, structured queries, stream processing and machine learning, and accelerates workloads by keeping intermediate data in memory between operations. Spark abstracts distributed datasets as fault-tolerant collections and schedules computations as directed acyclic graphs of stages, making it a foundational tool for big-data engineering and analytics."@en ;
rdfs:label "Apache Spark"@en ;
rdfs:subClassOf ngm:distributed-computing ;
vc:bridgesTo ngm:apache-kafka ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:contrastsWith ngm:apache-flink ;
vc:dependsOn ngm:scalability ;
vc:enables ngm:big-data ;
vc:enables ngm:data-processing ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:data-pipeline ;
vc:isPartOf ngm:data-engineering ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:big-data ;
vc:relatedTo ngm:data-engineering ;
vc:slug "apache-spark" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:batch-processing ;
vc:supports ngm:stream-processing ;
vc:uses ngm:distributed-computing ;
vc:uses ngm:in-memory-computing .
ngm:apache-tinker-pop a skos:Concept ;
rdfs:label "Apache Tinker Pop"@en .
ngm:apache-tinkerpop a skos:Concept ;
rdfs:label "Apache Tinkerpop"@en .
ngm:apache-trino a skos:Concept ;
rdfs:label "Apache Trino"@en .
ngm:apache-tvm a skos:Concept ;
rdfs:label "Apache Tvm"@en .
ngm:ape a skos:Concept ;
rdfs:label "Ape"@en .
ngm:apec-cbpr a skos:Concept ;
rdfs:label "Apec Cbpr"@en .
ngm:apecoin-dao a skos:Concept ;
rdfs:label "Apecoin DAO"@en .
ngm:api a owl:Class ;
rdfs:comment "An Application Programming Interface: a defined set of operations, inputs, and outputs through which software components or services communicate without exposing their internal implementation, enabling modular composition and system integration."@en ;
rdfs:label "API"@en ;
rdfs:subClassOf ngm:software-engineering ;
rdfs:subClassOf _:r864 ;
rdfs:subClassOf _:r865 ;
rdfs:subClassOf _:r866 ;
rdfs:subClassOf _:r867 ;
vc:bridgesTo ngm:http ;
vc:bridgesTo ngm:interoperability-standards ;
vc:bridgesTo ngm:smart-contract ;
vc:bridgesTo ngm:spatial-computing ;
vc:enables ngm:interoperability ;
vc:enables ngm:microservices ;
vc:enables ngm:service-integration ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:versioning-system ;
vc:implements ngm:g-rpc ;
vc:implements ngm:graph-ql ;
vc:implements ngm:rest ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:rate-limiting ;
vc:relatedTo ngm:software-architecture ;
vc:requires ngm:authentication ;
vc:requires ngm:communication-protocols ;
vc:requires ngm:data-serialization ;
vc:slug "api" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:interoperability-standards ;
vc:standardizedBy ngm:open-api-specification ;
vc:uses ngm:http ;
vc:uses ngm:json-data-interchange-format ;
vc:uses ngm:oauth .
ngm:api-access a skos:Concept ;
rdfs:label "API Access"@en .
ngm:api-contract a owl:Class ;
rdfs:comment "An API contract is the agreed, machine-readable specification of how a service may be called and what it will return, covering endpoints, request and response schemas, data types, status codes and error semantics. It functions as a formal agreement between the provider and consumers of an interface, allowing each side to develop and test independently against a shared definition. Expressed in formats such as OpenAPI or GraphQL schemas, the contract enables tooling for validation, mocking, code generation and compatibility checking across versions."@en ;
rdfs:label "Api Contract"@en ;
rdfs:subClassOf ngm:data-schema ;
rdfs:subClassOf _:r1740 ;
rdfs:subClassOf _:r1741 ;
rdfs:subClassOf _:r1742 ;
rdfs:subClassOf _:r1743 ;
vc:enables ngm:backward-compatibility ;
vc:enables ngm:data-validation ;
vc:enables ngm:interoperability ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:api-versioning ;
vc:hasPart ngm:schema ;
vc:implements ngm:open-api-specification ;
vc:implements ngm:rest-api ;
vc:isPartOf ngm:api-design ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:api ;
vc:relatedTo ngm:graph-ql ;
vc:requires ngm:data-schema ;
vc:requires ngm:schema ;
vc:slug "api-contract" ;
vc:sourceDomain "data" ;
vc:standardizedBy ngm:open-api-specification ;
vc:supports ngm:api-gateway ;
vc:supports ngm:microservices ;
vc:uses ngm:semantic-versioning .
ngm:api-contract-testing a skos:Concept ;
rdfs:label "API Contract Testing"@en .
ngm:api-design a owl:Class ;
rdfs:comment "API design is the discipline of specifying the contract, structure, and behaviour of an application programming interface so that it is consistent, intuitive, evolvable, and reliable for the developers who consume it. It covers resource and operation modelling, naming and conventions, request and response schemas, error semantics, authentication, versioning, and documentation, balancing usability against the constraints of the underlying system. Good API design treats the interface as a long-lived product whose contract must remain stable and backward-compatible while still allowing the implementation behind it to evolve."@en ;
rdfs:label "API Design"@en ;
rdfs:subClassOf ngm:software-architecture ;
rdfs:subClassOf _:r827 ;
rdfs:subClassOf _:r828 ;
rdfs:subClassOf _:r829 ;
rdfs:subClassOf _:r830 ;
vc:bridgesTo ngm:api-gateway ;
vc:bridgesTo ngm:microservices ;
vc:contrastsWith ngm:graph-ql ;
vc:dependsOn ngm:software-architecture ;
vc:enables ngm:interoperability ;
vc:enables ngm:microservices ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:api-versioning ;
vc:hasPart ngm:interface-design ;
vc:implements ngm:graph-ql ;
vc:implements ngm:rest-api ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:interface-design ;
vc:relatedTo ngm:rest-api ;
vc:requires ngm:api-security ;
vc:requires ngm:backward-compatibility ;
vc:slug "api-design" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:api-gateway ;
vc:supports ngm:rate-limiting ;
vc:uses ngm:http ;
vc:uses ngm:open-api-specification .
ngm:api-discoverability a skos:Concept ;
rdfs:label "API Discoverability"@en .
ngm:api-economy a owl:Class ;
rdfs:comment "The API economy is the ecosystem of business value created when organisations expose their data and services as application-programming interfaces that other parties can consume, compose, and monetise. By packaging capabilities as products, firms turn internal functions into reusable building blocks that partners and developers integrate, enabling new revenue streams, faster innovation, and platform network effects. It underpins models such as open banking and embedded services, and its growth depends on robust API management, gateways, and developer experience to govern access, security, and consumption at scale."@en ;
rdfs:label "Api Economy"@en ;
rdfs:subClassOf ngm:platform-economy ;
rdfs:subClassOf _:r1744 ;
rdfs:subClassOf _:r1745 ;
vc:bridgesTo ngm:digital-platform ;
vc:bridgesTo ngm:open-banking ;
vc:dependsOn ngm:application-programming-interface ;
vc:enables ngm:microservices ;
vc:enables ngm:platform-economy ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:interoperability ;
vc:requires ngm:api ;
vc:requires ngm:api-management ;
vc:slug "api-economy" ;
vc:sourceDomain "finance" ;
vc:supports ngm:webhook ;
vc:uses ngm:api-gateway ;
vc:uses ngm:graph-ql ;
vc:uses ngm:rest-api .
ngm:api-first-web a skos:Concept ;
rdfs:label "API First Web"@en .
ngm:api-gateway a owl:Class ;
rdfs:comment "Infrastructure component serving as the unified northbound entry point for client requests into a Distributed System|distributed or Microservices|microservices backend, providing cross-cutting policy enforcement (request routing across hundreds-to-thousands of upstream services, authentic..."@en ;
rdfs:label "API Gateway"@en ;
rdfs:subClassOf ngm:cloud-native-component ;
rdfs:subClassOf ngm:infra-network-and-comms ;
rdfs:subClassOf ngm:middleware ;
rdfs:subClassOf ngm:network-infrastructure ;
rdfs:subClassOf ngm:policy-enforcement-point ;
rdfs:subClassOf ngm:reverse-proxy ;
rdfs:subClassOf _:r831 ;
rdfs:subClassOf _:r832 ;
rdfs:subClassOf _:r833 ;
rdfs:subClassOf _:r834 ;
skos:broader ngm:infra-network-and-comms ;
vc:contrastsWith ngm:cdn ;
vc:contrastsWith ngm:enterprise-service-bus ;
vc:contrastsWith ngm:load-balancer ;
vc:contrastsWith ngm:reverse-proxy ;
vc:contrastsWith ngm:service-mesh ;
vc:dependsOn ngm:dns ;
vc:dependsOn ngm:http ;
vc:dependsOn ngm:http-protocol ;
vc:dependsOn ngm:service-discovery ;
vc:dependsOn ngm:tcp-ip ;
vc:dependsOn ngm:tls ;
vc:enables ngm:api-management ;
vc:enables ngm:backend-for-frontend ;
vc:enables ngm:graphql-federation ;
vc:enables ngm:microservices ;
vc:enables ngm:multi-tenancy ;
vc:enables ngm:strangler-fig-pattern ;
vc:enables ngm:zero-trust-architecture ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:access-log-emitter ;
vc:hasPart ngm:authentication-handler ;
vc:hasPart ngm:distributed-tracing-collector ;
vc:hasPart ngm:health-checker ;
vc:hasPart ngm:plugin-runtime ;
vc:hasPart ngm:rate-limiter ;
vc:hasPart ngm:request-router ;
vc:hasPart ngm:request-transformer ;
vc:hasPart ngm:response-cache ;
vc:hasPart ngm:tls-terminator ;
vc:implements ngm:bulkhead-pattern ;
vc:implements ngm:circuit-breaker ;
vc:implements ngm:jwt ;
vc:implements ngm:mtls ;
vc:implements ngm:oauth-2-0 ;
vc:implements ngm:oidc ;
vc:implements ngm:rate-limiting ;
vc:implements ngm:retry-pattern ;
vc:implements ngm:token-bucket-algorithm ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:ai-gateway ;
vc:relatedTo ngm:api-management ;
vc:relatedTo ngm:cdn ;
vc:relatedTo ngm:identity-aware-proxy ;
vc:relatedTo ngm:ingress-controller ;
vc:relatedTo ngm:service-mesh ;
vc:relatedTo ngm:web-application-firewall ;
vc:requires ngm:access-control-system ;
vc:requires ngm:certificate-authority ;
vc:requires ngm:configuration-store ;
vc:requires ngm:identity-provider ;
vc:requires ngm:observability-pipeline ;
vc:requires ngm:service-discovery ;
vc:slug "api-gateway" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:cncf ;
vc:standardizedBy ngm:ietf ;
vc:standardizedBy ngm:kubernetes-gateway-api ;
vc:standardizedBy ngm:openapi-initiative ;
vc:supports ngm:g-rpc ;
vc:supports ngm:graph-ql ;
vc:supports ngm:mqtt ;
vc:supports ngm:rest ;
vc:supports ngm:server-sent-events ;
vc:supports ngm:web-socket ;
vc:supports ngm:webhook ;
vc:uses ngm:asyncapi ;
vc:uses ngm:open-api-specification ;
vc:uses ngm:open-telemetry ;
vc:uses ngm:prometheus ;
vc:uses ngm:protobuf ;
vc:uses ngm:protocol-buffer ;
vc:uses ngm:w3c-trace-context .
ngm:api-integration a owl:Class ;
rdfs:comment "API Integration is the discipline of connecting disparate software systems, services, and data sources through Application Programming Interfaces to achieve seamless interoperability and automated data exchange. It encompasses the design, implementation, orchestration, and maintenance of integration layers — including synchronous REST and GraphQL calls, asynchronous message queues, webhook-based push notifications, and event-driven streams — that allow applications to communicate via standardised contracts while abstracting the complexity of underlying system differences. Effective API integration reduces manual data transfer, accelerates business workflows, and forms the structural backbone of modern microservices, cloud-native, and composable enterprise architectures. Integration governance concerns — versioning, rate limiting, authentication, observability, and schema evolution — are integral to sustaining reliable integrations at scale."@en ;
rdfs:label "API Integration"@en ;
rdfs:subClassOf ngm:software-engineering ;
rdfs:subClassOf _:r835 ;
rdfs:subClassOf _:r836 ;
rdfs:subClassOf _:r837 ;
rdfs:subClassOf _:r838 ;
rdfs:subClassOf _:r839 ;
rdfs:subClassOf _:r840 ;
rdfs:subClassOf _:r841 ;
rdfs:subClassOf _:r842 ;
vc:bridgesTo ngm:ai-agent ;
vc:bridgesTo ngm:blockchain-oracle ;
vc:contrastsWith ngm:enterprise-service-bus ;
vc:contrastsWith ngm:point-to-point-integration ;
vc:enables ngm:composable-architecture ;
vc:enables ngm:data-pipeline ;
vc:enables ngm:digital-transformation ;
vc:enables ngm:event-driven-architecture ;
vc:enables ngm:microservices-architecture ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:api-gateway ;
vc:hasPart ngm:api-versioning ;
vc:hasPart ngm:rate-limiting ;
vc:hasPart ngm:webhook ;
vc:qualityScore "0.73"^^xsd:float ;
vc:relatedTo ngm:cloud-computing ;
vc:relatedTo ngm:data-integration ;
vc:relatedTo ngm:distributed-system ;
vc:relatedTo ngm:integration-platform-as-a-service ;
vc:relatedTo ngm:service-mesh ;
vc:requires ngm:authentication-service ;
vc:requires ngm:data-serialization ;
vc:requires ngm:network-protocol ;
vc:slug "api-integration" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:asyncapi ;
vc:standardizedBy ngm:open-api-specification ;
vc:uses ngm:graph-ql ;
vc:uses ngm:message-queue ;
vc:uses ngm:middleware ;
vc:uses ngm:oauth ;
vc:uses ngm:rest-api .
ngm:api-key-authentication a owl:Class ;
rdfs:comment "API key authentication is a simple scheme in which a client includes a static, secret key with each request to identify and authenticate itself to an API. The server checks the key against issued keys to grant or deny access and to attribute usage and rate limits. Although easy to adopt, it offers coarse-grained control and weaker security than token-based or signature-based schemes because the long-lived key alone confers access."@en ;
rdfs:label "Api Key Authentication"@en ;
rdfs:subClassOf ngm:authentication ;
rdfs:subClassOf _:r1746 ;
vc:bridgesTo ngm:identity-provider ;
vc:contrastsWith ngm:bearer-token ;
vc:contrastsWith ngm:mutual-tls ;
vc:dependsOn ngm:authentication ;
vc:enables ngm:api ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:authentication ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:api ;
vc:relatedTo ngm:authorization ;
vc:relatedTo ngm:oauth ;
vc:relatedTo ngm:token ;
vc:requires ngm:encryption ;
vc:slug "api-key-authentication" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:standards ;
vc:supports ngm:authorization ;
vc:uses ngm:token .
ngm:api-lifecycle a owl:Class ;
rdfs:comment "The end-to-end progression of an application programming interface from design and specification through implementation, publication, versioning, monitoring, deprecation, and eventual retirement. Managing the API lifecycle as a deliberate process — with contract-first design, semantic versioning, sunset policies, and consumer migration paths — is what keeps evolving service interfaces stable for the clients that depend on them."@en ;
rdfs:label "API Lifecycle"@en ;
rdfs:subClassOf ngm:api-management ;
rdfs:subClassOf _:r843 ;
rdfs:subClassOf _:r844 ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:api-design ;
vc:hasPart ngm:api-versioning ;
vc:hasPart ngm:deprecation ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:api-gateway ;
vc:slug "api-lifecycle" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:semantic-versioning .
ngm:api-management a owl:Class ;
rdfs:comment "API Management is the discipline and tooling concerned with designing, publishing, documenting, securing, monitoring, and analysing application programming interfaces throughout their lifecycle. It provides a centralised control plane that governs how internal and external consumers discover and consume backend services, enforcing policies such as authentication, rate-limiting, and traffic shaping at a gateway layer. Modern API management platforms combine developer portals, analytics dashboards, and policy engines to ensure reliability, security, and business alignment across distributed service ecosystems."@en ;
rdfs:label "API Management"@en ;
rdfs:subClassOf ngm:technology-infrastructure ;
rdfs:subClassOf _:r845 ;
rdfs:subClassOf _:r846 ;
rdfs:subClassOf _:r847 ;
rdfs:subClassOf _:r848 ;
rdfs:subClassOf _:r849 ;
vc:bridgesTo ngm:data-governance ;
vc:contrastsWith ngm:enterprise-service-bus ;
vc:contrastsWith ngm:service-mesh ;
vc:dependsOn ngm:load-balancer ;
vc:dependsOn ngm:service-discovery ;
vc:enables ngm:api-integration ;
vc:enables ngm:api-monetisation ;
vc:enables ngm:microservices-architecture ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:api-gateway ;
vc:hasPart ngm:authentication-service ;
vc:hasPart ngm:developer-portal ;
vc:hasPart ngm:monitoring-system ;
vc:implements ngm:open-api-specification ;
vc:implements ngm:zero-trust-architecture ;
vc:isPartOf ngm:cloud-native-architecture ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:container-orchestration ;
vc:requires ngm:identity-provider ;
vc:requires ngm:tls ;
vc:slug "api-management" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:api-standard ;
vc:standardizedBy ngm:openapi-initiative ;
vc:supports ngm:api-versioning ;
vc:supports ngm:rest-api ;
vc:uses ngm:graph-ql ;
vc:uses ngm:json-data-interchange-format-web-token ;
vc:uses ngm:oauth-2-0 .
ngm:api-monetisation a owl:Class ;
rdfs:comment "The practice of generating revenue directly from programmatic interfaces by metering consumption and charging for it — through subscription tiers, pay-per-call and usage-based pricing, revenue sharing, or machine-payable protocols such as L402 — turning an API from an integration mechanism into a product with its own pricing, packaging, billing, and developer-experience lifecycle."@en ;
rdfs:label "API Monetisation"@en ;
rdfs:subClassOf ngm:api-management ;
vc:dependsOn ngm:lightning-network ;
vc:dependsOn ngm:micropayment ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:isPartOf ngm:api-management ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:streaming-payment ;
vc:slug "api-monetisation" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:api-gateway ;
vc:uses ngm:rate-limiting .
ngm:api-only-agent a skos:Concept ;
rdfs:label "API Only Agent"@en .
ngm:api-only-ai-services a skos:Concept ;
rdfs:label "API Only AI Services"@en .
ngm:api-rate-limiting a skos:Concept ;
rdfs:label "API Rate Limiting"@en .
ngm:api-reference a skos:Concept ;
rdfs:label "API Reference"@en .
ngm:api-reference-generation a skos:Concept ;
rdfs:label "API Reference Generation"@en .
ngm:api-security a owl:Class ;
rdfs:comment "API security is the discipline of protecting application programming interfaces from misuse, abuse, and attack across their lifecycle, covering authentication, authorisation, input validation, transport encryption, rate limiting, and monitoring. As APIs expose business logic and data directly to clients and partners, they present a broad attack surface addressed through tokens such as OAuth and JWT, gateways, and threat modelling against risks like broken object-level authorisation. It is a core component of modern application and web security."@en ;
rdfs:label "API Security"@en ;
rdfs:subClassOf ngm:security ;
rdfs:subClassOf _:r850 ;
rdfs:subClassOf _:r851 ;
rdfs:subClassOf _:r852 ;
rdfs:subClassOf _:r853 ;
vc:enables ngm:api-management ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:api-gateway ;
vc:hasPart ngm:rate-limiting ;
vc:implements ngm:zero-trust-architecture ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:microservices ;
vc:relatedTo ngm:penetration-testing ;
vc:requires ngm:authentication ;
vc:requires ngm:authorization ;
vc:slug "api-security" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:tls ;
vc:supports ngm:api-design ;
vc:supports ngm:rest-api ;
vc:uses ngm:encryption ;
vc:uses ngm:mutual-tls ;
vc:uses ngm:oauth ;
vc:uses ngm:tls .
ngm:api-server-protocol a skos:Concept ;
rdfs:label "API Server Protocol"@en .
ngm:api-specification a owl:Class ;
rdfs:comment "An API Specification is a formal, machine-readable document that precisely defines the interface contract of a software API, including its endpoints, request and response schemas, authentication requirements, and error codes. It enables automated tooling such as code generation, validation, and interactive documentation to be derived directly from a single source of truth. Common specification formats include OpenAPI, AsyncAPI, and GraphQL SDL."@en ;
rdfs:label "API Specification"@en ;
rdfs:subClassOf ngm:software-engineering ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.7"^^xsd:float ;
vc:relatedTo ngm:web-services ;
vc:slug "api-specification" ;
vc:sourceDomain "infrastructure" .
ngm:api-specifications a skos:Concept ;
rdfs:label "API Specifications"@en .
ngm:api-standard a owl:Class ;
rdfs:comment "Specification defining how independent software components communicate, establishing protocols, data formats, versioning rules, and authentication mechanisms to ensure interoperability across systems and platforms."@en ;
rdfs:label "API Standard"@en ;
rdfs:subClassOf ngm:infra-network-and-comms ;
rdfs:subClassOf _:r854 ;
rdfs:subClassOf _:r855 ;
rdfs:subClassOf _:r856 ;
rdfs:subClassOf _:r857 ;
rdfs:subClassOf _:r858 ;
rdfs:subClassOf _:r859 ;
rdfs:subClassOf _:r860 ;
skos:broader ngm:infra-network-and-comms ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:smart-contract ;
vc:bridgesTo ngm:spatial-computing-runtime ;
vc:contrastsWith ngm:proprietary-interface ;
vc:dependsOn ngm:identity-and-access-management ;
vc:dependsOn ngm:transport-layer ;
vc:enables ngm:component-integration ;
vc:enables ngm:microservices-architecture ;
vc:enables ngm:system-interoperability ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:api-versioning ;
vc:hasPart ngm:authentication-schema ;
vc:hasPart ngm:communication-protocol ;
vc:hasPart ngm:data-format-standard ;
vc:implements ngm:open-api-specification ;
vc:implements ngm:rest ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:service-mesh ;
vc:requires ngm:schema-definition ;
vc:requires ngm:technical-documentation ;
vc:slug "api-standard" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:etsi ;
vc:standardizedBy ngm:ietf ;
vc:standardizedBy ngm:w3-c ;
vc:supports ngm:api-gateway ;
vc:supports ngm:developer-portal ;
vc:uses ngm:http-protocol ;
vc:uses ngm:json-data-interchange-format .
ngm:api-standards a skos:Concept ;
rdfs:label "API Standards"@en .
ngm:api-testing a skos:Concept ;
rdfs:label "API Testing"@en .
ngm:api-versioning a owl:Class ;
rdfs:comment "API versioning is the discipline of evolving a programmatic interface over time while controlling the impact of changes on existing consumers. It defines how new versions are identified, published, and retired, and how backward compatibility is preserved or broken deliberately. Sound versioning lets providers innovate without forcing every client to upgrade in lockstep."@en ;
rdfs:label "API Versioning"@en ;
rdfs:subClassOf ngm:api-management ;
rdfs:subClassOf _:r861 ;
rdfs:subClassOf _:r862 ;
rdfs:subClassOf _:r863 ;
vc:enables ngm:microservices ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:backward-compatibility ;
vc:hasPart ngm:deprecation ;
vc:hasPart ngm:semantic-versioning ;
vc:isPartOf ngm:api-lifecycle ;
vc:isPartOf ngm:api-management ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:api-design ;
vc:relatedTo ngm:api-gateway ;
vc:relatedTo ngm:rest ;
vc:requires ngm:api-design ;
vc:slug "api-versioning" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:open-api-specification ;
vc:supports ngm:api-management ;
vc:supports ngm:backward-compatibility ;
vc:uses ngm:open-api-specification ;
vc:uses ngm:semantic-versioning .
ngm:api3 a skos:Concept ;
rdfs:label "Api3"@en .
ngm:apilayer a owl:Class ;
rdfs:comment "The API Layer is the stratum that exposes a system's capabilities as callable, contractually defined endpoints. It sits above the application logic it fronts and below integration and interface strata that connect consumers. It contains endpoint definitions, request and response schemas, authentication hooks, and versioning."@en ;
rdfs:label "APILayer"@en ;
rdfs:subClassOf ngm:owl-thing ;
rdfs:subClassOf ngm:software-engineering ;
rdfs:subClassOf _:r868 ;
vc:bridgesTo ngm:open-api-specification ;
vc:bridgesTo ngm:rest ;
vc:enables ngm:integration-layer ;
vc:enables ngm:interface-layer ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:application-layer ;
vc:slug "apilayer" ;
vc:sourceDomain "infrastructure" .
ngm:apoapsis a owl:Class ;
rdfs:label "Apoapsis"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:orbital-dynamics ;
vc:slug "apoapsis" ;
vc:sourceDomain "space-science-and-systems" .
ngm:apogee a owl:Class ;
rdfs:label "Apogee"@en ;
rdfs:subClassOf ngm:apoapsis ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:orbital-dynamics ;
vc:slug "apogee" ;
vc:sourceDomain "space-science-and-systems" .
ngm:apollo-research a skos:Concept ;
rdfs:label "Apollo Research"@en .
ngm:app-store a skos:Concept ;
rdfs:label "App Store"@en .
ngm:apparent-magnitude a owl:Class ;
rdfs:label "Apparent Magnitude"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:astronomy ;
vc:slug "apparent-magnitude" ;
vc:sourceDomain "space-science-and-systems" .
ngm:appdaemon a skos:Concept ;
rdfs:label "Appdaemon"@en .
ngm:appeal-mechanism a skos:Concept ;
rdfs:label "Appeal Mechanism"@en .
ngm:appeal-process a skos:Concept ;
rdfs:label "Appeal Process"@en .
ngm:appearance-translation a owl:Class ;
rdfs:comment "Appearance Translation refers to neural style transfer and image-to-image translation techniques that use deep learning to transform the visual style of images or video while preserving semantic content, enabling artistic stylization, domain adaptation, and visual content transformation across di..."@en ;
rdfs:label "Appearance Translation"@en ;
rdfs:subClassOf ngm:neural-image-processing ;
rdfs:subClassOf ngm:sc-display-and-rendering ;
rdfs:subClassOf _:r1747 ;
rdfs:subClassOf _:r1748 ;
skos:broader ngm:sc-display-and-rendering ;
vc:bridgesTo ngm:computer-vision ;
vc:enables ngm:artistic-stylization ;
vc:enables ngm:domain-adaptation ;
vc:enables ngm:visual-content-transformation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:content-preservation ;
vc:requires ngm:convolutional-neural-network ;
vc:requires ngm:style-representations ;
vc:slug "appearance-translation" ;
vc:sourceDomain "spatial-computing" .
ngm:append-only-data-structure a skos:Concept ;
rdfs:label "Append Only Data Structure"@en .
ngm:append-only-database a skos:Concept ;
rdfs:label "Append Only Database"@en .
ngm:append-only-log a owl:Class ;
rdfs:comment "An append-only log is a data structure in which records can only be added to the end and never modified or deleted in place, producing an immutable, totally ordered sequence of events. Each entry is durably persisted before subsequent entries, giving a tamper-evident history that consumers can replay deterministically from any offset. Append-only logs underpin event sourcing, distributed ledgers, write-ahead logging and certificate transparency, where verifiability and an authoritative ordering of changes are required."@en ;
rdfs:label "Append-Only Log"@en ;
rdfs:subClassOf ngm:data-structure ;
rdfs:subClassOf _:r1749 ;
vc:bridgesTo ngm:blockchain ;
vc:enables ngm:audit-log ;
vc:enables ngm:certificate-transparency ;
vc:enables ngm:non-repudiation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:event-sourcing ;
vc:implements ngm:immutability ;
vc:isPartOf ngm:distributed-ledger ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:blockchain-ledger ;
vc:relatedTo ngm:merkle-tree ;
vc:requires ngm:data-integrity ;
vc:slug "append-only-log" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:data-replication ;
vc:uses ngm:cryptographic-hash ;
vc:uses ngm:hash-function .
ngm:apple-core-ml a skos:Concept ;
rdfs:label "Apple Core ML"@en .
ngm:apple-differential-privacy a skos:Concept ;
rdfs:label "Apple Differential Privacy"@en .
ngm:apple-homekit a skos:Concept ;
rdfs:label "Apple Homekit"@en .
ngm:apple-inc-technology-corporation a owl:Class ;
rdfs:comment "Apple Inc. is an American multinational technology corporation headquartered in Cupertino, California, that designs, manufactures, and markets consumer electronics, computer software, and online services spanning smartphones, personal computers, wearables, and spatial computing devices. Its strategic foundation rests on vertical integration of proprietary silicon (Apple Silicon, A-series, M-series SoCs), operating system platforms (iOS, macOS, visionOS, watchOS), and tightly controlled distribution through the App Store and developer ecosystem. Apple applies on-device machine learning inference, secure enclave hardware, and private cloud compute to deliver privacy-preserving AI features — branded Apple Intelligence — across its device portfolio. As one of the highest market-capitalisation companies globally, Apple's architectural decisions in silicon design, software APIs, and platform policy propagate directly into industry-wide infrastructure and standards."@en ;
rdfs:label "Apple Inc Technology Corporation"@en ;
rdfs:subClassOf ngm:hardware ;
rdfs:subClassOf _:r1750 ;
vc:bridgesTo ngm:federated-learning ;
vc:bridgesTo ngm:large-language-model ;
vc:bridgesTo ngm:spatial-ai ;
vc:contrastsWith ngm:android ;
vc:contrastsWith ngm:google-ai-technology-corporation ;
vc:contrastsWith ngm:microsoft ;
vc:enables ngm:augmented-reality ;
vc:enables ngm:on-device-learning ;
vc:enables ngm:private-cloud-compute ;
vc:enables ngm:spatial-computing ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:app-store ;
vc:hasPart ngm:apple-inc-technology-corporation-vision-pro ;
vc:hasPart ngm:apple-silicon ;
vc:hasPart ngm:ios ;
vc:hasPart ngm:macos ;
vc:implements ngm:arm-architecture ;
vc:implements ngm:neural-processing-unit ;
vc:implements ngm:secure-enclave ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:digital-markets-act ;
vc:relatedTo ngm:platform-economy ;
vc:relatedTo ngm:supply-chain-management ;
vc:slug "apple-inc-technology-corporation" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:compiler ;
vc:uses ngm:hardware-acceleration ;
vc:uses ngm:unified-memory-architecture .
ngm:apple-inc-technology-corporation-mixed-reality-headset a owl:Class ;
rdfs:comment "A mixed reality headset developed by Apple, announced in 2023 and released in 2024. It blends digital content with the user's surroundings using high-resolution displays and eye, hand, and voice input."@en ;
rdfs:label "Apple Mixed Reality Headset"@en ;
rdfs:subClassOf ngm:mixed-reality ;
rdfs:subClassOf _:r1751 ;
vc:bridgesTo ngm:apple-inc-technology-corporation ;
vc:enables ngm:augmented-reality ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:spatial-computing ;
vc:requires ngm:spatial-computing-paradigm ;
vc:slug "apple-mixed-reality-headset" ;
vc:sourceDomain "metaverse" .
ngm:apple-inc-technology-corporation-vision-pro a owl:Class ;
rdfs:comment "Apple Vision Pro is a spatial computing head-mounted display developed by Apple, announced in June 2023 and released in the United States in February 2024, running the visionOS operating system. It combines ultra-high-resolution micro-OLED displays, a custom R1 chip for sensor processing, and an M2 chip for compute, enabling a fully immersive or passthrough-composited mixed reality experience. The device employs eye-tracking, hand-tracking, and voice input as its primary interaction modalities, replacing the traditional touchscreen paradigm with gaze-and-pinch gesture control."@en ;
rdfs:label "Apple Vision Pro"@en ;
rdfs:subClassOf ngm:head-mounted-display ;
rdfs:subClassOf _:r1752 ;
rdfs:subClassOf _:r1753 ;
rdfs:subClassOf _:r1754 ;
rdfs:subClassOf _:r1755 ;
vc:bridgesTo ngm:human-computer-interaction ;
vc:bridgesTo ngm:metaverse ;
vc:contrastsWith ngm:meta-quest ;
vc:contrastsWith ngm:tele-025-microsoft-hololens ;
vc:enables ngm:immersive-experience ;
vc:enables ngm:mixed-reality ;
vc:enables ngm:spatial-computing ;
vc:enables ngm:spatial-user-interfaces ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:apple-inc-technology-corporation ;
vc:hasPart ngm:apple-inc-technology-corporation-vision-pro ;
vc:hasPart ngm:micro-oled-display ;
vc:isPartOf ngm:apple-inc-technology-corporation ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:display-technology ;
vc:relatedTo ngm:extended-reality ;
vc:relatedTo ngm:wearable-computing ;
vc:requires ngm:computer-vision ;
vc:requires ngm:spatial-computing-runtime ;
vc:slug "apple-vision-pro" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:eye-tracking ;
vc:uses ngm:hand-tracking ;
vc:uses ngm:passthrough-video ;
vc:uses ngm:realitykit ;
vc:uses ngm:spatial-audio .
ngm:apple-metal a skos:Concept ;
rdfs:label "Apple Metal"@en .
ngm:apple-mixed-reality-headsetcessing a owl:Class ;
rdfs:comment "Vision processing is the computational transformation of raw image and video data into structured representations and decisions, spanning low-level operations such as filtering and feature extraction through high-level recognition and interpretation. It is the algorithmic core of computer-vision systems and specialised applications such as medical imaging. Efficient vision processing increasingly runs on dedicated accelerators to meet real-time demands."@en ;
rdfs:label "Vision Processing"@en ;
rdfs:subClassOf ngm:computer-vision ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:image-segmentation ;
vc:relatedTo ngm:medical-imaging-ai ;
vc:slug "vision-processing" ;
vc:sourceDomain "ai" .
ngm:apple-neural-engine a skos:Concept ;
rdfs:label "Apple Neural Engine"@en .
ngm:apple-pay a skos:Concept ;
rdfs:label "Apple Pay"@en .
ngm:apple-silicon a skos:Concept ;
rdfs:label "Apple Silicon"@en .
ngm:apple-supplier-responsibility a skos:Concept ;
rdfs:label "Apple Supplier Responsibility"@en .
ngm:apple-visionos-hand-input a skos:Concept ;
rdfs:label "Apple Visionos Hand Input"@en .
ngm:application-ai-companies a skos:Concept ;
rdfs:label "Application AI Companies"@en .
ngm:application-api a skos:Concept ;
rdfs:label "Application API"@en .
ngm:application-architecture a skos:Concept ;
rdfs:label "Application Architecture"@en .
ngm:application-binary-interface a owl:Class ;
rdfs:comment "An application binary interface (ABI) is the specification of how software components interact at the binary level, defining calling conventions, data layout and, for smart contracts, the encoding used to invoke functions and pass arguments. On blockchains such as Ethereum, a contract's ABI describes its callable functions, events and parameter types in a machine-readable form that clients use to encode transactions and decode returned data. It is what allows external tools, wallets and other contracts to interact correctly with a deployed contract without access to its source code."@en ;
rdfs:label "Application Binary Interface"@en ;
rdfs:subClassOf ngm:interface ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.65"^^xsd:float ;
vc:relatedTo ngm:token-standard ;
vc:slug "application-binary-interface" ;
vc:sourceDomain "blockchain" .
ngm:application-debug-log a skos:Concept ;
rdfs:label "Application Debug Log"@en .
ngm:application-development a owl:Class ;
rdfs:comment "Application development is the systematic process of designing, building, testing, and deploying software applications to meet specified user or organisational requirements, encompassing activities from requirements analysis through to release and maintenance. It involves selecting appropriate technology stacks, architectural patterns, and development methodologies to produce reliable, maintainable, and performant software. The discipline spans mobile, web, desktop, and embedded application domains, each with distinct toolchains and constraints."@en ;
rdfs:label "Application Development"@en ;
rdfs:subClassOf ngm:software-development ;
vc:enables ngm:cloud-native-applications ;
vc:enables ngm:platform-service ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:microservices ;
vc:relatedTo ngm:software-development-process ;
vc:slug "application-development" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:api-integration ;
vc:uses ngm:cloud-computing ;
vc:uses ngm:software-engineering .
ngm:application-domain a skos:Concept ;
rdfs:label "Application Domain"@en .
ngm:application-layer a owl:Class ;
rdfs:comment "Software layer providing domain-specific application interfaces and services for metaverse experiences including education, commerce, healthcare, and entertainment applications."@en ;
rdfs:label "Application Layer"@en ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf _:r1756 ;
rdfs:subClassOf _:r1757 ;
rdfs:subClassOf _:r1758 ;
rdfs:subClassOf _:r1759 ;
skos:broader ngm:sc-platform-and-environment ;
vc:bridgesTo ngm:telecollaboration ;
vc:dependsOn ngm:content-delivery ;
vc:dependsOn ngm:identity-services ;
vc:dependsOn ngm:platform-services ;
vc:enables ngm:business-services ;
vc:enables ngm:cross-platform-interoperability ;
vc:enables ngm:domain-specific-applications ;
vc:enables ngm:user-experience ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:application-api ;
vc:hasPart ngm:business-logic-layer ;
vc:hasPart ngm:service-interface ;
vc:hasPart ngm:user-interface-framework ;
vc:isPartOf ngm:metaverse-architecture-stack ;
vc:isPartOf ngm:metaverse-stack ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:compute-layer ;
vc:requires ngm:data-storage-layer ;
vc:requires ngm:network-infrastructure ;
vc:slug "application-layer" ;
vc:sourceDomain "spatial-computing" .
ngm:application-ontology a skos:Concept ;
rdfs:label "Application Ontology"@en .
ngm:application-programming-interface a owl:Class ;
rdfs:comment "An application programming interface (API) is a formally specified contract that defines how software components request services and exchange data with one another. It abstracts an implementation behind a stable set of operations, data types, and protocols, decoupling callers from internal details. APIs span in-process library interfaces, inter-process and network endpoints, and platform service boundaries."@en ;
rdfs:label "Application Programming Interface"@en ;
rdfs:subClassOf ngm:interface ;
rdfs:subClassOf _:r1760 ;
vc:contrastsWith ngm:graphics-pipeline ;
vc:dependsOn ngm:http ;
vc:dependsOn ngm:network-protocol ;
vc:enables ngm:microservices ;
vc:enables ngm:rest-api ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:rest-api ;
vc:implements ngm:interface ;
vc:isPartOf ngm:software-architecture ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:scalability ;
vc:relatedTo ngm:software-architecture ;
vc:slug "application-programming-interface" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:edge-computing ;
vc:uses ngm:software-engineering .
ngm:application-software a skos:Concept ;
rdfs:label "Application Software"@en .
ngm:application-specific-blockchain a owl:Class ;
rdfs:comment "An application-specific blockchain is a sovereign blockchain purpose-built to run a single application or tightly scoped set of applications, rather than serving as a general-purpose smart-contract platform. By controlling the full stack — consensus, execution, and governance — it can optimise throughput, fee economics, and customisation for its target use case. This architecture, popularised by the Cosmos ecosystem and rollup frameworks, trades shared security for sovereignty and performance."@en ;
rdfs:label "Application-Specific Blockchain"@en ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf ngm:blockchain-network ;
skos:broader ngm:blockchain ;
vc:bridgesTo ngm:ibc ;
vc:contrastsWith ngm:layer-1 ;
vc:dependsOn ngm:consensus ;
vc:enables ngm:scalability ;
vc:enables ngm:throughput ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:cosmos-sdk ;
vc:implements ngm:tendermint ;
vc:isPartOf ngm:cosmos ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:ibc ;
vc:relatedTo ngm:layer-3 ;
vc:relatedTo ngm:polkadot ;
vc:relatedTo ngm:rollup ;
vc:slug "application-specific-blockchain" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:blockchain-application ;
vc:supports ngm:de-fi ;
vc:uses ngm:consensus ;
vc:uses ngm:validator-set .
ngm:application-specific-integrated-circuit a owl:Class ;
rdfs:comment "An application-specific integrated circuit (ASIC) is a chip designed and fabricated to perform a single, fixed function with maximum efficiency rather than to run general-purpose programs. In blockchain, ASICs are built to compute a particular proof-of-work hash function at far higher speed and energy efficiency than general processors, making them dominant in mining for hashes such as SHA-256. Because the silicon is customised for one task, ASICs offer superior performance per watt but cannot be repurposed for other workloads."@en ;
rdfs:label "Application Specific Integrated Circuit"@en ;
rdfs:subClassOf ngm:mining-hardware ;
rdfs:subClassOf _:r1761 ;
vc:contrastsWith ngm:field-programmable-gate-array ;
vc:contrastsWith ngm:fpga ;
vc:contrastsWith ngm:gpu ;
vc:enables ngm:hardware-acceleration ;
vc:enables ngm:mining ;
vc:enables ngm:proof-of-work ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:hardware-acceleration ;
vc:implements ngm:sha-256 ;
vc:isPartOf ngm:mining ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:gpu ;
vc:relatedTo ngm:mining-hardware ;
vc:requires ngm:energy-consumption ;
vc:slug "application-specific-integrated-circuit" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:bitcoin ;
vc:supports ngm:block-reward ;
vc:supports ngm:consensus-mechanism ;
vc:uses ngm:cryptographic-hash-function ;
vc:uses ngm:sha-256 .
ngm:application-window-capture a owl:Class ;
rdfs:comment "Application Window Capture is a screen-capture technique that grabs the pixels of a single specified application window rather than the entire display or a region. It lets users share or record one program while keeping other windows, notifications, and private content off-screen. Operating systems expose it through window-enumeration and per-window framebuffer APIs used by recording and conferencing software."@en ;
rdfs:label "Application Window Capture"@en ;
rdfs:subClassOf ngm:dc-workspace-tools ;
skos:broader ngm:dc-workspace-tools ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:screen-recording ;
vc:relatedTo ngm:screen-sharing ;
vc:slug "application-window-capture" ;
vc:sourceDomain "metaverse" .
ngm:applied-ai-research-portfolio a owl:Class ;
rdfs:comment "Recent Projects is a curated portfolio page cataloguing active and completed applied research and commercial engagements spanning conversational AI, autonomous marine vision systems, human-attention analytics, large-scale exhibition AI, GenAI film pre-visualisation, interactive image/video generation, text-to-3D modelling, Bitcoin-native digital assets, AI education products, and Logseq-based training materials. It serves as an index of practical deployments demonstrating cross-domain expertise in AI, robotics, spatial computing, and blockchain."@en ;
rdfs:label "Applied AI Research Portfolio"@en ;
rdfs:subClassOf ngm:software-engineering ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:blockchain ;
vc:relatedTo ngm:edge-computing ;
vc:relatedTo ngm:generative-content ;
vc:relatedTo ngm:immersive-entertainment ;
vc:relatedTo ngm:metaverse-application ;
vc:slug "applied-ai-research-portfolio" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:artificial-intelligence ;
vc:uses ngm:computer-vision ;
vc:uses ngm:hardware-and-edge .
ngm:applied-machine-learning a owl:Class ;
rdfs:comment "Applied Machine Learning is the deployment-focused discipline of adapting and operationalising machine-learning methods to solve concrete real-world problems under domain constraints of latency, cost, reliability, and compliance. It spans the full lifecycle from problem framing and data acquisition through feature engineering, model selection, rigorous evaluation using cross-validation and holdout sets, and sustained production monitoring via MLOps practices. Unlike theoretical ML research, which focuses on novel algorithmic contributions, Applied ML prioritises practical impact: models must generalise reliably to unseen data, behave predictably under distribution shift, and be maintainable by engineering teams across months or years of operation."@en ;
rdfs:label "Applied Machine Learning"@en ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf _:r1762 ;
rdfs:subClassOf _:r1763 ;
rdfs:subClassOf _:r1764 ;
rdfs:subClassOf _:r1765 ;
rdfs:subClassOf _:r1766 ;
rdfs:subClassOf _:r1767 ;
rdfs:subClassOf _:r1768 ;
rdfs:subClassOf _:r1769 ;
rdfs:subClassOf _:r1770 ;
rdfs:subClassOf _:r1771 ;
rdfs:subClassOf _:r1772 ;
rdfs:subClassOf _:r1773 ;
rdfs:subClassOf _:r1774 ;
rdfs:subClassOf _:r1775 ;
rdfs:subClassOf _:r1776 ;
rdfs:subClassOf _:r1777 ;
skos:broader ngm:ai-research-area ;
vc:contrastsWith ngm:adversarial-machine-learning ;
vc:contrastsWith ngm:imbalanced-learning ;
vc:dependsOn ngm:applied-mathematics ;
vc:dependsOn ngm:bias-variance-tradeoff ;
vc:dependsOn ngm:ensemble-methods ;
vc:dependsOn ngm:gradient-descent ;
vc:dependsOn ngm:neural-network ;
vc:dependsOn ngm:regularisation ;
vc:enables ngm:anomaly-detection ;
vc:enables ngm:computer-vision-domain ;
vc:enables ngm:demand-forecasting ;
vc:enables ngm:logistics-optimisation ;
vc:enables ngm:natural-language-processing ;
vc:enables ngm:recommendation-system ;
vc:enables ngm:time-series-analysis ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:cross-validation ;
vc:hasPart ngm:data-augmentation ;
vc:hasPart ngm:data-preprocessing ;
vc:hasPart ngm:feature-engineering ;
vc:hasPart ngm:feature-selection ;
vc:hasPart ngm:feature-store ;
vc:hasPart ngm:hyperparameter-optimisation ;
vc:hasPart ngm:mlops ;
vc:hasPart ngm:model-evaluation ;
vc:hasPart ngm:model-selection ;
vc:implements ngm:active-learning ;
vc:implements ngm:reinforcement-learning ;
vc:implements ngm:supervised-learning ;
vc:implements ngm:transfer-learning ;
vc:implements ngm:unsupervised-learning ;
vc:qualityScore "0.92"^^xsd:float ;
vc:relatedTo ngm:applied-mathematics ;
vc:relatedTo ngm:auto-ml ;
vc:relatedTo ngm:deep-learning ;
vc:relatedTo ngm:explainable-ai ;
vc:relatedTo ngm:fairness-in-machine-learning ;
vc:relatedTo ngm:federated-learning ;
vc:relatedTo ngm:mathematical-foundations ;
vc:requires ngm:applied-mathematics ;
vc:requires ngm:bias-variance-tradeoff ;
vc:requires ngm:data-pipeline ;
vc:requires ngm:loss-function ;
vc:requires ngm:mathematical-foundations ;
vc:requires ngm:performance-metrics ;
vc:slug "applied-machine-learning" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:iso-iec-22989-2022 ;
vc:standardizedBy ngm:nist-ai-standards ;
vc:supports ngm:explainable-ai ;
vc:supports ngm:fairness-in-machine-learning ;
vc:supports ngm:federated-learning ;
vc:supports ngm:model-compression ;
vc:uses ngm:auto-ml ;
vc:uses ngm:bayesian-optimisation ;
vc:uses ngm:boosting ;
vc:uses ngm:convolutional-neural-network ;
vc:uses ngm:random-forest .
ngm:applied-mathematics a owl:Class ;
rdfs:comment "Applied Mathematics is the systematic use of mathematical structures, methods, and reasoning to model, analyse, and solve problems arising in science, engineering, economics, computing, and industry. Distinct from pure mathematics by its orientation toward practical effectiveness, Applied Mathematics encompasses numerical analysis, mathematical modelling, optimisation, probability and statistics, differential equations, control theory, fluid dynamics, information theory, and scientific computing. It provides the formal substrate on which machine learning training dynamics, signal processing algorithms, control systems, financial derivatives pricing, and physical simulation all rest. The discipline demands both rigorous theoretical grounding — convergence proofs, stability analysis, error bounds — and pragmatic accommodation of real constraints such as floating-point arithmetic, computational cost, and measurement noise."@en ;
rdfs:label "Applied Mathematics"@en ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf ngm:mathematical-science ;
rdfs:subClassOf ngm:owl-thing ;
rdfs:subClassOf _:r1778 ;
rdfs:subClassOf _:r1779 ;
rdfs:subClassOf _:r1780 ;
rdfs:subClassOf _:r1781 ;
rdfs:subClassOf _:r1782 ;
rdfs:subClassOf _:r1783 ;
rdfs:subClassOf _:r1784 ;
rdfs:subClassOf _:r1785 ;
rdfs:subClassOf _:r1786 ;
rdfs:subClassOf _:r1787 ;
rdfs:subClassOf _:r1788 ;
rdfs:subClassOf _:r1789 ;
rdfs:subClassOf _:r1790 ;
rdfs:subClassOf _:r1791 ;
rdfs:subClassOf _:r1792 ;
rdfs:subClassOf _:r1793 ;
skos:broader ngm:ai-research-area ;
vc:bridgesTo ngm:functional-analysis ;
vc:contrastsWith ngm:mathematical-hard-problems ;
vc:contrastsWith ngm:mathematical-logic ;
vc:dependsOn ngm:mathematical-hard-problems ;
vc:dependsOn ngm:mathematical-science ;
vc:enables ngm:combinatorial-optimisation ;
vc:enables ngm:convex-optimisation ;
vc:enables ngm:cryptography ;
vc:enables ngm:deep-learning ;
vc:enables ngm:machine-learning-discipline ;
vc:enables ngm:numerical-methods ;
vc:enables ngm:operations-research ;
vc:enables ngm:scientific-computing ;
vc:enables ngm:signal-processing ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:calculus ;
vc:hasPart ngm:control-theory ;
vc:hasPart ngm:differential-equations ;
vc:hasPart ngm:fourier-analysis ;
vc:hasPart ngm:functional-analysis ;
vc:hasPart ngm:graph-theory ;
vc:hasPart ngm:information-theory ;
vc:hasPart ngm:linear-algebra ;
vc:hasPart ngm:mathematical-optimisation ;
vc:hasPart ngm:numerical-integration ;
vc:hasPart ngm:numerical-methods ;
vc:hasPart ngm:probability-theory ;
vc:hasPart ngm:stochastic-processes ;
vc:implements ngm:monte-carlo-methods ;
vc:implements ngm:optimisation-algorithm ;
vc:implements ngm:principal-component-analysis ;
vc:implements ngm:simulation ;
vc:qualityScore "0.92"^^xsd:float ;
vc:relatedTo ngm:loss-function ;
vc:relatedTo ngm:mathematical-foundations ;
vc:relatedTo ngm:mathematical-hard-problems ;
vc:relatedTo ngm:mathematical-reasoning ;
vc:relatedTo ngm:neural-network ;
vc:relatedTo ngm:quantum-computation-paradigm ;
vc:relatedTo ngm:regularisation ;
vc:relatedTo ngm:simulation ;
vc:requires ngm:mathematical-foundations ;
vc:requires ngm:mathematical-logic ;
vc:requires ngm:mathematical-reasoning ;
vc:slug "applied-mathematics" ;
vc:sourceDomain "machine-learning" ;
vc:supports ngm:applied-machine-learning ;
vc:supports ngm:backpropagation ;
vc:supports ngm:bayesian-deep-learning ;
vc:supports ngm:bayesian-optimisation ;
vc:supports ngm:diffusion-models ;
vc:supports ngm:gradient-descent ;
vc:supports ngm:reinforcement-learning ;
vc:supports ngm:tensor-decomposition ;
vc:uses ngm:fourier-analysis ;
vc:uses ngm:game-theory ;
vc:uses ngm:graph-theory ;
vc:uses ngm:information-theory .
ngm:appraisal-theory a skos:Concept ;
rdfs:label "Appraisal Theory"@en .
ngm:apprenticeship a skos:Concept ;
rdfs:label "Apprenticeship"@en .
ngm:apprenticeship-learning a owl:Class ;
rdfs:comment "Apprenticeship learning is the problem of learning to perform a task at expert level from demonstrations, without an explicitly specified reward function. Introduced by Abbeel and Ng (2004), it proceeds via inverse reinforcement learning: the learner infers a reward function under which the expert's behaviour is near-optimal — typically as a linear combination of state features whose expected values it seeks to match — and then optimises a policy against that inferred reward, yielding performance guarantees relative to the expert and better generalisation than directly mimicking actions."@en ;
rdfs:label "Apprenticeship Learning"@en ;
rdfs:subClassOf ngm:imitation-learning ;
vc:dependsOn ngm:reward-function ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:reinforcement-learning ;
vc:slug "apprenticeship-learning" ;
vc:sourceDomain "machine-learning" ;
vc:uses ngm:inverse-reinforcement-learning ;
vc:uses ngm:reinforcement-learning .
ngm:approval-gate a skos:Concept ;
rdfs:label "Approval Gate"@en .
ngm:approval-workflow a skos:Concept ;
rdfs:label "Approval Workflow"@en .
ngm:approved-persons-regime a skos:Concept ;
rdfs:label "Approved Persons Regime"@en .
ngm:approximate-bayesian-computation a skos:Concept ;
rdfs:label "Approximate Bayesian Computation"@en .
ngm:approximate-bayesian-inference a skos:Concept ;
rdfs:label "Approximate Bayesian Inference"@en .
ngm:approximate-dynamic-programming a skos:Concept ;
rdfs:label "Approximate Dynamic Programming"@en .
ngm:approximate-inference a skos:Concept ;
rdfs:label "Approximate Inference"@en .
ngm:approximate-nearest-neighbor a skos:Concept ;
rdfs:label "Approximate Nearest Neighbor"@en .
ngm:approximate-nearest-neighbour-search a skos:Concept ;
rdfs:label "Approximate Nearest Neighbour Search"@en .
ngm:approximate-posterior a skos:Concept ;
rdfs:label "Approximate Posterior"@en .
ngm:approximation a skos:Concept ;
rdfs:label "Approximation"@en .
ngm:approximation-algorithm a skos:Concept ;
rdfs:label "Approximation Algorithm"@en .
ngm:approximation-algorithms a skos:Concept ;
rdfs:label "Approximation Algorithms"@en .
ngm:april-tag a owl:Class ;
rdfs:comment "An AprilTag is a square fiducial marker, resembling a simplified QR code, designed for robust detection and accurate 6-DoF pose estimation by computer-vision systems. Each tag encodes a unique ID with strong error correction, enabling reliable recognition under poor lighting, partial occlusion, and oblique viewing angles. AprilTags are widely used as visual landmarks for camera calibration, robot localization, and augmented-reality registration."@en ;
rdfs:label "April Tag"@en ;
rdfs:subClassOf ngm:robo-perception ;
skos:broader ngm:robo-perception ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:lens-and-camera-calibration ;
vc:slug "april-tag" ;
vc:sourceDomain "robotics" .
ngm:apriltag a skos:Concept ;
rdfs:label "Apriltag"@en .
ngm:aptos a owl:Class ;
rdfs:comment "Aptos is a Layer 1 proof-of-stake blockchain platform founded in 2022 by former Diem (Meta) engineers, designed for safety, scalability, and high throughput. It employs the Move programming language — a resource-oriented, formally verifiable language originally created for the Diem project — to express accounts, digital assets, and smart contracts. Its primary performance innovation is Block-STM (Software Transactional Memory), a parallel transaction execution engine that speculatively executes transactions and resolves conflicts at runtime, enabling high concurrent throughput without requiring developers to pre-declare access sets. The network uses a Byzantine Fault Tolerant consensus mechanism (AptosBFT, derived from HotStuff) to reach finality with low latency."@en ;
rdfs:label "Aptos"@en ;
rdfs:subClassOf ngm:blockchain-network ;
rdfs:subClassOf _:r1794 ;
rdfs:subClassOf _:r1795 ;
rdfs:subClassOf _:r1796 ;
vc:bridgesTo ngm:formal-verification ;
vc:bridgesTo ngm:software-transactional-memory ;
vc:contrastsWith ngm:ethereum ;
vc:contrastsWith ngm:solana ;
vc:contrastsWith ngm:sui ;
vc:enables ngm:de-fi ;
vc:enables ngm:digital-asset ;
vc:enables ngm:non-fungible-token ;
vc:enables ngm:smart-contract ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:layer-1 ;
vc:implements ngm:parallel-execution ;
vc:implements ngm:resource-oriented-programming ;
vc:isPartOf ngm:blockchain-network ;
vc:isPartOf ngm:layer-1 ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:consensus-mechanism ;
vc:relatedTo ngm:cryptographic-proof ;
vc:relatedTo ngm:diem ;
vc:relatedTo ngm:tokenomics ;
vc:requires ngm:byzantine-fault-tolerance ;
vc:requires ngm:proof-of-stake ;
vc:requires ngm:validator-node ;
vc:slug "aptos" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:aptosbft ;
vc:uses ngm:block-stm ;
vc:uses ngm:merkle-tree ;
vc:uses ngm:move-programming-language .
ngm:aptosbft a skos:Concept ;
rdfs:label "Aptosbft"@en .
ngm:aquiclude a owl:Class ;
rdfs:label "Aquiclude"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-system-phenomena ;
vc:slug "aquiclude" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:aquifer a owl:Class ;
rdfs:label "Aquifer"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-system-phenomena ;
vc:slug "aquifer" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:aquifuge a owl:Class ;
rdfs:label "Aquifuge"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-system-phenomena ;
vc:slug "aquifuge" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:aquitard a owl:Class ;
rdfs:label "Aquitard"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-system-phenomena ;
vc:slug "aquitard" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:ar-content-creation a skos:Concept ;
rdfs:label "AR Content Creation"@en .
ngm:ar-content-positioning a skos:Concept ;
rdfs:label "AR Content Positioning"@en .
ngm:ar-content-removal a skos:Concept ;
rdfs:label "AR Content Removal"@en .
ngm:ar-display-device a owl:Class ;
rdfs:comment "AR Display Device encompasses hardware systems including smart glasses, headsets, and head-mounted displays that superimpose computer-generated imagery onto the user's view of the real world through optical technologies such as waveguides, birdbath optics, holographic displays, and metasurfaces."@en ;
rdfs:label "Ar Display Device"@en ;
rdfs:subClassOf ngm:display-hardware ;
rdfs:subClassOf ngm:sc-display-and-rendering ;
rdfs:subClassOf _:r1797 ;
rdfs:subClassOf _:r1798 ;
rdfs:subClassOf _:r1799 ;
skos:broader ngm:sc-display-and-rendering ;
vc:bridgesTo ngm:sensor-input ;
vc:enables ngm:augmented-reality ;
vc:enables ngm:mixed-reality ;
vc:enables ngm:spatial-computing ;
vc:enables ngm:spatial-computing-paradigm ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:display-technology ;
vc:requires ngm:optical-systems ;
vc:requires ngm:pose-tracking ;
vc:slug "ar-display-device" ;
vc:sourceDomain "spatial-computing" .
ngm:ar-display-devices a skos:Concept ;
rdfs:label "AR Display Devices"@en .
ngm:ar-experiences a owl:Class ;
rdfs:comment "AR Experiences are interactive augmented reality applications that overlay digital content onto the physical world in real-time through smartphones, tablets, or AR headsets, enabling enhanced visualization, contextual information display, and immersive interaction with virtual objects anchored in..."@en ;
rdfs:label "Ar Experiences"@en ;
rdfs:subClassOf ngm:immersive-technology-applications ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf _:r1800 ;
rdfs:subClassOf _:r1801 ;
rdfs:subClassOf _:r1802 ;
skos:broader ngm:sc-platform-and-environment ;
vc:bridgesTo ngm:sensor-input ;
vc:enables ngm:contextual-information ;
vc:enables ngm:enhanced-visualization ;
vc:enables ngm:interactive-learning ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:ar-display-device ;
vc:requires ngm:ar-display-devices ;
vc:requires ngm:computer-vision ;
vc:requires ngm:spatial-mapping ;
vc:slug "ar-experiences" ;
vc:sourceDomain "spatial-computing" .
ngm:ar-frame a owl:Class ;
rdfs:comment "An AR Frame is a head-worn optical see-through augmented reality platform integrating a transparent or semi-transparent microdisplay (typically a microOLED, LCoS, or holographic waveguide projecting 480p-1080p imagery onto a combiner lens of 20°-50° diagonal field-of-view), onboard processing (AR..."@en ;
rdfs:label "AR Frame"@en ;
rdfs:subClassOf ngm:ar-hardware ;
rdfs:subClassOf ngm:head-mounted-display ;
rdfs:subClassOf ngm:optical-see-through-hmd ;
rdfs:subClassOf ngm:sc-display-and-rendering ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf ngm:spatial-computing ;
rdfs:subClassOf ngm:wearable-device-integration ;
rdfs:subClassOf _:r869 ;
rdfs:subClassOf _:r870 ;
rdfs:subClassOf _:r871 ;
rdfs:subClassOf _:r872 ;
rdfs:subClassOf _:r873 ;
rdfs:subClassOf _:r874 ;
rdfs:subClassOf _:r875 ;
rdfs:subClassOf _:r876 ;
rdfs:subClassOf _:r877 ;
rdfs:subClassOf _:r878 ;
rdfs:subClassOf _:r879 ;
rdfs:subClassOf _:r880 ;
rdfs:subClassOf _:r881 ;
skos:broader ngm:sc-display-and-rendering ;
skos:broader ngm:sc-platform-and-environment ;
skos:broader ngm:spatial-computing ;
vc:contrastsWith ngm:holographic-display ;
vc:contrastsWith ngm:projection-mapping-system ;
vc:contrastsWith ngm:smartphone-ar ;
vc:contrastsWith ngm:video-passthrough-hmd ;
vc:contrastsWith ngm:virtual-reality-headset ;
vc:dependsOn ngm:computer-vision ;
vc:dependsOn ngm:edge-ai ;
vc:dependsOn ngm:inertial-navigation ;
vc:dependsOn ngm:microelectromechanical-systems ;
vc:dependsOn ngm:wireless-networking ;
vc:enables ngm:environmental-awareness ;
vc:enables ngm:hands-free-interaction ;
vc:enables ngm:heads-up-display ;
vc:enables ngm:persistent-content-anchoring ;
vc:enables ngm:real-time-translation ;
vc:enables ngm:remote-assistance ;
vc:enables ngm:visual-question-answering ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:battery ;
vc:hasPart ngm:eye-tracking ;
vc:hasPart ngm:inertial-measurement-unit ;
vc:hasPart ngm:microdisplay ;
vc:hasPart ngm:microphone-array ;
vc:hasPart ngm:onboard-soc ;
vc:hasPart ngm:optical-combiner ;
vc:hasPart ngm:wireless-radio ;
vc:hasPart ngm:world-facing-camera ;
vc:implements ngm:foveated-rendering ;
vc:implements ngm:late-stage-reprojection ;
vc:implements ngm:sensor-fusion ;
vc:implements ngm:slam ;
vc:implements ngm:xr-runtime-environment ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:ambient-computing ;
vc:relatedTo ngm:digital-twin ;
vc:relatedTo ngm:metaverse ;
vc:relatedTo ngm:mixed-reality ;
vc:relatedTo ngm:spatial-computing ;
vc:relatedTo ngm:spatial-computing-paradigm ;
vc:relatedTo ngm:wearable-ai ;
vc:requires ngm:edge-computing ;
vc:requires ngm:imu-sensors ;
vc:requires ngm:optical-display ;
vc:requires ngm:power-management ;
vc:requires ngm:slam ;
vc:requires ngm:wireless-connectivity ;
vc:slug "ar-frame" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:bluetooth-sig ;
vc:standardizedBy ngm:ieee-802-11 ;
vc:standardizedBy ngm:khronos-gl-tf ;
vc:standardizedBy ngm:khronos-open-xr ;
vc:standardizedBy ngm:mpeg-i ;
vc:standardizedBy ngm:usb-if ;
vc:standardizedBy ngm:w-3-c-web-xr ;
vc:supports ngm:accessibility-captioning ;
vc:supports ngm:ai-assistant ;
vc:supports ngm:field-service ;
vc:supports ngm:industrial-inspection ;
vc:supports ngm:retail-assistance ;
vc:supports ngm:surgical-navigation ;
vc:supports ngm:tourism-guidance ;
vc:uses ngm:birdbath-optics ;
vc:uses ngm:bluetooth-low-energy ;
vc:uses ngm:micro-oled-display ;
vc:uses ngm:microled-display ;
vc:uses ngm:microoled-display ;
vc:uses ngm:snapdragon-ar-soc ;
vc:uses ngm:waveguide-optics ;
vc:uses ngm:wi-fi-6 .
ngm:ar-interoperability a owl:Class ;
rdfs:comment "AR interoperability is the capacity for augmented reality content, spatial anchors, and experiences to function consistently across different hardware devices, operating systems, and rendering engines. It depends on shared data formats for spatial maps and anchors, common coordinate reference conventions, and standardised APIs for camera, tracking, and rendering access, as pursued by efforts such as the ETSI Augmented Reality Framework. Without it, AR content authored for one platform typically requires substantial rework to run on another, fragmenting the content ecosystem and raising development cost. It is a prerequisite for shared, persistent AR experiences that multiple users on different devices can view and manipulate together."@en ;
rdfs:label "AR Interoperability"@en ;
rdfs:subClassOf ngm:cross-platform-interoperability ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.0"^^xsd:float ;
vc:slug "ar-interoperability" ;
vc:sourceDomain "spatial-computing" .
ngm:ar-occlusion a owl:Class ;
rdfs:comment "AR occlusion is the computational technique by which virtual objects rendered in an augmented reality scene are correctly hidden or partially hidden by real-world geometry that physically lies in front of them from the viewer's perspective. Achieving occlusion requires real-time estimation of the depth structure of the physical scene, typically via depth sensors or monocular depth estimation neural networks, so that the rendering pipeline can apply correct depth ordering between real and virtual content. Without occlusion, virtual objects appear to float unconvincingly in front of all physical surfaces regardless of their spatial relationship."@en ;
rdfs:label "AR Occlusion"@en ;
rdfs:subClassOf ngm:augmented-reality ;
rdfs:subClassOf ngm:sc-display-and-rendering ;
skos:broader ngm:sc-display-and-rendering ;
vc:enables ngm:real-time-rendering ;
vc:enables ngm:spatial-mapping ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:mixed-reality ;
vc:relatedTo ngm:occlusion-rendering ;
vc:slug "ar-occlusion" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:computer-vision ;
vc:uses ngm:depth-estimation ;
vc:uses ngm:scene-understanding .
ngm:ar-overlay a owl:Class ;
rdfs:comment "AR Overlay refers to the digital layer of virtual elements including holograms, data visualizations, animations, and 3D objects that are spatially anchored and rendered over the user's view of the physical world in augmented reality systems, creating a seamless blend of virtual and real content."@en ;
rdfs:label "Ar Overlay"@en ;
rdfs:subClassOf ngm:digital-display-layer ;
rdfs:subClassOf ngm:sc-display-and-rendering ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf _:r1803 ;
rdfs:subClassOf _:r1804 ;
rdfs:subClassOf _:r1805 ;
skos:broader ngm:sc-display-and-rendering ;
skos:broader ngm:sc-platform-and-environment ;
vc:bridgesTo ngm:computer-vision ;
vc:enables ngm:information-augmentation ;
vc:enables ngm:spatial-annotation ;
vc:enables ngm:virtual-object-placement ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:environmental-understanding ;
vc:requires ngm:real-time-rendering ;
vc:requires ngm:spatial-anchoring ;
vc:slug "ar-overlay" ;
vc:sourceDomain "spatial-computing" .
ngm:ar-quick-look a skos:Concept ;
rdfs:label "AR Quick Look"@en .
ngm:ar-registration a owl:Class ;
rdfs:comment "AR Registration is the spatial alignment process that anchors virtual content to real-world coordinates through Computer Vision, Sensor Input, and tracking algorithms."@en ;
rdfs:label "AR Registration"@en ;
rdfs:subClassOf ngm:computer-vision ;
rdfs:subClassOf ngm:sc-interaction ;
rdfs:subClassOf ngm:spatial-tracking ;
rdfs:subClassOf _:r882 ;
rdfs:subClassOf _:r883 ;
rdfs:subClassOf _:r884 ;
rdfs:subClassOf _:r885 ;
skos:broader ngm:sc-interaction ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:sensor-input ;
vc:bridgesTo ngm:spatial-anchoring ;
vc:enables ngm:geometric-accuracy ;
vc:enables ngm:interaction-with-physical-objects ;
vc:enables ngm:persistent-content-anchoring ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:camera-calibration ;
vc:requires ngm:feature-matching ;
vc:requires ngm:imu ;
vc:requires ngm:pose-estimation ;
vc:slug "ar-registration" ;
vc:sourceDomain "spatial-computing" .
ngm:ar-scene-graph a owl:Class ;
rdfs:comment "AR Scene Graph is a hierarchical data structure used in augmented reality to represent and organize spatial relationships between virtual objects, real-world elements, and their transformations, enabling context-aware placement, semantic understanding, and natural interaction between digital cont..."@en ;
rdfs:label "Ar Scene Graph"@en ;
rdfs:subClassOf ngm:sc-content-and-assets ;
rdfs:subClassOf ngm:spatial-data-structure ;
rdfs:subClassOf _:r1806 ;
rdfs:subClassOf _:r1807 ;
skos:broader ngm:sc-content-and-assets ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:spatial-data-structure ;
vc:enables ngm:ar-experiences ;
vc:enables ngm:context-aware-ar ;
vc:enables ngm:semantic-scene-understanding ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:3-d-scene-reconstruction ;
vc:requires ngm:object-detection ;
vc:requires ngm:spatial-relationships ;
vc:slug "ar-scene-graph" ;
vc:sourceDomain "spatial-computing" .
ngm:ar-screen-projection a skos:Concept ;
rdfs:label "AR Screen Projection"@en .
ngm:ar-technology a owl:Class ;
rdfs:comment "AR Technology encompasses the hardware, software, and algorithmic systems enabling real-time digital content overlay on physical environments, including spatial tracking, environmental understanding, rendering pipelines, and interaction modalities across mobile, wearable, and projection-based form factors."@en ;
rdfs:label "AR Technology"@en ;
rdfs:subClassOf ngm:augmented-reality-ar ;
rdfs:subClassOf ngm:extended-reality ;
rdfs:subClassOf _:r886 ;
rdfs:subClassOf _:r887 ;
rdfs:subClassOf _:r888 ;
rdfs:subClassOf _:r889 ;
rdfs:subClassOf _:r890 ;
rdfs:subClassOf _:r891 ;
rdfs:subClassOf _:r892 ;
rdfs:subClassOf _:r893 ;
rdfs:subClassOf _:r894 ;
vc:bridgesTo ngm:3-d-rendering-engine ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:internet-of-things ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:bridgesTo ngm:sensor-input ;
vc:contrastsWith ngm:virtual-reality ;
vc:enables ngm:industrial-guidance ;
vc:enables ngm:mixed-reality ;
vc:enables ngm:remote-assistance ;
vc:enables ngm:spatial-computing ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:3-d-rendering-engine ;
vc:hasPart ngm:simultaneous-localisation-and-mapping ;
vc:hasPart ngm:spatial-anchor ;
vc:qualityScore "0.65"^^xsd:float ;
vc:relatedTo ngm:spatial-computing ;
vc:relatedTo ngm:web-xr ;
vc:requires ngm:ar-frame ;
vc:requires ngm:ar-registration ;
vc:requires ngm:computer-vision ;
vc:requires ngm:display-technology ;
vc:requires ngm:edge-computing ;
vc:requires ngm:sensor-input ;
vc:slug "ar-technology" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:gesture-recognition ;
vc:supports ngm:voice-interaction ;
vc:uses ngm:depth-sensing ;
vc:uses ngm:gpu-acceleration ;
vc:uses ngm:inertial-measurement-unit .
ngm:ar-token a skos:Concept ;
rdfs:label "AR Token"@en .
ngm:ar-tracking-subsystem a skos:Concept ;
rdfs:label "AR Tracking Subsystem"@en .
ngm:ar-vr-experiences a skos:Concept ;
rdfs:label "AR VR Experiences"@en .
ngm:ar-vr-streaming a skos:Concept ;
rdfs:label "AR VR Streaming"@en .
ngm:ar-xiv a skos:Concept ;
rdfs:label "AR Xiv"@en .
ngm:aragon a owl:Class ;
rdfs:comment "A framework and set of smart contracts for creating and operating decentralised autonomous organisations on Ethereum, providing modular governance, treasury and permission components."@en ;
rdfs:label "Aragon"@en ;
rdfs:subClassOf ngm:dao-tooling ;
rdfs:subClassOf _:r1808 ;
rdfs:subClassOf _:r1809 ;
rdfs:subClassOf _:r1810 ;
rdfs:subClassOf _:r1811 ;
rdfs:subClassOf _:r1812 ;
vc:bridgesTo ngm:dao ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:bridgesTo ngm:infrastructure ;
vc:contrastsWith ngm:governance ;
vc:contrastsWith ngm:moloch-dao ;
vc:contrastsWith ngm:snapshot ;
vc:enables ngm:decentralised-governance ;
vc:enables ngm:governance ;
vc:enables ngm:on-chain-voting ;
vc:enables ngm:treasury-management ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:dao-governance ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:decentralised-autonomous-organisation ;
vc:relatedTo ngm:ethereum ;
vc:requires ngm:access-control ;
vc:requires ngm:decentralised-autonomous-organisation ;
vc:requires ngm:ethereum-smart-contract-platform ;
vc:requires ngm:smart-contracts ;
vc:requires ngm:token-weighted-voting ;
vc:slug "aragon" ;
vc:sourceDomain "governance" ;
vc:uses ngm:governance-token ;
vc:uses ngm:multisig-wallet ;
vc:uses ngm:proxy-pattern .
ngm:aragon-conviction-voting-app-abi a skos:Concept ;
rdfs:label "Aragon Conviction Voting App Abi"@en .
ngm:aragon-governance a skos:Concept ;
rdfs:label "Aragon Governance"@en .
ngm:arbitrage a owl:Class ;
rdfs:comment "Arbitrage is the practice of simultaneously buying and selling an asset across different markets or instruments to profit from a price discrepancy with minimal directional risk. In decentralised finance it is a central economic force that aligns token prices across exchanges and liquidity pools, often executed by automated bots exploiting transient inefficiencies. Arbitrage activity drives price discovery and improves market efficiency, but is closely tied to phenomena such as miner/maximal extractable value and impermanent loss."@en ;
rdfs:label "Arbitrage"@en ;
rdfs:subClassOf ngm:market-efficiency ;
rdfs:subClassOf _:r1813 ;
rdfs:subClassOf _:r1814 ;
vc:dependsOn ngm:price-discovery ;
vc:enables ngm:liquidity ;
vc:enables ngm:market-efficiency ;
vc:enables ngm:price-discovery ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:cryptocurrency ;
vc:relatedTo ngm:impermanent-loss ;
vc:relatedTo ngm:mev ;
vc:relatedTo ngm:risk-management ;
vc:relatedTo ngm:yield-farming ;
vc:requires ngm:liquidity ;
vc:requires ngm:order-book ;
vc:slug "arbitrage" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:de-fi ;
vc:supports ngm:digital-asset-trading ;
vc:uses ngm:decentralized-exchange ;
vc:uses ngm:dex ;
vc:uses ngm:flash-loan .
ngm:arbitration-clauses a skos:Concept ;
rdfs:label "Arbitration Clauses"@en .
ngm:arbitration-decision-engine a owl:Class ;
rdfs:comment "Arbitration Decision Engine is an AI-powered or smart contract-based automated system that evaluates evidence, applies predetermined rules, and renders decisions in dispute resolution processes, functioning as an oracle that can trigger smart contract modifications and enable self-enforcing arbit..."@en ;
rdfs:label "Arbitration Decision Engine"@en ;
rdfs:subClassOf ngm:automated-dispute-resolution ;
rdfs:subClassOf ngm:sc-governance-and-safety ;
rdfs:subClassOf _:r1815 ;
rdfs:subClassOf _:r1816 ;
rdfs:subClassOf _:r1817 ;
rdfs:subClassOf _:r1818 ;
skos:broader ngm:sc-governance-and-safety ;
vc:bridgesTo ngm:automated-dispute-resolution ;
vc:bridgesTo ngm:blockchain ;
vc:enables ngm:decentralized-arbitration ;
vc:enables ngm:self-enforcing-awards ;
vc:enables ngm:smart-contract-resolution ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:authentication ;
vc:requires ngm:blockchain ;
vc:requires ngm:rule-encoding ;
vc:slug "arbitration-decision-engine" ;
vc:sourceDomain "spatial-computing" .
ngm:arbitration-process a owl:Class ;
rdfs:comment "Arbitration Process in the blockchain and metaverse context refers to structured dispute resolution procedures using smart contracts and decentralized technologies, encompassing both on-chain mechanisms with automatic award enforcement and off-chain proceedings with traditional arbitral framework..."@en ;
rdfs:label "Arbitration Process"@en ;
rdfs:subClassOf ngm:alternative-dispute-resolution ;
rdfs:subClassOf ngm:sc-governance-and-safety ;
skos:broader ngm:sc-governance-and-safety ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:infra-legal-and-regulatory ;
vc:enables ngm:confidential-proceedings ;
vc:enables ngm:dispute-resolution ;
vc:enables ngm:smart-contract-enforcement ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:arbitration-clauses ;
vc:requires ngm:evidence-procedures ;
vc:requires ngm:neutral-selection ;
vc:slug "arbitration-process" ;
vc:sourceDomain "spatial-computing" .
ngm:arbitrator-expertise a owl:Class ;
rdfs:comment "Arbitrator Expertise in blockchain and digital asset contexts refers to the specialized technical knowledge, legal background, and industry experience required by neutral decision-makers to understand distributed ledger technology, smart contracts, tokenomics, and crypto-asset classification for ..."@en ;
rdfs:label "Arbitrator Expertise"@en ;
rdfs:subClassOf ngm:professional-qualification ;
rdfs:subClassOf ngm:sc-governance-and-safety ;
skos:broader ngm:sc-governance-and-safety ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:infra-legal-and-regulatory ;
vc:enables ngm:fair-outcomes ;
vc:enables ngm:informed-decision-making ;
vc:enables ngm:technical-evidence-evaluation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:blockchain-knowledge ;
vc:requires ngm:industry-experience ;
vc:requires ngm:legal-training ;
vc:slug "arbitrator-expertise" ;
vc:sourceDomain "spatial-computing" .
ngm:arbitrum a owl:Class ;
rdfs:comment "Arbitrum is a family of Ethereum layer-2 scaling solutions developed by Offchain Labs that use optimistic rollup technology to increase transaction throughput and reduce fees. Its flagship network, Arbitrum One, launched on mainnet in 2021 and executes transactions in a custom virtual machine while posting transaction data and state commitments to Ethereum. Arbitrum's interactive multi-round fraud-proof protocol distinguishes it from other optimistic rollups by narrowing disputes to a single instruction before on-chain resolution. The ARB token governs the network through the Arbitrum DAO, and Arbitrum Nitro and Orbit extend the technology to custom chains."@en ;
rdfs:label "Arbitrum"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf ngm:blockchain-domain ;
rdfs:subClassOf _:r1819 ;
rdfs:subClassOf _:r1820 ;
rdfs:subClassOf _:r1821 ;
rdfs:subClassOf _:r1822 ;
rdfs:subClassOf _:r1823 ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:bridgesTo ngm:distributed-systems ;
vc:bridgesTo ngm:finance ;
vc:bridgesTo ngm:optimism ;
vc:bridgesTo ngm:polygon ;
vc:bridgesTo ngm:zk-sync ;
vc:contrastsWith ngm:optimism ;
vc:contrastsWith ngm:zero-knowledge-rollup ;
vc:contrastsWith ngm:zk-sync ;
vc:dependsOn ngm:data-availability ;
vc:enables ngm:de-fi ;
vc:enables ngm:decentralised-finance-domain ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:evm-compatibility ;
vc:implements ngm:fraud-proof ;
vc:implements ngm:optimistic-rollup ;
vc:isPartOf ngm:ethereum ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:layer-2-scaling ;
vc:relatedTo ngm:plasma ;
vc:requires ngm:ethereum-smart-contract-platform ;
vc:requires ngm:fraud-proof ;
vc:requires ngm:rollup ;
vc:requires ngm:sequencer ;
vc:requires ngm:validator-node ;
vc:slug "arbitrum" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:cross-chain-bridge ;
vc:supports ngm:smart-contract ;
vc:uses ngm:calldata-compression ;
vc:uses ngm:governance-token ;
vc:uses ngm:web-assembly .
ngm:arbitrum-dao a owl:Class ;
rdfs:comment "Arbitrum DAO is the decentralised autonomous organisation that governs the Arbitrum One and Arbitrum Nova Layer 2 blockchain networks, operating through the ARB governance token launched by Offchain Labs in March 2023. Token holders propose and vote on protocol upgrades, treasury allocations, and parameter changes via on-chain governance contracts, making Arbitrum DAO one of the largest DAOs by treasury value in the Ethereum ecosystem. Governance decisions are executed through a Security Council with emergency intervention powers and a broader Arbitrum Improvement Proposal (AIP) process for standard changes."@en ;
rdfs:label "Arbitrum DAO"@en ;
rdfs:subClassOf ngm:dao ;
vc:enables ngm:dao-governance ;
vc:enables ngm:on-chain-governance ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:ethereum-smart-contract-platform ;
vc:relatedTo ngm:on-chain-voting ;
vc:slug "arbitrum-dao" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:governance-token ;
vc:uses ngm:layer-2-scaling ;
vc:uses ngm:smart-contract .
ngm:arbitrum-sepolia a skos:Concept ;
rdfs:label "Arbitrum Sepolia"@en .
ngm:arc-agi a owl:Class ;
rdfs:comment "ARC-AGI (Abstraction and Reasoning Corpus for Artificial General Intelligence) is a benchmark designed by François Chollet and published in 2019 to measure general fluid intelligence in AI systems through abstract visual pattern completion tasks that require novel rule induction rather than pattern recall from training data. Each task presents a small number of input-output grid transformation examples from which the solver must infer the underlying rule and apply it to a new input, using only core knowledge priors available to young children. The benchmark explicitly resists solution by memorisation, making it a proxy test for human-like generalisation ability."@en ;
rdfs:label "ARC-AGI"@en ;
rdfs:subClassOf ngm:benchmark-evaluation ;
rdfs:subClassOf ngm:benchmark-standard ;
rdfs:subClassOf ngm:benchmarks ;
rdfs:subClassOf _:r895 ;
rdfs:subClassOf _:r896 ;
vc:contrastsWith ngm:deep-learning ;
vc:contrastsWith ngm:large-language-models ;
vc:contrastsWith ngm:transfer-learning ;
vc:dependsOn ngm:cognitive-science ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:programme-synthesis ;
vc:enables ngm:ai-safety-research ;
vc:enables ngm:automated-reasoning ;
vc:enables ngm:benchmark-evaluation ;
vc:enables ngm:generalisation ;
vc:enables ngm:pattern-recognition ;
vc:enables ngm:reasoning ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:arc-agi-2 ;
vc:hasPart ngm:arc-agi-3 ;
vc:hasPart ngm:arc-prize ;
vc:hasPart ngm:core-knowledge-priors ;
vc:hasPart ngm:evaluation-leaderboard ;
vc:hasPart ngm:grid-based-tasks ;
vc:implements ngm:benchmark-dataset ;
vc:implements ngm:benchmark-standard ;
vc:implements ngm:evaluation-metric ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:ai-benchmark-epistemological-critique ;
vc:relatedTo ngm:ai-safety-research ;
vc:relatedTo ngm:artificial-general-intelligence ;
vc:relatedTo ngm:automated-reasoning ;
vc:relatedTo ngm:benchmark-standard ;
vc:relatedTo ngm:few-shot-learning ;
vc:relatedTo ngm:neuro-symbolic-ai ;
vc:relatedTo ngm:reinforcement-learning ;
vc:requires ngm:core-knowledge-priors ;
vc:requires ngm:few-shot-generalisation ;
vc:requires ngm:few-shot-learning ;
vc:requires ngm:reasoning ;
vc:requires ngm:visual-reasoning ;
vc:slug "arc-agi" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:arc-prize ;
vc:supports ngm:ai-benchmark-epistemological-critique ;
vc:supports ngm:artificial-general-intelligence ;
vc:supports ngm:chain-of-thought-reasoning ;
vc:supports ngm:neuro-symbolic-ai ;
vc:uses ngm:benchmark-dataset ;
vc:uses ngm:cognitive-science ;
vc:uses ngm:domain-specific-language ;
vc:uses ngm:evaluation-metric ;
vc:uses ngm:inductive-logic-programming ;
vc:uses ngm:machine-learning-discipline .
ngm:arc-agi-2 a skos:Concept ;
rdfs:label "Arc Agi 2"@en .
ngm:arc-agi-3 a skos:Concept ;
rdfs:label "Arc Agi 3"@en .
ngm:arc-consistency a owl:Class ;
rdfs:comment "A local consistency property of binary constraint networks in which, for every value in one variable's domain, each constraint linking it to another variable admits at least one compatible supporting value in that variable's domain. Enforcing it — classically with the AC-3 algorithm — deletes unsupported values until a fixed point, providing the most widely used level of constraint propagation and the pruning backbone of practical constraint solvers."@en ;
rdfs:label "Arc Consistency"@en ;
rdfs:subClassOf ngm:constraint-propagation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:constraint-satisfaction ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:backtracking-search ;
vc:relatedTo ngm:constraint ;
vc:slug "arc-consistency" ;
vc:sourceDomain "artificial-intelligence" .
ngm:arc-face a owl:Class ;
rdfs:comment "ArcFace is a deep learning loss function and associated training methodology for facial recognition, introduced by Deng et al. at Imperial College London in 2019, that improves discriminative feature learning by adding an additive angular margin penalty to the softmax loss function. By penalising the angle between a sample embedding and its class centre in hyperspherical feature space, ArcFace forces the model to learn more compact intra-class and more separable inter-class feature embeddings than standard softmax or earlier margin-based losses. It has achieved state-of-the-art performance on numerous facial recognition benchmarks and is widely adopted in production identity verification systems."@en ;
rdfs:label "ArcFace"@en ;
rdfs:subClassOf ngm:facial-recognition ;
rdfs:subClassOf ngm:loss-function ;
rdfs:subClassOf ngm:representation-learning ;
rdfs:subClassOf _:r1824 ;
rdfs:subClassOf _:r1825 ;
rdfs:subClassOf _:r1826 ;
rdfs:subClassOf _:r1827 ;
rdfs:subClassOf _:r1828 ;
rdfs:subClassOf _:r1829 ;
rdfs:subClassOf _:r1830 ;
rdfs:subClassOf _:r1831 ;
rdfs:subClassOf _:r1832 ;
vc:contrastsWith ngm:contrastive-learning ;
vc:contrastsWith ngm:self-supervised-learning ;
vc:enables ngm:access-control ;
vc:enables ngm:biometric-authentication ;
vc:enables ngm:biometric-verification ;
vc:enables ngm:digital-identity-verification ;
vc:enables ngm:fraud-detection ;
vc:enables ngm:identity-verification ;
vc:enables ngm:kyc ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:cross-entropy-loss ;
vc:hasPart ngm:embedding ;
vc:qualityScore "0.92"^^xsd:float ;
vc:relatedTo ngm:biometric-data ;
vc:relatedTo ngm:contrastive-learning ;
vc:relatedTo ngm:data-protection ;
vc:relatedTo ngm:eu-ai-act-regulatory-instrument ;
vc:relatedTo ngm:explainable-ai ;
vc:relatedTo ngm:face-swap ;
vc:relatedTo ngm:graph-neural-network ;
vc:relatedTo ngm:liveness-detection ;
vc:relatedTo ngm:neural-network-architecture ;
vc:relatedTo ngm:representation-learning ;
vc:relatedTo ngm:transfer-learning ;
vc:relatedTo ngm:transformer-architecture ;
vc:requires ngm:backpropagation ;
vc:requires ngm:feature-extraction ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:gradient-descent ;
vc:requires ngm:hyperparameter-tuning ;
vc:requires ngm:image-processing ;
vc:requires ngm:model-training ;
vc:slug "arc-face" ;
vc:sourceDomain "ai" ;
vc:supports ngm:anomaly-detection ;
vc:supports ngm:liveness-detection ;
vc:supports ngm:surveillance ;
vc:uses ngm:attention-mechanism ;
vc:uses ngm:backpropagation ;
vc:uses ngm:batch-normalisation ;
vc:uses ngm:convolutional-neural-network ;
vc:uses ngm:cosine-similarity ;
vc:uses ngm:cross-entropy-loss ;
vc:uses ngm:deep-learning ;
vc:uses ngm:dropout ;
vc:uses ngm:embedding ;
vc:uses ngm:gpu-compute ;
vc:uses ngm:gradient-descent ;
vc:uses ngm:loss-function ;
vc:uses ngm:transformer-architecture .
ngm:arc-prize a skos:Concept ;
rdfs:label "Arc Prize"@en .
ngm:archaeological-site-reconstruction a owl:Class ;
rdfs:comment "Archaeological Site Reconstruction refers to the use of 3D modeling, photogrammetry, LiDAR, and virtual reality technologies to create accurate digital representations of ancient sites, enabling study, documentation, preservation, and immersive public access to cultural heritage through realistic..."@en ;
rdfs:label "Archaeological Site Reconstruction"@en ;
rdfs:subClassOf ngm:digital-heritage ;
rdfs:subClassOf ngm:sc-content-and-assets ;
rdfs:subClassOf _:r1833 ;
rdfs:subClassOf _:r1834 ;
rdfs:subClassOf _:r1835 ;
skos:broader ngm:sc-content-and-assets ;
vc:bridgesTo ngm:computer-vision ;
vc:enables ngm:cultural-heritage-preservation ;
vc:enables ngm:educational-experiences ;
vc:enables ngm:virtual-tourism ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:3d-modelling ;
vc:requires ngm:historical-research ;
vc:requires ngm:photogrammetry ;
vc:slug "archaeological-site-reconstruction" ;
vc:sourceDomain "spatial-computing" .
ngm:architectural-decision-records a skos:Concept ;
rdfs:label "Architectural Decision Records"@en .
ngm:architectural-layer a owl:Class ;
rdfs:comment "An architectural layer is a discrete horizontal stratum within a layered software or system architecture, responsible for a cohesive set of concerns and communicating only with adjacent layers through well-defined interfaces. Layered decomposition is a fundamental pattern in software architecture that promotes separation of concerns, replaceability of individual layers, and independent evolution of distinct system capabilities. Classic examples include the OSI network model's seven layers, the three-tier application architecture (presentation, logic, data), and the cloud-native separation of infrastructure, platform, and application layers."@en ;
rdfs:label "Architectural Layer"@en ;
rdfs:subClassOf ngm:software-architecture ;
rdfs:subClassOf _:r1836 ;
rdfs:subClassOf _:r1837 ;
rdfs:subClassOf _:r1838 ;
rdfs:subClassOf _:r1839 ;
vc:enables ngm:hardware-abstraction ;
vc:enables ngm:microservices-architecture ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:application-layer ;
vc:hasPart ngm:network-layer ;
vc:hasPart ngm:service-layer ;
vc:hasPart ngm:technology-infrastructure-domain-layer ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:api-standard ;
vc:relatedTo ngm:system-architecture ;
vc:slug "architectural-layer" ;
vc:sourceDomain "infrastructure" .
ngm:architectural-pattern a skos:Concept ;
rdfs:label "Architectural Pattern"@en .
ngm:architectural-visualisation a owl:Class ;
rdfs:comment "Architectural visualisation is the discipline of producing photorealistic or stylised two- and three-dimensional representations of proposed buildings, interiors, and urban environments to communicate design intent to clients, planners, and the public before construction. It combines techniques from 3D modelling, physically based rendering, and real-time graphics to produce still images, animations, and interactive walkthroughs. Advances in real-time rendering engines and spatial computing have extended the discipline to include immersive virtual reality experiences and augmented reality overlays on physical construction sites."@en ;
rdfs:label "Architectural Visualisation"@en ;
rdfs:subClassOf ngm:sc-content-and-assets ;
skos:broader ngm:sc-content-and-assets ;
vc:enables ngm:digital-twin ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:augmented-reality ;
vc:relatedTo ngm:bim-virtual-model ;
vc:slug "architectural-visualisation" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:3-d-model ;
vc:uses ngm:real-time-rendering .
ngm:architecture a owl:Class ;
rdfs:comment "In the AI domain, Architecture refers to the structural design of an AI model or system, specifying how computational components—such as layers, modules, attention heads, and connections—are organised and interact to process inputs and produce outputs. Architectural choices fundamentally determine a model's capacity, inductive biases, scalability, and suitability for particular tasks."@en ;
rdfs:label "Architecture"@en ;
rdfs:subClassOf ngm:ai-model-architecture ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf ngm:neural-network-architecture ;
rdfs:subClassOf _:r1840 ;
rdfs:subClassOf _:r1841 ;
rdfs:subClassOf _:r1842 ;
rdfs:subClassOf _:r1843 ;
rdfs:subClassOf _:r1844 ;
rdfs:subClassOf _:r1845 ;
rdfs:subClassOf _:r1846 ;
rdfs:subClassOf _:r1847 ;
rdfs:subClassOf _:r1848 ;
rdfs:subClassOf _:r1849 ;
rdfs:subClassOf _:r1850 ;
rdfs:subClassOf _:r1851 ;
rdfs:subClassOf _:r1852 ;
rdfs:subClassOf _:r1853 ;
rdfs:subClassOf _:r1854 ;
rdfs:subClassOf _:r1855 ;
skos:broader ngm:ai-model-architecture ;
skos:broader ngm:artificial-intelligence ;
vc:contrastsWith ngm:knowledge-distillation ;
vc:contrastsWith ngm:neural-architecture-search ;
vc:dependsOn ngm:backpropagation ;
vc:dependsOn ngm:gradient-descent ;
vc:dependsOn ngm:loss-function ;
vc:enables ngm:computer-vision ;
vc:enables ngm:deep-learning ;
vc:enables ngm:generative-ai ;
vc:enables ngm:model-training ;
vc:enables ngm:natural-language-processing ;
vc:enables ngm:reinforcement-learning ;
vc:enables ngm:transfer-learning ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:activation-function ;
vc:hasPart ngm:attention-mechanism ;
vc:hasPart ngm:batch-normalisation ;
vc:hasPart ngm:decoder ;
vc:hasPart ngm:dropout ;
vc:hasPart ngm:embedding ;
vc:hasPart ngm:encoder ;
vc:hasPart ngm:neural-network-layer ;
vc:hasPart ngm:positional-encoding ;
vc:hasPart ngm:residual-connection ;
vc:implements ngm:convolutional-neural-network ;
vc:implements ngm:feedforward-neural-network ;
vc:implements ngm:graph-neural-network ;
vc:implements ngm:recurrent-neural-network ;
vc:implements ngm:transformer-architecture ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:ai-model ;
vc:relatedTo ngm:diffusion-model ;
vc:relatedTo ngm:eu-ai-act-regulatory-instrument ;
vc:relatedTo ngm:foundation-model ;
vc:relatedTo ngm:graph-neural-network ;
vc:relatedTo ngm:knowledge-distillation ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:mixture-of-experts ;
vc:relatedTo ngm:neural-architecture-search ;
vc:relatedTo ngm:neural-network-architecture ;
vc:relatedTo ngm:responsible-ai ;
vc:relatedTo ngm:self-supervised-learning ;
vc:relatedTo ngm:transformer-architecture ;
vc:requires ngm:backpropagation ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:gradient-descent ;
vc:requires ngm:hyperparameter-tuning ;
vc:requires ngm:inductive-bias ;
vc:requires ngm:loss-function ;
vc:slug "architecture" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:supports ngm:ai-safety ;
vc:supports ngm:model-deployment ;
vc:supports ngm:multimodal-ai ;
vc:supports ngm:multimodal-ai-architecture-ai ;
vc:uses ngm:batch-normalisation ;
vc:uses ngm:dropout ;
vc:uses ngm:edge-computing ;
vc:uses ngm:feedforward-neural-network ;
vc:uses ngm:gpu-compute ;
vc:uses ngm:neural-network .
ngm:architecture-and-reference-framework a skos:Concept ;
rdfs:label "Architecture And Reference Framework"@en .
ngm:architecture-decision-record a skos:Concept ;
rdfs:label "Architecture Decision Record"@en .
ngm:architecture-documentation a skos:Concept ;
rdfs:label "Architecture Documentation"@en .
ngm:archival-node a owl:Class ;
rdfs:comment "An Archival Node is a blockchain network participant that stores the complete historical state of the ledger—every block, transaction, and state root from genesis to the current tip—without pruning older data. Unlike pruned nodes or light nodes, an archival node can respond to queries about any historical state at any block height, making it essential for block explorers, analytics services, and smart contract developers who need point-in-time state access."@en ;
rdfs:label "Archival Node"@en ;
rdfs:subClassOf ngm:blockchain-entity ;
rdfs:subClassOf ngm:network-component ;
rdfs:subClassOf _:r1856 ;
rdfs:subClassOf _:r1857 ;
vc:contrastsWith ngm:light-node ;
vc:contrastsWith ngm:pruned-node ;
vc:enables ngm:blockchain-compliance ;
vc:enables ngm:blockchain-transaction ;
vc:enables ngm:long-term-archival ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:blockchain-infrastructure ;
vc:relatedTo ngm:blockchain-network ;
vc:relatedTo ngm:chain-state ;
vc:relatedTo ngm:full-node ;
vc:requires ngm:blockchain-protocol ;
vc:requires ngm:peer-to-peer-network ;
vc:slug "archival-node" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:state-machine-replication .
ngm:archival-photo-restoration a skos:Concept ;
rdfs:label "Archival Photo Restoration"@en .
ngm:archival-standards a owl:Class ;
rdfs:comment "Archival Standards encompass frameworks, specifications, and best practices for long-term digital preservation, including metadata standards (PREMIS, METS), reference models (OAIS), and storage technologies that ensure digital content remains accessible, authentic, and interpretable across technological changes."@en ;
rdfs:label "Archival Standards"@en ;
rdfs:subClassOf ngm:preservation-standards ;
rdfs:subClassOf ngm:sc-standards-and-interop ;
rdfs:subClassOf _:r1858 ;
rdfs:subClassOf _:r1859 ;
rdfs:subClassOf _:r1860 ;
skos:broader ngm:sc-standards-and-interop ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:data-governance ;
vc:bridgesTo ngm:infra-legal-and-regulatory ;
vc:contrastsWith ngm:backup-and-recovery ;
vc:enables ngm:content-authenticity ;
vc:enables ngm:digital-repository ;
vc:enables ngm:format-migration ;
vc:enables ngm:long-term-preservation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:metadata-standard ;
vc:implements ngm:reference-model ;
vc:qualityScore "0.7"^^xsd:float ;
vc:relatedTo ngm:open-archival-information-system ;
vc:relatedTo ngm:records-management ;
vc:requires ngm:digital-preservation ;
vc:requires ngm:metadata-management ;
vc:requires ngm:preservation-planning ;
vc:requires ngm:storage-infrastructure ;
vc:slug "archival-standards" ;
vc:sourceDomain "standards" ;
vc:standardizedBy ngm:iso-14721 ;
vc:supports ngm:information-governance ;
vc:supports ngm:interoperability ;
vc:supports ngm:regulatory-compliance ;
vc:uses ngm:checksum-verification ;
vc:uses ngm:digital-signature ;
vc:uses ngm:provenance-tracking .
ngm:archive-node a skos:Concept ;
rdfs:label "Archive Node"@en .
ngm:archive-permanence a skos:Concept ;
rdfs:label "Archive Permanence"@en .
ngm:archived-data-state a owl:Class ;
rdfs:label "Archived Data State"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-processing ;
vc:slug "archived-data-state" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:arcjet a owl:Class ;
rdfs:label "Arcjet"@en ;
rdfs:subClassOf ngm:thruster ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:spacecraft-propulsion ;
vc:slug "arcjet" ;
vc:sourceDomain "space-science-and-systems" .
ngm:arcore a owl:Class ;
rdfs:comment "ARCore is Google's software development kit for building augmented-reality applications on Android and, via web standards, the browser. It provides motion tracking, environmental understanding and light estimation by fusing camera frames with inertial sensors to anchor virtual content in the physical world. ARCore is the principal counterpart to Apple's ARKit in the mobile-AR ecosystem."@en ;
rdfs:label "Arcore"@en ;
rdfs:subClassOf ngm:ar-experiences ;
rdfs:subClassOf ngm:augmented-reality ;
rdfs:subClassOf _:r1861 ;
vc:dependsOn ngm:visual-slam ;
vc:enables ngm:scene-understanding ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:slam ;
vc:isPartOf ngm:augmented-reality ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:spatial-anchors ;
vc:requires ngm:camera-calibration ;
vc:slug "arcore" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:augmented-reality ;
vc:supports ngm:spatial-anchor ;
vc:supports ngm:spatial-anchors ;
vc:uses ngm:depth-estimation ;
vc:uses ngm:slam ;
vc:uses ngm:visual-slam .
ngm:area-chairs a skos:Concept ;
rdfs:label "Area Chairs"@en .
ngm:area-under-the-curve a skos:Concept ;
rdfs:label "Area Under The Curve"@en .
ngm:arena-hard a skos:Concept ;
rdfs:label "Arena Hard"@en .
ngm:ares-framework a skos:Concept ;
rdfs:label "Ares Framework"@en .
ngm:argent a owl:Class ;
rdfs:comment "A smart contract wallet for Ethereum and Layer 2 networks that uses account abstraction to provide features such as social recovery, spending limits and gasless transactions."@en ;
rdfs:label "Argent"@en ;
rdfs:subClassOf ngm:wallet ;
rdfs:subClassOf _:r1862 ;
rdfs:subClassOf _:r1863 ;
vc:bridgesTo ngm:ethereum-smart-contract-platform ;
vc:bridgesTo ngm:wallet ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:account-abstraction ;
vc:requires ngm:smart-contracts ;
vc:slug "argent" ;
vc:sourceDomain "blockchain" .
ngm:argo-blockchain a owl:Class ;
rdfs:comment "Argo Blockchain is a publicly listed cryptocurrency mining company that operates data centres performing the hashing that secures proof-of-work networks, chiefly Bitcoin."@en ;
rdfs:label "Argo Blockchain"@en ;
rdfs:subClassOf ngm:bitcoin-proof-of-work-protocol-mining ;
rdfs:subClassOf _:r1864 ;
vc:bridgesTo ngm:cryptocurrency ;
vc:bridgesTo ngm:sustainability-domain ;
vc:enables ngm:bitcoin-proof-of-work-protocol ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:bitcoin-proof-of-work-protocol-mining ;
vc:slug "argo-blockchain" ;
vc:sourceDomain "metaverse" .
ngm:argo-cd a skos:Concept ;
rdfs:label "Argo Cd"@en .
ngm:argo-project a skos:Concept ;
rdfs:label "Argo Project"@en .
ngm:argo-rollouts a skos:Concept ;
rdfs:label "Argo Rollouts"@en .
ngm:argon2 a skos:Concept ;
rdfs:label "Argon2"@en .
ngm:arguana a skos:Concept ;
rdfs:label "Arguana"@en .
ngm:argument-of-periapsis a owl:Class ;
rdfs:label "Argument of Periapsis"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:orbital-dynamics ;
vc:slug "argument-of-periapsis" ;
vc:sourceDomain "space-science-and-systems" .
ngm:argument-parser a skos:Concept ;
rdfs:label "Argument Parser"@en .
ngm:argument-validator a skos:Concept ;
rdfs:label "Argument Validator"@en .
ngm:aria a skos:Concept ;
rdfs:label "Aria"@en .
ngm:aria-role a skos:Concept ;
rdfs:label "Aria Role"@en .
ngm:aria-state a skos:Concept ;
rdfs:label "Aria State"@en .
ngm:aries-askar a skos:Concept ;
rdfs:label "Aries Askar"@en .
ngm:aries-cloud-agent-python a skos:Concept ;
rdfs:label "Aries Cloud Agent Python"@en .
ngm:arima a skos:Concept ;
rdfs:label "Arima"@en .
ngm:arithmetic-circuit a owl:Class ;
rdfs:comment "A directed acyclic graph (DAG) of addition and multiplication gates over a field, used to represent polynomial computations in a form amenable to cryptographic proof systems. Arithmetic circuits are the canonical intermediate representation for zero-knowledge proof schemes such as zk-SNARKs and STARKs: a computation is first expressed as an arithmetic circuit, then compiled into a system of polynomial constraints (R1CS or Plonkish), and finally proved using a cryptographic proving system. The complexity of a circuit is characterised by its depth (for parallelism) and size (gate count)."@en ;
rdfs:label "Arithmetic Circuit"@en ;
rdfs:subClassOf ngm:security ;
rdfs:subClassOf _:r1865 ;
rdfs:subClassOf _:r1866 ;
vc:bridgesTo ngm:blockchain ;
vc:contrastsWith ngm:boolean-circuit ;
vc:dependsOn ngm:elliptic-curve-cryptography ;
vc:enables ngm:verifiable-computation ;
vc:enables ngm:zk-snark ;
vc:enables ngm:zk-starks ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:logic-gate ;
vc:implements ngm:cryptographic-protocol ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:boolean-circuit ;
vc:relatedTo ngm:homomorphic-encryption ;
vc:relatedTo ngm:secure-multi-party-computation ;
vc:requires ngm:finite-field-arithmetic ;
vc:requires ngm:polynomial-commitment ;
vc:slug "arithmetic-circuit" ;
vc:sourceDomain "security" ;
vc:supports ngm:privacy-preserving-computation ;
vc:uses ngm:constraint-system ;
vc:uses ngm:zero-knowledge-proof .
ngm:ark-protocol a owl:Class ;
rdfs:comment "Ark is a layer-two protocol for Bitcoin that uses shared, periodically refreshed off-chain outputs to let users transact cheaply and privately while retaining the ability to settle on the base chain."@en ;
rdfs:label "Ark Protocol"@en ;
rdfs:subClassOf ngm:bitcoin-proof-of-work-protocol ;
rdfs:subClassOf _:r1867 ;
vc:bridgesTo ngm:payment-network ;
vc:bridgesTo ngm:stablecoin ;
vc:enables ngm:cross-border-payments ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:bitcoin-proof-of-work-protocol ;
vc:slug "ark-protocol" ;
vc:sourceDomain "metaverse" .
ngm:arkg-i2-benchmark a owl:Class ;
rdfs:comment "A standardized evaluation metric used to assess the performance of large language models on specific reasoning or intelligence tasks."@en ;
rdfs:label "ARKG I2 Benchmark"@en ;
rdfs:subClassOf ngm:model-performance ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:deep-think ;
vc:relatedTo ngm:model-performance ;
vc:slug "arkg-i2-benchmark" ;
vc:sourceDomain "artificial-intelligence" .
ngm:arkit a owl:Class ;
rdfs:comment "ARKit is Apple's augmented reality development framework for iOS and iPadOS devices, providing motion tracking, environment understanding and rendering integration for placing virtual content in the physical world. It uses visual-inertial odometry, plane detection and scene reconstruction to anchor digital objects stably relative to real surfaces. ARKit gives developers a high-level API over the device camera, motion sensors and Neural Engine to build mobile AR experiences."@en ;
rdfs:label "Arkit"@en ;
rdfs:subClassOf ngm:augmented-reality ;
rdfs:subClassOf ngm:environmental-mapping ;
vc:contrastsWith ngm:arcore ;
vc:enables ngm:augmented-reality ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:augmented-reality ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:arcore ;
vc:slug "arkit" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:spatial-computing ;
vc:supports ngm:spatial-computing ;
vc:supports ngm:unity ;
vc:uses ngm:scene-understanding ;
vc:uses ngm:slam ;
vc:uses ngm:spatial-anchor .
ngm:arm-architecture a skos:Concept ;
rdfs:label "Arm Architecture"@en .
ngm:arm-cortex a skos:Concept ;
rdfs:label "Arm Cortex"@en .
ngm:arm-cortex-m a skos:Concept ;
rdfs:label "Arm Cortex M"@en .
ngm:arm-ecosystem a skos:Concept ;
rdfs:label "Arm Ecosystem"@en .
ngm:arm-ethos-npu a skos:Concept ;
rdfs:label "Arm Ethos Npu"@en .
ngm:arm-holdings a skos:Concept ;
rdfs:label "Arm Holdings"@en .
ngm:arm-nn a skos:Concept ;
rdfs:label "Arm Nn"@en .
ngm:arm-trust-zone a owl:Class ;
rdfs:comment "ARM TrustZone is a hardware security technology built into ARM processors that partitions the system into two isolated execution worlds — a Secure World and a Normal World — enforced at the level of the CPU, memory, and peripherals. Sensitive code and data, such as cryptographic keys and biometric matching, run in the Secure World inaccessible to the rich operating system in the Normal World, providing a trusted execution environment without a separate security chip. It is ubiquitous in mobile devices, embedded systems, and IoT hardware."@en ;
rdfs:label "ARM TrustZone"@en ;
rdfs:subClassOf ngm:tee ;
vc:enables ngm:secure-enclave ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:tee ;
vc:slug "arm-trust-zone" ;
vc:sourceDomain "security" ;
vc:supports ngm:hardware-security .
ngm:arm64-linux a skos:Concept ;
rdfs:label "Arm64 Linux"@en .
ngm:arp4754-a a owl:Class ;
rdfs:comment "ARP4754A is an aerospace recommended practice published by SAE International in 2010, titled 'Guidelines for Development of Civil Aircraft and Systems,' which provides a structured framework for the development and safety assessment of complex aircraft systems and functions. It establishes processes for identifying and mitigating failure conditions across the full aircraft system lifecycle, defining Development Assurance Levels (DAL A through E) that calibrate the rigour of development and verification activities to the severity of the failure conditions a system can contribute to. ARP4754A works in conjunction with related standards including ARP4761 for safety assessment and DO-178C for software development."@en ;
rdfs:label "ARP4754A"@en ;
rdfs:subClassOf ngm:safety-standard ;
rdfs:subClassOf _:r897 ;
rdfs:subClassOf _:r898 ;
rdfs:subClassOf _:r899 ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:do-178-c ;
vc:relatedTo ngm:functional-safety ;
vc:relatedTo ngm:safety-critical-systems ;
vc:requires ngm:hazard-analysis ;
vc:requires ngm:safety-assessment ;
vc:requires ngm:verification ;
vc:slug "arp4754-a" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:compliance ;
vc:supports ngm:systems-engineering .
ngm:arpu a owl:Class ;
rdfs:comment "Average Revenue Per User is a key performance indicator that measures the average revenue generated per customer over a specific period."@en ;
rdfs:label "ARPU"@en ;
rdfs:subClassOf ngm:advertising ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:advertising ;
vc:relatedTo ngm:programmatic-advertising ;
vc:slug "arpu" ;
vc:sourceDomain "economics" .
ngm:array a skos:Concept ;
rdfs:label "Array"@en .
ngm:arrow-impossibility-theorem a skos:Concept ;
rdfs:label "Arrow Impossibility Theorem"@en .
ngm:arrows-impossibility-theorem a skos:Concept ;
rdfs:label "Arrows Impossibility Theorem"@en .
ngm:art-curation a skos:Concept ;
rdfs:label "Art Curation"@en .
ngm:art-direction a skos:Concept ;
rdfs:label "Art Direction"@en .
ngm:art-historical-knowledge a skos:Concept ;
rdfs:label "Art Historical Knowledge"@en .
ngm:article-6-compliance a skos:Concept ;
rdfs:label "Article 6 Compliance"@en .
ngm:article-8-fund-classification a skos:Concept ;
rdfs:label "Article 8 Fund Classification"@en .
ngm:article-9-fund-classification a skos:Concept ;
rdfs:label "Article 9 Fund Classification"@en .
ngm:article-iv-consultation a skos:Concept ;
rdfs:label "Article Iv Consultation"@en .
ngm:articles-of-agreement a skos:Concept ;
rdfs:label "Articles Of Agreement"@en .
ngm:articles-of-organization a skos:Concept ;
rdfs:label "Articles Of Organization"@en .
ngm:articulation-point-detection a skos:Concept ;
rdfs:label "Articulation Point Detection"@en .
ngm:artifact-metadata a owl:Class ;
rdfs:comment "Artifact Metadata refers to structured descriptive, administrative, and provenance information associated with digital assets and cultural objects, particularly in NFT and blockchain contexts, documenting ownership history, authenticity, cultural significance, and preservation status for verifica..."@en ;
rdfs:label "Artifact Metadata"@en ;
rdfs:subClassOf ngm:digital-metadata ;
rdfs:subClassOf ngm:sc-content-and-assets ;
rdfs:subClassOf _:r1868 ;
rdfs:subClassOf _:r1869 ;
rdfs:subClassOf _:r1870 ;
rdfs:subClassOf _:r1871 ;
rdfs:subClassOf _:r1872 ;
skos:broader ngm:sc-content-and-assets ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:data-management ;
vc:enables ngm:content-authenticity ;
vc:enables ngm:cultural-preservation ;
vc:enables ngm:provenance-verification ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:blockchain ;
vc:requires ngm:metadata-standards ;
vc:requires ngm:technical-documentation ;
vc:slug "artifact-metadata" ;
vc:sourceDomain "spatial-computing" .
ngm:artifact-versioning a skos:Concept ;
rdfs:label "Artifact Versioning"@en .
ngm:artificial-general-intelligence a owl:Class ;
rdfs:comment "Artificial General Intelligence (AGI) denotes a hypothesised class of computational systems whose cognitive competence is broad rather than narrow — capable of matching or exceeding human performance across the full distribution of economically and intellectually significant tasks rather than exc..."@en ;
rdfs:label "Artificial General Intelligence"@en ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf ngm:foundation-model-capability ;
rdfs:subClassOf ngm:frontier-ai ;
rdfs:subClassOf ngm:general-intelligence ;
rdfs:subClassOf _:r1873 ;
rdfs:subClassOf _:r1874 ;
rdfs:subClassOf _:r1875 ;
rdfs:subClassOf _:r1876 ;
rdfs:subClassOf _:r1877 ;
rdfs:subClassOf _:r1878 ;
rdfs:subClassOf _:r1879 ;
rdfs:subClassOf _:r1880 ;
skos:broader ngm:ai-research-area ;
skos:broader ngm:artificial-intelligence ;
vc:contrastsWith ngm:domain-specific-ai ;
vc:contrastsWith ngm:expert-systems ;
vc:contrastsWith ngm:narrow-ai ;
vc:contrastsWith ngm:symbolic-ai ;
vc:contrastsWith ngm:weak-ai ;
vc:dependsOn ngm:benchmarks ;
vc:dependsOn ngm:bitter-lesson ;
vc:dependsOn ngm:compute-trends ;
vc:dependsOn ngm:pretraining ;
vc:dependsOn ngm:rlhf ;
vc:dependsOn ngm:transformer-architecture ;
vc:enables ngm:autonomous-agent ;
vc:enables ngm:economic-automation ;
vc:enables ngm:recursive-self-improvement ;
vc:enables ngm:scientific-discovery-acceleration ;
vc:enables ngm:transformative-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:autonomous-reasoning ;
vc:hasPart ngm:cross-domain-transfer ;
vc:hasPart ngm:generalisation-capability ;
vc:hasPart ngm:long-horizon-planning ;
vc:hasPart ngm:open-ended-learning ;
vc:hasPart ngm:tool-use ;
vc:hasPart ngm:world-model ;
vc:implements ngm:chain-of-thought-reasoning ;
vc:implements ngm:constitutional-ai-training-methodology ;
vc:implements ngm:inference-compute ;
vc:implements ngm:mixture-of-experts-architecture ;
vc:implements ngm:multimodal-ai-architecture-learning ;
vc:implements ngm:scaling-hypothesis ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:ai-alignment ;
vc:relatedTo ngm:existential-risk ;
vc:relatedTo ngm:foundation-model ;
vc:relatedTo ngm:frontier-ai ;
vc:relatedTo ngm:large-scale-pretrained-foundation-model ;
vc:relatedTo ngm:recursive-self-improvement ;
vc:relatedTo ngm:superintelligence ;
vc:relatedTo ngm:transformative-ai ;
vc:requires ngm:alignment-techniques ;
vc:requires ngm:evaluation-infrastructure ;
vc:requires ngm:frontier-training-data ;
vc:requires ngm:large-scale-compute ;
vc:requires ngm:reinforcement-learning ;
vc:requires ngm:scaling-laws ;
vc:slug "artificial-general-intelligence" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:deepmind-levels-of-agi-framework ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:standardizedBy ngm:openai-charter ;
vc:supports ngm:ai-governance ;
vc:supports ngm:ai-policy ;
vc:supports ngm:ai-safety-research ;
vc:supports ngm:alignment-research ;
vc:supports ngm:existential-risk-studies ;
vc:uses ngm:arc-agi ;
vc:uses ngm:frontiermath ;
vc:uses ngm:gpqa ;
vc:uses ngm:humanity-s-last-exam ;
vc:uses ngm:metr-evaluations ;
vc:uses ngm:mmlu ;
vc:uses ngm:swe-bench .
ngm:artificial-intelligence a owl:Class ;
a skos:Concept ;
rdfs:comment "Artificial Intelligence is a artificial intelligence concept and a type of owl:Thing. that enables Autonomous Systems, Decision Support. comprising Computer Vision, Deep Learning."@en ;
rdfs:label "Artificial Intelligence"@en ;
rdfs:subClassOf ngm:thing ;
rdfs:subClassOf _:r1915 ;
rdfs:subClassOf _:r1916 ;
rdfs:subClassOf _:r1917 ;
rdfs:subClassOf _:r1918 ;
rdfs:subClassOf _:r1919 ;
rdfs:subClassOf _:r1920 ;
rdfs:subClassOf _:r1921 ;
rdfs:subClassOf _:r1922 ;
rdfs:subClassOf _:r1923 ;
rdfs:subClassOf _:r1924 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:robotics ;
vc:bridgesTo ngm:telecollaboration ;
vc:enables ngm:autonomous-system ;
vc:enables ngm:decision-support ;
vc:enables ngm:intelligent-automation ;
vc:enables ngm:personalisation ;
vc:enables ngm:predictive-analytics ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:computer-vision ;
vc:hasPart ngm:deep-learning ;
vc:hasPart ngm:generative-ai ;
vc:hasPart ngm:machine-learning-discipline ;
vc:hasPart ngm:natural-language-processing ;
vc:hasPart ngm:reinforcement-learning ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:computational-infrastructure ;
vc:requires ngm:neural-network ;
vc:requires ngm:training-data ;
vc:slug "artificial-intelligence" ;
vc:sourceDomain "artificial-intelligence" .
ngm:artificial-intelligence-act a skos:Concept ;
rdfs:label "Artificial Intelligence Act"@en .
ngm:artificial-intelligence-core a owl:Class ;
rdfs:comment "Artificial Intelligence Core is the foundational upper class that anchors the core concepts and capabilities of artificial intelligence within the ontology, serving as the common ancestor for machine learning, agent systems, and related disciplines. It represents the essential body of theory and method by which machines perform tasks that normally require human intelligence, such as learning, reasoning, perception, and decision-making. As a structural root it organizes more specific AI subfields beneath a single semantic anchor, encompassing symbolic methods, statistical learning, connectionist architectures, and their contemporary convergences in foundation models and agentic systems."@en ;
rdfs:label "Artificial Intelligence Core"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf _:r1881 ;
rdfs:subClassOf _:r1882 ;
rdfs:subClassOf _:r1883 ;
rdfs:subClassOf _:r1884 ;
rdfs:subClassOf _:r1885 ;
rdfs:subClassOf _:r1886 ;
rdfs:subClassOf _:r1887 ;
rdfs:subClassOf _:r1888 ;
rdfs:subClassOf _:r1889 ;
rdfs:subClassOf _:r1890 ;
rdfs:subClassOf _:r1891 ;
rdfs:subClassOf _:r1892 ;
rdfs:subClassOf _:r1893 ;
rdfs:subClassOf _:r1894 ;
rdfs:subClassOf _:r1895 ;
rdfs:subClassOf _:r1896 ;
rdfs:subClassOf _:r1897 ;
rdfs:subClassOf _:r1898 ;
rdfs:subClassOf _:r1899 ;
rdfs:subClassOf _:r1900 ;
rdfs:subClassOf _:r1901 ;
skos:broader ngm:ai-technique ;
skos:broader ngm:artificial-intelligence ;
vc:contrastsWith ngm:expert-systems ;
vc:contrastsWith ngm:symbolic-ai ;
vc:dependsOn ngm:active-learning ;
vc:dependsOn ngm:gpu-compute ;
vc:dependsOn ngm:neural-network ;
vc:dependsOn ngm:probability-theory ;
vc:dependsOn ngm:supervised-learning ;
vc:dependsOn ngm:transfer-learning ;
vc:dependsOn ngm:unsupervised-learning ;
vc:enables ngm:agentic-ai ;
vc:enables ngm:agentic-workflow ;
vc:enables ngm:ai-safety-research ;
vc:enables ngm:artificial-general-intelligence ;
vc:enables ngm:autonomous-agent ;
vc:enables ngm:benchmark-evaluation ;
vc:enables ngm:explainable-ai ;
vc:enables ngm:foundation-model ;
vc:enables ngm:large-language-models ;
vc:enables ngm:multimodal-ai-architecture-ai ;
vc:enables ngm:open-source-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:agentic-ai ;
vc:hasPart ngm:computer-vision ;
vc:hasPart ngm:deep-learning ;
vc:hasPart ngm:expert-systems ;
vc:hasPart ngm:knowledge-representation ;
vc:hasPart ngm:machine-learning-discipline ;
vc:hasPart ngm:multimodal-ai-architecture-ai ;
vc:hasPart ngm:natural-language-processing ;
vc:hasPart ngm:neural-network ;
vc:hasPart ngm:planning-and-search ;
vc:hasPart ngm:reinforcement-learning ;
vc:hasPart ngm:robotics ;
vc:implements ngm:active-learning ;
vc:implements ngm:attention-mechanism ;
vc:implements ngm:backpropagation ;
vc:implements ngm:bayesian-inference ;
vc:implements ngm:continual-learning ;
vc:implements ngm:data-driven-learning ;
vc:implements ngm:reinforcement-learning ;
vc:implements ngm:transformer-architecture ;
vc:qualityScore "0.91"^^xsd:float ;
vc:relatedTo ngm:adversarial-machine-learning ;
vc:relatedTo ngm:ai-agent-system ;
vc:relatedTo ngm:ai-research ;
vc:relatedTo ngm:applied-machine-learning ;
vc:relatedTo ngm:artificial-general-intelligence ;
vc:relatedTo ngm:bayesian-deep-learning ;
vc:relatedTo ngm:cognitive-science ;
vc:relatedTo ngm:contrastive-learning ;
vc:relatedTo ngm:curriculum-learning ;
vc:relatedTo ngm:frontier-ai ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:neural-symbolic-ai ;
vc:relatedTo ngm:robotics ;
vc:relatedTo ngm:symbolic-ai ;
vc:requires ngm:dataset-curation ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:gradient-descent ;
vc:requires ngm:information-theory ;
vc:requires ngm:loss-function ;
vc:requires ngm:optimisation ;
vc:requires ngm:probability-theory ;
vc:requires ngm:statistical-learning ;
vc:requires ngm:supervised-learning ;
vc:requires ngm:transfer-learning ;
vc:requires ngm:unsupervised-learning ;
vc:slug "artificial-intelligence-core" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:alan-turing-institute ;
vc:supports ngm:ai-ethics ;
vc:supports ngm:ai-policy ;
vc:supports ngm:ai-research ;
vc:supports ngm:ai-safety-research ;
vc:supports ngm:alignment-research ;
vc:supports ngm:benchmark-evaluation ;
vc:supports ngm:explainable-ai ;
vc:uses ngm:cognitive-science ;
vc:uses ngm:hypothesis-testing ;
vc:uses ngm:information-theory ;
vc:uses ngm:probability-theory ;
vc:uses ngm:scientific-method ;
vc:uses ngm:statistical-learning-theory .
ngm:artificial-intelligence-ethics a skos:Concept ;
rdfs:label "Artificial Intelligence Ethics"@en .
ngm:artificial-intelligence-hardware a skos:Concept ;
rdfs:label "Artificial Intelligence Hardware"@en .
ngm:artificial-intelligence-in-finance a skos:Concept ;
rdfs:label "Artificial Intelligence In Finance"@en .
ngm:artificial-intelligence-operations a skos:Concept ;
rdfs:label "Artificial Intelligence Operations"@en .
ngm:artificial-intelligence-research a owl:Class ;
rdfs:comment "Artificial intelligence research is the scientific and engineering discipline concerned with understanding and building systems that exhibit intelligent behaviour, including perception, reasoning, learning, planning, and language. It spans theoretical foundations, algorithmic innovation, and empirical evaluation, and feeds discoveries into subfields such as machine learning, computer vision, and natural language processing. The field advances through hypothesis-driven inquiry using the scientific method, publication and peer review, standardised benchmarking, and reproducible experimentation, generating knowledge that flows into applied AI systems and deployed products across industry and government."@en ;
rdfs:label "Artificial Intelligence Research"@en ;
rdfs:subClassOf ngm:research-and-development ;
rdfs:subClassOf _:r1902 ;
rdfs:subClassOf _:r1903 ;
rdfs:subClassOf _:r1904 ;
rdfs:subClassOf _:r1905 ;
rdfs:subClassOf _:r1906 ;
rdfs:subClassOf _:r1907 ;
rdfs:subClassOf _:r1908 ;
rdfs:subClassOf _:r1909 ;
rdfs:subClassOf _:r1910 ;
rdfs:subClassOf _:r1911 ;
rdfs:subClassOf _:r1912 ;
rdfs:subClassOf _:r1913 ;
rdfs:subClassOf _:r1914 ;
vc:bridgesTo ngm:ai-safety-research ;
vc:bridgesTo ngm:applied-machine-learning ;
vc:bridgesTo ngm:deep-learning ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:bridgesTo ngm:natural-language-processing ;
vc:contrastsWith ngm:applied-machine-learning ;
vc:dependsOn ngm:benchmark-evaluation ;
vc:dependsOn ngm:dataset-curation ;
vc:dependsOn ngm:gpu-compute ;
vc:dependsOn ngm:open-source-ai ;
vc:dependsOn ngm:preprint-culture ;
vc:dependsOn ngm:research-and-development ;
vc:enables ngm:agentic-ai ;
vc:enables ngm:ai-safety-research ;
vc:enables ngm:alignment-research ;
vc:enables ngm:artificial-general-intelligence ;
vc:enables ngm:artificial-intelligence ;
vc:enables ngm:explainable-ai ;
vc:enables ngm:foundation-model ;
vc:enables ngm:frontier-ai ;
vc:enables ngm:knowledge-discovery ;
vc:enables ngm:large-language-models ;
vc:enables ngm:multimodal-ai-architecture-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:benchmark-evaluation ;
vc:hasPart ngm:dataset-curation ;
vc:hasPart ngm:empirical-evaluation ;
vc:hasPart ngm:evaluation-metric ;
vc:hasPart ngm:experimental-design ;
vc:hasPart ngm:hypothesis-testing ;
vc:hasPart ngm:peer-review ;
vc:hasPart ngm:preprint-culture ;
vc:hasPart ngm:reproducibility ;
vc:implements ngm:benchmark-evaluation ;
vc:implements ngm:empirical-evaluation ;
vc:implements ngm:experimental-design ;
vc:implements ngm:hypothesis-testing ;
vc:implements ngm:peer-review ;
vc:implements ngm:reproducibility ;
vc:implements ngm:scientific-method ;
vc:isPartOf ngm:research-and-development ;
vc:qualityScore "0.91"^^xsd:float ;
vc:relatedTo ngm:active-learning ;
vc:relatedTo ngm:adversarial-machine-learning ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:ai-policy ;
vc:relatedTo ngm:artificial-general-intelligence ;
vc:relatedTo ngm:attention-mechanism ;
vc:relatedTo ngm:bayesian-deep-learning ;
vc:relatedTo ngm:computer-vision ;
vc:relatedTo ngm:continual-learning ;
vc:relatedTo ngm:contrastive-learning ;
vc:relatedTo ngm:curriculum-learning ;
vc:relatedTo ngm:knowledge-discovery ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:neural-network ;
vc:relatedTo ngm:neural-symbolic-ai ;
vc:relatedTo ngm:reinforcement-learning ;
vc:relatedTo ngm:robotics ;
vc:relatedTo ngm:symbolic-ai ;
vc:relatedTo ngm:transfer-learning ;
vc:relatedTo ngm:transformer-architecture ;
vc:requires ngm:benchmarks ;
vc:requires ngm:dataset-curation ;
vc:requires ngm:evaluation-metric ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:open-source-ai ;
vc:requires ngm:preprint-culture ;
vc:requires ngm:scientific-method ;
vc:slug "artificial-intelligence-research" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:alan-turing-institute ;
vc:supports ngm:ai-ethics ;
vc:supports ngm:ai-policy ;
vc:supports ngm:ai-safety-research ;
vc:supports ngm:alignment-research ;
vc:supports ngm:artificial-intelligence ;
vc:supports ngm:deep-learning ;
vc:supports ngm:explainable-ai ;
vc:supports ngm:foundation-model ;
vc:supports ngm:machine-learning-discipline ;
vc:supports ngm:neural-network ;
vc:uses ngm:alan-turing-institute ;
vc:uses ngm:benchmarks ;
vc:uses ngm:evaluation-metric ;
vc:uses ngm:gpu-compute ;
vc:uses ngm:open-source-ai ;
vc:uses ngm:preprint-culture ;
vc:uses ngm:reproducibility ;
vc:uses ngm:scientific-method .
ngm:artificial-intimacy a skos:Concept ;
rdfs:label "Artificial Intimacy"@en .
ngm:artificial-life a skos:Concept ;
rdfs:label "Artificial Life"@en .
ngm:artificial-superintelligence-theory a owl:Class ;
rdfs:comment "A hypothetical form of artificial intelligence that surpasses human cognitive performance across all domains, capable of recursive self-improvement leading to an intelligence explosion. Distinguished from artificial general intelligence by the degree of capability surplus; considered an existential risk scenario requiring robust safety and alignment research before any attempt at development."@en ;
rdfs:label "Artificial Superintelligence Theory"@en ;
rdfs:subClassOf ngm:infra-computing-and-cloud ;
rdfs:subClassOf _:r1925 ;
rdfs:subClassOf _:r1926 ;
skos:broader ngm:infra-computing-and-cloud ;
vc:contrastsWith ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:ai-risks ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:singularity ;
vc:requires ngm:artificial-general-intelligence ;
vc:requires ngm:machine-learning-discipline ;
vc:slug "artificial-superintelligence-theory" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:aiethics .
ngm:artistic-stylization a skos:Concept ;
rdfs:label "Artistic Stylization"@en .
ngm:aruco a skos:Concept ;
rdfs:label "Aruco"@en .
ngm:arweave a owl:Class ;
rdfs:comment "Arweave is a decentralised, blockweave-based storage protocol that enables permanent, censorship-resistant archival of data through a proof-of-access consensus mechanism, where miners must demonstrate retention of a randomly selected historic block to produce new blocks. It introduces the 'permaweb' — a permanent, publicly accessible layer of the web sustained by a one-time payment model where a portion of each storage fee accrues to an endowment that compensates miners across an indefinite time horizon. The network's economic model assumes that declining hardware costs will be outpaced by AR token appreciation, funding perpetual content replication across an open, permissionless peer set. Beyond raw storage, Arweave hosts SmartWeave lazy-evaluation contracts and the AO actor-oriented compute environment, extending it into a foundation for permanent, verifiable decentralised computation."@en ;
rdfs:label "Arweave"@en ;
rdfs:subClassOf ngm:decentralized-storage ;
rdfs:subClassOf _:r1927 ;
vc:bridgesTo ngm:data-provenance ;
vc:bridgesTo ngm:knowledge-graph ;
vc:bridgesTo ngm:verifiable-credentials ;
vc:contrastsWith ngm:bittorrent ;
vc:contrastsWith ngm:filecoin ;
vc:contrastsWith ngm:ipfs ;
vc:contrastsWith ngm:object-storage ;
vc:enables ngm:censorship-resistance ;
vc:enables ngm:data-persistence ;
vc:enables ngm:decentralised-application ;
vc:enables ngm:digital-archive ;
vc:enables ngm:non-fungible-token ;
vc:enables ngm:smart-contract ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ao-compute ;
vc:hasPart ngm:blockweave ;
vc:hasPart ngm:bundlr-network ;
vc:hasPart ngm:smartweave ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:de-fi ;
vc:relatedTo ngm:distributed-storage ;
vc:relatedTo ngm:web3 ;
vc:requires ngm:ar-token ;
vc:requires ngm:peer-to-peer-network ;
vc:slug "arweave" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:content-addressing ;
vc:uses ngm:cryptographic-hash-function ;
vc:uses ngm:merkle-dag ;
vc:uses ngm:proof-of-access ;
vc:uses ngm:proof-of-work ;
vc:uses ngm:token-economics .
ngm:arxiv a skos:Concept ;
rdfs:label "Arxiv"@en .
ngm:arxiv-preprint a skos:Concept ;
rdfs:label "Arxiv Preprint"@en .
ngm:arxiv-preprint-standards a skos:Concept ;
rdfs:label "Arxiv Preprint Standards"@en .
ngm:asa a skos:Concept ;
rdfs:label "Asa"@en .
ngm:ascii-art-attack a skos:Concept ;
rdfs:label "Ascii Art Attack"@en .
ngm:asean-ai-governance-guide a skos:Concept ;
rdfs:label "Asean AI Governance Guide"@en .
ngm:asean-digital-ministers-meeting a skos:Concept ;
rdfs:label "Asean Digital Ministers Meeting"@en .
ngm:asia-pacific-regulation a owl:Class ;
rdfs:comment "Asia Pacific Regulation denotes the polycentric, jurisdictionally heterogeneous body of AI, generative-AI, algorithmic, and digital-technology law operating across the Asia-Pacific region between 2023 and 2026, comprising statutory regimes, administrative measures, soft-law guidance, supervisory ..."@en ;
rdfs:label "Asia Pacific Regulation"@en ;
rdfs:subClassOf ngm:ai-governance ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:cross-border-ai-law ;
rdfs:subClassOf ngm:digital-technology-policy ;
rdfs:subClassOf ngm:regional-ai-regulation ;
rdfs:subClassOf ngm:regulatory-framework ;
rdfs:subClassOf _:r1928 ;
rdfs:subClassOf _:r1929 ;
rdfs:subClassOf _:r1930 ;
rdfs:subClassOf _:r1931 ;
rdfs:subClassOf _:r1932 ;
rdfs:subClassOf _:r1933 ;
rdfs:subClassOf _:r1934 ;
rdfs:subClassOf _:r1935 ;
rdfs:subClassOf _:r1936 ;
rdfs:subClassOf _:r1937 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:contrastsWith ngm:brazil-ai-bill-pl-2338 ;
vc:contrastsWith ngm:canada-aida ;
vc:contrastsWith ngm:eu-ai-act-regulatory-instrument ;
vc:contrastsWith ngm:uk-ai-regulation-white-paper ;
vc:contrastsWith ngm:us-executive-action-on-ai ;
vc:dependsOn ngm:cyberspace-administration-of-china ;
vc:dependsOn ngm:department-of-industry-science-and-resources ;
vc:dependsOn ngm:imda ;
vc:dependsOn ngm:japan-ai-safety-institute ;
vc:dependsOn ngm:korea-ai-safety-institute ;
vc:dependsOn ngm:meity ;
vc:dependsOn ngm:office-of-the-privacy-commissioner-hong-kong ;
vc:dependsOn ngm:personal-information-protection-commission ;
vc:enables ngm:ai-safety-testing ;
vc:enables ngm:algorithmic-accountability ;
vc:enables ngm:compliance ;
vc:enables ngm:cross-border-ai-cooperation ;
vc:enables ngm:frontier-model-evaluation ;
vc:enables ngm:generative-ai-labelling ;
vc:enables ngm:risk-mitigation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ai-framework-act ;
vc:hasPart ngm:ai-governance-framework ;
vc:hasPart ngm:ai-verify ;
vc:hasPart ngm:asean-ai-governance-guide ;
vc:hasPart ngm:digital-personal-data-protection-act-2023 ;
vc:hasPart ngm:indiaai-mission ;
vc:hasPart ngm:interim-measures-for-generative-ai-services ;
vc:hasPart ngm:meti-ai-guidelines-for-business ;
vc:hasPart ngm:pcpd-ai-model-personal-data-protection-framework ;
vc:hasPart ngm:safety-standard ;
vc:implements ngm:bletchley-declaration ;
vc:implements ngm:frontier-ai-safety-commitments ;
vc:implements ngm:g20-ai-principles ;
vc:implements ngm:hiroshima-ai-process ;
vc:implements ngm:oecd-ai-principles ;
vc:implements ngm:seoul-declaration ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:ai-safety-institute ;
vc:relatedTo ngm:cross-border-data-transfer ;
vc:relatedTo ngm:data-security ;
vc:relatedTo ngm:export-controls ;
vc:relatedTo ngm:gdpr ;
vc:relatedTo ngm:hiroshima-ai-process ;
vc:relatedTo ngm:personal-information-protection-law ;
vc:requires ngm:algorithm-filing ;
vc:requires ngm:content-labelling ;
vc:requires ngm:data-localisation ;
vc:requires ngm:human-oversight ;
vc:requires ngm:personal-information-protection-law ;
vc:requires ngm:risk-management ;
vc:requires ngm:security-audit ;
vc:requires ngm:transparency-obligation ;
vc:slug "asia-pacific-regulation" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:ai-verify-foundation ;
vc:standardizedBy ngm:asean-digital-ministers-meeting ;
vc:standardizedBy ngm:cyberspace-administration-of-china ;
vc:standardizedBy ngm:iso-iec-jtc1-sc42 ;
vc:standardizedBy ngm:meti ;
vc:standardizedBy ngm:national-science-and-technology-council-taiwan ;
vc:standardizedBy ngm:personal-information-protection-commission ;
vc:supports ngm:ai-safety-summit ;
vc:supports ngm:algorithmic-transparency ;
vc:supports ngm:cross-border-data-transfer ;
vc:supports ngm:foundation-model-governance ;
vc:supports ngm:hiroshima-ai-process ;
vc:supports ngm:international-ai-safety-report ;
vc:uses ngm:ai-model-card ;
vc:uses ngm:algorithm-registry ;
vc:uses ngm:model-cards ;
vc:uses ngm:regulatory-sandbox ;
vc:uses ngm:risk-assessment ;
vc:uses ngm:self-regulatory-organisation ;
vc:uses ngm:standard-contractual-clauses ;
vc:uses ngm:watermarking-service .
ngm:asic a owl:Class ;
rdfs:comment "An Application-Specific Integrated Circuit (ASIC) is a custom integrated circuit designed and fabricated at the transistor and mask level to perform a specific function or narrow set of functions with maximum efficiency, in contrast to general-purpose processors such as CPUs and GPUs that are optimised for programmable flexibility. ASICs achieve superior performance-per-watt and cost efficiency at production volume by eliminating logic not required for the target workload, at the expense of reconfigurability. Design is conducted using hardware description languages (VHDL, SystemVerilog), electronic design automation suites, and a foundry-specific tape-out flow; non-recurring engineering costs at advanced nodes (5nm, 3nm) can exceed tens of millions of pounds, making economic viability contingent on volume or uniquely demanding performance requirements. ASICs are central to cryptocurrency mining, AI inference and training acceleration, high-speed networking switch fabric, signal processing, and consumer electronics where power, cost, and performance constraints demand purpose-built silicon."@en ;
rdfs:label "ASIC"@en ;
rdfs:subClassOf ngm:hardware ;
rdfs:subClassOf _:r900 ;
rdfs:subClassOf _:r901 ;
rdfs:subClassOf _:r902 ;
rdfs:subClassOf _:r903 ;
vc:bridgesTo ngm:ai-accelerator ;
vc:bridgesTo ngm:proof-of-work ;
vc:contrastsWith ngm:central-processing-unit ;
vc:contrastsWith ngm:fpga ;
vc:contrastsWith ngm:gpu-compute ;
vc:dependsOn ngm:cmos-process ;
vc:dependsOn ngm:supply-chain-management ;
vc:enables ngm:bitcoin-proof-of-work-protocol-mining ;
vc:enables ngm:hardware-acceleration ;
vc:enables ngm:high-speed-networking ;
vc:enables ngm:inference-hardware ;
vc:enables ngm:neural-processing-unit ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:physical-layout ;
vc:hasPart ngm:register-transfer-level ;
vc:hasPart ngm:standard-cell-library ;
vc:implements ngm:cryptographic-hash-function ;
vc:implements ngm:matrix-multiplication ;
vc:isPartOf ngm:semiconductor-industry ;
vc:isPartOf ngm:system-on-chip ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:embedded-systems ;
vc:relatedTo ngm:hardware-component ;
vc:relatedTo ngm:node-shrink ;
vc:relatedTo ngm:tape-out ;
vc:requires ngm:electronic-design-automation ;
vc:requires ngm:foundry ;
vc:requires ngm:hardware-description-language ;
vc:slug "asic" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:advanced-packaging ;
vc:uses ngm:chiplet-architecture .
ngm:asic-e-waste a skos:Concept ;
rdfs:label "Asic E Waste"@en .
ngm:asic-hardware a owl:Class ;
rdfs:comment "Application-Specific Integrated Circuits (ASICs) are custom silicon chips designed and manufactured to perform a fixed, narrowly defined computational task with maximum efficiency. Unlike general-purpose processors, ASIC hardware sacrifices programmability for dramatically superior performance-per-watt ratios in its target workload, making it the dominant substrate for high-throughput, power-sensitive deployments."@en ;
rdfs:label "ASIC Hardware"@en ;
rdfs:subClassOf ngm:computer-hardware ;
vc:contrastsWith ngm:fpga ;
vc:enables ngm:digital-signal-processing ;
vc:enables ngm:neural-processing-unit ;
vc:enables ngm:parallel-processing ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:embedded-systems ;
vc:slug "asic-hardware" ;
vc:sourceDomain "infrastructure" .
ngm:asic-manufacturer a skos:Concept ;
rdfs:label "Asic Manufacturer"@en .
ngm:asic-manufacturer-duopoly a skos:Concept ;
rdfs:label "Asic Manufacturer Duopoly"@en .
ngm:asic-mining a skos:Concept ;
rdfs:label "Asic Mining"@en .
ngm:asil-automotive-safety-integrity-level a skos:Concept ;
rdfs:label "Asil Automotive Safety Integrity Level"@en .
ngm:ask-side a skos:Concept ;
rdfs:label "Ask Side"@en .
ngm:aspect-based-sentiment-analysis a skos:Concept ;
rdfs:label "Aspect Based Sentiment Analysis"@en .
ngm:aspiration-level a skos:Concept ;
rdfs:label "Aspiration Level"@en .
ngm:assay-certificate a skos:Concept ;
rdfs:label "Assay Certificate"@en .
ngm:assembly-automation a owl:Class ;
rdfs:comment "Assembly automation is the use of robotic manipulators to perform repetitive joining, fastening, insertion or fitting operations that combine discrete parts into a finished product on a production line. It depends on precise manipulation and often force or vision feedback to handle part tolerances and orientation. It is one of the earliest and most economically significant applications of industrial robot manipulators."@en ;
rdfs:label "Assembly Automation"@en ;
rdfs:subClassOf ngm:manipulation ;
rdfs:subClassOf _:r1938 ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.55"^^xsd:float ;
vc:requires ngm:manipulation ;
vc:slug "assembly-automation" ;
vc:sourceDomain "robotics" ;
vc:uses ngm:manipulator .
ngm:assembly-operations a skos:Concept ;
rdfs:label "Assembly Operations"@en .
ngm:assemblyai a skos:Concept ;
rdfs:label "Assemblyai"@en .
ngm:assertive-marker a skos:Concept ;
rdfs:label "Assertive Marker"@en .
ngm:assessment-dimension a skos:Concept ;
rdfs:label "Assessment Dimension"@en .
ngm:assessment-framework a skos:Concept ;
rdfs:label "Assessment Framework"@en .
ngm:assessment-integrity a skos:Concept ;
rdfs:label "Assessment Integrity"@en .
ngm:assessment-methodology a skos:Concept ;
rdfs:label "Assessment Methodology"@en .
ngm:assessment-system a skos:Concept ;
rdfs:label "Assessment System"@en .
ngm:asset-allocation a skos:Concept ;
rdfs:label "Asset Allocation"@en .
ngm:asset-archive a owl:Class ;
rdfs:comment "Asset Archive is a digital repository system for long-term storage, management, and preservation of 3D models, textures, animations, and other virtual world components, incorporating provenance tracking, version control, and standardized formats to ensure accessibility and interoperability across..."@en ;
rdfs:label "Asset Archive"@en ;
rdfs:subClassOf ngm:digital-repository ;
rdfs:subClassOf ngm:sc-content-and-assets ;
rdfs:subClassOf _:r1939 ;
rdfs:subClassOf _:r1940 ;
rdfs:subClassOf _:r1941 ;
skos:broader ngm:sc-content-and-assets ;
vc:bridgesTo ngm:computer-vision ;
vc:enables ngm:asset-preservation ;
vc:enables ngm:content-reuse ;
vc:enables ngm:cross-platform-interoperability ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:metadata-management ;
vc:requires ngm:standardized-formats ;
vc:requires ngm:storage-infrastructure ;
vc:slug "asset-archive" ;
vc:sourceDomain "spatial-computing" .
ngm:asset-authentication a skos:Concept ;
rdfs:label "Asset Authentication"@en .
ngm:asset-authenticity a skos:Concept ;
rdfs:label "Asset Authenticity"@en .
ngm:asset-bridging a skos:Concept ;
rdfs:label "Asset Bridging"@en .
ngm:asset-browsing a skos:Concept ;
rdfs:label "Asset Browsing"@en .
ngm:asset-catalog a skos:Concept ;
rdfs:label "Asset Catalog"@en .
ngm:asset-compression a skos:Concept ;
rdfs:label "Asset Compression"@en .
ngm:asset-continuity a skos:Concept ;
rdfs:label "Asset Continuity"@en .
ngm:asset-creation a owl:Class ;
rdfs:comment "Asset Creation is the structured practice of producing digital or physical resources — including geometry, textures, audio, code, and data — intended for use within interactive experiences, virtual environments, or production pipelines. It encompasses the full authoring lifecycle from concept through final deliverable, applying artistic, technical, and automated methods to yield artefacts that meet quality, format, and performance requirements."@en ;
rdfs:label "Asset Creation"@en ;
rdfs:subClassOf ngm:content-creation ;
rdfs:subClassOf _:r1942 ;
rdfs:subClassOf _:r1943 ;
vc:enables ngm:asset-pipeline ;
vc:enables ngm:digital-content-creation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:3-d-animation ;
vc:hasPart ngm:3d-modelling ;
vc:qualityScore "0.8"^^xsd:float ;
vc:slug "asset-creation" ;
vc:sourceDomain "metaverse" ;
vc:uses ngm:game-engine ;
vc:uses ngm:procedural-content-generation .
ngm:asset-database a owl:Class ;
rdfs:comment "An Asset Database is a structured, queryable repository that stores descriptive records, binary references, version histories, and relational metadata for digital assets within a production or distribution system. It provides the persistent backbone enabling discovery, retrieval, provenance tracking, and lifecycle management of assets across teams and pipelines."@en ;
rdfs:label "Asset Database"@en ;
rdfs:subClassOf ngm:database-system ;
rdfs:subClassOf _:r1944 ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:metadata ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:knowledge-graph ;
vc:slug "asset-database" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:asset-management-system ;
vc:supports ngm:digital-asset-management ;
vc:uses ngm:metadata-schema ;
vc:uses ngm:search-engine .
ngm:asset-digitization a owl:Class ;
rdfs:comment "Asset Digitization is the process of converting physical objects, spaces, documents, or analogue media into discrete digital representations suitable for storage, transmission, and computational use. It encompasses acquisition technologies such as scanning, photogrammetry, and LiDAR, as well as the post-processing steps that clean, structure, and format the resulting data for target applications."@en ;
rdfs:label "Asset Digitization"@en ;
rdfs:subClassOf ngm:reality-capture ;
vc:enables ngm:3-d-asset ;
vc:enables ngm:cultural-heritage-preservation ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:digital-asset-management ;
vc:slug "asset-digitization" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:lidar-scanning ;
vc:uses ngm:photogrammetry ;
vc:uses ngm:point-cloud-processing .
ngm:asset-discovery a skos:Concept ;
rdfs:label "Asset Discovery"@en .
ngm:asset-exchange a skos:Concept ;
rdfs:label "Asset Exchange"@en .
ngm:asset-format-standards a owl:Class ;
rdfs:comment "Asset Format Standards are technical specifications defining file formats, data structures, and interchange protocols for 3D models, textures, animations, and scene descriptions, enabling interoperability between content creation tools, game engines, and metaverse platforms through standards like..."@en ;
rdfs:label "Asset Format Standards"@en ;
rdfs:subClassOf ngm:sc-standards-and-interop ;
rdfs:subClassOf ngm:technical-standards ;
rdfs:subClassOf _:r1945 ;
skos:broader ngm:sc-standards-and-interop ;
vc:bridgesTo ngm:computer-vision ;
vc:enables ngm:content-portability ;
vc:enables ngm:cross-platform-assets ;
vc:enables ngm:tool-interoperability ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:conversion-tools ;
vc:requires ngm:format-compliance ;
vc:requires ngm:validation-systems ;
vc:slug "asset-format-standards" ;
vc:sourceDomain "spatial-computing" .
ngm:asset-generation a skos:Concept ;
rdfs:label "Asset Generation"@en .
ngm:asset-group-key a skos:Concept ;
rdfs:label "Asset Group Key"@en .
ngm:asset-interchange a skos:Concept ;
rdfs:label "Asset Interchange"@en .
ngm:asset-interchange-system a skos:Concept ;
rdfs:label "Asset Interchange System"@en .
ngm:asset-interoperability a owl:Class ;
rdfs:comment "Asset Interoperability is the technical capacity for digital assets — including 3D models, avatars, NFTs, in-game items, and financial instruments — to function, be recognised, and retain their properties across multiple distinct platforms, ecosystems, or blockchains without loss of fidelity or ownership provenance. It encompasses both syntactic compatibility (shared file formats and protocols) and semantic compatibility (consistent meaning of asset attributes across contexts). Achieving asset interoperability typically requires common standards bodies, bridge contracts, or cross-chain protocols that translate asset representations between heterogeneous systems. It is a foundational concern for open metaverse architectures, decentralised finance, and multi-chain gaming economies."@en ;
rdfs:label "Asset Interoperability"@en ;
rdfs:subClassOf ngm:interoperability ;
rdfs:subClassOf _:r1946 ;
rdfs:subClassOf _:r1947 ;
vc:bridgesTo ngm:de-fi ;
vc:bridgesTo ngm:spatial-computing ;
vc:contrastsWith ngm:vendor-lock-in ;
vc:contrastsWith ngm:walled-garden ;
vc:dependsOn ngm:data-format-standard ;
vc:dependsOn ngm:decentralised-identity ;
vc:dependsOn ngm:provenance-tracking ;
vc:dependsOn ngm:smart-contract ;
vc:enables ngm:blockchain-gaming ;
vc:enables ngm:digital-asset-ecosystem ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:erc-1155 ;
vc:implements ngm:erc-721-standard ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:avatar-interoperability ;
vc:relatedTo ngm:blockchain-interoperability ;
vc:relatedTo ngm:cross-chain-interoperability ;
vc:relatedTo ngm:digital-twin ;
vc:relatedTo ngm:interoperability-standard ;
vc:relatedTo ngm:open-metaverse ;
vc:requires ngm:metadata-schema ;
vc:requires ngm:ontology-alignment ;
vc:slug "asset-interoperability" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:khronos-group ;
vc:standardizedBy ngm:metaverse-standards-forum ;
vc:standardizedBy ngm:open-metaverse-interoperability-group ;
vc:uses ngm:bridge-contract ;
vc:uses ngm:digital-asset-standards ;
vc:uses ngm:gltf-standard ;
vc:uses ngm:interoperability-protocol ;
vc:uses ngm:wrapped-token .
ngm:asset-inventory a owl:Class ;
rdfs:comment "Asset Inventory is the systematic, continuously maintained catalogue of all hardware, software, data stores, network devices and cloud resources within an organisation's environment. It establishes the authoritative record of what must be protected, forming the foundation for vulnerability management, configuration control and incident response. An accurate inventory enables defenders to scope attack surfaces, prioritise patching and detect unauthorised or rogue assets."@en ;
rdfs:label "Asset Inventory"@en ;
rdfs:subClassOf ngm:vulnerability-management ;
rdfs:subClassOf _:r1948 ;
rdfs:subClassOf _:r1949 ;
vc:bridgesTo ngm:cybersecurity ;
vc:contrastsWith ngm:threat-intelligence ;
vc:dependsOn ngm:monitoring ;
vc:enables ngm:incident-response ;
vc:enables ngm:threat-intelligence ;
vc:enables ngm:vulnerability-management ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:vulnerability-management ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:configuration-management ;
vc:relatedTo ngm:network-security ;
vc:relatedTo ngm:vulnerability ;
vc:requires ngm:configuration-management ;
vc:requires ngm:monitoring ;
vc:slug "asset-inventory" ;
vc:sourceDomain "security" ;
vc:supports ngm:cybersecurity ;
vc:supports ngm:threat-model ;
vc:uses ngm:monitoring .
ngm:asset-issuance a skos:Concept ;
rdfs:label "Asset Issuance"@en .
ngm:asset-libraries a skos:Concept ;
rdfs:label "Asset Libraries"@en .
ngm:asset-life-extension a skos:Concept ;
rdfs:label "Asset Life Extension"@en .
ngm:asset-lifecycle-management a skos:Concept ;
rdfs:label "Asset Lifecycle Management"@en .
ngm:asset-liquidity a owl:Class ;
rdfs:comment "Asset Liquidity is the degree to which a digital or tokenised asset can be converted into cash or another asset at close to its fair market value without materially moving that price or incurring prohibitive friction. In decentralised finance and tokenised asset markets, liquidity is determined by order-book depth, automated market maker reserves, and the breadth of platforms on which an asset can be traded."@en ;
rdfs:label "Asset Liquidity"@en ;
rdfs:subClassOf ngm:de-fi ;
vc:enables ngm:atomic-swap ;
vc:enables ngm:nft-marketplace ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:blockchain-economics ;
vc:relatedTo ngm:digital-ownership ;
vc:slug "asset-liquidity" ;
vc:sourceDomain "finance" ;
vc:uses ngm:exchange-mechanism ;
vc:uses ngm:liquidity-pool .
ngm:asset-management a owl:Class ;
rdfs:comment "The professional management of digital and traditional assets through strategies including portfolio construction, risk management, custody, and performance optimization. In the context of fintech and DeFi, asset management encompasses crypto portfolio management, tokenized securities, yield optimization, and institutional-grade custody solutions that enable investors to navigate volatile digital markets while maximizing risk-adjusted returns."@en ;
rdfs:label "Asset Management"@en ;
rdfs:subClassOf ngm:financial-services ;
rdfs:subClassOf _:r1956 ;
rdfs:subClassOf _:r1957 ;
rdfs:subClassOf _:r1958 ;
rdfs:subClassOf _:r1959 ;
rdfs:subClassOf _:r1960 ;
rdfs:subClassOf _:r1961 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:decentralized-finance-de-fi ;
vc:bridgesTo ngm:distributed-ledger-technology ;
vc:contrastsWith ngm:passive-investing ;
vc:contrastsWith ngm:self-custody ;
vc:dependsOn ngm:risk-management ;
vc:enables ngm:institutional-investment ;
vc:enables ngm:portfolio-management ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:custody ;
vc:hasPart ngm:performance ;
vc:hasPart ngm:portfolio-management ;
vc:hasPart ngm:risk-management ;
vc:isPartOf ngm:financial-services ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:decentralized-finance-de-fi ;
vc:relatedTo ngm:exchange-traded-fund ;
vc:relatedTo ngm:real-world-asset-tokenisation ;
vc:relatedTo ngm:tokenization ;
vc:requires ngm:custody ;
vc:requires ngm:regulatory-compliance ;
vc:slug "asset-management" ;
vc:sourceDomain "finance" ;
vc:standardizedBy ngm:financial-industry-regulatory-authority ;
vc:standardizedBy ngm:securities-and-exchange-commission ;
vc:supports ngm:decentralized-finance-de-fi ;
vc:supports ngm:institutional-investment ;
vc:uses ngm:custody ;
vc:uses ngm:risk-management ;
vc:uses ngm:smart-contracts ;
vc:uses ngm:tokenization .
ngm:asset-management-system a owl:Class ;
rdfs:comment "An Asset Management System (AMS) is an integrated software platform that tracks, manages, and optimises the lifecycle of physical, digital, or financial assets across an organisation. It consolidates asset data including acquisition, depreciation, maintenance, and disposal into a single governed repository. Modern AMS platforms enforce audit trails, automate compliance reporting, and feed into enterprise resource planning (ERP) and financial systems. They enable organisations to reduce total cost of ownership, mitigate risk, and demonstrate regulatory compliance."@en ;
rdfs:label "Asset Management System"@en ;
rdfs:subClassOf ngm:asset-management ;
rdfs:subClassOf _:r1950 ;
rdfs:subClassOf _:r1951 ;
rdfs:subClassOf _:r1952 ;
rdfs:subClassOf _:r1953 ;
rdfs:subClassOf _:r1954 ;
rdfs:subClassOf _:r1955 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:supply-chain-management ;
vc:dependsOn ngm:database-management-system ;
vc:dependsOn ngm:enterprise-resource-planning ;
vc:enables ngm:compliance-audit-trail ;
vc:enables ngm:compliance-monitoring ;
vc:enables ngm:predictive-maintenance ;
vc:enables ngm:quality-assurance ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:asset-registry ;
vc:hasPart ngm:digital-asset-management ;
vc:hasPart ngm:monitoring-system ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:financial-reporting ;
vc:requires ngm:audit-logging ;
vc:requires ngm:data-governance ;
vc:requires ngm:identity-and-access-management ;
vc:slug "asset-management-system" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:lifecycle-management ;
vc:supports ngm:regulatory-compliance ;
vc:uses ngm:iot-sensor ;
vc:uses ngm:rest-api .
ngm:asset-metadata a owl:Class ;
rdfs:comment "Asset Metadata is the structured descriptive, administrative, and technical information attached to a digital asset that contextualises it within a system without being the primary content of that asset. It encompasses identifiers, provenance records, format specifications, rights information, semantic tags, and dependency relationships, enabling discovery, validation, licensing, and lifecycle management."@en ;
rdfs:label "Asset Metadata"@en ;
rdfs:subClassOf ngm:metadata ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:knowledge-graph ;
vc:relatedTo ngm:ontology ;
vc:slug "asset-metadata" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:asset-management-system ;
vc:supports ngm:digital-asset-management ;
vc:uses ngm:metadata-schema ;
vc:uses ngm:metadata-standard .
ngm:asset-monetization a skos:Concept ;
rdfs:label "Asset Monetization"@en .
ngm:asset-movement a skos:Concept ;
rdfs:label "Asset Movement"@en .
ngm:asset-optimization a owl:Class ;
rdfs:comment "Asset Optimization is the systematic process of reducing the computational cost, memory footprint, and bandwidth consumption of digital assets while preserving their perceptual quality and functional correctness for target deployment environments. It applies techniques including polygon reduction, texture compression, audio resampling, and level-of-detail generation to ensure assets perform acceptably on constrained hardware."@en ;
rdfs:label "Asset Optimization"@en ;
rdfs:subClassOf ngm:optimisation ;
vc:enables ngm:gpu-acceleration ;
vc:enables ngm:performance-optimization ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:slug "asset-optimization" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:asset-pipeline ;
vc:supports ngm:game-engine ;
vc:uses ngm:level-of-detail ;
vc:uses ngm:rendering-pipeline .
ngm:asset-ownership a skos:Concept ;
rdfs:label "Asset Ownership"@en .
ngm:asset-persistence a skos:Concept ;
rdfs:label "Asset Persistence"@en .
ngm:asset-pipeline a owl:Class ;
rdfs:comment "An asset pipeline is an automated, staged workflow that ingests raw digital content—meshes, textures, audio, animations, and shaders—and transforms it through validation, processing, optimisation, and packaging steps into runtime-ready formats consumable by real-time engines, streaming platforms, or spatial computing environments. It enforces deterministic builds, enables version-controlled dependency graphs, and dramatically reduces manual content-preparation labour. Asset pipelines are foundational to game development, visual effects, and metaverse platform engineering, and increasingly incorporate AI-assisted level-of-detail generation, texture compression, and semantic tagging to scale content delivery across heterogeneous device targets."@en ;
rdfs:label "Asset Pipeline"@en ;
rdfs:subClassOf ngm:content-pipeline ;
rdfs:subClassOf _:r1962 ;
rdfs:subClassOf _:r1963 ;
rdfs:subClassOf _:r1964 ;
rdfs:subClassOf _:r1965 ;
rdfs:subClassOf _:r1966 ;
rdfs:subClassOf _:r1967 ;
rdfs:subClassOf _:r1968 ;
vc:bridgesTo ngm:content-generation ;
vc:bridgesTo ngm:supply-chain-provenance ;
vc:dependsOn ngm:continuous-integration ;
vc:dependsOn ngm:metadata-schema ;
vc:enables ngm:content-delivery ;
vc:enables ngm:digital-twin-creation ;
vc:enables ngm:extended-reality ;
vc:enables ngm:game-engine ;
vc:enables ngm:real-time-rendering ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:asset-management ;
vc:hasPart ngm:build-system ;
vc:hasPart ngm:level-of-detail ;
vc:hasPart ngm:render-pipeline ;
vc:hasPart ngm:texture-compression ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:asset-format-standards ;
vc:relatedTo ngm:procedural-generation ;
vc:relatedTo ngm:vfx-tools ;
vc:requires ngm:content-addressed-storage ;
vc:requires ngm:dependency-graph ;
vc:requires ngm:version-control ;
vc:slug "asset-pipeline" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:khronos-group ;
vc:standardizedBy ngm:open-usd ;
vc:supports ngm:creator-economy ;
vc:supports ngm:digital-rights-management ;
vc:uses ngm:3-d-asset ;
vc:uses ngm:3-d-file-format ;
vc:uses ngm:data-compression ;
vc:uses ngm:gltf-standard ;
vc:uses ngm:shader ;
vc:uses ngm:usd .
ngm:asset-portability a owl:Class ;
rdfs:comment "Asset portability is the technical and standards-based capability to transfer, import, and faithfully render digital assets — including 3D models, textures, avatars, animations, and environments — across different rendering engines, platforms, and virtual world applications without loss of fidelity or functionality. It depends on open file formats, agreed semantic conventions for material properties and skeletal rigs, and runtime interoperability layers. Asset portability is a prerequisite for platform-neutral digital property ownership in the open metaverse, enabling creators and users to carry value across application boundaries. It intersects with data portability principles in broader digital-rights discourse and with blockchain-based ownership for non-fungible digital items."@en ;
rdfs:label "Asset Portability"@en ;
rdfs:subClassOf ngm:sc-content-and-assets ;
rdfs:subClassOf _:r1969 ;
rdfs:subClassOf _:r1970 ;
rdfs:subClassOf _:r1971 ;
rdfs:subClassOf _:r1972 ;
skos:broader ngm:sc-content-and-assets ;
vc:bridgesTo ngm:data-portability ;
vc:bridgesTo ngm:decentralised-identity ;
vc:bridgesTo ngm:non-fungible-token ;
vc:contrastsWith ngm:proprietary-format ;
vc:contrastsWith ngm:vendor-lock-in ;
vc:dependsOn ngm:gltf-standard ;
vc:dependsOn ngm:runtime-api ;
vc:dependsOn ngm:usd ;
vc:enables ngm:avatar-portability ;
vc:enables ngm:cross-platform-interoperability ;
vc:enables ngm:digital-property-rights ;
vc:enables ngm:open-metaverse ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:3-d-asset-standard ;
vc:relatedTo ngm:content-pipeline ;
vc:relatedTo ngm:scene-graph ;
vc:requires ngm:3-d-file-format ;
vc:requires ngm:interoperability ;
vc:requires ngm:open-standard ;
vc:requires ngm:physically-based-rendering ;
vc:slug "asset-portability" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:alliance-for-openusd ;
vc:standardizedBy ngm:khronos-group ;
vc:standardizedBy ngm:metaverse-standards-forum ;
vc:supports ngm:digital-twin ;
vc:supports ngm:extended-reality ;
vc:supports ngm:spatial-computing ;
vc:uses ngm:open-xr ;
vc:uses ngm:vrm-format ;
vc:uses ngm:web-xr .
ngm:asset-preservation a skos:Concept ;
rdfs:label "Asset Preservation"@en .
ngm:asset-recovery a owl:Class ;
rdfs:comment "Asset recovery is the process of identifying, tracing, freezing, and ultimately returning funds or property obtained through fraud, corruption, money laundering, or other financial crime. It combines financial investigation, legal action, and cross-border cooperation to follow illicit value through layered transactions and recover it for victims or the state. In the digital era it increasingly relies on blockchain analytics to trace cryptocurrency proceeds."@en ;
rdfs:label "Asset Recovery"@en ;
rdfs:subClassOf ngm:aml ;
rdfs:subClassOf _:r1973 ;
rdfs:subClassOf _:r1974 ;
vc:bridgesTo ngm:cryptocurrency ;
vc:dependsOn ngm:traceability ;
vc:enables ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:aml ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:aml ;
vc:relatedTo ngm:finance ;
vc:relatedTo ngm:financial-services ;
vc:relatedTo ngm:risk-management ;
vc:requires ngm:audit ;
vc:requires ngm:kyc ;
vc:slug "asset-recovery" ;
vc:sourceDomain "finance" ;
vc:supports ngm:compliance ;
vc:supports ngm:governance ;
vc:uses ngm:blockchain-analytics ;
vc:uses ngm:fraud-detection .
ngm:asset-referenced-token a skos:Concept ;
rdfs:label "Asset Referenced Token"@en .
ngm:asset-registry a owl:Class ;
rdfs:comment "An Asset Registry is a cryptographically-secured, on-chain or hybrid on/off-chain system for recording, authenticating, and transferring legal ownership rights and provenance metadata for real-world or digital assets, implemented through Smart Contracts, Distributed Ledger infrastruct..."@en ;
rdfs:label "Asset Registry"@en ;
rdfs:subClassOf ngm:bc-token-and-asset ;
rdfs:subClassOf ngm:blockchain-application ;
rdfs:subClassOf ngm:distributed-ledger ;
rdfs:subClassOf ngm:financial-infrastructure ;
rdfs:subClassOf ngm:ownership-system ;
rdfs:subClassOf _:r1975 ;
rdfs:subClassOf _:r1976 ;
rdfs:subClassOf _:r1977 ;
rdfs:subClassOf _:r1978 ;
rdfs:subClassOf _:r1979 ;
rdfs:subClassOf _:r1980 ;
rdfs:subClassOf _:r1981 ;
rdfs:subClassOf _:r1982 ;
rdfs:subClassOf _:r1983 ;
rdfs:subClassOf _:r1984 ;
rdfs:subClassOf _:r1985 ;
rdfs:subClassOf _:r1986 ;
rdfs:subClassOf _:r1987 ;
skos:broader ngm:bc-token-and-asset ;
vc:contrastsWith ngm:centralised-database ;
vc:contrastsWith ngm:paper-based-land-registry ;
vc:contrastsWith ngm:traditional-title-systems ;
vc:dependsOn ngm:blockchain-network ;
vc:dependsOn ngm:cryptography-security-and-privacy ;
vc:dependsOn ngm:distributed-identity ;
vc:dependsOn ngm:hash-function ;
vc:dependsOn ngm:smart-contract ;
vc:enables ngm:automated-compliance ;
vc:enables ngm:cross-border-settlement ;
vc:enables ngm:fractional-ownership ;
vc:enables ngm:provenance-tracking ;
vc:enables ngm:real-world-asset-tokenisation ;
vc:enables ngm:secondary-market-liquidity ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:access-control-system ;
vc:hasPart ngm:asset-tokenisation ;
vc:hasPart ngm:compliance-monitoring ;
vc:hasPart ngm:digital-identity-wallet ;
vc:hasPart ngm:digital-signature ;
vc:hasPart ngm:merkle-tree ;
vc:hasPart ngm:smart-contract ;
vc:implements ngm:aml-kyc-compliance ;
vc:implements ngm:distributed-identity ;
vc:implements ngm:enterprise-token-standards ;
vc:implements ngm:erc3643-standard ;
vc:implements ngm:esg-reporting ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:asset-tokenisation ;
vc:relatedTo ngm:blockchain-interoperability ;
vc:relatedTo ngm:carbon-credit-tracking ;
vc:relatedTo ngm:cbdcs ;
vc:relatedTo ngm:enterprise-token-standards ;
vc:relatedTo ngm:ethical-sourcing ;
vc:requires ngm:cryptography-security-and-privacy ;
vc:requires ngm:digital-identity-wallet ;
vc:requires ngm:digital-signature ;
vc:requires ngm:distributed-ledger ;
vc:requires ngm:identity-verification ;
vc:requires ngm:smart-contract ;
vc:slug "asset-registry" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:erc3643-standard ;
vc:standardizedBy ngm:hyperledger-indy ;
vc:standardizedBy ngm:iso-24165 ;
vc:standardizedBy ngm:polymesh-protocol ;
vc:standardizedBy ngm:token-standard ;
vc:supports ngm:carbon-credit-tracking ;
vc:supports ngm:de-fi ;
vc:supports ngm:real-estate-registry ;
vc:supports ngm:securities-settlement ;
vc:supports ngm:supply-chain-tracking ;
vc:uses ngm:access-control-system ;
vc:uses ngm:digital-signature ;
vc:uses ngm:enterprise-smart-contracts ;
vc:uses ngm:graph-database ;
vc:uses ngm:hash-function .
ngm:asset-resolution a skos:Concept ;
rdfs:label "Asset Resolution"@en .
ngm:asset-service a owl:Class ;
rdfs:comment "An Asset Service is a runtime or backend system that exposes digital assets and their associated metadata to consuming applications through well-defined APIs, handling storage, retrieval, transcoding, access control, and lifecycle operations as managed infrastructure. It abstracts the complexity of distributed storage and processing from client applications, enabling consistent, scalable access to asset libraries."@en ;
rdfs:label "Asset Service"@en ;
rdfs:subClassOf ngm:service-layer ;
vc:enables ngm:microservices-architecture ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:platform-service ;
vc:slug "asset-service" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:asset-management-system ;
vc:supports ngm:content-pipeline ;
vc:uses ngm:api-management ;
vc:uses ngm:digital-asset-management .
ngm:asset-synthesizer a skos:Concept ;
rdfs:label "Asset Synthesizer"@en .
ngm:asset-tokenisation a owl:Class ;
rdfs:comment "Asset tokenisation is the process of representing ownership, revenue rights, or access rights in a real-world or digital asset as a cryptographically secured blockchain token governed by a smart contract. The token encodes legally binding claims — to real estate, private equity, bonds, commodities, or intellectual property — while embedding compliance logic such as KYC whitelisting and transfer restrictions directly on-chain. Tokenisation enables fractional ownership, continuous secondary trading, and automated settlement without traditional intermediaries, sitting at the convergence of securities regulation, distributed ledger infrastructure, and programmable finance."@en ;
rdfs:label "Asset Tokenisation"@en ;
rdfs:subClassOf ngm:digital-asset ;
rdfs:subClassOf _:r1988 ;
rdfs:subClassOf _:r1989 ;
rdfs:subClassOf _:r1990 ;
rdfs:subClassOf _:r1991 ;
vc:bridgesTo ngm:artificial-intelligence-in-finance ;
vc:bridgesTo ngm:decentralised-autonomous-organisation ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:real-estate ;
vc:bridgesTo ngm:supply-chain-finance ;
vc:contrastsWith ngm:central-bank-digital-currency-cbdc ;
vc:contrastsWith ngm:fiat-currency ;
vc:contrastsWith ngm:traditional-securities ;
vc:dependsOn ngm:blockchain ;
vc:dependsOn ngm:consensus-mechanism ;
vc:dependsOn ngm:cryptographic-hash-function ;
vc:dependsOn ngm:cryptographic-infrastructure ;
vc:dependsOn ngm:oracle ;
vc:enables ngm:automated-market-maker ;
vc:enables ngm:de-fi ;
vc:enables ngm:fractional-ownership ;
vc:enables ngm:liquidity ;
vc:enables ngm:programmable-money ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:aml ;
vc:relatedTo ngm:decentralised-exchange ;
vc:relatedTo ngm:real-world-asset-tokenisation ;
vc:relatedTo ngm:special-purpose-vehicle ;
vc:relatedTo ngm:stablecoin ;
vc:requires ngm:custody ;
vc:requires ngm:digital-identity ;
vc:requires ngm:kyc ;
vc:requires ngm:regulatory-compliance ;
vc:slug "asset-tokenisation" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:erc-1400 ;
vc:standardizedBy ngm:erc-20-token-standard ;
vc:standardizedBy ngm:erc-721-standard ;
vc:standardizedBy ngm:financial-action-task-force ;
vc:standardizedBy ngm:international-organisation-of-securities-commissions ;
vc:uses ngm:digital-wallet ;
vc:uses ngm:distributed-ledger-technology ;
vc:uses ngm:non-fungible-token ;
vc:uses ngm:smart-contracts ;
vc:uses ngm:token-standard .
ngm:asset-tracking a owl:Class ;
rdfs:comment "Asset tracking is the continuous identification and localisation of physical objects, such as inventory, equipment, and vehicles, across their lifecycle and movement. It combines identification technologies like RFID and BLE beacons with positioning systems and connectivity to give organisations real-time visibility of where assets are and in what condition. Asset tracking underpins supply-chain transparency, loss prevention, and operational efficiency."@en ;
rdfs:label "Asset Tracking"@en ;
rdfs:subClassOf ngm:internet-of-things ;
rdfs:subClassOf _:r1992 ;
rdfs:subClassOf _:r1993 ;
rdfs:subClassOf _:r1994 ;
vc:bridgesTo ngm:mesh-networking ;
vc:dependsOn ngm:internet-of-things ;
vc:enables ngm:inventory-management ;
vc:enables ngm:logistics ;
vc:enables ngm:supply-chain-visibility ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:bluetooth-low-energy ;
vc:hasPart ngm:rfid ;
vc:isPartOf ngm:internet-of-things ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:gps ;
vc:relatedTo ngm:inventory-management ;
vc:relatedTo ngm:supply-chain-visibility ;
vc:requires ngm:sensor ;
vc:slug "asset-tracking" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:logistics ;
vc:uses ngm:bluetooth-low-energy ;
vc:uses ngm:gps ;
vc:uses ngm:rfid .
ngm:asset-trading a owl:Class ;
rdfs:comment "The exchange of digital and traditional financial assets through centralized exchanges (CEXs), decentralized exchanges (DEXs), and hybrid platforms."@en ;
rdfs:label "Asset Trading"@en ;
rdfs:subClassOf ngm:bc-defi-and-economics ;
rdfs:subClassOf ngm:financial-services ;
skos:broader ngm:bc-defi-and-economics ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:financial-services ;
vc:enables ngm:decentralized-exchange ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:asset-management ;
vc:relatedTo ngm:market-making ;
vc:slug "asset-trading" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:price-discovery ;
vc:uses ngm:liquidity-pool ;
vc:uses ngm:smart-contract .
ngm:asset-transfer a owl:Class ;
rdfs:comment "Asset transfer is the act of moving ownership or control of a digital asset from one party or address to another, recorded as a state change on a ledger. It is the basic operation that custody arrangements must secure and that digital-ownership systems rely on to change the recorded holder of a token or asset. Cross-chain and tokenised real-world-asset transfer are specialised forms that move value across ledgers or between on-chain and off-chain representations."@en ;
rdfs:label "Asset Transfer"@en ;
rdfs:subClassOf ngm:custody ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "asset-transfer" ;
vc:sourceDomain "blockchain" .
ngm:asset-translation-layer a skos:Concept ;
rdfs:label "Asset Translation Layer"@en .
ngm:asset-utilization a skos:Concept ;
rdfs:label "Asset Utilization"@en .
ngm:asset-validation a skos:Concept ;
rdfs:label "Asset Validation"@en .
ngm:asset-valuation a skos:Concept ;
rdfs:label "Asset Valuation"@en .
ngm:asset-witness-proof a skos:Concept ;
rdfs:label "Asset Witness Proof"@en .
ngm:assignment-client a skos:Concept ;
rdfs:label "Assignment Client"@en .
ngm:assignment-client-architecture a skos:Concept ;
rdfs:label "Assignment Client Architecture"@en .
ngm:assimilation a owl:Class ;
rdfs:label "Assimilation"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-processing ;
vc:slug "assimilation" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:assist-voice-pipeline a skos:Concept ;
rdfs:label "Assist Voice Pipeline"@en .
ngm:assistive-robotics a owl:Class ;
rdfs:comment "Assistive Robotics is a branch of robotics concerned with designing, building, and deploying robotic systems that augment, restore, or substitute impaired human physical and cognitive functions for people with disabilities, age-related decline, or rehabilitation needs. Systems span powered exoskeletons for gait restoration, robotic prostheses with sensorimotor feedback, autonomous mobility aids, and socially interactive companion robots that provide cognitive and emotional support. Operating in close physical proximity to humans, these devices must satisfy stringent requirements for safety, transparency, and user control while integrating sensing, AI-driven intent inference, and adaptive interfaces that respond to changing physiological states."@en ;
rdfs:label "Assistive Robotics"@en ;
rdfs:subClassOf ngm:robotic-system ;
rdfs:subClassOf _:r1995 ;
rdfs:subClassOf _:r1996 ;
rdfs:subClassOf _:r1997 ;
rdfs:subClassOf _:r1998 ;
rdfs:subClassOf _:r1999 ;
rdfs:subClassOf _:r2000 ;
vc:bridgesTo ngm:affective-computing ;
vc:bridgesTo ngm:ai-companions ;
vc:contrastsWith ngm:industrial-robotics ;
vc:dependsOn ngm:battery-management-system ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:real-time-control ;
vc:enables ngm:accessibility ;
vc:enables ngm:independent-living ;
vc:enables ngm:motor-rehabilitation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:exoskeleton-robot ;
vc:hasPart ngm:robotic-prosthesis ;
vc:hasPart ngm:social-robotics ;
vc:isPartOf ngm:rehabilitation-engineering ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:compliant-actuation ;
vc:relatedTo ngm:neuroprosthetics ;
vc:relatedTo ngm:wearable-robotics ;
vc:requires ngm:actuator ;
vc:requires ngm:embedded-systems ;
vc:requires ngm:human-robot-interaction ;
vc:requires ngm:sensor-fusion ;
vc:slug "assistive-robotics" ;
vc:sourceDomain "robotics" ;
vc:standardizedBy ngm:iso-13482 ;
vc:standardizedBy ngm:medical-device-regulation ;
vc:supports ngm:disability-inclusion ;
vc:supports ngm:elderly-care ;
vc:uses ngm:brain-computer-interfaces ;
vc:uses ngm:electromyography ;
vc:uses ngm:lower-limb-exoskeleton ;
vc:uses ngm:natural-language-processing .
ngm:assistive-technology a owl:Class ;
rdfs:comment "Assistive technology is equipment or software that helps people with disabilities perform tasks they would otherwise find difficult. Examples include screen readers, hearing aids and alternative input devices."@en ;
rdfs:label "Assistive Technology"@en ;
rdfs:subClassOf ngm:accessibility ;
vc:bridgesTo ngm:accessibility ;
vc:enables ngm:education ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:slug "assistive-technology" ;
vc:sourceDomain "standards" .
ngm:assistive-technology-ecosystem a skos:Concept ;
rdfs:label "Assistive Technology Ecosystem"@en .
ngm:assistive-technology-integration a owl:Class ;
rdfs:comment "Assistive Technology Integration is the practice of embedding tools, software, and hardware designed to support people with disabilities into digital systems, applications, and physical environments so that those individuals can access and interact with technology equitably. It encompasses screen readers, alternative input devices, augmentative communication systems, and adaptive interfaces, requiring compliance with accessibility standards and universal design principles. Effective integration ensures that assistive technologies interoperate seamlessly with underlying platforms rather than operating as bolt-on afterthoughts. The discipline spans hardware-software co-design, API compatibility, and user-centred testing with disabled communities."@en ;
rdfs:label "Assistive Technology Integration"@en ;
rdfs:subClassOf ngm:accessibility ;
rdfs:subClassOf ngm:inclusive-design ;
rdfs:subClassOf ngm:universal-design ;
rdfs:subClassOf _:r2001 ;
rdfs:subClassOf _:r2002 ;
rdfs:subClassOf _:r2003 ;
rdfs:subClassOf _:r2004 ;
rdfs:subClassOf _:r2005 ;
rdfs:subClassOf _:r2006 ;
rdfs:subClassOf _:r2007 ;
rdfs:subClassOf _:r2008 ;
rdfs:subClassOf _:r2009 ;
vc:contrastsWith ngm:cognitive-accessibility ;
vc:dependsOn ngm:gesture-recognition ;
vc:dependsOn ngm:multimodal-ai-architecture ;
vc:dependsOn ngm:neural-xr-interfaces ;
vc:dependsOn ngm:real-time-processing ;
vc:dependsOn ngm:speech-recognition ;
vc:enables ngm:accessible-experience ;
vc:enables ngm:augmented-connected-workforce ;
vc:enables ngm:equitable-access ;
vc:enables ngm:inclusive-participation ;
vc:enables ngm:inclusive-xr-design ;
vc:enables ngm:inclusive-xr-experience ;
vc:enables ngm:telecollaboration ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:accessibility-captioning ;
vc:hasPart ngm:accessibility-tree ;
vc:hasPart ngm:alternative-text ;
vc:hasPart ngm:audio-description ;
vc:hasPart ngm:colour-contrast ;
vc:hasPart ngm:haptic-feedback ;
vc:hasPart ngm:live-captions ;
vc:implements ngm:aria ;
vc:implements ngm:interaction-design ;
vc:implements ngm:universal-design ;
vc:implements ngm:wcag-2-2 ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:accessibility-standard ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:augmented-reality-ar ;
vc:relatedTo ngm:bias-mitigation-techniques ;
vc:relatedTo ngm:digital-equity ;
vc:relatedTo ngm:ethical-ai ;
vc:relatedTo ngm:explainable-ai ;
vc:relatedTo ngm:extended-reality-xr ;
vc:relatedTo ngm:human-computer-interaction ;
vc:relatedTo ngm:inclusive-design ;
vc:relatedTo ngm:khronos-open-xr ;
vc:relatedTo ngm:multimodal-ai ;
vc:relatedTo ngm:open-xr ;
vc:relatedTo ngm:spatial-computing ;
vc:relatedTo ngm:universal-design ;
vc:requires ngm:accessibility-audit-tool ;
vc:requires ngm:accessibility-standard ;
vc:requires ngm:accessibility-tree ;
vc:requires ngm:participatory-design ;
vc:requires ngm:user-centred-design ;
vc:slug "assistive-technology-integration" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:accessibility-standard ;
vc:supports ngm:cognitive-accessibility ;
vc:supports ngm:digital-technology-access-equity ;
vc:supports ngm:human-computer-interaction ;
vc:supports ngm:user-experience ;
vc:uses ngm:accessibility-audit-tool ;
vc:uses ngm:computer-vision ;
vc:uses ngm:edge-computing ;
vc:uses ngm:gesture-recognition ;
vc:uses ngm:haptic-feedback ;
vc:uses ngm:large-language-models ;
vc:uses ngm:multimodal-ai-architecture-ai ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:speech-recognition ;
vc:uses ngm:wearable-computing .
ngm:assistive-technology-support a owl:Class ;
rdfs:comment "Assistive Technology Support is the set of capabilities that make software interoperate correctly with assistive tools such as screen readers, magnifiers, switch access, and voice control. It is achieved by exposing semantic roles, names, states, and keyboard operability through accessibility APIs so that users with disabilities can perceive and operate an interface. Robust support is a prerequisite for accessible experiences and for compliance with standards like WCAG."@en ;
rdfs:label "Assistive Technology Support"@en ;
rdfs:subClassOf ngm:human-computer-interaction ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:accessibility ;
vc:relatedTo ngm:accessible-experience ;
vc:slug "assistive-technology-support" ;
vc:sourceDomain "infrastructure" .
ngm:association-for-computational-linguistics a skos:Concept ;
rdfs:label "Association For Computational Linguistics"@en .
ngm:association-for-computing-machinery a skos:Concept ;
rdfs:label "Association For Computing Machinery"@en .
ngm:association-rule-learning a owl:Class ;
rdfs:label "Association Rule Learning"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-processing ;
vc:slug "association-rule-learning" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:associative-learning a skos:Concept ;
rdfs:label "Associative Learning"@en .
ngm:associativity a skos:Concept ;
rdfs:label "Associativity"@en .
ngm:assurance-level a skos:Concept ;
rdfs:label "Assurance Level"@en .
ngm:asteroid a owl:Class ;
rdfs:label "Asteroid"@en ;
rdfs:subClassOf ngm:astronomical-body ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:astronomy ;
vc:slug "asteroid" ;
vc:sourceDomain "space-science-and-systems" .
ngm:astm-international a skos:Concept ;
rdfs:label "Astm International"@en .
ngm:astrobiology a owl:Class ;
rdfs:label "Astrobiology"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:planetary-science ;
vc:slug "astrobiology" ;
vc:sourceDomain "space-science-and-systems" .
ngm:astrometry a owl:Class ;
rdfs:label "Astrometry"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:astronomy ;
vc:slug "astrometry" ;
vc:sourceDomain "space-science-and-systems" .
ngm:astronomical-body a owl:Class ;
rdfs:label "Astronomical Body"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:astronomy ;
vc:slug "astronomical-body" ;
vc:sourceDomain "space-science-and-systems" .
ngm:astronomical-photometry a owl:Class ;
rdfs:label "Astronomical Photometry"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:astronomy ;
vc:slug "astronomical-photometry" ;
vc:sourceDomain "space-science-and-systems" .
ngm:astronomical-spectroscopy a owl:Class ;
rdfs:label "Astronomical Spectroscopy"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:astronomy ;
vc:slug "astronomical-spectroscopy" ;
vc:sourceDomain "space-science-and-systems" .
ngm:astronomical-time-system a owl:Class ;
rdfs:label "Astronomical Time System"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:space-reference-systems ;
vc:slug "astronomical-time-system" ;
vc:sourceDomain "space-science-and-systems" .
ngm:astronomy a owl:Class ;
rdfs:label "Astronomy"@en ;
rdfs:subClassOf ngm:space-science ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:slug "astronomy" ;
vc:sourceDomain "space-science-and-systems" .
ngm:astrophysical-jet a owl:Class ;
rdfs:label "Astrophysical Jet"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:black-hole ;
vc:relatedTo ngm:quasar ;
vc:slug "astrophysical-jet" ;
vc:sourceDomain "space-science-and-systems" .
ngm:astrophysics a owl:Class ;
rdfs:label "Astrophysics"@en ;
rdfs:subClassOf ngm:space-science ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:astronomy ;
vc:slug "astrophysics" ;
vc:sourceDomain "space-science-and-systems" .
ngm:asymmetric-cryptography a owl:Class ;
rdfs:comment "Asymmetric Cryptography is a cryptographic paradigm in which mathematically related key pairs — a public key and a private key — serve distinct roles: the public key may be freely shared and used to encrypt messages or verify signatures, while the private key is kept secret and used to decrypt or sign. Security rests on the computational intractability of reversing the underlying mathematical problems without knowledge of the private key."@en ;
rdfs:label "Asymmetric Cryptography"@en ;
rdfs:subClassOf ngm:cryptography ;
rdfs:subClassOf _:r2010 ;
rdfs:subClassOf _:r2011 ;
rdfs:subClassOf _:r2012 ;
rdfs:subClassOf _:r2013 ;
rdfs:subClassOf _:r2014 ;
rdfs:subClassOf _:r2015 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:zero-knowledge-proof ;
vc:contrastsWith ngm:post-quantum-cryptography ;
vc:contrastsWith ngm:symmetric-cryptography ;
vc:dependsOn ngm:hardware-security-module ;
vc:dependsOn ngm:key-management ;
vc:enables ngm:authentication ;
vc:enables ngm:cryptographic-infrastructure ;
vc:enables ngm:non-repudiation ;
vc:enables ngm:tls ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:digital-signature ;
vc:hasPart ngm:key-pair ;
vc:hasPart ngm:private-key ;
vc:hasPart ngm:public-key ;
vc:implements ngm:diffie-hellman-key-exchange ;
vc:implements ngm:elliptic-curve-cryptography ;
vc:implements ngm:rsa ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:certificate-transparency ;
vc:relatedTo ngm:fido2 ;
vc:relatedTo ngm:key-management ;
vc:requires ngm:random-number-generation ;
vc:requires ngm:trapdoor-function ;
vc:slug "asymmetric-cryptography" ;
vc:sourceDomain "security" ;
vc:supports ngm:code-signing ;
vc:supports ngm:end-to-end-encryption .
ngm:asymmetric-encryption a owl:Class ;
rdfs:comment "A cryptographic system using mathematically related public-private key pairs where the public key encrypts data that only the corresponding private key can decrypt, enabling secure communication, digital signatures, and trustless verification without pre-shared secrets."@en ;
rdfs:label "Asymmetric Encryption"@en ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf ngm:cryptographic-primitive ;
rdfs:subClassOf _:r2016 ;
rdfs:subClassOf _:r2017 ;
skos:broader ngm:blockchain ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:did-nostr-identity ;
vc:bridgesTo ngm:threshold-signature-scheme ;
vc:contrastsWith ngm:post-quantum-cryptography ;
vc:contrastsWith ngm:symmetric-encryption ;
vc:dependsOn ngm:number-theory ;
vc:enables ngm:cryptographic-infrastructure ;
vc:enables ngm:digital-signature ;
vc:enables ngm:key-exchange ;
vc:enables ngm:non-repudiation ;
vc:enables ngm:zero-knowledge-proof ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:elliptic-curve-cryptography ;
vc:implements ngm:rsa-cryptosystem ;
vc:implements ngm:trapdoor-function ;
vc:isPartOf ngm:cryptographic-infrastructure ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:certificate-authority ;
vc:relatedTo ngm:tls ;
vc:requires ngm:computational-hardness-assumption ;
vc:requires ngm:key-management ;
vc:slug "asymmetric-encryption" ;
vc:sourceDomain "security" ;
vc:supports ngm:authentication ;
vc:supports ngm:data-confidentiality ;
vc:supports ngm:information-security ;
vc:uses ngm:hash-function ;
vc:uses ngm:key-derivation-function ;
vc:uses ngm:random-number-generator .
ngm:asymmetric-key-pair a owl:Class ;
rdfs:comment "An asymmetric key pair is the pair of mathematically related keys, a public key and a private key, that together enable asymmetric cryptography: data encrypted or signed with one key can only be decrypted or verified with the other. The private key must be kept secret by its owner, while the public key can be freely distributed, allowing anyone to encrypt a message intended for the owner or verify a signature the owner has produced. Asymmetric key pairs underpin public-key infrastructure, digital signatures, and blockchain account ownership."@en ;
rdfs:label "Asymmetric Key Pair"@en ;
rdfs:subClassOf ngm:asymmetric-cryptography ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:isPartOf ngm:asymmetric-cryptography ;
vc:qualityScore "0.5"^^xsd:float ;
vc:slug "asymmetric-key-pair" ;
vc:sourceDomain "security" .
ngm:async-first-work-culture a skos:Concept ;
rdfs:label "Async First Work Culture"@en .
ngm:async-standup a skos:Concept ;
rdfs:label "Async Standup"@en .
ngm:asyncapi a owl:Class ;
rdfs:comment "AsyncAPI is an open specification for describing event-driven and message-based APIs in a machine-readable document, analogous to how OpenAPI describes request-response REST APIs. It defines channels, messages, payloads and the protocols and brokers used to exchange them, enabling documentation, code generation, validation and tooling for asynchronous systems. AsyncAPI standardises contracts for publish-subscribe and streaming architectures."@en ;
rdfs:label "Asyncapi"@en ;
rdfs:subClassOf ngm:api-specification ;
rdfs:subClassOf _:r2018 ;
vc:bridgesTo ngm:api-gateway ;
vc:contrastsWith ngm:open-api-specification ;
vc:contrastsWith ngm:rest-api ;
vc:dependsOn ngm:json-data-interchange-format-schema ;
vc:enables ngm:event-driven-architecture ;
vc:enables ngm:streaming-data ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:event-driven-architecture ;
vc:relatedTo ngm:open-api-specification ;
vc:requires ngm:message-broker ;
vc:slug "asyncapi" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:interoperability-standard ;
vc:supports ngm:asynchronous-messaging ;
vc:supports ngm:event-driven-architecture ;
vc:uses ngm:json-data-interchange-format-schema ;
vc:uses ngm:schema-validation .
ngm:asyncapi-specification a skos:Concept ;
rdfs:label "Asyncapi Specification"@en .
ngm:asynchronous-code-review a skos:Concept ;
rdfs:label "Asynchronous Code Review"@en .
ngm:asynchronous-collaboration a owl:Class ;
rdfs:comment "Time-independent collaboration mode where distributed participants contribute at different times through shared persistent artifacts, enabling flexible schedules, deep work periods, and global accessibility while maintaining coordination through explicit documentation and version control."@en ;
rdfs:label "Asynchronous Collaboration"@en ;
rdfs:subClassOf ngm:tc-0001-telecollaboration-domain ;
rdfs:subClassOf ngm:telecollaboration ;
rdfs:subClassOf _:r2019 ;
rdfs:subClassOf _:r2020 ;
rdfs:subClassOf _:r2021 ;
rdfs:subClassOf _:r2022 ;
rdfs:subClassOf _:r2023 ;
vc:bridgesTo ngm:distributed-systems ;
vc:bridgesTo ngm:knowledge-graph ;
vc:contrastsWith ngm:real-time-communication ;
vc:contrastsWith ngm:synchronous-collaboration ;
vc:enables ngm:accessibility ;
vc:enables ngm:open-source-development ;
vc:enables ngm:remote-work ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:code-review ;
vc:hasPart ngm:issue-tracking ;
vc:hasPart ngm:project-management ;
vc:hasPart ngm:tc-0002-collaborative-document-editing ;
vc:qualityScore "0.68"^^xsd:float ;
vc:requires ngm:documentation-culture ;
vc:requires ngm:version-control ;
vc:slug "asynchronous-collaboration" ;
vc:sourceDomain "distributed-collaboration" ;
vc:standardizedBy ngm:iso ;
vc:supports ngm:knowledge-management ;
vc:supports ngm:tc-0080-team-coordination ;
vc:uses ngm:conflict-free-replicated-data-type ;
vc:uses ngm:operational-transformation ;
vc:uses ngm:version-control .
ngm:asynchronous-communication a owl:Class ;
rdfs:comment "Asynchronous communication is a messaging paradigm in which senders and receivers operate independently in time: the sender dispatches a message and immediately resumes processing without blocking, while the message is buffered, queued, or stored until the recipient is ready to consume it. This temporal decoupling eliminates tight runtime coupling between system components, enabling fault isolation, backpressure management, and geographic distribution across heterogeneous networks. The pattern underpins modern distributed architectures including event-driven systems, message-oriented middleware, and stream-processing platforms, and contrasts sharply with synchronous request-response protocols where the caller blocks awaiting a reply. By permitting independent scaling, retry semantics, and durable delivery guarantees, asynchronous communication is foundational to resilient, cloud-native, and edge-deployed systems."@en ;
rdfs:label "Asynchronous Communication"@en ;
rdfs:subClassOf ngm:infra-network-and-comms ;
skos:broader ngm:infra-network-and-comms ;
vc:bridgesTo ngm:federated-learning ;
vc:bridgesTo ngm:multi-agent-systems ;
vc:contrastsWith ngm:remote-procedure-call ;
vc:contrastsWith ngm:synchronous-communication ;
vc:enables ngm:asynchronous-execution ;
vc:enables ngm:distributed-collaboration ;
vc:enables ngm:event-driven-architecture ;
vc:enables ngm:microservices-architecture ;
vc:enables ngm:stream-processing ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:ai-infrastructure ;
vc:relatedTo ngm:cloud-native-architecture ;
vc:relatedTo ngm:eventual-consistency ;
vc:relatedTo ngm:reactive-programming ;
vc:requires ngm:delivery-guarantees ;
vc:requires ngm:message-durability ;
vc:slug "asynchronous-communication" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:amqp ;
vc:standardizedBy ngm:mqtt ;
vc:supports ngm:backpressure ;
vc:supports ngm:edge-computing ;
vc:supports ngm:fault-tolerance ;
vc:supports ngm:parallel-processing ;
vc:uses ngm:message-broker ;
vc:uses ngm:message-queue ;
vc:uses ngm:protobuf ;
vc:uses ngm:protocol-buffer ;
vc:uses ngm:publish-subscribe-pattern .
ngm:asynchronous-coordination a owl:Class ;
rdfs:comment "Asynchronous Coordination is the alignment of distributed agents or processes that act without a shared global clock or blocking synchronization, communicating through messages, shared state, or eventual-consistency mechanisms. It tolerates network delay and partial failure by letting participants make progress independently and reconcile state later. This model underpins resilient distributed systems and decentralized multi-agent and swarm control."@en ;
rdfs:label "Asynchronous Coordination"@en ;
rdfs:subClassOf ngm:distributed-systems ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:decentralised-coordination ;
vc:relatedTo ngm:decentralized-swarm-control ;
vc:slug "asynchronous-coordination" ;
vc:sourceDomain "infrastructure" .
ngm:asynchronous-discussion-forum a skos:Concept ;
rdfs:label "Asynchronous Discussion Forum"@en .
ngm:asynchronous-execution a owl:Class ;
rdfs:comment "An execution model in which operations are initiated without blocking the calling thread; completion is signalled via callbacks, promises, futures, or events, enabling high-throughput concurrent processing particularly suited to I/O-bound workloads and distributed system communication."@en ;
rdfs:label "Asynchronous Execution"@en ;
rdfs:subClassOf ngm:execution-model ;
vc:bridgesTo ngm:ai-infrastructure ;
vc:bridgesTo ngm:edge-computing ;
vc:enables ngm:microservices-architecture ;
vc:enables ngm:parallel-processing ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:slug "asynchronous-execution" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:ai-agent-system ;
vc:supports ngm:edge-computing ;
vc:uses ngm:asynchronous-communication ;
vc:uses ngm:event-driven-architecture .
ngm:asynchronous-ideation a skos:Concept ;
rdfs:label "Asynchronous Ideation"@en .
ngm:asynchronous-meeting-access a skos:Concept ;
rdfs:label "Asynchronous Meeting Access"@en .
ngm:asynchronous-messaging a owl:Class ;
rdfs:comment "Asynchronous Messaging is a communication pattern in which a sender dispatches a message to an intermediary and continues processing without waiting for the receiver to respond. Messages are buffered in queues or brokers and consumed when downstream services are ready, decoupling producers from consumers in time and load. This pattern improves resilience, scalability and fault tolerance in distributed and event-driven architectures."@en ;
rdfs:label "Asynchronous Messaging"@en ;
rdfs:subClassOf ngm:message-queue ;
vc:contrastsWith ngm:synchronous-communication ;
vc:enables ngm:fault-tolerance ;
vc:enables ngm:resilience ;
vc:enables ngm:scalability ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:apache-kafka ;
vc:implements ngm:rabbitmq ;
vc:isPartOf ngm:event-driven-architecture ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:distributed-systems ;
vc:relatedTo ngm:rest-api ;
vc:slug "asynchronous-messaging" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:amqp ;
vc:supports ngm:microservices ;
vc:supports ngm:webhook ;
vc:uses ngm:message-broker ;
vc:uses ngm:message-queue .
ngm:asynchronous-network a skos:Concept ;
rdfs:label "Asynchronous Network"@en .
ngm:asynchronous-programming a owl:Class ;
rdfs:comment "Asynchronous programming is a concurrency model in which operations that would otherwise block — such as input/output, network calls or timers — are initiated without halting the executing thread, allowing other work to proceed until results become available. It uses constructs such as callbacks, promises, futures and async/await to express continuations cleanly. The approach improves responsiveness and throughput for input/output-bound workloads without the overhead of one thread per task."@en ;
rdfs:label "Asynchronous Programming"@en ;
rdfs:subClassOf ngm:concurrency ;
rdfs:subClassOf ngm:software-engineering ;
rdfs:subClassOf _:r2024 ;
vc:contrastsWith ngm:parallel-processing ;
vc:enables ngm:scalability ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:software-engineering ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:concurrency ;
vc:relatedTo ngm:multithreading ;
vc:relatedTo ngm:parallel-computing ;
vc:relatedTo ngm:software-development ;
vc:requires ngm:software-engineering ;
vc:slug "asynchronous-programming" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:cloud-computing ;
vc:supports ngm:distributed-computing ;
vc:uses ngm:multithreading ;
vc:uses ngm:python .
ngm:asynchronous-rl a skos:Concept ;
rdfs:label "Asynchronous Rl"@en .
ngm:asynchronous-sgd a skos:Concept ;
rdfs:label "Asynchronous Sgd"@en .
ngm:asynchronous-video a owl:Class ;
rdfs:comment "Asynchronous video is a Distributed Collaboration communication modality in which recorded video messages — combining screen capture, webcam footage, audio narration, and on-screen annotation — are produced by a sender and consumed by recipients independently of the sender's presence, elimina..."@en ;
rdfs:label "Asynchronous Video"@en ;
rdfs:subClassOf ngm:asynchronous-communication ;
rdfs:subClassOf ngm:dc-communication ;
rdfs:subClassOf ngm:digital-workplace-technology ;
rdfs:subClassOf ngm:distributed-collaboration ;
rdfs:subClassOf ngm:knowledge-management ;
rdfs:subClassOf ngm:video-based-communication ;
rdfs:subClassOf _:r2025 ;
rdfs:subClassOf _:r2026 ;
rdfs:subClassOf _:r2027 ;
rdfs:subClassOf _:r2028 ;
rdfs:subClassOf _:r2029 ;
rdfs:subClassOf _:r2030 ;
skos:broader ngm:dc-communication ;
skos:broader ngm:distributed-collaboration ;
vc:contrastsWith ngm:email ;
vc:contrastsWith ngm:instant-messaging ;
vc:contrastsWith ngm:screencasting ;
vc:contrastsWith ngm:synchronous-meeting ;
vc:contrastsWith ngm:video-conferencing ;
vc:dependsOn ngm:automatic-speech-recognition ;
vc:dependsOn ngm:av1-video-codec ;
vc:dependsOn ngm:h-264-video-codec ;
vc:dependsOn ngm:natural-language-processing ;
vc:dependsOn ngm:object-storage ;
vc:dependsOn ngm:web-rtc ;
vc:enables ngm:async-standup ;
vc:enables ngm:asynchronous-code-review ;
vc:enables ngm:complex-decision-documentation ;
vc:enables ngm:distributed-onboarding ;
vc:enables ngm:remote-team-alignment ;
vc:enables ngm:sales-outreach-video ;
vc:enables ngm:time-zone-decoupled-communication ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ai-video-summary ;
vc:hasPart ngm:audio-narration ;
vc:hasPart ngm:chapter-marker ;
vc:hasPart ngm:click-tracking ;
vc:hasPart ngm:emoji-reaction ;
vc:hasPart ngm:screen-recording ;
vc:hasPart ngm:timeline-annotation ;
vc:hasPart ngm:timestamped-comment ;
vc:hasPart ngm:video-transcription ;
vc:hasPart ngm:viewer-analytics ;
vc:implements ngm:async-first-work-culture ;
vc:implements ngm:communication-synchronicity-theory ;
vc:implements ngm:media-richness-theory ;
vc:implements ngm:retrieval-augmented-video-search ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:claap ;
vc:relatedTo ngm:jira ;
vc:relatedTo ngm:loom ;
vc:relatedTo ngm:meeting-ai-assistant ;
vc:relatedTo ngm:meeting-recording ;
vc:relatedTo ngm:notion ;
vc:relatedTo ngm:otter-ai ;
vc:relatedTo ngm:slack ;
vc:relatedTo ngm:veed-io ;
vc:relatedTo ngm:vidyard ;
vc:relatedTo ngm:zoom-ai-companion ;
vc:requires ngm:browser-based-screen-capture ;
vc:requires ngm:cdn ;
vc:requires ngm:cloud-storage ;
vc:requires ngm:speech-recognition ;
vc:requires ngm:video-codec ;
vc:requires ngm:video-playback-infrastructure ;
vc:slug "asynchronous-video" ;
vc:sourceDomain "distributed-collaboration" ;
vc:standardizedBy ngm:aom-av1-specification ;
vc:standardizedBy ngm:ietf-rfc-7742-web-rtc-video ;
vc:standardizedBy ngm:ietf-rfc-7742-webrtc-video ;
vc:standardizedBy ngm:iso-iec-14496-mpeg-4 ;
vc:standardizedBy ngm:web-rtc-w-3-c-specification ;
vc:supports ngm:customer-onboarding ;
vc:supports ngm:design-review ;
vc:supports ngm:distributed-teams ;
vc:supports ngm:executive-communication ;
vc:supports ngm:remote-work ;
vc:supports ngm:software-engineering-workflows ;
vc:uses ngm:large-language-models ;
vc:uses ngm:named-entity-recognition ;
vc:uses ngm:optical-character-recognition ;
vc:uses ngm:semantic-search ;
vc:uses ngm:speaker-diarisation .
ngm:asynchronous-workflows a skos:Concept ;
rdfs:label "Asynchronous Workflows"@en .
ngm:at-least-once-delivery a skos:Concept ;
rdfs:label "At Least Once Delivery"@en .
ngm:at-protocol a owl:Class ;
rdfs:comment "The AT Protocol (Authenticated Transfer Protocol) is an open, federated networking protocol for decentralised social applications, originally developed for Bluesky, that combines portable accounts, signed data repositories, and account migration with a separation between data hosting and algorithmic curation. It uses decentralised identifiers and content-addressed records so users own their identity and data independently of any single provider. The protocol aims to deliver large-scale interoperable social networking with user choice over feeds and moderation."@en ;
rdfs:label "At Protocol"@en ;
rdfs:subClassOf ngm:open-standards ;
rdfs:subClassOf _:r2031 ;
rdfs:subClassOf _:r2032 ;
rdfs:subClassOf _:r2033 ;
rdfs:subClassOf _:r2034 ;
vc:bridgesTo ngm:infrastructure ;
vc:contrastsWith ngm:activity-pub ;
vc:dependsOn ngm:did ;
vc:enables ngm:decentralised-identity ;
vc:enables ngm:federation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:content-addressing ;
vc:implements ngm:open-standards ;
vc:implements ngm:protocol ;
vc:isPartOf ngm:open-standards ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:activity-pub ;
vc:relatedTo ngm:cross-platform-identity ;
vc:requires ngm:content-addressing ;
vc:requires ngm:did ;
vc:slug "at-protocol" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:federation ;
vc:uses ngm:content-addressing ;
vc:uses ngm:did .
ngm:atag-2-0 a skos:Concept ;
rdfs:label "Atag 2 0"@en .
ngm:atala-prism a skos:Concept ;
rdfs:label "Atala Prism"@en .
ngm:ate-pairing a skos:Concept ;
rdfs:label "Ate Pairing"@en .
ngm:atex-directive-2014-34-eu a skos:Concept ;
rdfs:label "Atex Directive 2014 34 Eu"@en .
ngm:atk-at-spi a skos:Concept ;
rdfs:label "Atk At Spi"@en .
ngm:atkinson-index a skos:Concept ;
rdfs:label "Atkinson Index"@en .
ngm:atlas a skos:Concept ;
rdfs:label "Atlas"@en .
ngm:atmosphere-layer a owl:Class ;
rdfs:label "Atmosphere Layer"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-system-phenomena ;
vc:slug "atmosphere-layer" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:atmosphere-revitalisation a owl:Class ;
rdfs:label "Atmosphere Revitalisation"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:space-life-sciences ;
vc:slug "atmosphere-revitalisation" ;
vc:sourceDomain "space-science-and-systems" .
ngm:atmospheric-composition-monitoring a owl:Class ;
rdfs:label "Atmospheric Composition Monitoring"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-applications ;
vc:slug "atmospheric-composition-monitoring" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:atmospheric-correction a owl:Class ;
rdfs:label "Atmospheric Correction"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-processing ;
vc:slug "atmospheric-correction" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:atmospheric-drag a owl:Class ;
rdfs:label "Atmospheric Drag"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:orbital-dynamics ;
vc:slug "atmospheric-drag" ;
vc:sourceDomain "space-science-and-systems" .
ngm:atoken a skos:Concept ;
rdfs:label "Atoken"@en .
ngm:atomic-batch-transactions a skos:Concept ;
rdfs:label "Atomic Batch Transactions"@en .
ngm:atomic-broadcast a owl:Class ;
rdfs:comment "Atomic broadcast (also called total-order broadcast) is a distributed communication primitive guaranteeing that all correct processes deliver the same set of messages in the same total order. It strengthens reliable broadcast with an ordering property, ensuring agreement on both the content and sequence of delivered messages. Atomic broadcast is equivalent in power to consensus and underpins state-machine replication."@en ;
rdfs:label "Atomic Broadcast"@en ;
rdfs:subClassOf ngm:distributed-systems ;
rdfs:subClassOf _:r2035 ;
rdfs:subClassOf _:r2036 ;
vc:bridgesTo ngm:practical-byzantine-fault-tolerance ;
vc:contrastsWith ngm:byzantine-generals-problem ;
vc:dependsOn ngm:distributed-system ;
vc:enables ngm:consensus ;
vc:enables ngm:replication ;
vc:enables ngm:state-machine-replication ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:blockchain-consensus ;
vc:relatedTo ngm:clock-synchronization ;
vc:relatedTo ngm:consensus ;
vc:requires ngm:fault-tolerance ;
vc:requires ngm:message-passing ;
vc:slug "atomic-broadcast" ;
vc:sourceDomain "distributed-systems" ;
vc:supports ngm:byzantine-fault-tolerance ;
vc:supports ngm:crash-fault-tolerance ;
vc:uses ngm:paxos ;
vc:uses ngm:raft .
ngm:atomic-clock a skos:Concept ;
rdfs:label "Atomic Clock"@en .
ngm:atomic-composability a skos:Concept ;
rdfs:label "Atomic Composability"@en .
ngm:atomic-delivery-versus-payment a owl:Class ;
rdfs:comment "Atomic Delivery versus Payment (atomic DvP) is a settlement mechanism in which the transfer of an asset and the corresponding payment are executed as a single indivisible transaction: either both legs complete simultaneously or neither does, eliminating counterparty risk by making it impossible for one party to receive value without the other receiving theirs. It applies the atomicity property of database transactions to financial and digital asset exchange."@en ;
rdfs:label "Atomic Delivery versus Payment"@en ;
rdfs:subClassOf ngm:delivery-versus-payment ;
vc:enables ngm:atomic-swap ;
vc:enables ngm:cross-chain-asset-transfer ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:blockchain-transaction ;
vc:relatedTo ngm:smart-contract-execution ;
vc:slug "atomic-delivery-versus-payment" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:hash-time-locked-contract ;
vc:uses ngm:smart-contract .
ngm:atomic-layer-deposition a skos:Concept ;
rdfs:label "Atomic Layer Deposition"@en .
ngm:atomic-multi-asset-transfer a skos:Concept ;
rdfs:label "Atomic Multi Asset Transfer"@en .
ngm:atomic-refactoring a skos:Concept ;
rdfs:label "Atomic Refactoring"@en .
ngm:atomic-settlement a owl:Class ;
rdfs:comment "Atomic settlement is a transaction completion mechanism in which the transfer of assets between two or more parties either executes in its entirety or not at all, eliminating counterparty risk and the possibility of partial fulfilment. The mechanism is enforced at the protocol level, ensuring that delivery and payment occur simultaneously and indivisibly within a single transaction or smart contract execution. This property derives from atomicity — one of the four ACID properties of database transactions — applied to financial and digital asset exchanges. Atomic settlement is the foundational guarantee underpinning trustless exchange protocols, cross-chain bridges, real-time gross settlement systems, and delivery-versus-payment architectures in both decentralised and regulated financial markets."@en ;
rdfs:label "Atomic Settlement"@en ;
rdfs:subClassOf ngm:transaction ;
rdfs:subClassOf _:r2037 ;
rdfs:subClassOf _:r2038 ;
rdfs:subClassOf _:r2039 ;
rdfs:subClassOf _:r2040 ;
vc:bridgesTo ngm:distributed-transaction ;
vc:bridgesTo ngm:two-phase-commit ;
vc:contrastsWith ngm:bilateral-netting ;
vc:contrastsWith ngm:deferred-net-settlement ;
vc:contrastsWith ngm:settlement-risk ;
vc:dependsOn ngm:blockchain ;
vc:dependsOn ngm:consensus-mechanism ;
vc:dependsOn ngm:finality ;
vc:enables ngm:cross-chain-interoperability ;
vc:enables ngm:decentralized-exchange ;
vc:enables ngm:securities-settlement ;
vc:enables ngm:settlement ;
vc:enables ngm:trustless-settlement ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:acid-properties ;
vc:implements ngm:delivery-versus-payment ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:atomic-swap ;
vc:relatedTo ngm:central-counterparty ;
vc:relatedTo ngm:payment-channel ;
vc:relatedTo ngm:real-time-gross-settlement ;
vc:requires ngm:cryptographic-commitment ;
vc:requires ngm:hash-time-locked-contract ;
vc:requires ngm:smart-contract ;
vc:requires ngm:transaction-finality ;
vc:slug "atomic-settlement" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:central-bank-digital-currency-cbdc ;
vc:supports ngm:de-fi ;
vc:supports ngm:tokenised-securities ;
vc:uses ngm:digital-signature ;
vc:uses ngm:escrow-system ;
vc:uses ngm:hash-time-locked-contract ;
vc:uses ngm:smart-contract .
ngm:atomic-swap a owl:Class ;
rdfs:comment "Trustless peer-to-peer cryptocurrency exchange mechanism across different blockchains using Hash Time-Locked Contracts (HTLCs) that guarantees atomic execution where the swap either completes fully or not at all, eliminating counterparty risk without requiring centralized intermediaries."@en ;
rdfs:label "Atomic Swap"@en ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf ngm:blockchain-protocol ;
rdfs:subClassOf _:r2041 ;
rdfs:subClassOf _:r2042 ;
skos:broader ngm:blockchain ;
vc:bridgesTo ngm:de-fi ;
vc:bridgesTo ngm:virtual-economy ;
vc:contrastsWith ngm:centralized-exchange ;
vc:contrastsWith ngm:cross-chain-bridge ;
vc:contrastsWith ngm:wrapped-token ;
vc:dependsOn ngm:blockchain ;
vc:dependsOn ngm:consensus-mechanism ;
vc:dependsOn ngm:cryptographic-hash-function ;
vc:enables ngm:cross-chain-interoperability ;
vc:enables ngm:decentralized-exchange ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:hash-time-locked-contract ;
vc:isPartOf ngm:decentralized-exchange ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:bitcoin ;
vc:relatedTo ngm:erc-20-tokens ;
vc:relatedTo ngm:ethereum ;
vc:relatedTo ngm:polkadot ;
vc:requires ngm:payment-channel ;
vc:requires ngm:smart-contract ;
vc:slug "atomic-swap" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:adaptor-signature ;
vc:supports ngm:lightning-network ;
vc:supports ngm:submarine-swap ;
vc:uses ngm:commitment-scheme ;
vc:uses ngm:digital-signature ;
vc:uses ngm:hash-function .
ngm:atomic-swap-only-protocol a skos:Concept ;
rdfs:label "Atomic Swap Only Protocol"@en .
ngm:atsc a skos:Concept ;
rdfs:label "Atsc"@en .
ngm:atsc-3-0 a skos:Concept ;
rdfs:label "Atsc 3 0"@en .
ngm:atsc-standards a skos:Concept ;
rdfs:label "Atsc Standards"@en .
ngm:attack-trees a skos:Concept ;
rdfs:label "Attack Trees"@en .
ngm:attack-vector a owl:Class ;
rdfs:comment "A specific path, method, or mechanism that a threat actor uses to gain unauthorised access, exploit vulnerabilities, or cause damage to a system, network, or organisation. Attack vectors span network-based exploitation, social engineering, supply-chain compromise, and AI-specific techniques such as prompt injection or model poisoning, and are categorised by access method, target layer, and sophistication."@en ;
rdfs:label "Attack Vector"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf ngm:infra-security-and-identity ;
rdfs:subClassOf _:r2043 ;
rdfs:subClassOf _:r2044 ;
rdfs:subClassOf _:r2045 ;
rdfs:subClassOf _:r2046 ;
skos:broader ngm:artificial-intelligence ;
skos:broader ngm:infra-security-and-identity ;
vc:bridgesTo ngm:adversarial-machine-learning ;
vc:bridgesTo ngm:blockchain ;
vc:contrastsWith ngm:defense-in-depth ;
vc:contrastsWith ngm:resilience ;
vc:contrastsWith ngm:security ;
vc:enables ngm:data-breach ;
vc:enables ngm:exploit ;
vc:enables ngm:privilege-escalation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:social-engineering ;
vc:hasPart ngm:supply-chain-attack ;
vc:isPartOf ngm:threat-model ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:adversarial-robustness ;
vc:relatedTo ngm:incident-response ;
vc:relatedTo ngm:intrusion-detection ;
vc:relatedTo ngm:risk ;
vc:requires ngm:access-control ;
vc:requires ngm:threat-actor ;
vc:requires ngm:vulnerability ;
vc:slug "attack-vector" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:cvss ;
vc:uses ngm:malware ;
vc:uses ngm:zero-day-exploits .
ngm:attended-automation a skos:Concept ;
rdfs:label "Attended Automation"@en .
ngm:attention a owl:Class ;
rdfs:comment "Attention is a differentiable content-based addressing mechanism for neural networks that computes a weighted combination of value vectors according to learned compatibility scores between a query vector and a set of key vectors, formalised in its most influential form as Scaled Dot-Product Atten..."@en ;
rdfs:label "Attention"@en ;
rdfs:subClassOf ngm:ai-model-architecture ;
rdfs:subClassOf ngm:differentiable-memory ;
rdfs:subClassOf ngm:neural-network ;
rdfs:subClassOf ngm:neural-network-mechanism ;
rdfs:subClassOf ngm:representation-learning ;
rdfs:subClassOf ngm:sequence-model ;
rdfs:subClassOf _:r2076 ;
rdfs:subClassOf _:r2077 ;
rdfs:subClassOf _:r2078 ;
rdfs:subClassOf _:r2079 ;
rdfs:subClassOf _:r2080 ;
rdfs:subClassOf _:r2081 ;
rdfs:subClassOf _:r2082 ;
rdfs:subClassOf _:r2083 ;
rdfs:subClassOf _:r2084 ;
rdfs:subClassOf _:r2085 ;
rdfs:subClassOf _:r2086 ;
rdfs:subClassOf _:r2087 ;
rdfs:subClassOf _:r2088 ;
skos:broader ngm:ai-model-architecture ;
vc:contrastsWith ngm:convolutional-neural-network ;
vc:contrastsWith ngm:gated-recurrent-unit ;
vc:contrastsWith ngm:long-short-term-memory ;
vc:contrastsWith ngm:recurrent-neural-network ;
vc:contrastsWith ngm:state-space-model ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:information-theory ;
vc:dependsOn ngm:linear-algebra ;
vc:dependsOn ngm:probability-theory ;
vc:dependsOn ngm:stochastic-gradient-descent ;
vc:enables ngm:context-window ;
vc:enables ngm:cross-modal-conditioning ;
vc:enables ngm:in-context-learning ;
vc:enables ngm:large-language-model ;
vc:enables ngm:large-language-models ;
vc:enables ngm:neural-machine-translation ;
vc:enables ngm:transformer ;
vc:enables ngm:vision-transformer ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:attention-head ;
vc:hasPart ngm:attention-score ;
vc:hasPart ngm:attention-weight ;
vc:hasPart ngm:datalog-knowledge-graph-query-language ;
vc:hasPart ngm:key ;
vc:hasPart ngm:positional-encoding ;
vc:hasPart ngm:query ;
vc:hasPart ngm:softmax-function ;
vc:hasPart ngm:value ;
vc:implements ngm:content-addressing ;
vc:implements ngm:differentiable-lookup ;
vc:implements ngm:permutation-equivariance ;
vc:implements ngm:soft-alignment ;
vc:implements ngm:weighted-aggregation ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:graph-neural-network ;
vc:relatedTo ngm:memory-augmented-neural-network ;
vc:relatedTo ngm:mixture-of-experts-architecture ;
vc:relatedTo ngm:neural-turing-machine ;
vc:relatedTo ngm:pointer-network ;
vc:requires ngm:backpropagation ;
vc:requires ngm:differentiable-architecture ;
vc:requires ngm:embedding ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:linear-projection ;
vc:requires ngm:matrix-multiplication ;
vc:slug "attention" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:acl ;
vc:standardizedBy ngm:cvpr ;
vc:standardizedBy ngm:iclr ;
vc:standardizedBy ngm:icml ;
vc:standardizedBy ngm:neur-ips ;
vc:standardizedBy ngm:onnx-operator-set ;
vc:standardizedBy ngm:openai-triton ;
vc:supports ngm:code-generation ;
vc:supports ngm:diffusion-model ;
vc:supports ngm:foundation-model ;
vc:supports ngm:large-scale-pretrained-foundation-model ;
vc:supports ngm:multimodal-ai-architecture-reasoning ;
vc:supports ngm:protein-structure-prediction ;
vc:supports ngm:speech-recognition ;
vc:uses ngm:causal-mask ;
vc:uses ngm:flash-attention ;
vc:uses ngm:kv-cache ;
vc:uses ngm:multi-head-attention ;
vc:uses ngm:rotary-position-embedding ;
vc:uses ngm:scaled-dot-product-attention ;
vc:uses ngm:sliding-window .
ngm:attention-analytics a skos:Concept ;
rdfs:label "Attention Analytics"@en .
ngm:attention-aware-interaction a owl:Class ;
rdfs:comment "Attention Aware Interaction refers to human-computer interaction techniques that leverage eye tracking, gaze detection, and attention modeling to understand user focus and adapt interfaces accordingly, enabling foveated rendering, gaze-based selection, and contextual content presentation in VR, A..."@en ;
rdfs:label "Attention Aware Interaction"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:human-computer-interaction ;
rdfs:subClassOf _:r2047 ;
rdfs:subClassOf _:r2048 ;
skos:broader ngm:ai-application ;
vc:bridgesTo ngm:sensor-input ;
vc:enables ngm:adaptive-interfaces ;
vc:enables ngm:foveated-rendering ;
vc:enables ngm:gaze-based-selection ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:attention-modeling ;
vc:requires ngm:eye-tracking ;
vc:requires ngm:gaze-detection-algorithms ;
vc:slug "attention-aware-interaction" ;
vc:sourceDomain "artificial-intelligence" .
ngm:attention-economy a owl:Class ;
rdfs:comment "An economic framing, articulated by Herbert Simon in 1971, in which human attention is treated as the scarce resource that information-rich systems compete to capture, allocate, and monetise. In digital markets it describes the business logic of advertising-funded platforms whose revenue scales with engagement, driving recommendation algorithms, infinite feeds, and notification design that optimise for time-on-platform — with documented consequences for information quality, creator livelihoods, and individual wellbeing."@en ;
rdfs:label "Attention Economy"@en ;
rdfs:subClassOf ngm:digital-economy ;
vc:dependsOn ngm:digital-platform ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:content-curation ;
vc:relatedTo ngm:creator-economy ;
vc:relatedTo ngm:creator-monetization ;
vc:relatedTo ngm:digital-society-harms ;
vc:slug "attention-economy" ;
vc:sourceDomain "governance" .
ngm:attention-head a owl:Class ;
rdfs:comment "One of multiple parallel scaled dot-product attention mechanisms in a multi-head attention layer, each operating over a distinct linear projection of the input. Individual heads specialise in different linguistic or structural patterns; most learn simple positional relationships and many can be pruned without significant loss, though a subset carry disproportionate representational load."@en ;
rdfs:label "Attention Head"@en ;
rdfs:subClassOf ngm:ai-model-architecture ;
skos:broader ngm:ai-model-architecture ;
vc:bridgesTo ngm:computer-vision ;
vc:enables ngm:transformers ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:isPartOf ngm:attention-mechanism ;
vc:isPartOf ngm:network-architecture ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:attention ;
vc:relatedTo ngm:transformer-architecture ;
vc:slug "attention-head" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:attention-weight .
ngm:attention-manipulation a skos:Concept ;
rdfs:label "Attention Manipulation"@en .
ngm:attention-mask a owl:Class ;
rdfs:comment "A mechanism that controls which positions in a sequence can attend to which other positions, typically implemented by adding large negative values before softmax to zero out unwanted attention weights; used for causal masking in autoregressive decoders and padding masking in batched variable-length sequences."@en ;
rdfs:label "Attention Mask"@en ;
rdfs:subClassOf ngm:ai-model-architecture ;
skos:broader ngm:ai-model-architecture ;
vc:bridgesTo ngm:telecollaboration ;
vc:enables ngm:albert ;
vc:enables ngm:large-language-models ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:isPartOf ngm:transformer-architecture ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:bart ;
vc:relatedTo ngm:neural-network-architecture ;
vc:slug "attention-mask" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:natural-language-processing .
ngm:attention-mechanism a owl:Class ;
rdfs:comment "An Attention Mechanism is a neural network component that enables models to dynamically weight the relevance of different input positions when producing each output element, computing weighted combinations based on learned similarity scores. Originally introduced for sequence-to-sequence machine translation, self-attention and multi-head attention are now the core computational primitives of transformer architectures, enabling parallel processing of sequences and capturing long-range dependencies that recurrent models struggle with."@en ;
rdfs:label "Attention Mechanism"@en ;
rdfs:subClassOf ngm:neural-network-component ;
rdfs:subClassOf _:r2049 ;
rdfs:subClassOf _:r2050 ;
rdfs:subClassOf _:r2051 ;
rdfs:subClassOf _:r2052 ;
rdfs:subClassOf _:r2053 ;
rdfs:subClassOf _:r2054 ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:multimodal-ai-architecture-ai ;
vc:bridgesTo ngm:telecollaboration ;
vc:contrastsWith ngm:long-short-term-memory ;
vc:contrastsWith ngm:recurrent-neural-network ;
vc:dependsOn ngm:backpropagation ;
vc:dependsOn ngm:gradient-descent ;
vc:enables ngm:large-language-models ;
vc:enables ngm:long-range-dependency-modelling ;
vc:enables ngm:machine-translation ;
vc:enables ngm:natural-language-processing ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:multi-head-attention ;
vc:hasPart ngm:query-key-value ;
vc:hasPart ngm:self-attention ;
vc:hasPart ngm:softmax-function ;
vc:implements ngm:sequence-to-sequence-learning ;
vc:isPartOf ngm:transformer-architecture ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:explainable-ai ;
vc:relatedTo ngm:graph-neural-network ;
vc:requires ngm:matrix-multiplication ;
vc:requires ngm:positional-encoding ;
vc:slug "attention-mechanism" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:image-captioning ;
vc:supports ngm:speech-recognition ;
vc:uses ngm:neural-network .
ngm:attention-mechanisms a owl:Class ;
rdfs:comment "Attention mechanisms are a family of neural network components that compute context-dependent weighted combinations of value representations by scoring the relevance of query vectors against key vectors, enabling each output position to draw selectively from any position in an input sequence — overcoming the fixed-length bottleneck of recurrent encoders. Originally introduced as additive (Bahdanau) attention for neural machine translation in 2015, they were generalised to scaled dot-product attention and multi-head attention in the 2017 Transformer architecture, where they became the sole sequence-modelling primitive, replacing recurrence entirely. Attention mechanisms now underpin virtually all frontier deep learning systems across language, vision, speech, biology, and multimodal reasoning."@en ;
rdfs:label "Attention Mechanisms"@en ;
rdfs:subClassOf ngm:ai-model-architecture ;
rdfs:subClassOf ngm:attention-mechanism ;
rdfs:subClassOf ngm:neural-network-component ;
rdfs:subClassOf _:r2055 ;
rdfs:subClassOf _:r2056 ;
rdfs:subClassOf _:r2057 ;
rdfs:subClassOf _:r2058 ;
rdfs:subClassOf _:r2059 ;
rdfs:subClassOf _:r2060 ;
rdfs:subClassOf _:r2061 ;
rdfs:subClassOf _:r2062 ;
rdfs:subClassOf _:r2063 ;
rdfs:subClassOf _:r2064 ;
rdfs:subClassOf _:r2065 ;
rdfs:subClassOf _:r2066 ;
rdfs:subClassOf _:r2067 ;
rdfs:subClassOf _:r2068 ;
skos:broader ngm:ai-model-architecture ;
vc:contrastsWith ngm:lstm ;
vc:contrastsWith ngm:recurrent-neural-network ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:feed-forward-network ;
vc:dependsOn ngm:lstm ;
vc:dependsOn ngm:positional-encoding ;
vc:enables ngm:diffusion-transformer ;
vc:enables ngm:graph-attention-network ;
vc:enables ngm:large-language-models ;
vc:enables ngm:machine-translation ;
vc:enables ngm:multimodal-ai-architecture ;
vc:enables ngm:multimodal-ai-architecture-reasoning ;
vc:enables ngm:natural-language-processing ;
vc:enables ngm:speech-recognition ;
vc:enables ngm:transformer ;
vc:enables ngm:transformer-architecture ;
vc:enables ngm:vision-transformer ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:attention-head ;
vc:hasPart ngm:attention-mask ;
vc:hasPart ngm:attention-weight ;
vc:hasPart ngm:causal-attention ;
vc:hasPart ngm:cross-attention ;
vc:hasPart ngm:multi-head-attention ;
vc:hasPart ngm:query-key-value ;
vc:hasPart ngm:scaled-dot-product-attention ;
vc:hasPart ngm:self-attention ;
vc:implements ngm:ai-model-architecture ;
vc:qualityScore "0.93"^^xsd:float ;
vc:relatedTo ngm:backpropagation ;
vc:relatedTo ngm:computer-vision ;
vc:relatedTo ngm:diffusion-transformer ;
vc:relatedTo ngm:explainable-ai ;
vc:relatedTo ngm:flash-attention ;
vc:relatedTo ngm:gemini-multimodal-language-model ;
vc:relatedTo ngm:grouped-query-attention ;
vc:relatedTo ngm:mixture-of-experts ;
vc:relatedTo ngm:multimodal-ai-architecture-learning ;
vc:relatedTo ngm:multimodal-ai-architecture-understanding ;
vc:relatedTo ngm:paged-attention ;
vc:relatedTo ngm:speculative-decoding ;
vc:requires ngm:backpropagation ;
vc:requires ngm:gradient-descent ;
vc:requires ngm:neural-network ;
vc:requires ngm:positional-encoding ;
vc:requires ngm:softmax-function ;
vc:slug "attention-mechanisms" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:transformer-architecture ;
vc:supports ngm:attention-aware-interaction ;
vc:supports ngm:explainable-ai ;
vc:supports ngm:knowledge-distillation ;
vc:supports ngm:reinforcement-learning-from-human-feedback ;
vc:uses ngm:flash-attention ;
vc:uses ngm:grouped-query-attention ;
vc:uses ngm:mixture-of-experts ;
vc:uses ngm:paged-attention ;
vc:uses ngm:speculative-decoding .
ngm:attention-modeling a skos:Concept ;
rdfs:label "Attention Modeling"@en .
ngm:attention-redirection a skos:Concept ;
rdfs:label "Attention Redirection"@en .
ngm:attention-score a skos:Concept ;
rdfs:label "Attention Score"@en .
ngm:attention-tiling a skos:Concept ;
rdfs:label "Attention Tiling"@en .
ngm:attention-tracker a skos:Concept ;
rdfs:label "Attention Tracker"@en .
ngm:attention-weight a owl:Class ;
rdfs:comment "A scalar coefficient produced by an attention mechanism that quantifies the relevance of one position (key/value) to another (query) in a sequence or across modalities. Attention weights are computed via a softmax over scaled dot-products of query and key vectors, and govern how much each value contributes to the output representation. They are the core computational primitive of Transformer-based models."@en ;
rdfs:label "Attention Weight"@en ;
rdfs:subClassOf ngm:ai-model-architecture ;
rdfs:subClassOf ngm:neural-network ;
rdfs:subClassOf _:r2069 ;
rdfs:subClassOf _:r2070 ;
rdfs:subClassOf _:r2071 ;
rdfs:subClassOf _:r2072 ;
rdfs:subClassOf _:r2073 ;
rdfs:subClassOf _:r2074 ;
rdfs:subClassOf _:r2075 ;
skos:broader ngm:ai-model-architecture ;
vc:bridgesTo ngm:ai-agent ;
vc:bridgesTo ngm:autonomous-agent ;
vc:bridgesTo ngm:graph-neural-network ;
vc:bridgesTo ngm:knowledge-graph ;
vc:bridgesTo ngm:protein-structure-prediction ;
vc:bridgesTo ngm:sparse-autoencoders ;
vc:bridgesTo ngm:telecollaboration ;
vc:contrastsWith ngm:convolutional-neural-network ;
vc:contrastsWith ngm:long-short-term-memory ;
vc:contrastsWith ngm:recurrent-neural-network ;
vc:contrastsWith ngm:state-space-model ;
vc:dependsOn ngm:automatic-differentiation ;
vc:dependsOn ngm:backpropagation ;
vc:dependsOn ngm:gradient-descent ;
vc:enables ngm:computer-vision ;
vc:enables ngm:explainable-ai ;
vc:enables ngm:image-captioning ;
vc:enables ngm:large-language-models ;
vc:enables ngm:machine-translation ;
vc:enables ngm:multimodal-ai-architecture-ai ;
vc:enables ngm:natural-language-processing ;
vc:enables ngm:sequence-to-sequence-learning ;
vc:enables ngm:speech-recognition ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:layer-normalisation ;
vc:hasPart ngm:query-key-value ;
vc:hasPart ngm:softmax-function ;
vc:implements ngm:scaled-dot-product-attention ;
vc:implements ngm:sequence-to-sequence-learning ;
vc:implements ngm:token-alignment ;
vc:isPartOf ngm:attention-mechanism ;
vc:isPartOf ngm:cross-attention ;
vc:isPartOf ngm:encoder-decoder-architecture ;
vc:isPartOf ngm:multi-head-attention ;
vc:isPartOf ngm:self-attention ;
vc:isPartOf ngm:transformer-architecture ;
vc:qualityScore "0.88"^^xsd:float ;
vc:relatedTo ngm:alphafold ;
vc:relatedTo ngm:batch-normalisation ;
vc:relatedTo ngm:bert ;
vc:relatedTo ngm:causal-language-modelling ;
vc:relatedTo ngm:chain-of-thought-reasoning ;
vc:relatedTo ngm:cross-attention ;
vc:relatedTo ngm:dropout ;
vc:relatedTo ngm:fine-tuning ;
vc:relatedTo ngm:gpt ;
vc:relatedTo ngm:layer-normalisation ;
vc:relatedTo ngm:masked-language-modelling ;
vc:relatedTo ngm:mixture-of-experts ;
vc:relatedTo ngm:multi-head-attention ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:neural-network-text-tokenisation ;
vc:relatedTo ngm:positional-encoding ;
vc:relatedTo ngm:prompt-engineering ;
vc:relatedTo ngm:retrieval-augmented-generation ;
vc:relatedTo ngm:self-attention ;
vc:relatedTo ngm:self-supervised-learning ;
vc:relatedTo ngm:telecollaboration ;
vc:relatedTo ngm:transfer-learning ;
vc:relatedTo ngm:vision-transformer ;
vc:requires ngm:embedding ;
vc:requires ngm:gpu-computing ;
vc:requires ngm:matrix-multiplication ;
vc:requires ngm:positional-encoding ;
vc:slug "attention-weight" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:iso-iec-22989-2022 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:computer-vision ;
vc:supports ngm:graph-neural-network ;
vc:supports ngm:multimodal-ai-architecture-ai ;
vc:supports ngm:protein-structure-prediction ;
vc:supports ngm:speech-recognition ;
vc:uses ngm:automatic-differentiation ;
vc:uses ngm:encoder-decoder-architecture ;
vc:uses ngm:feed-forward-network ;
vc:uses ngm:gpu-computing ;
vc:uses ngm:layer-normalisation ;
vc:uses ngm:neural-network ;
vc:uses ngm:transformer-architecture .
ngm:attestation a owl:Class ;
rdfs:comment "Attestation is the act of producing verifiable, signed evidence that a claim, state, or property is true, allowing a relying party to trust it without re-deriving it. In blockchain proof-of-stake consensus, validators broadcast attestations voting on the head of the chain and on checkpoints, and the aggregate of these signed votes drives finalisation. More broadly, remote attestation lets a trusted execution environment cryptographically prove its identity and integrity to a remote verifier. Attestations are typically cryptographic signatures over structured claims, and they underpin trust, accountability, and slashing-based security."@en ;
rdfs:label "Attestation"@en ;
rdfs:subClassOf ngm:cryptographic-proof ;
rdfs:subClassOf _:r2089 ;
rdfs:subClassOf _:r2090 ;
rdfs:subClassOf _:r2091 ;
vc:dependsOn ngm:slashing ;
vc:enables ngm:economic-finality ;
vc:enables ngm:finality ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:cryptographic-proof ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:consensus ;
vc:relatedTo ngm:remote-attestation ;
vc:relatedTo ngm:validator ;
vc:requires ngm:cryptography ;
vc:requires ngm:validator ;
vc:slug "attestation" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:proof-of-stake ;
vc:supports ngm:tee ;
vc:uses ngm:cryptographic-proof ;
vc:uses ngm:cryptography .
ngm:attestation-regime a skos:Concept ;
rdfs:label "Attestation Regime"@en .
ngm:attestation-report a skos:Concept ;
rdfs:label "Attestation Report"@en .
ngm:attestation-schema a skos:Concept ;
rdfs:label "Attestation Schema"@en .
ngm:attitude-control a owl:Class ;
rdfs:label "Attitude Control"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:spacecraft-guidance-navigation-and-control ;
vc:slug "attitude-control" ;
vc:sourceDomain "space-science-and-systems" .
ngm:attitude-control-thruster a owl:Class ;
rdfs:label "Attitude Control Thruster"@en ;
rdfs:subClassOf ngm:actuator ;
rdfs:subClassOf ngm:thruster ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:spacecraft-guidance-navigation-and-control ;
vc:slug "attitude-control-thruster" ;
vc:sourceDomain "space-science-and-systems" .
ngm:attitude-determination a owl:Class ;
rdfs:label "Attitude Determination"@en ;
vc:bridgesTo ngm:state-estimation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:spacecraft-guidance-navigation-and-control ;
vc:slug "attitude-determination" ;
vc:sourceDomain "space-science-and-systems" .
ngm:attitude-estimation a owl:Class ;
rdfs:comment "Attitude estimation is the process of determining the orientation of a rigid body, typically expressed as roll, pitch and yaw or as a quaternion, relative to a reference frame. It fuses measurements from an inertial measurement unit's gyroscopes, accelerometers and magnetometers using sensor-fusion algorithms such as complementary or Kalman filters to counteract individual sensor drift and noise. Accurate attitude estimation is a prerequisite for stable flight control, robot balancing and any system that must reason about its own orientation in space."@en ;
rdfs:label "Attitude Estimation"@en ;
rdfs:subClassOf ngm:sensor-fusion ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "attitude-estimation" ;
vc:sourceDomain "robotics" .
ngm:attitude-quaternion a owl:Class ;
rdfs:label "Attitude Quaternion"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:spacecraft-guidance-navigation-and-control ;
vc:slug "attitude-quaternion" ;
vc:sourceDomain "space-science-and-systems" .
ngm:attorney-general-enforcement a skos:Concept ;
rdfs:label "Attorney General Enforcement"@en .
ngm:attractor a skos:Concept ;
rdfs:label "Attractor"@en .
ngm:attribute-based-access-control a owl:Class ;
rdfs:comment "Attribute-Based Access Control (ABAC) is an authorisation model that grants or denies access by evaluating policies against attributes of the subject, resource, action, and environment rather than against static role assignments. Decisions are computed dynamically from these attributes at request time, enabling fine-grained, context-aware control. ABAC is a cornerstone of zero-trust architectures because it can express rich conditional rules without proliferating roles."@en ;
rdfs:label "Attribute-Based Access Control"@en ;
rdfs:subClassOf ngm:access-control ;
rdfs:subClassOf _:r2095 ;
rdfs:subClassOf _:r2096 ;
rdfs:subClassOf _:r2097 ;
vc:bridgesTo ngm:zero-trust-architecture ;
vc:contrastsWith ngm:role-based-access-control ;
vc:dependsOn ngm:identity-and-access-management ;
vc:enables ngm:data-minimisation ;
vc:enables ngm:zero-trust-architecture ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:access-control-policy ;
vc:hasPart ngm:authorization ;
vc:implements ngm:authorization ;
vc:isPartOf ngm:identity-and-access-management ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:audit-logging ;
vc:relatedTo ngm:cybersecurity ;
vc:requires ngm:authentication ;
vc:slug "attribute-based-access-control" ;
vc:sourceDomain "security" ;
vc:supports ngm:compliance-monitoring ;
vc:uses ngm:access-control-policy .
ngm:attribute-encoder a skos:Concept ;
rdfs:label "Attribute Encoder"@en .
ngm:attribute-evaluation a skos:Concept ;
rdfs:label "Attribute Evaluation"@en .
ngm:attribute-exchange a skos:Concept ;
rdfs:label "Attribute Exchange"@en .
ngm:attribute-preservation a skos:Concept ;
rdfs:label "Attribute Preservation"@en .
ngm:attribute-schema a skos:Concept ;
rdfs:label "Attribute Schema"@en .
ngm:attribute-sharing a owl:Class ;
rdfs:comment "Attribute Sharing refers to identity federation mechanisms that enable selective disclosure of user credentials and identity attributes across metaverse platforms and blockchain applications, using Self-Sovereign Identity (SSI) principles and decentralized identifiers to maintain user control whi..."@en ;
rdfs:label "Attribute Sharing"@en ;
rdfs:subClassOf ngm:identity-management ;
rdfs:subClassOf ngm:sc-governance-and-safety ;
rdfs:subClassOf _:r2092 ;
rdfs:subClassOf _:r2093 ;
rdfs:subClassOf _:r2094 ;
skos:broader ngm:sc-governance-and-safety ;
vc:bridgesTo ngm:did-nostr-identity ;
vc:bridgesTo ngm:identity-management ;
vc:enables ngm:credential-verification ;
vc:enables ngm:cross-platform-identity ;
vc:enables ngm:selective-disclosure ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:blockchain-anchoring ;
vc:requires ngm:decentralized-identifiers ;
vc:requires ngm:verifiable-credentials ;
vc:slug "attribute-sharing" ;
vc:sourceDomain "spatial-computing" .
ngm:attribute-translation a skos:Concept ;
rdfs:label "Attribute Translation"@en .
ngm:attribution a skos:Concept ;
rdfs:label "Attribution"@en .
ngm:attribution-capability a skos:Concept ;
rdfs:label "Attribution Capability"@en .
ngm:attribution-model a skos:Concept ;
rdfs:label "Attribution Model"@en .
ngm:attribution-modelling a skos:Concept ;
rdfs:label "Attribution Modelling"@en .
ngm:atx-standard a skos:Concept ;
rdfs:label "Atx Standard"@en .
ngm:au-intensity-coding a skos:Concept ;
rdfs:label "Au Intensity Coding"@en .
ngm:au-occurrence-detection a skos:Concept ;
rdfs:label "Au Occurrence Detection"@en .
ngm:auc a owl:Class ;
rdfs:comment "Area Under the Curve (AUC), specifically the area under the Receiver Operating Characteristic (ROC) curve (ROC-AUC or AUROC), is a single scalar performance metric for binary classifiers representing the probability that the model ranks a randomly chosen positive instance higher than a randomly c..."@en ;
rdfs:label "AUC"@en ;
rdfs:subClassOf ngm:ai-technique ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:evaluation-metric ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:artificial-intelligence ;
vc:slug "auc" ;
vc:sourceDomain "artificial-intelligence" .
ngm:auc-roc a skos:Concept ;
rdfs:label "Auc Roc"@en .
ngm:auction-mechanism a owl:Class ;
rdfs:comment "An auction mechanism is a structured rule set for allocating goods or resources and determining prices through competitive bidding among participants with private valuations. It specifies how bids are collected, who wins, and what each winner pays, with classic forms including English, Dutch, first-price sealed-bid, and Vickrey (second-price) auctions, each inducing different bidding incentives. Auction mechanisms are central to market design, online advertising, and resource allocation in multi-agent and computational settings."@en ;
rdfs:label "Auction Mechanism"@en ;
rdfs:subClassOf ngm:mechanism-design ;
rdfs:subClassOf _:r2098 ;
rdfs:subClassOf _:r2099 ;
vc:contrastsWith ngm:price-discovery ;
vc:enables ngm:programmatic-advertising ;
vc:enables ngm:resource-allocation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:incentive-mechanism ;
vc:hasPart ngm:price-discovery ;
vc:implements ngm:mechanism-design ;
vc:isPartOf ngm:economic-mechanism ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:marketplace ;
vc:relatedTo ngm:resource-management ;
vc:slug "auction-mechanism" ;
vc:sourceDomain "data" ;
vc:supports ngm:multi-agent-coordination ;
vc:supports ngm:virtual-economy ;
vc:uses ngm:game-theory .
ngm:auction-theory a owl:Class ;
rdfs:comment "Auction theory is a branch of applied mathematics, economics, and game theory that analyses competitive bidding mechanisms through which goods, services, or rights are allocated to participants. It characterises how auction format rules (e.g. English, Dutch, Vickrey), information structure (private vs. common values), and bidder strategy interact to determine allocative efficiency, revenue, and equilibrium outcomes. The field provides formal tools for designing mechanisms that incentivise truthful bidding, prevent collusion, and optimise social welfare or seller revenue. Foundational results include the Revenue Equivalence Theorem and optimal auction design frameworks due to Myerson."@en ;
rdfs:label "Auction Theory"@en ;
rdfs:subClassOf ngm:game-theory ;
rdfs:subClassOf _:r2100 ;
rdfs:subClassOf _:r2101 ;
rdfs:subClassOf _:r2102 ;
rdfs:subClassOf _:r2103 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:de-fi ;
vc:bridgesTo ngm:multi-agent-system ;
vc:bridgesTo ngm:reinforcement-learning ;
vc:contrastsWith ngm:negotiation ;
vc:contrastsWith ngm:posted-price-mechanism ;
vc:dependsOn ngm:information-theory ;
vc:dependsOn ngm:probability-theory ;
vc:enables ngm:gas-mechanism ;
vc:enables ngm:programmatic-advertising ;
vc:enables ngm:smart-contract ;
vc:enables ngm:spectrum-auction ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:combinatorial-auction ;
vc:hasPart ngm:dutch-auction ;
vc:hasPart ngm:english-auction ;
vc:hasPart ngm:vickrey-auction ;
vc:isPartOf ngm:economics ;
vc:isPartOf ngm:mechanism-design ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:market-design ;
vc:relatedTo ngm:myerson-optimal-auction ;
vc:relatedTo ngm:optimal-control ;
vc:relatedTo ngm:revenue-equivalence-theorem ;
vc:requires ngm:bayesian-inference ;
vc:requires ngm:game-theory ;
vc:requires ngm:information-asymmetry ;
vc:slug "auction-theory" ;
vc:sourceDomain "finance" ;
vc:uses ngm:incentive-compatibility ;
vc:uses ngm:mechanism-design ;
vc:uses ngm:nash-equilibrium .
ngm:audience-analytics a skos:Concept ;
rdfs:label "Audience Analytics"@en .
ngm:audience-builder a skos:Concept ;
rdfs:label "Audience Builder"@en .
ngm:audience-engagement a owl:Class ;
rdfs:comment "Audience engagement is the set of strategies and interactive mechanisms by which creators and platforms capture, sustain and deepen the attention and participation of viewers. It spans techniques such as live polls, question-and-answer sessions, gamification, reactions and personalised content, measured through metrics like watch time, interaction rate and retention. Strong audience engagement drives community growth, loyalty and monetisation across live and on-demand media."@en ;
rdfs:label "Audience Engagement"@en ;
rdfs:subClassOf ngm:content-creation ;
rdfs:subClassOf ngm:user-engagement ;
rdfs:subClassOf ngm:user-experience ;
rdfs:subClassOf _:r2104 ;
rdfs:subClassOf _:r2105 ;
rdfs:subClassOf _:r2106 ;
rdfs:subClassOf _:r2107 ;
rdfs:subClassOf _:r2108 ;
rdfs:subClassOf _:r2109 ;
rdfs:subClassOf _:r2110 ;
rdfs:subClassOf _:r2111 ;
rdfs:subClassOf _:r2112 ;
rdfs:subClassOf _:r2113 ;
rdfs:subClassOf _:r2114 ;
vc:bridgesTo ngm:augmented-reality ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:creator-economy ;
vc:bridgesTo ngm:digital-identity ;
vc:bridgesTo ngm:metaverse-content-pipeline ;
vc:bridgesTo ngm:virtual-reality ;
vc:contrastsWith ngm:passive-consumption ;
vc:dependsOn ngm:content-creation ;
vc:dependsOn ngm:content-distribution ;
vc:dependsOn ngm:data-analytics ;
vc:dependsOn ngm:social-platform ;
vc:dependsOn ngm:user-interface ;
vc:enables ngm:advertising-technology ;
vc:enables ngm:content-monetisation ;
vc:enables ngm:creator-economy ;
vc:enables ngm:digital-marketplace ;
vc:enables ngm:loyalty-programs ;
vc:enables ngm:subscription-model ;
vc:enables ngm:user-engagement ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:data-analytics ;
vc:hasPart ngm:gamification ;
vc:hasPart ngm:live-polls-and-qanda ;
vc:hasPart ngm:moderation ;
vc:hasPart ngm:real-time-communication ;
vc:hasPart ngm:recommendation-systems ;
vc:hasPart ngm:sentiment-analysis ;
vc:implements ngm:gamification ;
vc:implements ngm:hyper-personalisation ;
vc:implements ngm:natural-interaction ;
vc:implements ngm:reward-function ;
vc:isPartOf ngm:content-creation ;
vc:isPartOf ngm:live-streaming ;
vc:isPartOf ngm:user-experience ;
vc:isPartOf ngm:virtual-event ;
vc:qualityScore "0.88"^^xsd:float ;
vc:relatedTo ngm:advertising-technology ;
vc:relatedTo ngm:attention-economy ;
vc:relatedTo ngm:audience-analytics ;
vc:relatedTo ngm:augmented-reality ;
vc:relatedTo ngm:collaborative-systems-modality-filtering ;
vc:relatedTo ngm:community-management ;
vc:relatedTo ngm:content-distribution ;
vc:relatedTo ngm:creator-royalty-token ;
vc:relatedTo ngm:digital-content ;
vc:relatedTo ngm:digital-marketplace ;
vc:relatedTo ngm:esports ;
vc:relatedTo ngm:growth-hacking ;
vc:relatedTo ngm:hyper-personalisation ;
vc:relatedTo ngm:influencer-marketing ;
vc:relatedTo ngm:interaction-rate ;
vc:relatedTo ngm:live-commerce ;
vc:relatedTo ngm:metaverse-content-pipeline ;
vc:relatedTo ngm:natural-interaction ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:network-effects ;
vc:relatedTo ngm:parasocial-relationship ;
vc:relatedTo ngm:platform-economy ;
vc:relatedTo ngm:safety ;
vc:relatedTo ngm:short-form-video ;
vc:relatedTo ngm:social-proof ;
vc:relatedTo ngm:subscription-model ;
vc:relatedTo ngm:token-economy ;
vc:relatedTo ngm:user-engagement ;
vc:relatedTo ngm:user-interface ;
vc:relatedTo ngm:watch-time ;
vc:requires ngm:cdn ;
vc:requires ngm:content-creation ;
vc:requires ngm:digital-content ;
vc:requires ngm:real-time-communication ;
vc:requires ngm:user-interface ;
vc:slug "audience-engagement" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:digital-services-act ;
vc:standardizedBy ngm:ofcom ;
vc:standardizedBy ngm:online-safety-act-2023 ;
vc:supports ngm:cdn ;
vc:supports ngm:live-streaming ;
vc:supports ngm:social-platform ;
vc:supports ngm:video-streaming ;
vc:supports ngm:virtual-event ;
vc:uses ngm:artificial-intelligence ;
vc:uses ngm:blockchain ;
vc:uses ngm:collaborative-systems-modality-filtering ;
vc:uses ngm:creator-economy-platform ;
vc:uses ngm:creator-royalty-token ;
vc:uses ngm:data-analytics ;
vc:uses ngm:digital-identity ;
vc:uses ngm:edge-computing ;
vc:uses ngm:esports ;
vc:uses ngm:gamification ;
vc:uses ngm:hyper-personalisation ;
vc:uses ngm:interaction-rate ;
vc:uses ngm:live-polls-and-qanda ;
vc:uses ngm:moderation ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:network-effects ;
vc:uses ngm:parasocial-relationship ;
vc:uses ngm:recommendation-systems ;
vc:uses ngm:reward-function ;
vc:uses ngm:sentiment-analysis ;
vc:uses ngm:short-form-video ;
vc:uses ngm:token-economy ;
vc:uses ngm:virtual-reality ;
vc:uses ngm:watch-time .
ngm:audience-seating a skos:Concept ;
rdfs:label "Audience Seating"@en .
ngm:audience-segmentation a owl:Class ;
rdfs:comment "Audience segmentation is the practice of dividing a population of users or customers into distinct groups that share attributes, behaviours, or needs. Segments are derived from demographic, behavioural, contextual, and inferred signals and are used to tailor messaging, targeting, and experiences. Segmentation makes personalisation, efficient targeting, and measurement possible across marketing and product functions."@en ;
rdfs:label "Audience Segmentation"@en ;
rdfs:subClassOf ngm:digital-marketing ;
rdfs:subClassOf _:r2115 ;
rdfs:subClassOf _:r2116 ;
vc:bridgesTo ngm:privacy ;
vc:dependsOn ngm:customer-data-platform ;
vc:enables ngm:personalisation ;
vc:enables ngm:programmatic-advertising ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:a-b-testing ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:gdpr ;
vc:relatedTo ngm:recommendation-system ;
vc:relatedTo ngm:search-engine-optimisation ;
vc:requires ngm:behavioural-analytics ;
vc:requires ngm:first-party-data ;
vc:slug "audience-segmentation" ;
vc:sourceDomain "data" ;
vc:supports ngm:conversion-rate-optimisation ;
vc:supports ngm:user-engagement ;
vc:uses ngm:identity-resolution ;
vc:uses ngm:machine-learning-discipline .
ngm:audio-api a skos:Concept ;
rdfs:label "Audio API"@en .
ngm:audio-buffering a skos:Concept ;
rdfs:label "Audio Buffering"@en .
ngm:audio-capture a skos:Concept ;
rdfs:label "Audio Capture"@en .
ngm:audio-classification a skos:Concept ;
rdfs:label "Audio Classification"@en .
ngm:audio-codec a owl:Class ;
rdfs:comment "An audio codec is a technology that encodes audio into a compressed digital representation and decodes it back for playback, reducing storage and bandwidth requirements. Lossy codecs discard perceptually less important information to achieve high compression, while lossless codecs preserve the original signal exactly. Codecs balance bitrate, audio quality, latency and computational cost, and define container-independent bitstream formats. They are essential to streaming, telephony, broadcasting and immersive spatial audio."@en ;
rdfs:label "Audio Codec"@en ;
rdfs:subClassOf ngm:audio-processing ;
rdfs:subClassOf _:r2117 ;
rdfs:subClassOf _:r2118 ;
rdfs:subClassOf _:r2119 ;
rdfs:subClassOf _:r2120 ;
vc:contrastsWith ngm:lossy-compression ;
vc:contrastsWith ngm:video-codec ;
vc:dependsOn ngm:psychoacoustics ;
vc:dependsOn ngm:quantisation ;
vc:enables ngm:audio-streaming ;
vc:enables ngm:spatial-audio ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:decoder ;
vc:hasPart ngm:encoder ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:bitrate ;
vc:relatedTo ngm:sample-rate ;
vc:requires ngm:data-compression ;
vc:requires ngm:digital-signal-processing ;
vc:slug "audio-codec" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:voice-over-ip ;
vc:uses ngm:lossless-compression ;
vc:uses ngm:signal-processing .
ngm:audio-compression a owl:Class ;
rdfs:comment "Audio Compression is the process of reducing the storage size or bandwidth required for audio data, using lossy codecs that discard perceptually less-important information or lossless codecs that preserve the exact waveform. It underlies streaming, spatial audio delivery, and real-time voice communication, balancing fidelity against transmission constraints. Common lossy approaches use psychoacoustic models to remove sound outside human hearing thresholds."@en ;
rdfs:label "Audio Compression"@en ;
rdfs:subClassOf ngm:data-compression ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "audio-compression" ;
vc:sourceDomain "data" .
ngm:audio-data a skos:Concept ;
rdfs:label "Audio Data"@en .
ngm:audio-deepfake a skos:Concept ;
rdfs:label "Audio Deepfake"@en .
ngm:audio-description a skos:Concept ;
rdfs:label "Audio Description"@en .
ngm:audio-design a skos:Concept ;
rdfs:label "Audio Design"@en .
ngm:audio-diffusion a skos:Concept ;
rdfs:label "Audio Diffusion"@en .
ngm:audio-driver a owl:Class ;
rdfs:comment "An audio driver is the low-level software component that mediates between an operating system's audio subsystem and physical sound hardware, translating generic playback and capture requests into device-specific commands. It manages buffering, sample-rate conversion, latency and device enumeration, and is a prerequisite for any higher-level audio pipeline to reach speakers, headphones or microphones. In spatial and immersive computing, driver latency and buffer size directly affect the achievable audio-visual synchronisation."@en ;
rdfs:label "Audio Driver"@en ;
rdfs:subClassOf ngm:audio-system ;
rdfs:subClassOf _:r2121 ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.65"^^xsd:float ;
vc:requires ngm:audio-system ;
vc:slug "audio-driver" ;
vc:sourceDomain "spatial-computing" .
ngm:audio-engine a owl:Class ;
rdfs:comment "An Audio Engine is a software subsystem that manages the real-time synthesis, processing, mixing, and spatialisation of sound within an interactive or generative application. It abstracts hardware audio interfaces, schedules audio computation on dedicated threads or hardware DSP units, and exposes higher-level APIs for triggering, routing, and modulating sound objects in response to application events."@en ;
rdfs:label "Audio Engine"@en ;
rdfs:subClassOf ngm:audio-system ;
vc:enables ngm:audio-spatialization ;
vc:enables ngm:procedural-audio-generator ;
vc:enables ngm:spatial-audio ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:game-engine ;
vc:slug "audio-engine" ;
vc:sourceDomain "metaverse" ;
vc:uses ngm:audio-signal-processing ;
vc:uses ngm:digital-signal-processing .
ngm:audio-engineering a skos:Concept ;
rdfs:label "Audio Engineering"@en .
ngm:audio-frame-classification a skos:Concept ;
rdfs:label "Audio Frame Classification"@en .
ngm:audio-generation a owl:Class ;
rdfs:comment "Audio generation is the use of generative machine-learning models to synthesise sound — including speech, music, sound effects, and ambient audio — from inputs such as text, symbolic scores, or learned latent representations. Models learn the statistical structure of audio either in the raw waveform domain or in compressed time-frequency representations such as spectrograms, then sample new outputs that are perceptually realistic. The field encompasses text-to-speech, music generation, voice cloning, and general audio synthesis, drawing on autoregressive, diffusion, and adversarial generative architectures."@en ;
rdfs:label "Audio Generation"@en ;
rdfs:subClassOf ngm:deep-learning ;
rdfs:subClassOf ngm:generative-ai ;
rdfs:subClassOf ngm:multimodal-ai-architecture-ai ;
rdfs:subClassOf _:r2122 ;
rdfs:subClassOf _:r2123 ;
rdfs:subClassOf _:r2124 ;
vc:bridgesTo ngm:ethical-ai ;
vc:bridgesTo ngm:intellectual-property-rights-framework ;
vc:bridgesTo ngm:multimodal-ai ;
vc:bridgesTo ngm:multimodal-ai-architecture-ai ;
vc:contrastsWith ngm:audio-processing ;
vc:contrastsWith ngm:image-generation ;
vc:contrastsWith ngm:video-generation ;
vc:dependsOn ngm:audio-processing ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:feature-extraction ;
vc:dependsOn ngm:gpu-compute ;
vc:dependsOn ngm:neural-network ;
vc:dependsOn ngm:psychoacoustics ;
vc:enables ngm:extended-reality ;
vc:enables ngm:music-generation ;
vc:enables ngm:spatial-audio ;
vc:enables ngm:speech-recognition ;
vc:enables ngm:speech-synthesis ;
vc:enables ngm:text-to-speech ;
vc:enables ngm:voice-cloning ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:audio-codec ;
vc:hasPart ngm:neural-vocoder ;
vc:hasPart ngm:residual-vector-quantisation ;
vc:hasPart ngm:spectrogram ;
vc:hasPart ngm:vae ;
vc:implements ngm:autoregressive-model ;
vc:implements ngm:diffusion-model ;
vc:implements ngm:generative-adversarial-network ;
vc:implements ngm:generative-model ;
vc:implements ngm:score-based-generative-model ;
vc:qualityScore "0.91"^^xsd:float ;
vc:relatedTo ngm:latent-diffusion ;
vc:relatedTo ngm:music-information-retrieval ;
vc:relatedTo ngm:psychoacoustics ;
vc:relatedTo ngm:real-time-inference ;
vc:relatedTo ngm:reinforcement-learning-from-human-feedback ;
vc:relatedTo ngm:spectrogram ;
vc:relatedTo ngm:watermarking-service ;
vc:relatedTo ngm:waveform ;
vc:slug "audio-generation" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:mpeg-h-audio ;
vc:standardizedBy ngm:opus-codec ;
vc:supports ngm:extended-reality ;
vc:supports ngm:multimodal-ai ;
vc:supports ngm:multimodal-ai-architecture-ai ;
vc:supports ngm:music-information-retrieval ;
vc:supports ngm:natural-language-processing ;
vc:supports ngm:speech-recognition ;
vc:uses ngm:attention-mechanism ;
vc:uses ngm:autoregressive-model ;
vc:uses ngm:convolutional-neural-network ;
vc:uses ngm:diffusion-model ;
vc:uses ngm:feature-extraction ;
vc:uses ngm:flow-matching ;
vc:uses ngm:generative-adversarial-network ;
vc:uses ngm:large-language-models ;
vc:uses ngm:neural-vocoder ;
vc:uses ngm:residual-vector-quantisation ;
vc:uses ngm:transformer-architecture ;
vc:uses ngm:vae .
ngm:audio-manipulation a skos:Concept ;
rdfs:label "Audio Manipulation"@en .
ngm:audio-mixer a skos:Concept ;
rdfs:label "Audio Mixer"@en .
ngm:audio-narration a skos:Concept ;
rdfs:label "Audio Narration"@en .
ngm:audio-object a skos:Concept ;
rdfs:label "Audio Object"@en .
ngm:audio-parameters a owl:Class ;
rdfs:comment "Audio Parameters are the configurable settings and properties defining spatial audio behavior in virtual environments, including source position, direction, attenuation, room acoustics, HRTF profiles, and rendering parameters that enable realistic 3D sound experiences in VR, AR, and metaverse app..."@en ;
rdfs:label "Audio Parameters"@en ;
rdfs:subClassOf ngm:audio-configuration ;
rdfs:subClassOf ngm:sc-content-and-assets ;
rdfs:subClassOf ngm:sc-display-and-rendering ;
rdfs:subClassOf _:r2125 ;
skos:broader ngm:sc-content-and-assets ;
skos:broader ngm:sc-display-and-rendering ;
vc:bridgesTo ngm:telepresence ;
vc:enables ngm:immersive-audio ;
vc:enables ngm:spatial-sound-rendering ;
vc:enables ngm:telepresence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:audio-engine ;
vc:requires ngm:environmental-modeling ;
vc:requires ngm:hrtf-data ;
vc:slug "audio-parameters" ;
vc:sourceDomain "spatial-computing" .
ngm:audio-processing a owl:Class ;
rdfs:comment "Audio processing is the computational manipulation of digital audio signals to transform, analyse, enhance, or synthesise sound, encompassing operations such as filtering, compression, equalisation, spatialisation, and feature extraction. It operates on discrete-time representations of acoustic waveforms using algorithms drawn from digital signal processing theory, spanning both time-domain and frequency-domain approaches. Applications range from consumer media playback and telecommunications to professional studio production, speech recognition pipelines, neural audio codecs, and immersive spatial audio for extended reality environments. Machine learning has significantly expanded the discipline, enabling source separation, generative synthesis, and zero-shot audio enhancement that were previously intractable."@en ;
rdfs:label "Audio Processing"@en ;
rdfs:subClassOf ngm:digital-signal-processing ;
rdfs:subClassOf ngm:signal-processing ;
rdfs:subClassOf _:r2132 ;
rdfs:subClassOf _:r2133 ;
rdfs:subClassOf _:r2134 ;
rdfs:subClassOf _:r2135 ;
rdfs:subClassOf _:r2136 ;
rdfs:subClassOf _:r2137 ;
rdfs:subClassOf _:r2138 ;
rdfs:subClassOf _:r2139 ;
vc:bridgesTo ngm:audio-generation ;
vc:bridgesTo ngm:audio-spatialisation ;
vc:bridgesTo ngm:audio-spatialization ;
vc:bridgesTo ngm:extended-reality ;
vc:bridgesTo ngm:spatial-audio ;
vc:contrastsWith ngm:analogue-signal-processing ;
vc:contrastsWith ngm:image-processing ;
vc:dependsOn ngm:digital-signal-processing ;
vc:dependsOn ngm:fourier-analysis ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:nyquist-shannon-sampling-theorem ;
vc:dependsOn ngm:psychoacoustics ;
vc:enables ngm:audio-generation ;
vc:enables ngm:immersive-audio-system ;
vc:enables ngm:music-generation ;
vc:enables ngm:music-information-retrieval ;
vc:enables ngm:noise-cancellation ;
vc:enables ngm:spatial-audio-system ;
vc:enables ngm:speech-recognition ;
vc:enables ngm:text-to-speech ;
vc:enables ngm:voice-activity-detection ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:audio-codec ;
vc:hasPart ngm:audio-spatialisation ;
vc:hasPart ngm:digital-signal-processing ;
vc:hasPart ngm:feature-extraction ;
vc:hasPart ngm:noise-cancellation ;
vc:hasPart ngm:source-separation ;
vc:hasPart ngm:spectrogram ;
vc:hasPart ngm:waveform ;
vc:isPartOf ngm:multimedia-processing ;
vc:isPartOf ngm:signal-processing ;
vc:qualityScore "0.92"^^xsd:float ;
vc:relatedTo ngm:audio-generation ;
vc:relatedTo ngm:audio-processing-system ;
vc:relatedTo ngm:deep-learning ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:music-information-retrieval ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:psychoacoustics ;
vc:relatedTo ngm:waveform ;
vc:requires ngm:analogue-to-digital-conversion ;
vc:requires ngm:fast-fourier-transform ;
vc:requires ngm:nyquist-shannon-sampling-theorem ;
vc:requires ngm:psychoacoustics ;
vc:requires ngm:spectrogram ;
vc:slug "audio-processing" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:mpeg-h-audio ;
vc:standardizedBy ngm:opus-codec ;
vc:supports ngm:audio-generation ;
vc:supports ngm:extended-reality ;
vc:supports ngm:human-computer-interaction ;
vc:supports ngm:music-information-retrieval ;
vc:supports ngm:natural-language-processing ;
vc:supports ngm:speech-recognition ;
vc:supports ngm:telecommunications ;
vc:uses ngm:attention-mechanism ;
vc:uses ngm:audio-parameters ;
vc:uses ngm:convolutional-neural-network ;
vc:uses ngm:deep-learning ;
vc:uses ngm:diffusion-model ;
vc:uses ngm:neural-network ;
vc:uses ngm:residual-vector-quantisation ;
vc:uses ngm:transformer-architecture .
ngm:audio-processing-system a owl:Class ;
rdfs:comment "An Audio Processing System is a hardware or software subsystem responsible for capturing, transforming, and rendering audio signals within spatial computing environments. It encompasses digital signal processing, spatial audio rendering (binaural, ambisonics, HRTF), noise cancellation, speech recognition integration, and real-time mixing for immersive presence."@en ;
rdfs:label "Audio Processing System"@en ;
rdfs:subClassOf ngm:sc-display-and-rendering ;
rdfs:subClassOf _:r2126 ;
rdfs:subClassOf _:r2127 ;
rdfs:subClassOf _:r2128 ;
rdfs:subClassOf _:r2129 ;
rdfs:subClassOf _:r2130 ;
rdfs:subClassOf _:r2131 ;
skos:broader ngm:sc-display-and-rendering ;
vc:bridgesTo ngm:inference ;
vc:bridgesTo ngm:natural-language-processing ;
vc:dependsOn ngm:low-latency-networking ;
vc:enables ngm:audio-technology ;
vc:enables ngm:immersive-presence ;
vc:enables ngm:telepresence ;
vc:enables ngm:voice-user-interface ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:audio-codec ;
vc:hasPart ngm:audio-mixer ;
vc:hasPart ngm:audio-spatialization ;
vc:hasPart ngm:digital-signal-processor ;
vc:hasPart ngm:noise-cancellation ;
vc:isPartOf ngm:extended-reality ;
vc:isPartOf ngm:spatial-computing ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:haptic-feedback-system ;
vc:requires ngm:audio-driver ;
vc:requires ngm:microphone-array ;
vc:slug "audio-processing-system" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:binaural-audio ;
vc:supports ngm:real-time-communication ;
vc:uses ngm:ambisonics ;
vc:uses ngm:head-related-transfer-function ;
vc:uses ngm:signal-processing ;
vc:uses ngm:speech-recognition .
ngm:audio-recording-equipment a skos:Concept ;
rdfs:label "Audio Recording Equipment"@en .
ngm:audio-rendering-pipeline a skos:Concept ;
rdfs:label "Audio Rendering Pipeline"@en .
ngm:audio-response-module a skos:Concept ;
rdfs:label "Audio Response Module"@en .
ngm:audio-signal-processing a owl:Class ;
rdfs:comment "Audio Signal Processing is the application of signal processing theory and algorithms to the analysis, transformation, synthesis, and encoding of audio-frequency signals, operating in either the time domain or frequency domain. It encompasses filtering, equalisation, dynamic range control, time-frequency analysis, psychoacoustic coding, and spatial rendering as applied to sound reproduction, communication, and computational audition systems."@en ;
rdfs:label "Audio Signal Processing"@en ;
rdfs:subClassOf ngm:audio-processing ;
rdfs:subClassOf ngm:signal-processing ;
rdfs:subClassOf _:r2140 ;
rdfs:subClassOf _:r2141 ;
rdfs:subClassOf _:r2142 ;
rdfs:subClassOf _:r2143 ;
rdfs:subClassOf _:r2144 ;
rdfs:subClassOf _:r2145 ;
rdfs:subClassOf _:r2146 ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:bridgesTo ngm:spatial-computing ;
vc:contrastsWith ngm:audio-synthesis ;
vc:dependsOn ngm:audio-parameters ;
vc:dependsOn ngm:digital-signal-processing ;
vc:dependsOn ngm:embedded-systems ;
vc:dependsOn ngm:gpu-acceleration ;
vc:enables ngm:audio-compression ;
vc:enables ngm:audio-spatialization ;
vc:enables ngm:automatic-speech-recognition ;
vc:enables ngm:binaural-audio ;
vc:enables ngm:music-information-retrieval ;
vc:enables ngm:noise-suppression ;
vc:enables ngm:spatial-audio ;
vc:enables ngm:speech-recognition ;
vc:enables ngm:speech-synthesis ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:beamforming ;
vc:hasPart ngm:digital-filter ;
vc:hasPart ngm:dynamic-range-compression ;
vc:hasPart ngm:echo-cancellation ;
vc:hasPart ngm:equalisation ;
vc:hasPart ngm:fast-fourier-transform ;
vc:hasPart ngm:noise-cancellation ;
vc:hasPart ngm:source-separation ;
vc:implements ngm:convolution ;
vc:implements ngm:fourier-transform ;
vc:implements ngm:psychoacoustics ;
vc:qualityScore "0.92"^^xsd:float ;
vc:relatedTo ngm:audio-codec ;
vc:relatedTo ngm:audio-engine ;
vc:relatedTo ngm:audio-generation ;
vc:relatedTo ngm:audio-processing-system ;
vc:relatedTo ngm:audio-technology ;
vc:relatedTo ngm:generative-ai ;
vc:relatedTo ngm:neural-audio-codec ;
vc:requires ngm:digital-signal-processor ;
vc:requires ngm:fourier-analysis ;
vc:requires ngm:pulse-code-modulation ;
vc:requires ngm:real-time-computing ;
vc:slug "audio-signal-processing" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:telecommunications ;
vc:supports ngm:adaptive-music ;
vc:supports ngm:audio-engine ;
vc:supports ngm:audio-system ;
vc:supports ngm:hearing-aids ;
vc:supports ngm:telecommunications ;
vc:supports ngm:web-rtc ;
vc:uses ngm:audio-parameters ;
vc:uses ngm:convolution ;
vc:uses ngm:convolutional-neural-network ;
vc:uses ngm:deep-learning ;
vc:uses ngm:diffusion-model ;
vc:uses ngm:digital-signal-processing ;
vc:uses ngm:feature-extraction ;
vc:uses ngm:mel-spectrogram ;
vc:uses ngm:mfcc ;
vc:uses ngm:pulse-code-modulation ;
vc:uses ngm:recurrent-neural-network ;
vc:uses ngm:transformer .
ngm:audio-spatialisation a skos:Concept ;
rdfs:label "Audio Spatialisation"@en .
ngm:audio-spatialization a owl:Class ;
rdfs:comment "Audio Spatialization is the technique of positioning sounds in three-dimensional space using Head-Related Transfer Functions (HRTFs), binaural processing, and ambisonics to create realistic 3D audio experiences that respond to listener position and head movement in virtual reality and immersive applications."@en ;
rdfs:label "Audio Spatialization"@en ;
rdfs:subClassOf ngm:sc-display-and-rendering ;
rdfs:subClassOf ngm:spatial-audio ;
rdfs:subClassOf _:r2147 ;
rdfs:subClassOf _:r2148 ;
rdfs:subClassOf _:r2149 ;
rdfs:subClassOf _:r2150 ;
rdfs:subClassOf _:r2151 ;
rdfs:subClassOf _:r2152 ;
skos:broader ngm:sc-display-and-rendering ;
vc:bridgesTo ngm:human-computer-interaction ;
vc:bridgesTo ngm:metaverse ;
vc:bridgesTo ngm:sensor-input ;
vc:contrastsWith ngm:stereo-audio ;
vc:enables ngm:3-d-perception ;
vc:enables ngm:immersive-audio ;
vc:enables ngm:localisation ;
vc:enables ngm:presence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:ambisonics ;
vc:hasPart ngm:binaural-rendering ;
vc:hasPart ngm:hrtf-filters ;
vc:hasPart ngm:interaural-level-difference ;
vc:hasPart ngm:interaural-time-difference ;
vc:isPartOf ngm:immersive-audio ;
vc:isPartOf ngm:spatial-audio ;
vc:qualityScore "0.68"^^xsd:float ;
vc:relatedTo ngm:psychoacoustics ;
vc:relatedTo ngm:room-acoustics ;
vc:requires ngm:binaural-rendering ;
vc:requires ngm:hrtf-filters ;
vc:requires ngm:optical-tracking ;
vc:requires ngm:sensor-input ;
vc:slug "audio-spatialization" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:aes69-sofa ;
vc:supports ngm:augmented-reality ;
vc:supports ngm:virtual-reality ;
vc:uses ngm:convolution ;
vc:uses ngm:digital-signal-processing .
ngm:audio-stream a skos:Concept ;
rdfs:label "Audio Stream"@en .
ngm:audio-streaming a skos:Concept ;
rdfs:label "Audio Streaming"@en .
ngm:audio-streaming-protocol a skos:Concept ;
rdfs:label "Audio Streaming Protocol"@en .
ngm:audio-synthesis a owl:Class ;
rdfs:comment "Audio synthesis is the generation of audio signals, including speech, music, and sound effects, from symbolic, textual, or latent representations. Contemporary approaches use deep generative models such as autoregressive networks, diffusion models, and neural vocoders to produce high-fidelity waveforms. It underpins text-to-speech, music generation, and sound design, and is a core modality of generative artificial intelligence."@en ;
rdfs:label "Audio Synthesis"@en ;
rdfs:subClassOf ngm:audio-generation ;
rdfs:subClassOf ngm:deep-generative-model ;
rdfs:subClassOf ngm:generative-ai ;
rdfs:subClassOf _:r2153 ;
rdfs:subClassOf _:r2154 ;
rdfs:subClassOf _:r2155 ;
rdfs:subClassOf _:r2156 ;
rdfs:subClassOf _:r2157 ;
rdfs:subClassOf _:r2158 ;
rdfs:subClassOf _:r2159 ;
rdfs:subClassOf _:r2160 ;
vc:bridgesTo ngm:multimodal-ai ;
vc:bridgesTo ngm:natural-language-processing ;
vc:contrastsWith ngm:audio-signal-processing ;
vc:contrastsWith ngm:source-separation ;
vc:dependsOn ngm:autoregressive-model ;
vc:dependsOn ngm:convolutional-neural-network ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:recurrent-neural-network ;
vc:dependsOn ngm:transformer ;
vc:enables ngm:adaptive-music ;
vc:enables ngm:audio-generation ;
vc:enables ngm:audio-spatialization ;
vc:enables ngm:binaural-audio ;
vc:enables ngm:music-generation ;
vc:enables ngm:spatial-audio ;
vc:enables ngm:speech-synthesis ;
vc:enables ngm:text-to-speech ;
vc:enables ngm:voice-cloning ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:autoregressive-model ;
vc:hasPart ngm:flow-matching ;
vc:hasPart ngm:mel-spectrogram ;
vc:hasPart ngm:neural-audio-codec ;
vc:hasPart ngm:noise-schedule ;
vc:implements ngm:diffusion-models ;
vc:implements ngm:gan ;
vc:implements ngm:latent-diffusion ;
vc:implements ngm:score-based-model ;
vc:implements ngm:vae ;
vc:isPartOf ngm:generative-ai ;
vc:qualityScore "0.91"^^xsd:float ;
vc:relatedTo ngm:audio-deepfake ;
vc:relatedTo ngm:audio-processing ;
vc:relatedTo ngm:audio-signal-processing ;
vc:relatedTo ngm:explainable-ai ;
vc:relatedTo ngm:gan ;
vc:relatedTo ngm:multimodal-ai-architecture-ai ;
vc:relatedTo ngm:speaker-verification ;
vc:requires ngm:gpu-acceleration ;
vc:requires ngm:model-evaluation ;
vc:requires ngm:psychoacoustics ;
vc:requires ngm:training-data ;
vc:slug "audio-synthesis" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:mean-opinion-score ;
vc:supports ngm:adaptive-music ;
vc:supports ngm:audio-system ;
vc:supports ngm:audio-technology ;
vc:supports ngm:content-generation ;
vc:uses ngm:audio-codec ;
vc:uses ngm:deep-learning ;
vc:uses ngm:diffusion-models ;
vc:uses ngm:feature-extraction ;
vc:uses ngm:large-language-model ;
vc:uses ngm:mel-spectrogram ;
vc:uses ngm:neural-audio-codec ;
vc:uses ngm:neural-network ;
vc:uses ngm:reinforcement-learning-from-human-feedback ;
vc:uses ngm:zero-shot-learning .
ngm:audio-system a owl:Class ;
rdfs:comment "An Audio System is an integrated hardware and software architecture responsible for the capture, processing, transmission, and reproduction of sound signals within computing environments, including spatial audio rendering, acoustic signal processing, voice input/output, and environmental sound simulation. In spatial computing and extended reality contexts it delivers positional audio cues that reinforce presence and depth perception, coordinating microphone arrays, digital signal processors, codecs, and loudspeaker or headphone transducers. Audio systems implement psychoacoustic models — including head-related transfer functions (HRTFs) and room acoustics simulation — to produce convincing three-dimensional soundscapes. They underpin voice communication, speech interaction, accessibility features, and immersive media across consumer electronics, professional audio, telecommunication, and mixed-reality platforms."@en ;
rdfs:label "Audio System"@en ;
rdfs:subClassOf ngm:signal-processing ;
rdfs:subClassOf _:r2161 ;
rdfs:subClassOf _:r2162 ;
rdfs:subClassOf _:r2163 ;
rdfs:subClassOf _:r2164 ;
rdfs:subClassOf _:r2165 ;
rdfs:subClassOf _:r2166 ;
rdfs:subClassOf _:r2167 ;
rdfs:subClassOf _:r2168 ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:bridgesTo ngm:natural-language-processing ;
vc:contrastsWith ngm:visual-rendering-system ;
vc:dependsOn ngm:operating-system ;
vc:dependsOn ngm:real-time-computing ;
vc:enables ngm:accessibility ;
vc:enables ngm:augmented-reality ;
vc:enables ngm:speech-recognition ;
vc:enables ngm:telecollaboration ;
vc:enables ngm:voice-user-interface ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:audio-codec ;
vc:hasPart ngm:audio-spatialization ;
vc:hasPart ngm:digital-signal-processor ;
vc:hasPart ngm:microphone-array ;
vc:hasPart ngm:spatial-audio ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:ambisonics ;
vc:relatedTo ngm:audio-processing-system ;
vc:relatedTo ngm:binaural-audio ;
vc:requires ngm:acoustic-model ;
vc:requires ngm:audio-driver ;
vc:requires ngm:digital-signal-processing ;
vc:slug "audio-system" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:openal ;
vc:standardizedBy ngm:web-audio-api ;
vc:supports ngm:mixed-reality ;
vc:supports ngm:telepresence ;
vc:supports ngm:virtual-reality ;
vc:uses ngm:audio-compression ;
vc:uses ngm:head-related-transfer-function ;
vc:uses ngm:pulse-code-modulation .
ngm:audio-technology a owl:Class ;
rdfs:comment "The hardware, software, and signal-processing techniques used to capture, synthesise, spatialise, and reproduce sound within spatial computing and metaverse environments. Audio technology in immersive contexts encompasses spatial audio rendering, binaural processing, voice interaction, and real-time acoustic simulation to enhance presence and communication fidelity."@en ;
rdfs:label "Audio Technology"@en ;
rdfs:subClassOf ngm:sc-display-and-rendering ;
rdfs:subClassOf _:r2169 ;
rdfs:subClassOf _:r2170 ;
skos:broader ngm:sc-display-and-rendering ;
vc:bridgesTo ngm:telepresence ;
vc:enables ngm:virtual-presence ;
vc:enables ngm:voice-interaction ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:immersive-audio-technology ;
vc:hasPart ngm:spatial-audio ;
vc:qualityScore "0.35"^^xsd:float ;
vc:slug "audio-technology" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:audio-processing-system .
ngm:audio-video-channel a skos:Concept ;
rdfs:label "Audio Video Channel"@en .
ngm:audio-visual-environment a skos:Concept ;
rdfs:label "Audio Visual Environment"@en .
ngm:audio-visual-systems a skos:Concept ;
rdfs:label "Audio Visual Systems"@en .
ngm:audio-watermarking a skos:Concept ;
rdfs:label "Audio Watermarking"@en .
ngm:audiobook-narration a skos:Concept ;
rdfs:label "Audiobook Narration"@en .
ngm:audioseal-watermarking a skos:Concept ;
rdfs:label "Audioseal Watermarking"@en .
ngm:audiovisual-forgery a skos:Concept ;
rdfs:label "Audiovisual Forgery"@en .
ngm:audit a owl:Class ;
rdfs:comment "A systematic, independent examination of records, systems, processes, or controls carried out by a qualified party to assess their accuracy, completeness, and conformance with applicable standards, regulations, or policies. Audits generate structured, documented evidence that supports accountability, risk management, and informed decision-making by management, stakeholders, and regulators. The discipline spans financial, operational, information-security, algorithmic, and sustainability domains, each governed by domain-specific professional standards and methodologies. Audit outputs — opinions, findings, and recommendations — are foundational instruments of organisational governance and public trust."@en ;
rdfs:label "Audit"@en ;
rdfs:subClassOf ngm:accountability-mechanism ;
rdfs:subClassOf _:r2189 ;
rdfs:subClassOf _:r2190 ;
rdfs:subClassOf _:r2191 ;
rdfs:subClassOf _:r2192 ;
vc:bridgesTo ngm:ai-governance ;
vc:bridgesTo ngm:algorithmic-auditing ;
vc:bridgesTo ngm:smart-contract-audit ;
vc:contrastsWith ngm:inspection ;
vc:contrastsWith ngm:monitoring ;
vc:contrastsWith ngm:review ;
vc:dependsOn ngm:internal-controls ;
vc:dependsOn ngm:risk-assessment ;
vc:enables ngm:accountability ;
vc:enables ngm:compliance ;
vc:enables ngm:regulatory-reporting ;
vc:enables ngm:transparency ;
vc:enables ngm:trust ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:audit-finding ;
vc:hasPart ngm:audit-log ;
vc:hasPart ngm:audit-mechanism ;
vc:hasPart ngm:audit-opinion ;
vc:hasPart ngm:audit-report ;
vc:hasPart ngm:audit-trail ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:data-governance ;
vc:relatedTo ngm:fraud-detection ;
vc:relatedTo ngm:zero-trust-architecture ;
vc:requires ngm:documentation ;
vc:requires ngm:evidence ;
vc:requires ngm:independence ;
vc:requires ngm:professional-judgement ;
vc:slug "audit" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:cobit ;
vc:standardizedBy ngm:international-standards-on-auditing ;
vc:standardizedBy ngm:iso-iec-27001 ;
vc:standardizedBy ngm:soc-2 ;
vc:supports ngm:corporate-governance ;
vc:supports ngm:esg-reporting ;
vc:supports ngm:governance ;
vc:supports ngm:risk-management .
ngm:audit-and-accountability a skos:Concept ;
rdfs:label "Audit And Accountability"@en .
ngm:audit-and-certification a skos:Concept ;
rdfs:label "Audit And Certification"@en .
ngm:audit-and-compliance a skos:Concept ;
rdfs:label "Audit And Compliance"@en .
ngm:audit-automation a skos:Concept ;
rdfs:label "Audit Automation"@en .
ngm:audit-capacity a skos:Concept ;
rdfs:label "Audit Capacity"@en .
ngm:audit-committee a owl:Class ;
rdfs:comment "An audit committee is a sub-committee of an organisation's board of directors charged with overseeing financial reporting, internal controls, risk management, and the relationship with internal and external auditors. Composed primarily of independent non-executive directors, it provides assurance to the board and stakeholders on the integrity of financial statements and the effectiveness of control systems. The committee is a central pillar of corporate governance and regulatory compliance regimes."@en ;
rdfs:label "Audit Committee"@en ;
rdfs:subClassOf ngm:governance-structure ;
rdfs:subClassOf _:r2171 ;
rdfs:subClassOf _:r2172 ;
rdfs:subClassOf _:r2173 ;
vc:dependsOn ngm:corporate-governance ;
vc:enables ngm:compliance ;
vc:enables ngm:risk-management ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:compliance ;
vc:isPartOf ngm:corporate-governance ;
vc:isPartOf ngm:governance-structure ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:governance ;
vc:relatedTo ngm:prudential-regulation ;
vc:relatedTo ngm:stakeholder ;
vc:requires ngm:accountability ;
vc:requires ngm:fiduciary-duty ;
vc:slug "audit-committee" ;
vc:sourceDomain "governance" ;
vc:supports ngm:financial-stability ;
vc:uses ngm:risk-management .
ngm:audit-compliance a skos:Concept ;
rdfs:label "Audit Compliance"@en .
ngm:audit-finding a skos:Concept ;
rdfs:label "Audit Finding"@en .
ngm:audit-function a owl:Class ;
rdfs:comment "An organisational capability or dedicated unit responsible for the planning, execution, and reporting of audit activities within or on behalf of an enterprise. The audit function provides independent assurance over risk management, internal controls, and governance processes, acting as a critical third line of defence in enterprise risk frameworks."@en ;
rdfs:label "Audit Function"@en ;
rdfs:subClassOf ngm:audit ;
rdfs:subClassOf _:r2174 ;
rdfs:subClassOf _:r2175 ;
vc:enables ngm:accountability ;
vc:enables ngm:compliance ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:audit-mechanism ;
vc:hasPart ngm:audit-trail ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:governance-framework ;
vc:relatedTo ngm:risk-management-framework ;
vc:relatedTo ngm:transparency ;
vc:slug "audit-function" ;
vc:sourceDomain "governance" .
ngm:audit-log a owl:Class ;
rdfs:comment "An audit log is an immutable, chronologically ordered record of discrete system events that captures who performed an action, what action was performed, on which resource, at what time, and from what source context, providing an authoritative evidence trail for security investigation, regulatory compliance, and forensic analysis. Each entry is structured with a timestamp, actor identity, event type, affected object identifier, outcome status, and contextual metadata. Audit logs are foundational to accountability in information systems, distinguished from operational logs by their emphasis on human-actionable accountability and legal evidentiary weight rather than system diagnostics. In high-assurance environments, entries are cryptographically chained so that deletion or modification of any record invalidates all subsequent hashes, making tampering detectable."@en ;
rdfs:label "Audit Log"@en ;
rdfs:subClassOf ngm:audit-trail ;
rdfs:subClassOf _:r2176 ;
rdfs:subClassOf _:r2177 ;
rdfs:subClassOf _:r2178 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:certificate-transparency ;
vc:contrastsWith ngm:debug-log ;
vc:contrastsWith ngm:operational-log ;
vc:enables ngm:anomaly-detection ;
vc:enables ngm:regulatory-reporting ;
vc:enables ngm:security-audit ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:audit-trail ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:audit-logging ;
vc:relatedTo ngm:compliance-audit-trail ;
vc:relatedTo ngm:data-integrity ;
vc:relatedTo ngm:forensic-analysis ;
vc:relatedTo ngm:non-repudiation ;
vc:relatedTo ngm:siem ;
vc:requires ngm:identity-management ;
vc:requires ngm:tamper-evident-storage ;
vc:requires ngm:time-synchronisation ;
vc:slug "audit-log" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:common-event-format ;
vc:standardizedBy ngm:iso-27001 ;
vc:standardizedBy ngm:nist ;
vc:supports ngm:access-control ;
vc:supports ngm:compliance-framework ;
vc:supports ngm:incident-response ;
vc:supports ngm:information-security ;
vc:supports ngm:threat-detection ;
vc:uses ngm:append-only-data-structure ;
vc:uses ngm:cryptographic-hash ;
vc:uses ngm:digital-signature ;
vc:uses ngm:event-sourcing ;
vc:uses ngm:merkle-tree .
ngm:audit-logging a owl:Class ;
rdfs:comment "Audit logging is the systematic, tamper-evident recording of security-relevant events, user actions, and system operations to an immutable or append-only store, enabling retrospective forensic analysis, regulatory compliance, and incident response. Each log entry captures who performed an action, what was performed, when, from where, and the outcome, providing an authoritative chain of evidence. Audit logs are distinct from general application logs by their integrity guarantees and structured, queryable format."@en ;
rdfs:label "Audit Logging"@en ;
rdfs:subClassOf ngm:audit-log ;
rdfs:subClassOf _:r2179 ;
rdfs:subClassOf _:r2180 ;
vc:bridgesTo ngm:blockchain-immutability ;
vc:bridgesTo ngm:data-provenance ;
vc:dependsOn ngm:cryptographic-hash-function ;
vc:enables ngm:algorithmic-auditing ;
vc:enables ngm:compliance-verification ;
vc:enables ngm:forensic-analysis ;
vc:enables ngm:incident-response ;
vc:enables ngm:non-repudiation ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:identity-and-access-management ;
vc:isPartOf ngm:security-information-and-event-management ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:cybersecurity ;
vc:relatedTo ngm:information-security ;
vc:requires ngm:access-control ;
vc:requires ngm:trusted-timestamping ;
vc:slug "audit-logging" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:iso-iec-27001 ;
vc:standardizedBy ngm:nist ;
vc:supports ngm:audit-trail ;
vc:supports ngm:compliance-framework ;
vc:supports ngm:compliance-monitoring ;
vc:supports ngm:regulatory-reporting ;
vc:supports ngm:zero-trust-architecture .
ngm:audit-management a skos:Concept ;
rdfs:label "Audit Management"@en .
ngm:audit-mechanism a owl:Class ;
rdfs:comment "The specific technical or procedural instrument used to capture, preserve, and retrieve evidence of system events, user actions, or organisational activities for auditing purposes. Audit mechanisms range from low-level kernel event hooks and cryptographic tamper-evident logs to high-level workflow checkpoints and policy-enforcement records."@en ;
rdfs:label "Audit Mechanism"@en ;
rdfs:subClassOf ngm:audit ;
rdfs:subClassOf _:r2181 ;
rdfs:subClassOf _:r2182 ;
rdfs:subClassOf _:r2183 ;
rdfs:subClassOf _:r2184 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:zero-knowledge-proof ;
vc:contrastsWith ngm:monitoring ;
vc:dependsOn ngm:secure-storage ;
vc:enables ngm:audit-logging ;
vc:enables ngm:audit-trail ;
vc:enables ngm:compliance-audit-trail ;
vc:enables ngm:incident-response ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:event-log ;
vc:isPartOf ngm:security-information-and-event-management ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:data-integrity ;
vc:relatedTo ngm:forensic-investigation ;
vc:requires ngm:identity-and-access-management ;
vc:requires ngm:non-repudiation ;
vc:requires ngm:retention-policy ;
vc:slug "audit-mechanism" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:iso-27001 ;
vc:standardizedBy ngm:nist-cybersecurity-framework ;
vc:supports ngm:regulatory-compliance ;
vc:uses ngm:cryptography ;
vc:uses ngm:digital-signature ;
vc:uses ngm:hash-function ;
vc:uses ngm:immutability .
ngm:audit-mechanisms a skos:Concept ;
rdfs:label "Audit Mechanisms"@en .
ngm:audit-opinion a skos:Concept ;
rdfs:label "Audit Opinion"@en .
ngm:audit-readiness a owl:Class ;
rdfs:comment "Audit Readiness is the state in which an organization maintains the evidence, controls, documentation, and traceability needed to pass a compliance or security audit at any time with minimal preparation. It involves continuously capturing logs, change records, policy attestations, and control-effectiveness proof mapped to specific regulatory or standards requirements. Sustained readiness shifts auditing from a disruptive periodic scramble to an ongoing, verifiable posture."@en ;
rdfs:label "Audit Readiness"@en ;
rdfs:subClassOf ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:compliance ;
vc:relatedTo ngm:regulatory-compliance ;
vc:slug "audit-readiness" ;
vc:sourceDomain "governance" .
ngm:audit-record a skos:Concept ;
rdfs:label "Audit Record"@en .
ngm:audit-report a skos:Concept ;
rdfs:label "Audit Report"@en .
ngm:audit-trail a owl:Class ;
rdfs:comment "A chronological, tamper-evident record of system activities, transactions, and events that enables reconstruction and verification of sequences of operations for compliance, security, and forensic analysis."@en ;
rdfs:label "Audit Trail"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:compliance-mechanism ;
rdfs:subClassOf ngm:governance-artifact ;
rdfs:subClassOf ngm:security-record ;
rdfs:subClassOf _:r2185 ;
rdfs:subClassOf _:r2186 ;
rdfs:subClassOf _:r2187 ;
rdfs:subClassOf _:r2188 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:distributed-ledger-technology ;
vc:bridgesTo ngm:smart-contract ;
vc:contrastsWith ngm:application-debug-log ;
vc:contrastsWith ngm:mutable-log ;
vc:contrastsWith ngm:volatile-telemetry ;
vc:dependsOn ngm:event-schema ;
vc:dependsOn ngm:identity-and-access-management ;
vc:dependsOn ngm:logging-protocol ;
vc:dependsOn ngm:provenance-standard ;
vc:dependsOn ngm:siem ;
vc:dependsOn ngm:time-synchronization-service ;
vc:enables ngm:accountability ;
vc:enables ngm:breach-detection ;
vc:enables ngm:compliance-verification ;
vc:enables ngm:data-provenance ;
vc:enables ngm:forensic-analysis ;
vc:enables ngm:incident-investigation ;
vc:enables ngm:non-repudiation ;
vc:enables ngm:regulatory-audit ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:access-logs ;
vc:hasPart ngm:cryptographic-hash-chain ;
vc:hasPart ngm:digital-signature-record ;
vc:hasPart ngm:event-log ;
vc:hasPart ngm:system-state-snapshots ;
vc:hasPart ngm:timestamp-records ;
vc:hasPart ngm:transaction-records ;
vc:hasPart ngm:user-activity-logs ;
vc:isPartOf ngm:ai-governance-framework ;
vc:isPartOf ngm:algorithmic-transparency-index ;
vc:isPartOf ngm:compliance-framework ;
vc:isPartOf ngm:data-provenance ;
vc:isPartOf ngm:governance-system ;
vc:isPartOf ngm:risk-management ;
vc:isPartOf ngm:security-infrastructure ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:chain-of-custody ;
vc:relatedTo ngm:data-governance ;
vc:relatedTo ngm:evidence-management ;
vc:relatedTo ngm:privacy-enhancing-technologies ;
vc:relatedTo ngm:zero-trust-architecture ;
vc:requires ngm:clock-synchronization ;
vc:requires ngm:cryptographic-integrity-protection ;
vc:requires ngm:event-schema ;
vc:requires ngm:logging-infrastructure ;
vc:requires ngm:logging-protocol ;
vc:requires ngm:secure-storage ;
vc:requires ngm:time-synchronization-service ;
vc:slug "audit-trail" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:etsi-gr-arf-010 ;
vc:standardizedBy ngm:eu-ai-act-article-12 ;
vc:standardizedBy ngm:iso-iec-27001 ;
vc:standardizedBy ngm:nist-csf-2-0 ;
vc:standardizedBy ngm:pci-dss-v4-0 ;
vc:supports ngm:ai-governance ;
vc:supports ngm:dora-compliance ;
vc:supports ngm:eu-ai-act-regulatory-instrument ;
vc:supports ngm:gdpr-compliance ;
vc:supports ngm:iso-27001 ;
vc:supports ngm:nis2-directive ;
vc:supports ngm:pci-dss ;
vc:supports ngm:soc-2-certification ;
vc:uses ngm:append-only-database ;
vc:uses ngm:cryptographic-infrastructure ;
vc:uses ngm:digital-signature ;
vc:uses ngm:hash-function ;
vc:uses ngm:worm-storage .
ngm:audit-trail-generator a skos:Concept ;
rdfs:label "Audit Trail Generator"@en .
ngm:audit-trails a skos:Concept ;
rdfs:label "Audit Trails"@en .
ngm:auditability a owl:Class ;
rdfs:comment "Auditability is the property of a system, process, or record that allows an independent party to examine and verify its actions, decisions, and state against expected behaviour or policy. It depends on complete, tamper-evident records — logs, audit trails, and provenance — that establish who did what, when, and why, enabling accountability and compliance review. Auditability is a foundational governance requirement for trustworthy financial, blockchain, and AI systems."@en ;
rdfs:label "Auditability"@en ;
rdfs:subClassOf ngm:governance ;
rdfs:subClassOf _:r2193 ;
rdfs:subClassOf _:r2194 ;
rdfs:subClassOf _:r2195 ;
rdfs:subClassOf _:r2196 ;
vc:contrastsWith ngm:model-transparency ;
vc:enables ngm:accountability ;
vc:enables ngm:compliance ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:audit-trail ;
vc:hasPart ngm:provenance ;
vc:isPartOf ngm:governance ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:access-control ;
vc:relatedTo ngm:conformity-assessment ;
vc:relatedTo ngm:permissioned-blockchain ;
vc:requires ngm:traceability ;
vc:requires ngm:transparency ;
vc:slug "auditability" ;
vc:sourceDomain "governance" ;
vc:supports ngm:governance-framework ;
vc:supports ngm:regulatory-compliance ;
vc:uses ngm:monitoring .
ngm:augmented-bonding-curve-communities a skos:Concept ;
rdfs:label "Augmented Bonding Curve Communities"@en .
ngm:augmented-connected-workforce a owl:Class ;
rdfs:comment "The Augmented Connected Workforce (ACW) is a digitally enhanced work paradigm in which human capabilities are amplified through the seamless integration of AI, augmented reality, virtual reality, and IoT technologies, enabling immersive spatial interactions and real-time connectivity across distributed teams. ACW systems overlay contextual digital information onto physical workspaces and connect workers to shared virtual environments, boosting safety, training efficacy, and operational coordination. It is recognised by Gartner as a strategic technology trend reshaping how organisations design, operate, and evolve their human workforce."@en ;
rdfs:label "Augmented Connected Workforce"@en ;
rdfs:subClassOf ngm:metaverse-and-telecollaboration ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf _:r2197 ;
rdfs:subClassOf _:r2198 ;
skos:broader ngm:sc-platform-and-environment ;
vc:bridgesTo ngm:telecollaboration ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:collaboration-platform ;
vc:relatedTo ngm:digital-workplace-platform ;
vc:relatedTo ngm:immersive-workspaces ;
vc:relatedTo ngm:telecollaboration ;
vc:requires ngm:extended-reality ;
vc:requires ngm:immersive-technology ;
vc:slug "augmented-connected-workforce" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:augmented-reality ;
vc:uses ngm:internet-of-things ;
vc:uses ngm:virtual-reality ;
vc:uses ngm:wearable-computing-platform .
ngm:augmented-reality a owl:Class ;
rdfs:comment "Augmented Reality (AR) is a technology that overlays digital content onto the real world in real-time, enhancing users' perception of their physical environment through smartphones, head-mounted displays, or smart glasses. AR systems require coupling of real and virtual environments, real-time interaction, and precise 3D registration of virtual objects aligned with physical space."@en ;
rdfs:label "Augmented Reality"@en ;
rdfs:subClassOf ngm:extended-reality ;
rdfs:subClassOf ngm:extended-reality-xr ;
rdfs:subClassOf _:r2212 ;
rdfs:subClassOf _:r2213 ;
rdfs:subClassOf _:r2214 ;
rdfs:subClassOf _:r2215 ;
rdfs:subClassOf _:r2216 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:internet-of-things ;
vc:contrastsWith ngm:mixed-reality ;
vc:contrastsWith ngm:virtual-reality ;
vc:dependsOn ngm:edge-computing ;
vc:dependsOn ngm:gpu ;
vc:dependsOn ngm:simultaneous-localisation-and-mapping ;
vc:enables ngm:contextual-information-display ;
vc:enables ngm:immersive-experiences ;
vc:enables ngm:industrial-maintenance ;
vc:enables ngm:remote-assistance ;
vc:enables ngm:surgical-navigation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:marker-based-tracking ;
vc:hasPart ngm:spatial-mapping ;
vc:isPartOf ngm:metaverse ;
vc:isPartOf ngm:spatial-computing ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:gesture-recognition ;
vc:relatedTo ngm:scene-understanding ;
vc:requires ngm:computer-vision ;
vc:requires ngm:inertial-measurement-unit ;
vc:requires ngm:real-time-rendering ;
vc:slug "augmented-reality" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:open-xr ;
vc:standardizedBy ngm:web-xr ;
vc:supports ngm:digital-twin ;
vc:supports ngm:remote-collaboration ;
vc:uses ngm:depth-sensor ;
vc:uses ngm:head-mounted-display ;
vc:uses ngm:machine-learning-discipline .
ngm:augmented-reality-ar a owl:Class ;
rdfs:comment "Interactive system that overlays digital content (visual, audio, haptic) onto the physical environment in real time, enabling spatially-registered blended experiences where virtual information enhances physical perception."@en ;
rdfs:label "Augmented Reality (AR)"@en ;
rdfs:subClassOf ngm:extended-reality-xr ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf _:r2199 ;
rdfs:subClassOf _:r2200 ;
rdfs:subClassOf _:r2201 ;
rdfs:subClassOf _:r2202 ;
rdfs:subClassOf _:r2203 ;
rdfs:subClassOf _:r2204 ;
rdfs:subClassOf _:r2205 ;
rdfs:subClassOf _:r2206 ;
rdfs:subClassOf _:r2207 ;
skos:broader ngm:sc-platform-and-environment ;
vc:bridgesTo ngm:sensor-input ;
vc:dependsOn ngm:6-do-f-tracking ;
vc:dependsOn ngm:depth-sensing ;
vc:dependsOn ngm:environmental-understanding ;
vc:dependsOn ngm:slam ;
vc:enables ngm:contextual-information-overlay ;
vc:enables ngm:interactive-holograms ;
vc:enables ngm:object-recognition ;
vc:enables ngm:spatial-anchoring ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ar-display-device ;
vc:hasPart ngm:digital-content-overlay ;
vc:hasPart ngm:environmental-sensor ;
vc:hasPart ngm:spatial-tracking-system ;
vc:isPartOf ngm:extended-reality-xr ;
vc:isPartOf ngm:spatial-computing ;
vc:isPartOf ngm:spatial-computing-paradigm ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:camera ;
vc:requires ngm:computer-vision ;
vc:requires ngm:real-time-rendering ;
vc:requires ngm:spatial-mapping ;
vc:slug "augmented-reality-ar" ;
vc:sourceDomain "spatial-computing" .
ngm:augmented-reality-collaboration a owl:Class ;
rdfs:comment "\"Collaborative work where geographically distributed team members share a common augmented reality environment, viewing and manipulating virtual 3D objects overlaid on their respective physical spaces whilst communicating via spatial audio and holographic avatars, enabling hybrid physical-virtual..."@en ;
rdfs:label "Augmented Reality Collaboration"@en ;
rdfs:subClassOf ngm:telecollaboration ;
rdfs:subClassOf ngm:telepresence ;
rdfs:subClassOf _:r2208 ;
rdfs:subClassOf _:r2209 ;
vc:enables ngm:collaborative-systems-modality-design ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:web-rtc ;
vc:slug "augmented-reality-collaboration" ;
vc:sourceDomain "distributed-collaboration" .
ngm:augmented-reality-content a skos:Concept ;
rdfs:label "Augmented Reality Content"@en .
ngm:augmented-reality-content-creation a skos:Concept ;
rdfs:label "Augmented Reality Content Creation"@en .
ngm:augmented-reality-framework a skos:Concept ;
rdfs:label "Augmented Reality Framework"@en .
ngm:augmented-reality-tracking a owl:Class ;
rdfs:comment "Augmented reality tracking is the continuous estimation of a device's position and orientation relative to the physical environment so that virtual content can be registered and rendered as if anchored in the real world. It fuses camera imagery, inertial measurements and depth or feature data to maintain a stable six-degree-of-freedom pose at interactive rates. Robust tracking is the foundation of believable spatial overlay, addressing drift, occlusion and relocalisation."@en ;
rdfs:label "Augmented Reality Tracking"@en ;
rdfs:subClassOf ngm:pose-estimation ;
rdfs:subClassOf _:r2210 ;
rdfs:subClassOf _:r2211 ;
vc:bridgesTo ngm:augmented-reality ;
vc:bridgesTo ngm:spatial-mapping ;
vc:dependsOn ngm:visual-slam ;
vc:enables ngm:localisation ;
vc:enables ngm:marker-based-tracking ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:marker-based-tracking ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:localisation ;
vc:relatedTo ngm:tracking ;
vc:requires ngm:pose-estimation ;
vc:requires ngm:slam ;
vc:slug "augmented-reality-tracking" ;
vc:sourceDomain "robotics" ;
vc:supports ngm:augmented-reality ;
vc:supports ngm:spatial-computing ;
vc:uses ngm:computer-vision ;
vc:uses ngm:extended-kalman-filter ;
vc:uses ngm:kalman-filter ;
vc:uses ngm:sensor-fusion .
ngm:aum-shinrikyo-biological-programme a skos:Concept ;
rdfs:label "Aum Shinrikyo Biological Programme"@en .
ngm:aura-blockchain a skos:Concept ;
rdfs:label "Aura Blockchain"@en .
ngm:aura-finance a skos:Concept ;
rdfs:label "Aura Finance"@en .
ngm:aurora a owl:Class ;
rdfs:label "Aurora"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:heliophysics ;
vc:slug "aurora" ;
vc:sourceDomain "space-science-and-systems" .
ngm:austerity a skos:Concept ;
rdfs:label "Austerity"@en .
ngm:austrac a skos:Concept ;
rdfs:label "Austrac"@en .
ngm:australia-group a skos:Concept ;
rdfs:label "Australia Group"@en .
ngm:australia-group-export-controls a skos:Concept ;
rdfs:label "Australia Group Export Controls"@en .
ngm:austrian-economics a owl:Class ;
rdfs:comment "Austrian Economics is a heterodox school of economic thought originating in late 19th-century Vienna, most associated with Carl Menger, Ludwig von Mises, and Friedrich Hayek. It emphasises methodological individualism, the subjective theory of value, and the role of entrepreneurship in coordinating dispersed knowledge through price signals. The school critiques central planning and Keynesian intervention on the grounds that spontaneous market order cannot be replicated by any central authority, and that artificial credit expansion inevitably produces malinvestment and business cycles. Austrian insights have strongly influenced Bitcoin monetary theory, particularly the argument that hard-capped supply reproduces the properties of sound, commodity-backed money."@en ;
rdfs:label "Austrian Economics"@en ;
rdfs:subClassOf ngm:economics ;
vc:contrastsWith ngm:inflation-control ;
vc:contrastsWith ngm:monetary-sovereignty ;
vc:enables ngm:bitcoin-proof-of-work-protocol-value-proposition ;
vc:enables ngm:hyperbitcoinization ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:inflation ;
vc:relatedTo ngm:monetary-policy-implementation ;
vc:relatedTo ngm:sound-money ;
vc:slug "austrian-economics" ;
vc:sourceDomain "finance" ;
vc:supports ngm:bitcoin-proof-of-work-protocol-standard ;
vc:supports ngm:decentralisation .
ngm:austrian-hard-money-theory a owl:Class ;
rdfs:comment "Austrian hard money theory is the monetary doctrine, rooted in the Austrian School of economics, holding that sound money must have a credibly fixed or hard-to-inflate supply so it can reliably preserve purchasing power over time. It favours commodity-like monies (historically gold, latterly Bitcoin) over fiat currencies whose supply central banks can expand at will, arguing that inflation distorts price signals and the capital structure. The theory underpins Bitcoin's framing as a deflationary store of value with an absolutely scarce, algorithmically capped issuance."@en ;
rdfs:label "Austrian Hard Money Theory"@en ;
rdfs:subClassOf ngm:economics ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol-as-money ;
vc:relatedTo ngm:store-of-value ;
vc:slug "austrian-hard-money-theory" ;
vc:sourceDomain "blockchain" .
ngm:authentic-content a skos:Concept ;
rdfs:label "Authentic Content"@en .
ngm:authentic-internet a skos:Concept ;
rdfs:label "Authentic Internet"@en .
ngm:authentic-ugc a skos:Concept ;
rdfs:label "Authentic Ugc"@en .
ngm:authenticated-encryption a owl:Class ;
rdfs:comment "Authenticated encryption is a class of symmetric cryptographic schemes that simultaneously provide confidentiality, integrity and authenticity of a message in a single operation. Authenticated encryption with associated data (AEAD) additionally binds unencrypted header data to the ciphertext, so any tampering with the message or its context is detected on decryption. Modern AEAD constructions such as AES-GCM and ChaCha20-Poly1305 are the recommended default for secure communication because they avoid the pitfalls of composing encryption and authentication separately."@en ;
rdfs:label "Authenticated Encryption"@en ;
rdfs:subClassOf ngm:encryption ;
rdfs:subClassOf _:r2217 ;
rdfs:subClassOf _:r2218 ;
vc:enables ngm:data-confidentiality ;
vc:enables ngm:data-integrity ;
vc:enables ngm:secure-communication ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:aes-gcm ;
vc:isPartOf ngm:cryptography ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:cryptography ;
vc:relatedTo ngm:hash-function ;
vc:requires ngm:cryptographic-protocol ;
vc:requires ngm:key-management ;
vc:slug "authenticated-encryption" ;
vc:sourceDomain "security" ;
vc:supports ngm:tls ;
vc:supports ngm:tls-1-3 ;
vc:uses ngm:message-authentication-code ;
vc:uses ngm:nonce ;
vc:uses ngm:symmetric-encryption .
ngm:authentication a owl:Class ;
rdfs:comment "Authentication is the security process of verifying that a claimed identity of a user, device, application, or service is genuine before granting access to protected resources. It is fundamentally distinct from authorisation, which determines what permissions an authenticated principal possesses. Authentication evidence is categorised into knowledge factors (passwords, PINs, security questions), possession factors (hardware security keys, TOTP devices, mobile authenticators), and inherence factors (biometrics such as fingerprint or facial recognition), with cryptographic proofs (digital signatures, TLS client certificates, FIDO2 passkeys) increasingly replacing shared-secret schemes. Modern secure systems combine multiple independent factors through multi-factor authentication to achieve strong resistance against credential theft, phishing, replay attacks, and session hijacking."@en ;
rdfs:label "Authentication"@en ;
rdfs:subClassOf ngm:identity-and-access-management ;
rdfs:subClassOf _:r2234 ;
rdfs:subClassOf _:r2235 ;
rdfs:subClassOf _:r2236 ;
vc:bridgesTo ngm:decentralised-identity ;
vc:bridgesTo ngm:self-sovereign-identity ;
vc:bridgesTo ngm:verifiable-credentials ;
vc:contrastsWith ngm:anonymity ;
vc:contrastsWith ngm:authorisation ;
vc:dependsOn ngm:digital-signatures ;
vc:dependsOn ngm:key-management ;
vc:dependsOn ngm:secure-communication ;
vc:enables ngm:access-control ;
vc:enables ngm:authorisation ;
vc:enables ngm:session-management ;
vc:enables ngm:single-sign-on ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:fido2 ;
vc:implements ngm:oauth-2-0 ;
vc:implements ngm:open-id-connect ;
vc:implements ngm:saml ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:biometrics ;
vc:relatedTo ngm:federation ;
vc:relatedTo ngm:identity-provider ;
vc:relatedTo ngm:multi-factor-authentication ;
vc:relatedTo ngm:threat-model ;
vc:requires ngm:cryptographic-infrastructure ;
vc:requires ngm:cryptography ;
vc:requires ngm:identity-verification ;
vc:slug "authentication" ;
vc:sourceDomain "security" ;
vc:supports ngm:compliance ;
vc:supports ngm:privacy ;
vc:supports ngm:zero-trust-architecture .
ngm:authentication-engine a skos:Concept ;
rdfs:label "Authentication Engine"@en .
ngm:authentication-handler a skos:Concept ;
rdfs:label "Authentication Handler"@en .
ngm:authentication-layer a skos:Concept ;
rdfs:label "Authentication Layer"@en .
ngm:authentication-mechanism a owl:Class ;
rdfs:comment "An authentication mechanism is a technical procedure or protocol that verifies the claimed identity of a user, device, or system before granting access to protected resources. Such mechanisms range from simple password checks to sophisticated cryptographic challenges and biometric verification. They form the foundational layer of access control systems, ensuring that only authorised principals can interact with sensitive data or services. The strength and appropriateness of a chosen mechanism directly influences the overall security posture of a system."@en ;
rdfs:label "Authentication Mechanism"@en ;
rdfs:subClassOf ngm:authentication ;
rdfs:subClassOf _:r2219 ;
rdfs:subClassOf _:r2220 ;
rdfs:subClassOf _:r2221 ;
rdfs:subClassOf _:r2222 ;
rdfs:subClassOf _:r2223 ;
vc:bridgesTo ngm:decentralised-identity ;
vc:bridgesTo ngm:self-sovereign-identity ;
vc:dependsOn ngm:cryptographic-protocol ;
vc:dependsOn ngm:digital-identity ;
vc:dependsOn ngm:trust-anchor ;
vc:enables ngm:authorisation ;
vc:enables ngm:multi-factor-authentication ;
vc:enables ngm:zero-trust-architecture ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:challenge-response-protocol ;
vc:hasPart ngm:verifiable-credential-standard ;
vc:isPartOf ngm:identity-and-access-management ;
vc:isPartOf ngm:security-protocol ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:session-management ;
vc:requires ngm:cryptographic-infrastructure ;
vc:requires ngm:cryptographic-keys ;
vc:requires ngm:secure-channel ;
vc:slug "authentication-mechanism" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:fido2 ;
vc:standardizedBy ngm:oauth-2-0 ;
vc:standardizedBy ngm:open-id-connect ;
vc:supports ngm:access-control ;
vc:supports ngm:cybersecurity ;
vc:supports ngm:non-repudiation ;
vc:uses ngm:authentication-standards ;
vc:uses ngm:biometric-data ;
vc:uses ngm:one-time-password .
ngm:authentication-protocol a owl:Class ;
rdfs:comment "A defined sequence of exchanges through which one party proves its identity to another over a communication channel."@en ;
rdfs:label "Authentication Protocol"@en ;
rdfs:subClassOf ngm:cryptographic-protocol ;
rdfs:subClassOf _:r2224 ;
rdfs:subClassOf _:r2225 ;
vc:bridgesTo ngm:oauth ;
vc:enables ngm:access-control ;
vc:enables ngm:multi-factor-authentication ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:authentication ;
vc:requires ngm:cryptography ;
vc:slug "authentication-protocol" ;
vc:sourceDomain "security" .
ngm:authentication-record a skos:Concept ;
rdfs:label "Authentication Record"@en .
ngm:authentication-schema a skos:Concept ;
rdfs:label "Authentication Schema"@en .
ngm:authentication-server a skos:Concept ;
rdfs:label "Authentication Server"@en .
ngm:authentication-service a owl:Class ;
rdfs:comment "An authentication service is a system component that verifies the identity of users, devices, or applications attempting to access protected resources. It validates credentials against stored identity information and issues tokens or assertions that enable authorised access across applications and services, forming the foundation of secure identity management in enterprise systems."@en ;
rdfs:label "Authentication Service"@en ;
rdfs:subClassOf ngm:infra-security-and-identity ;
rdfs:subClassOf ngm:security-service ;
rdfs:subClassOf _:r2226 ;
rdfs:subClassOf _:r2227 ;
rdfs:subClassOf _:r2228 ;
rdfs:subClassOf _:r2229 ;
skos:broader ngm:infra-security-and-identity ;
vc:bridgesTo ngm:cryptography ;
vc:bridgesTo ngm:decentralised-identity ;
vc:bridgesTo ngm:security-services ;
vc:contrastsWith ngm:authorisation ;
vc:enables ngm:authorisation ;
vc:enables ngm:federated-identity ;
vc:enables ngm:multi-factor-authentication ;
vc:enables ngm:session-management ;
vc:enables ngm:single-sign-on ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:credential-store ;
vc:hasPart ngm:identity-provider ;
vc:hasPart ngm:token-service ;
vc:implements ngm:credential-validation ;
vc:implements ngm:identity-verification ;
vc:implements ngm:oauth-2-0 ;
vc:implements ngm:open-id-connect ;
vc:isPartOf ngm:identity-and-access-management ;
vc:isPartOf ngm:zero-trust-architecture ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:access-control ;
vc:relatedTo ngm:security-token ;
vc:requires ngm:cryptographic-infrastructure ;
vc:requires ngm:cryptography ;
vc:slug "authentication-service" ;
vc:sourceDomain "security" ;
vc:supports ngm:adaptive-authentication ;
vc:supports ngm:passwordless-authentication ;
vc:uses ngm:json-data-interchange-format-web-token ;
vc:uses ngm:lightweight-directory-access-protocol ;
vc:uses ngm:saml .
ngm:authentication-standards a owl:Class ;
rdfs:comment "Authentication Standards encompass protocols and specifications for verifying user identity in digital systems, particularly FIDO2 and WebAuthn standards that enable passwordless, phishing-resistant authentication using public key cryptography and hardware authenticators for secure access to metaverse platforms and blockchain applications."@en ;
rdfs:label "Authentication Standards"@en ;
rdfs:subClassOf ngm:security-standards ;
rdfs:subClassOf _:r2230 ;
rdfs:subClassOf _:r2231 ;
rdfs:subClassOf _:r2232 ;
rdfs:subClassOf _:r2233 ;
vc:bridgesTo ngm:access-control ;
vc:bridgesTo ngm:blockchain-identity ;
vc:bridgesTo ngm:did-nostr-identity ;
vc:contrastsWith ngm:password-authentication ;
vc:dependsOn ngm:asymmetric-cryptography ;
vc:enables ngm:multi-factor-authentication ;
vc:enables ngm:passwordless-authentication ;
vc:enables ngm:phishing-resistance ;
vc:enables ngm:secure-platform-access ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:fido2 ;
vc:hasPart ngm:web-authn ;
vc:implements ngm:nist-sp-800-63 ;
vc:isPartOf ngm:identity-and-access-management ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:oauth-2-0 ;
vc:relatedTo ngm:open-id-connect ;
vc:requires ngm:client-implementation ;
vc:requires ngm:digital-certificate ;
vc:requires ngm:hardware-authenticators ;
vc:requires ngm:public-key-cryptography ;
vc:slug "authentication-standards" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:fido-alliance ;
vc:standardizedBy ngm:w3-c ;
vc:supports ngm:decentralized-identity ;
vc:supports ngm:single-sign-on ;
vc:uses ngm:biometric-verification ;
vc:uses ngm:challenge-response-protocol .
ngm:authentication-system a owl:Class ;
rdfs:comment "An authentication system is an infrastructure component responsible for verifying the claimed identity of users, devices, or services before granting access to protected resources. It integrates credential management, identity verification workflows, session management, and integration with downstream access control mechanisms to enforce the principle that only legitimate principals can initiate authenticated sessions. Authentication systems range from simple password databases to federated multi-factor frameworks spanning organisational boundaries."@en ;
rdfs:label "Authentication System"@en ;
rdfs:subClassOf ngm:authentication ;
vc:enables ngm:access-control ;
vc:enables ngm:zero-trust-architecture ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:authentication-standards ;
vc:relatedTo ngm:decentralised-identity ;
vc:relatedTo ngm:identity-provider ;
vc:slug "authentication-system" ;
vc:sourceDomain "security" ;
vc:uses ngm:cryptographic-signature ;
vc:uses ngm:multi-factor-authentication ;
vc:uses ngm:oauth-2-0 ;
vc:uses ngm:open-id-connect .
ngm:authentication-systems a skos:Concept ;
rdfs:label "Authentication Systems"@en .
ngm:authenticity-certification a owl:Class ;
rdfs:comment "A formal process or credential that attests to the genuine origin, integrity, and provenance of a digital or physical artefact, typically employing cryptographic signing, trusted third-party attestation, or standards-based metadata embedding. Authenticity certification enables recipients to verify that content has not been altered and originated from a claimed source."@en ;
rdfs:label "Authenticity Certification"@en ;
rdfs:subClassOf ngm:content-authenticity ;
vc:enables ngm:provenance-verification ;
vc:enables ngm:trust ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:certificate-authority ;
vc:relatedTo ngm:data-provenance ;
vc:relatedTo ngm:deepfake-detection ;
vc:slug "authenticity-certification" ;
vc:sourceDomain "security" ;
vc:uses ngm:cryptography ;
vc:uses ngm:digital-signature ;
vc:uses ngm:hash-function .
ngm:authenticity-detection a skos:Concept ;
rdfs:label "Authenticity Detection"@en .
ngm:authored-content a skos:Concept ;
rdfs:label "Authored Content"@en .
ngm:authoring-tool a owl:Class ;
rdfs:comment "Software application for creating or editing immersive content, including 3D models, environments, interactions, and multimedia assets for metaverse experiences."@en ;
rdfs:label "Authoring Tool"@en ;
rdfs:subClassOf ngm:digital-content-creation ;
rdfs:subClassOf ngm:sc-content-and-assets ;
rdfs:subClassOf _:r2237 ;
rdfs:subClassOf _:r2238 ;
rdfs:subClassOf _:r2239 ;
rdfs:subClassOf _:r2240 ;
skos:broader ngm:sc-content-and-assets ;
vc:bridgesTo ngm:computer-vision ;
vc:enables ngm:3d-modelling ;
vc:enables ngm:content-creation ;
vc:enables ngm:interactive-experience-development ;
vc:enables ngm:scene-design ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:asset-pipeline ;
vc:hasPart ngm:editor-interface ;
vc:hasPart ngm:generative-design-tool ;
vc:hasPart ngm:preview-system ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:compute-infrastructure ;
vc:requires ngm:graphics-api ;
vc:slug "authoring-tool" ;
vc:sourceDomain "spatial-computing" .
ngm:authorisation a owl:Class ;
rdfs:comment "Authorisation is the process of determining and enforcing whether an authenticated principal—user, service, or device—has the right to perform a requested action on a protected resource. It operates downstream of authentication, translating verified identity claims into permitted operations according to configured access policies. Modern authorisation frameworks encompass role-based, attribute-based, relationship-based, and policy-as-code access control models, each balancing expressiveness with enforcement performance. Robust authorisation design underpins regulatory compliance, auditability, and the principle of least privilege across distributed digital systems."@en ;
rdfs:label "Authorisation"@en ;
rdfs:subClassOf ngm:access-control ;
rdfs:subClassOf _:r2241 ;
rdfs:subClassOf _:r2242 ;
rdfs:subClassOf _:r2243 ;
rdfs:subClassOf _:r2244 ;
rdfs:subClassOf _:r2245 ;
rdfs:subClassOf _:r2246 ;
rdfs:subClassOf _:r2247 ;
vc:bridgesTo ngm:ai-agent ;
vc:bridgesTo ngm:decentralised-identity ;
vc:bridgesTo ngm:smart-contract ;
vc:contrastsWith ngm:accountability ;
vc:contrastsWith ngm:authentication ;
vc:dependsOn ngm:cryptography ;
vc:dependsOn ngm:digital-identity ;
vc:dependsOn ngm:secure-token-service ;
vc:enables ngm:audit-trail ;
vc:enables ngm:compliance-monitoring ;
vc:enables ngm:least-privilege ;
vc:enables ngm:privacy-controls ;
vc:enables ngm:zero-trust-architecture ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:access-control ;
vc:hasPart ngm:attribute-based-access-control ;
vc:hasPart ngm:relationship-based-access-control ;
vc:hasPart ngm:role-based-access-control ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:data-governance ;
vc:relatedTo ngm:identity-and-access-management ;
vc:relatedTo ngm:privilege-escalation ;
vc:relatedTo ngm:separation-of-duties ;
vc:requires ngm:authentication ;
vc:requires ngm:identity-management ;
vc:requires ngm:policy-engine ;
vc:slug "authorisation" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:iso-iec-27001 ;
vc:standardizedBy ngm:oauth-2-0 ;
vc:standardizedBy ngm:open-id-connect ;
vc:standardizedBy ngm:xacml ;
vc:uses ngm:access-token ;
vc:uses ngm:compliance-framework ;
vc:uses ngm:json-data-interchange-format-web-token ;
vc:uses ngm:oauth-2-0 ;
vc:uses ngm:open-policy-agent .
ngm:authorisation-engine a skos:Concept ;
rdfs:label "Authorisation Engine"@en .
ngm:authorised-economic-operator a skos:Concept ;
rdfs:label "Authorised Economic Operator"@en .
ngm:authorised-representative a owl:Class ;
rdfs:comment "A natural or legal person located or established in the EU who has received and accepted a written mandate from a non-EU provider of an AI system or general-purpose AI model to perform regulatory tasks on its behalf, including maintaining technical documentation, cooperating with market surveillance authorities, and serving as the primary EU contact point under the EU AI Act."@en ;
rdfs:label "Authorised Representative"@en ;
rdfs:subClassOf ngm:sc-governance-and-safety ;
rdfs:subClassOf _:r2248 ;
rdfs:subClassOf _:r2249 ;
skos:broader ngm:sc-governance-and-safety ;
vc:bridgesTo ngm:governance ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:privacy ;
vc:relatedTo ngm:risk-management ;
vc:requires ngm:compliance-framework ;
vc:requires ngm:eu-ai-act-regulatory-instrument ;
vc:slug "authorised-representative" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:governance-framework ;
vc:supports ngm:ai-governance-and-ethics ;
vc:supports ngm:governance .
ngm:authoritative-data-source a skos:Concept ;
rdfs:label "Authoritative Data Source"@en .
ngm:authoritative-name-server a skos:Concept ;
rdfs:label "Authoritative Name Server"@en .
ngm:authority-arbitration a skos:Concept ;
rdfs:label "Authority Arbitration"@en .
ngm:authorization a owl:Class ;
rdfs:comment "The security process that determines what actions an authenticated principal is permitted to perform on specific resources within a system. Authorization evaluates the subject's identity, role, attributes, and contextual factors against a policy to produce an access decision, operating as a distinct layer from authentication and separate from audit."@en ;
rdfs:label "Authorization"@en ;
rdfs:subClassOf ngm:access-control ;
rdfs:subClassOf _:r2250 ;
rdfs:subClassOf _:r2251 ;
vc:enables ngm:compliance ;
vc:enables ngm:privacy ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:audit ;
vc:relatedTo ngm:zero-trust-architecture ;
vc:requires ngm:authentication ;
vc:requires ngm:identity-and-access-management ;
vc:slug "authorization" ;
vc:sourceDomain "security" ;
vc:uses ngm:policy-decision-point ;
vc:uses ngm:role-based-access-control .
ngm:authorization-code-flow a skos:Concept ;
rdfs:label "Authorization Code Flow"@en .
ngm:authorization-framework a skos:Concept ;
rdfs:label "Authorization Framework"@en .
ngm:authorized-participant a skos:Concept ;
rdfs:label "Authorized Participant"@en .
ngm:authorized-participant-network a skos:Concept ;
rdfs:label "Authorized Participant Network"@en .
ngm:auto-gen a owl:Class ;
rdfs:comment "AutoGen is an open-source multi-agent conversation framework originating from Microsoft Research that defines conversable agents — autonomous entities backed by large language models, tools, or human inputs — which coordinate through structured message exchange to decompose and complete complex tasks. The framework introduced the conversable-agent abstraction as a unified primitive supporting LLM-powered reasoning, code execution, and adaptive human participation within a single coherent programming model. Forked in 2025 as the community-governed AG2 project and simultaneously merged by Microsoft into the broader Microsoft Agent Framework combining AutoGen agent abstractions with Semantic Kernel enterprise features."@en ;
rdfs:label "AutoGen"@en ;
rdfs:subClassOf ngm:agent-frameworks ;
rdfs:subClassOf ngm:multi-agent-systems ;
rdfs:subClassOf _:r2256 ;
rdfs:subClassOf _:r2257 ;
rdfs:subClassOf _:r2258 ;
rdfs:subClassOf _:r2259 ;
rdfs:subClassOf _:r2260 ;
rdfs:subClassOf _:r2261 ;
rdfs:subClassOf _:r2262 ;
rdfs:subClassOf _:r2263 ;
rdfs:subClassOf _:r2264 ;
vc:contrastsWith ngm:crew-ai ;
vc:contrastsWith ngm:lang-graph ;
vc:contrastsWith ngm:metagpt ;
vc:contrastsWith ngm:openai-research-organisation-agents-sdk ;
vc:contrastsWith ngm:single-agent-systems ;
vc:dependsOn ngm:actor-model ;
vc:dependsOn ngm:api-integration ;
vc:dependsOn ngm:language-model ;
vc:enables ngm:agentic-workflow ;
vc:enables ngm:autonomous-coding ;
vc:enables ngm:multi-agent-coordination ;
vc:enables ngm:task-planning ;
vc:enables ngm:workflow-automation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:agent-memory ;
vc:hasPart ngm:code-execution ;
vc:hasPart ngm:code-executor ;
vc:hasPart ngm:conversable-agent ;
vc:hasPart ngm:group-chat ;
vc:hasPart ngm:human-in-the-loop ;
vc:hasPart ngm:orchestration ;
vc:implements ngm:agentic-workflow ;
vc:implements ngm:re-act-pattern ;
vc:qualityScore "0.87"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:ai-agent ;
vc:relatedTo ngm:autonomous-agent ;
vc:relatedTo ngm:azure ;
vc:relatedTo ngm:model-context-protocol ;
vc:relatedTo ngm:semantic-kernel ;
vc:relatedTo ngm:software-engineering ;
vc:relatedTo ngm:swe-bench ;
vc:requires ngm:context-window ;
vc:requires ngm:function-calling ;
vc:requires ngm:language-model ;
vc:requires ngm:large-language-models ;
vc:requires ngm:tool-use ;
vc:slug "auto-gen" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:model-context-protocol ;
vc:supports ngm:ai-safety ;
vc:supports ngm:human-in-the-loop ;
vc:supports ngm:retrieval-augmented-generation ;
vc:uses ngm:chain-of-thought ;
vc:uses ngm:model-context-protocol ;
vc:uses ngm:natural-language-processing .
ngm:auto-ml a owl:Class ;
rdfs:comment "Automated Machine Learning (AutoML) is the discipline and associated tooling that automates the end-to-end pipeline of applying machine learning to real-world problems — encompassing automated data pre-processing, feature engineering, algorithm selection, Neural Architecture Search (NAS), hyp..."@en ;
rdfs:label "AutoML"@en ;
rdfs:subClassOf ngm:ai-agent-system ;
rdfs:subClassOf ngm:automated-optimisation-system ;
rdfs:subClassOf ngm:machine-learning-discipline-pipeline ;
rdfs:subClassOf _:r2265 ;
rdfs:subClassOf _:r2266 ;
rdfs:subClassOf _:r2267 ;
rdfs:subClassOf _:r2268 ;
rdfs:subClassOf _:r2269 ;
rdfs:subClassOf _:r2270 ;
rdfs:subClassOf _:r2271 ;
rdfs:subClassOf _:r2272 ;
rdfs:subClassOf _:r2273 ;
rdfs:subClassOf _:r2274 ;
vc:bridgesTo ngm:ai-infrastructure ;
vc:bridgesTo ngm:gazebo-simulator ;
vc:bridgesTo ngm:lang-chain ;
vc:bridgesTo ngm:machine-learning-discipline-pipeline ;
vc:bridgesTo ngm:web-assembly ;
vc:dependsOn ngm:optuna-hpo-framework ;
vc:dependsOn ngm:py-torch ;
vc:dependsOn ngm:ray-tune ;
vc:dependsOn ngm:tensor-flow ;
vc:enables ngm:democratised-ml-development ;
vc:enables ngm:rapid-model-iteration ;
vc:enables ngm:reproducible-experiments ;
vc:enables ngm:reproducible-research ;
vc:enables ngm:resource-efficiency ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:algorithm-selection ;
vc:hasPart ngm:feature-engineering ;
vc:hasPart ngm:hyperparameter-optimisation ;
vc:hasPart ngm:meta-learning ;
vc:hasPart ngm:neural-architecture-search ;
vc:hasPart ngm:optimisation ;
vc:implements ngm:bayesian-optimisation ;
vc:implements ngm:differentiable-architecture ;
vc:implements ngm:neural-architecture-search ;
vc:isPartOf ngm:ai-lifecycle ;
vc:isPartOf ngm:mlops ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:computational-budget ;
vc:requires ngm:evaluation-metric ;
vc:requires ngm:search-space-definition ;
vc:requires ngm:training-dataset ;
vc:slug "auto-ml" ;
vc:sourceDomain "artificial-intelligence" .
ngm:auto-scaling a owl:Class ;
rdfs:comment "Auto-scaling is the automated adjustment of computing capacity in response to observed demand, adding or removing resources to maintain performance and control cost. It uses metrics, policies and controllers to scale horizontally by changing instance counts or vertically by resizing instances. Auto-scaling is foundational to elastic cloud infrastructure, balancing responsiveness against efficiency without manual intervention."@en ;
rdfs:label "Auto-Scaling"@en ;
rdfs:subClassOf ngm:scalability ;
rdfs:subClassOf _:r2252 ;
rdfs:subClassOf _:r2253 ;
rdfs:subClassOf _:r2254 ;
rdfs:subClassOf _:r2255 ;
vc:dependsOn ngm:resource-management ;
vc:enables ngm:fault-tolerance ;
vc:enables ngm:high-availability ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:monitoring ;
vc:hasPart ngm:resource-allocation ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:cloud-computing ;
vc:relatedTo ngm:orchestration ;
vc:requires ngm:capacity-planning ;
vc:requires ngm:observability ;
vc:slug "auto-scaling" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:microservices ;
vc:supports ngm:performance-optimization ;
vc:uses ngm:load-balancing ;
vc:uses ngm:monitoring .
ngm:autoaugment a skos:Concept ;
rdfs:label "Autoaugment"@en .
ngm:autocorrelation-analysis a skos:Concept ;
rdfs:label "Autocorrelation Analysis"@en .
ngm:autocratic-governance a skos:Concept ;
rdfs:label "Autocratic Governance"@en .
ngm:autodesk a skos:Concept ;
rdfs:label "Autodesk"@en .
ngm:autodesk-fusion-360 a skos:Concept ;
rdfs:label "Autodesk Fusion 360"@en .
ngm:autodesk-maya a skos:Concept ;
rdfs:label "Autodesk Maya"@en .
ngm:autoencoder a owl:Class ;
rdfs:comment "An Autoencoder is a neural network trained to reconstruct its input by learning a compressed latent representation. The encoder maps input data to a lower-dimensional latent space and the decoder reconstructs the original from this representation, minimising a reconstruction loss. Variants including variational autoencoders (VAEs), denoising autoencoders, and convolutional autoencoders extend this framework to generative modelling, anomaly detection, and feature extraction."@en ;
rdfs:label "Autoencoder"@en ;
rdfs:subClassOf ngm:deep-learning ;
rdfs:subClassOf _:r2275 ;
rdfs:subClassOf _:r2276 ;
rdfs:subClassOf _:r2277 ;
rdfs:subClassOf _:r2278 ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:natural-language-processing ;
vc:bridgesTo ngm:signal-processing ;
vc:contrastsWith ngm:generative-adversarial-network ;
vc:contrastsWith ngm:principal-component-analysis ;
vc:enables ngm:anomaly-detection ;
vc:enables ngm:dimensionality-reduction ;
vc:enables ngm:representation-learning ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:decoder-network ;
vc:hasPart ngm:encoder ;
vc:hasPart ngm:neural-network-latent-space ;
vc:implements ngm:dimensionality-reduction ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:feature-extraction ;
vc:relatedTo ngm:generative-model ;
vc:relatedTo ngm:neural-network ;
vc:relatedTo ngm:transfer-learning ;
vc:relatedTo ngm:variational-autoencoders ;
vc:requires ngm:backpropagation ;
vc:slug "autoencoder" ;
vc:sourceDomain "machine-learning" ;
vc:uses ngm:gradient-descent ;
vc:uses ngm:neural-network-latent-space ;
vc:uses ngm:unsupervised-learning .
ngm:automata-theory a owl:Class ;
rdfs:comment "Automata theory is the branch of theoretical computer science that studies abstract computing machines (automata) and the classes of formal languages they can recognise. It classifies machines such as finite-state automata, pushdown automata, and Turing machines by their computational power, establishing a hierarchy that defines what problems are decidable. The theory provides the formal foundations for compiler design, regular expressions, protocol verification, and model checking."@en ;
rdfs:label "Automata Theory"@en ;
rdfs:subClassOf ngm:software-engineering ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:ai-research-area ;
vc:relatedTo ngm:state-machine ;
vc:slug "automata-theory" ;
vc:sourceDomain "infrastructure" .
ngm:automated-accessibility-testing a skos:Concept ;
rdfs:label "Automated Accessibility Testing"@en .
ngm:automated-alerting a skos:Concept ;
rdfs:label "Automated Alerting"@en .
ngm:automated-assessment a skos:Concept ;
rdfs:label "Automated Assessment"@en .
ngm:automated-biofoundry a skos:Concept ;
rdfs:label "Automated Biofoundry"@en .
ngm:automated-carbon-accounting a skos:Concept ;
rdfs:label "Automated Carbon Accounting"@en .
ngm:automated-code-review a owl:Class ;
rdfs:comment "Automated code review is the use of software tools, static analysis and, increasingly, large language models to inspect source code for defects, style violations, security weaknesses and maintainability issues without requiring manual reading of every change. It augments or partially replaces human review by surfacing actionable findings directly in pull requests and continuous integration pipelines. Modern systems combine rule-based linters with learned models that reason about code intent and propose fixes."@en ;
rdfs:label "Automated Code Review"@en ;
rdfs:subClassOf ngm:code-review ;
rdfs:subClassOf _:r2279 ;
vc:bridgesTo ngm:code-generation ;
vc:bridgesTo ngm:static-analysis ;
vc:enables ngm:continuous-integration ;
vc:enables ngm:software-engineering ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:code-review ;
vc:isPartOf ngm:code-review ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:code-generation ;
vc:relatedTo ngm:static-analysis ;
vc:relatedTo ngm:technical-debt ;
vc:requires ngm:version-control ;
vc:slug "automated-code-review" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:continuous-integration ;
vc:supports ngm:devops ;
vc:uses ngm:large-language-model ;
vc:uses ngm:static-analysis .
ngm:automated-compliance a owl:Class ;
rdfs:comment "Automated Compliance refers to the use of software systems and rule engines to continuously monitor, evaluate, and enforce regulatory requirements without manual intervention. It encompasses real-time policy checking, evidence collection, and exception reporting across business processes and IT systems. By embedding compliance logic directly into workflows, organisations can dramatically reduce audit burden and human error. The discipline draws on regulatory technology, policy engines, and audit trails to provide defensible evidence of conformance. It is particularly vital in heavily regulated sectors such as financial services, healthcare, and data protection."@en ;
rdfs:label "Automated Compliance"@en ;
rdfs:subClassOf ngm:compliance-framework ;
rdfs:subClassOf _:r2280 ;
rdfs:subClassOf _:r2281 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:security ;
vc:contrastsWith ngm:audit ;
vc:enables ngm:algorithmic-auditing ;
vc:enables ngm:compliance-audit-trail ;
vc:enables ngm:compliance-monitoring ;
vc:enables ngm:compliance-verification ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:compliance ;
vc:implements ngm:policy-as-code ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:dev-sec-ops ;
vc:relatedTo ngm:smart-contract ;
vc:requires ngm:data-governance ;
vc:requires ngm:identity-management ;
vc:slug "automated-compliance" ;
vc:sourceDomain "governance" ;
vc:supports ngm:gdpr-compliance ;
vc:supports ngm:regulatory-reporting ;
vc:supports ngm:risk-management ;
vc:uses ngm:access-control ;
vc:uses ngm:audit-trail ;
vc:uses ngm:digital-signature ;
vc:uses ngm:policy-engine ;
vc:uses ngm:regulatory-technology ;
vc:uses ngm:rule-engine .
ngm:automated-control a skos:Concept ;
rdfs:label "Automated Control"@en .
ngm:automated-corporate-actions a skos:Concept ;
rdfs:label "Automated Corporate Actions"@en .
ngm:automated-decision-making a owl:Class ;
rdfs:comment "Automated decision making is the use of algorithms or machine learning models to reach decisions about individuals or situations without meaningful human involvement. It ranges from rule-based scoring to predictions from trained models, applied to outcomes such as eligibility, pricing or risk classification. Because such decisions can significantly affect people, data protection frameworks like the GDPR grant rights around solely automated decisions, including a right to obtain human intervention and an explanation. Responsible deployment depends on fairness, transparency and accountability safeguards."@en ;
rdfs:label "Automated Decision Making"@en ;
rdfs:subClassOf ngm:decision-making ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf _:r2282 ;
vc:bridgesTo ngm:governance ;
vc:contrastsWith ngm:human-in-the-loop ;
vc:dependsOn ngm:model ;
vc:dependsOn ngm:predictive-analytics ;
vc:enables ngm:predictive-analytics ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:algorithmic-fairness ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:accountability ;
vc:relatedTo ngm:bias ;
vc:relatedTo ngm:explainable-ai ;
vc:relatedTo ngm:fairness ;
vc:requires ngm:transparency ;
vc:slug "automated-decision-making" ;
vc:sourceDomain "machine-learning" ;
vc:supports ngm:human-in-the-loop ;
vc:uses ngm:model ;
vc:uses ngm:risk-assessment .
ngm:automated-decision-system a skos:Concept ;
rdfs:label "Automated Decision System"@en .
ngm:automated-delivery a skos:Concept ;
rdfs:label "Automated Delivery"@en .
ngm:automated-design a owl:Class ;
rdfs:comment "Automated Design is the application of computational algorithms, machine learning, and optimisation techniques — spanning combinatorial search, gradient-based topology optimisation, evolutionary algorithms, reinforcement learning, and deep generative modelling — to generate, evaluate, and iteratively refine design artefacts with minimal or no step-by-step human direction. The field encompasses electronic design automation (EDA) for integrated circuits and printed circuit boards, neural architecture search (NAS) for machine-learning model topologies, topology optimisation for structural engineering, generative architectural layout synthesis, and LLM-assisted hardware description language generation. The unifying abstraction is the design space traversal guided by evaluation functions encoding physical, functional, economic, or aesthetic criteria: the algorithm explores candidate designs, evaluates each against the specified criteria, and updates its search strategy to navigate toward regions of the space satisfying design objectives. Commercial impact has been transformative across semiconductor, aerospace, automotive, and construction sectors, where design cycles have been compressed from months to days whilst exploring solution spaces too large for human enumeration."@en ;
rdfs:label "Automated Design"@en ;
rdfs:subClassOf ngm:generative-design ;
rdfs:subClassOf ngm:optimisation ;
rdfs:subClassOf _:r2283 ;
rdfs:subClassOf _:r2284 ;
rdfs:subClassOf _:r2285 ;
rdfs:subClassOf _:r2286 ;
rdfs:subClassOf _:r2287 ;
rdfs:subClassOf _:r2288 ;
rdfs:subClassOf _:r2289 ;
vc:contrastsWith ngm:parametric-design-methodology-modeling ;
vc:dependsOn ngm:multi-objective-optimisation ;
vc:dependsOn ngm:physics-simulation ;
vc:dependsOn ngm:surrogate-model ;
vc:enables ngm:additive-manufacturing ;
vc:enables ngm:auto-ml ;
vc:enables ngm:digital-twin ;
vc:enables ngm:generative-design-tool ;
vc:enables ngm:smart-manufacturing ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:electronic-design-automation ;
vc:hasPart ngm:hyperparameter-optimisation ;
vc:hasPart ngm:neural-architecture-search ;
vc:hasPart ngm:topology-optimisation ;
vc:implements ngm:multi-objective-optimisation ;
vc:implements ngm:parametric-design-methodology ;
vc:qualityScore "0.88"^^xsd:float ;
vc:relatedTo ngm:additive-manufacturing ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:cad-software ;
vc:relatedTo ngm:constraint-based-design ;
vc:relatedTo ngm:formal-verification ;
vc:relatedTo ngm:foundation-model ;
vc:relatedTo ngm:generative-design ;
vc:relatedTo ngm:hardware-description-language ;
vc:relatedTo ngm:intellectual-property-rights-framework ;
vc:requires ngm:cad-software ;
vc:requires ngm:constraint-based-design ;
vc:requires ngm:physics-simulation ;
vc:requires ngm:simulation ;
vc:slug "automated-design" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:formal-verification ;
vc:supports ngm:explainability ;
vc:supports ngm:formal-verification ;
vc:supports ngm:human-in-the-loop ;
vc:uses ngm:algorithm ;
vc:uses ngm:deep-generative-model ;
vc:uses ngm:diffusion-model ;
vc:uses ngm:evolutionary-algorithm ;
vc:uses ngm:gradient-descent ;
vc:uses ngm:graph-neural-network ;
vc:uses ngm:large-language-models ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:reinforcement-learning ;
vc:uses ngm:simulation ;
vc:uses ngm:surrogate-model ;
vc:uses ngm:transfer-learning .
ngm:automated-dispute-resolution a owl:Class ;
rdfs:comment "A class of system that applies algorithmic, rule-based, or machine-learning-driven processes to adjudicate disputes between parties without requiring direct human arbitrator involvement for each case. Automated dispute resolution mechanisms ingest evidence and contractual terms, apply predefined or learned decision rules, and produce binding or advisory outcomes, typically operating within a blockchain or smart-contract execution environment."@en ;
rdfs:label "Automated Dispute Resolution"@en ;
rdfs:subClassOf ngm:dispute-resolution ;
vc:enables ngm:conflict-resolution ;
vc:enables ngm:enforcement-mechanism ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:arbitration-process ;
vc:relatedTo ngm:dao-governance ;
vc:relatedTo ngm:legal-framework ;
vc:slug "automated-dispute-resolution" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:arbitration-decision-engine ;
vc:uses ngm:oracle-network ;
vc:uses ngm:smart-contract .
ngm:automated-duty-calculation a skos:Concept ;
rdfs:label "Automated Duty Calculation"@en .
ngm:automated-enforcement a skos:Concept ;
rdfs:label "Automated Enforcement"@en .
ngm:automated-evaluation a skos:Concept ;
rdfs:label "Automated Evaluation"@en .
ngm:automated-filtering a skos:Concept ;
rdfs:label "Automated Filtering"@en .
ngm:automated-grading a skos:Concept ;
rdfs:label "Automated Grading"@en .
ngm:automated-identification a skos:Concept ;
rdfs:label "Automated Identification"@en .
ngm:automated-lesion-detection a skos:Concept ;
rdfs:label "Automated Lesion Detection"@en .
ngm:automated-lot-release a skos:Concept ;
rdfs:label "Automated Lot Release"@en .
ngm:automated-machine a skos:Concept ;
rdfs:label "Automated Machine"@en .
ngm:automated-market-maker a owl:Class ;
rdfs:comment "Automated Market Maker (AMM) is a decentralized exchange protocol that uses algorithmic pricing mechanisms and liquidity pools instead of traditional order books, enabling permissionless token swaps where prices adjust automatically based on supply and demand within smart contract-managed reserves."@en ;
rdfs:label "Automated Market Maker"@en ;
rdfs:subClassOf ngm:de-fi-protocol ;
rdfs:subClassOf _:r2290 ;
rdfs:subClassOf _:r2291 ;
rdfs:subClassOf _:r2292 ;
rdfs:subClassOf _:r2293 ;
rdfs:subClassOf _:r2294 ;
rdfs:subClassOf _:r2295 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:de-fi ;
vc:bridgesTo ngm:virtual-economy ;
vc:contrastsWith ngm:centralized-exchange ;
vc:contrastsWith ngm:order-book-exchange ;
vc:enables ngm:liquidity-provision ;
vc:enables ngm:permissionless-trading ;
vc:enables ngm:price-discovery ;
vc:enables ngm:token-swaps ;
vc:enables ngm:yield-farming ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:constant-product-formula ;
vc:hasPart ngm:liquidity-pool ;
vc:hasPart ngm:lp-token ;
vc:implements ngm:decentralized-exchange ;
vc:qualityScore "0.7"^^xsd:float ;
vc:relatedTo ngm:arbitrage ;
vc:relatedTo ngm:impermanent-loss ;
vc:relatedTo ngm:miner-extractable-value ;
vc:relatedTo ngm:slippage ;
vc:requires ngm:blockchain ;
vc:requires ngm:liquidity-pools ;
vc:requires ngm:pricing-algorithms ;
vc:requires ngm:smart-contracts ;
vc:requires ngm:token-standard ;
vc:slug "automated-market-maker" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:oracle ;
vc:uses ngm:token-bonding-curve .
ngm:automated-market-making a owl:Class ;
rdfs:comment "Automated Market Making is the practice and modology of operating decentralized exchange protocols that use algorithmic pricing and liquidity pools to facilitate permissionless trading, encompassing pool design, fee structures, capital efficiency optimization, and impermanent loss mitigation stra..."@en ;
rdfs:label "Automated Market Making"@en ;
rdfs:subClassOf ngm:defi-operations ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf _:r2296 ;
rdfs:subClassOf _:r2297 ;
rdfs:subClassOf _:r2298 ;
rdfs:subClassOf _:r2299 ;
skos:broader ngm:sc-platform-and-environment ;
vc:bridgesTo ngm:bc-defi-and-economics ;
vc:bridgesTo ngm:blockchain ;
vc:enables ngm:decentralized-trading ;
vc:enables ngm:liquidity-mining ;
vc:enables ngm:token-accessibility ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:liquidity-provision ;
vc:requires ngm:price-oracle ;
vc:requires ngm:smart-contract-deployment ;
vc:slug "automated-market-making" ;
vc:sourceDomain "spatial-computing" .
ngm:automated-meeting-notes a skos:Concept ;
rdfs:label "Automated Meeting Notes"@en .
ngm:automated-modeling a owl:Class ;
rdfs:comment "The application of AI and machine learning techniques to automatically generate, refine, or parameterise three-dimensional models and spatial environments, reducing manual content-creation overhead in metaverse, digital-twin, and spatial-computing platforms."@en ;
rdfs:label "Automated Modeling"@en ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
skos:broader ngm:sc-platform-and-environment ;
vc:bridgesTo ngm:computer-vision ;
vc:dependsOn ngm:neural-network ;
vc:enables ngm:generative-ai ;
vc:enables ngm:metaverse ;
vc:enables ngm:metaverse-domain ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:natural-language-processing ;
vc:slug "automated-modeling" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:computer-vision ;
vc:uses ngm:machine-learning-model .
ngm:automated-payment-enforcement a skos:Concept ;
rdfs:label "Automated Payment Enforcement"@en .
ngm:automated-pipeline a skos:Concept ;
rdfs:label "Automated Pipeline"@en .
ngm:automated-planning a owl:Class ;
rdfs:comment "Automated Planning is a field of artificial intelligence concerned with the computational synthesis of action sequences (plans) that transform an initial world state into a desired goal state, using formal representations of states, actions, and constraints alongside algorithmic search and reasoning techniques."@en ;
rdfs:label "Automated Planning"@en ;
rdfs:subClassOf ngm:planning-and-scheduling ;
rdfs:subClassOf _:r2300 ;
rdfs:subClassOf _:r2301 ;
rdfs:subClassOf _:r2302 ;
rdfs:subClassOf _:r2303 ;
rdfs:subClassOf _:r2304 ;
vc:bridgesTo ngm:autonomous-robot ;
vc:bridgesTo ngm:robotics ;
vc:bridgesTo ngm:supply-chain-management ;
vc:contrastsWith ngm:reactive-planning ;
vc:contrastsWith ngm:reinforcement-learning ;
vc:dependsOn ngm:heuristic-function ;
vc:dependsOn ngm:search-algorithm ;
vc:enables ngm:autonomous-system ;
vc:enables ngm:multi-agent-coordination ;
vc:enables ngm:task-automation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:hierarchical-task-network ;
vc:hasPart ngm:pddl ;
vc:hasPart ngm:state-space-search ;
vc:implements ngm:strips ;
vc:isPartOf ngm:artificial-intelligence ;
vc:isPartOf ngm:decision-making ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:markov-decision-process ;
vc:relatedTo ngm:planning-and-scheduling ;
vc:relatedTo ngm:temporal-reasoning ;
vc:requires ngm:formal-logic ;
vc:requires ngm:knowledge-representation ;
vc:slug "automated-planning" ;
vc:sourceDomain "ai" ;
vc:supports ngm:autonomous-robot ;
vc:supports ngm:logistics-optimisation ;
vc:uses ngm:constraint-satisfaction .
ngm:automated-playtesting a skos:Concept ;
rdfs:label "Automated Playtesting"@en .
ngm:automated-podcasting a owl:Class ;
rdfs:comment "Automated Podcasting is the application of artificial intelligence, machine learning, and generative systems to partially or fully automate the end-to-end podcast production pipeline—spanning script generation, synthetic voice synthesis, AI-driven audio editing, automated transcription, show-note..."@en ;
rdfs:label "Automated Podcasting"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:ai-audio ;
rdfs:subClassOf ngm:ai-companions ;
rdfs:subClassOf ngm:ai-video ;
rdfs:subClassOf ngm:content-automation ;
rdfs:subClassOf ngm:generative-ai ;
rdfs:subClassOf ngm:speech-synthesis ;
rdfs:subClassOf _:r2305 ;
rdfs:subClassOf _:r2306 ;
rdfs:subClassOf _:r2307 ;
rdfs:subClassOf _:r2308 ;
rdfs:subClassOf _:r2309 ;
rdfs:subClassOf _:r2310 ;
rdfs:subClassOf _:r2311 ;
rdfs:subClassOf _:r2312 ;
rdfs:subClassOf _:r2313 ;
rdfs:subClassOf _:r2314 ;
rdfs:subClassOf _:r2315 ;
skos:broader ngm:ai-application ;
vc:contrastsWith ngm:human-podcast-production ;
vc:contrastsWith ngm:manual-audio-editing ;
vc:contrastsWith ngm:studio-recording ;
vc:contrastsWith ngm:traditional-radio-broadcasting ;
vc:dependsOn ngm:attention ;
vc:dependsOn ngm:audio-signal-processing ;
vc:dependsOn ngm:generative-ai ;
vc:dependsOn ngm:large-language-models ;
vc:dependsOn ngm:speech-and-voice ;
vc:dependsOn ngm:transformer-architecture ;
vc:enables ngm:accessible-media ;
vc:enables ngm:creator-economy ;
vc:enables ngm:low-cost-podcast-creation ;
vc:enables ngm:multilingual-podcasting ;
vc:enables ngm:personalised-audio-summaries ;
vc:enables ngm:real-time-content-conversion ;
vc:enables ngm:scalable-audio-content-production ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ai-audio-editing ;
vc:hasPart ngm:ai-script-generation ;
vc:hasPart ngm:automated-transcription ;
vc:hasPart ngm:neural-audio-enhancement ;
vc:hasPart ngm:podcast-distribution-automation ;
vc:hasPart ngm:show-notes-generation ;
vc:hasPart ngm:speaker-diarisation ;
vc:hasPart ngm:text-to-speech ;
vc:hasPart ngm:voice-cloning ;
vc:implements ngm:automatic-speech-recognition ;
vc:implements ngm:dynamic-ad-insertion ;
vc:implements ngm:neural-audio-enhancement ;
vc:implements ngm:retrieval-augmented-generation ;
vc:implements ngm:speaker-embedding ;
vc:implements ngm:transformer-based-tts ;
vc:implements ngm:voice-cloning ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:ai-adoption ;
vc:relatedTo ngm:ai-companies ;
vc:relatedTo ngm:ai-video ;
vc:relatedTo ngm:constitutional-ai-training-methodology-language-model-family ;
vc:relatedTo ngm:generative-ai ;
vc:relatedTo ngm:instruction-following-conversational-ai-system ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:speech-and-voice ;
vc:requires ngm:audio-signal-processing ;
vc:requires ngm:cloud-computing ;
vc:requires ngm:large-language-models ;
vc:requires ngm:natural-language-processing ;
vc:requires ngm:speech-recognition ;
vc:requires ngm:text-to-speech ;
vc:slug "automated-podcasting" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:c2-pa-content-credentials ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument-article-50 ;
vc:standardizedBy ngm:ftc-endorsement-guidelines ;
vc:standardizedBy ngm:ofcom-broadcasting-code ;
vc:supports ngm:ai-companions ;
vc:supports ngm:ai-search ;
vc:supports ngm:ai-video ;
vc:supports ngm:creator-economy ;
vc:supports ngm:media-accessibility ;
vc:supports ngm:podcast-distribution ;
vc:supports ngm:seo-optimisation ;
vc:uses ngm:adobe-podcast ;
vc:uses ngm:assemblyai ;
vc:uses ngm:descript ;
vc:uses ngm:eleven-labs ;
vc:uses ngm:notebooklm ;
vc:uses ngm:openai-research-organisation-whisper ;
vc:uses ngm:otter-ai ;
vc:uses ngm:retrieval-augmented-generation .
ngm:automated-privacy-compliance a skos:Concept ;
rdfs:label "Automated Privacy Compliance"@en .
ngm:automated-promotion a skos:Concept ;
rdfs:label "Automated Promotion"@en .
ngm:automated-publishing a skos:Concept ;
rdfs:label "Automated Publishing"@en .
ngm:automated-quality-monitoring a skos:Concept ;
rdfs:label "Automated Quality Monitoring"@en .
ngm:automated-reasoner a skos:Concept ;
rdfs:label "Automated Reasoner"@en .
ngm:automated-reasoning a owl:Class ;
rdfs:comment "Automated Reasoning is a subfield of artificial intelligence and computer science concerned with developing algorithms and systems that can perform logical inference, theorem proving, satisfiability checking, and knowledge-based deduction without continuous human guidance. It encompasses formal methods such as first-order logic, propositional calculus, and higher-order logics, implemented in systems ranging from SAT solvers and automated theorem provers to description logic reasoners underpinning knowledge graphs. Automated reasoning forms the rigorous backbone of formal verification, ontology inference, planning, and constraint satisfaction problems."@en ;
rdfs:label "Automated Reasoning"@en ;
rdfs:subClassOf ngm:reasoning ;
rdfs:subClassOf ngm:symbolic-ai ;
rdfs:subClassOf ngm:symbolic-reasoning ;
rdfs:subClassOf _:r2316 ;
rdfs:subClassOf _:r2317 ;
rdfs:subClassOf _:r2318 ;
rdfs:subClassOf _:r2319 ;
rdfs:subClassOf _:r2320 ;
rdfs:subClassOf _:r2321 ;
rdfs:subClassOf _:r2322 ;
rdfs:subClassOf _:r2323 ;
rdfs:subClassOf _:r2324 ;
rdfs:subClassOf _:r2325 ;
rdfs:subClassOf _:r2326 ;
rdfs:subClassOf _:r2327 ;
vc:bridgesTo ngm:formal-methods ;
vc:contrastsWith ngm:deep-learning ;
vc:contrastsWith ngm:probabilistic-reasoning ;
vc:dependsOn ngm:first-order-logic ;
vc:dependsOn ngm:inference-engine ;
vc:enables ngm:automated-planning ;
vc:enables ngm:expert-systems ;
vc:enables ngm:explainable-ai ;
vc:enables ngm:formal-verification ;
vc:enables ngm:knowledge-graph ;
vc:enables ngm:program-synthesis ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:automated-theorem-proving ;
vc:hasPart ngm:constraint-satisfaction ;
vc:hasPart ngm:description-logic ;
vc:hasPart ngm:inference-engine ;
vc:hasPart ngm:model-checking ;
vc:hasPart ngm:sat-solving ;
vc:hasPart ngm:theorem-proving ;
vc:implements ngm:bayesian-inference ;
vc:implements ngm:logic-programming ;
vc:qualityScore "0.91"^^xsd:float ;
vc:relatedTo ngm:automatic-differentiation ;
vc:relatedTo ngm:explainable-ai ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:logic-programming ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:neuro-symbolic-ai ;
vc:relatedTo ngm:symbolic-reasoning ;
vc:requires ngm:first-order-logic ;
vc:requires ngm:formal-logic ;
vc:requires ngm:formal-methods ;
vc:requires ngm:inference-engine ;
vc:requires ngm:knowledge-representation ;
vc:slug "automated-reasoning" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:formal-methods ;
vc:supports ngm:ai-alignment ;
vc:supports ngm:expert-systems ;
vc:supports ngm:neuro-symbolic-ai ;
vc:supports ngm:symbolic-ai ;
vc:uses ngm:constraint-satisfaction ;
vc:uses ngm:first-order-logic ;
vc:uses ngm:ontology ;
vc:uses ngm:semantic-web-linked-data-standard .
ngm:automated-reconciliation a skos:Concept ;
rdfs:label "Automated Reconciliation"@en .
ngm:automated-reporting a skos:Concept ;
rdfs:label "Automated Reporting"@en .
ngm:automated-software-scaffolding a skos:Concept ;
rdfs:label "Automated Software Scaffolding"@en .
ngm:automated-storage-and-retrieval-system a skos:Concept ;
rdfs:label "Automated Storage And Retrieval System"@en .
ngm:automated-summarization a owl:Class ;
rdfs:comment "Automated Summarization is an NLP task in which a system produces a condensed representation of one or more source documents that preserves salient information and is significantly shorter than the original. Extractive approaches select and concatenate verbatim sentences or passages from the source; abstractive approaches generate novel text that may paraphrase, fuse, or infer content not explicitly stated in the source. Modern large language model-based summarizers are predominantly abstractive, achieving strong performance on long-form documents, meeting transcripts, scientific papers, and news articles, but remain susceptible to hallucination, factual inconsistency, and salience mismatch relative to the reader's intent."@en ;
rdfs:label "Automated Summarization"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:natural-language-processing ;
rdfs:subClassOf _:r2328 ;
rdfs:subClassOf _:r2329 ;
rdfs:subClassOf _:r2330 ;
rdfs:subClassOf _:r2331 ;
rdfs:subClassOf _:r2332 ;
skos:broader ngm:ai-application ;
vc:bridgesTo ngm:meeting-recording ;
vc:enables ngm:documentation-generation ;
vc:enables ngm:knowledge-base ;
vc:enables ngm:meeting-ai-assistant ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:language-modeling ;
vc:hasPart ngm:text-generation ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:knowledge-graph-construction ;
vc:relatedTo ngm:meeting-transcription ;
vc:relatedTo ngm:question-answering ;
vc:relatedTo ngm:sentiment-analysis ;
vc:requires ngm:large-language-models ;
vc:requires ngm:natural-language-understanding ;
vc:requires ngm:transformer-architecture ;
vc:slug "automated-summarization" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:information-retrieval ;
vc:uses ngm:retrieval-augmented-generation .
ngm:automated-tax-filing a skos:Concept ;
rdfs:label "Automated Tax Filing"@en .
ngm:automated-testing a owl:Class ;
rdfs:comment "Automated testing is the practice of using software tools to execute predefined test cases against a system and compare actual outcomes to expected results without manual intervention. It spans unit, integration, end-to-end, and regression tests, and is typically wired into build pipelines so defects are caught early and consistently. By making verification repeatable and fast, it enables continuous integration and reliable software delivery at scale."@en ;
rdfs:label "Automated Testing"@en ;
rdfs:subClassOf ngm:software-development ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:cli-multi-agent-systems ;
vc:relatedTo ngm:continuous-integration ;
vc:slug "automated-testing" ;
vc:sourceDomain "infrastructure" .
ngm:automated-theorem-proving a owl:Class ;
rdfs:comment "Automated theorem proving is the subfield of automated reasoning concerned with constructing formal proofs of mathematical or logical statements by machine. Given a set of axioms and a conjecture expressed in a formal logic, an automated theorem prover searches for a derivation that establishes the conjecture as a consequence of the axioms. Techniques span resolution, tableaux, term rewriting and decision procedures, and underpin formal verification, mathematics and AI reasoning."@en ;
rdfs:label "Automated Theorem Proving"@en ;
rdfs:subClassOf ngm:automated-reasoning ;
rdfs:subClassOf _:r2333 ;
vc:bridgesTo ngm:formal-verification ;
vc:bridgesTo ngm:symbolic-ai ;
vc:dependsOn ngm:automated-reasoning ;
vc:enables ngm:formal-verification ;
vc:enables ngm:theorem-proving ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:theorem-proving ;
vc:isPartOf ngm:automated-reasoning ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:constraint-satisfaction ;
vc:relatedTo ngm:symbolic-ai ;
vc:relatedTo ngm:theorem-proving ;
vc:requires ngm:automated-reasoning ;
vc:slug "automated-theorem-proving" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:formal-verification ;
vc:uses ngm:constraint-satisfaction .
ngm:automated-trading a skos:Concept ;
rdfs:label "Automated Trading"@en .
ngm:automated-transcription a skos:Concept ;
rdfs:label "Automated Transcription"@en .
ngm:automatic-1111-web-ui a owl:Class ;
rdfs:comment "AUTOMATIC1111 WebUI (also referred to as sd-webui or A1111) is an open-source, community-maintained browser-based graphical interface for running Stable Diffusion latent diffusion models locally on consumer and professional GPU hardware. Built in Python with a Gradio front end, it wraps the core Stable Diffusion inference pipeline in an accessible point-and-click UI that exposes text-to-image generation, image-to-image transformation, inpainting, outpainting, upscaling, model training tabs, and an extensible plugin architecture. Since its first public release in August 2022, it has accumulated over 160,000 GitHub stars, making it one of the most-starred open-source AI repositories in history and the dominant entry point for local Stable Diffusion experimentation."@en ;
rdfs:label "AUTOMATIC1111 WebUI"@en ;
rdfs:subClassOf ngm:generative-ai ;
rdfs:subClassOf ngm:image-generation ;
rdfs:subClassOf ngm:open-generative-ai-tools ;
rdfs:subClassOf _:r904 ;
rdfs:subClassOf _:r905 ;
rdfs:subClassOf _:r906 ;
rdfs:subClassOf _:r907 ;
rdfs:subClassOf _:r908 ;
rdfs:subClassOf _:r909 ;
rdfs:subClassOf _:r910 ;
rdfs:subClassOf _:r911 ;
rdfs:subClassOf _:r912 ;
rdfs:subClassOf _:r913 ;
rdfs:subClassOf _:r914 ;
rdfs:subClassOf _:r915 ;
vc:contrastsWith ngm:comfy-ui ;
vc:contrastsWith ngm:invoke-ai ;
vc:dependsOn ngm:attention-mechanism ;
vc:dependsOn ngm:clip ;
vc:dependsOn ngm:gpu-compute ;
vc:dependsOn ngm:gradio ;
vc:dependsOn ngm:python ;
vc:dependsOn ngm:u-net ;
vc:dependsOn ngm:vae ;
vc:enables ngm:image-to-image ;
vc:enables ngm:inpainting ;
vc:enables ngm:kohya-dreambooth-and-similar ;
vc:enables ngm:local-ai ;
vc:enables ngm:outpainting ;
vc:enables ngm:text-to-image ;
vc:enables ngm:textual-inversion ;
vc:enables ngm:upscaling ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:image-to-image ;
vc:hasPart ngm:inpainting ;
vc:hasPart ngm:kohya-dreambooth-and-similar ;
vc:hasPart ngm:outpainting ;
vc:hasPart ngm:sampler ;
vc:hasPart ngm:text-to-image ;
vc:hasPart ngm:textual-inversion ;
vc:hasPart ngm:upscaling ;
vc:implements ngm:classifier-free-guidance ;
vc:implements ngm:latent-diffusion ;
vc:implements ngm:sampler ;
vc:qualityScore "0.85"^^xsd:float ;
vc:relatedTo ngm:civitai ;
vc:relatedTo ngm:diffusion-model ;
vc:relatedTo ngm:flux-1 ;
vc:relatedTo ngm:generative-adversarial-network ;
vc:relatedTo ngm:hugging-face ;
vc:relatedTo ngm:image-generation ;
vc:relatedTo ngm:latent-diffusion ;
vc:relatedTo ngm:prompt-engineering ;
vc:relatedTo ngm:stable-diffusion-image-model ;
vc:relatedTo ngm:stable-diffusion-xl ;
vc:requires ngm:clip ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:gradio ;
vc:requires ngm:python ;
vc:requires ngm:stable-diffusion-image-model ;
vc:requires ngm:u-net ;
vc:requires ngm:vae ;
vc:slug "automatic-1111-web-ui" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:civitai ;
vc:standardizedBy ngm:hugging-face ;
vc:supports ngm:computer-vision ;
vc:supports ngm:generative-ai ;
vc:supports ngm:open-generative-ai-tools ;
vc:supports ngm:prompt-engineering ;
vc:supports ngm:stable-video-diffusion ;
vc:uses ngm:attention-mechanism ;
vc:uses ngm:classifier-free-guidance ;
vc:uses ngm:clip ;
vc:uses ngm:control-net ;
vc:uses ngm:diffusion-model ;
vc:uses ngm:hypernetwork ;
vc:uses ngm:lo-ra ;
vc:uses ngm:stable-diffusion-image-model ;
vc:uses ngm:textual-inversion ;
vc:uses ngm:vae .
ngm:automatic-call-distribution a skos:Concept ;
rdfs:label "Automatic Call Distribution"@en .
ngm:automatic-chain-of-thought a skos:Concept ;
rdfs:label "Automatic Chain Of Thought"@en .
ngm:automatic-curriculum a skos:Concept ;
rdfs:label "Automatic Curriculum"@en .
ngm:automatic-differentiation a owl:Class ;
rdfs:comment "Automatic differentiation (AD) is a family of computational techniques for evaluating the derivative of a function specified by a computer program, by systematically applying the chain rule to elementary arithmetic operations rather than through symbolic algebra or finite-difference approximation. It operates in two principal modes: forward mode, which propagates tangent values alongside primal values, and reverse mode (backpropagation), which accumulates gradients in a backward pass over a recorded computation graph. AD produces machine-precision derivatives at a cost linear in the number of program operations, making it the computational backbone of modern deep learning frameworks."@en ;
rdfs:label "Automatic Differentiation"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:numerical-methods ;
rdfs:subClassOf ngm:optimisation ;
rdfs:subClassOf _:r2334 ;
rdfs:subClassOf _:r2335 ;
rdfs:subClassOf _:r2336 ;
rdfs:subClassOf _:r2337 ;
rdfs:subClassOf _:r2338 ;
rdfs:subClassOf _:r2339 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:differentiable-rendering ;
vc:bridgesTo ngm:robotics-control ;
vc:contrastsWith ngm:forward-mode-differentiation ;
vc:contrastsWith ngm:numerical-methods ;
vc:dependsOn ngm:computation-graph ;
vc:dependsOn ngm:loss-function ;
vc:enables ngm:backpropagation ;
vc:enables ngm:deep-learning ;
vc:enables ngm:differentiable-architecture ;
vc:enables ngm:differentiable-programming ;
vc:enables ngm:differentiable-rendering ;
vc:enables ngm:gradient-descent ;
vc:enables ngm:neural-ordinary-differential-equation ;
vc:enables ngm:physics-simulation ;
vc:enables ngm:probabilistic-programming ;
vc:enables ngm:reinforcement-learning ;
vc:enables ngm:scientific-machine-learning ;
vc:enables ngm:stochastic-gradient-descent ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:backpropagation ;
vc:hasPart ngm:computation-graph ;
vc:hasPart ngm:forward-mode-differentiation ;
vc:implements ngm:backpropagation ;
vc:implements ngm:gradient-descent ;
vc:qualityScore "0.92"^^xsd:float ;
vc:relatedTo ngm:adam-optimiser ;
vc:relatedTo ngm:automated-reasoning ;
vc:relatedTo ngm:just-in-time-compilation ;
vc:relatedTo ngm:loss-function ;
vc:relatedTo ngm:numerical-methods ;
vc:relatedTo ngm:optimisation ;
vc:relatedTo ngm:stochastic-gradient-descent ;
vc:requires ngm:activation-function ;
vc:requires ngm:chain-rule ;
vc:requires ngm:computation-graph ;
vc:requires ngm:differentiable-function ;
vc:requires ngm:loss-function ;
vc:slug "automatic-differentiation" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:machine-learning-discipline-framework ;
vc:supports ngm:differentiable-rendering ;
vc:supports ngm:large-language-models ;
vc:supports ngm:physics-simulation ;
vc:supports ngm:probabilistic-programming ;
vc:supports ngm:scientific-machine-learning ;
vc:supports ngm:transformer-architecture ;
vc:uses ngm:batch-normalisation ;
vc:uses ngm:computation-graph ;
vc:uses ngm:gradient-accumulation ;
vc:uses ngm:gradient-checkpointing ;
vc:uses ngm:gradient-clipping ;
vc:uses ngm:jax ;
vc:uses ngm:machine-learning-discipline-framework ;
vc:uses ngm:neural-network .
ngm:automatic-exchange-of-information a skos:Concept ;
rdfs:label "Automatic Exchange Of Information"@en .
ngm:automatic-failover a skos:Concept ;
rdfs:label "Automatic Failover"@en .
ngm:automatic-freeu-module a skos:Concept ;
rdfs:label "Automatic Freeu Module"@en .
ngm:automatic-grouping a skos:Concept ;
rdfs:label "Automatic Grouping"@en .
ngm:automatic-prompt-optimisation a owl:Class ;
rdfs:comment "Automatic Prompt Optimisation (APO) is the family of algorithmic techniques that search for, refine, or generate the most effective natural-language or soft-token instructions for a large language model, replacing manual prompt crafting with automated search processes guided by an objective function. Methods span gradient-free discrete search (APE, OPRO, ProTeGi), evolutionary self-improvement loops (PromptBreeder, GEPA), LLM-as-optimiser meta-prompting, textual back-propagation (TextGrad), and compiler-based programmatic optimisation (DSPy), each scoring candidate prompts against a held-out evaluation metric and iteratively retaining the highest-performing variants. APO addresses the brittleness and labour cost of hand-tuned prompting and has become a core component of production LLM pipelines, enabling measurable, reproducible performance gains without requiring access to model weights."@en ;
rdfs:label "Automatic Prompt Optimisation"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf ngm:model-optimisation-and-performance ;
rdfs:subClassOf ngm:natural-language-processing ;
rdfs:subClassOf ngm:prompt-engineering ;
rdfs:subClassOf _:r2340 ;
rdfs:subClassOf _:r2341 ;
rdfs:subClassOf _:r2342 ;
rdfs:subClassOf _:r2343 ;
rdfs:subClassOf _:r2344 ;
rdfs:subClassOf _:r2345 ;
rdfs:subClassOf _:r2346 ;
rdfs:subClassOf _:r2347 ;
rdfs:subClassOf _:r2348 ;
rdfs:subClassOf _:r2349 ;
rdfs:subClassOf _:r2350 ;
rdfs:subClassOf _:r2351 ;
rdfs:subClassOf _:r2352 ;
skos:broader ngm:ai-technique ;
vc:contrastsWith ngm:prefix-tuning ;
vc:contrastsWith ngm:soft-prompt-tuning ;
vc:contrastsWith ngm:training-and-fine-tuning ;
vc:dependsOn ngm:context-window ;
vc:dependsOn ngm:few-shot-prompting ;
vc:dependsOn ngm:large-language-models ;
vc:dependsOn ngm:transformer-architecture ;
vc:enables ngm:agents ;
vc:enables ngm:code-generation ;
vc:enables ngm:reasoning ;
vc:enables ngm:retrieval-augmented-generation ;
vc:enables ngm:structured-output ;
vc:enables ngm:tool-use ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:ape ;
vc:hasPart ngm:chain-of-thought ;
vc:hasPart ngm:dspy ;
vc:hasPart ngm:few-shot-prompting ;
vc:hasPart ngm:opro ;
vc:hasPart ngm:prefix-tuning ;
vc:hasPart ngm:prompt-breeder ;
vc:hasPart ngm:protegi ;
vc:hasPart ngm:re-act ;
vc:hasPart ngm:self-consistency ;
vc:hasPart ngm:soft-prompt-tuning ;
vc:hasPart ngm:textgrad ;
vc:hasPart ngm:tree-of-thoughts ;
vc:hasPart ngm:zero-shot-prompting ;
vc:implements ngm:active-learning ;
vc:implements ngm:bayesian-optimisation ;
vc:implements ngm:evolutionary-algorithm ;
vc:implements ngm:meta-learning ;
vc:implements ngm:reinforcement-learning ;
vc:qualityScore "0.87"^^xsd:float ;
vc:relatedTo ngm:ai-alignment ;
vc:relatedTo ngm:bias-in-large-language-models ;
vc:relatedTo ngm:hallucination ;
vc:relatedTo ngm:in-context-learning ;
vc:relatedTo ngm:structured-output ;
vc:relatedTo ngm:training-and-fine-tuning ;
vc:requires ngm:context-window ;
vc:requires ngm:evaluation-benchmarks-and-leaderboards ;
vc:requires ngm:in-context-learning ;
vc:requires ngm:instruction-following ;
vc:requires ngm:large-language-models ;
vc:slug "automatic-prompt-optimisation" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:dspy ;
vc:standardizedBy ngm:evaluation-benchmarks-and-leaderboards ;
vc:supports ngm:ai-alignment ;
vc:supports ngm:evaluation-benchmarks-and-leaderboards ;
vc:supports ngm:model-optimisation-and-performance ;
vc:uses ngm:chain-of-thought ;
vc:uses ngm:dspy ;
vc:uses ngm:lang-chain ;
vc:uses ngm:reinforcement-learning .
ngm:automatic-recovery a skos:Concept ;
rdfs:label "Automatic Recovery"@en .
ngm:automatic-refiner-scheduler a skos:Concept ;
rdfs:label "Automatic Refiner Scheduler"@en .
ngm:automatic-speech-recognition a owl:Class ;
rdfs:comment "Automatic Speech Recognition (ASR) is the technology that converts spoken language into written text by jointly modelling acoustic signals — frame-level spectral features derived from raw audio waveforms — and linguistic context, using neural sequence-to-sequence architectures trained on large corpora of paired audio and transcripts. Modern ASR systems built on transformer and conformer encoder-decoder designs achieve near-human word error rates on clean speech benchmarks (Whisper Large-v3 at 2.7% WER on LibriSpeech test-clean) and have been extended to multilingual and low-resource settings through large-scale self-supervised pre-training on unlabelled audio. ASR serves as a foundational component for voice assistants, real-time transcription services, accessibility tooling, and spoken language understanding pipelines, and underpins multimodal AI systems that must bridge the speech and text modalities."@en ;
rdfs:label "Automatic Speech Recognition"@en ;
rdfs:subClassOf ngm:audio-signal-processing ;
rdfs:subClassOf ngm:deep-learning ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf ngm:natural-language-processing ;
rdfs:subClassOf ngm:speech-processing ;
rdfs:subClassOf _:r2353 ;
rdfs:subClassOf _:r2354 ;
rdfs:subClassOf _:r2355 ;
rdfs:subClassOf _:r2356 ;
rdfs:subClassOf _:r2357 ;
rdfs:subClassOf _:r2358 ;
rdfs:subClassOf _:r2359 ;
rdfs:subClassOf _:r2360 ;
rdfs:subClassOf _:r2361 ;
rdfs:subClassOf _:r2362 ;
rdfs:subClassOf _:r2363 ;
rdfs:subClassOf _:r2364 ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:bridgesTo ngm:spatial-audio ;
vc:contrastsWith ngm:keyword-spotting ;
vc:contrastsWith ngm:text-to-speech ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:recurrent-neural-network ;
vc:dependsOn ngm:self-supervised-learning ;
vc:dependsOn ngm:training-data ;
vc:dependsOn ngm:transformer-architecture ;
vc:enables ngm:large-language-models ;
vc:enables ngm:machine-translation ;
vc:enables ngm:natural-language-processing ;
vc:enables ngm:real-time-captioning ;
vc:enables ngm:spoken-language-understanding ;
vc:enables ngm:voice-interaction ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:acoustic-model ;
vc:hasPart ngm:attention-mechanism ;
vc:hasPart ngm:beam-search ;
vc:hasPart ngm:connectionist-temporal-classification ;
vc:hasPart ngm:feature-extraction ;
vc:hasPart ngm:language-model ;
vc:hasPart ngm:positional-encoding ;
vc:hasPart ngm:rnn-transducer ;
vc:implements ngm:attention-mechanism ;
vc:implements ngm:connectionist-temporal-classification ;
vc:implements ngm:self-supervised-learning ;
vc:implements ngm:transfer-learning ;
vc:implements ngm:transformer-architecture ;
vc:qualityScore "0.89"^^xsd:float ;
vc:relatedTo ngm:distributed-collaboration ;
vc:relatedTo ngm:knowledge-distillation ;
vc:relatedTo ngm:language-modeling ;
vc:relatedTo ngm:model-compression ;
vc:relatedTo ngm:spatial-audio ;
vc:relatedTo ngm:speaker-diarisation ;
vc:relatedTo ngm:speaker-recognition ;
vc:relatedTo ngm:word-error-rate ;
vc:requires ngm:audio-signal-processing ;
vc:requires ngm:deep-learning ;
vc:requires ngm:gpu-computing ;
vc:requires ngm:training-data ;
vc:slug "automatic-speech-recognition" ;
vc:sourceDomain "ai" ;
vc:supports ngm:accessibility ;
vc:supports ngm:distributed-collaboration ;
vc:supports ngm:human-computer-interaction ;
vc:supports ngm:multimodal-ai-architecture-ai ;
vc:supports ngm:spatial-computing ;
vc:uses ngm:attention-mechanism ;
vc:uses ngm:beam-search ;
vc:uses ngm:connectionist-temporal-classification ;
vc:uses ngm:deep-learning ;
vc:uses ngm:knowledge-distillation ;
vc:uses ngm:quantisation ;
vc:uses ngm:recurrent-neural-network ;
vc:uses ngm:self-supervised-learning ;
vc:uses ngm:transfer-learning ;
vc:uses ngm:transformer-architecture .
ngm:automatic1111 a owl:Class ;
rdfs:comment "An open-source, browser-based graphical user interface for Stable Diffusion and compatible diffusion models, providing extensive control over image-generation parameters, model loading, and an extensible plugin architecture. Automatic1111 (AUTOMATIC1111/stable-diffusion-webui on GitHub) became the dominant community-facing inference frontend for locally hosted image-generation models from 2022 onwards."@en ;
rdfs:label "Automatic1111"@en ;
rdfs:subClassOf ngm:generative-ai ;
rdfs:subClassOf ngm:image-generation ;
rdfs:subClassOf ngm:open-source-software ;
rdfs:subClassOf _:r2365 ;
rdfs:subClassOf _:r2366 ;
rdfs:subClassOf _:r2367 ;
rdfs:subClassOf _:r2368 ;
rdfs:subClassOf _:r2369 ;
rdfs:subClassOf _:r2370 ;
rdfs:subClassOf _:r2371 ;
rdfs:subClassOf _:r2372 ;
rdfs:subClassOf _:r2373 ;
rdfs:subClassOf _:r2374 ;
rdfs:subClassOf _:r2375 ;
rdfs:subClassOf _:r2376 ;
rdfs:subClassOf _:r2377 ;
rdfs:subClassOf _:r2378 ;
rdfs:subClassOf _:r2379 ;
vc:contrastsWith ngm:comfy-ui ;
vc:contrastsWith ngm:flux ;
vc:contrastsWith ngm:fooocus ;
vc:contrastsWith ngm:invoke-ai ;
vc:contrastsWith ngm:stable-diffusion-webui-forge ;
vc:dependsOn ngm:cuda ;
vc:dependsOn ngm:gpu-acceleration ;
vc:dependsOn ngm:gradio ;
vc:dependsOn ngm:py-torch ;
vc:dependsOn ngm:python ;
vc:dependsOn ngm:stable-diffusion-image-model ;
vc:enables ngm:high-resolution-upscaling ;
vc:enables ngm:image-editing ;
vc:enables ngm:image-to-image ;
vc:enables ngm:inpainting ;
vc:enables ngm:outpainting ;
vc:enables ngm:prompt-engineering ;
vc:enables ngm:text-to-image ;
vc:enables ngm:text-to-image-generation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:classifier-free-guidance ;
vc:hasPart ngm:clip ;
vc:hasPart ngm:control-net ;
vc:hasPart ngm:gradio ;
vc:hasPart ngm:hypernetwork ;
vc:hasPart ngm:lo-ra ;
vc:hasPart ngm:sampling ;
vc:hasPart ngm:textual-inversion ;
vc:hasPart ngm:u-net ;
vc:hasPart ngm:vae ;
vc:implements ngm:classifier-free-guidance ;
vc:implements ngm:denoising-diffusion-probabilistic-models ;
vc:implements ngm:latent-diffusion ;
vc:implements ngm:textual-inversion ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:black-forest-labs ;
vc:relatedTo ngm:civitai ;
vc:relatedTo ngm:comfy-ui ;
vc:relatedTo ngm:control-net ;
vc:relatedTo ngm:generative-ai ;
vc:relatedTo ngm:open-source-software ;
vc:relatedTo ngm:prompt-engineering ;
vc:relatedTo ngm:sdxl ;
vc:relatedTo ngm:stable-diffusion-3 ;
vc:relatedTo ngm:stable-diffusion-image-model ;
vc:requires ngm:clip ;
vc:requires ngm:diffusion-model ;
vc:requires ngm:gpu-acceleration ;
vc:requires ngm:latent-diffusion ;
vc:requires ngm:py-torch ;
vc:requires ngm:python ;
vc:requires ngm:stable-diffusion-image-model ;
vc:slug "automatic1111" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:hugging-face ;
vc:standardizedBy ngm:stability-ai ;
vc:supports ngm:civitai ;
vc:supports ngm:control-net ;
vc:supports ngm:hypernetwork ;
vc:supports ngm:lo-ra ;
vc:supports ngm:sdxl ;
vc:supports ngm:stable-diffusion-image-model ;
vc:supports ngm:textual-inversion ;
vc:uses ngm:classifier-free-guidance ;
vc:uses ngm:clip ;
vc:uses ngm:diffusion-model ;
vc:uses ngm:gpu-acceleration ;
vc:uses ngm:latent-diffusion ;
vc:uses ngm:lo-ra ;
vc:uses ngm:sampling ;
vc:uses ngm:textual-inversion ;
vc:uses ngm:u-net ;
vc:uses ngm:vae .
ngm:automation a owl:Class ;
rdfs:comment "Automation is the application of technology, control systems, and software to execute processes, tasks, or workflows with minimal or no human intervention, transferring decision-making and execution from people to machines or algorithms. It encompasses industrial and manufacturing automation driven by programmable logic controllers and robotics, as well as software-driven process automation that replicates repetitive digital workflows. The primary goals are to increase throughput, reduce error rates, lower operational costs, and free human attention for non-routine judgement tasks. Automation exists on a spectrum from fixed mechanisation through programmable control, flexible automation, and fully autonomous adaptive systems."@en ;
rdfs:label "Automation"@en ;
rdfs:subClassOf ngm:software-engineering ;
rdfs:subClassOf _:r2381 ;
rdfs:subClassOf _:r2382 ;
rdfs:subClassOf _:r2383 ;
rdfs:subClassOf _:r2384 ;
rdfs:subClassOf _:r2385 ;
rdfs:subClassOf _:r2386 ;
rdfs:subClassOf _:r2387 ;
rdfs:subClassOf _:r2388 ;
rdfs:subClassOf _:r2389 ;
vc:bridgesTo ngm:agents ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:digital-twin ;
vc:contrastsWith ngm:human-in-the-loop ;
vc:dependsOn ngm:feedback-loop ;
vc:dependsOn ngm:logic ;
vc:enables ngm:continuous-integration ;
vc:enables ngm:devops ;
vc:enables ngm:robotics ;
vc:enables ngm:scalability ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:industrial-automation ;
vc:hasPart ngm:robotic-process-automation ;
vc:hasPart ngm:test-automation ;
vc:hasPart ngm:workflow-automation ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:autonomous-system ;
vc:relatedTo ngm:internet-of-things ;
vc:relatedTo ngm:orchestration ;
vc:requires ngm:actuators ;
vc:requires ngm:control-system ;
vc:requires ngm:sensors ;
vc:slug "automation" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:business-process-management ;
vc:supports ngm:edge-computing ;
vc:supports ngm:supply-chain-management ;
vc:uses ngm:computer-vision ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:natural-language-processing .
ngm:automation-bias a owl:Class ;
rdfs:comment "Automation bias is the human tendency to over-rely on automated systems, accepting their outputs uncritically and discounting contradictory information, including one's own judgement. It manifests as errors of commission, following an automated recommendation that is wrong, and errors of omission, failing to act because the system did not prompt. Driven by the perceived authority of computers and the cognitive ease of deferring, it grows with workload, trust, and system opacity. Automation bias is a central human-factors concern in the governance of decision-support systems and human-in-the-loop oversight, where it can erode the very safeguards that human supervision is meant to provide."@en ;
rdfs:label "Automation Bias"@en ;
rdfs:subClassOf ngm:bias ;
rdfs:subClassOf _:r2380 ;
vc:contrastsWith ngm:human-in-the-loop ;
vc:contrastsWith ngm:human-oversight ;
vc:contrastsWith ngm:situational-awareness ;
vc:dependsOn ngm:automation ;
vc:dependsOn ngm:trust ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:human-factors ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:accountability ;
vc:relatedTo ngm:automation ;
vc:relatedTo ngm:explainability ;
vc:relatedTo ngm:human-factors ;
vc:relatedTo ngm:trust ;
vc:requires ngm:explainability ;
vc:slug "automation-bias" ;
vc:sourceDomain "governance" ;
vc:supports ngm:accountability .
ngm:automerge a owl:Class ;
rdfs:comment "Automerge is a library and data format implementing a JSON-like CRDT that enables automatic merging of concurrent changes to shared documents without requiring a central server. It models document history as an append-only log of operations, allowing peers to exchange and apply changes in any order while converging to the same state. Automerge supports rich text, rich data structures, and is designed for local-first software where data lives on the user's device and syncs opportunistically."@en ;
rdfs:label "Automerge"@en ;
rdfs:subClassOf ngm:dc-protocol-and-infra ;
skos:broader ngm:dc-protocol-and-infra ;
vc:enables ngm:crdt ;
vc:enables ngm:local-first-software ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.7"^^xsd:float ;
vc:relatedTo ngm:yjs-framework ;
vc:slug "automerge" ;
vc:sourceDomain "distributed-collaboration" .
ngm:automotive-control a skos:Concept ;
rdfs:label "Automotive Control"@en .
ngm:automotive-cybersecurity a skos:Concept ;
rdfs:label "Automotive Cybersecurity"@en .
ngm:automotive-manufacturing a skos:Concept ;
rdfs:label "Automotive Manufacturing"@en .
ngm:automotive-safety-standard a skos:Concept ;
rdfs:label "Automotive Safety Standard"@en .
ngm:autonomic-computing a skos:Concept ;
rdfs:label "Autonomic Computing"@en .
ngm:autonomous-agent a owl:Class ;
rdfs:comment "Software entity capable of acting autonomously to achieve goals within a metaverse, exhibiting goal-directed behavior, decision-making, and adaptive responses without continuous human intervention."@en ;
rdfs:label "Autonomous Agent"@en ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf _:r2396 ;
rdfs:subClassOf _:r2397 ;
rdfs:subClassOf _:r2398 ;
rdfs:subClassOf _:r2399 ;
rdfs:subClassOf _:r2400 ;
rdfs:subClassOf _:r2401 ;
rdfs:subClassOf _:r2402 ;
skos:broader ngm:sc-platform-and-environment ;
vc:bridgesTo ngm:autonomous-robot ;
vc:dependsOn ngm:ai-framework ;
vc:dependsOn ngm:data-source ;
vc:dependsOn ngm:knowledge-base ;
vc:enables ngm:autonomous-behavior ;
vc:enables ngm:content-moderation ;
vc:enables ngm:decision-support ;
vc:enables ngm:npc-interaction ;
vc:enables ngm:process-automation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:action-executor ;
vc:hasPart ngm:decision-engine ;
vc:hasPart ngm:goal-system ;
vc:hasPart ngm:learning-component ;
vc:hasPart ngm:perception-module ;
vc:isPartOf ngm:ai-system ;
vc:isPartOf ngm:autonomous-system ;
vc:isPartOf ngm:intelligent-environment ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:computational-resources ;
vc:requires ngm:goal-specification ;
vc:requires ngm:runtime-environment ;
vc:slug "autonomous-agent" ;
vc:sourceDomain "spatial-computing" .
ngm:autonomous-agent-framework-catalogue a owl:Class ;
rdfs:comment "A curated catalogue of open-source and commercial autonomous agent frameworks and projects, spanning general-purpose agents (AutoGPT, BabyAGI, CAMEL), coding agents (GPT Engineer, SWE-Agent), productivity agents, research agents, and DIY framework scaffolds (CrewAI, MetaGPT, AutoGen). The list provides practitioners with an entry point into the rapidly expanding agentic AI ecosystem."@en ;
rdfs:label "Autonomous Agent Framework Catalogue"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf _:r2394 ;
rdfs:subClassOf _:r2395 ;
skos:broader ngm:ai-application ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:agentic-ai ;
vc:hasPart ngm:autonomous-agent ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:reinforcement-learning ;
vc:slug "autonomous-agent-framework-catalogue" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:large-language-models ;
vc:uses ngm:tool-use .
ngm:autonomous-agent-learning a skos:Concept ;
rdfs:label "Autonomous Agent Learning"@en .
ngm:autonomous-agent-operation a skos:Concept ;
rdfs:label "Autonomous Agent Operation"@en .
ngm:autonomous-ai-agents a owl:Class ;
rdfs:comment "Autonomous AI Agents are intelligent software systems capable of independently perceiving their environment, reasoning over goals, planning multi-step action sequences, and executing tasks without continuous human intervention, typically powered by large language models or reinforcement learning. They differ from simpler AI tools by their ability to set sub-goals, call external tools, manage memory, and adapt dynamically to novel situations. Autonomous agents are increasingly deployed in enterprise workflows, research automation, customer service, and multi-agent collaborative systems."@en ;
rdfs:label "Autonomous AI Agents"@en ;
rdfs:subClassOf ngm:ai-agent-system ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf _:r2390 ;
rdfs:subClassOf _:r2391 ;
rdfs:subClassOf _:r2392 ;
rdfs:subClassOf _:r2393 ;
skos:broader ngm:ai-application ;
vc:bridgesTo ngm:autonomous-robot ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:planning-and-scheduling ;
vc:hasPart ngm:reasoning ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:autonomous-agent ;
vc:relatedTo ngm:autonomous-robot ;
vc:relatedTo ngm:multi-agent-systems ;
vc:requires ngm:ai-safety ;
vc:requires ngm:explainability ;
vc:slug "autonomous-ai-agents" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:large-language-models ;
vc:uses ngm:reinforcement-learning ;
vc:uses ngm:workflow-automation .
ngm:autonomous-artistic-system a skos:Concept ;
rdfs:label "Autonomous Artistic System"@en .
ngm:autonomous-behavior a owl:Class ;
rdfs:comment "The capacity of an agent, robot, or AI system to select and execute actions in pursuit of goals without continuous human instruction, using internal models of the world, perception of environmental state, and learned or programmed decision policies. Autonomous behaviour spans a continuum from simple reactive reflexes to deliberative planning over extended time horizons."@en ;
rdfs:label "Autonomous Behavior"@en ;
rdfs:subClassOf ngm:agentic-ai ;
rdfs:subClassOf ngm:autonomous-operation ;
rdfs:subClassOf ngm:goal-directed-behavior ;
rdfs:subClassOf _:r2403 ;
rdfs:subClassOf _:r2404 ;
rdfs:subClassOf _:r2405 ;
rdfs:subClassOf _:r2406 ;
rdfs:subClassOf _:r2407 ;
rdfs:subClassOf _:r2408 ;
rdfs:subClassOf _:r2409 ;
rdfs:subClassOf _:r2410 ;
rdfs:subClassOf _:r2411 ;
rdfs:subClassOf _:r2412 ;
rdfs:subClassOf _:r2413 ;
vc:contrastsWith ngm:human-in-the-loop ;
vc:contrastsWith ngm:remote-control ;
vc:contrastsWith ngm:rule-based-systems ;
vc:contrastsWith ngm:supervised-automation ;
vc:contrastsWith ngm:teleoperation ;
vc:dependsOn ngm:cognitive-architecture ;
vc:dependsOn ngm:perception-system ;
vc:dependsOn ngm:reinforcement-learning ;
vc:dependsOn ngm:reward-function ;
vc:dependsOn ngm:sensor-fusion ;
vc:dependsOn ngm:world-model ;
vc:enables ngm:agent-based-modelling ;
vc:enables ngm:autonomous-agent ;
vc:enables ngm:autonomous-task-execution ;
vc:enables ngm:embodied-ai ;
vc:enables ngm:multi-agent-systems ;
vc:enables ngm:swarm-intelligence ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:action-selection ;
vc:hasPart ngm:decision-making ;
vc:hasPart ngm:execution-monitor ;
vc:hasPart ngm:feedback-loop ;
vc:hasPart ngm:goal-representation ;
vc:hasPart ngm:perception-system ;
vc:hasPart ngm:planning-module ;
vc:hasPart ngm:policy-network ;
vc:hasPart ngm:world-model ;
vc:implements ngm:bdi-model ;
vc:implements ngm:hybrid-deliberative-reactive-architecture ;
vc:implements ngm:ooda-loop ;
vc:implements ngm:reinforcement-learning ;
vc:implements ngm:sense-plan-act-loop ;
vc:implements ngm:subsumption-architecture ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:agent-based-modelling ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:ai-alignment ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:bdi-model ;
vc:relatedTo ngm:behavioral-modeling ;
vc:relatedTo ngm:cognitive-architecture ;
vc:relatedTo ngm:embodied-ai ;
vc:relatedTo ngm:goal ;
vc:relatedTo ngm:reinforcement-learning ;
vc:relatedTo ngm:swarm-intelligence ;
vc:requires ngm:decision-making ;
vc:requires ngm:decision-policy ;
vc:requires ngm:feedback-loop ;
vc:requires ngm:goal-representation ;
vc:requires ngm:perception-system ;
vc:requires ngm:planning-module ;
vc:requires ngm:reward-function ;
vc:requires ngm:world-model ;
vc:slug "autonomous-behavior" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:ieee-p-7009 ;
vc:standardizedBy ngm:iso-8373 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:standardizedBy ngm:sae-j-3016 ;
vc:supports ngm:agent-based-modelling ;
vc:supports ngm:agentic-ai ;
vc:supports ngm:ai-safety ;
vc:supports ngm:human-in-the-loop ;
vc:supports ngm:multi-agent-systems ;
vc:supports ngm:swarm-intelligence ;
vc:uses ngm:behavioral-modeling ;
vc:uses ngm:large-language-models ;
vc:uses ngm:neural-network ;
vc:uses ngm:planning-module ;
vc:uses ngm:reinforcement-learning ;
vc:uses ngm:sensor-fusion ;
vc:uses ngm:task-planning .
ngm:autonomous-business-operations a owl:Class ;
rdfs:comment "The use of artificial intelligence systems to independently manage, execute, and optimize core business functions and workflows with minimal human intervention."@en ;
rdfs:label "Autonomous Business Operations"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:intelligent-automation ;
vc:slug "autonomous-business-operations" ;
vc:sourceDomain "artificial-intelligence" .
ngm:autonomous-coding a owl:Class ;
rdfs:comment "Autonomous coding is the capability of an AI agent to write, modify, test and debug software with minimal human intervention, planning and executing multi-step coding tasks end to end. It builds on code generation but adds agentic control loops for tool use, self-correction and iterative verification against a goal. It is a core capability enabled by agent frameworks, orchestrators and execution sandboxes."@en ;
rdfs:label "Autonomous Coding"@en ;
rdfs:subClassOf ngm:code-generation ;
vc:enables ngm:code-generation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:slug "autonomous-coding" ;
vc:sourceDomain "ai" .
ngm:autonomous-debugging a skos:Concept ;
rdfs:label "Autonomous Debugging"@en .
ngm:autonomous-decision-making a owl:Class ;
rdfs:comment "Autonomous decision making is the capacity of an artificial agent to select and commit to actions in pursuit of goals without requiring human authorisation for each choice. It combines perception of the environment, internal reasoning or learned policies, evaluation of expected outcomes, and action selection under uncertainty. Drawing on decision theory, planning, and reinforcement learning, it lets agents operate in dynamic settings where human supervision is impractical or too slow. Autonomous decision making is foundational to autonomous vehicles, robotic systems, and multi-agent coordination, and raises governance questions about accountability and human oversight."@en ;
rdfs:label "Autonomous Decision Making"@en ;
rdfs:subClassOf ngm:decision-making ;
rdfs:subClassOf _:r2414 ;
rdfs:subClassOf _:r2415 ;
rdfs:subClassOf _:r2416 ;
rdfs:subClassOf _:r2417 ;
vc:dependsOn ngm:decision-theory ;
vc:dependsOn ngm:reasoning ;
vc:enables ngm:autonomous-agent ;
vc:enables ngm:autonomous-vehicle ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:goal ;
vc:hasPart ngm:planning ;
vc:implements ngm:control-system ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:autonomous-agent ;
vc:relatedTo ngm:decision-theory ;
vc:relatedTo ngm:reasoning ;
vc:requires ngm:perception-system ;
vc:requires ngm:situational-awareness ;
vc:slug "autonomous-decision-making" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:multi-agent-system ;
vc:supports ngm:robotics ;
vc:uses ngm:planning ;
vc:uses ngm:reinforcement-learning .
ngm:autonomous-decision-making-without-oversight a skos:Concept ;
rdfs:label "Autonomous Decision Making Without Oversight"@en .
ngm:autonomous-delivery a owl:Class ;
rdfs:comment "Autonomous delivery is the use of self-navigating ground or aerial robots to transport goods from an origin to a destination without a human driver or operator. Delivery robots combine mapping, obstacle avoidance and route planning capabilities from autonomous mobile robotics with payload handling and secure drop-off mechanisms. It is deployed for last-mile parcel delivery, food delivery and campus or warehouse logistics, where it reduces labour cost and enables continuous operation."@en ;
rdfs:label "Autonomous Delivery"@en ;
rdfs:subClassOf ngm:autonomous-mobile-robots ;
rdfs:subClassOf _:r2418 ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.55"^^xsd:float ;
vc:requires ngm:autonomous-mobile-robots ;
vc:slug "autonomous-delivery" ;
vc:sourceDomain "robotics" .
ngm:autonomous-driving a owl:Class ;
rdfs:comment "Autonomous driving is the technical capability enabling a vehicle to perceive its environment, predict the behaviour of surrounding agents, plan a safe trajectory, and execute actuator commands without direct human intervention. The system architecture decomposes into perception (camera, Lidar, radar fusion), localisation (HD map matching, SLAM), prediction (probabilistic motion modelling), planning (route, behaviour, and motion planning layers), and control (longitudinal and lateral actuation). Safety assurance draws on formal verification, simulation, and real-world validation mileage, with regulatory oversight governed by frameworks such as SAE J3016, ISO 26262, and UN ECE WP.29. The field bridges robotics, machine learning, embedded systems, and transport infrastructure."@en ;
rdfs:label "Autonomous Driving"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:robotics ;
rdfs:subClassOf ngm:safety-critical-systems ;
rdfs:subClassOf _:r2427 ;
rdfs:subClassOf _:r2428 ;
rdfs:subClassOf _:r2429 ;
rdfs:subClassOf _:r2430 ;
rdfs:subClassOf _:r2431 ;
rdfs:subClassOf _:r2432 ;
rdfs:subClassOf _:r2433 ;
rdfs:subClassOf _:r2434 ;
rdfs:subClassOf _:r2435 ;
rdfs:subClassOf _:r2436 ;
rdfs:subClassOf _:r2437 ;
rdfs:subClassOf _:r2438 ;
rdfs:subClassOf _:r2439 ;
rdfs:subClassOf _:r2440 ;
rdfs:subClassOf _:r2441 ;
rdfs:subClassOf _:r2442 ;
skos:broader ngm:ai-application ;
skos:broader ngm:robotics ;
vc:bridgesTo ngm:5-g-network ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:robotics ;
vc:bridgesTo ngm:smart-city-infrastructure ;
vc:contrastsWith ngm:advanced-driver-assistance-system ;
vc:contrastsWith ngm:manual-driving ;
vc:contrastsWith ngm:teleoperation ;
vc:dependsOn ngm:edge-computing ;
vc:dependsOn ngm:functional-safety ;
vc:dependsOn ngm:gnss ;
vc:dependsOn ngm:gpu-compute ;
vc:dependsOn ngm:hd-maps ;
vc:dependsOn ngm:v2x-communication ;
vc:enables ngm:autonomous-freight ;
vc:enables ngm:autonomous-shuttle ;
vc:enables ngm:autonomous-vehicle ;
vc:enables ngm:last-mile-delivery ;
vc:enables ngm:robotaxi ;
vc:enables ngm:smart-city-infrastructure ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:autonomous-driving-perception ;
vc:hasPart ngm:behaviour-prediction ;
vc:hasPart ngm:hd-maps ;
vc:hasPart ngm:motion-planning ;
vc:hasPart ngm:path-planning ;
vc:hasPart ngm:simultaneous-localisation-and-mapping ;
vc:hasPart ngm:vehicle-control ;
vc:implements ngm:end-to-end-driving ;
vc:implements ngm:occupancy-prediction ;
vc:implements ngm:sae-j-3016 ;
vc:implements ngm:sensor-fusion ;
vc:qualityScore "0.88"^^xsd:float ;
vc:relatedTo ngm:digital-twin ;
vc:relatedTo ngm:functional-safety ;
vc:relatedTo ngm:internet-of-things ;
vc:relatedTo ngm:robotics ;
vc:relatedTo ngm:safety-critical-systems ;
vc:requires ngm:autonomous-driving-perception ;
vc:requires ngm:computer-vision ;
vc:requires ngm:edge-computing ;
vc:requires ngm:functional-safety ;
vc:requires ngm:gnss ;
vc:requires ngm:hd-maps ;
vc:requires ngm:lidar ;
vc:requires ngm:object-detection ;
vc:requires ngm:sensor-fusion ;
vc:requires ngm:simultaneous-localisation-and-mapping ;
vc:requires ngm:training-data ;
vc:slug "autonomous-driving" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:iso-26262 ;
vc:standardizedBy ngm:iso-sae-pas-21448 ;
vc:standardizedBy ngm:sae-j-3016 ;
vc:standardizedBy ngm:un-ece-wp-29 ;
vc:supports ngm:5-g-network ;
vc:supports ngm:digital-twin ;
vc:supports ngm:smart-city-infrastructure ;
vc:supports ngm:zero-emission-vehicles ;
vc:uses ngm:bayesian-inference ;
vc:uses ngm:convolutional-neural-network ;
vc:uses ngm:deep-learning ;
vc:uses ngm:model-predictive-control ;
vc:uses ngm:motion-planning ;
vc:uses ngm:path-planning ;
vc:uses ngm:reinforcement-learning ;
vc:uses ngm:transformer-architecture .
ngm:autonomous-driving-perception a owl:Class ;
rdfs:comment "The subsystem of an autonomous vehicle responsible for interpreting sensor data to construct a structured understanding of the vehicle's immediate environment, including the detection, classification, and tracking of objects, lane geometry, road surfaces, traffic signage, and dynamic actors. Autonomous driving perception fuses inputs from cameras, LiDAR, radar, and ultrasonic sensors to produce a real-time scene representation sufficient for safe navigation decisions."@en ;
rdfs:label "Autonomous Driving Perception"@en ;
rdfs:subClassOf ngm:computer-vision ;
rdfs:subClassOf ngm:perception-system ;
rdfs:subClassOf _:r2419 ;
rdfs:subClassOf _:r2420 ;
rdfs:subClassOf _:r2421 ;
rdfs:subClassOf _:r2422 ;
rdfs:subClassOf _:r2423 ;
rdfs:subClassOf _:r2424 ;
rdfs:subClassOf _:r2425 ;
rdfs:subClassOf _:r2426 ;
vc:contrastsWith ngm:remote-sensing ;
vc:contrastsWith ngm:rule-based-vision ;
vc:contrastsWith ngm:teleoperation ;
vc:dependsOn ngm:bayesian-inference ;
vc:dependsOn ngm:calibration ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:edge-computing ;
vc:dependsOn ngm:functional-safety ;
vc:dependsOn ngm:signal-processing ;
vc:enables ngm:autonomous-driving ;
vc:enables ngm:collision-avoidance ;
vc:enables ngm:motion-planning ;
vc:enables ngm:robotaxi ;
vc:enables ngm:scene-understanding ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:bird-eye-view ;
vc:hasPart ngm:bird-s-eye-view ;
vc:hasPart ngm:depth-estimation ;
vc:hasPart ngm:lane-detection ;
vc:hasPart ngm:object-detection ;
vc:hasPart ngm:object-tracking ;
vc:hasPart ngm:occupancy-prediction ;
vc:hasPart ngm:semantic-segmentation ;
vc:implements ngm:bird-s-eye-view ;
vc:implements ngm:multi-sensor-fusion ;
vc:implements ngm:occupancy-prediction ;
vc:qualityScore "0.85"^^xsd:float ;
vc:relatedTo ngm:digital-twin ;
vc:relatedTo ngm:functional-safety ;
vc:relatedTo ngm:iso-26262 ;
vc:relatedTo ngm:reinforcement-learning ;
vc:relatedTo ngm:simultaneous-localisation-and-mapping ;
vc:relatedTo ngm:sotif ;
vc:relatedTo ngm:v2x-communication ;
vc:requires ngm:camera-sensor ;
vc:requires ngm:edge-computing ;
vc:requires ngm:functional-safety ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:training-data ;
vc:slug "autonomous-driving-perception" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:iso-26262 ;
vc:standardizedBy ngm:iso-sae-pas-21448 ;
vc:supports ngm:behaviour-prediction ;
vc:supports ngm:path-planning ;
vc:supports ngm:simultaneous-localisation-and-mapping ;
vc:uses ngm:computer-vision ;
vc:uses ngm:convolutional-neural-network ;
vc:uses ngm:deep-learning ;
vc:uses ngm:hd-maps ;
vc:uses ngm:lidar ;
vc:uses ngm:point-cloud ;
vc:uses ngm:radar ;
vc:uses ngm:sensor-fusion ;
vc:uses ngm:transformer-architecture .
ngm:autonomous-driving-simulation a skos:Concept ;
rdfs:label "Autonomous Driving Simulation"@en .
ngm:autonomous-economic-agent a skos:Concept ;
rdfs:label "Autonomous Economic Agent"@en .
ngm:autonomous-economic-agents a skos:Concept ;
rdfs:label "Autonomous Economic Agents"@en .
ngm:autonomous-freight a skos:Concept ;
rdfs:label "Autonomous Freight"@en .
ngm:autonomous-governance a owl:Class ;
rdfs:comment "Autonomous governance is a model in which decision-making and rule enforcement are executed by code and protocol rather than by a central administrator, typically via smart contracts and on-chain voting. It enables decentralised organisations such as DAOs to allocate resources, upgrade parameters, and resolve disputes through transparent, programmatically binding processes. The approach trades human discretion for verifiable, tamper-resistant execution of collectively agreed rules."@en ;
rdfs:label "Autonomous Governance"@en ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
skos:broader ngm:bc-governance-and-regulation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:blockchain-entity ;
vc:relatedTo ngm:decentralised-coordination ;
vc:slug "autonomous-governance" ;
vc:sourceDomain "blockchain" .
ngm:autonomous-manipulation a owl:Class ;
rdfs:comment "Autonomous manipulation is the capability of a robot to perceive, plan and physically interact with objects to achieve a task goal without step-by-step human teleoperation. It integrates perception, grasp and motion planning, force control and feedback to handle uncertainty in object pose, shape and contact dynamics. The aim is robust, closed-loop interaction in unstructured environments rather than the repetition of pre-programmed trajectories."@en ;
rdfs:label "Autonomous Manipulation"@en ;
rdfs:subClassOf ngm:robotic-manipulation ;
rdfs:subClassOf _:r2443 ;
rdfs:subClassOf _:r2444 ;
vc:dependsOn ngm:feedback-control ;
vc:dependsOn ngm:robot-perception ;
vc:enables ngm:humanoid-robotics ;
vc:enables ngm:pick-and-place ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:motion-planning ;
vc:isPartOf ngm:robotic-manipulation ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:dexterous-manipulation ;
vc:relatedTo ngm:robotic-manipulation ;
vc:requires ngm:motion-planning ;
vc:requires ngm:robot-perception ;
vc:slug "autonomous-manipulation" ;
vc:sourceDomain "robotics" ;
vc:supports ngm:pick-and-place ;
vc:uses ngm:dexterous-manipulation ;
vc:uses ngm:robot-control .
ngm:autonomous-manufacturing a owl:Class ;
rdfs:comment "Autonomous manufacturing is a production model in which robotic systems and automated machinery execute manufacturing tasks — assembly, inspection, material handling, and quality control — with minimal or no direct human intervention, coordinated by software that senses conditions and adapts in real time. It extends manufacturing automation by incorporating perception, planning, and decision-making capabilities that let equipment respond to variation on the production line rather than following fixed, pre-programmed sequences. Autonomous manufacturing is a core pillar of Industry 4.0 initiatives that seek to combine robotics, sensing, and data analytics across the factory floor."@en ;
rdfs:label "Autonomous Manufacturing"@en ;
rdfs:subClassOf ngm:manufacturing-automation ;
rdfs:subClassOf _:r2445 ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:industry-4-0 ;
vc:slug "autonomous-manufacturing" ;
vc:sourceDomain "robotics" .
ngm:autonomous-market-operations a skos:Concept ;
rdfs:label "Autonomous Market Operations"@en .
ngm:autonomous-medical-ai a skos:Concept ;
rdfs:label "Autonomous Medical AI"@en .
ngm:autonomous-mobile-robot-safety a skos:Concept ;
rdfs:label "Autonomous Mobile Robot Safety"@en .
ngm:autonomous-mobile-robots a owl:Class ;
rdfs:comment "Robotic platforms capable of self-directed locomotion through environments, navigating without fixed infrastructure guidance by using onboard sensing, mapping, localisation, and path-planning capabilities. Autonomous mobile robots (AMRs) operate in dynamic, human-shared spaces and are distinguished from automated guided vehicles (AGVs) by their ability to adapt routes in real time rather than following pre-defined paths."@en ;
rdfs:label "Autonomous Mobile Robots"@en ;
rdfs:subClassOf ngm:mobile-robot ;
rdfs:subClassOf ngm:mobile-robotics ;
rdfs:subClassOf _:r2446 ;
rdfs:subClassOf _:r2447 ;
rdfs:subClassOf _:r2448 ;
rdfs:subClassOf _:r2449 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:spatial-computing ;
vc:enables ngm:autonomous-delivery ;
vc:enables ngm:logistics-automation ;
vc:enables ngm:mobile-manipulation ;
vc:enables ngm:warehouse-automation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:collision-avoidance ;
vc:hasPart ngm:navigation-stack ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:fleet-management ;
vc:relatedTo ngm:human-robot-interaction ;
vc:relatedTo ngm:mobile-robot-platform ;
vc:relatedTo ngm:ros-navigation-stack ;
vc:requires ngm:functional-safety ;
vc:requires ngm:real-time-computing ;
vc:slug "autonomous-mobile-robots" ;
vc:sourceDomain "robotics" ;
vc:standardizedBy ngm:iec-61508 ;
vc:standardizedBy ngm:iso-13482 ;
vc:uses ngm:deep-learning ;
vc:uses ngm:lidar ;
vc:uses ngm:path-planning ;
vc:uses ngm:ros ;
vc:uses ngm:sensor-fusion ;
vc:uses ngm:slam .
ngm:autonomous-navigation a owl:Class ;
rdfs:comment "Autonomous Navigation encompasses the complete system capability for a robot or autonomous agent to move from one location to another without human guidance, integrating perception, localisation, mapping, path planning, obstacle avoidance, and control. Autonomous navigation systems employ SLAM, sensor fusion, and AI-based decision-making to operate safely in unknown or dynamic environments."@en ;
rdfs:label "Autonomous Navigation"@en ;
rdfs:subClassOf ngm:autonomous-agent ;
rdfs:subClassOf _:r2450 ;
rdfs:subClassOf _:r2451 ;
rdfs:subClassOf _:r2452 ;
rdfs:subClassOf _:r2453 ;
rdfs:subClassOf _:r2454 ;
rdfs:subClassOf _:r2455 ;
vc:bridgesTo ngm:autonomous-robot ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:spatial-computing ;
vc:contrastsWith ngm:teleoperation ;
vc:dependsOn ngm:coordinate-frame ;
vc:dependsOn ngm:real-time-computing ;
vc:enables ngm:autonomous-robot ;
vc:enables ngm:autonomous-vehicle ;
vc:enables ngm:delivery-robot ;
vc:enables ngm:unmanned-aerial-vehicle ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:localisation ;
vc:hasPart ngm:obstacle-avoidance ;
vc:implements ngm:a-star-algorithm ;
vc:implements ngm:pid-controller ;
vc:isPartOf ngm:mobile-robotics ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:kalman-filter ;
vc:requires ngm:odometry ;
vc:requires ngm:perception ;
vc:requires ngm:sensor-fusion ;
vc:requires ngm:slam ;
vc:slug "autonomous-navigation" ;
vc:sourceDomain "robotics" ;
vc:supports ngm:human-robot-interaction ;
vc:supports ngm:search-and-rescue-robotics ;
vc:uses ngm:computer-vision ;
vc:uses ngm:lidar ;
vc:uses ngm:motion-planning ;
vc:uses ngm:path-planning ;
vc:uses ngm:reinforcement-learning .
ngm:autonomous-operation a owl:Class ;
rdfs:comment "The sustained execution of a system's core functions without ongoing human intervention, encompassing self-monitoring, self-configuration, self-healing, and self-optimisation capabilities that allow the system to maintain operational objectives across varying environmental conditions and failure states. Autonomous operation represents the highest level of system self-sufficiency on the automation continuum."@en ;
rdfs:label "Autonomous Operation"@en ;
rdfs:subClassOf ngm:autonomous-system ;
rdfs:subClassOf ngm:process-automation ;
rdfs:subClassOf ngm:workflow-automation ;
rdfs:subClassOf _:r2456 ;
rdfs:subClassOf _:r2457 ;
rdfs:subClassOf _:r2458 ;
rdfs:subClassOf _:r2459 ;
rdfs:subClassOf _:r2460 ;
rdfs:subClassOf _:r2461 ;
rdfs:subClassOf _:r2462 ;
rdfs:subClassOf _:r2463 ;
rdfs:subClassOf _:r2464 ;
rdfs:subClassOf _:r2465 ;
rdfs:subClassOf _:r2466 ;
vc:bridgesTo ngm:agentic-ai ;
vc:bridgesTo ngm:autonomous-task-execution ;
vc:bridgesTo ngm:internet-of-things ;
vc:bridgesTo ngm:multi-agent-orchestration ;
vc:bridgesTo ngm:smart-grid ;
vc:contrastsWith ngm:human-in-the-loop ;
vc:contrastsWith ngm:manual-control ;
vc:contrastsWith ngm:robotic-process-automation ;
vc:contrastsWith ngm:supervised-automation ;
vc:contrastsWith ngm:teleoperation ;
vc:dependsOn ngm:autonomic-computing ;
vc:dependsOn ngm:cognitive-architecture ;
vc:dependsOn ngm:foundation-model ;
vc:dependsOn ngm:reinforcement-learning ;
vc:dependsOn ngm:sensor-networks ;
vc:dependsOn ngm:state-estimation ;
vc:dependsOn ngm:tool-use ;
vc:enables ngm:agentic-workflow ;
vc:enables ngm:aiops ;
vc:enables ngm:autonomous-agent ;
vc:enables ngm:autonomous-mobile-robots ;
vc:enables ngm:autonomous-task-execution ;
vc:enables ngm:predictive-maintenance ;
vc:enables ngm:process-automation ;
vc:enables ngm:self-healing-system ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:agent-loop ;
vc:hasPart ngm:decision-engine ;
vc:hasPart ngm:fault-tolerant-control ;
vc:hasPart ngm:feedback-control ;
vc:hasPart ngm:mape-k-loop ;
vc:hasPart ngm:monitoring-system ;
vc:hasPart ngm:perception-module ;
vc:hasPart ngm:self-healing-system ;
vc:implements ngm:adaptive-control ;
vc:implements ngm:autonomic-computing ;
vc:implements ngm:cognitive-architecture ;
vc:implements ngm:mape-k-loop ;
vc:implements ngm:reinforcement-learning ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:aiops ;
vc:relatedTo ngm:closed-loop-control ;
vc:relatedTo ngm:cybersecurity ;
vc:relatedTo ngm:digital-twin ;
vc:relatedTo ngm:distributed-control-system ;
vc:relatedTo ngm:graceful-degradation ;
vc:relatedTo ngm:multi-agent-orchestration ;
vc:relatedTo ngm:operational-design-domain ;
vc:relatedTo ngm:prompt-injection ;
vc:requires ngm:autonomous-behavior ;
vc:requires ngm:decision-engine ;
vc:requires ngm:fault-tolerant-control ;
vc:requires ngm:feedback-control ;
vc:requires ngm:operational-design-domain ;
vc:requires ngm:perception-module ;
vc:requires ngm:situation-awareness ;
vc:slug "autonomous-operation" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:functional-safety ;
vc:standardizedBy ngm:iec-61508 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:standardizedBy ngm:sae-j-3016 ;
vc:supports ngm:ai-alignment ;
vc:supports ngm:ai-safety ;
vc:supports ngm:fault-tolerant-control ;
vc:supports ngm:functional-safety ;
vc:supports ngm:human-in-the-loop ;
vc:uses ngm:agent-memory ;
vc:uses ngm:chain-of-thought ;
vc:uses ngm:digital-twin ;
vc:uses ngm:distributed-control-system ;
vc:uses ngm:function-calling ;
vc:uses ngm:large-language-models ;
vc:uses ngm:model-context-protocol .
ngm:autonomous-proof-generation a owl:Class ;
rdfs:comment "The capability of AI systems to independently formulate, generate, and verify mathematical proofs without human intervention."@en ;
rdfs:label "Autonomous Proof Generation"@en ;
rdfs:subClassOf ngm:model ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:alethea-agent ;
vc:relatedTo ngm:model ;
vc:slug "autonomous-proof-generation" ;
vc:sourceDomain "artificial-intelligence" .
ngm:autonomous-reasoning a skos:Concept ;
rdfs:label "Autonomous Reasoning"@en .
ngm:autonomous-replication a skos:Concept ;
rdfs:label "Autonomous Replication"@en .
ngm:autonomous-robot a owl:Class ;
rdfs:comment "A robotic system equipped with sensors, processing units, and actuators that operates independently to perform tasks without direct human control, using Artificial Intelligence and Autonomous Navigation to perceive, reason, and act in physical or virtual environments."@en ;
rdfs:label "Autonomous Robot"@en ;
rdfs:subClassOf ngm:robotic-system ;
rdfs:subClassOf _:r2467 ;
rdfs:subClassOf _:r2468 ;
rdfs:subClassOf _:r2469 ;
rdfs:subClassOf _:r2470 ;
rdfs:subClassOf _:r2471 ;
rdfs:subClassOf _:r2472 ;
rdfs:subClassOf _:r2473 ;
vc:bridgesTo ngm:blockchain-identity ;
vc:bridgesTo ngm:deep-learning ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:edge-computing ;
vc:bridgesTo ngm:internet-of-things ;
vc:contrastsWith ngm:teleoperated-robot ;
vc:dependsOn ngm:artificial-intelligence ;
vc:dependsOn ngm:simultaneous-localisation-and-mapping ;
vc:enables ngm:autonomous-delivery ;
vc:enables ngm:autonomous-navigation ;
vc:enables ngm:warehouse-automation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:actuators ;
vc:hasPart ngm:obstacle-avoidance ;
vc:hasPart ngm:sensors ;
vc:implements ngm:ai-system ;
vc:implements ngm:mobile-robot ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:multi-agent-systems ;
vc:relatedTo ngm:robot-learning ;
vc:relatedTo ngm:swarm-robotics ;
vc:requires ngm:computer-vision ;
vc:requires ngm:path-planning ;
vc:requires ngm:real-time-control ;
vc:requires ngm:sensor-fusion ;
vc:slug "autonomous-robot" ;
vc:sourceDomain "robotics" ;
vc:supports ngm:human-robot-interaction ;
vc:supports ngm:multi-agent-systems ;
vc:uses ngm:deep-learning ;
vc:uses ngm:motion-planning ;
vc:uses ngm:reinforcement-learning ;
vc:uses ngm:robot-perception .
ngm:autonomous-shuttle a skos:Concept ;
rdfs:label "Autonomous Shuttle"@en .
ngm:autonomous-suturing a skos:Concept ;
rdfs:label "Autonomous Suturing"@en .
ngm:autonomous-system a owl:Class ;
rdfs:comment "An Autonomous System is a computational or physical entity capable of perceiving its environment through sensors, reasoning over that perception, and executing goal-directed actions without continuous human intervention, forming closed-loop sense-plan-act cycles. Architecturally, autonomous systems combine perception pipelines, world-model maintenance, deliberative or reactive planning, and actuator control, often augmented by machine learning to handle environmental uncertainty. They operate across a spectrum from fully automated (no human input required) to conditionally autonomous (human on the loop), and encompass platforms as diverse as self-driving vehicles, unmanned aerial systems, autonomous underwater vehicles, industrial robotic cells, and intelligent software agents."@en ;
rdfs:label "Autonomous System"@en ;
rdfs:subClassOf ngm:robo-robot-type ;
rdfs:subClassOf _:r2474 ;
rdfs:subClassOf _:r2475 ;
rdfs:subClassOf _:r2476 ;
rdfs:subClassOf _:r2477 ;
rdfs:subClassOf _:r2478 ;
rdfs:subClassOf _:r2479 ;
rdfs:subClassOf _:r2480 ;
rdfs:subClassOf _:r2481 ;
skos:broader ngm:robo-robot-type ;
vc:bridgesTo ngm:ai-safety ;
vc:bridgesTo ngm:edge-computing ;
vc:contrastsWith ngm:semi-autonomous-system ;
vc:contrastsWith ngm:teleoperated-robot ;
vc:dependsOn ngm:control-theory ;
vc:dependsOn ngm:embedded-systems ;
vc:enables ngm:autonomous-agent ;
vc:enables ngm:autonomous-robot ;
vc:enables ngm:autonomous-vehicle ;
vc:enables ngm:autonomous-warehouse-robot ;
vc:enables ngm:unmanned-aerial-vehicle ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:actuation-system ;
vc:hasPart ngm:perception-module ;
vc:hasPart ngm:planning-module ;
vc:hasPart ngm:sensor ;
vc:hasPart ngm:world-model ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:cyber-physical-systems ;
vc:relatedTo ngm:functional-safety ;
vc:relatedTo ngm:robot-safety ;
vc:requires ngm:motion-planning ;
vc:requires ngm:real-time-computing ;
vc:requires ngm:sensor-fusion ;
vc:requires ngm:state-estimation ;
vc:slug "autonomous-system" ;
vc:sourceDomain "robotics" ;
vc:standardizedBy ngm:iso-iec-42010 ;
vc:standardizedBy ngm:sae-j-3016 ;
vc:supports ngm:human-robot-interaction ;
vc:supports ngm:multi-robot-systems ;
vc:uses ngm:computer-vision ;
vc:uses ngm:deep-learning ;
vc:uses ngm:reinforcement-learning ;
vc:uses ngm:simultaneous-localisation-and-mapping .
ngm:autonomous-systems a skos:Concept ;
rdfs:label "Autonomous Systems"@en .
ngm:autonomous-task-execution a owl:Class ;
rdfs:comment "Autonomous Task Execution refers to the capacity of AI agents or automated systems to independently carry out goal-directed actions — including planning, tool invocation, error recovery, and result validation — without continuous human supervision. It encompasses the full lifecycle from task decomposition through completion, spanning single-step tool calls and long-horizon multi-step workflows."@en ;
rdfs:label "Autonomous Task Execution"@en ;
rdfs:subClassOf ngm:agentic-ai ;
rdfs:subClassOf ngm:autonomous-operation ;
rdfs:subClassOf ngm:process-automation ;
rdfs:subClassOf ngm:workflow-automation ;
rdfs:subClassOf _:r2482 ;
rdfs:subClassOf _:r2483 ;
rdfs:subClassOf _:r2484 ;
rdfs:subClassOf _:r2485 ;
rdfs:subClassOf _:r2486 ;
rdfs:subClassOf _:r2487 ;
rdfs:subClassOf _:r2488 ;
rdfs:subClassOf _:r2489 ;
rdfs:subClassOf _:r2490 ;
rdfs:subClassOf _:r2491 ;
rdfs:subClassOf _:r2492 ;
rdfs:subClassOf _:r2493 ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:bridgesTo ngm:internet-of-agents ;
vc:bridgesTo ngm:physical-automation ;
vc:bridgesTo ngm:robotics ;
vc:contrastsWith ngm:manual-task-completion ;
vc:contrastsWith ngm:robotic-process-automation ;
vc:contrastsWith ngm:scripted-automation ;
vc:contrastsWith ngm:single-turn-inference ;
vc:contrastsWith ngm:supervised-automation ;
vc:dependsOn ngm:agent-memory ;
vc:dependsOn ngm:agentic-ai ;
vc:dependsOn ngm:context-management ;
vc:dependsOn ngm:foundation-model ;
vc:dependsOn ngm:large-language-models ;
vc:dependsOn ngm:reasoning ;
vc:dependsOn ngm:retrieval-augmented-generation ;
vc:dependsOn ngm:vector-database ;
vc:enables ngm:agentic-workflow ;
vc:enables ngm:autonomous-coding ;
vc:enables ngm:human-in-the-loop ;
vc:enables ngm:multi-agent-orchestration ;
vc:enables ngm:process-automation ;
vc:enables ngm:scientific-discovery ;
vc:enables ngm:software-development-automation ;
vc:enables ngm:workflow-automation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:agent-loop ;
vc:hasPart ngm:error-recovery ;
vc:hasPart ngm:result-validation ;
vc:hasPart ngm:sandboxed-execution ;
vc:hasPart ngm:task-decomposition ;
vc:hasPart ngm:task-planning ;
vc:hasPart ngm:tool-use ;
vc:implements ngm:chain-of-thought ;
vc:implements ngm:function-calling ;
vc:implements ngm:long-horizon-planning ;
vc:implements ngm:model-context-protocol ;
vc:implements ngm:plan-and-execute-pattern ;
vc:implements ngm:react-prompting ;
vc:implements ngm:reflexion ;
vc:qualityScore "0.92"^^xsd:float ;
vc:relatedTo ngm:agent-frameworks ;
vc:relatedTo ngm:ai-alignment ;
vc:relatedTo ngm:autonomous-operation ;
vc:relatedTo ngm:cognitive-architecture ;
vc:relatedTo ngm:distributed-collaboration ;
vc:relatedTo ngm:llm-agents ;
vc:relatedTo ngm:long-horizon-planning ;
vc:relatedTo ngm:prompt-injection ;
vc:relatedTo ngm:react-prompting ;
vc:relatedTo ngm:swe-bench ;
vc:relatedTo ngm:task-completion-verification ;
vc:requires ngm:error-recovery ;
vc:requires ngm:foundation-model ;
vc:requires ngm:operational-design-domain ;
vc:requires ngm:reasoning ;
vc:requires ngm:sandboxed-execution ;
vc:requires ngm:task-decomposition ;
vc:requires ngm:task-planning ;
vc:slug "autonomous-task-execution" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:model-context-protocol ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:standardizedBy ngm:owasp-llm-top-10-2025 ;
vc:supports ngm:ai-alignment ;
vc:supports ngm:ai-safety ;
vc:supports ngm:functional-safety ;
vc:supports ngm:human-in-the-loop ;
vc:uses ngm:automated-planning ;
vc:uses ngm:chain-of-thought ;
vc:uses ngm:embedding-model ;
vc:uses ngm:function-calling ;
vc:uses ngm:large-language-models ;
vc:uses ngm:model-context-protocol ;
vc:uses ngm:prompt-engineering ;
vc:uses ngm:reinforcement-learning ;
vc:uses ngm:tool-use ;
vc:uses ngm:working-memory .
ngm:autonomous-underwater-vehicle a skos:Concept ;
rdfs:label "Autonomous Underwater Vehicle"@en .
ngm:autonomous-vehicle a owl:Class ;
rdfs:comment "An Autonomous Vehicle is a self-driving vehicle capable of navigating and operating without human intervention, employing artificial intelligence for perception, localisation, path planning, motion control, and decision-making. Autonomous vehicles integrate sensor fusion, computer vision, deep learning, and control algorithms to achieve SAE automation levels ranging from Level 1 (driver assistance) to Level 5 (full automation)."@en ;
rdfs:label "Autonomous Vehicle"@en ;
rdfs:subClassOf ngm:autonomous-robot ;
rdfs:subClassOf _:r2498 ;
rdfs:subClassOf _:r2499 ;
rdfs:subClassOf _:r2500 ;
rdfs:subClassOf _:r2501 ;
rdfs:subClassOf _:r2502 ;
rdfs:subClassOf _:r2503 ;
vc:bridgesTo ngm:autonomous-robot ;
vc:bridgesTo ngm:smart-city-infrastructure ;
vc:bridgesTo ngm:v2x-communication ;
vc:contrastsWith ngm:remotely-operated-vehicle-rov ;
vc:enables ngm:autonomous-navigation ;
vc:enables ngm:last-mile-delivery ;
vc:enables ngm:robotaxi ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:decision-making ;
vc:hasPart ngm:motion-planning ;
vc:hasPart ngm:perception-system ;
vc:implements ngm:adas ;
vc:implements ngm:path-planning ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:ground-robot ;
vc:relatedTo ngm:path-planning ;
vc:relatedTo ngm:self-driving-car ;
vc:requires ngm:perception-system ;
vc:requires ngm:sensor-fusion ;
vc:requires ngm:slam ;
vc:slug "autonomous-vehicle" ;
vc:sourceDomain "robotics" ;
vc:standardizedBy ngm:iso-21448 ;
vc:standardizedBy ngm:iso-26262 ;
vc:standardizedBy ngm:sae-j-3016 ;
vc:uses ngm:computer-vision ;
vc:uses ngm:deep-learning ;
vc:uses ngm:lidar ;
vc:uses ngm:motion-planning ;
vc:uses ngm:reinforcement-learning ;
vc:uses ngm:slam .
ngm:autonomous-vehicle-control a owl:Class ;
rdfs:comment "Autonomous vehicle control is the set of algorithms and systems that compute steering, acceleration and braking commands for a self-driving vehicle in order to safely follow a planned trajectory. It draws on model-based control, which uses an explicit dynamics model to compute corrective actions, and on optimal control, which formulates control as minimising a cost function subject to the vehicle's dynamics and constraints. It must operate reliably under uncertainty from sensing, actuation and the surrounding environment."@en ;
rdfs:label "Autonomous Vehicle Control"@en ;
rdfs:subClassOf ngm:autonomous-vehicle ;
rdfs:subClassOf _:r2494 ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:optimal-control ;
vc:slug "autonomous-vehicle-control" ;
vc:sourceDomain "robotics" .
ngm:autonomous-vehicle-regulation a skos:Concept ;
rdfs:label "Autonomous Vehicle Regulation"@en .
ngm:autonomous-vehicle-simulation a skos:Concept ;
rdfs:label "Autonomous Vehicle Simulation"@en .
ngm:autonomous-vehicle-testing a owl:Class ;
rdfs:comment "Autonomous vehicle testing is the discipline of validating the safety, reliability, and performance of self-driving systems through simulation, closed-course trials, and supervised public-road operation. It exercises the perception, planning, and control stack against a vast space of driving scenarios, including rare and hazardous edge cases that are impractical to encounter physically. Simulation-based testing has become central because it enables scalable, repeatable, and safe exploration of these scenarios before real-world deployment."@en ;
rdfs:label "Autonomous Vehicle Testing"@en ;
rdfs:subClassOf ngm:autonomous-vehicle ;
rdfs:subClassOf _:r2495 ;
rdfs:subClassOf _:r2496 ;
rdfs:subClassOf _:r2497 ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:enables ngm:self-driving-car ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:simulation ;
vc:implements ngm:computational-model ;
vc:isPartOf ngm:autonomous-vehicle ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:digital-twin ;
vc:relatedTo ngm:robotics ;
vc:relatedTo ngm:spatial-computing ;
vc:requires ngm:computational-model ;
vc:requires ngm:perception-system ;
vc:slug "autonomous-vehicle-testing" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:autonomous-driving ;
vc:supports ngm:self-driving-car ;
vc:uses ngm:digital-twin ;
vc:uses ngm:physics-engine ;
vc:uses ngm:simulation .
ngm:autonomous-warehouse-robot a skos:Concept ;
rdfs:label "Autonomous Warehouse Robot"@en .
ngm:autonomous-warehousing a skos:Concept ;
rdfs:label "Autonomous Warehousing"@en .
ngm:autonomous-weapons a skos:Concept ;
rdfs:label "Autonomous Weapons"@en .
ngm:autonomous-weapons-system a skos:Concept ;
rdfs:label "Autonomous Weapons System"@en .
ngm:autonomous-workflows a skos:Concept ;
rdfs:label "Autonomous Workflows"@en .
ngm:autonomousvehicles a skos:Concept ;
rdfs:label "Autonomousvehicles"@en .
ngm:autonomy-level a owl:Class ;
rdfs:comment "A graded classification (typically 0–5) quantifying the degree to which an agent perceives, decides, and acts without human intervention, ranging from fully manual operation through partial and conditional autonomy to full self-governance, with domain-specific scales for AI, robotics, blockchain DAOs, and multi-agent systems."@en ;
rdfs:label "Autonomy Level"@en ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf ngm:network-component ;
rdfs:subClassOf _:r2504 ;
rdfs:subClassOf _:r2505 ;
rdfs:subClassOf _:r2506 ;
skos:broader ngm:blockchain ;
vc:enables ngm:ai-agent-system ;
vc:enables ngm:bdi-model ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:agent ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:goal ;
vc:relatedTo ngm:objective ;
vc:requires ngm:human-in-the-loop ;
vc:requires ngm:safety ;
vc:slug "autonomy-level" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument .
ngm:autopilot a skos:Concept ;
rdfs:label "Autopilot"@en .
ngm:autopoiesis a skos:Concept ;
rdfs:label "Autopoiesis"@en .
ngm:autoregressive-decoding a owl:Class ;
rdfs:comment "Autoregressive decoding is the process by which a sequence model, such as a transformer language model, generates output one token at a time, conditioning each new token on all previously generated tokens. At every step the model produces a probability distribution over the vocabulary, a token is selected by a chosen strategy, and the token is appended and fed back as input for the next step. It is the dominant generation paradigm for large language models and is the primary target of inference optimisations such as caching and speculative methods."@en ;
rdfs:label "Autoregressive Decoding"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:large-language-model ;
rdfs:subClassOf _:r2507 ;
rdfs:subClassOf _:r2508 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:model-serving ;
vc:contrastsWith ngm:beam-search ;
vc:dependsOn ngm:attention-mechanism ;
vc:enables ngm:large-language-model ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:sampling ;
vc:implements ngm:sampling ;
vc:isPartOf ngm:large-language-model ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:beam-search ;
vc:relatedTo ngm:speculative-decoding ;
vc:requires ngm:transformer ;
vc:slug "autoregressive-decoding" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:transformer ;
vc:supports ngm:model-serving ;
vc:uses ngm:kv-cache .
ngm:autoregressive-factorisation a skos:Concept ;
rdfs:label "Autoregressive Factorisation"@en .
ngm:autoregressive-generation a owl:Class ;
rdfs:comment "Autoregressive generation is a sequence-modelling approach in which each output element is produced conditioned on all previously generated elements, factorising the joint probability of a sequence into a product of conditional next-element distributions. In language models it manifests as repeated next-token prediction, where the model samples or selects a token, appends it to the context, and repeats. This left-to-right dependency is the dominant decoding paradigm for large language models and underlies generative text, code, and other ordered outputs."@en ;
rdfs:label "Autoregressive Generation"@en ;
rdfs:subClassOf ngm:generative-ai ;
rdfs:subClassOf _:r2509 ;
rdfs:subClassOf _:r2510 ;
rdfs:subClassOf _:r2511 ;
vc:bridgesTo ngm:attention-mechanism ;
vc:dependsOn ngm:language-model ;
vc:enables ngm:large-language-model ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:decoder ;
vc:hasPart ngm:token ;
vc:implements ngm:generative-ai ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:inference ;
vc:relatedTo ngm:large-language-model ;
vc:requires ngm:inference ;
vc:slug "autoregressive-generation" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:natural-language-generation ;
vc:supports ngm:text-generation ;
vc:uses ngm:beam-search ;
vc:uses ngm:sampling ;
vc:uses ngm:transformer .
ngm:autoregressive-image-decoding a skos:Concept ;
rdfs:label "Autoregressive Image Decoding"@en .
ngm:autoregressive-model a owl:Class ;
rdfs:comment "An autoregressive model generates sequences by predicting each element conditioned on all previously generated elements, thereby factorising the joint probability distribution of a sequence into an ordered product of conditional distributions via the chain rule of probability. This approach yields exact log-likelihoods and a straightforward maximum-likelihood training objective, making it the dominant paradigm for large language models, neural audio synthesis, and image generation. Inference is inherently sequential — each token must be sampled before the next can be computed — creating a fundamental latency trade-off relative to parallel decoding strategies. Modern architectures such as the Transformer exploit masked self-attention to parallelise training while preserving the strictly left-to-right conditional structure at inference time."@en ;
rdfs:label "Autoregressive Model"@en ;
rdfs:subClassOf ngm:deep-generative-model ;
rdfs:subClassOf ngm:generative-model ;
rdfs:subClassOf ngm:probabilistic-model ;
rdfs:subClassOf _:r2512 ;
rdfs:subClassOf _:r2513 ;
rdfs:subClassOf _:r2514 ;
rdfs:subClassOf _:r2515 ;
rdfs:subClassOf _:r2516 ;
rdfs:subClassOf _:r2517 ;
rdfs:subClassOf _:r2518 ;
vc:bridgesTo ngm:constitutional-ai-training-methodology ;
vc:bridgesTo ngm:multimodal-ai-architecture-ai ;
vc:bridgesTo ngm:protein-structure-prediction ;
vc:bridgesTo ngm:reinforcement-learning-from-human-feedback ;
vc:contrastsWith ngm:diffusion-model ;
vc:contrastsWith ngm:flow-based-model ;
vc:contrastsWith ngm:generative-adversarial-network ;
vc:contrastsWith ngm:masked-language-modelling ;
vc:contrastsWith ngm:vae ;
vc:dependsOn ngm:byte-pair-encoding ;
vc:dependsOn ngm:cross-entropy-loss ;
vc:dependsOn ngm:gpu-computing ;
vc:dependsOn ngm:self-attention ;
vc:dependsOn ngm:softmax-function ;
vc:dependsOn ngm:training-data ;
vc:enables ngm:code-generation ;
vc:enables ngm:image-generation ;
vc:enables ngm:language-model ;
vc:enables ngm:large-language-model ;
vc:enables ngm:neural-audio-synthesis ;
vc:enables ngm:protein-structure-prediction ;
vc:enables ngm:text-generation ;
vc:enables ngm:time-series-forecasting ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:decoder-stack ;
vc:hasPart ngm:embedding-layer ;
vc:hasPart ngm:key-value-cache ;
vc:hasPart ngm:language-model-head ;
vc:implements ngm:maximum-likelihood-estimation ;
vc:implements ngm:next-token-prediction ;
vc:implements ngm:teacher-forcing ;
vc:qualityScore "0.92"^^xsd:float ;
vc:relatedTo ngm:beam-search ;
vc:relatedTo ngm:hallucination ;
vc:relatedTo ngm:next-token-prediction ;
vc:relatedTo ngm:pixelcnn ;
vc:relatedTo ngm:recurrent-neural-network ;
vc:relatedTo ngm:scaling-laws ;
vc:relatedTo ngm:speculative-decoding ;
vc:relatedTo ngm:time-series-forecasting ;
vc:relatedTo ngm:wave-net ;
vc:requires ngm:chain-rule-of-probability ;
vc:requires ngm:gpu-computing ;
vc:requires ngm:neural-network-text-tokenisation ;
vc:requires ngm:probabilistic-model ;
vc:requires ngm:tokenization ;
vc:requires ngm:training-data ;
vc:slug "autoregressive-model" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:acl ;
vc:standardizedBy ngm:iclr ;
vc:standardizedBy ngm:icml ;
vc:standardizedBy ngm:neur-ips ;
vc:supports ngm:chain-of-thought-reasoning ;
vc:supports ngm:in-context-learning ;
vc:supports ngm:prompt-engineering ;
vc:supports ngm:retrieval-augmented-generation ;
vc:uses ngm:beam-search ;
vc:uses ngm:byte-pair-encoding ;
vc:uses ngm:cross-entropy-loss ;
vc:uses ngm:flash-attention ;
vc:uses ngm:key-value-cache ;
vc:uses ngm:self-attention ;
vc:uses ngm:softmax-function ;
vc:uses ngm:speculative-decoding ;
vc:uses ngm:transformer .
ngm:autoregressive-sampling a skos:Concept ;
rdfs:label "Autoregressive Sampling"@en .
ngm:autoscaling a owl:Class ;
rdfs:comment "Autoscaling is the automated adjustment of computing resources allocated to an application in response to observed demand, scaling capacity up under load and down when demand falls. It monitors metrics such as utilisation, request rate or queue depth and triggers provisioning or removal of compute instances or containers against defined policies. Autoscaling improves cost efficiency and availability by matching supply to demand without manual intervention."@en ;
rdfs:label "Autoscaling"@en ;
rdfs:subClassOf ngm:resource-management ;
rdfs:subClassOf _:r2519 ;
rdfs:subClassOf _:r2520 ;
rdfs:subClassOf _:r2521 ;
rdfs:subClassOf _:r2522 ;
vc:contrastsWith ngm:capacity-planning ;
vc:dependsOn ngm:cloud-computing ;
vc:enables ngm:high-availability ;
vc:enables ngm:scalability ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:load-balancing ;
vc:hasPart ngm:monitoring ;
vc:implements ngm:infrastructure-as-code ;
vc:isPartOf ngm:resource-management ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:auto-scaling ;
vc:relatedTo ngm:load-balancing ;
vc:relatedTo ngm:microservices ;
vc:requires ngm:capacity-planning ;
vc:requires ngm:monitoring ;
vc:slug "autoscaling" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:cloud-native ;
vc:supports ngm:high-availability ;
vc:supports ngm:performance-optimization ;
vc:uses ngm:container-orchestration ;
vc:uses ngm:kubernetes ;
vc:uses ngm:observability .
ngm:autostereoscopic-display a skos:Concept ;
rdfs:label "Autostereoscopic Display"@en .
ngm:auxiliary-load-balancing-loss a skos:Concept ;
rdfs:label "Auxiliary Load Balancing Loss"@en .
ngm:auxiliary-variable-method a skos:Concept ;
rdfs:label "Auxiliary Variable Method"@en .
ngm:av1-codec a owl:Class ;
rdfs:comment "AV1 is a royalty-free video coding format developed by the Alliance for Open Media to deliver high compression efficiency for streaming and real-time video. It typically achieves around 30 percent better compression than HEVC/VP9 at equivalent quality, making it well suited to bandwidth-constrained applications such as screen sharing and live video. Being open and licence-free, it is widely adopted across browsers, hardware decoders, and conferencing platforms."@en ;
rdfs:label "AV1 Codec"@en ;
rdfs:subClassOf ngm:technical-standard ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:screen-sharing ;
vc:slug "av1-codec" ;
vc:sourceDomain "infrastructure" .
ngm:av1-video-codec a skos:Concept ;
rdfs:label "AV1 Video Codec"@en .
ngm:avail a skos:Concept ;
rdfs:label "Avail"@en .
ngm:availability a skos:Concept ;
rdfs:label "Availability"@en .
ngm:availability-scheduler a skos:Concept ;
rdfs:label "Availability Scheduler"@en .
ngm:avalanche a owl:Class ;
rdfs:comment "Avalanche is a high-throughput, low-latency layer-1 blockchain platform developed by Ava Labs that employs the Avalanche consensus family — a suite of leaderless, Byzantine-fault-tolerant protocols (Snowflake, Snowball, Avalanche) based on repeated random sub-sampled voting — to achieve probabilistic transaction finality in under two seconds. The platform is architecturally divided into three purpose-built chains: the Exchange Chain (X-Chain) for UTXO-model asset transfers, the Platform Chain (P-Chain) for validator and subnet management, and the Contract Chain (C-Chain) providing an EVM-compatible execution environment for Solidity smart contracts. Its subnet (now called L1) model allows developers to launch application-specific blockchains with custom virtual machines while optionally sharing primary-network validator sets, enabling both permissioned enterprise deployments and public decentralised applications within a unified interoperable ecosystem."@en ;
rdfs:label "Avalanche"@en ;
rdfs:subClassOf ngm:blockchain-network ;
rdfs:subClassOf _:r2526 ;
rdfs:subClassOf _:r2527 ;
vc:bridgesTo ngm:enterprise-blockchain ;
vc:bridgesTo ngm:real-world-asset-tokenisation ;
vc:contrastsWith ngm:ethereum ;
vc:contrastsWith ngm:polkadot ;
vc:contrastsWith ngm:polygon ;
vc:contrastsWith ngm:solana ;
vc:enables ngm:cross-chain-interoperability ;
vc:enables ngm:decentralised-application ;
vc:enables ngm:decentralized-application ;
vc:enables ngm:decentralized-finance-de-fi ;
vc:enables ngm:neural-network-text-tokenisation ;
vc:enables ngm:tokenization ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:c-chain ;
vc:hasPart ngm:p-chain ;
vc:hasPart ngm:subnet ;
vc:hasPart ngm:x-chain ;
vc:implements ngm:avalanche-consensus ;
vc:implements ngm:byzantine-fault-tolerance ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:distributed-ledger-technology ;
vc:relatedTo ngm:ethereum-smart-contract-platform ;
vc:relatedTo ngm:layer-1-blockchain ;
vc:relatedTo ngm:warp-messaging ;
vc:requires ngm:staking ;
vc:requires ngm:validator-node ;
vc:slug "avalanche" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:consensus-mechanism ;
vc:uses ngm:evm ;
vc:uses ngm:proof-of-stake ;
vc:uses ngm:smart-contract .
ngm:avalanche-consensus a skos:Concept ;
rdfs:label "Avalanche Consensus"@en .
ngm:avalanche-effect a owl:Class ;
rdfs:comment "The avalanche effect is a desirable property of cryptographic primitives whereby a tiny change in the input, such as flipping a single bit, produces an extensive, unpredictable change in the output, ideally altering about half of the output bits. In hash functions and ciphers it is the practical expression of diffusion, ensuring that outputs reveal no exploitable correlation with their inputs. A strong avalanche effect is essential for collision and preimage resistance and for resisting differential cryptanalysis."@en ;
rdfs:label "Avalanche Effect"@en ;
rdfs:subClassOf ngm:cryptography ;
rdfs:subClassOf _:r2523 ;
rdfs:subClassOf _:r2524 ;
rdfs:subClassOf _:r2525 ;
vc:enables ngm:collision-resistance ;
vc:enables ngm:preimage-resistance ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:cryptographic-hash ;
vc:implements ngm:cryptographic-hash-function ;
vc:isPartOf ngm:cryptography ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:information-security ;
vc:relatedTo ngm:merkle-tree ;
vc:requires ngm:cryptographic-hash-function ;
vc:requires ngm:hash-function ;
vc:slug "avalanche-effect" ;
vc:sourceDomain "security" ;
vc:supports ngm:blockchain-security ;
vc:supports ngm:digital-signature ;
vc:supports ngm:encryption ;
vc:uses ngm:hash-function .
ngm:avalanche-photodiode a skos:Concept ;
rdfs:label "Avalanche Photodiode"@en .
ngm:avalanche-snow-consensus a skos:Concept ;
rdfs:label "Avalanche Snow Consensus"@en .
ngm:avatar a owl:Class ;
rdfs:comment "A digital representation of a person or autonomous agent used to perceive, act, and interact within a virtual or mixed-reality environment, embodying identity, appearance, and behavioural state."@en ;
rdfs:label "Avatar"@en ;
rdfs:subClassOf ngm:sc-content-and-assets ;
rdfs:subClassOf _:r2554 ;
rdfs:subClassOf _:r2555 ;
rdfs:subClassOf _:r2556 ;
rdfs:subClassOf _:r2557 ;
skos:broader ngm:sc-content-and-assets ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:self-sovereign-identity ;
vc:contrastsWith ngm:ai-agent ;
vc:contrastsWith ngm:non-player-character ;
vc:dependsOn ngm:identity-management ;
vc:dependsOn ngm:network-synchronization ;
vc:enables ngm:distributed-collaboration ;
vc:enables ngm:non-verbal-communication ;
vc:enables ngm:social-presence ;
vc:enables ngm:user-embodiment ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:animation-rig ;
vc:hasPart ngm:visual-mesh ;
vc:implements ngm:gltf-standard ;
vc:implements ngm:hanim-standard ;
vc:isPartOf ngm:metaverse ;
vc:isPartOf ngm:virtual-world ;
vc:qualityScore "0.7"^^xsd:float ;
vc:relatedTo ngm:augmented-reality ;
vc:relatedTo ngm:virtual-reality ;
vc:requires ngm:3-d-rendering-engine ;
vc:requires ngm:motion-capture ;
vc:requires ngm:physics-engine ;
vc:slug "avatar" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:accessibility ;
vc:supports ngm:personalisation ;
vc:uses ngm:inverse-kinematics ;
vc:uses ngm:level-of-detail .
ngm:avatar-animation a owl:Class ;
rdfs:comment "Avatar animation is the specialised subset of digital animation concerned with driving the motion and expression of user-controlled or AI-controlled avatar representations in real-time interactive environments. It encompasses full-body locomotion, facial expression synthesis, hand and gaze tracking, and upper-body gesture systems, all coordinated to produce social believability within virtual and extended reality spaces. Avatar animation systems must balance visual fidelity with low-latency responsiveness to maintain user embodiment and presence. Standards such as VRM and glTF define interchange formats that allow avatar animations to transfer across platforms."@en ;
rdfs:label "Avatar Animation"@en ;
rdfs:subClassOf ngm:animation ;
rdfs:subClassOf _:r2528 ;
rdfs:subClassOf _:r2529 ;
rdfs:subClassOf _:r2530 ;
rdfs:subClassOf _:r2531 ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:bridgesTo ngm:natural-language-processing ;
vc:enables ngm:embodied-interaction ;
vc:enables ngm:immersive-experience ;
vc:enables ngm:social-presence ;
vc:enables ngm:telepresence ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:facial-animation ;
vc:hasPart ngm:gaze-tracking ;
vc:hasPart ngm:lip-sync ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:avatar ;
vc:relatedTo ngm:avatar-interoperability ;
vc:relatedTo ngm:avatar-system ;
vc:relatedTo ngm:embodiment ;
vc:relatedTo ngm:non-verbal-communication ;
vc:relatedTo ngm:virtual-reality ;
vc:requires ngm:pose-estimation ;
vc:requires ngm:real-time-rendering ;
vc:slug "avatar-animation" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:gltf-standard ;
vc:standardizedBy ngm:metaverse-standards-forum ;
vc:uses ngm:animation-retargeting ;
vc:uses ngm:blend-tree ;
vc:uses ngm:inverse-kinematics ;
vc:uses ngm:motion-capture ;
vc:uses ngm:skeletal-animation ;
vc:uses ngm:vrm-format .
ngm:avatar-behavior a owl:Class ;
rdfs:comment "The set of behavioural patterns, animation responses, and interactive capabilities that govern how avatars and NPCs act in virtual environments, driven by AI/ML inference, procedural animation, inverse kinematics, facial expression synthesis, and real-time response to user inputs and social context."@en ;
rdfs:label "Avatar Behavior"@en ;
rdfs:subClassOf ngm:metaverse ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
skos:broader ngm:sc-platform-and-environment ;
vc:bridgesTo ngm:did-nostr-identity ;
vc:enables ngm:immersive-experience ;
vc:enables ngm:social-presence ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:metaverse ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:ai-avatars ;
vc:relatedTo ngm:avatar ;
vc:relatedTo ngm:avatar-system ;
vc:relatedTo ngm:digital-human-technology ;
vc:relatedTo ngm:intelligent-npc ;
vc:slug "avatar-behavior" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:animation-retargeting ;
vc:uses ngm:behavioral-modeling ;
vc:uses ngm:inverse-kinematics .
ngm:avatar-creation a owl:Class ;
rdfs:comment "Avatar Creation is the process of designing and generating 3D digital representations of users for metaverse environments, encompassing selfie-based AI generation, manual customization tools, full-body scanning, and procedural generation techniques that enable personalized virtual identities."@en ;
rdfs:label "Avatar Creation"@en ;
rdfs:subClassOf ngm:digital-identity-creation ;
rdfs:subClassOf ngm:sc-content-and-assets ;
rdfs:subClassOf ngm:sc-interaction ;
rdfs:subClassOf _:r2532 ;
rdfs:subClassOf _:r2533 ;
rdfs:subClassOf _:r2534 ;
rdfs:subClassOf _:r2535 ;
rdfs:subClassOf _:r2536 ;
rdfs:subClassOf _:r2537 ;
skos:broader ngm:sc-content-and-assets ;
skos:broader ngm:sc-interaction ;
vc:bridgesTo ngm:did-nostr-identity ;
vc:enables ngm:metaverse ;
vc:enables ngm:persona ;
vc:enables ngm:virtual-self-expression ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:3d-modelling ;
vc:requires ngm:ai-art-generation ;
vc:requires ngm:avatar-customization ;
vc:slug "avatar-creation" ;
vc:sourceDomain "spatial-computing" .
ngm:avatar-creator a skos:Concept ;
rdfs:label "Avatar Creator"@en .
ngm:avatar-customisation a skos:Concept ;
rdfs:label "Avatar Customisation"@en .
ngm:avatar-customization a owl:Class ;
rdfs:comment "Avatar Customization is the practice of modifying and personalizing digital avatar attributes including physical features, clothing, accessories, animations, and expressions to create unique virtual representations that reflect user identity and preferences in metaverse and spatial-computing environments."@en ;
rdfs:label "Avatar Customization"@en ;
rdfs:subClassOf ngm:digital-personalization ;
rdfs:subClassOf ngm:sc-content-and-assets ;
rdfs:subClassOf _:r2538 ;
rdfs:subClassOf _:r2539 ;
skos:broader ngm:sc-content-and-assets ;
vc:bridgesTo ngm:decentralised-identity ;
vc:bridgesTo ngm:did-nostr-identity ;
vc:contrastsWith ngm:non-player-character ;
vc:dependsOn ngm:parametric-design-methodology ;
vc:dependsOn ngm:user-generated-content ;
vc:enables ngm:identity-representation ;
vc:enables ngm:self-expression ;
vc:enables ngm:social-distinction ;
vc:enables ngm:social-presence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:avatar-animation ;
vc:implements ngm:digital-identity ;
vc:qualityScore "0.7"^^xsd:float ;
vc:relatedTo ngm:avatar-interoperability ;
vc:relatedTo ngm:ready-player-me ;
vc:requires ngm:3-d-rendering-engine ;
vc:requires ngm:asset-libraries ;
vc:requires ngm:customization-tools ;
vc:requires ngm:real-time-preview ;
vc:slug "avatar-customization" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:cross-platform-avatar ;
vc:supports ngm:virtual-economy ;
vc:uses ngm:procedural-generation ;
vc:uses ngm:recommendation-system ;
vc:uses ngm:texture-mapping .
ngm:avatar-embodiment a owl:Class ;
rdfs:comment "Avatar Embodiment is the psychological and technical phenomenon in which a user perceives a digital avatar as an extension or representation of their own body within a virtual or mixed reality environment. It involves mapping real-time motion capture, physiological signals, and expressive cues from the user onto the avatar to create a sense of ownership and presence. High-fidelity embodiment enhances social telepresence by allowing remote participants to express identity, emotion, and intent through their avatars."@en ;
rdfs:label "Avatar Embodiment"@en ;
rdfs:subClassOf ngm:telepresence ;
vc:enables ngm:social-presence ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.7"^^xsd:float ;
vc:relatedTo ngm:shared-virtual-space ;
vc:relatedTo ngm:virtual-reality-telepresence ;
vc:slug "avatar-embodiment" ;
vc:sourceDomain "distributed-collaboration" .
ngm:avatar-generation a skos:Concept ;
rdfs:label "Avatar Generation"@en .
ngm:avatar-interoperability a owl:Class ;
rdfs:comment "Capability enabling an avatar's identity, appearance, and behaviors to function seamlessly across multiple metaverse platforms and virtual environments."@en ;
rdfs:label "Avatar Interoperability"@en ;
rdfs:subClassOf ngm:infra-network-and-comms ;
rdfs:subClassOf _:r2540 ;
rdfs:subClassOf _:r2541 ;
rdfs:subClassOf _:r2542 ;
rdfs:subClassOf _:r2543 ;
rdfs:subClassOf _:r2544 ;
skos:broader ngm:infra-network-and-comms ;
vc:bridgesTo ngm:did-nostr-identity ;
vc:dependsOn ngm:gltf-standard ;
vc:dependsOn ngm:hanim-standard ;
vc:dependsOn ngm:vrm-format ;
vc:enables ngm:cross-platform-presence ;
vc:enables ngm:persistent-identity ;
vc:enables ngm:seamless-migration ;
vc:enables ngm:universal-avatar ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:appearance-translation ;
vc:hasPart ngm:behavior-mapping ;
vc:hasPart ngm:cross-platform-authentication ;
vc:hasPart ngm:identity-portability ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:avatar-standard ;
vc:requires ngm:data-serialization ;
vc:requires ngm:identity-protocol ;
vc:requires ngm:platform-api ;
vc:slug "avatar-interoperability" ;
vc:sourceDomain "infrastructure" .
ngm:avatar-physics a skos:Concept ;
rdfs:label "Avatar Physics"@en .
ngm:avatar-portability a owl:Class ;
rdfs:comment "Avatar Portability is the capability to transfer digital avatar representations between different metaverse platforms, applications, and virtual worlds while maintaining visual fidelity, customization, and associated digital assets, enabled by standardized formats and interoperability frameworks."@en ;
rdfs:label "Avatar Portability"@en ;
rdfs:subClassOf ngm:asset-portability ;
rdfs:subClassOf ngm:sc-standards-and-interop ;
rdfs:subClassOf _:r2545 ;
rdfs:subClassOf _:r2546 ;
skos:broader ngm:sc-standards-and-interop ;
vc:bridgesTo ngm:bc-token-and-asset ;
vc:bridgesTo ngm:did-nostr-identity ;
vc:bridgesTo ngm:non-fungible-token ;
vc:bridgesTo ngm:self-sovereign-identity ;
vc:contrastsWith ngm:platform-lock-in ;
vc:dependsOn ngm:gltf-standard ;
vc:dependsOn ngm:open-metaverse-interoperability ;
vc:dependsOn ngm:vrm-format ;
vc:enables ngm:asset-continuity ;
vc:enables ngm:cross-platform-identity ;
vc:enables ngm:seamless-world-transitions ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:asset-portability ;
vc:isPartOf ngm:metaverse-interoperability ;
vc:qualityScore "0.68"^^xsd:float ;
vc:relatedTo ngm:digital-twin ;
vc:relatedTo ngm:ready-player-me ;
vc:requires ngm:digital-identity ;
vc:requires ngm:platform-integration ;
vc:requires ngm:standardized-formats ;
vc:requires ngm:translation-frameworks ;
vc:slug "avatar-portability" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:khronos-group ;
vc:supports ngm:metaverse-standards-forum ;
vc:uses ngm:did-nostr-identity .
ngm:avatar-presence a skos:Concept ;
rdfs:label "Avatar Presence"@en .
ngm:avatar-renderer a skos:Concept ;
rdfs:label "Avatar Renderer"@en .
ngm:avatar-sdk a skos:Concept ;
rdfs:label "Avatar SDK"@en .
ngm:avatar-standard a owl:Class ;
rdfs:comment "Avatar Standard refers to technical specifications defining file formats, data structures, rigging conventions, and metadata schemas for 3D humanoid avatars, particularly the VRM format built on glTF 2.0 that enables cross-platform avatar interoperability in metaverse environments."@en ;
rdfs:label "Avatar Standard"@en ;
rdfs:subClassOf ngm:sc-standards-and-interop ;
rdfs:subClassOf ngm:technical-standard ;
rdfs:subClassOf _:r2547 ;
skos:broader ngm:sc-standards-and-interop ;
vc:bridgesTo ngm:technical-standard ;
vc:enables ngm:avatar-interoperability ;
vc:enables ngm:platform-independent-identities ;
vc:enables ngm:standardized-rigging ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:format-compliance ;
vc:requires ngm:metadata-specification ;
vc:requires ngm:skeleton-configuration ;
vc:slug "avatar-standard" ;
vc:sourceDomain "spatial-computing" .
ngm:avatar-streaming a skos:Concept ;
rdfs:label "Avatar Streaming"@en .
ngm:avatar-synthesis a skos:Concept ;
rdfs:label "Avatar Synthesis"@en .
ngm:avatar-system a owl:Class ;
rdfs:comment "Avatar System is the integrated technical architecture for creating, customizing, animating, and rendering digital representations of users in virtual environments, encompassing character models, animation systems, facial expression rigs, physics simulations, and real-time rendering pipelines."@en ;
rdfs:label "Avatar System"@en ;
rdfs:subClassOf ngm:sc-content-and-assets ;
rdfs:subClassOf ngm:virtual-character-system ;
rdfs:subClassOf _:r2548 ;
rdfs:subClassOf _:r2549 ;
rdfs:subClassOf _:r2550 ;
rdfs:subClassOf _:r2551 ;
rdfs:subClassOf _:r2552 ;
rdfs:subClassOf _:r2553 ;
skos:broader ngm:sc-content-and-assets ;
vc:bridgesTo ngm:digital-identity ;
vc:contrastsWith ngm:non-player-character ;
vc:dependsOn ngm:facial-tracking ;
vc:dependsOn ngm:graphics-pipeline ;
vc:dependsOn ngm:motion-capture ;
vc:enables ngm:embodied-presence ;
vc:enables ngm:nonverbal-communication ;
vc:enables ngm:social-interaction ;
vc:enables ngm:user-representation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:animation-controller ;
vc:hasPart ngm:level-of-detail ;
vc:hasPart ngm:physics-simulation ;
vc:implements ngm:inverse-kinematics ;
vc:implements ngm:physically-based-rendering ;
vc:isPartOf ngm:metaverse-infrastructure ;
vc:isPartOf ngm:virtual-world-platform ;
vc:qualityScore "0.7"^^xsd:float ;
vc:relatedTo ngm:augmented-reality ;
vc:relatedTo ngm:virtual-reality ;
vc:requires ngm:3-d-rendering-engine ;
vc:requires ngm:animation-controller ;
vc:requires ngm:input-processing ;
vc:requires ngm:skeletal-mesh ;
vc:slug "avatar-system" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:avatar-customization ;
vc:supports ngm:avatar-interoperability ;
vc:uses ngm:blend-shape ;
vc:uses ngm:eye-tracking .
ngm:avatar-wearable a owl:Class ;
rdfs:comment "Digital clothing, accessories, and cosmetic items that can be equipped by avatars in virtual environments, often tokenised as NFTs to enable ownership, cross-platform portability, and secondary-market trading within metaverse economies."@en ;
rdfs:label "Avatar Wearable"@en ;
rdfs:subClassOf ngm:digital-asset ;
rdfs:subClassOf ngm:sc-content-and-assets ;
skos:broader ngm:sc-content-and-assets ;
vc:bridgesTo ngm:digital-asset ;
vc:bridgesTo ngm:telecollaboration ;
vc:enables ngm:virtual-economy-infrastructure ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:avatar-system ;
vc:isPartOf ngm:virtual-economy ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:avatar ;
vc:relatedTo ngm:avatar-customization ;
vc:relatedTo ngm:avatar-interoperability ;
vc:relatedTo ngm:nft ;
vc:relatedTo ngm:nft-standard ;
vc:slug "avatar-wearable" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:3-d-asset ;
vc:uses ngm:digital-asset-management .
ngm:average-case-complexity a skos:Concept ;
rdfs:label "Average Case Complexity"@en .
ngm:average-handle-time-reduction a skos:Concept ;
rdfs:label "Average Handle Time Reduction"@en .
ngm:average-lagging-metric a skos:Concept ;
rdfs:label "Average Lagging Metric"@en .
ngm:average-precision a skos:Concept ;
rdfs:label "Average Precision"@en .
ngm:avionics a owl:Class ;
rdfs:comment "Avionics refers to the electronic systems used on aircraft and spacecraft for communication, navigation, flight control, monitoring, and mission management. These systems are safety-critical and must meet stringent real-time, reliability, and certification standards such as DO-178C and DO-254. Avionics is a canonical domain for hard real-time computing, where deterministic timing and fault tolerance are essential to flight safety."@en ;
rdfs:label "Avionics"@en ;
rdfs:subClassOf ngm:control-system ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:real-time ;
vc:slug "avionics" ;
vc:sourceDomain "infrastructure" .
ngm:avs3 a skos:Concept ;
rdfs:label "Avs3"@en .
ngm:awareness a owl:Class ;
rdfs:comment "Awareness in metaverse contexts refers to systems and mechanisms that provide users with perception of other participants, environmental changes, and relevant contextual information in shared virtual spaces, supporting presence, social interaction, and collaborative activities through visual, aud..."@en ;
rdfs:label "Awareness"@en ;
rdfs:subClassOf ngm:sc-interaction ;
rdfs:subClassOf ngm:social-computing ;
rdfs:subClassOf _:r2558 ;
rdfs:subClassOf _:r2559 ;
rdfs:subClassOf _:r2560 ;
skos:broader ngm:sc-interaction ;
vc:bridgesTo ngm:dc-communication ;
vc:enables ngm:collaborative-presence ;
vc:enables ngm:collaborative-systems-modality-presence ;
vc:enables ngm:situational-understanding ;
vc:enables ngm:social-interaction ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:notification-system ;
vc:requires ngm:notification-systems ;
vc:requires ngm:presence-detection ;
vc:requires ngm:state-synchronisation ;
vc:slug "awareness" ;
vc:sourceDomain "spatial-computing" .
ngm:aws a skos:Concept ;
rdfs:label "Aws"@en .
ngm:aws-bedrock a skos:Concept ;
rdfs:label "Aws Bedrock"@en .
ngm:aws-bedrock-agentcore a skos:Concept ;
rdfs:label "Aws Bedrock Agentcore"@en .
ngm:aws-financial-performance a skos:Concept ;
rdfs:label "Aws Financial Performance"@en .
ngm:aws-iam a skos:Concept ;
rdfs:label "Aws Iam"@en .
ngm:aws-nitro-enclaves a skos:Concept ;
rdfs:label "Aws Nitro Enclaves"@en .
ngm:aws-open-data-sponsorship-programme a skos:Concept ;
rdfs:label "Aws Open Data Sponsorship Programme"@en .
ngm:axe-core a skos:Concept ;
rdfs:label "Axe Core"@en .
ngm:axelar a owl:Class ;
rdfs:comment "Axelar is a decentralised cross-chain communication network that enables general message passing and token transfers between heterogeneous blockchains via a proof-of-stake overlay network and a permissionless gateway smart contract model. It provides a Universal Message Passing (UMP) primitive that allows any contract on any connected chain to call any contract on any other connected chain as a single composable operation."@en ;
rdfs:label "Axelar"@en ;
rdfs:subClassOf ngm:cross-chain-interoperability ;
rdfs:subClassOf _:r2561 ;
rdfs:subClassOf _:r2562 ;
rdfs:subClassOf _:r2563 ;
rdfs:subClassOf _:r2564 ;
rdfs:subClassOf _:r2565 ;
vc:bridgesTo ngm:cosmos-ibc ;
vc:bridgesTo ngm:ethereum-smart-contract-platform ;
vc:contrastsWith ngm:chainlink-ccip ;
vc:contrastsWith ngm:layer-zero ;
vc:contrastsWith ngm:wormhole ;
vc:dependsOn ngm:byzantine-fault-tolerance ;
vc:dependsOn ngm:cosmos-sdk ;
vc:enables ngm:cross-chain-dex ;
vc:enables ngm:cross-chain-governance ;
vc:enables ngm:cross-chain-messaging ;
vc:enables ngm:omnichain-application ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:interchain-token-service ;
vc:hasPart ngm:smart-contract ;
vc:hasPart ngm:squid-router ;
vc:hasPart ngm:token ;
vc:isPartOf ngm:cosmos ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:bridge ;
vc:relatedTo ngm:interoperability-protocol ;
vc:requires ngm:threshold-cryptography ;
vc:requires ngm:validator-set ;
vc:slug "axelar" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:de-fi-protocol ;
vc:supports ngm:evm ;
vc:supports ngm:non-evm-chain ;
vc:uses ngm:consensus-mechanism ;
vc:uses ngm:message-passing ;
vc:uses ngm:proof-of-stake .
ngm:axie-infinity a owl:Class ;
rdfs:comment "Axie Infinity is a blockchain-based game in which players collect, breed, and battle digital creatures called Axies that are represented as non-fungible tokens."@en ;
rdfs:label "Axie Infinity"@en ;
rdfs:subClassOf ngm:nft ;
rdfs:subClassOf _:r2566 ;
rdfs:subClassOf _:r2567 ;
vc:bridgesTo ngm:ethereum-smart-contract-platform ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:nft ;
vc:requires ngm:smart-contract ;
vc:slug "axie-infinity" ;
vc:sourceDomain "blockchain" .
ngm:axiom a skos:Concept ;
rdfs:label "Axiom"@en .
ngm:axiom-rules a skos:Concept ;
rdfs:label "Axiom Rules"@en .
ngm:axiom-set a skos:Concept ;
rdfs:label "Axiom Set"@en .
ngm:axis-vector a skos:Concept ;
rdfs:label "Axis Vector"@en .
ngm:aya-expanse a skos:Concept ;
rdfs:label "Aya Expanse"@en .
ngm:azimuth-drive a skos:Concept ;
rdfs:label "Azimuth Drive"@en .
ngm:aztec a owl:Class ;
rdfs:comment "A privacy-focused Layer 2 network for Ethereum that uses zero-knowledge proofs to enable confidential transactions and private smart contract execution, supporting encrypted notes, private state transitions, and programmable privacy at the application layer."@en ;
rdfs:label "Aztec"@en ;
rdfs:subClassOf ngm:layer-2-networks ;
rdfs:subClassOf _:r2576 ;
rdfs:subClassOf _:r2577 ;
rdfs:subClassOf _:r2578 ;
rdfs:subClassOf _:r2579 ;
rdfs:subClassOf _:r2580 ;
vc:bridgesTo ngm:aztec-protocol ;
vc:bridgesTo ngm:distributed-systems ;
vc:bridgesTo ngm:security ;
vc:contrastsWith ngm:arbitrum ;
vc:contrastsWith ngm:blockchain ;
vc:contrastsWith ngm:optimism ;
vc:dependsOn ngm:cryptographic-proof ;
vc:dependsOn ngm:ethereum ;
vc:enables ngm:confidential-transactions ;
vc:enables ngm:privacy ;
vc:enables ngm:private-smart-contract ;
vc:enables ngm:programmable-privacy ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:aztec-protocol ;
vc:implements ngm:optimistic-rollup ;
vc:implements ngm:privacy-preserving-computation ;
vc:isPartOf ngm:blockchain ;
vc:isPartOf ngm:ethereum ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:polygon-zkevm ;
vc:relatedTo ngm:starknet ;
vc:relatedTo ngm:tornado-cash ;
vc:requires ngm:ethereum-smart-contract-platform ;
vc:requires ngm:rollup ;
vc:requires ngm:zero-knowledge-proof ;
vc:requires ngm:zk-snark ;
vc:slug "aztec" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:de-fi ;
vc:supports ngm:digital-asset ;
vc:uses ngm:homomorphic-encryption ;
vc:uses ngm:noir ;
vc:uses ngm:utxo-model .
ngm:aztec-network a owl:Class ;
rdfs:comment "The privacy-preserving Layer 2 network operated under the Aztec protocol, providing confidential transactions and private smart contracts settled on Ethereum."@en ;
rdfs:label "Aztec Network"@en ;
rdfs:subClassOf ngm:aztec ;
rdfs:subClassOf _:r2568 ;
rdfs:subClassOf _:r2569 ;
vc:bridgesTo ngm:layer-2-networks ;
vc:enables ngm:privacy ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:aztec-protocol ;
vc:requires ngm:ethereum-smart-contract-platform ;
vc:slug "aztec-network" ;
vc:sourceDomain "blockchain" .
ngm:aztec-protocol a owl:Class ;
rdfs:comment "The protocol underlying the Aztec network that combines zero-knowledge proofs with an encrypted note model to provide confidential transactions and private smart contracts on Ethereum, enabling programmable privacy through a UTXO-style note commitment scheme verified by recursive ZK rollup proofs."@en ;
rdfs:label "Aztec Protocol"@en ;
rdfs:subClassOf ngm:aztec ;
rdfs:subClassOf _:r2570 ;
rdfs:subClassOf _:r2571 ;
rdfs:subClassOf _:r2572 ;
rdfs:subClassOf _:r2573 ;
rdfs:subClassOf _:r2574 ;
rdfs:subClassOf _:r2575 ;
vc:bridgesTo ngm:aztec-network ;
vc:bridgesTo ngm:de-fi ;
vc:bridgesTo ngm:security ;
vc:contrastsWith ngm:optimistic-rollup ;
vc:contrastsWith ngm:tornado-cash ;
vc:contrastsWith ngm:zcash ;
vc:enables ngm:confidential-transactions ;
vc:enables ngm:privacy ;
vc:enables ngm:private-smart-contract ;
vc:enables ngm:programmable-privacy ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:aztec ;
vc:hasPart ngm:aztec-network ;
vc:implements ngm:plonk ;
vc:implements ngm:utxo-model ;
vc:implements ngm:zk-rollup ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:cryptographic-commitment ;
vc:relatedTo ngm:ethereum ;
vc:relatedTo ngm:layer-2-scaling ;
vc:requires ngm:commitment-scheme ;
vc:requires ngm:ethereum-smart-contract-platform ;
vc:requires ngm:zero-knowledge-proof ;
vc:requires ngm:zk-snark ;
vc:slug "aztec-protocol" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:homomorphic-encryption ;
vc:uses ngm:merkle-tree ;
vc:uses ngm:noir .
ngm:azure a owl:Class ;
rdfs:comment "Azure is Microsoft's public cloud computing platform offering compute, storage, networking, identity and managed services."@en ;
rdfs:label "Azure"@en ;
rdfs:subClassOf ngm:cloud-computing ;
rdfs:subClassOf _:r2581 ;
vc:bridgesTo ngm:microsoft-entra-verified-id ;
vc:enables ngm:web-3-infrastructure ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:identity-management ;
vc:slug "azure" ;
vc:sourceDomain "distributed-systems" .
ngm:azure-active-directory a skos:Concept ;
rdfs:label "Azure Active Directory"@en .
ngm:azure-blob-storage a skos:Concept ;
rdfs:label "Azure Blob Storage"@en .
ngm:azure-confidential-consortium-framework a skos:Concept ;
rdfs:label "Azure Confidential Consortium Framework"@en .
ngm:azure-confidential-ledger a skos:Concept ;
rdfs:label "Azure Confidential Ledger"@en .
ngm:azure-machine-learning a skos:Concept ;
rdfs:label "Azure Machine Learning"@en .
ngm:b-tree a skos:Concept ;
rdfs:label "B Tree"@en .
ngm:b-tree-index a owl:Class ;
rdfs:comment "A B-tree index is a self-balancing tree data structure used by database engines to maintain sorted data and support efficient logarithmic-time lookups, range scans, insertions, and deletions. Each node holds multiple sorted keys and child pointers, keeping the tree shallow and minimising disk reads relative to a binary tree. It is the default index structure in relational database systems such as PostgreSQL for primary keys and most secondary indexes."@en ;
rdfs:label "B-Tree Index"@en ;
rdfs:subClassOf ngm:data-structure ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.0"^^xsd:float ;
vc:slug "b-tree-index" ;
vc:sourceDomain "infrastructure" .
ngm:b-tree-indexing a skos:Concept ;
rdfs:label "B Tree Indexing"@en .
ngm:b2b-collaboration a skos:Concept ;
rdfs:label "B2b Collaboration"@en .
ngm:b2c-identity a skos:Concept ;
rdfs:label "B2c Identity"@en .
ngm:b2e-identity a skos:Concept ;
rdfs:label "B2e Identity"@en .
ngm:b3i a skos:Concept ;
rdfs:label "B3i"@en .
ngm:baai a skos:Concept ;
rdfs:label "Baai"@en .
ngm:babe-consensus a skos:Concept ;
rdfs:label "Babe Consensus"@en .
ngm:babylon-js a owl:Class ;
rdfs:comment "Babylon.js is an open-source, JavaScript and TypeScript real-time 3D rendering engine for the web that drives interactive graphics, games, and immersive experiences through WebGL and WebGPU backends. It provides a scene graph, physically based rendering, a node-based material system, glTF asset loading, an animation system, physics integration, and first-class WebXR support for virtual and augmented reality. As a spatial-computing framework it is a common foundation for browser-delivered metaverse and 3D applications, abstracting low-level GPU programming behind a high-level scene and entity API."@en ;
rdfs:label "Babylon Js"@en ;
rdfs:subClassOf ngm:rendering-engine ;
rdfs:subClassOf _:r2692 ;
rdfs:subClassOf _:r2693 ;
vc:bridgesTo ngm:game-engine ;
vc:bridgesTo ngm:web-xr ;
vc:contrastsWith ngm:three-js ;
vc:dependsOn ngm:rendering-pipeline ;
vc:enables ngm:real-time-rendering ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:scene-graph ;
vc:implements ngm:physically-based-rendering ;
vc:implements ngm:rendering-pipeline ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:real-time-rendering ;
vc:relatedTo ngm:scene-graph ;
vc:relatedTo ngm:three-js ;
vc:requires ngm:webgpu ;
vc:slug "babylon-js" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:gltf-standard ;
vc:supports ngm:web-xr ;
vc:uses ngm:shader ;
vc:uses ngm:webgpu .
ngm:babylon-protocol a skos:Concept ;
rdfs:label "Babylon Protocol"@en .
ngm:back-face-culling a skos:Concept ;
rdfs:label "Back Face Culling"@en .
ngm:back-office-automation a skos:Concept ;
rdfs:label "Back Office Automation"@en .
ngm:back-translation a owl:Class ;
rdfs:comment "Back-translation is a data augmentation and quality-assurance technique in machine translation where text translated into a target language is translated back into the source language. As an augmentation method, monolingual target-language data is translated into the source language to create synthetic parallel pairs that improve translation models. As a QA method, the round-trip output is compared with the original to detect meaning drift."@en ;
rdfs:label "Back-Translation"@en ;
rdfs:subClassOf ngm:data-augmentation ;
rdfs:subClassOf ngm:natural-language-processing ;
rdfs:subClassOf _:r2694 ;
rdfs:subClassOf _:r2695 ;
rdfs:subClassOf _:r2696 ;
rdfs:subClassOf _:r2697 ;
rdfs:subClassOf _:r2698 ;
rdfs:subClassOf _:r2699 ;
rdfs:subClassOf _:r2700 ;
vc:contrastsWith ngm:forward-translation ;
vc:contrastsWith ngm:knowledge-distillation ;
vc:contrastsWith ngm:round-trip-translation ;
vc:dependsOn ngm:attention-mechanism ;
vc:dependsOn ngm:encoder-decoder-architecture ;
vc:dependsOn ngm:neural-machine-translation ;
vc:dependsOn ngm:transformer-architecture ;
vc:enables ngm:domain-adaptation ;
vc:enables ngm:low-resource-language ;
vc:enables ngm:multilingual-model ;
vc:enables ngm:semi-supervised-learning ;
vc:enables ngm:translation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:iterative-training ;
vc:hasPart ngm:monolingual-data ;
vc:hasPart ngm:noise-injection ;
vc:hasPart ngm:parallel-corpus ;
vc:hasPart ngm:quality-estimation ;
vc:hasPart ngm:synthetic-data ;
vc:implements ngm:data-augmentation ;
vc:implements ngm:self-training ;
vc:implements ngm:semi-supervised-learning ;
vc:qualityScore "0.92"^^xsd:float ;
vc:relatedTo ngm:data-augmentation-strategies ;
vc:relatedTo ngm:multilingual-model ;
vc:relatedTo ngm:parallel-corpus ;
vc:relatedTo ngm:text-generation ;
vc:requires ngm:beam-search ;
vc:requires ngm:monolingual-data ;
vc:requires ngm:neural-machine-translation ;
vc:requires ngm:sequence-to-sequence-model ;
vc:slug "back-translation" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:wmt-benchmark ;
vc:supports ngm:curriculum-learning ;
vc:supports ngm:machine-translation ;
vc:supports ngm:quality-estimation ;
vc:supports ngm:transfer-learning ;
vc:uses ngm:beam-search ;
vc:uses ngm:bleu-score ;
vc:uses ngm:cross-entropy-loss ;
vc:uses ngm:language-model ;
vc:uses ngm:large-language-models .
ngm:backbone-network a skos:Concept ;
rdfs:label "Backbone Network"@en .
ngm:backdoor-attack a owl:Class ;
rdfs:comment "A training-time adversarial attack that embeds a hidden trigger pattern into an AI model via data poisoning, causing the model to behave normally on standard inputs but produce attacker-chosen outputs when the trigger is present, creating a covert vulnerability that survives fine-tuning and is exploitable post-deployment."@en ;
rdfs:label "Backdoor Attack"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf _:r2701 ;
skos:broader ngm:ai-technique ;
vc:contrastsWith ngm:adversarial-attack ;
vc:contrastsWith ngm:adversarial-robustness ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:model-robustness ;
vc:relatedTo ngm:privacy ;
vc:requires ngm:ai-safety ;
vc:slug "backdoor-attack" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:data-poisoning ;
vc:uses ngm:machine-learning-model .
ngm:backdrivability a owl:Class ;
rdfs:comment "Backdrivability is the property of a mechanical actuator or transmission that allows external forces applied at the output to drive the input in reverse, so motion and force pass freely in both directions. A highly backdrivable joint exhibits low reflected inertia and friction, enabling it to comply with and sense external contact. It is a key enabler of safe, compliant physical human-robot interaction and force-controlled robots."@en ;
rdfs:label "Backdrivability"@en ;
rdfs:subClassOf ngm:actuator ;
rdfs:subClassOf _:r2702 ;
vc:bridgesTo ngm:safety ;
vc:contrastsWith ngm:rigid-body ;
vc:enables ngm:admittance-control ;
vc:enables ngm:impedance-control ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:series-elastic-actuator ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:actuator ;
vc:relatedTo ngm:manipulator ;
vc:relatedTo ngm:robotics ;
vc:requires ngm:torque ;
vc:slug "backdrivability" ;
vc:sourceDomain "robotics" ;
vc:supports ngm:compliance ;
vc:supports ngm:force-control ;
vc:supports ngm:torque-control ;
vc:uses ngm:transparency .
ngm:backend-for-frontend a skos:Concept ;
rdfs:label "Backend For Frontend"@en .
ngm:background-removal a skos:Concept ;
rdfs:label "Background Removal"@en .
ngm:background-subtraction a skos:Concept ;
rdfs:label "Background Subtraction"@en .
ngm:background-tokens a skos:Concept ;
rdfs:label "Background Tokens"@en .
ngm:backlash a owl:Class ;
rdfs:comment "Backlash - The non-linear loss of motion in a mechanical transmission system caused by gaps, tolerances, or wear between gears, joints, or actuators, compromising Precision, Repeatability, and Accuracy in robotic manipulation."@en ;
rdfs:label "Backlash"@en ;
rdfs:subClassOf ngm:robo-actuation-and-control ;
rdfs:subClassOf ngm:robot-dynamics ;
rdfs:subClassOf ngm:robotics ;
skos:broader ngm:robo-actuation-and-control ;
skos:broader ngm:robotics ;
vc:enables ngm:backlash-measurement ;
vc:enables ngm:performance-degradation-detection ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:joint-mechanics ;
vc:isPartOf ngm:robot-dynamics ;
vc:qualityScore "0.48"^^xsd:float ;
vc:requires ngm:control-algorithm-tuning ;
vc:requires ngm:mechanical-compensation ;
vc:slug "backlash" ;
vc:sourceDomain "robotics" .
ngm:backlash-measurement a skos:Concept ;
rdfs:label "Backlash Measurement"@en .
ngm:backpressure a skos:Concept ;
rdfs:label "Backpressure"@en .
ngm:backpressure-management a skos:Concept ;
rdfs:label "Backpressure Management"@en .
ngm:backpropagation a owl:Class ;
rdfs:comment "Backpropagation is the algorithm for computing gradients of the loss function with respect to each weight in a neural network by applying the chain rule of calculus in reverse through the computation graph. It enables efficient gradient calculation across all layers in a single backward pass, making large-scale neural network training computationally feasible."@en ;
rdfs:label "Backpropagation"@en ;
rdfs:subClassOf ngm:optimisation-algorithm ;
rdfs:subClassOf _:r2703 ;
rdfs:subClassOf _:r2704 ;
rdfs:subClassOf _:r2705 ;
vc:bridgesTo ngm:federated-learning ;
vc:bridgesTo ngm:neuromorphic-computing ;
vc:contrastsWith ngm:forward-mode-differentiation ;
vc:contrastsWith ngm:genetic-algorithm ;
vc:dependsOn ngm:activation-function ;
vc:dependsOn ngm:loss-function ;
vc:enables ngm:deep-learning ;
vc:enables ngm:gradient-descent ;
vc:enables ngm:model-training ;
vc:enables ngm:weight-update ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:backward-pass ;
vc:hasPart ngm:chain-rule ;
vc:hasPart ngm:forward-pass ;
vc:isPartOf ngm:neural-network-training ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:activation-function ;
vc:relatedTo ngm:batch-normalisation ;
vc:relatedTo ngm:dropout ;
vc:relatedTo ngm:recurrent-neural-network ;
vc:relatedTo ngm:vanishing-gradient-problem ;
vc:requires ngm:computation-graph ;
vc:requires ngm:differentiable-function ;
vc:slug "backpropagation" ;
vc:sourceDomain "machine-learning" ;
vc:uses ngm:automatic-differentiation ;
vc:uses ngm:loss-function ;
vc:uses ngm:neural-network ;
vc:uses ngm:stochastic-gradient-descent .
ngm:backpropagation-through-time a owl:Class ;
rdfs:comment "Backpropagation through time (BPTT) is the extension of the backpropagation algorithm used to train recurrent neural networks, in which the recurrent network is unrolled across time steps into an equivalent feedforward network so that gradients of the loss can be computed and propagated backward through every step of the sequence. Because gradients must flow through many time steps, BPTT is prone to vanishing and exploding gradients on long sequences, which motivated architectures such as LSTM that mitigate the problem through gating. Truncated BPTT, which limits the number of steps backpropagated, is commonly used in practice to control computational cost on long sequences."@en ;
rdfs:label "Backpropagation Through Time"@en ;
rdfs:subClassOf ngm:backpropagation ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:backpropagation ;
vc:qualityScore "0.55"^^xsd:float ;
vc:relatedTo ngm:lstm ;
vc:relatedTo ngm:recurrent-neural-network ;
vc:slug "backpropagation-through-time" ;
vc:sourceDomain "machine-learning" .
ngm:backstepping a skos:Concept ;
rdfs:label "Backstepping"@en .
ngm:backtracking a skos:Concept ;
rdfs:label "Backtracking"@en .
ngm:backtracking-search a owl:Class ;
rdfs:comment "A depth-first search strategy for combinatorial problems that incrementally extends a partial assignment one variable at a time, checks it against the problem's constraints, and on any violation abandons the current branch by undoing the most recent choice and trying an alternative. Because it prunes every extension of an inconsistent partial assignment, it explores a small fraction of the full assignment space, and with constraint propagation and intelligent variable ordering it forms the core complete algorithm of constraint solvers and SAT solvers."@en ;
rdfs:label "Backtracking Search"@en ;
rdfs:subClassOf ngm:search-algorithm ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:constraint-solver ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:constraint-satisfaction ;
vc:relatedTo ngm:depth-first-search ;
vc:slug "backtracking-search" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:constraint-propagation .
ngm:backup a skos:Concept ;
rdfs:label "Backup"@en .
ngm:backup-and-recovery a owl:Class ;
rdfs:comment "Backup and Recovery is the set of processes, technologies, and policies that ensure data and system state can be copied to a secondary store and restored to a known-good condition following data loss, corruption, or infrastructure failure. It encompasses full, incremental, and differential backup strategies alongside recovery time objectives (RTO) and recovery point objectives (RPO) that define acceptable loss and restoration windows."@en ;
rdfs:label "Backup and Recovery"@en ;
rdfs:subClassOf ngm:disaster-recovery ;
rdfs:subClassOf _:r2706 ;
rdfs:subClassOf _:r2707 ;
vc:bridgesTo ngm:cybersecurity ;
vc:bridgesTo ngm:data-governance ;
vc:contrastsWith ngm:fault-tolerance ;
vc:contrastsWith ngm:replication ;
vc:dependsOn ngm:data-replication ;
vc:dependsOn ngm:storage-infrastructure ;
vc:enables ngm:high-availability ;
vc:enables ngm:operational-resilience ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:recovery-point-objective ;
vc:hasPart ngm:recovery-time-objective ;
vc:isPartOf ngm:business-continuity ;
vc:isPartOf ngm:disaster-recovery ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:air-gap ;
vc:relatedTo ngm:data-protection ;
vc:relatedTo ngm:fault-tolerance ;
vc:requires ngm:data-integrity ;
vc:requires ngm:data-storage ;
vc:slug "backup-and-recovery" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:regulatory-compliance ;
vc:uses ngm:cloud-storage ;
vc:uses ngm:data-replication ;
vc:uses ngm:immutable-storage ;
vc:uses ngm:snapshot .
ngm:backward-chaining a owl:Class ;
rdfs:comment "A goal-driven inference strategy that starts from a hypothesis to be proved and works backwards through the rule base, decomposing each goal into the subgoals given by the antecedents of rules whose consequents match it, recursing until every subgoal is grounded in known facts or fails. It is the query-answering counterpart to forward chaining, the evaluation strategy underlying Prolog's SLD resolution, and the diagnostic engine of classic expert systems such as MYCIN."@en ;
rdfs:label "Backward Chaining"@en ;
rdfs:subClassOf ngm:inference ;
vc:contrastsWith ngm:forward-chaining ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:rule-based-systems ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:expert-systems ;
vc:relatedTo ngm:inference-engine ;
vc:slug "backward-chaining" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:knowledge-representation .
ngm:backward-compatibility a owl:Class ;
rdfs:comment "Backward compatibility is the property of a system, interface, or data format that allows newer versions to continue working correctly with inputs, clients, or data produced for older versions. It ensures that existing consumers do not break when a producer is upgraded, preserving established contracts while permitting evolution. Maintaining backward compatibility typically requires additive, non-breaking changes and careful deprecation policies."@en ;
rdfs:label "Backward Compatibility"@en ;
rdfs:subClassOf ngm:software-engineering ;
rdfs:subClassOf _:r2708 ;
rdfs:subClassOf _:r2709 ;
rdfs:subClassOf _:r2710 ;
vc:contrastsWith ngm:api-versioning ;
vc:enables ngm:interoperability ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:api-design ;
vc:relatedTo ngm:software-development ;
vc:relatedTo ngm:software-engineering ;
vc:relatedTo ngm:standards ;
vc:requires ngm:api-versioning ;
vc:requires ngm:semantic-versioning ;
vc:requires ngm:version-control ;
vc:slug "backward-compatibility" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:interoperability ;
vc:supports ngm:reliability ;
vc:supports ngm:software-system .
ngm:backward-pass a skos:Concept ;
rdfs:label "Backward Pass"@en .
ngm:bag-of-words a skos:Concept ;
rdfs:label "Bag Of Words"@en .
ngm:bag-of-words-model a skos:Concept ;
rdfs:label "Bag Of Words Model"@en .
ngm:bagging a owl:Class ;
rdfs:comment "Bagging is a artificial intelligence concept and a type of Ensemble Mods. that enables Parallel Training."@en ;
rdfs:label "Bagging"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:ensemble-methods ;
skos:broader ngm:ai-technique ;
vc:enables ngm:training ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:slug "bagging" ;
vc:sourceDomain "artificial-intelligence" .
ngm:baked-lightmaps a skos:Concept ;
rdfs:label "Baked Lightmaps"@en .
ngm:bakong a skos:Concept ;
rdfs:label "Bakong"@en .
ngm:balance-control a skos:Concept ;
rdfs:label "Balance Control"@en .
ngm:balance-of-payments a owl:Class ;
rdfs:comment "The balance of payments is a systematic record of all economic transactions between a country's residents and the rest of the world over a given period, comprising the current account (trade in goods, services, and income) and the capital and financial accounts (investment and asset flows). It is a core macroeconomic accounting framework used to assess a country's external economic position and currency stability. Historically it was central to the gold standard's adjustment mechanism, where payment imbalances triggered gold flows that altered domestic money supply."@en ;
rdfs:label "Balance of Payments"@en ;
rdfs:subClassOf ngm:macroeconomics ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:slug "balance-of-payments" ;
vc:sourceDomain "finance" .
ngm:balance-of-payments-financing a skos:Concept ;
rdfs:label "Balance Of Payments Financing"@en .
ngm:balanced-dataset a skos:Concept ;
rdfs:label "Balanced Dataset"@en .
ngm:balancer a owl:Class ;
rdfs:comment "Balancer is a decentralised automated market maker (AMM) protocol on Ethereum and compatible EVM chains that generalises the constant-product AMM model to support weighted multi-asset pools, where pool weights can be set arbitrarily (e.g., 80/20 or 60/20/20 distributions) rather than the 50/50 split of Uniswap. It functions simultaneously as a self-rebalancing portfolio manager, a liquidity provider, and a price sensor."@en ;
rdfs:label "Balancer"@en ;
rdfs:subClassOf ngm:automated-market-maker ;
rdfs:subClassOf _:r2711 ;
rdfs:subClassOf _:r2712 ;
vc:bridgesTo ngm:distributed-systems ;
vc:bridgesTo ngm:finance ;
vc:contrastsWith ngm:constant-product-amm ;
vc:contrastsWith ngm:order-book-exchange ;
vc:enables ngm:asset-liquidity ;
vc:enables ngm:decentralized-exchange ;
vc:enables ngm:decentralized-finance-de-fi ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:concentrated-liquidity ;
vc:relatedTo ngm:curve-finance ;
vc:relatedTo ngm:governance-token ;
vc:relatedTo ngm:liquid-staking-token ;
vc:relatedTo ngm:lp-token ;
vc:relatedTo ngm:uniswap ;
vc:requires ngm:arbitrage ;
vc:requires ngm:liquidity-provider ;
vc:slug "balancer" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:evm ;
vc:uses ngm:liquidity-pool ;
vc:uses ngm:smart-contract ;
vc:uses ngm:stable-swap-invariant ;
vc:uses ngm:vote-escrow-model .
ngm:balancing-services a skos:Concept ;
rdfs:label "Balancing Services"@en .
ngm:ball-screw a skos:Concept ;
rdfs:label "Ball Screw"@en .
ngm:ball-screw-mechanism a skos:Concept ;
rdfs:label "Ball Screw Mechanism"@en .
ngm:ballistic-coefficient a owl:Class ;
rdfs:label "Ballistic Coefficient"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:orbital-dynamics ;
vc:slug "ballistic-coefficient" ;
vc:sourceDomain "space-science-and-systems" .
ngm:band-protocol a skos:Concept ;
rdfs:label "Band Protocol"@en .
ngm:bandit-algorithm a skos:Concept ;
rdfs:label "Bandit Algorithm"@en .
ngm:bandwidth a owl:Class ;
rdfs:comment "The maximum rate at which data can be transferred over a network path or communication channel, commonly measured in bits per second. In signal processing it also refers to the range of frequencies a channel can carry."@en ;
rdfs:label "Bandwidth"@en ;
rdfs:subClassOf ngm:network-protocol ;
vc:bridgesTo ngm:latency ;
vc:enables ngm:video-streaming ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:slug "bandwidth" ;
vc:sourceDomain "infrastructure" .
ngm:bandwidth-adaptation a owl:Class ;
rdfs:comment "Bandwidth adaptation is the real-time, algorithmic process by which a media transmission system continuously measures available network capacity and dynamically adjusts encoding parameters — bitrate, resolution, frame rate, codec profile, and layer selection — to maintain the highest achievable [..."@en ;
rdfs:label "Bandwidth Adaptation"@en ;
rdfs:subClassOf ngm:adaptive-bitrate-streaming ;
rdfs:subClassOf ngm:congestion-control ;
rdfs:subClassOf ngm:dc-protocol-and-infra ;
rdfs:subClassOf ngm:network-quality-of-service ;
rdfs:subClassOf ngm:quality-of-experience ;
rdfs:subClassOf ngm:real-time-transport-optimisation ;
rdfs:subClassOf _:r2713 ;
rdfs:subClassOf _:r2714 ;
skos:broader ngm:dc-protocol-and-infra ;
vc:bridgesTo ngm:congestion-control ;
vc:bridgesTo ngm:infra-network-and-comms ;
vc:contrastsWith ngm:buffering-only-adaptation ;
vc:contrastsWith ngm:circuit-switching ;
vc:contrastsWith ngm:constant-bitrate-encoding ;
vc:contrastsWith ngm:fixed-bitrate-streaming ;
vc:dependsOn ngm:5-g-network ;
vc:dependsOn ngm:cdn-infrastructure ;
vc:dependsOn ngm:codec-ecosystem ;
vc:dependsOn ngm:http3 ;
vc:dependsOn ngm:quic ;
vc:dependsOn ngm:rtp-protocol ;
vc:dependsOn ngm:web-rtc ;
vc:enables ngm:cloud-gaming ;
vc:enables ngm:emerging-market-accessibility ;
vc:enables ngm:global-participation-across-networks ;
vc:enables ngm:graceful-degradation ;
vc:enables ngm:mobile-collaboration ;
vc:enables ngm:spatial-computing ;
vc:enables ngm:video-streaming ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:abr-algorithm ;
vc:hasPart ngm:bandwidth-estimator ;
vc:hasPart ngm:bitrate-ladder ;
vc:hasPart ngm:buffer-manager ;
vc:hasPart ngm:codec-parameter-controller ;
vc:hasPart ngm:network-capacity-probing ;
vc:hasPart ngm:rate-distortion-optimisation ;
vc:hasPart ngm:rtcp-feedback ;
vc:hasPart ngm:segment-scheduler ;
vc:implements ngm:bola-algorithm ;
vc:implements ngm:congestion-control ;
vc:implements ngm:dash-adaptive-streaming ;
vc:implements ngm:hls-adaptive-bitrate ;
vc:implements ngm:mpc-algorithm ;
vc:implements ngm:pensieve-rl-policy ;
vc:implements ngm:scalable-video-coding ;
vc:implements ngm:web-rtc ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:cdn ;
vc:relatedTo ngm:edge-computing ;
vc:relatedTo ngm:forward-error-correction ;
vc:relatedTo ngm:latency-optimisation ;
vc:relatedTo ngm:network-slicing ;
vc:relatedTo ngm:packet-loss-recovery ;
vc:relatedTo ngm:web-rtc ;
vc:requires ngm:congestion-signal ;
vc:requires ngm:multi-bitrate-encoding ;
vc:requires ngm:network-measurement ;
vc:requires ngm:playback-buffer ;
vc:requires ngm:rtcp-feedback ;
vc:requires ngm:throughput-estimation ;
vc:slug "bandwidth-adaptation" ;
vc:sourceDomain "distributed-collaboration" ;
vc:standardizedBy ngm:3-gpp ;
vc:standardizedBy ngm:apple-inc-technology-corporation ;
vc:standardizedBy ngm:iso ;
vc:standardizedBy ngm:itu-t ;
vc:standardizedBy ngm:quic ;
vc:standardizedBy ngm:web-rtc-w-3-c-specification ;
vc:supports ngm:ar-vr-streaming ;
vc:supports ngm:cloud-gaming ;
vc:supports ngm:live-streaming ;
vc:supports ngm:remote-work-infrastructure ;
vc:supports ngm:screen-sharing ;
vc:supports ngm:telemedicine ;
vc:supports ngm:video-conferencing ;
vc:uses ngm:kalman-filter ;
vc:uses ngm:lyapunov-optimisation ;
vc:uses ngm:model-predictive-control ;
vc:uses ngm:psnr-metric ;
vc:uses ngm:reinforcement-learning ;
vc:uses ngm:ssim-metric ;
vc:uses ngm:transformer-architecture ;
vc:uses ngm:vmaf-metric .
ngm:bandwidth-allocation a skos:Concept ;
rdfs:label "Bandwidth Allocation"@en .
ngm:bandwidth-efficiency a skos:Concept ;
rdfs:label "Bandwidth Efficiency"@en .
ngm:bandwidth-efficient-communication a skos:Concept ;
rdfs:label "Bandwidth Efficient Communication"@en .
ngm:bandwidth-estimator a skos:Concept ;
rdfs:label "Bandwidth Estimator"@en .
ngm:bandwidth-optimization a owl:Class ;
rdfs:comment "Bandwidth Optimisation is the set of techniques and algorithms that maximise the effective throughput of network links by reducing unnecessary data transmission, prioritising critical traffic, and intelligently managing congestion. It encompasses data compression, deduplication, caching, traffic shaping, protocol selection, and adaptive bitrate strategies applied across local, wide-area, and wireless network infrastructures."@en ;
rdfs:label "Bandwidth Optimization"@en ;
rdfs:subClassOf ngm:quality-of-service ;
vc:enables ngm:latency-management-protocol ;
vc:enables ngm:low-latency ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:cdn ;
vc:relatedTo ngm:network-latency ;
vc:slug "bandwidth-optimization" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:cdn ;
vc:uses ngm:data-compression .
ngm:bandwidthcapacity a skos:Concept ;
rdfs:label "Bandwidthcapacity"@en .
ngm:bandwidthdesign a skos:Concept ;
rdfs:label "Bandwidthdesign"@en .
ngm:bang-bang-control a skos:Concept ;
rdfs:label "Bang Bang Control"@en .
ngm:bangladesh-accord a skos:Concept ;
rdfs:label "Bangladesh Accord"@en .
ngm:bank-account-access a skos:Concept ;
rdfs:label "Bank Account Access"@en .
ngm:bank-deposit a skos:Concept ;
rdfs:label "Bank Deposit"@en .
ngm:bank-for-international-settlements a owl:Class ;
rdfs:comment "The Bank for International Settlements (BIS) is an international financial institution, established in 1930 and headquartered in Basel, that serves as a bank for central banks and fosters international monetary and financial cooperation. It provides banking services to its central bank members, hosts standard-setting bodies such as the Basel Committee on Banking Supervision, and conducts economic research on global financial stability. Through its Innovation Hub it also coordinates experimentation with central bank digital currencies and the modernisation of cross-border payments."@en ;
rdfs:label "Bank for International Settlements"@en ;
rdfs:subClassOf ngm:central-bank ;
rdfs:subClassOf _:r2721 ;
rdfs:subClassOf _:r2722 ;
rdfs:subClassOf _:r2723 ;
vc:bridgesTo ngm:central-bank-digital-currency-cbdc ;
vc:enables ngm:central-bank-cooperation ;
vc:enables ngm:cross-border-payments ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:basel-committee-on-banking-supervision ;
vc:hasPart ngm:bis-innovation-hub ;
vc:implements ngm:banking-regulation ;
vc:isPartOf ngm:international-financial-system ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:financial-stability-board ;
vc:relatedTo ngm:imf ;
vc:relatedTo ngm:swift ;
vc:requires ngm:international-cooperation ;
vc:slug "bank-for-international-settlements" ;
vc:sourceDomain "finance" ;
vc:standardizedBy ngm:basel-accords ;
vc:supports ngm:financial-stability ;
vc:supports ngm:monetary-policy-coordination ;
vc:uses ngm:economic-research .
ngm:bank-of-england a owl:Class ;
rdfs:comment "The Bank of England (BoE) is the United Kingdom's central bank, founded in 1694 by Royal Charter to finance the Crown, and nationalised in 1946. It is responsible for monetary policy via the Monetary Policy Committee (MPC), which sets Bank Rate to maintain a 2% CPI inflation target; macroprudential financial stability policy via the Financial Policy Committee (FPC); and microprudential supervision of deposit-taking institutions, insurers, and systemically important financial market infrastructures via the Prudential Regulation Authority (PRA). The Bank also operates the UK's Real-Time Gross Settlement (RTGS) payment infrastructure and issues sterling banknotes, acting as the operational backbone of the UK financial system."@en ;
rdfs:label "Bank of England"@en ;
rdfs:subClassOf ngm:central-bank ;
rdfs:subClassOf _:r2724 ;
rdfs:subClassOf _:r2725 ;
rdfs:subClassOf _:r2726 ;
vc:bridgesTo ngm:ai-governance ;
vc:bridgesTo ngm:distributed-ledger-technology ;
vc:contrastsWith ngm:european-central-bank ;
vc:contrastsWith ngm:federal-reserve ;
vc:enables ngm:financial-stability ;
vc:enables ngm:payment-system ;
vc:enables ngm:quantitative-easing ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:financial-policy-committee ;
vc:hasPart ngm:monetary-policy-committee ;
vc:hasPart ngm:prudential-regulation-authority ;
vc:isPartOf ngm:uk-financial-regulatory-framework ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:central-bank-digital-currency-cbdc ;
vc:relatedTo ngm:financial-regulation ;
vc:relatedTo ngm:inflation-targeting ;
vc:relatedTo ngm:lender-of-last-resort ;
vc:relatedTo ngm:systemic-risk ;
vc:requires ngm:monetary-policy ;
vc:requires ngm:prudential-regulation ;
vc:slug "bank-of-england" ;
vc:sourceDomain "finance" ;
vc:standardizedBy ngm:basel-iii ;
vc:standardizedBy ngm:financial-stability-board ;
vc:supports ngm:compliance-framework ;
vc:supports ngm:financial-market-infrastructure ;
vc:supports ngm:risk-management-framework ;
vc:uses ngm:interest-rate-policy ;
vc:uses ngm:real-time-gross-settlement .
ngm:bank-run a skos:Concept ;
rdfs:label "Bank Run"@en .
ngm:bank-secrecy-act a owl:Class ;
rdfs:comment "The Bank Secrecy Act (BSA), enacted in the United States in 1970, is the primary federal anti-money-laundering statute that requires financial institutions to assist US government agencies in detecting and preventing money laundering and financial crime. It mandates customer identification, suspicious activity reporting (SARs), currency transaction reporting (CTRs), and record-keeping — establishing the foundational framework for AML compliance in the US financial system."@en ;
rdfs:label "Bank Secrecy Act"@en ;
rdfs:subClassOf ngm:financial-regulation ;
rdfs:subClassOf _:r2715 ;
rdfs:subClassOf _:r2716 ;
rdfs:subClassOf _:r2717 ;
rdfs:subClassOf _:r2718 ;
rdfs:subClassOf _:r2719 ;
rdfs:subClassOf _:r2720 ;
vc:bridgesTo ngm:bc-0456-virtual-asset-service-providers ;
vc:bridgesTo ngm:corporate-transparency-act ;
vc:bridgesTo ngm:travel-rule ;
vc:contrastsWith ngm:gdpr ;
vc:enables ngm:financial-crime-detection ;
vc:enables ngm:sanctions-screening ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:currency-transaction-report ;
vc:hasPart ngm:kyc ;
vc:implements ngm:aml-kyc-compliance ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:aml-kyc-compliance ;
vc:relatedTo ngm:counter-terrorist-financing ;
vc:relatedTo ngm:regulatory-compliance ;
vc:relatedTo ngm:usa-patriot-act ;
vc:requires ngm:aml ;
vc:requires ngm:beneficial-ownership ;
vc:requires ngm:customer-due-diligence ;
vc:requires ngm:suspicious-activity-report ;
vc:requires ngm:transaction-monitoring ;
vc:slug "bank-secrecy-act" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:fatf .
ngm:banking a owl:Class ;
rdfs:comment "Banking is the system of financial intermediation through which licensed institutions accept deposits, extend credit, and provide payment and related services to individuals, businesses, and governments. Banks transform short-term deposits into longer-term loans, manage liquidity and risk, and operate the payment rails that move money through the economy. As a regulated, systemically important sector, banking sits at the centre of monetary policy transmission and financial stability."@en ;
rdfs:label "Banking"@en ;
rdfs:subClassOf ngm:financial-services ;
rdfs:subClassOf _:r2733 ;
rdfs:subClassOf _:r2734 ;
rdfs:subClassOf _:r2735 ;
rdfs:subClassOf _:r2736 ;
rdfs:subClassOf _:r2737 ;
vc:dependsOn ngm:central-bank ;
vc:enables ngm:fintech ;
vc:enables ngm:open-banking ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:clearing ;
vc:hasPart ngm:payment-system ;
vc:hasPart ngm:settlement ;
vc:isPartOf ngm:financial-services ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:finance ;
vc:requires ngm:regulation ;
vc:requires ngm:risk-management ;
vc:slug "banking" ;
vc:sourceDomain "finance" ;
vc:supports ngm:liquidity ;
vc:supports ngm:monetary-policy ;
vc:uses ngm:interest-rate .
ngm:banking-infrastructure a skos:Concept ;
rdfs:label "Banking Infrastructure"@en .
ngm:banking-law a skos:Concept ;
rdfs:label "Banking Law"@en .
ngm:banking-rail a skos:Concept ;
rdfs:label "Banking Rail"@en .
ngm:banking-regulation a owl:Class ;
rdfs:comment "Banking Regulation encompasses the body of laws, rules, and supervisory frameworks that govern the formation, operation, and dissolution of banks and other deposit-taking institutions. Its primary purposes are to ensure systemic financial stability, protect depositors, prevent money laundering, and enforce prudential capital and liquidity requirements. Key regulatory regimes include Basel III, the EU's CRD/CRR framework, and the US Dodd-Frank Act."@en ;
rdfs:label "Banking Regulation"@en ;
rdfs:subClassOf ngm:infra-legal-and-regulatory ;
skos:broader ngm:infra-legal-and-regulatory ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.7"^^xsd:float ;
vc:relatedTo ngm:digital-signature-verification ;
vc:slug "banking-regulation" ;
vc:sourceDomain "infrastructure" .
ngm:banking-system a owl:Class ;
rdfs:comment "An organised network of financial institutions, regulatory bodies, payment infrastructure, and legal frameworks that collectively facilitate the creation, custody, transfer, and lending of money within an economy. A banking system includes central banks, commercial banks, investment banks, and clearing houses, all operating under a body of prudential regulation. It underpins economic activity by providing mechanisms for capital allocation, risk distribution, and monetary policy transmission. Modern banking systems increasingly integrate digital and real-time payment rails."@en ;
rdfs:label "Banking System"@en ;
rdfs:subClassOf ngm:finance ;
rdfs:subClassOf _:r2727 ;
rdfs:subClassOf _:r2728 ;
rdfs:subClassOf _:r2729 ;
rdfs:subClassOf _:r2730 ;
rdfs:subClassOf _:r2731 ;
rdfs:subClassOf _:r2732 ;
vc:contrastsWith ngm:de-fi ;
vc:dependsOn ngm:infrastructure ;
vc:enables ngm:capital-allocation ;
vc:enables ngm:credit-creation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:central-bank ;
vc:hasPart ngm:clearing-house ;
vc:hasPart ngm:commercial-bank ;
vc:hasPart ngm:payment-system ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:digital-currency ;
vc:relatedTo ngm:fintech ;
vc:relatedTo ngm:open-banking ;
vc:requires ngm:financial-regulation ;
vc:requires ngm:monetary-policy ;
vc:slug "banking-system" ;
vc:sourceDomain "finance" ;
vc:standardizedBy ngm:basel-framework ;
vc:supports ngm:economic-stability ;
vc:supports ngm:financial-inclusion .
ngm:banknote a skos:Concept ;
rdfs:label "Banknote"@en .
ngm:bara a skos:Concept ;
rdfs:label "Bara"@en .
ngm:barcode a owl:Class ;
rdfs:comment "A barcode is a machine-readable optical representation of data that encodes information in the widths and spacings of parallel lines (one-dimensional) or in patterns of dots, squares and other geometric shapes (two-dimensional). Barcodes are scanned by optical readers or cameras to retrieve an identifier that links a physical item to a record in an information system. They underpin automatic identification and data capture in retail, logistics and inventory control."@en ;
rdfs:label "Barcode"@en ;
rdfs:subClassOf ngm:standards ;
vc:bridgesTo ngm:supply-chain-traceability ;
vc:contrastsWith ngm:nfc ;
vc:contrastsWith ngm:rfid ;
vc:enables ngm:inventory-management ;
vc:enables ngm:supply-chain-traceability ;
vc:enables ngm:traceability ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:gs-1-standards ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:gs1-epcis ;
vc:relatedTo ngm:qr-code ;
vc:requires ngm:product-identification ;
vc:slug "barcode" ;
vc:sourceDomain "standards" ;
vc:standardizedBy ngm:gs-1-standards ;
vc:supports ngm:inventory-management ;
vc:uses ngm:qr-code ;
vc:uses ngm:rfid .
ngm:barcode-scanning a skos:Concept ;
rdfs:label "Barcode Scanning"@en .
ngm:barda-medical-countermeasures a skos:Concept ;
rdfs:label "Barda Medical Countermeasures"@en .
ngm:bare-metal a skos:Concept ;
rdfs:label "Bare Metal"@en .
ngm:bare-metal-execution a skos:Concept ;
rdfs:label "Bare Metal Execution"@en .
ngm:bare-metal-programming a skos:Concept ;
rdfs:label "Bare Metal Programming"@en .
ngm:barker-acceptance-function a skos:Concept ;
rdfs:label "Barker Acceptance Function"@en .
ngm:bart a owl:Class ;
rdfs:comment "Bidirectional and Auto-Regressive Transformers: a denoising sequence-to-sequence pre-training architecture developed by Meta AI that combines a bidirectional encoder (as in BERT) with an autoregressive decoder (as in GPT), achieving state-of-the-art results on abstractive summarisation, dialogue, and machine translation through flexible noise-based corruption objectives."@en ;
rdfs:label "BART"@en ;
rdfs:subClassOf ngm:ai-model-architecture ;
skos:broader ngm:ai-model-architecture ;
vc:contrastsWith ngm:albert ;
vc:contrastsWith ngm:ro-berta ;
vc:enables ngm:fine-tuning ;
vc:enables ngm:natural-language-processing ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:large-language-models ;
vc:slug "bart" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:attention-mask ;
vc:uses ngm:transformer-architecture .
ngm:barter-system a owl:Class ;
rdfs:comment "A decentralized exchange mechanism enabling peer-to-peer trading of goods, services, or digital assets without monetary intermediaries, enhanced in digital contexts through blockchain-based matching algorithms and smart contracts that solve the traditional \"double coincidence of wants\" problem."@en ;
rdfs:label "Barter System"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:exchange-mechanism ;
rdfs:subClassOf _:r2738 ;
rdfs:subClassOf _:r2739 ;
rdfs:subClassOf _:r2740 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:exchange-mechanism ;
vc:enables ngm:asset-exchange ;
vc:enables ngm:peer-to-peer-trading ;
vc:enables ngm:virtual-economy ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:matching-algorithm ;
vc:requires ngm:smart-contracts ;
vc:requires ngm:trust-mechanism ;
vc:slug "barter-system" ;
vc:sourceDomain "artificial-intelligence" .
ngm:barycentric-dynamical-time a owl:Class ;
rdfs:label "Barycentric Dynamical Time"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:space-reference-systems ;
vc:slug "barycentric-dynamical-time" ;
vc:sourceDomain "space-science-and-systems" .
ngm:base a owl:Class ;
rdfs:comment "An Ethereum Layer 2 network built by Coinbase using the Optimism OP Stack, providing low-cost, EVM-compatible transactions settled on and secured by the Ethereum mainnet."@en ;
rdfs:label "Base"@en ;
rdfs:subClassOf ngm:layer-2-scaling ;
rdfs:subClassOf _:r2745 ;
rdfs:subClassOf _:r2746 ;
rdfs:subClassOf _:r2747 ;
rdfs:subClassOf _:r2748 ;
rdfs:subClassOf _:r2749 ;
rdfs:subClassOf _:r2750 ;
rdfs:subClassOf _:r2751 ;
vc:bridgesTo ngm:coinbase ;
vc:bridgesTo ngm:decentralised-finance-infrastructure ;
vc:bridgesTo ngm:web3-payments ;
vc:contrastsWith ngm:arbitrum ;
vc:contrastsWith ngm:polygon ;
vc:contrastsWith ngm:zk-rollup ;
vc:dependsOn ngm:coinbase ;
vc:dependsOn ngm:ethereum-proof-of-stake ;
vc:enables ngm:de-fi ;
vc:enables ngm:erc-20-tokens ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ethereum-smart-contract-platform-virtual-machine ;
vc:hasPart ngm:fraud-proof ;
vc:hasPart ngm:sequencer ;
vc:isPartOf ngm:optimism-collective ;
vc:isPartOf ngm:superchain ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:ethereum-bridge ;
vc:requires ngm:ethereum-smart-contract-platform ;
vc:requires ngm:op-stack ;
vc:requires ngm:optimism ;
vc:requires ngm:optimistic-rollup ;
vc:slug "base" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:decentralised-exchange ;
vc:supports ngm:non-fungible-token ;
vc:supports ngm:smart-contract ;
vc:uses ngm:calldata-compression ;
vc:uses ngm:eip-4844 .
ngm:base-carbon-tonne-standard a skos:Concept ;
rdfs:label "Base Carbon Tonne Standard"@en .
ngm:base-erosion-and-profit-shifting a skos:Concept ;
rdfs:label "Base Erosion And Profit Shifting"@en .
ngm:base-fee a owl:Class ;
rdfs:comment "The Base Fee is the algorithmically determined minimum fee per unit of gas that every transaction must pay to be included in an Ethereum block, introduced by EIP-1559. It adjusts automatically each block based on whether the previous block was above or below its gas target, increasing when demand is high and decreasing when low. Unlike miner tips, the base fee is burned rather than paid to validators, creating a deflationary pressure on ETH supply and making gas price prediction more reliable for users."@en ;
rdfs:label "Base Fee"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf ngm:blockchain-entity ;
rdfs:subClassOf ngm:economic-mechanism ;
rdfs:subClassOf _:r2741 ;
rdfs:subClassOf _:r2742 ;
rdfs:subClassOf _:r2743 ;
rdfs:subClassOf _:r2744 ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:contrastsWith ngm:miner ;
vc:contrastsWith ngm:priority-fee ;
vc:enables ngm:burning-mechanism ;
vc:enables ngm:gas-fee-market ;
vc:enables ngm:mev ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:blockchain-economics ;
vc:isPartOf ngm:gas-fee-market ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:block-reward ;
vc:relatedTo ngm:blockchain-economics ;
vc:relatedTo ngm:gas-limit ;
vc:relatedTo ngm:gas-price ;
vc:relatedTo ngm:priority-fee ;
vc:requires ngm:blockchain-transaction ;
vc:requires ngm:eip-1559 ;
vc:requires ngm:gas ;
vc:requires ngm:mempool ;
vc:slug "base-fee" ;
vc:sourceDomain "blockchain" .
ngm:base-layer a skos:Concept ;
rdfs:label "Base Layer"@en .
ngm:base-learner a owl:Class ;
rdfs:comment "A base learner is an individual model trained as one member of an ensemble, whose predictions are combined with those of other base learners to produce a final output. Base learners are typically simple or weak relative to the ensemble as a whole - for example shallow decision trees in a random forest or boosting sequence - so that their errors are diverse and can partially cancel when aggregated. The choice of base learner architecture and training procedure directly affects the diversity and accuracy of the resulting ensemble."@en ;
rdfs:label "Base Learner"@en ;
rdfs:subClassOf ngm:machine-learning-model ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.0"^^xsd:float ;
vc:slug "base-learner" ;
vc:sourceDomain "machine-learning" .
ngm:base-model a skos:Concept ;
rdfs:label "Base Model"@en .
ngm:base-properties a skos:Concept ;
rdfs:label "Base Properties"@en .
ngm:base-support a skos:Concept ;
rdfs:label "Base Support"@en .
ngm:base58-encoding a skos:Concept ;
rdfs:label "Base58 Encoding"@en .
ngm:base64-encoding a skos:Concept ;
rdfs:label "Base64 Encoding"@en .
ngm:base64url-encoding a owl:Class ;
rdfs:comment "Base64URL encoding is a variant of Base64 that replaces the characters plus and slash with hyphen and underscore and typically omits padding, so that encoded data can be safely embedded in URLs and filenames without escaping. It is the encoding used for the header, payload and signature segments of a JSON Web Token, and for the compact serialisation used by SD-JWT. Its safety for use in URL query parameters and path segments is the reason it was chosen over standard Base64 for these token formats."@en ;
rdfs:label "Base64URL Encoding"@en ;
rdfs:subClassOf ngm:data-format ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "base64url-encoding" ;
vc:sourceDomain "security" .
ngm:based-on a owl:Class ;
rdfs:comment "\"Based on\" is a provenance and derivation relation used in robotics standards and quality management frameworks to indicate that a system, design, or specification is derived from or conforms to an authoritative reference standard such as ISO 9001 or functional-safety norms. Within the robotics domain it records the normative lineage of robot software architectures, safety certifications, and performance benchmarks relative to their governing standards."@en ;
rdfs:label "based on"@en ;
rdfs:subClassOf ngm:robo-safety-and-standards ;
rdfs:subClassOf _:r22721 ;
rdfs:subClassOf _:r22722 ;
skos:broader ngm:robo-safety-and-standards ;
vc:bridgesTo ngm:robotics-platform ;
vc:bridgesTo ngm:safety-standard ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:functional-safety ;
vc:relatedTo ngm:iso-standards ;
vc:relatedTo ngm:quality-standard ;
vc:relatedTo ngm:robotics ;
vc:requires ngm:standardization-bodies ;
vc:requires ngm:standards-documentation ;
vc:slug "based-on" ;
vc:sourceDomain "robotics" ;
vc:supports ngm:robot-safety ;
vc:supports ngm:robotics-systems ;
vc:uses ngm:compliance-standards ;
vc:uses ngm:standards-conformance .
ngm:basel-accords a owl:Class ;
rdfs:comment "The Basel Accords are a series of international banking-supervision agreements developed by the Basel Committee on Banking Supervision under the Bank for International Settlements, establishing minimum standards for bank capital, leverage, and liquidity. Successive accords progressively strengthened requirements for risk-weighted capital, introduced leverage and liquidity ratios, and refined the treatment of credit, market, and operational risk. They are non-binding recommendations that member jurisdictions transpose into national law to enhance the resilience and stability of the global financial system."@en ;
rdfs:label "Basel Accords"@en ;
rdfs:subClassOf ngm:financial-regulation ;
rdfs:subClassOf _:r2752 ;
rdfs:subClassOf _:r2753 ;
rdfs:subClassOf _:r2754 ;
vc:dependsOn ngm:risk-management ;
vc:enables ngm:systemic-risk ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:basel-iii ;
vc:hasPart ngm:capital-adequacy ;
vc:implements ngm:capital-adequacy ;
vc:isPartOf ngm:financial-regulation ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:basel-iii ;
vc:relatedTo ngm:capital-adequacy ;
vc:relatedTo ngm:financial-regulation ;
vc:relatedTo ngm:risk-management ;
vc:requires ngm:stress-testing ;
vc:slug "basel-accords" ;
vc:sourceDomain "finance" ;
vc:standardizedBy ngm:bank-for-international-settlements ;
vc:supports ngm:liquidity .
ngm:basel-committee a owl:Class ;
rdfs:comment "The Basel Committee on Banking Supervision (BCBS) is an international standard-setting body hosted by the Bank for International Settlements (BIS) in Basel, Switzerland, that develops global regulatory standards for the prudential supervision of banks. Its accords — Basel I (1988), Basel II (2004), and Basel III (2010, finalised 2017) — set internationally agreed minimum capital adequacy, liquidity, and leverage requirements for commercial banks."@en ;
rdfs:label "Basel Committee"@en ;
rdfs:subClassOf ngm:financial-regulation ;
rdfs:subClassOf _:r2759 ;
rdfs:subClassOf _:r2760 ;
rdfs:subClassOf _:r2761 ;
rdfs:subClassOf _:r2762 ;
rdfs:subClassOf _:r2763 ;
rdfs:subClassOf _:r2764 ;
vc:bridgesTo ngm:ai-model-risk ;
vc:bridgesTo ngm:cryptoasset-regulation ;
vc:bridgesTo ngm:operational-resilience ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:basel-i ;
vc:hasPart ngm:basel-ii ;
vc:hasPart ngm:basel-iii ;
vc:hasPart ngm:capital-adequacy ;
vc:implements ngm:capital-adequacy ;
vc:isPartOf ngm:international-financial-architecture ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:central-bank ;
vc:relatedTo ngm:compliance-framework ;
vc:relatedTo ngm:financial-stability-board ;
vc:relatedTo ngm:imf ;
vc:relatedTo ngm:risk-management-framework ;
vc:relatedTo ngm:systemic-risk ;
vc:requires ngm:capital-adequacy ;
vc:requires ngm:liquidity-coverage-ratio ;
vc:requires ngm:risk-weighted-assets ;
vc:slug "basel-committee" ;
vc:sourceDomain "finance" ;
vc:standardizedBy ngm:bis ;
vc:supports ngm:financial-stability ;
vc:supports ngm:systemic-risk .
ngm:basel-committee-on-banking-supervision a owl:Class ;
rdfs:comment "The Basel Committee on Banking Supervision (BCBS) is the primary global standard-setter for the prudential regulation of banks, operating under the auspices of the Bank for International Settlements in Basel, Switzerland. It develops minimum capital, liquidity, and leverage requirements — collectively the Basel Accords (Basel I, II, III, and the finalised Basel III framework completed in 2017) — that are adopted into national law by its 45-member jurisdictions. The Committee does not possess formal supranational authority; compliance is achieved through voluntary adoption by member central banks and supervisory agencies."@en ;
rdfs:label "Basel Committee on Banking Supervision"@en ;
rdfs:subClassOf ngm:regulatory-authority ;
rdfs:subClassOf _:r2755 ;
rdfs:subClassOf _:r2756 ;
rdfs:subClassOf _:r2757 ;
rdfs:subClassOf _:r2758 ;
vc:bridgesTo ngm:cryptoasset-regulation ;
vc:dependsOn ngm:central-bank ;
vc:dependsOn ngm:national-competent-authority ;
vc:enables ngm:financial-stability ;
vc:enables ngm:prudential-supervision ;
vc:enables ngm:regulatory-compliance ;
vc:enables ngm:regulatory-framework ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:basel-accords ;
vc:hasPart ngm:capital-adequacy ;
vc:hasPart ngm:liquidity-coverage-ratio ;
vc:implements ngm:prudential-regulation ;
vc:implements ngm:stress-testing ;
vc:isPartOf ngm:bank-for-international-settlements ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:capital-requirements-regulation ;
vc:relatedTo ngm:financial-stability-board ;
vc:relatedTo ngm:regulatory-standards ;
vc:relatedTo ngm:regulatory-technology ;
vc:requires ngm:common-equity-tier-1 ;
vc:requires ngm:risk-weighted-assets ;
vc:slug "basel-committee-on-banking-supervision" ;
vc:sourceDomain "finance" ;
vc:supports ngm:financial-regulation ;
vc:supports ngm:risk-management ;
vc:supports ngm:systemic-risk .
ngm:basel-framework a skos:Concept ;
rdfs:label "Basel Framework"@en .
ngm:basel-i a skos:Concept ;
rdfs:label "Basel I"@en .
ngm:basel-ii a owl:Class ;
rdfs:comment "Basel II is the second of the Basel Accords, issued by the Basel Committee on Banking Supervision in 2004 to refine the international framework for bank capital adequacy. It organised prudential regulation around three pillars: minimum capital requirements made more risk-sensitive through standardised and internal-ratings-based approaches to credit risk plus explicit treatment of operational risk; supervisory review of institutions' own capital adequacy assessments; and market discipline through enhanced disclosure. Distinct from both its predecessor Basel I and its successor Basel III, Basel II is a specific accord version; the 2007-2009 financial crisis exposed its underweighting of liquidity and leverage, prompting the tighter Basel III reforms that superseded and contrast with it."@en ;
rdfs:label "Basel II"@en ;
rdfs:subClassOf ngm:basel-accords ;
vc:contrastsWith ngm:basel-iii ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:basel-committee ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:banking-regulation ;
vc:relatedTo ngm:prudential-regulation ;
vc:relatedTo ngm:risk-management ;
vc:slug "basel-ii" ;
vc:sourceDomain "finance" .
ngm:basel-iii a owl:Class ;
rdfs:comment "Basel III is an international set of banking regulatory standards on capital adequacy, stress-tested liquidity buffers, and leverage limits, developed by the Basel Committee on Banking Supervision in response to the 2007-2009 global financial crisis."@en ;
rdfs:label "Basel III"@en ;
rdfs:subClassOf ngm:financial-regulation ;
rdfs:subClassOf _:r2765 ;
rdfs:subClassOf _:r2766 ;
rdfs:subClassOf _:r2767 ;
rdfs:subClassOf _:r2768 ;
vc:bridgesTo ngm:central-bank-digital-currency-cbdc ;
vc:bridgesTo ngm:de-fi ;
vc:bridgesTo ngm:risk-management ;
vc:contrastsWith ngm:basel-i ;
vc:contrastsWith ngm:basel-ii ;
vc:dependsOn ngm:credit-risk ;
vc:dependsOn ngm:market-risk ;
vc:dependsOn ngm:operational-risk ;
vc:dependsOn ngm:risk-management ;
vc:enables ngm:financial-stability ;
vc:enables ngm:systemic-risk ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:capital-adequacy ;
vc:hasPart ngm:capital-conservation-buffer ;
vc:hasPart ngm:liquidity-coverage-ratio ;
vc:implements ngm:macroprudential-policy ;
vc:isPartOf ngm:basel-accords ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:countercyclical-capital-buffer ;
vc:requires ngm:regulatory-frameworks ;
vc:requires ngm:stress-testing ;
vc:slug "basel-iii" ;
vc:sourceDomain "finance" ;
vc:standardizedBy ngm:bank-for-international-settlements ;
vc:standardizedBy ngm:basel-committee-on-banking-supervision .
ngm:basel-iv a skos:Concept ;
rdfs:label "Basel Iv"@en .
ngm:baseline a skos:Concept ;
rdfs:label "Baseline"@en .
ngm:baseline-metrics a skos:Concept ;
rdfs:label "Baseline Metrics"@en .
ngm:bash a skos:Concept ;
rdfs:label "Bash"@en .
ngm:basic-reproduction-number a skos:Concept ;
rdfs:label "Basic Reproduction Number"@en .
ngm:basin-of-attraction a skos:Concept ;
rdfs:label "Basin Of Attraction"@en .
ngm:basis-vector a skos:Concept ;
rdfs:label "Basis Vector"@en .
ngm:bast-automation-levels a skos:Concept ;
rdfs:label "Bast Automation Levels"@en .
ngm:batch-auction-matching a skos:Concept ;
rdfs:label "Batch Auction Matching"@en .
ngm:batch-data-migration a skos:Concept ;
rdfs:label "Batch Data Migration"@en .
ngm:batch-gradient-descent a skos:Concept ;
rdfs:label "Batch Gradient Descent"@en .
ngm:batch-image-processing a owl:Class ;
rdfs:comment "Batch image processing is the automated application of a fixed sequence of image operations, such as resizing, format conversion, colour correction, or generative transformation, across a large set of images without per-image manual intervention. It is exposed by image-generation platforms and pipeline tools as queued or scripted workflows that process many inputs sequentially or in parallel under a shared configuration. Batch processing trades per-image customisation for throughput, making it suited to dataset preparation and bulk content production."@en ;
rdfs:label "Batch Image Processing"@en ;
rdfs:subClassOf ngm:image-processing ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:image-processing ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "batch-image-processing" ;
vc:sourceDomain "artificial-intelligence" .
ngm:batch-inference a owl:Class ;
rdfs:comment "The process of applying a trained machine learning model to a collection of inputs simultaneously rather than processing each input individually in real time. Batch inference amortises per-request overhead by grouping inputs into tensors that saturate GPU or accelerator memory bandwidth, significantly reducing per-sample latency at scale. It is the dominant serving pattern for offline analytics, embedding generation, and large-scale data enrichment pipelines where latency deadlines are relaxed. Contrast with online inference, which prioritises low single-request latency over throughput."@en ;
rdfs:label "Batch Inference"@en ;
rdfs:subClassOf ngm:ai-infrastructure ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf ngm:model-serving ;
rdfs:subClassOf _:r2769 ;
rdfs:subClassOf _:r2770 ;
rdfs:subClassOf _:r2771 ;
rdfs:subClassOf _:r2772 ;
rdfs:subClassOf _:r2773 ;
rdfs:subClassOf _:r2774 ;
rdfs:subClassOf _:r2775 ;
vc:contrastsWith ngm:distributed-inference ;
vc:contrastsWith ngm:edge-inference ;
vc:contrastsWith ngm:online-inference ;
vc:contrastsWith ngm:streaming-inference ;
vc:dependsOn ngm:gpu-computing ;
vc:dependsOn ngm:large-language-models ;
vc:dependsOn ngm:machine-learning-discipline-infrastructure ;
vc:enables ngm:cost-optimisation ;
vc:enables ngm:data-pipeline ;
vc:enables ngm:embedding-generation ;
vc:enables ngm:model-serving ;
vc:enables ngm:scalability ;
vc:enables ngm:throughput-optimisation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:continuous-batching ;
vc:hasPart ngm:flash-attention ;
vc:hasPart ngm:inference-pipeline ;
vc:hasPart ngm:kv-cache ;
vc:hasPart ngm:speculative-decoding ;
vc:hasPart ngm:throughput-optimisation ;
vc:implements ngm:inference-pipeline ;
vc:implements ngm:model-deployment ;
vc:isPartOf ngm:mlops ;
vc:qualityScore "0.93"^^xsd:float ;
vc:relatedTo ngm:distributed-training ;
vc:relatedTo ngm:latency ;
vc:relatedTo ngm:model-quantization ;
vc:relatedTo ngm:neural-network-quantisation ;
vc:relatedTo ngm:tensor-parallelism ;
vc:relatedTo ngm:throughput-optimisation ;
vc:requires ngm:gpu-computing ;
vc:requires ngm:machine-learning-discipline-infrastructure ;
vc:requires ngm:tensor-processing ;
vc:slug "batch-inference" ;
vc:sourceDomain "machine-learning" ;
vc:supports ngm:distributed-training ;
vc:supports ngm:mlops ;
vc:supports ngm:scalability ;
vc:uses ngm:deep-learning-framework ;
vc:uses ngm:flash-attention ;
vc:uses ngm:gpu-architecture ;
vc:uses ngm:kv-cache ;
vc:uses ngm:neural-network ;
vc:uses ngm:transformer-architecture .
ngm:batch-learning a skos:Concept ;
rdfs:label "Batch Learning"@en .
ngm:batch-machine-translation a skos:Concept ;
rdfs:label "Batch Machine Translation"@en .
ngm:batch-minting a skos:Concept ;
rdfs:label "Batch Minting"@en .
ngm:batch-normalisation a owl:Class ;
rdfs:comment "A technique that normalises layer inputs within a mini-batch to zero mean and unit variance, stabilising training dynamics, enabling higher learning rates, and acting as a form of regularisation in deep neural networks. Introduced by Ioffe and Szegedy (2015), it reduces internal covariate shift and has become a standard component in convolutional and other deep learning architectures."@en ;
rdfs:label "Batch Normalisation"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf _:r2776 ;
rdfs:subClassOf _:r2777 ;
rdfs:subClassOf _:r2778 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:model-deployment ;
vc:bridgesTo ngm:transfer-learning ;
vc:contrastsWith ngm:group-normalisation ;
vc:contrastsWith ngm:instance-normalisation ;
vc:contrastsWith ngm:layer-normalisation ;
vc:contrastsWith ngm:weight-normalisation ;
vc:dependsOn ngm:backpropagation ;
vc:dependsOn ngm:neural-network-layer ;
vc:enables ngm:deep-learning ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:parameter ;
vc:isPartOf ngm:convolutional-neural-network ;
vc:isPartOf ngm:deep-neural-network ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:dropout ;
vc:relatedTo ngm:gradient-descent ;
vc:relatedTo ngm:optimisation ;
vc:relatedTo ngm:regularisation ;
vc:relatedTo ngm:technique ;
vc:requires ngm:mini-batch ;
vc:requires ngm:stochastic-gradient-descent ;
vc:slug "batch-normalisation" ;
vc:sourceDomain "machine-learning" ;
vc:uses ngm:neural-network ;
vc:uses ngm:statistics .
ngm:batch-operations a skos:Concept ;
rdfs:label "Batch Operations"@en .
ngm:batch-optimisation a skos:Concept ;
rdfs:label "Batch Optimisation"@en .
ngm:batch-payment a skos:Concept ;
rdfs:label "Batch Payment"@en .
ngm:batch-process a skos:Concept ;
rdfs:label "Batch Process"@en .
ngm:batch-processing a owl:Class ;
rdfs:comment "A computational paradigm in which jobs are accumulated and executed as a group rather than individually in real-time. Batch processing optimises throughput by amortising fixed overhead across many records, enabling efficient ETL pipelines, model training over large datasets, report generation, and vulnerability scanning. Scheduling may be time-based, event-triggered, or dependency-driven."@en ;
rdfs:label "Batch Processing"@en ;
rdfs:subClassOf ngm:data-pipeline ;
rdfs:subClassOf _:r2779 ;
rdfs:subClassOf _:r2780 ;
rdfs:subClassOf _:r2781 ;
rdfs:subClassOf _:r2782 ;
rdfs:subClassOf _:r2783 ;
vc:bridgesTo ngm:data-management ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:reinforcement-learning ;
vc:contrastsWith ngm:inference ;
vc:contrastsWith ngm:real-time-processing ;
vc:contrastsWith ngm:stream-processing ;
vc:dependsOn ngm:workflow-orchestration ;
vc:enables ngm:etl-pipeline ;
vc:enables ngm:machine-learning-discipline-pipeline ;
vc:enables ngm:model-training ;
vc:enables ngm:vulnerability-scanning ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:batch-normalisation ;
vc:hasPart ngm:batch-size ;
vc:hasPart ngm:message-queue ;
vc:isPartOf ngm:data-pipeline ;
vc:isPartOf ngm:lambda-architecture ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:data-warehousing ;
vc:relatedTo ngm:parallel-computing ;
vc:requires ngm:compute-cluster ;
vc:requires ngm:distributed-storage ;
vc:slug "batch-processing" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:ai-infrastructure ;
vc:uses ngm:apache-spark .
ngm:batch-recommendation a skos:Concept ;
rdfs:label "Batch Recommendation"@en .
ngm:batch-sampling a skos:Concept ;
rdfs:label "Batch Sampling"@en .
ngm:batch-scheduler a skos:Concept ;
rdfs:label "Batch Scheduler"@en .
ngm:batch-size a owl:Class ;
rdfs:comment "Batch Size is the number of training examples processed together in a single forward and backward pass before model parameters are updated. It is a critical hyperparameter governing the trade-off between training speed, memory usage, gradient noise, and convergence stability—small batches introduce regularising noise via stochastic gradient estimates, whilst large batches enable faster hardware utilisation but may generalise less well."@en ;
rdfs:label "Batch Size"@en ;
rdfs:subClassOf ngm:ai-technique ;
skos:broader ngm:ai-technique ;
vc:contrastsWith ngm:overfitting ;
vc:dependsOn ngm:deep-learning ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:isPartOf ngm:gradient-descent ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:epoch ;
vc:relatedTo ngm:hyperparameter ;
vc:slug "batch-size" ;
vc:sourceDomain "artificial-intelligence" .
ngm:batch-tax-processing a skos:Concept ;
rdfs:label "Batch Tax Processing"@en .
ngm:batch-training a skos:Concept ;
rdfs:label "Batch Training"@en .
ngm:batch-verification a owl:Class ;
rdfs:comment "Batch verification is a cryptographic technique that checks the validity of many signatures or proofs together using a single, combined computation, rather than verifying each one independently. It exploits algebraic structure in schemes such as Schnorr signatures and Bulletproofs to amortise the cost of verification across a batch, giving large speed-ups when many proofs must be checked, for example during blockchain block validation. The trade-off is that a failing batch identifies only that some element is invalid, not which one, without additional bisection."@en ;
rdfs:label "Batch Verification"@en ;
rdfs:subClassOf ngm:cryptographic-verification ;
rdfs:subClassOf _:r2784 ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.65"^^xsd:float ;
vc:requires ngm:cryptographic-verification ;
vc:slug "batch-verification" ;
vc:sourceDomain "security" .
ngm:batching a owl:Class ;
rdfs:comment "Batching is the practice of grouping multiple discrete operations, requests or data items so that they are processed together in a single pass rather than individually. It amortises fixed per-operation overheads such as draw calls, network round trips or kernel launches across many items, improving throughput at the cost of added latency for the items that wait to be grouped. Batching appears throughout computing, from GPU rendering (combining draw calls to reduce state changes) to machine learning inference (grouping requests to maximise accelerator utilisation)."@en ;
rdfs:label "Batching"@en ;
rdfs:subClassOf ngm:batch-processing ;
vc:enables ngm:throughput ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:batch-processing ;
vc:qualityScore "0.65"^^xsd:float ;
vc:slug "batching" ;
vc:sourceDomain "infrastructure" .
ngm:bathymetry a owl:Class ;
rdfs:label "Bathymetry"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:geodesy ;
vc:slug "bathymetry" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:battery a skos:Concept ;
rdfs:label "Battery"@en .
ngm:battery-energy-storage a skos:Concept ;
rdfs:label "Battery Energy Storage"@en .
ngm:battery-management-system a owl:Class ;
rdfs:comment "A Battery Management System (BMS) is an embedded electronic system that monitors, protects, and optimises the operation of a rechargeable battery pack by continuously measuring cell voltages, currents, and temperatures, then enforcing safety limits and balancing cell state-of-charge to extend pack lifetime. It provides the digital intelligence layer between raw electrochemical energy storage and the broader power electronics or vehicle system, communicating pack status via standardised interfaces such as CAN bus. Accurate state-of-charge and state-of-health estimation algorithms are the defining computational challenge of modern BMS design."@en ;
rdfs:label "Battery Management System"@en ;
rdfs:subClassOf ngm:embedded-systems ;
rdfs:subClassOf _:r2785 ;
rdfs:subClassOf _:r2786 ;
rdfs:subClassOf _:r2787 ;
rdfs:subClassOf _:r2788 ;
rdfs:subClassOf _:r2789 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:cloud-computing ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:enables ngm:power-supply ;
vc:enables ngm:predictive-maintenance ;
vc:enables ngm:thermal-management ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:current-sensor ;
vc:hasPart ngm:monitoring-system ;
vc:hasPart ngm:temperature-sensor ;
vc:isPartOf ngm:electric-vehicle ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:energy-and-power ;
vc:relatedTo ngm:energy-management ;
vc:relatedTo ngm:hardware-component ;
vc:requires ngm:can-bus ;
vc:requires ngm:firmware ;
vc:slug "battery-management-system" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:iso-26262 ;
vc:supports ngm:fleet-management ;
vc:supports ngm:functional-safety ;
vc:uses ngm:control-system ;
vc:uses ngm:kalman-filter ;
vc:uses ngm:power-management .
ngm:battery-or-inductive-power-link a skos:Concept ;
rdfs:label "Battery Or Inductive Power Link"@en .
ngm:battery-storage a skos:Concept ;
rdfs:label "Battery Storage"@en .
ngm:battery-technology a skos:Concept ;
rdfs:label "Battery Technology"@en .
ngm:battle-damage-assessment a skos:Concept ;
rdfs:label "Battle Damage Assessment"@en .
ngm:baum-welch-algorithm a skos:Concept ;
rdfs:label "Baum Welch Algorithm"@en .
ngm:bayes-centre a skos:Concept ;
rdfs:label "Bayes Centre"@en .
ngm:bayes-filter a owl:Class ;
rdfs:comment "BayesFilter denotes the canonical recursive probabilistic framework for sequential state estimation in partially-observable stochastic dynamical systems, computing at each timestep the posterior belief bel(x_t) = p(x_t | z_{1:t}, u_{1:t}) over the latent system state x_t conditioned on the full h..."@en ;
rdfs:label "Bayes Filter"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:bayesian-inference ;
rdfs:subClassOf ngm:probabilistic-filter ;
rdfs:subClassOf ngm:recursive-estimator ;
rdfs:subClassOf ngm:sequential-monte-carlo ;
rdfs:subClassOf ngm:state-estimation ;
rdfs:subClassOf _:r2790 ;
rdfs:subClassOf _:r2791 ;
rdfs:subClassOf _:r2792 ;
rdfs:subClassOf _:r2793 ;
rdfs:subClassOf _:r2794 ;
rdfs:subClassOf _:r2795 ;
rdfs:subClassOf _:r2796 ;
rdfs:subClassOf _:r2797 ;
rdfs:subClassOf _:r2798 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:robo-navigation-and-planning ;
vc:contrastsWith ngm:batch-optimisation ;
vc:contrastsWith ngm:deterministic-observer ;
vc:contrastsWith ngm:least-squares-estimation ;
vc:contrastsWith ngm:pose-graph ;
vc:contrastsWith ngm:pure-neural-state-estimation ;
vc:dependsOn ngm:dynamic-bayesian-networks ;
vc:dependsOn ngm:hidden-markov-models ;
vc:dependsOn ngm:measure-theory ;
vc:dependsOn ngm:probability-theory ;
vc:dependsOn ngm:stochastic-processes ;
vc:enables ngm:active-perception ;
vc:enables ngm:belief-space-planning ;
vc:enables ngm:robot-localisation ;
vc:enables ngm:sensor-fusion ;
vc:enables ngm:simultaneous-localisation-and-mapping ;
vc:enables ngm:target-tracking ;
vc:enables ngm:uncertainty-quantification ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:belief-state ;
vc:hasPart ngm:measurement-update-step ;
vc:hasPart ngm:motion-model ;
vc:hasPart ngm:normalisation-constant ;
vc:hasPart ngm:observation-model ;
vc:hasPart ngm:posterior-distribution ;
vc:hasPart ngm:prediction-step ;
vc:hasPart ngm:prior-distribution ;
vc:implements ngm:bayes-rule ;
vc:implements ngm:bayesian-inference ;
vc:implements ngm:chapman-kolmogorov-equation ;
vc:implements ngm:state-estimation ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:expectation-maximisation ;
vc:relatedTo ngm:factor-graph ;
vc:relatedTo ngm:pomdp ;
vc:relatedTo ngm:smoothing-and-mapping ;
vc:relatedTo ngm:variational-inference ;
vc:requires ngm:control-inputs ;
vc:requires ngm:initial-belief ;
vc:requires ngm:markov-assumption ;
vc:requires ngm:motion-model ;
vc:requires ngm:observation-model ;
vc:requires ngm:sensor-measurements ;
vc:slug "bayes-filter" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:ieee-robotics-and-automation-society ;
vc:standardizedBy ngm:probabilistic-robotics-textbook ;
vc:standardizedBy ngm:ros-navigation-stack ;
vc:supports ngm:aerospace-guidance-navigation-control ;
vc:supports ngm:autonomous-driving ;
vc:supports ngm:autonomous-navigation ;
vc:supports ngm:drone-autonomy ;
vc:supports ngm:mobile-robotics ;
vc:supports ngm:surgical-robotics ;
vc:uses ngm:gaussian-distribution ;
vc:uses ngm:importance-sampling ;
vc:uses ngm:linearisation ;
vc:uses ngm:monte-carlo-integration ;
vc:uses ngm:resampling ;
vc:uses ngm:sigma-point-sampling .
ngm:bayes-rule a skos:Concept ;
rdfs:label "Bayes Rule"@en .
ngm:bayes-theorem a owl:Class ;
rdfs:comment "Bayes' theorem is a fundamental result in probability theory that describes how to update the probability of a hypothesis in light of new evidence. It expresses the posterior probability as proportional to the product of the prior probability and the likelihood of the evidence, normalised by the total probability of the evidence. The theorem is the mathematical foundation of Bayesian inference and probabilistic reasoning in artificial intelligence."@en ;
rdfs:label "Bayes Theorem"@en ;
rdfs:subClassOf ngm:probability-theory ;
rdfs:subClassOf ngm:statistical-inference ;
rdfs:subClassOf _:r2799 ;
rdfs:subClassOf _:r2800 ;
rdfs:subClassOf _:r2801 ;
rdfs:subClassOf _:r2802 ;
rdfs:subClassOf _:r2803 ;
rdfs:subClassOf _:r2804 ;
vc:bridgesTo ngm:bayesian-deep-learning ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:bridgesTo ngm:natural-language-processing ;
vc:contrastsWith ngm:frequentist-statistics ;
vc:contrastsWith ngm:maximum-likelihood-estimation ;
vc:dependsOn ngm:conditional-probability ;
vc:dependsOn ngm:probabilistic-model ;
vc:dependsOn ngm:probability-theory ;
vc:enables ngm:active-learning ;
vc:enables ngm:bayesian-inference ;
vc:enables ngm:bayesian-network ;
vc:enables ngm:bayesian-optimisation ;
vc:enables ngm:gaussian-process ;
vc:enables ngm:model-selection ;
vc:enables ngm:naive-bayes-classifier ;
vc:enables ngm:statistical-inference ;
vc:enables ngm:uncertainty-quantification ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:bayesian-decision-theory ;
vc:hasPart ngm:bayesian-deep-learning ;
vc:hasPart ngm:bayesian-optimisation ;
vc:hasPart ngm:likelihood-function ;
vc:hasPart ngm:marginal-likelihood ;
vc:hasPart ngm:posterior-distribution ;
vc:hasPart ngm:prior-distribution ;
vc:implements ngm:bayesian-inference ;
vc:isPartOf ngm:probability-theory ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:expectation-maximisation ;
vc:relatedTo ngm:markov-chain-monte-carlo ;
vc:relatedTo ngm:maximum-likelihood-estimation ;
vc:relatedTo ngm:statistical-inference ;
vc:relatedTo ngm:variational-inference ;
vc:slug "bayes-theorem" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:probability-theory ;
vc:supports ngm:decision-theory ;
vc:supports ngm:inference ;
vc:supports ngm:machine-learning-discipline ;
vc:supports ngm:reasoning ;
vc:uses ngm:conjugate-prior ;
vc:uses ngm:probabilistic-model .
ngm:bayesian-analysis-journal a skos:Concept ;
rdfs:label "Bayesian Analysis Journal"@en .
ngm:bayesian-brain-hypothesis a skos:Concept ;
rdfs:label "Bayesian Brain Hypothesis"@en .
ngm:bayesian-decision-theory a owl:Class ;
rdfs:comment "Bayesian decision theory is a framework for making decisions under uncertainty by combining probabilities of outcomes with a loss or utility function to choose actions that minimise expected loss. It uses Bayesian updating to incorporate evidence."@en ;
rdfs:label "Bayesian Decision Theory"@en ;
rdfs:subClassOf ngm:decision-theory ;
rdfs:subClassOf ngm:statistical-decision-theory ;
rdfs:subClassOf ngm:statistics ;
rdfs:subClassOf _:r2805 ;
rdfs:subClassOf _:r2806 ;
rdfs:subClassOf _:r2807 ;
rdfs:subClassOf _:r2808 ;
rdfs:subClassOf _:r2809 ;
rdfs:subClassOf _:r2810 ;
rdfs:subClassOf _:r2811 ;
rdfs:subClassOf _:r2812 ;
rdfs:subClassOf _:r2813 ;
rdfs:subClassOf _:r2814 ;
rdfs:subClassOf _:r2815 ;
rdfs:subClassOf _:r2816 ;
rdfs:subClassOf _:r2817 ;
vc:bridgesTo ngm:game-theory ;
vc:bridgesTo ngm:operations-research ;
vc:bridgesTo ngm:reinforcement-learning ;
vc:contrastsWith ngm:frequentist-statistics ;
vc:contrastsWith ngm:minimax-decision-theory ;
vc:dependsOn ngm:bayes-theorem ;
vc:dependsOn ngm:bayesian-inference ;
vc:dependsOn ngm:prior-distribution ;
vc:dependsOn ngm:probability-theory ;
vc:enables ngm:active-learning ;
vc:enables ngm:bayesian-optimisation ;
vc:enables ngm:hypothesis-testing ;
vc:enables ngm:markov-decision-process ;
vc:enables ngm:naive-bayes-classifier ;
vc:enables ngm:optimal-classifier ;
vc:enables ngm:uncertainty-quantification ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:active-learning ;
vc:hasPart ngm:bayesian-deep-learning ;
vc:hasPart ngm:bayesian-optimisation ;
vc:hasPart ngm:loss-function ;
vc:hasPart ngm:optimal-classifier ;
vc:hasPart ngm:posterior-distribution ;
vc:hasPart ngm:prior-distribution ;
vc:hasPart ngm:risk-minimisation ;
vc:hasPart ngm:utility-function ;
vc:implements ngm:bayes-theorem ;
vc:implements ngm:bayesian-inference ;
vc:implements ngm:expected-utility-theory ;
vc:qualityScore "0.6"^^xsd:float ;
vc:relatedTo ngm:game-theory ;
vc:relatedTo ngm:gaussian-process ;
vc:relatedTo ngm:information-theory ;
vc:relatedTo ngm:neural-network ;
vc:relatedTo ngm:statistical-decision-theory ;
vc:requires ngm:bayes-theorem ;
vc:requires ngm:bayesian-inference ;
vc:requires ngm:loss-function ;
vc:requires ngm:posterior-distribution ;
vc:requires ngm:probability-theory ;
vc:requires ngm:statistics ;
vc:slug "bayesian-decision-theory" ;
vc:sourceDomain "machine-learning" ;
vc:supports ngm:ai-safety ;
vc:supports ngm:machine-learning-discipline ;
vc:supports ngm:operations-research ;
vc:supports ngm:reinforcement-learning ;
vc:uses ngm:bayesian-inference ;
vc:uses ngm:expected-utility-theory ;
vc:uses ngm:gaussian-process ;
vc:uses ngm:information-theory .
ngm:bayesian-deep-learning a owl:Class ;
rdfs:comment "Bayesian deep learning combines neural networks with Bayesian inference to represent uncertainty over model parameters and predictions. It treats network weights as random variables with prior and posterior distributions rather than fixed point estimates, enabling calibrated uncertainty quantification over both model parameters and outputs."@en ;
rdfs:label "Bayesian Deep Learning"@en ;
rdfs:subClassOf ngm:bayesian-inference ;
rdfs:subClassOf ngm:deep-learning ;
rdfs:subClassOf ngm:probabilistic-machine-learning ;
rdfs:subClassOf _:r2818 ;
rdfs:subClassOf _:r2819 ;
rdfs:subClassOf _:r2820 ;
rdfs:subClassOf _:r2821 ;
rdfs:subClassOf _:r2822 ;
rdfs:subClassOf _:r2823 ;
rdfs:subClassOf _:r2824 ;
rdfs:subClassOf _:r2825 ;
rdfs:subClassOf _:r2826 ;
rdfs:subClassOf _:r2827 ;
rdfs:subClassOf _:r2828 ;
vc:bridgesTo ngm:causal-inference ;
vc:bridgesTo ngm:continual-learning ;
vc:bridgesTo ngm:foundation-model ;
vc:bridgesTo ngm:robotics ;
vc:bridgesTo ngm:scientific-computing ;
vc:contrastsWith ngm:dropout ;
vc:contrastsWith ngm:frequentist-statistics ;
vc:contrastsWith ngm:maximum-a-posteriori-estimation ;
vc:contrastsWith ngm:maximum-likelihood-estimation ;
vc:dependsOn ngm:activation-function ;
vc:dependsOn ngm:convolutional-neural-network ;
vc:dependsOn ngm:loss-function ;
vc:dependsOn ngm:transformer-architecture ;
vc:enables ngm:active-learning ;
vc:enables ngm:anomaly-detection ;
vc:enables ngm:continual-learning ;
vc:enables ngm:model-calibration ;
vc:enables ngm:out-of-distribution-detection ;
vc:enables ngm:safe-ai ;
vc:enables ngm:uncertainty-quantification ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:deep-ensembles ;
vc:hasPart ngm:evidence-lower-bound ;
vc:hasPart ngm:laplace-approximation ;
vc:hasPart ngm:likelihood-function ;
vc:hasPart ngm:monte-carlo-dropout ;
vc:hasPart ngm:posterior-distribution ;
vc:hasPart ngm:prior-distribution ;
vc:implements ngm:evidence-lower-bound ;
vc:implements ngm:markov-chain-monte-carlo ;
vc:implements ngm:posterior-approximation ;
vc:implements ngm:variational-inference ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:diffusion-model ;
vc:relatedTo ngm:gaussian-process ;
vc:relatedTo ngm:generative-adversarial-network ;
vc:relatedTo ngm:graphical-model ;
vc:relatedTo ngm:model-calibration ;
vc:relatedTo ngm:neural-architecture-search ;
vc:relatedTo ngm:neural-network ;
vc:relatedTo ngm:normalising-flow ;
vc:relatedTo ngm:vae ;
vc:requires ngm:backpropagation ;
vc:requires ngm:bayesian-inference ;
vc:requires ngm:deep-learning ;
vc:requires ngm:gradient-descent ;
vc:requires ngm:neural-network ;
vc:requires ngm:prior-distribution ;
vc:requires ngm:probabilistic-inference ;
vc:slug "bayesian-deep-learning" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:iso-iec-22989-2022 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:autonomous-vehicle ;
vc:supports ngm:federated-learning ;
vc:supports ngm:medical-ai ;
vc:supports ngm:robotics ;
vc:supports ngm:scientific-computing ;
vc:uses ngm:laplace-approximation ;
vc:uses ngm:markov-chain-monte-carlo ;
vc:uses ngm:monte-carlo-dropout ;
vc:uses ngm:reparameterisation-trick ;
vc:uses ngm:stochastic-gradient-descent ;
vc:uses ngm:variational-inference .
ngm:bayesian-estimation a skos:Concept ;
rdfs:label "Bayesian Estimation"@en .
ngm:bayesian-forecasting a skos:Concept ;
rdfs:label "Bayesian Forecasting"@en .
ngm:bayesian-game a skos:Concept ;
rdfs:label "Bayesian Game"@en .
ngm:bayesian-inference a owl:Class ;
rdfs:comment "Bayesian Inference is a principled statistical framework that updates the probability of a hypothesis as new evidence is observed, using Bayes' theorem to combine a prior distribution over parameters with a likelihood function derived from data to yield a posterior distribution. Unlike frequentist methods, it treats probability as a degree of belief and propagates uncertainty through every step of reasoning, enabling calibrated predictions and natural model comparison via marginal likelihoods. In machine learning, it underpins probabilistic graphical models, Gaussian processes, Bayesian neural networks, variational inference, and Markov Chain Monte Carlo methods. Its capacity to incorporate domain knowledge through priors and to quantify epistemic uncertainty makes it foundational for safety-critical AI, active learning, and sequential decision-making."@en ;
rdfs:label "Bayesian Inference"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:probabilistic-inference ;
rdfs:subClassOf ngm:statistical-inference ;
rdfs:subClassOf _:r2829 ;
rdfs:subClassOf _:r2830 ;
rdfs:subClassOf _:r2831 ;
rdfs:subClassOf _:r2832 ;
rdfs:subClassOf _:r2833 ;
rdfs:subClassOf _:r2834 ;
rdfs:subClassOf _:r2835 ;
rdfs:subClassOf _:r2836 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:causal-inference ;
vc:bridgesTo ngm:decision-theory ;
vc:bridgesTo ngm:information-theory ;
vc:bridgesTo ngm:minimum-description-length ;
vc:contrastsWith ngm:deep-learning ;
vc:contrastsWith ngm:frequentist-statistics ;
vc:contrastsWith ngm:maximum-a-posteriori-estimation ;
vc:contrastsWith ngm:maximum-likelihood-estimation ;
vc:dependsOn ngm:conditional-probability ;
vc:dependsOn ngm:information-theory ;
vc:dependsOn ngm:probability-theory ;
vc:enables ngm:active-learning ;
vc:enables ngm:anomaly-detection ;
vc:enables ngm:bayesian-deep-learning ;
vc:enables ngm:bayesian-optimisation ;
vc:enables ngm:continual-learning ;
vc:enables ngm:model-selection ;
vc:enables ngm:sequential-decision-making ;
vc:enables ngm:uncertainty-quantification ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:approximate-bayesian-computation ;
vc:hasPart ngm:conjugate-prior ;
vc:hasPart ngm:empirical-bayes ;
vc:hasPart ngm:hierarchical-bayesian-model ;
vc:hasPart ngm:likelihood-function ;
vc:hasPart ngm:marginal-likelihood ;
vc:hasPart ngm:markov-chain-monte-carlo ;
vc:hasPart ngm:posterior-distribution ;
vc:hasPart ngm:posterior-predictive-distribution ;
vc:hasPart ngm:prior-distribution ;
vc:hasPart ngm:simulation-based-inference ;
vc:hasPart ngm:variational-inference ;
vc:implements ngm:bayes-theorem ;
vc:implements ngm:posterior-approximation ;
vc:implements ngm:probabilistic-programming ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:causal-inference ;
vc:relatedTo ngm:decision-theory ;
vc:relatedTo ngm:deep-learning ;
vc:relatedTo ngm:diffusion-model ;
vc:relatedTo ngm:gaussian-process ;
vc:relatedTo ngm:graphical-model ;
vc:relatedTo ngm:information-theory ;
vc:relatedTo ngm:normalising-flow ;
vc:requires ngm:bayes-theorem ;
vc:requires ngm:conditional-probability ;
vc:requires ngm:probability-theory ;
vc:requires ngm:statistical-model ;
vc:slug "bayesian-inference" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:iso-iec-22989-2022 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:computer-vision ;
vc:supports ngm:machine-learning-discipline ;
vc:supports ngm:natural-language-processing ;
vc:supports ngm:reinforcement-learning ;
vc:supports ngm:robotics ;
vc:supports ngm:scientific-computing ;
vc:uses ngm:expectation-maximisation ;
vc:uses ngm:gaussian-process ;
vc:uses ngm:hamiltonian-monte-carlo ;
vc:uses ngm:knowledge-representation ;
vc:uses ngm:stochastic-gradient-langevin-dynamics ;
vc:uses ngm:variational-inference .
ngm:bayesian-knowledge-tracing a owl:Class ;
rdfs:comment "Bayesian Knowledge Tracing (BKT) is a probabilistic modelling technique that estimates a learner's mastery of a skill over time by treating knowledge as a latent binary state inferred from a sequence of correct and incorrect responses. Using a hidden Markov model with parameters for prior knowledge, learning, guessing, and slipping, BKT updates the probability that a student has mastered each skill after every interaction. It is a cornerstone of intelligent tutoring systems and adaptive learning, enabling personalised pacing and content selection."@en ;
rdfs:label "Bayesian Knowledge Tracing"@en ;
rdfs:subClassOf ngm:adaptive-learning ;
rdfs:subClassOf ngm:bayesian-inference ;
rdfs:subClassOf ngm:learner-model ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf ngm:probabilistic-model ;
rdfs:subClassOf _:r2837 ;
rdfs:subClassOf _:r2838 ;
rdfs:subClassOf _:r2839 ;
rdfs:subClassOf _:r2840 ;
rdfs:subClassOf _:r2841 ;
rdfs:subClassOf _:r2842 ;
rdfs:subClassOf _:r2843 ;
rdfs:subClassOf _:r2844 ;
rdfs:subClassOf _:r2845 ;
rdfs:subClassOf _:r2846 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:data-privacy ;
vc:bridgesTo ngm:deep-knowledge-tracing ;
vc:bridgesTo ngm:explainable-ai ;
vc:bridgesTo ngm:large-language-model ;
vc:bridgesTo ngm:learning-analytics ;
vc:bridgesTo ngm:open-learner-model ;
vc:contrastsWith ngm:deep-knowledge-tracing ;
vc:contrastsWith ngm:item-response-theory ;
vc:contrastsWith ngm:neural-network ;
vc:contrastsWith ngm:reinforcement-learning ;
vc:contrastsWith ngm:spaced-repetition ;
vc:dependsOn ngm:bayesian-inference ;
vc:dependsOn ngm:expectation-maximisation ;
vc:dependsOn ngm:hidden-markov-model ;
vc:dependsOn ngm:knowledge-component-model ;
vc:dependsOn ngm:probabilistic-inference ;
vc:enables ngm:adaptive-learning ;
vc:enables ngm:computerised-adaptive-testing ;
vc:enables ngm:formative-assessment ;
vc:enables ngm:intelligent-tutoring-system ;
vc:enables ngm:learning-analytics ;
vc:enables ngm:mastery-learning ;
vc:enables ngm:open-learner-model ;
vc:enables ngm:personalised-learning ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:bayesian-inference ;
vc:hasPart ngm:expectation-maximisation ;
vc:hasPart ngm:hidden-markov-model ;
vc:hasPart ngm:knowledge-component-model ;
vc:hasPart ngm:mastery-learning ;
vc:hasPart ngm:probabilistic-inference ;
vc:implements ngm:adaptive-learning ;
vc:implements ngm:bayesian-inference ;
vc:implements ngm:mastery-learning ;
vc:implements ngm:personalised-learning ;
vc:isPartOf ngm:adaptive-learning ;
vc:isPartOf ngm:intelligent-tutoring-system ;
vc:qualityScore "0.91"^^xsd:float ;
vc:relatedTo ngm:affective-computing ;
vc:relatedTo ngm:attention-mechanism ;
vc:relatedTo ngm:cognitive-science ;
vc:relatedTo ngm:content-repository ;
vc:relatedTo ngm:curriculum-learning ;
vc:relatedTo ngm:deep-knowledge-tracing ;
vc:relatedTo ngm:federated-learning ;
vc:relatedTo ngm:gamification ;
vc:relatedTo ngm:graph-neural-network ;
vc:relatedTo ngm:item-response-theory ;
vc:relatedTo ngm:knowledge-graph ;
vc:relatedTo ngm:large-language-model ;
vc:relatedTo ngm:psychometrics ;
vc:relatedTo ngm:reinforcement-learning ;
vc:relatedTo ngm:spaced-repetition ;
vc:relatedTo ngm:transfer-learning ;
vc:relatedTo ngm:transformer-architecture ;
vc:relatedTo ngm:two-sigma-problem ;
vc:requires ngm:bayesian-inference ;
vc:requires ngm:educational-technology ;
vc:requires ngm:formative-assessment ;
vc:requires ngm:knowledge-component-model ;
vc:requires ngm:psychometrics ;
vc:slug "bayesian-knowledge-tracing" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:ieee-ltsc ;
vc:standardizedBy ngm:ims-global-learning-consortium ;
vc:supports ngm:adaptive-learning ;
vc:supports ngm:computerised-adaptive-testing ;
vc:supports ngm:domain-model ;
vc:supports ngm:formative-assessment ;
vc:supports ngm:learner-model ;
vc:supports ngm:personalised-learning ;
vc:supports ngm:reinforcement-learning ;
vc:uses ngm:bayesian-inference ;
vc:uses ngm:cognitive-science ;
vc:uses ngm:expectation-maximisation ;
vc:uses ngm:hidden-markov-model ;
vc:uses ngm:knowledge-component-model ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:probabilistic-inference .
ngm:bayesian-network a skos:Concept ;
rdfs:label "Bayesian Network"@en .
ngm:bayesian-networks a skos:Concept ;
rdfs:label "Bayesian Networks"@en .
ngm:bayesian-nonparametrics a skos:Concept ;
rdfs:label "Bayesian Nonparametrics"@en .
ngm:bayesian-optimisation a owl:Class ;
rdfs:comment "Bayesian Optimisation is a sequential, sample-efficient strategy for optimising expensive black-box objective functions by constructing a probabilistic surrogate model — most commonly a Gaussian Process — over the function's input space, then using an acquisition function to select the next evaluation point by trading off exploration of uncertain regions against exploitation of known optima. The method accumulates knowledge about the objective between evaluations, making it uniquely valuable when each function evaluation is computationally or financially costly. It maintains a posterior distribution over the objective that quantifies uncertainty and guides convergence to a global optimum with far fewer evaluations than grid search or random search. Applications span hyperparameter tuning, neural architecture search, drug discovery, materials science, and robotics controller design."@en ;
rdfs:label "Bayesian Optimisation"@en ;
rdfs:subClassOf ngm:bayesian-inference ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf ngm:optimisation ;
rdfs:subClassOf ngm:probabilistic-model ;
rdfs:subClassOf _:r2847 ;
rdfs:subClassOf _:r2848 ;
rdfs:subClassOf _:r2849 ;
rdfs:subClassOf _:r2850 ;
rdfs:subClassOf _:r2851 ;
rdfs:subClassOf _:r2852 ;
rdfs:subClassOf _:r2853 ;
rdfs:subClassOf _:r2854 ;
rdfs:subClassOf _:r2855 ;
rdfs:subClassOf _:r2856 ;
rdfs:subClassOf _:r2857 ;
rdfs:subClassOf _:r2858 ;
vc:bridgesTo ngm:experimental-design ;
vc:bridgesTo ngm:large-language-model ;
vc:bridgesTo ngm:model-predictive-control ;
vc:bridgesTo ngm:protein-engineering ;
vc:bridgesTo ngm:robotics ;
vc:bridgesTo ngm:self-driving-laboratory ;
vc:contrastsWith ngm:evolutionary-algorithm ;
vc:contrastsWith ngm:gradient-descent ;
vc:contrastsWith ngm:grid-search ;
vc:contrastsWith ngm:random-search ;
vc:dependsOn ngm:gaussian-process ;
vc:dependsOn ngm:gaussian-process-regression ;
vc:dependsOn ngm:kernel-function ;
vc:dependsOn ngm:marginal-likelihood ;
vc:dependsOn ngm:probabilistic-inference ;
vc:dependsOn ngm:surrogate-model ;
vc:enables ngm:auto-ml ;
vc:enables ngm:automated-design ;
vc:enables ngm:drug-discovery ;
vc:enables ngm:hyperparameter-optimisation ;
vc:enables ngm:hyperparameter-tuning ;
vc:enables ngm:material-science ;
vc:enables ngm:multi-objective-optimisation ;
vc:enables ngm:neural-architecture-search ;
vc:enables ngm:protein-engineering ;
vc:enables ngm:self-driving-laboratory ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:acquisition-function ;
vc:hasPart ngm:expected-improvement ;
vc:hasPart ngm:exploration-exploitation-tradeoff ;
vc:hasPart ngm:gaussian-process ;
vc:hasPart ngm:kernel-function ;
vc:hasPart ngm:marginal-likelihood ;
vc:hasPart ngm:surrogate-model ;
vc:hasPart ngm:uncertainty-quantification ;
vc:implements ngm:active-learning ;
vc:implements ngm:bayesian-inference ;
vc:implements ngm:experimental-design ;
vc:implements ngm:exploration-exploitation-tradeoff ;
vc:implements ngm:uncertainty-quantification ;
vc:qualityScore "0.93"^^xsd:float ;
vc:relatedTo ngm:active-learning ;
vc:relatedTo ngm:expected-improvement ;
vc:relatedTo ngm:exploration-exploitation-tradeoff ;
vc:relatedTo ngm:gaussian-process-regression ;
vc:relatedTo ngm:hyperparameter-optimisation ;
vc:relatedTo ngm:kriging ;
vc:relatedTo ngm:multi-fidelity-optimisation ;
vc:relatedTo ngm:reinforcement-learning ;
vc:relatedTo ngm:sparse-gaussian-process ;
vc:relatedTo ngm:transfer-learning ;
vc:relatedTo ngm:uncertainty-quantification ;
vc:relatedTo ngm:variational-inference ;
vc:requires ngm:bayesian-inference ;
vc:requires ngm:gaussian-process ;
vc:requires ngm:kernel-function ;
vc:requires ngm:probabilistic-inference ;
vc:requires ngm:surrogate-model ;
vc:requires ngm:uncertainty-quantification ;
vc:slug "bayesian-optimisation" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:hpobench ;
vc:standardizedBy ngm:neurips-black-box-optimisation-competition ;
vc:supports ngm:auto-ml ;
vc:supports ngm:deep-learning ;
vc:supports ngm:drug-discovery ;
vc:supports ngm:hyperparameter-tuning ;
vc:supports ngm:machine-learning-discipline ;
vc:supports ngm:material-science ;
vc:supports ngm:model-predictive-control ;
vc:supports ngm:robotics ;
vc:uses ngm:acquisition-function ;
vc:uses ngm:bayesian-inference ;
vc:uses ngm:expected-improvement ;
vc:uses ngm:gaussian-process ;
vc:uses ngm:kernel-function ;
vc:uses ngm:probabilistic-model ;
vc:uses ngm:sparse-gaussian-process ;
vc:uses ngm:surrogate-model ;
vc:uses ngm:variational-inference .
ngm:bayesian-risk-models a skos:Concept ;
rdfs:label "Bayesian Risk Models"@en .
ngm:bbc-generative-ai-principles a skos:Concept ;
rdfs:label "Bbc Generative AI Principles"@en .
ngm:bbc-iplayer a skos:Concept ;
rdfs:label "Bbc Iplayer"@en .
ngm:bbq-benchmark a skos:Concept ;
rdfs:label "Bbq Benchmark"@en .
ngm:bbr-algorithm a skos:Concept ;
rdfs:label "Bbr Algorithm"@en .
ngm:bbs-signature a owl:Class ;
rdfs:comment "BBS+ Signature is a pairing-based digital signature scheme that signs a vector of messages simultaneously and supports the generation of zero-knowledge proofs that reveal only a chosen subset of those messages — a property known as selective disclosure — without revealing the full signed message set or enabling linkage of multiple presentations to the same credential. It is a cornerstone primitive for privacy-preserving verifiable credentials."@en ;
rdfs:label "BBS+ Signature"@en ;
rdfs:subClassOf ngm:cryptographic-signature ;
vc:enables ngm:privacy-preserving-identity ;
vc:enables ngm:selective-disclosure ;
vc:enables ngm:verifiable-credentials ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:bls-signature ;
vc:relatedTo ngm:decentralized-identifiers ;
vc:slug "bbs-signature" ;
vc:sourceDomain "security" ;
vc:uses ngm:cryptographic-primitive ;
vc:uses ngm:cryptographic-proof .
ngm:bbs-signatures a owl:Class ;
rdfs:comment "BBS+ Signatures is the collective term for the class of pairing-based multi-message signature schemes derived from the BBS construction, encompassing both the base signature algorithm and the proof-of-knowledge protocols that enable selective disclosure and unlinkable presentation of signed credential attributes. As a scheme family, BBS+ Signatures represent the cryptographic foundation for privacy-preserving digital credential ecosystems."@en ;
rdfs:label "BBS+ Signatures"@en ;
rdfs:subClassOf ngm:cryptographic-signature ;
rdfs:subClassOf _:r2582 ;
rdfs:subClassOf _:r2583 ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:bridgesTo ngm:governance ;
vc:contrastsWith ngm:json-data-interchange-format-web-token ;
vc:dependsOn ngm:zero-knowledge-proof ;
vc:enables ngm:anonymous-credential ;
vc:enables ngm:privacy-preserving-authentication ;
vc:enables ngm:selective-disclosure ;
vc:enables ngm:verifiable-credentials ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:bbs-signature ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:digital-identity ;
vc:relatedTo ngm:privacy-preserving-identity ;
vc:requires ngm:bilinear-pairing ;
vc:slug "bbs-signatures" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:ietf ;
vc:standardizedBy ngm:w3-c ;
vc:supports ngm:decentralized-identifier ;
vc:supports ngm:self-sovereign-identity ;
vc:uses ngm:commitment-scheme ;
vc:uses ngm:cryptographic-primitive ;
vc:uses ngm:cryptographic-proof-system .
ngm:bc-0120-consensus-mechanism a owl:Class ;
rdfs:comment "BC-0120-consensus-mechanism is an ontology catalogue entry representing the knowledge domain of blockchain consensus mechanisms — the family of distributed protocols by which a peer-to-peer network of nodes agrees on a canonical ordering of transactions and the current state of a shared ledger without a trusted central authority. It serves as an organising concept node within a blockchain knowledge graph taxonomy."@en ;
rdfs:label "BC-0120-consensus-mechanism"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf _:r2584 ;
rdfs:subClassOf _:r2585 ;
rdfs:subClassOf _:r2586 ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:consensus-mechanism ;
vc:hasPart ngm:proof-of-stake ;
vc:hasPart ngm:proof-of-work ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:byzantine-fault-tolerance ;
vc:relatedTo ngm:finality ;
vc:relatedTo ngm:sybil-resistance ;
vc:slug "bc-0120-consensus-mechanism" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:fork-choice-rule .
ngm:bc-0442-certification-and-compliance a owl:Class ;
rdfs:comment "Certification and compliance in blockchain refers to the processes by which systems, service providers and tokens are assessed against technical standards and legal requirements, and formally attested as meeting them."@en ;
rdfs:label "BC-0442-certification-and-compliance"@en ;
rdfs:subClassOf ngm:regulatory-compliance ;
rdfs:subClassOf _:r2587 ;
vc:bridgesTo ngm:compliance ;
vc:enables ngm:compliance ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:regulatory-compliance ;
vc:slug "bc-0442-certification-and-compliance" ;
vc:sourceDomain "blockchain" .
ngm:bc-0456-virtual-asset-service-providers a owl:Class ;
rdfs:comment "Virtual asset service providers are businesses that conduct activities such as exchange, transfer, custody or issuance of crypto-assets on behalf of others, and that are subject to financial regulation."@en ;
rdfs:label "BC-0456-virtual-asset-service-providers"@en ;
rdfs:subClassOf ngm:regulatory-compliance ;
rdfs:subClassOf _:r2588 ;
rdfs:subClassOf _:r2589 ;
vc:bridgesTo ngm:fatf ;
vc:enables ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:aml-kyc-compliance ;
vc:requires ngm:travel-rule ;
vc:slug "bc-0456-virtual-asset-service-providers" ;
vc:sourceDomain "blockchain" .
ngm:bc-0480-kyc-requirements a owl:Class ;
rdfs:comment "KYC requirements are the obligations placed on regulated firms to identify and verify their customers, assess risk and monitor activity as part of anti-money-laundering and counter-terrorist-financing controls."@en ;
rdfs:label "BC-0480-kyc-requirements"@en ;
rdfs:subClassOf ngm:regulatory-compliance ;
rdfs:subClassOf _:r2590 ;
vc:bridgesTo ngm:kyc ;
vc:enables ngm:aml ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:identity-verification ;
vc:slug "bc-0480-kyc-requirements" ;
vc:sourceDomain "blockchain" .
ngm:bc-0482-eu-mica-regulation a owl:Class ;
rdfs:comment "The EU MiCA regulation is the European Union's Markets in Crypto-Assets framework, which establishes harmonised rules for the issuance, offering and provision of services relating to crypto-assets across member states."@en ;
rdfs:label "BC-0482-eu-mica-regulation"@en ;
rdfs:subClassOf ngm:regulatory-compliance ;
rdfs:subClassOf _:r2591 ;
vc:bridgesTo ngm:bc-0482-eu-mica-regulation ;
vc:enables ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:securities-regulation ;
vc:slug "bc-0482-eu-mica-regulation" ;
vc:sourceDomain "blockchain" .
ngm:bc-0484-markets-in-crypto-assets a owl:Class ;
rdfs:comment "Markets in Crypto-Assets is the European Union regulatory framework that defines categories of crypto-assets and sets authorisation and conduct rules for their issuers and service providers."@en ;
rdfs:label "BC-0484-markets-in-crypto-assets"@en ;
rdfs:subClassOf ngm:regulatory-compliance ;
rdfs:subClassOf _:r2592 ;
vc:bridgesTo ngm:bc-0482-eu-mica-regulation ;
vc:enables ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:securities-regulation ;
vc:slug "bc-0484-markets-in-crypto-assets" ;
vc:sourceDomain "blockchain" .
ngm:bc-cryptographic-primitive a owl:Class ;
a skos:Concept ;
rdfs:comment "Taxonomy hub for the foundational cryptographic building blocks underpinning blockchain systems, including hash functions, digital signatures, asymmetric encryption, zero-knowledge proofs, and cryptographic commitments. These primitives collectively provide the security properties of integrity, authenticity, and privacy that make distributed ledger technology trustworthy."@en ;
rdfs:label "Cryptographic Primitive (Blockchain)"@en ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf _:r22723 ;
rdfs:subClassOf _:r22724 ;
rdfs:subClassOf _:r22725 ;
rdfs:subClassOf _:r22726 ;
rdfs:subClassOf _:r22727 ;
rdfs:subClassOf _:r22728 ;
rdfs:subClassOf _:r22729 ;
rdfs:subClassOf _:r22730 ;
rdfs:subClassOf _:r22731 ;
rdfs:subClassOf _:r22732 ;
skos:broader ngm:blockchain ;
vc:enables ngm:consensus-mechanism ;
vc:enables ngm:cryptographic-protocol ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:asymmetric-encryption ;
vc:hasPart ngm:cryptographic-commitment ;
vc:hasPart ngm:cryptographic-hash-function ;
vc:hasPart ngm:digital-signature ;
vc:hasPart ngm:elliptic-curve-cryptography ;
vc:hasPart ngm:merkle-tree ;
vc:hasPart ngm:public-key-cryptography ;
vc:hasPart ngm:random-number-generation ;
vc:hasPart ngm:symmetric-encryption ;
vc:hasPart ngm:zero-knowledge-proof ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:cryptographic-infrastructure ;
vc:relatedTo ngm:homomorphic-encryption ;
vc:slug "bc-cryptographic-primitive" ;
vc:sourceDomain "blockchain" .
ngm:bc-defi-and-economics a owl:Class ;
a skos:Concept ;
rdfs:comment "Taxonomy category grouping decentralised finance protocols and blockchain-native economic mechanisms, including automated market makers, liquidity pools, yield farming, stablecoins, tokenisation, DAOs, and the incentive structures that govern on-chain economies."@en ;
rdfs:label "DeFi and Economics"@en ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf _:r22733 ;
rdfs:subClassOf _:r22734 ;
rdfs:subClassOf _:r22735 ;
rdfs:subClassOf _:r22736 ;
rdfs:subClassOf _:r22737 ;
rdfs:subClassOf _:r22738 ;
rdfs:subClassOf _:r22739 ;
rdfs:subClassOf _:r22740 ;
rdfs:subClassOf _:r22741 ;
rdfs:subClassOf _:r22742 ;
skos:broader ngm:blockchain ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:automated-market-maker ;
vc:hasPart ngm:blockchain-economics ;
vc:hasPart ngm:dao ;
vc:hasPart ngm:decentralized-exchange ;
vc:hasPart ngm:decentralized-finance-de-fi ;
vc:hasPart ngm:digital-asset-lending ;
vc:hasPart ngm:liquidity-pool ;
vc:hasPart ngm:stablecoin ;
vc:hasPart ngm:tokenization ;
vc:hasPart ngm:yield-farming ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:bc-protocol-and-consensus ;
vc:relatedTo ngm:blockchain-governance ;
vc:relatedTo ngm:smart-contract ;
vc:slug "bc-defi-and-economics" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:cryptographic-commitment ;
vc:uses ngm:incentive-alignment .
ngm:bc-governance-and-regulation a owl:Class ;
a skos:Concept ;
rdfs:comment "Taxonomy hub covering the legal, policy, and organisational frameworks that govern blockchain and distributed ledger deployments. This category spans compliance obligations, decentralised governance mechanisms, regulatory technology, and the evolving global ruleset for digital assets and smart contracts."@en ;
rdfs:label "Governance and Regulation"@en ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf _:r22743 ;
rdfs:subClassOf _:r22744 ;
rdfs:subClassOf _:r22745 ;
rdfs:subClassOf _:r22746 ;
rdfs:subClassOf _:r22747 ;
rdfs:subClassOf _:r22748 ;
rdfs:subClassOf _:r22749 ;
rdfs:subClassOf _:r22750 ;
rdfs:subClassOf _:r22751 ;
skos:broader ngm:blockchain ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:aml-kyc-compliance ;
vc:hasPart ngm:blockchain-compliance ;
vc:hasPart ngm:blockchain-governance ;
vc:hasPart ngm:dao ;
vc:hasPart ngm:financial-regulation ;
vc:hasPart ngm:regulatory-compliance ;
vc:hasPart ngm:regulatory-framework ;
vc:hasPart ngm:securities-regulation ;
vc:hasPart ngm:smart-contract ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:bc-defi-and-economics ;
vc:relatedTo ngm:bc-protocol-and-consensus ;
vc:relatedTo ngm:regulatory-technology ;
vc:slug "bc-governance-and-regulation" ;
vc:sourceDomain "blockchain" .
ngm:bc-network-component a owl:Class ;
a skos:Concept ;
rdfs:comment "Taxonomy hub for the node and network-layer components of a blockchain system. Network components are the participant entities and communication infrastructure through which blocks and transactions are propagated, validated, and stored across a distributed ledger."@en ;
rdfs:label "Network Component (Blockchain)"@en ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf _:r22752 ;
rdfs:subClassOf _:r22753 ;
rdfs:subClassOf _:r22754 ;
rdfs:subClassOf _:r22755 ;
rdfs:subClassOf _:r22756 ;
rdfs:subClassOf _:r22757 ;
skos:broader ngm:blockchain ;
vc:enables ngm:block-propagation ;
vc:enables ngm:consensus-mechanism ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:archival-node ;
vc:hasPart ngm:bootstrap-node ;
vc:hasPart ngm:full-node ;
vc:hasPart ngm:light-node ;
vc:hasPart ngm:mempool ;
vc:hasPart ngm:validator-node ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:blockchain-network ;
vc:relatedTo ngm:gossip-protocol ;
vc:relatedTo ngm:peer-to-peer-network ;
vc:slug "bc-network-component" ;
vc:sourceDomain "blockchain" .
ngm:bc-protocol-and-consensus a owl:Class ;
a skos:Concept ;
rdfs:comment "Taxonomy category grouping all protocol-level and consensus-layer concepts within the blockchain domain, including proof-of-work and proof-of-stake variants, Byzantine fault-tolerant algorithms, finality models, and the rules governing block production and chain selection."@en ;
rdfs:label "Protocol and Consensus"@en ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf _:r22758 ;
rdfs:subClassOf _:r22759 ;
rdfs:subClassOf _:r22760 ;
rdfs:subClassOf _:r22761 ;
rdfs:subClassOf _:r22762 ;
rdfs:subClassOf _:r22763 ;
rdfs:subClassOf _:r22764 ;
rdfs:subClassOf _:r22765 ;
rdfs:subClassOf _:r22766 ;
rdfs:subClassOf _:r22767 ;
skos:broader ngm:blockchain ;
vc:enables ngm:distributed-ledger-technology ;
vc:enables ngm:immutability ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:byzantine-fault-tolerance ;
vc:hasPart ngm:consensus-algorithm ;
vc:hasPart ngm:consensus-mechanism ;
vc:hasPart ngm:delegated-proof-of-stake ;
vc:hasPart ngm:finality ;
vc:hasPart ngm:nakamoto-consensus ;
vc:hasPart ngm:proof-of-stake ;
vc:hasPart ngm:proof-of-work ;
vc:hasPart ngm:pure-proof-of-stake ;
vc:hasPart ngm:utxo-model ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:bc-defi-and-economics ;
vc:relatedTo ngm:blockchain-governance ;
vc:relatedTo ngm:blockchain-scalability ;
vc:slug "bc-protocol-and-consensus" ;
vc:sourceDomain "blockchain" .
ngm:bc-token-and-asset a owl:Class ;
a skos:Concept ;
rdfs:comment "Taxonomy hub for blockchain-based digital tokens and on-chain asset representations. Covers fungible tokens, non-fungible tokens, stablecoins, security tokens, governance tokens, and the standards and mechanisms by which digital value is issued, transferred, and managed on distributed ledgers."@en ;
rdfs:label "Token and Asset"@en ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf _:r22768 ;
rdfs:subClassOf _:r22769 ;
rdfs:subClassOf _:r22770 ;
rdfs:subClassOf _:r22771 ;
rdfs:subClassOf _:r22772 ;
rdfs:subClassOf _:r22773 ;
rdfs:subClassOf _:r22774 ;
skos:broader ngm:blockchain ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:cryptocurrency ;
vc:hasPart ngm:fungible-token ;
vc:hasPart ngm:governance-token ;
vc:hasPart ngm:nft ;
vc:hasPart ngm:security-token ;
vc:hasPart ngm:stablecoin ;
vc:hasPart ngm:utility-token ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:asset-tokenisation ;
vc:relatedTo ngm:digital-asset ;
vc:relatedTo ngm:erc-20-token-standard ;
vc:relatedTo ngm:erc-721-standard ;
vc:slug "bc-token-and-asset" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:blockchain-transaction .
ngm:bci-society a skos:Concept ;
rdfs:label "Bci Society"@en .
ngm:bdd100k a skos:Concept ;
rdfs:label "Bdd100k"@en .
ngm:bdi-agent-architecture a skos:Concept ;
rdfs:label "Bdi Agent Architecture"@en .
ngm:bdi-architecture a skos:Concept ;
rdfs:label "Bdi Architecture"@en .
ngm:bdi-model a owl:Class ;
rdfs:comment "A deliberative agent architecture grounded in Bratman's theory of practical reasoning, structuring agent cognition around Beliefs (knowledge about the world), Desires (motivational goals), and Intentions (committed plans), with a reasoning cycle of belief revision, deliberation, means-end reasoning, and intention reconsideration."@en ;
rdfs:label "BDI Model"@en ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf _:r2593 ;
rdfs:subClassOf _:r2594 ;
skos:broader ngm:ai-research-area ;
skos:broader ngm:artificial-intelligence ;
vc:enables ngm:ai-agent-system ;
vc:enables ngm:autonomy-level ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:agent ;
vc:hasPart ngm:goal ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:human-in-the-loop ;
vc:relatedTo ngm:objective ;
vc:slug "bdi-model" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:artificial-intelligence .
ngm:beacon-chain a owl:Class ;
rdfs:comment "The Beacon Chain is the proof-of-stake consensus backbone introduced to Ethereum that coordinates validators, manages staking, and finalises blocks. It organises time into slots and epochs, assigns block-proposal and attestation duties, and applies a finality gadget that locks in the canonical chain. The Beacon Chain decouples consensus from execution, providing the security and randomness that the broader sharded and execution layers build upon."@en ;
rdfs:label "Beacon Chain"@en ;
rdfs:subClassOf ngm:consensus-layer ;
rdfs:subClassOf _:r2859 ;
rdfs:subClassOf _:r2860 ;
rdfs:subClassOf _:r2861 ;
rdfs:subClassOf _:r2862 ;
rdfs:subClassOf _:r2863 ;
rdfs:subClassOf _:r2864 ;
vc:dependsOn ngm:consensus-mechanism ;
vc:dependsOn ngm:staking ;
vc:enables ngm:finality ;
vc:enables ngm:sharding ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:attestation ;
vc:hasPart ngm:epoch ;
vc:hasPart ngm:validator ;
vc:implements ngm:consensus-mechanism ;
vc:implements ngm:proof-of-stake ;
vc:isPartOf ngm:consensus-layer ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:ethereum ;
vc:relatedTo ngm:finality ;
vc:relatedTo ngm:sharding ;
vc:requires ngm:proof-of-stake ;
vc:requires ngm:staking ;
vc:requires ngm:validator ;
vc:slug "beacon-chain" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:consensus-layer ;
vc:supports ngm:ethereum ;
vc:uses ngm:attestation ;
vc:uses ngm:block-proposal .
ngm:bead-adapter a skos:Concept ;
rdfs:label "Bead Adapter"@en .
ngm:beam-footprint a owl:Class ;
rdfs:label "Beam Footprint"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:satellite-communication ;
vc:slug "beam-footprint" ;
vc:sourceDomain "space-science-and-systems" .
ngm:beam-handover a owl:Class ;
rdfs:label "Beam Handover"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:satellite-communication ;
vc:slug "beam-handover" ;
vc:sourceDomain "space-science-and-systems" .
ngm:beam-search a owl:Class ;
rdfs:comment "Beam search is a heuristic search algorithm that explores a graph by expanding the most promising nodes within a fixed-width frontier, called the beam, at each step. In sequence generation tasks it retains the top-k candidate sequences at each decoding step rather than pursuing a single greedy choice, balancing exploration against computational cost."@en ;
rdfs:label "Beam Search"@en ;
rdfs:subClassOf ngm:heuristic-methods ;
rdfs:subClassOf ngm:natural-language-processing ;
rdfs:subClassOf ngm:search-algorithm ;
rdfs:subClassOf ngm:sequence-to-sequence-learning ;
rdfs:subClassOf _:r2876 ;
rdfs:subClassOf _:r2877 ;
rdfs:subClassOf _:r2878 ;
rdfs:subClassOf _:r2879 ;
rdfs:subClassOf _:r2880 ;
rdfs:subClassOf _:r2881 ;
rdfs:subClassOf _:r2882 ;
rdfs:subClassOf _:r2883 ;
rdfs:subClassOf _:r2884 ;
vc:bridgesTo ngm:natural-language-processing ;
vc:bridgesTo ngm:robotics ;
vc:contrastsWith ngm:greedy-decoding ;
vc:contrastsWith ngm:monte-carlo-tree-search ;
vc:contrastsWith ngm:nucleus-sampling ;
vc:contrastsWith ngm:sampling ;
vc:contrastsWith ngm:speculative-decoding ;
vc:contrastsWith ngm:viterbi-algorithm ;
vc:dependsOn ngm:attention-mechanism ;
vc:dependsOn ngm:dynamic-programming ;
vc:dependsOn ngm:encoder-decoder-architecture ;
vc:dependsOn ngm:log-probability ;
vc:dependsOn ngm:probability-distribution ;
vc:dependsOn ngm:transformer-architecture ;
vc:enables ngm:code-generation ;
vc:enables ngm:image-captioning ;
vc:enables ngm:machine-translation ;
vc:enables ngm:natural-language-generation ;
vc:enables ngm:natural-language-processing ;
vc:enables ngm:open-ended-generation ;
vc:enables ngm:question-answering ;
vc:enables ngm:sequence-to-sequence-learning ;
vc:enables ngm:speech-recognition ;
vc:enables ngm:text-generation ;
vc:enables ngm:text-summarisation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:constrained-decoding ;
vc:hasPart ngm:coverage-penalty ;
vc:hasPart ngm:diverse-beam-search ;
vc:hasPart ngm:kv-cache ;
vc:hasPart ngm:length-normalisation ;
vc:hasPart ngm:log-probability ;
vc:implements ngm:autoregressive-model ;
vc:implements ngm:breadth-first-search ;
vc:implements ngm:dynamic-programming ;
vc:implements ngm:heuristic-methods ;
vc:implements ngm:search-algorithm ;
vc:qualityScore "0.95"^^xsd:float ;
vc:relatedTo ngm:beam-search-decoding ;
vc:relatedTo ngm:constrained-decoding ;
vc:relatedTo ngm:coverage-penalty ;
vc:relatedTo ngm:diverse-beam-search ;
vc:relatedTo ngm:exposure-bias ;
vc:relatedTo ngm:inference-time-compute ;
vc:relatedTo ngm:large-language-model-training ;
vc:relatedTo ngm:process-reward-model ;
vc:relatedTo ngm:speculative-decoding ;
vc:relatedTo ngm:viterbi-algorithm ;
vc:requires ngm:autoregressive-model ;
vc:requires ngm:language-model ;
vc:requires ngm:probability-distribution ;
vc:requires ngm:sequence-model ;
vc:requires ngm:vocabulary ;
vc:slug "beam-search" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:natural-language-processing ;
vc:standardizedBy ngm:search-algorithm ;
vc:standardizedBy ngm:sequence-to-sequence-learning ;
vc:supports ngm:autoregressive-model ;
vc:supports ngm:inference-compute ;
vc:supports ngm:large-language-models ;
vc:supports ngm:natural-language-processing ;
vc:supports ngm:process-reward-model ;
vc:supports ngm:robotics ;
vc:uses ngm:attention-mechanism ;
vc:uses ngm:encoder-decoder-architecture ;
vc:uses ngm:heuristic-methods ;
vc:uses ngm:kv-cache ;
vc:uses ngm:language-model ;
vc:uses ngm:length-normalisation ;
vc:uses ngm:log-probability ;
vc:uses ngm:probability-distribution ;
vc:uses ngm:transformer-architecture ;
vc:uses ngm:vocabulary .
ngm:beam-search-decoding a owl:Class ;
rdfs:comment "Beam search decoding is the application of the beam search algorithm specifically to the inference phase of neural sequence-to-sequence and autoregressive language models, where token-by-token predictions are generated by retaining the k highest-scoring partial sequences at each step. It serves as the primary decoding strategy for tasks requiring high-fidelity, deterministic outputs such as translation, summarisation, and structured text generation."@en ;
rdfs:label "Beam Search Decoding"@en ;
rdfs:subClassOf ngm:autoregressive-model ;
rdfs:subClassOf ngm:beam-search ;
rdfs:subClassOf ngm:natural-language-processing ;
rdfs:subClassOf ngm:sequence-to-sequence-learning ;
rdfs:subClassOf _:r2865 ;
rdfs:subClassOf _:r2866 ;
rdfs:subClassOf _:r2867 ;
rdfs:subClassOf _:r2868 ;
rdfs:subClassOf _:r2869 ;
rdfs:subClassOf _:r2870 ;
rdfs:subClassOf _:r2871 ;
rdfs:subClassOf _:r2872 ;
rdfs:subClassOf _:r2873 ;
rdfs:subClassOf _:r2874 ;
rdfs:subClassOf _:r2875 ;
vc:contrastsWith ngm:diverse-beam-search ;
vc:contrastsWith ngm:greedy-decoding ;
vc:contrastsWith ngm:monte-carlo-tree-search ;
vc:contrastsWith ngm:nucleus-sampling ;
vc:contrastsWith ngm:sampling ;
vc:contrastsWith ngm:speculative-decoding ;
vc:dependsOn ngm:attention-mechanism ;
vc:dependsOn ngm:beam-search ;
vc:dependsOn ngm:dynamic-programming ;
vc:dependsOn ngm:encoder-decoder-architecture ;
vc:dependsOn ngm:large-language-model-training ;
vc:dependsOn ngm:log-probability ;
vc:dependsOn ngm:transformer-architecture ;
vc:enables ngm:code-generation ;
vc:enables ngm:formal-verification ;
vc:enables ngm:image-captioning ;
vc:enables ngm:machine-translation ;
vc:enables ngm:natural-language-generation ;
vc:enables ngm:open-ended-generation ;
vc:enables ngm:question-answering ;
vc:enables ngm:speech-recognition ;
vc:enables ngm:text-generation ;
vc:enables ngm:text-summarisation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:constrained-decoding ;
vc:hasPart ngm:coverage-penalty ;
vc:hasPart ngm:diverse-beam-search ;
vc:hasPart ngm:kv-cache ;
vc:hasPart ngm:length-normalisation ;
vc:hasPart ngm:log-probability ;
vc:hasPart ngm:vocabulary ;
vc:implements ngm:autoregressive-model ;
vc:implements ngm:beam-search ;
vc:implements ngm:natural-language-generation ;
vc:implements ngm:sequence-to-sequence-learning ;
vc:qualityScore "0.95"^^xsd:float ;
vc:relatedTo ngm:constrained-decoding ;
vc:relatedTo ngm:coverage-penalty ;
vc:relatedTo ngm:exposure-bias ;
vc:relatedTo ngm:inference-time-compute ;
vc:relatedTo ngm:large-language-model-training ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:process-reward-model ;
vc:relatedTo ngm:sampling ;
vc:relatedTo ngm:speculative-decoding ;
vc:relatedTo ngm:viterbi-algorithm ;
vc:requires ngm:autoregressive-model ;
vc:requires ngm:beam-search ;
vc:requires ngm:language-model ;
vc:requires ngm:probability-distribution ;
vc:requires ngm:sequence-model ;
vc:requires ngm:vocabulary ;
vc:slug "beam-search-decoding" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:beam-search ;
vc:standardizedBy ngm:natural-language-processing ;
vc:standardizedBy ngm:sequence-to-sequence-learning ;
vc:supports ngm:inference-compute ;
vc:supports ngm:large-language-models ;
vc:supports ngm:natural-language-processing ;
vc:supports ngm:process-reward-model ;
vc:supports ngm:robotics ;
vc:supports ngm:sequence-to-sequence-learning ;
vc:uses ngm:attention-mechanism ;
vc:uses ngm:encoder-decoder-architecture ;
vc:uses ngm:heuristic-methods ;
vc:uses ngm:kv-cache ;
vc:uses ngm:language-model ;
vc:uses ngm:large-language-models ;
vc:uses ngm:length-normalisation ;
vc:uses ngm:log-probability ;
vc:uses ngm:probability-distribution ;
vc:uses ngm:transformer-architecture ;
vc:uses ngm:vocabulary .
ngm:beamforming a owl:Class ;
rdfs:comment "Beamforming is a signal processing technique that combines the outputs of an antenna or sensor array with calculated phase and amplitude weightings to steer transmission or reception toward a specific spatial direction. It increases signal gain toward intended targets while suppressing interference from other directions, without physically moving the array. Beamforming is central to modern wireless communication standards and to radar systems that must resolve direction as well as range."@en ;
rdfs:label "Beamforming"@en ;
rdfs:subClassOf ngm:wireless-communication ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "beamforming" ;
vc:sourceDomain "infrastructure" .
ngm:bearer-token a owl:Class ;
rdfs:comment "A bearer token is a security credential that grants access to a protected resource to any party that presents it, without requiring the holder to prove possession of an associated cryptographic key. Commonly issued by authorisation servers and transmitted in an HTTP Authorization header, it is simple to use but must be protected in transit and at rest because anyone who obtains it can use it. Bearer tokens are central to modern API authorisation flows such as OAuth."@en ;
rdfs:label "Bearer Token"@en ;
rdfs:subClassOf ngm:token ;
rdfs:subClassOf _:r2885 ;
vc:bridgesTo ngm:identity ;
vc:contrastsWith ngm:cryptography ;
vc:dependsOn ngm:authorization ;
vc:enables ngm:api ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:authorization ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:authentication ;
vc:relatedTo ngm:identity ;
vc:relatedTo ngm:oauth ;
vc:relatedTo ngm:token ;
vc:requires ngm:tls ;
vc:slug "bearer-token" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:standards ;
vc:supports ngm:authentication ;
vc:uses ngm:oauth ;
vc:uses ngm:tls .
ngm:bearer-token-model a skos:Concept ;
rdfs:label "Bearer Token Model"@en .
ngm:bearer-token-transfer a skos:Concept ;
rdfs:label "Bearer Token Transfer"@en .
ngm:bearer-tokens a skos:Concept ;
rdfs:label "Bearer Tokens"@en .
ngm:bearing a skos:Concept ;
rdfs:label "Bearing"@en .
ngm:bearings a skos:Concept ;
rdfs:label "Bearings"@en .
ngm:beginner-friendly-deep-learning a skos:Concept ;
rdfs:label "Beginner Friendly Deep Learning"@en .
ngm:behavior-analysis a owl:Class ;
rdfs:comment "Behavior Analysis is an AI and machine learning technique concerned with the systematic observation, modelling, and interpretation of patterns in entity actions — whether human users, software agents, or autonomous systems — in order to detect anomalies, predict future actions, or classify intent. It combines statistical modelling, sequence analysis, and supervised or unsupervised learning to extract actionable intelligence from behavioural streams. Typical applications include cybersecurity threat detection, user experience optimisation, game AI design, and fraud prevention."@en ;
rdfs:label "Behavior Analysis"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf _:r2886 ;
rdfs:subClassOf _:r2887 ;
rdfs:subClassOf _:r2888 ;
rdfs:subClassOf _:r2889 ;
rdfs:subClassOf _:r2890 ;
rdfs:subClassOf _:r2891 ;
skos:broader ngm:ai-technique ;
vc:enables ngm:fraud-detection ;
vc:enables ngm:predictive-analytics ;
vc:enables ngm:predictive-personalization ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:anomaly-detection ;
vc:hasPart ngm:behavioral-modeling ;
vc:hasPart ngm:behavioural-analytics ;
vc:hasPart ngm:pattern-recognition ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:behavioral-learning ;
vc:relatedTo ngm:cybersecurity ;
vc:relatedTo ngm:explainability ;
vc:relatedTo ngm:interpretability ;
vc:relatedTo ngm:knowledge-graph ;
vc:relatedTo ngm:user-experience ;
vc:requires ngm:data-analytics ;
vc:requires ngm:supervised-learning ;
vc:slug "behavior-analysis" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:avatar-behavior ;
vc:uses ngm:deep-learning ;
vc:uses ngm:neural-network ;
vc:uses ngm:reinforcement-learning .
ngm:behavior-analytics a skos:Concept ;
rdfs:label "Behavior Analytics"@en .
ngm:behavior-controller a skos:Concept ;
rdfs:label "Behavior Controller"@en .
ngm:behavior-mapping a skos:Concept ;
rdfs:label "Behavior Mapping"@en .
ngm:behavioral-adaptation a skos:Concept ;
rdfs:label "Behavioral Adaptation"@en .
ngm:behavioral-data a skos:Concept ;
rdfs:label "Behavioral Data"@en .
ngm:behavioral-data-aggregator a skos:Concept ;
rdfs:label "Behavioral Data Aggregator"@en .
ngm:behavioral-futures-markets a skos:Concept ;
rdfs:label "Behavioral Futures Markets"@en .
ngm:behavioral-learning a owl:Class ;
rdfs:comment "An AI-driven approach that analyzes and predicts user behavior patterns from digital interactions including clicks, browsing patterns, movement trajectories, and gaze tracking, enabling automated decision-making and personalized experiences through machine learning and pattern recognition."@en ;
rdfs:label "Behavioral Learning"@en ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf ngm:sc-content-and-assets ;
rdfs:subClassOf _:r2892 ;
rdfs:subClassOf _:r2893 ;
rdfs:subClassOf _:r2894 ;
skos:broader ngm:sc-content-and-assets ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:enables ngm:personalization ;
vc:enables ngm:predictive-analytics ;
vc:enables ngm:user-experience-optimization ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:data-collection ;
vc:requires ngm:machine-learning-discipline-models ;
vc:requires ngm:pattern-recognition ;
vc:slug "behavioral-learning" ;
vc:sourceDomain "spatial-computing" .
ngm:behavioral-modeling a owl:Class ;
rdfs:comment "Behavioral Modeling is the application of machine learning and statistical methods to represent, predict, and simulate how agents (humans, robots, or software entities) act under varying conditions. It underpins applications ranging from user-behaviour analytics and fraud detection to reinforcement learning policies and autonomous agent control."@en ;
rdfs:label "Behavioral Modeling"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf ngm:predictive-analytics ;
rdfs:subClassOf _:r2895 ;
rdfs:subClassOf _:r2896 ;
rdfs:subClassOf _:r2897 ;
rdfs:subClassOf _:r2898 ;
rdfs:subClassOf _:r2899 ;
rdfs:subClassOf _:r2900 ;
rdfs:subClassOf _:r2901 ;
rdfs:subClassOf _:r2902 ;
rdfs:subClassOf _:r2903 ;
rdfs:subClassOf _:r2904 ;
rdfs:subClassOf _:r2905 ;
rdfs:subClassOf _:r2906 ;
rdfs:subClassOf _:r2907 ;
rdfs:subClassOf _:r2908 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:avatar-behavior ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:embodied-ai-simulation ;
vc:contrastsWith ngm:expert-systems ;
vc:contrastsWith ngm:rule-based-systems ;
vc:contrastsWith ngm:scripted-behaviour ;
vc:contrastsWith ngm:symbolic-ai ;
vc:dependsOn ngm:data-collection ;
vc:dependsOn ngm:environment-model ;
vc:dependsOn ngm:feature-engineering ;
vc:dependsOn ngm:reward-function ;
vc:dependsOn ngm:sensor-data ;
vc:dependsOn ngm:training-data ;
vc:enables ngm:autonomous-agent ;
vc:enables ngm:autonomous-driving ;
vc:enables ngm:digital-twin ;
vc:enables ngm:fraud-detection ;
vc:enables ngm:human-computer-interaction ;
vc:enables ngm:non-player-character ;
vc:enables ngm:predictive-policing ;
vc:enables ngm:robotics ;
vc:enables ngm:social-simulation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:anomaly-detection ;
vc:hasPart ngm:behavior-analysis ;
vc:hasPart ngm:behaviour-tree ;
vc:hasPart ngm:behavioural-analytics ;
vc:hasPart ngm:imitation-learning ;
vc:hasPart ngm:pattern-recognition ;
vc:hasPart ngm:policy-learning ;
vc:hasPart ngm:reward-modelling ;
vc:hasPart ngm:state-space-representation ;
vc:hasPart ngm:value-function ;
vc:implements ngm:behaviour-tree ;
vc:implements ngm:deep-q-network ;
vc:implements ngm:finite-state-machine ;
vc:implements ngm:hidden-markov-model ;
vc:implements ngm:markov-decision-process ;
vc:implements ngm:partially-observable-markov-decision-process ;
vc:isPartOf ngm:artificial-intelligence ;
vc:isPartOf ngm:predictive-analytics ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:agent-based-simulation ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:behavioural-analytics ;
vc:relatedTo ngm:cognitive-architecture ;
vc:relatedTo ngm:digital-twin ;
vc:relatedTo ngm:embodied-ai ;
vc:relatedTo ngm:foundation-model ;
vc:relatedTo ngm:meta-learning ;
vc:relatedTo ngm:multi-agent-system ;
vc:relatedTo ngm:reinforcement-learning ;
vc:relatedTo ngm:transfer-learning ;
vc:requires ngm:feature-engineering ;
vc:requires ngm:reward-signal ;
vc:requires ngm:simulation-environment ;
vc:requires ngm:state-space-representation ;
vc:requires ngm:training-data ;
vc:slug "behavioral-modeling" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:iso-42001 ;
vc:standardizedBy ngm:mitre-atlas ;
vc:standardizedBy ngm:mu-jo-co ;
vc:standardizedBy ngm:openai-research-organisation ;
vc:supports ngm:behavioural-analytics ;
vc:supports ngm:cybersecurity ;
vc:supports ngm:extended-reality ;
vc:supports ngm:game-ai ;
vc:supports ngm:human-computer-interaction ;
vc:supports ngm:robotics ;
vc:supports ngm:simulation ;
vc:uses ngm:deep-learning ;
vc:uses ngm:gaussian-mixture-model ;
vc:uses ngm:graph-neural-network ;
vc:uses ngm:hidden-markov-model ;
vc:uses ngm:large-language-model ;
vc:uses ngm:lstm ;
vc:uses ngm:machine-learning-model ;
vc:uses ngm:markov-decision-process ;
vc:uses ngm:reinforcement-learning ;
vc:uses ngm:statistical-model ;
vc:uses ngm:transformer-architecture .
ngm:behavioral-models a skos:Concept ;
rdfs:label "Behavioral Models"@en .
ngm:behavioral-pattern a skos:Concept ;
rdfs:label "Behavioral Pattern"@en .
ngm:behavioral-pattern-data a skos:Concept ;
rdfs:label "Behavioral Pattern Data"@en .
ngm:behavioral-surplus a skos:Concept ;
rdfs:label "Behavioral Surplus"@en .
ngm:behavioral-tracking-system a skos:Concept ;
rdfs:label "Behavioral Tracking System"@en .
ngm:behaviortree-cpp a skos:Concept ;
rdfs:label "Behaviortree Cpp"@en .
ngm:behaviour-based-robotics a skos:Concept ;
rdfs:label "Behaviour Based Robotics"@en .
ngm:behaviour-cloning a skos:Concept ;
rdfs:label "Behaviour Cloning"@en .
ngm:behaviour-prediction a skos:Concept ;
rdfs:label "Behaviour Prediction"@en .
ngm:behaviour-tree a owl:Class ;
rdfs:comment "A Behaviour Tree (BT) is a hierarchical, directed acyclic graph structure used to model the decision-making logic of autonomous agents, non-player characters (NPCs), and robots. Internal nodes represent control-flow composites — Sequence, Selector, Parallel, and Decorator — while leaf nodes represent atomic Actions or Conditions; execution propagates through the tree and each node returns Success, Failure, or Running to its parent. Behaviour Trees superseded Finite State Machines (FSMs) in many game and robotics contexts because they offer superior modularity, reusability, and comprehensibility: sub-trees encapsulate coherent behaviours that can be composed without explicit inter-state transition wiring. First popularised in the game-development community circa 2005 and later formalised in robotics frameworks such as BehaviorTree.CPP, BTs are now a standard control architecture in both real-time interactive media and autonomous robotic systems."@en ;
rdfs:label "Behaviour Tree"@en ;
rdfs:subClassOf ngm:agent-architecture ;
rdfs:subClassOf ngm:automated-planning ;
rdfs:subClassOf ngm:control-architecture ;
rdfs:subClassOf ngm:decision-making ;
rdfs:subClassOf ngm:reactive-systems ;
rdfs:subClassOf ngm:robo-navigation-and-planning ;
rdfs:subClassOf _:r2909 ;
rdfs:subClassOf _:r2910 ;
rdfs:subClassOf _:r2911 ;
rdfs:subClassOf _:r2912 ;
skos:broader ngm:robo-navigation-and-planning ;
vc:bridgesTo ngm:agentic-ai ;
vc:bridgesTo ngm:explainable-ai ;
vc:bridgesTo ngm:large-language-model ;
vc:bridgesTo ngm:reinforcement-learning ;
vc:bridgesTo ngm:robotics ;
vc:bridgesTo ngm:spatial-computing ;
vc:contrastsWith ngm:belief-desire-intention ;
vc:contrastsWith ngm:decision-tree ;
vc:contrastsWith ngm:finite-state-machine ;
vc:contrastsWith ngm:hierarchical-task-network ;
vc:contrastsWith ngm:state-machine ;
vc:contrastsWith ngm:subsumption-architecture ;
vc:contrastsWith ngm:teleo-reactive-program ;
vc:dependsOn ngm:motion-planning ;
vc:dependsOn ngm:pathfinding-algorithm ;
vc:dependsOn ngm:sensor-input ;
vc:dependsOn ngm:task-and-motion-planning ;
vc:dependsOn ngm:world-model ;
vc:enables ngm:ai-game-agent ;
vc:enables ngm:autonomous-agent ;
vc:enables ngm:concurrent-task-execution ;
vc:enables ngm:intelligent-npc ;
vc:enables ngm:mission-execution ;
vc:enables ngm:npc-interaction ;
vc:enables ngm:recovery-behaviour ;
vc:enables ngm:robot-navigation ;
vc:enables ngm:task-execution ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:action-node ;
vc:hasPart ngm:blackboard ;
vc:hasPart ngm:condition-node ;
vc:hasPart ngm:decorator-node ;
vc:hasPart ngm:parallel-node ;
vc:hasPart ngm:port-system ;
vc:hasPart ngm:selector-node ;
vc:hasPart ngm:sequence-node ;
vc:hasPart ngm:tick-loop ;
vc:implements ngm:asynchronous-execution ;
vc:implements ngm:hierarchical-task-decomposition ;
vc:implements ngm:interrupt-driven-control ;
vc:implements ngm:modular-behaviour-composition ;
vc:implements ngm:reactive-control ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:ai-game-agent ;
vc:relatedTo ngm:automated-planning ;
vc:relatedTo ngm:belief-desire-intention ;
vc:relatedTo ngm:cognitive-architecture ;
vc:relatedTo ngm:formal-verification ;
vc:relatedTo ngm:imitation-learning ;
vc:relatedTo ngm:intelligent-npc ;
vc:relatedTo ngm:multi-agent-system ;
vc:relatedTo ngm:nav2 ;
vc:relatedTo ngm:reinforcement-learning ;
vc:relatedTo ngm:teleo-reactive-program ;
vc:requires ngm:blackboard ;
vc:requires ngm:sensor-input ;
vc:requires ngm:state-space ;
vc:requires ngm:task-planning ;
vc:requires ngm:tick-loop ;
vc:requires ngm:world-model ;
vc:slug "behaviour-tree" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:behaviortree-cpp ;
vc:standardizedBy ngm:nav2 ;
vc:standardizedBy ngm:py-trees ;
vc:standardizedBy ngm:unreal-engine-ai ;
vc:supports ngm:autonomous-driving ;
vc:supports ngm:game-development ;
vc:supports ngm:game-engine ;
vc:supports ngm:human-robot-interaction ;
vc:supports ngm:manufacturing-automation ;
vc:supports ngm:ros ;
vc:supports ngm:spatial-computing ;
vc:supports ngm:swarm-robotics ;
vc:uses ngm:ai-agents ;
vc:uses ngm:blackboard ;
vc:uses ngm:goal-oriented-action-planning ;
vc:uses ngm:motion-planning ;
vc:uses ngm:pathfinding-algorithm ;
vc:uses ngm:pddl ;
vc:uses ngm:perception-module .
ngm:behaviour-trees a owl:Class ;
rdfs:comment "Behaviour trees are a model for organising the decision logic of autonomous agents and robots into a tree of tasks and control nodes. They are used in robotics and game artificial intelligence."@en ;
rdfs:label "Behaviour Trees"@en ;
rdfs:subClassOf ngm:robot-control ;
vc:bridgesTo ngm:behaviour-tree ;
vc:enables ngm:task-and-motion-planning ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:slug "behaviour-trees" ;
vc:sourceDomain "robotics" .
ngm:behavioural-ai a skos:Concept ;
rdfs:label "Behavioural AI"@en .
ngm:behavioural-analytics a owl:Class ;
rdfs:comment "Behavioural analytics is the security and analytics discipline that establishes baseline patterns of user, device and entity activity and detects meaningful deviations that may indicate threats, fraud or compromise. It applies statistical modelling and machine learning to telemetry such as login times, access sequences and transaction behaviour to surface anomalies that signature-based controls miss. The approach underpins user and entity behaviour analytics (UEBA) within modern security operations."@en ;
rdfs:label "Behavioural Analytics"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf ngm:security ;
rdfs:subClassOf _:r2913 ;
rdfs:subClassOf _:r2914 ;
rdfs:subClassOf _:r2915 ;
rdfs:subClassOf _:r2916 ;
rdfs:subClassOf _:r2917 ;
rdfs:subClassOf _:r2918 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:finance ;
vc:bridgesTo ngm:security ;
vc:contrastsWith ngm:rule-based-systems ;
vc:contrastsWith ngm:threat-detection ;
vc:dependsOn ngm:data-pipeline ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:siem ;
vc:dependsOn ngm:stream-processing ;
vc:enables ngm:cybersecurity ;
vc:enables ngm:data-analytics ;
vc:enables ngm:fraud-detection ;
vc:enables ngm:incident-response ;
vc:enables ngm:personalisation ;
vc:enables ngm:recommendation-system ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:anomaly-detection ;
vc:hasPart ngm:threat-detection ;
vc:hasPart ngm:user-profiling ;
vc:isPartOf ngm:cybersecurity ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:access-control ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:digital-twin ;
vc:relatedTo ngm:federated-learning ;
vc:relatedTo ngm:intrusion-detection-system ;
vc:relatedTo ngm:neural-network ;
vc:relatedTo ngm:privacy-preserving-machine-learning ;
vc:relatedTo ngm:user-and-entity-behaviour-analytics ;
vc:requires ngm:data-collection ;
vc:requires ngm:feature-engineering ;
vc:requires ngm:monitoring ;
vc:slug "behavioural-analytics" ;
vc:sourceDomain "security" ;
vc:supports ngm:risk-assessment ;
vc:uses ngm:anomaly-detection ;
vc:uses ngm:data-analytics ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:pattern-recognition ;
vc:uses ngm:predictive-analytics ;
vc:uses ngm:statistical-modelling ;
vc:uses ngm:time-series-analysis .
ngm:behavioural-biometrics a skos:Concept ;
rdfs:label "Behavioural Biometrics"@en .
ngm:behavioural-cloning a skos:Concept ;
rdfs:label "Behavioural Cloning"@en .
ngm:behavioural-economics a owl:Class ;
rdfs:comment "Behavioural economics is an interdisciplinary field that integrates insights from cognitive psychology and social science into economic modelling, documenting systematic ways in which human decision-making deviates from the predictions of classical rational-choice theory. It explains phenomena such as loss aversion, anchoring, present bias, and herd behaviour that standard utility maximisation models cannot account for."@en ;
rdfs:label "Behavioural Economics"@en ;
rdfs:subClassOf ngm:economics ;
rdfs:subClassOf _:r2919 ;
rdfs:subClassOf _:r2920 ;
vc:bridgesTo ngm:algorithmic-recommendation ;
vc:bridgesTo ngm:reinforcement-learning ;
vc:bridgesTo ngm:reward-modelling ;
vc:contrastsWith ngm:expected-utility-theory ;
vc:contrastsWith ngm:rational-choice-theory ;
vc:enables ngm:choice-architecture ;
vc:enables ngm:incentive-alignment ;
vc:enables ngm:mechanism-design ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:bounded-rationality ;
vc:hasPart ngm:loss-aversion ;
vc:hasPart ngm:nudge-theory ;
vc:hasPart ngm:present-bias ;
vc:hasPart ngm:prospect-theory ;
vc:isPartOf ngm:decision-science ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:behavioural-analytics ;
vc:relatedTo ngm:contract-theory ;
vc:relatedTo ngm:development-economics ;
vc:relatedTo ngm:game-theory ;
vc:relatedTo ngm:incentive-compatibility ;
vc:requires ngm:cognitive-psychology ;
vc:requires ngm:experimental-economics ;
vc:slug "behavioural-economics" ;
vc:sourceDomain "finance" ;
vc:uses ngm:behavioral-modeling ;
vc:uses ngm:heuristic-methods ;
vc:uses ngm:randomised-controlled-trial .
ngm:behavioural-feedback-loop a owl:Class ;
rdfs:comment "Recurring cycle where user actions influence environment responses which in turn modify subsequent user behavior through adaptive learning and reinforcement mechanisms."@en ;
rdfs:label "Behavioural Feedback Loop"@en ;
rdfs:subClassOf ngm:sc-interaction ;
rdfs:subClassOf _:r2921 ;
rdfs:subClassOf _:r2922 ;
rdfs:subClassOf _:r2923 ;
rdfs:subClassOf _:r2924 ;
rdfs:subClassOf _:r2925 ;
rdfs:subClassOf _:r2926 ;
skos:broader ngm:sc-interaction ;
vc:dependsOn ngm:affective-computing ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:user-modeling ;
vc:enables ngm:adaptive-virtual-experience ;
vc:enables ngm:behavioral-learning ;
vc:enables ngm:dynamic-adjustment ;
vc:enables ngm:personalized-interaction ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:action-recognition ;
vc:hasPart ngm:adaptive-reinforcement ;
vc:hasPart ngm:behavior-analysis ;
vc:hasPart ngm:environment-response ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:ai-model ;
vc:requires ngm:real-time-processing ;
vc:requires ngm:state-management ;
vc:requires ngm:user-tracking ;
vc:slug "behavioural-feedback-loop" ;
vc:sourceDomain "spatial-computing" .
ngm:behavioural-prediction a skos:Concept ;
rdfs:label "Behavioural Prediction"@en .
ngm:behavioural-science a skos:Concept ;
rdfs:label "Behavioural Science"@en .
ngm:behaviourism a owl:Class ;
rdfs:comment "A school of psychology and associated philosophy of mind holding that behaviour should be explained through observable stimulus–response relationships and learning histories rather than by appeal to inner mental states. Dominant from Watson's 1913 manifesto through Skinner's radical behaviourism of the mid-twentieth century, it produced the experimental analysis of classical and operant conditioning, was displaced as a general paradigm by the cognitive revolution, and survives today in applied behaviour analysis and in reinforcement learning's core concepts of reward-driven learning."@en ;
rdfs:label "Behaviourism"@en ;
rdfs:subClassOf ngm:psychology ;
vc:contrastsWith ngm:cognitive-psychology ;
vc:contrastsWith ngm:cognitive-science ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:philosophy-of-mind ;
vc:slug "behaviourism" ;
vc:sourceDomain "ai" .
ngm:behaviourist-drill-and-practice a skos:Concept ;
rdfs:label "Behaviourist Drill And Practice"@en .
ngm:behind-the-meter-generation a skos:Concept ;
rdfs:label "Behind The Meter Generation"@en .
ngm:beir a skos:Concept ;
rdfs:label "Beir"@en .
ngm:beir-benchmark a owl:Class ;
rdfs:comment "BEIR (Benchmarking IR) is a heterogeneous benchmark suite for evaluating the zero-shot generalisation of information retrieval models across eighteen diverse datasets spanning domains including biomedical, legal, financial, and Wikipedia text. It measures how well retrieval systems transfer across topic domains and retrieval task types without domain-specific fine-tuning, providing a standardised framework for comparing dense, sparse, and hybrid retrieval approaches."@en ;
rdfs:label "BEIR Benchmark"@en ;
rdfs:subClassOf ngm:benchmark-evaluation ;
rdfs:subClassOf ngm:evaluation-benchmarks-and-leaderboards ;
rdfs:subClassOf ngm:information-retrieval ;
rdfs:subClassOf ngm:natural-language-processing ;
vc:contrastsWith ngm:glue-benchmark ;
vc:contrastsWith ngm:ms-marco-benchmark ;
vc:contrastsWith ngm:squad ;
vc:contrastsWith ngm:triviaqa ;
vc:dependsOn ngm:bm25 ;
vc:dependsOn ngm:embedding-model ;
vc:dependsOn ngm:faiss ;
vc:dependsOn ngm:inverted-index ;
vc:dependsOn ngm:transformer ;
vc:enables ngm:cross-encoder-reranking ;
vc:enables ngm:dense-passage-retrieval ;
vc:enables ngm:hybrid-search ;
vc:enables ngm:retrieval-augmented-generation ;
vc:enables ngm:semantic-search ;
vc:enables ngm:zero-shot-generalisation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:arguana ;
vc:hasPart ngm:biomedical-trec ;
vc:hasPart ngm:climate-fever ;
vc:hasPart ngm:dbpedia-entity ;
vc:hasPart ngm:fever ;
vc:hasPart ngm:fiqa ;
vc:hasPart ngm:fiqa-2018 ;
vc:hasPart ngm:hotpotqa ;
vc:hasPart ngm:ms-marco ;
vc:hasPart ngm:natural-questions ;
vc:hasPart ngm:nfcorpus ;
vc:hasPart ngm:quora-question-pairs ;
vc:hasPart ngm:scifact ;
vc:hasPart ngm:trec-covid ;
vc:implements ngm:heterogeneous-domain-testing ;
vc:implements ngm:normalised-discounted-cumulative-gain ;
vc:implements ngm:zero-shot-evaluation-protocol ;
vc:qualityScore "0.92"^^xsd:float ;
vc:relatedTo ngm:colbert ;
vc:relatedTo ngm:cross-encoder-reranking ;
vc:relatedTo ngm:dense-passage-retrieval ;
vc:relatedTo ngm:hybrid-search ;
vc:relatedTo ngm:mteb-benchmark ;
vc:relatedTo ngm:question-answering ;
vc:relatedTo ngm:splade ;
vc:requires ngm:document-corpus ;
vc:requires ngm:ndcg-10 ;
vc:requires ngm:query-set ;
vc:requires ngm:recall-100 ;
vc:requires ngm:relevance-judgement ;
vc:slug "beir-benchmark" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:acl-anthology ;
vc:standardizedBy ngm:neurips-2021 ;
vc:standardizedBy ngm:sigir ;
vc:supports ngm:benchmark-driven-development ;
vc:supports ngm:model-comparison ;
vc:supports ngm:neural-retrieval-research ;
vc:supports ngm:rag-pipeline-development ;
vc:uses ngm:bge ;
vc:uses ngm:bm25 ;
vc:uses ngm:colbert ;
vc:uses ngm:e5 ;
vc:uses ngm:embedding-model ;
vc:uses ngm:faiss ;
vc:uses ngm:ndcg-metric ;
vc:uses ngm:recall-metric ;
vc:uses ngm:splade ;
vc:uses ngm:transformer .
ngm:belief-base a skos:Concept ;
rdfs:label "Belief Base"@en .
ngm:belief-desire-intention a owl:Class ;
rdfs:comment "The Belief-Desire-Intention (BDI) model is a framework for designing rational software agents in which mental states are represented as beliefs (what the agent knows about the world), desires (goals the agent wishes to achieve), and intentions (committed plans of action). Originating from Bratman's philosophical work on practical reasoning, BDI has been formalised into agent programming languages such as AgentSpeak and frameworks such as JADE. It underpins many autonomous and multi-agent systems requiring deliberative reasoning."@en ;
rdfs:label "Belief Desire Intention"@en ;
rdfs:subClassOf ngm:agent-architecture ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf ngm:cognitive-architecture ;
rdfs:subClassOf ngm:deliberative-system ;
rdfs:subClassOf ngm:multi-agent-system ;
rdfs:subClassOf ngm:rational-agent-model ;
rdfs:subClassOf _:r2927 ;
rdfs:subClassOf _:r2928 ;
rdfs:subClassOf _:r2929 ;
rdfs:subClassOf _:r2930 ;
rdfs:subClassOf _:r2931 ;
rdfs:subClassOf _:r2932 ;
skos:broader ngm:artificial-intelligence ;
vc:bridgesTo ngm:agentic-ai ;
vc:bridgesTo ngm:explainable-ai ;
vc:bridgesTo ngm:human-robot-interaction ;
vc:bridgesTo ngm:large-language-model ;
vc:bridgesTo ngm:neuro-symbolic-ai ;
vc:contrastsWith ngm:behaviour-tree ;
vc:contrastsWith ngm:finite-state-machine ;
vc:contrastsWith ngm:neural-network ;
vc:contrastsWith ngm:pure-reactive-system ;
vc:contrastsWith ngm:reactive-agent ;
vc:contrastsWith ngm:reinforcement-learning ;
vc:contrastsWith ngm:subsumption-architecture ;
vc:dependsOn ngm:belief-revision ;
vc:dependsOn ngm:knowledge-representation ;
vc:dependsOn ngm:logic-programming ;
vc:dependsOn ngm:modal-logic ;
vc:dependsOn ngm:ontology ;
vc:dependsOn ngm:planning ;
vc:enables ngm:agent-based-modelling ;
vc:enables ngm:autonomous-agent ;
vc:enables ngm:deliberative-reasoning ;
vc:enables ngm:explainable-ai ;
vc:enables ngm:human-robot-interaction ;
vc:enables ngm:multi-agent-system ;
vc:enables ngm:rational-agent ;
vc:enables ngm:social-simulation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:belief-base ;
vc:hasPart ngm:belief-revision ;
vc:hasPart ngm:deliberation-function ;
vc:hasPart ngm:desire-set ;
vc:hasPart ngm:filter-function ;
vc:hasPart ngm:intention-stack ;
vc:hasPart ngm:means-ends-reasoning ;
vc:hasPart ngm:options-generator ;
vc:hasPart ngm:plan-library ;
vc:hasPart ngm:reconsideration-function ;
vc:implements ngm:commitment-strategy ;
vc:implements ngm:deliberative-reasoning ;
vc:implements ngm:goal-management ;
vc:implements ngm:plan-selection ;
vc:implements ngm:practical-reasoning ;
vc:implements ngm:rational-agent ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:automated-planning ;
vc:relatedTo ngm:belief-revision ;
vc:relatedTo ngm:cognitive-architecture ;
vc:relatedTo ngm:goal-oriented-action-planning ;
vc:relatedTo ngm:modal-logic ;
vc:relatedTo ngm:multi-agent-system ;
vc:relatedTo ngm:symbolic-ai ;
vc:relatedTo ngm:temporal-logic ;
vc:requires ngm:agent-communication-language ;
vc:requires ngm:goal-directed-behaviour ;
vc:requires ngm:knowledge-representation ;
vc:requires ngm:logic-programming ;
vc:requires ngm:ontology ;
vc:requires ngm:planning ;
vc:requires ngm:reasoning-engine ;
vc:slug "belief-desire-intention" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:agentspeak ;
vc:standardizedBy ngm:fipa ;
vc:standardizedBy ngm:fipa-acl ;
vc:standardizedBy ngm:jade ;
vc:standardizedBy ngm:jason-framework ;
vc:supports ngm:air-traffic-management ;
vc:supports ngm:autonomous-vehicle ;
vc:supports ngm:distributed-collaboration ;
vc:supports ngm:healthcare-decision-support ;
vc:supports ngm:logistics-optimisation ;
vc:supports ngm:robotics ;
vc:supports ngm:smart-grid ;
vc:uses ngm:agent-architecture ;
vc:uses ngm:agentspeak ;
vc:uses ngm:fipa-acl ;
vc:uses ngm:jade ;
vc:uses ngm:jason-framework ;
vc:uses ngm:knowledge-representation ;
vc:uses ngm:plan-library ;
vc:uses ngm:reasoning-engine .
ngm:belief-propagation a owl:Class ;
rdfs:comment "Belief propagation is a message-passing algorithm for performing inference on graphical models by iteratively exchanging local messages between nodes representing variables and the factors that relate them. On tree-structured graphs it computes exact marginal distributions; on graphs with cycles, loopy belief propagation provides an approximate inference scheme that often works well in practice. It is the basis of efficient decoding for modern error-correcting codes and of probabilistic reasoning over structured domains."@en ;
rdfs:label "Belief Propagation"@en ;
rdfs:subClassOf ngm:graphical-model ;
rdfs:subClassOf ngm:probabilistic-inference ;
rdfs:subClassOf _:r2933 ;
rdfs:subClassOf _:r2934 ;
vc:contrastsWith ngm:markov-chain-monte-carlo ;
vc:enables ngm:inference ;
vc:enables ngm:probabilistic-inference ;
vc:enables ngm:reasoning ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:graphical-model ;
vc:hasPart ngm:message-passing ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:error-correcting-code ;
vc:relatedTo ngm:probabilistic-reasoning ;
vc:relatedTo ngm:variational-inference ;
vc:slug "belief-propagation" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:probabilistic-model ;
vc:supports ngm:statistical-inference ;
vc:uses ngm:markov-chain ;
vc:uses ngm:message-passing ;
vc:uses ngm:probability-theory .
ngm:belief-revision a skos:Concept ;
rdfs:label "Belief Revision"@en .
ngm:belief-space-planning a skos:Concept ;
rdfs:label "Belief Space Planning"@en .
ngm:belief-state a skos:Concept ;
rdfs:label "Belief State"@en .
ngm:belief-state-update a skos:Concept ;
rdfs:label "Belief State Update"@en .
ngm:believable-npc-behaviour a skos:Concept ;
rdfs:label "Believable Npc Behaviour"@en .
ngm:bellman-equation a owl:Class ;
rdfs:comment "The Bellman equation is a recursive relationship that expresses the value of a state as the immediate reward plus the discounted value of successor states under a given policy. It is the mathematical foundation of dynamic programming and reinforcement learning, characterising optimal behaviour through the principle of optimality. Solving or approximating the Bellman equation yields value functions and optimal policies for sequential decision problems."@en ;
rdfs:label "Bellman Equation"@en ;
rdfs:subClassOf ngm:dynamic-programming ;
vc:bridgesTo ngm:q-learning ;
vc:dependsOn ngm:markov-decision-process ;
vc:enables ngm:q-learning ;
vc:enables ngm:reinforcement-learning ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:dynamic-programming ;
vc:isPartOf ngm:markov-decision-process ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:policy ;
vc:relatedTo ngm:state-space ;
vc:relatedTo ngm:value-function ;
vc:slug "bellman-equation" ;
vc:sourceDomain "machine-learning" ;
vc:supports ngm:optimal-control ;
vc:supports ngm:planning ;
vc:uses ngm:reward-function ;
vc:uses ngm:value-function .
ngm:benchmark-contamination a skos:Concept ;
rdfs:label "Benchmark Contamination"@en .
ngm:benchmark-dataset a owl:Class ;
rdfs:comment "A benchmark dataset is a standardised, publicly shared collection of data with established splits and evaluation protocols, used to compare the performance of machine-learning models on a common task. By fixing the data, metrics, and procedure, benchmarks enable fair, reproducible comparison and track progress over time. Well-known benchmarks have driven advances in computer vision, natural language processing, and many other fields."@en ;
rdfs:label "Benchmark Dataset"@en ;
rdfs:subClassOf ngm:dataset ;
rdfs:subClassOf ngm:labelled-dataset ;
rdfs:subClassOf _:r2935 ;
rdfs:subClassOf _:r2936 ;
rdfs:subClassOf _:r2937 ;
rdfs:subClassOf _:r2938 ;
rdfs:subClassOf _:r2939 ;
rdfs:subClassOf _:r2940 ;
rdfs:subClassOf _:r2941 ;
rdfs:subClassOf _:r2942 ;
rdfs:subClassOf _:r2943 ;
vc:contrastsWith ngm:ai-benchmark-epistemological-critique ;
vc:contrastsWith ngm:overfitting ;
vc:dependsOn ngm:data-curation ;
vc:dependsOn ngm:data-quality ;
vc:dependsOn ngm:ground-truth-labels ;
vc:dependsOn ngm:human-evaluation ;
vc:enables ngm:benchmark-evaluation ;
vc:enables ngm:capability-evaluation ;
vc:enables ngm:model-evaluation ;
vc:enables ngm:reproducibility ;
vc:enables ngm:transfer-learning ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:data-annotation ;
vc:hasPart ngm:ground-truth-labels ;
vc:hasPart ngm:leaderboard ;
vc:hasPart ngm:training-data ;
vc:implements ngm:benchmark-standard ;
vc:implements ngm:benchmarking ;
vc:isPartOf ngm:model-evaluation ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:beir-benchmark ;
vc:relatedTo ngm:benchmarking ;
vc:relatedTo ngm:coco-dataset ;
vc:relatedTo ngm:frontier-model-evaluation ;
vc:relatedTo ngm:human-evaluation ;
vc:relatedTo ngm:large-scale-datasets ;
vc:relatedTo ngm:leaderboard ;
vc:relatedTo ngm:model-evaluation-results ;
vc:relatedTo ngm:performance-benchmarks ;
vc:relatedTo ngm:performance-metrics ;
vc:requires ngm:data-annotation ;
vc:requires ngm:data-curation ;
vc:requires ngm:data-quality ;
vc:requires ngm:ground-truth-labels ;
vc:slug "benchmark-dataset" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:benchmark-standard ;
vc:standardizedBy ngm:mlcommons ;
vc:supports ngm:computer-vision ;
vc:supports ngm:deep-learning ;
vc:supports ngm:image-classification ;
vc:supports ngm:natural-language-processing ;
vc:supports ngm:object-detection ;
vc:supports ngm:question-answering ;
vc:supports ngm:speech-recognition ;
vc:uses ngm:cross-validation ;
vc:uses ngm:evaluation-metric ;
vc:uses ngm:training-data .
ngm:benchmark-driven-development a skos:Concept ;
rdfs:label "Benchmark Driven Development"@en .
ngm:benchmark-evaluation a owl:Class ;
rdfs:comment "Benchmark evaluation is the systematic measurement of a model or system against a standardised dataset and scoring protocol so that results are comparable across systems and over time. A benchmark specifies the task, the data splits, the permitted inputs, and the metrics used to rank performance. In machine learning, benchmark evaluation drives the field's empirical progress, but it is subject to well-known failure modes including train-test contamination, overfitting to leaderboards, and construct validity gaps between the benchmark and the real-world capability it purports to measure."@en ;
rdfs:label "Benchmark Evaluation"@en ;
rdfs:subClassOf ngm:ai-evaluation ;
rdfs:subClassOf ngm:benchmarking ;
rdfs:subClassOf ngm:model-evaluation ;
rdfs:subClassOf _:r2944 ;
rdfs:subClassOf _:r2945 ;
rdfs:subClassOf _:r2946 ;
rdfs:subClassOf _:r2947 ;
rdfs:subClassOf _:r2948 ;
rdfs:subClassOf _:r2949 ;
rdfs:subClassOf _:r2950 ;
rdfs:subClassOf _:r2951 ;
vc:contrastsWith ngm:ai-benchmark-epistemological-critique ;
vc:contrastsWith ngm:heuristic-evaluation ;
vc:contrastsWith ngm:human-evaluation ;
vc:dependsOn ngm:data-annotation ;
vc:dependsOn ngm:data-quality ;
vc:dependsOn ngm:evaluation-harness ;
vc:dependsOn ngm:ground-truth-labels ;
vc:enables ngm:capability-evaluation ;
vc:enables ngm:frontier-model-evaluation ;
vc:enables ngm:leaderboard ;
vc:enables ngm:model-evaluation-results ;
vc:enables ngm:reproducibility ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:benchmark-dataset ;
vc:hasPart ngm:evaluation-metric ;
vc:hasPart ngm:leaderboard ;
vc:hasPart ngm:model-evaluation-results ;
vc:implements ngm:benchmark-standard ;
vc:implements ngm:benchmarking ;
vc:qualityScore "0.78"^^xsd:float ;
vc:relatedTo ngm:ai-benchmark-epistemological-critique ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:beir-benchmark ;
vc:relatedTo ngm:benchmark-standard ;
vc:relatedTo ngm:bias ;
vc:relatedTo ngm:continuous-integration ;
vc:relatedTo ngm:evaluation-benchmarks-and-leaderboards ;
vc:relatedTo ngm:evaluation-harness ;
vc:relatedTo ngm:frontier-model-evaluation ;
vc:relatedTo ngm:mlcommons ;
vc:relatedTo ngm:mteb-benchmark ;
vc:relatedTo ngm:overfitting ;
vc:relatedTo ngm:red-teaming ;
vc:requires ngm:benchmark-dataset ;
vc:requires ngm:evaluation-metric ;
vc:requires ngm:ground-truth-labels ;
vc:requires ngm:statistical-hypothesis-testing ;
vc:slug "benchmark-evaluation" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:benchmark-standard ;
vc:standardizedBy ngm:mlcommons ;
vc:supports ngm:computer-vision ;
vc:supports ngm:deep-learning ;
vc:supports ngm:large-language-models ;
vc:supports ngm:natural-language-processing ;
vc:supports ngm:question-answering ;
vc:supports ngm:supervised-learning ;
vc:supports ngm:transfer-learning ;
vc:uses ngm:benchmark-dataset ;
vc:uses ngm:cross-validation ;
vc:uses ngm:evaluation-harness ;
vc:uses ngm:evaluation-metric ;
vc:uses ngm:performance-benchmarks ;
vc:uses ngm:statistical-hypothesis-testing .
ngm:benchmark-registry a skos:Concept ;
rdfs:label "Benchmark Registry"@en .
ngm:benchmark-saturation a skos:Concept ;
rdfs:label "Benchmark Saturation"@en .
ngm:benchmark-standard a owl:Class ;
rdfs:comment "A vendor-agnostic reference specification for evaluating and comparing system performance, establishing standardized metrics and methodologies that enable fair, repeatable, and meaningful comparisons across computing systems, processes, or technologies."@en ;
rdfs:label "Benchmark Standard"@en ;
rdfs:subClassOf ngm:technical-standard ;
rdfs:subClassOf _:r2952 ;
rdfs:subClassOf _:r2953 ;
rdfs:subClassOf _:r2954 ;
rdfs:subClassOf _:r2955 ;
vc:bridgesTo ngm:benchmark-evaluation ;
vc:bridgesTo ngm:model-evaluation ;
vc:dependsOn ngm:standards-body ;
vc:enables ngm:model-evaluation ;
vc:enables ngm:performance-comparison ;
vc:enables ngm:quality-assurance ;
vc:enables ngm:regression ;
vc:enables ngm:vendor-selection ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:evaluation-harness ;
vc:isPartOf ngm:quality-assurance ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:capacity-planning ;
vc:relatedTo ngm:performance ;
vc:requires ngm:measurement-methodology ;
vc:requires ngm:reference-implementation ;
vc:requires ngm:reproducibility ;
vc:requires ngm:validation-process ;
vc:slug "benchmark-standard" ;
vc:sourceDomain "standards" ;
vc:standardizedBy ngm:iso-iec-jtc-1 ;
vc:standardizedBy ngm:standards-organization ;
vc:supports ngm:regulatory-compliance ;
vc:uses ngm:key-performance-indicator ;
vc:uses ngm:statistical-analysis ;
vc:uses ngm:workload-characterisation .
ngm:benchmark-trend-analysis a skos:Concept ;
rdfs:label "Benchmark Trend Analysis"@en .
ngm:benchmark-trend-extrapolation a skos:Concept ;
rdfs:label "Benchmark Trend Extrapolation"@en .
ngm:benchmarking a owl:Class ;
rdfs:comment "Benchmarking is the disciplined practice of measuring the performance, accuracy, efficiency, or quality of a system, component, or model against a standardised workload and a set of comparable baselines. It produces reproducible quantitative metrics — such as latency, throughput, resource utilisation, or task accuracy — that allow engineers to compare alternatives, detect regressions, and guide optimisation. Robust benchmarking requires controlled environments, representative workloads, statistically sound measurement, and transparent reporting to avoid misleading or non-generalisable results."@en ;
rdfs:label "Benchmarking"@en ;
rdfs:subClassOf ngm:performance-optimization ;
rdfs:subClassOf _:r2956 ;
rdfs:subClassOf _:r2957 ;
vc:bridgesTo ngm:performance-optimization ;
vc:enables ngm:continuous-integration ;
vc:enables ngm:performance-optimization ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:testing ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:classification ;
vc:relatedTo ngm:continuous-integration ;
vc:relatedTo ngm:high-performance-computing ;
vc:requires ngm:quality-assurance ;
vc:requires ngm:testing ;
vc:slug "benchmarking" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:quality-assurance ;
vc:uses ngm:bandwidth ;
vc:uses ngm:latency .
ngm:benchmarking-methodology a skos:Concept ;
rdfs:label "Benchmarking Methodology"@en .
ngm:benchmarks a owl:Class ;
rdfs:comment "Benchmarks are standardised tasks, datasets, or workloads used to measure and compare the capabilities or performance of systems, models, or components under controlled, reproducible conditions. In artificial intelligence they encompass curated evaluation suites that probe language understanding, mathematical reasoning, coding, and multimodal perception to produce comparable scores across model generations and research groups. In computing, robotics, and hardware engineering, benchmarks quantify throughput, latency, accuracy, and energy efficiency against fixed reference workloads. Benchmark results are published via leaderboards and model cards to support reproducible science, informed procurement, and regulatory accountability."@en ;
rdfs:label "Benchmarks"@en ;
rdfs:subClassOf ngm:evaluation-benchmarks-and-leaderboards ;
rdfs:subClassOf ngm:performance-metrics ;
rdfs:subClassOf ngm:reproducibility ;
rdfs:subClassOf _:r2958 ;
rdfs:subClassOf _:r2959 ;
rdfs:subClassOf _:r2960 ;
rdfs:subClassOf _:r2961 ;
rdfs:subClassOf _:r2962 ;
rdfs:subClassOf _:r2963 ;
rdfs:subClassOf _:r2964 ;
rdfs:subClassOf _:r2965 ;
vc:bridgesTo ngm:ai-regulation ;
vc:bridgesTo ngm:eu-ai-act-regulatory-instrument ;
vc:bridgesTo ngm:hardware-performance ;
vc:bridgesTo ngm:regulatory-compliance ;
vc:contrastsWith ngm:ablation-studies ;
vc:contrastsWith ngm:human-evaluation ;
vc:dependsOn ngm:annotation-pipelines ;
vc:dependsOn ngm:data-curation ;
vc:dependsOn ngm:statistical-testing ;
vc:enables ngm:evaluation-benchmarks-and-leaderboards ;
vc:enables ngm:model-comparison ;
vc:enables ngm:model-evaluation-results ;
vc:enables ngm:model-performance ;
vc:enables ngm:model-selection ;
vc:enables ngm:reproducibility ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:annotation-pipelines ;
vc:hasPart ngm:datasets ;
vc:hasPart ngm:evaluation-benchmarks-and-leaderboards ;
vc:hasPart ngm:evaluation-metric ;
vc:hasPart ngm:ground-truth-labels ;
vc:hasPart ngm:held-out-test-sets ;
vc:hasPart ngm:model-cards ;
vc:implements ngm:evaluation-harness ;
vc:implements ngm:scoring-function ;
vc:implements ngm:task-formulation ;
vc:isPartOf ngm:empirical-research ;
vc:isPartOf ngm:machine-learning-research-infrastructure ;
vc:isPartOf ngm:scientific-method ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:ablation-studies ;
vc:relatedTo ngm:adversarial-testing ;
vc:relatedTo ngm:annotation-pipelines ;
vc:relatedTo ngm:benchmark-standard ;
vc:relatedTo ngm:benign-overfitting ;
vc:relatedTo ngm:bias-and-fairness ;
vc:relatedTo ngm:calibration ;
vc:relatedTo ngm:deep-learning ;
vc:relatedTo ngm:foundation-model ;
vc:relatedTo ngm:goodhart-s-law ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:model-cards ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:overfitting ;
vc:relatedTo ngm:regularisation ;
vc:relatedTo ngm:software-testing ;
vc:relatedTo ngm:transfer-learning ;
vc:requires ngm:annotation-pipelines ;
vc:requires ngm:data-curation ;
vc:requires ngm:evaluation-harness ;
vc:requires ngm:evaluation-metric ;
vc:requires ngm:ground-truth-labels ;
vc:requires ngm:held-out-test-sets ;
vc:slug "benchmarks" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:iso-iec-22989-2022 ;
vc:standardizedBy ngm:mlcommons ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:standardizedBy ngm:spec ;
vc:supports ngm:ai-governance ;
vc:supports ngm:ai-safety ;
vc:supports ngm:mlops ;
vc:supports ngm:model-selection ;
vc:supports ngm:responsible-ai ;
vc:supports ngm:software-testing ;
vc:uses ngm:datasets ;
vc:uses ngm:evaluation-metric ;
vc:uses ngm:ground-truth-labels ;
vc:uses ngm:performance-metrics ;
vc:uses ngm:statistical-testing .
ngm:beneficial-ai a skos:Concept ;
rdfs:label "Beneficial AI"@en .
ngm:beneficial-ai-risk a skos:Concept ;
rdfs:label "Beneficial AI Risk"@en .
ngm:beneficial-ownership a owl:Class ;
rdfs:comment "Beneficial ownership identifies the natural persons who ultimately own or control a legal entity or arrangement, or on whose behalf a transaction is conducted, regardless of the formal legal title. It distinguishes the real human beneficiaries from nominee shareholders, trustees and layered corporate structures. Establishing beneficial ownership is a core obligation in anti-financial-crime regimes, enabling regulators and institutions to pierce opaque structures and attribute responsibility."@en ;
rdfs:label "Beneficial Ownership"@en ;
rdfs:subClassOf ngm:corporate-governance ;
rdfs:subClassOf _:r2968 ;
rdfs:subClassOf _:r2969 ;
rdfs:subClassOf _:r2970 ;
vc:bridgesTo ngm:identity-management ;
vc:contrastsWith ngm:transaction-privacy ;
vc:dependsOn ngm:regulatory-compliance ;
vc:enables ngm:financial-inclusion ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:sanctions-screening ;
vc:implements ngm:corporate-governance ;
vc:isPartOf ngm:kyc ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:digital-identity ;
vc:relatedTo ngm:financial-services ;
vc:relatedTo ngm:financial-system ;
vc:requires ngm:identity-verification ;
vc:requires ngm:kyc ;
vc:slug "beneficial-ownership" ;
vc:sourceDomain "finance" ;
vc:supports ngm:aml .
ngm:beneficial-ownership-disclosure a owl:Class ;
rdfs:comment "Beneficial ownership disclosure is the regulatory requirement for legal entities such as companies, trusts, and partnerships to identify and register the natural persons who ultimately own or control them above a defined threshold, typically 25% of shares or voting rights. The primary purpose is to prevent the misuse of corporate structures for money laundering, tax evasion, corruption, and sanctions circumvention by making true ownership transparent to regulators and, increasingly, the public."@en ;
rdfs:label "Beneficial Ownership Disclosure"@en ;
rdfs:subClassOf ngm:regulatory-compliance ;
rdfs:subClassOf _:r2966 ;
rdfs:subClassOf _:r2967 ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:fatf ;
vc:relatedTo ngm:kyc ;
vc:requires ngm:data-governance ;
vc:requires ngm:identity-verification ;
vc:slug "beneficial-ownership-disclosure" ;
vc:sourceDomain "governance" ;
vc:supports ngm:aml ;
vc:supports ngm:aml-kyc-compliance .
ngm:beneficial-ownership-registers a skos:Concept ;
rdfs:label "Beneficial Ownership Registers"@en .
ngm:beneficiary-information-requirement a skos:Concept ;
rdfs:label "Beneficiary Information Requirement"@en .
ngm:benevolent-dictatorship a skos:Concept ;
rdfs:label "Benevolent Dictatorship"@en .
ngm:benign-overfitting a owl:Class ;
rdfs:comment "Benign overfitting is the phenomenon, observed in heavily overparameterised models such as deep neural networks, where a model fits its training data exactly, including noise, yet still generalises well to unseen data. This contradicts the classical bias-variance trade-off, which predicts that interpolating noise should harm generalisation. It is closely associated with the double-descent risk curve and is a central puzzle in modern statistical learning theory."@en ;
rdfs:label "Benign Overfitting"@en ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf ngm:generalisation-theory ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf ngm:statistical-learning-theory ;
rdfs:subClassOf _:r2971 ;
rdfs:subClassOf _:r2972 ;
skos:broader ngm:ai-research-area ;
vc:bridgesTo ngm:ai-governance ;
vc:bridgesTo ngm:ai-safety ;
vc:bridgesTo ngm:eu-ai-act-regulatory-instrument ;
vc:bridgesTo ngm:model-governance ;
vc:bridgesTo ngm:responsible-ai ;
vc:contrastsWith ngm:classical-bias-variance-tradeoff ;
vc:contrastsWith ngm:early-stopping ;
vc:contrastsWith ngm:overfitting ;
vc:contrastsWith ngm:regularisation ;
vc:contrastsWith ngm:underfitting ;
vc:dependsOn ngm:data-covariance-spectrum ;
vc:dependsOn ngm:gradient-descent ;
vc:dependsOn ngm:implicit-bias ;
vc:dependsOn ngm:overparameterisation ;
vc:dependsOn ngm:statistical-learning-theory ;
vc:enables ngm:generalisation ;
vc:enables ngm:interpolation ;
vc:enables ngm:near-optimal-test-error ;
vc:enables ngm:zero-training-error ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:double-descent ;
vc:hasPart ngm:implicit-bias ;
vc:hasPart ngm:interpolation-threshold ;
vc:hasPart ngm:minimum-norm-interpolator ;
vc:hasPart ngm:overparameterisation ;
vc:implements ngm:gradient-descent ;
vc:implements ngm:implicit-bias ;
vc:implements ngm:minimum-norm-interpolator ;
vc:implements ngm:stochastic-gradient-descent ;
vc:isPartOf ngm:generalisation-theory ;
vc:isPartOf ngm:machine-learning-theory ;
vc:isPartOf ngm:statistical-learning-theory ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:algorithmic-bias-and-variance ;
vc:relatedTo ngm:attention-mechanism ;
vc:relatedTo ngm:benchmarks ;
vc:relatedTo ngm:chinchilla-scaling ;
vc:relatedTo ngm:cross-validation ;
vc:relatedTo ngm:deep-learning ;
vc:relatedTo ngm:differential-privacy ;
vc:relatedTo ngm:double-descent ;
vc:relatedTo ngm:empirical-risk-minimisation ;
vc:relatedTo ngm:foundation-model ;
vc:relatedTo ngm:grokking ;
vc:relatedTo ngm:kernel-methods ;
vc:relatedTo ngm:lo-ra ;
vc:relatedTo ngm:loss-function ;
vc:relatedTo ngm:memorisation ;
vc:relatedTo ngm:model-capacity ;
vc:relatedTo ngm:neural-architecture-search ;
vc:relatedTo ngm:overfitting ;
vc:relatedTo ngm:overparameterisation ;
vc:relatedTo ngm:regularisation ;
vc:relatedTo ngm:scaling-laws ;
vc:relatedTo ngm:statistical-learning-theory ;
vc:relatedTo ngm:stochastic-gradient-descent ;
vc:relatedTo ngm:transfer-learning ;
vc:relatedTo ngm:transformer ;
vc:requires ngm:gradient-descent ;
vc:requires ngm:implicit-bias ;
vc:requires ngm:overparameterisation ;
vc:requires ngm:training-data ;
vc:slug "benign-overfitting" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:statistical-learning-theory ;
vc:supports ngm:deep-learning ;
vc:supports ngm:foundation-model ;
vc:supports ngm:large-language-models ;
vc:supports ngm:neural-network .
ngm:bent-pipe-transponder a owl:Class ;
rdfs:label "Bent-pipe Transponder"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:satellite-communication ;
vc:slug "bent-pipe-transponder" ;
vc:sourceDomain "space-science-and-systems" .
ngm:bereavement-processing a skos:Concept ;
rdfs:label "Bereavement Processing"@en .
ngm:bernoulli-distribution a skos:Concept ;
rdfs:label "Bernoulli Distribution"@en .
ngm:bernoulli-equation a skos:Concept ;
rdfs:label "Bernoulli Equation"@en .
ngm:berry-1941 a skos:Concept ;
rdfs:label "Berry 1941"@en .
ngm:berry-esseen-theorem a skos:Concept ;
rdfs:label "Berry Esseen Theorem"@en .
ngm:bert a owl:Class ;
rdfs:comment "BERT (Bidirectional Encoder Representations from Transformers) is a pre-trained deep language representation model developed by Google AI Language, published in 2018, which applies a bidirectional Transformer encoder trained with masked language modelling (MLM) and next sentence prediction (NSP) objectives on large text corpora to produce contextualised word embeddings. Unlike prior unidirectional models, BERT conditions each token on its full left and right context simultaneously, enabling a richer semantic representation that generalises across diverse NLP tasks via fine-tuning. It established the pre-train-then-fine-tune paradigm for natural language processing, achieving state-of-the-art performance across eleven NLP benchmarks upon release, including GLUE and SQuAD. Its architecture directly underpins a large family of subsequent encoder models including RoBERTa, ALBERT, DistilBERT, and multilingual mBERT."@en ;
rdfs:label "BERT"@en ;
rdfs:subClassOf ngm:ai-model-architecture ;
rdfs:subClassOf ngm:language-model ;
rdfs:subClassOf ngm:pre-trained-language-model ;
rdfs:subClassOf _:r2595 ;
rdfs:subClassOf _:r2596 ;
rdfs:subClassOf _:r2597 ;
rdfs:subClassOf _:r2598 ;
rdfs:subClassOf _:r2599 ;
rdfs:subClassOf _:r2600 ;
rdfs:subClassOf _:r2601 ;
rdfs:subClassOf _:r2602 ;
rdfs:subClassOf _:r2603 ;
skos:broader ngm:ai-model-architecture ;
vc:bridgesTo ngm:knowledge-graph-embedding ;
vc:bridgesTo ngm:large-language-models ;
vc:bridgesTo ngm:retrieval-augmented-generation ;
vc:contrastsWith ngm:autoregressive-model ;
vc:contrastsWith ngm:elmo ;
vc:contrastsWith ngm:gpt ;
vc:contrastsWith ngm:recurrent-neural-network ;
vc:dependsOn ngm:backpropagation ;
vc:dependsOn ngm:large-scale-corpus ;
vc:dependsOn ngm:neural-network-text-tokenisation ;
vc:dependsOn ngm:transformer-architecture ;
vc:enables ngm:dense-passage-retrieval ;
vc:enables ngm:dense-retrieval ;
vc:enables ngm:fine-tuning ;
vc:enables ngm:knowledge-graph-embedding ;
vc:enables ngm:named-entity-recognition ;
vc:enables ngm:natural-language-understanding ;
vc:enables ngm:question-answering ;
vc:enables ngm:semantic-search ;
vc:enables ngm:sentiment-analysis ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:attention-mechanism ;
vc:hasPart ngm:cls-token ;
vc:hasPart ngm:masked-language-modelling ;
vc:hasPart ngm:next-sentence-prediction ;
vc:hasPart ngm:self-attention ;
vc:hasPart ngm:sep-token ;
vc:hasPart ngm:subword-tokenisation ;
vc:implements ngm:masked-language-modelling ;
vc:implements ngm:pre-training ;
vc:implements ngm:transfer-learning ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:albert ;
vc:relatedTo ngm:bleu-score ;
vc:relatedTo ngm:deberta ;
vc:relatedTo ngm:distilbert ;
vc:relatedTo ngm:glue-benchmark ;
vc:relatedTo ngm:gpt ;
vc:relatedTo ngm:knowledge-distillation ;
vc:relatedTo ngm:m-bert ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:ro-berta ;
vc:relatedTo ngm:squad ;
vc:relatedTo ngm:t5 ;
vc:requires ngm:attention-mechanism ;
vc:requires ngm:gradient-descent ;
vc:requires ngm:large-scale-corpus ;
vc:requires ngm:pre-training ;
vc:requires ngm:transfer-learning ;
vc:slug "bert" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:glue-benchmark ;
vc:standardizedBy ngm:transformers ;
vc:supports ngm:information-retrieval ;
vc:supports ngm:natural-language-processing ;
vc:supports ngm:retrieval-augmented-generation ;
vc:supports ngm:semantic-search ;
vc:uses ngm:attention-mechanism ;
vc:uses ngm:backpropagation ;
vc:uses ngm:embeddings ;
vc:uses ngm:masked-language-modelling ;
vc:uses ngm:self-attention ;
vc:uses ngm:subword-tokenisation ;
vc:uses ngm:transformer-architecture .
ngm:bert-based-nlp a skos:Concept ;
rdfs:label "Bert Based NLP"@en .
ngm:bert-score a skos:Concept ;
rdfs:label "Bert Score"@en .
ngm:bertscore a skos:Concept ;
rdfs:label "Bertscore"@en .
ngm:best-effort-delivery a skos:Concept ;
rdfs:label "Best Effort Delivery"@en .
ngm:best-effort-networking a skos:Concept ;
rdfs:label "Best Effort Networking"@en .
ngm:best-effort-retry a skos:Concept ;
rdfs:label "Best Effort Retry"@en .
ngm:best-effort-service a skos:Concept ;
rdfs:label "Best Effort Service"@en .
ngm:best-of-n-jailbreaking a skos:Concept ;
rdfs:label "Best Of N Jailbreaking"@en .
ngm:best-of-n-sampling a skos:Concept ;
rdfs:label "Best Of N Sampling"@en .
ngm:best-practice a owl:Class ;
rdfs:comment "A method, technique, or configuration that a professional community has found through accumulated experience to reliably produce superior results, codified so that others can adopt it without rediscovering it. Best practices sit between raw craft knowledge and formal standards: they are advisory rather than mandatory, evolve faster than standardisation processes allow, and are the substance that bodies of knowledge, reference architectures, and accessibility or security guidelines distil and disseminate."@en ;
rdfs:label "Best Practice"@en ;
rdfs:subClassOf ngm:knowledge-management ;
vc:contrastsWith ngm:technical-standard ;
vc:enables ngm:interoperability ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:governance-framework ;
vc:relatedTo ngm:reference-architecture ;
vc:slug "best-practice" ;
vc:sourceDomain "standards" .
ngm:best-practices a skos:Concept ;
rdfs:label "Best Practices"@en .
ngm:beta-vae a skos:Concept ;
rdfs:label "Beta Vae"@en .
ngm:better-reykjavik a skos:Concept ;
rdfs:label "Better Reykjavik"@en .
ngm:bettertogether a skos:Concept ;
rdfs:label "Bettertogether"@en .
ngm:bevy a skos:Concept ;
rdfs:label "Bevy"@en .
ngm:beyond-low-earth-orbit-spacecraft a owl:Class ;
rdfs:label "Beyond Low Earth Orbit Spacecraft"@en ;
rdfs:subClassOf ngm:spacecraft ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:space-life-sciences ;
vc:slug "beyond-low-earth-orbit-spacecraft" ;
vc:sourceDomain "space-science-and-systems" .
ngm:beyond-low-earth-orbit-spaceflight a owl:Class ;
rdfs:label "Beyond Low Earth Orbit Spaceflight"@en ;
rdfs:subClassOf ngm:spaceflight ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:space-life-sciences ;
vc:slug "beyond-low-earth-orbit-spaceflight" ;
vc:sourceDomain "space-science-and-systems" .
ngm:bfloat16 a owl:Class ;
rdfs:comment "Bfloat16 (brain floating point) is a 16-bit floating-point format that keeps the same 8-bit exponent as 32-bit IEEE float but truncates the mantissa to 7 bits. It preserves the dynamic range of single precision while halving memory and bandwidth, making it well suited to deep-learning training and inference. Because it trades precision for range, it avoids the overflow and underflow problems that affect narrower formats during gradient computation."@en ;
rdfs:label "Bfloat16"@en ;
rdfs:subClassOf ngm:mixed-precision-training ;
rdfs:subClassOf ngm:model-compression ;
rdfs:subClassOf _:r2973 ;
vc:bridgesTo ngm:memory-bandwidth ;
vc:contrastsWith ngm:quantisation ;
vc:dependsOn ngm:tensor-processing-unit ;
vc:enables ngm:inference-optimisation ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:model-compression ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:knowledge-distillation ;
vc:relatedTo ngm:pruning ;
vc:relatedTo ngm:quantisation ;
vc:relatedTo ngm:throughput ;
vc:relatedTo ngm:transformer-architecture ;
vc:requires ngm:tensor-core ;
vc:slug "bfloat16" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:gpu-acceleration ;
vc:uses ngm:tensor-core .
ngm:bfs-tree a skos:Concept ;
rdfs:label "Bfs Tree"@en .
ngm:bft-consensus a skos:Concept ;
rdfs:label "Bft Consensus"@en .
ngm:bge a skos:Concept ;
rdfs:label "Bge"@en .
ngm:bi-elliptic-transfer a owl:Class ;
rdfs:label "Bi-elliptic Transfer"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:orbital-dynamics ;
vc:slug "bi-elliptic-transfer" ;
vc:sourceDomain "space-science-and-systems" .
ngm:bi-encoder a skos:Concept ;
rdfs:label "Bi Encoder"@en .
ngm:bi-encoder-architecture a skos:Concept ;
rdfs:label "Bi Encoder Architecture"@en .
ngm:bias a owl:Class ;
rdfs:comment "Systematic deviation from fairness, objectivity, or expected outcomes in an AI system that leads to prejudiced results favouring or disfavouring particular groups, individuals, or outcomes, arising from data, algorithms, or deployment contexts."@en ;
rdfs:label "Bias"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf _:r3024 ;
rdfs:subClassOf _:r3025 ;
rdfs:subClassOf _:r3026 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:data-governance ;
vc:bridgesTo ngm:human-rights ;
vc:contrastsWith ngm:ai-fairness ;
vc:contrastsWith ngm:algorithmic-fairness ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:training-data ;
vc:enables ngm:algorithmic-auditing ;
vc:enables ngm:bias-mitigation-techniques ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:algorithmic-bias ;
vc:isPartOf ngm:ai-risks ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:accountability ;
vc:relatedTo ngm:ai-risks ;
vc:relatedTo ngm:bias-in-large-language-models ;
vc:relatedTo ngm:safety-and-alignment ;
vc:relatedTo ngm:transparency ;
vc:requires ngm:bias-detection-methods ;
vc:requires ngm:fairness-metrics ;
vc:slug "bias" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:iso-iec-tr-24027 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:uses ngm:confusion-matrix ;
vc:uses ngm:statistical-testing .
ngm:bias-analysis a skos:Concept ;
rdfs:label "Bias Analysis"@en .
ngm:bias-and-fairness a owl:Class ;
rdfs:comment "Bias and Fairness is the area of responsible AI concerned with detecting, measuring, and mitigating systematic disparities in how machine learning systems treat individuals and groups. It addresses biases that enter through training data, model design, and deployment context, and it formalises competing notions of fairness such as demographic parity, equalised odds, and individual fairness. The goal is to ensure that automated decisions do not unjustifiably disadvantage protected populations."@en ;
rdfs:label "Bias And Fairness"@en ;
rdfs:subClassOf ngm:ai-ethics ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:responsible-ai ;
rdfs:subClassOf _:r2974 ;
rdfs:subClassOf _:r2975 ;
rdfs:subClassOf _:r2976 ;
rdfs:subClassOf _:r2977 ;
rdfs:subClassOf _:r2978 ;
rdfs:subClassOf _:r2979 ;
rdfs:subClassOf _:r2980 ;
rdfs:subClassOf _:r2981 ;
rdfs:subClassOf _:r2982 ;
rdfs:subClassOf _:r2983 ;
rdfs:subClassOf _:r2984 ;
rdfs:subClassOf _:r2985 ;
rdfs:subClassOf _:r2986 ;
rdfs:subClassOf _:r2987 ;
rdfs:subClassOf _:r2988 ;
rdfs:subClassOf _:r2989 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:ai-impact-assessment ;
vc:bridgesTo ngm:human-ai-collaboration ;
vc:contrastsWith ngm:algorithmic-bias-and-variance ;
vc:contrastsWith ngm:automation-bias ;
vc:contrastsWith ngm:harmful-bias ;
vc:contrastsWith ngm:inductive-bias ;
vc:dependsOn ngm:automated-decision-making ;
vc:dependsOn ngm:data-governance ;
vc:dependsOn ngm:dataset ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:model-evaluation ;
vc:enables ngm:ai-fairness ;
vc:enables ngm:algorithmic-accountability ;
vc:enables ngm:algorithmic-auditing ;
vc:enables ngm:algorithmic-fairness ;
vc:enables ngm:algorithmic-impact-assessment ;
vc:enables ngm:explainability ;
vc:enables ngm:regulatory-compliance ;
vc:enables ngm:transparency ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:algorithmic-bias ;
vc:hasPart ngm:bias-detection-methods ;
vc:hasPart ngm:bias-mitigation-techniques ;
vc:hasPart ngm:disparate-impact ;
vc:hasPart ngm:fairness-auditing-tools ;
vc:hasPart ngm:fairness-constraints ;
vc:hasPart ngm:fairness-metrics ;
vc:hasPart ngm:group-vs-individual-fairness ;
vc:hasPart ngm:intersectional-fairness ;
vc:implements ngm:algorithmic-impact-assessment ;
vc:implements ngm:diversity-non-discrimination-and-fairness ;
vc:implements ngm:fairness-assessment ;
vc:isPartOf ngm:responsible-ai ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:ai-risk-management ;
vc:relatedTo ngm:algorithmic-bias ;
vc:relatedTo ngm:algorithmic-governance ;
vc:relatedTo ngm:algorithmic-transparency ;
vc:relatedTo ngm:bias ;
vc:relatedTo ngm:bias-in-large-language-models ;
vc:relatedTo ngm:data-quality-management ;
vc:relatedTo ngm:differential-privacy ;
vc:relatedTo ngm:explainability ;
vc:relatedTo ngm:fairness ;
vc:relatedTo ngm:fairness-accuracy-tradeoffs ;
vc:relatedTo ngm:fairness-oecd ;
vc:relatedTo ngm:transparency ;
vc:requires ngm:causal-inference ;
vc:requires ngm:data-quality ;
vc:requires ngm:dataset ;
vc:requires ngm:model-evaluation ;
vc:requires ngm:protected-attributes ;
vc:requires ngm:statistical-hypothesis-testing ;
vc:requires ngm:training-data ;
vc:slug "bias-and-fairness" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:ieee-p-7003-2021 ;
vc:standardizedBy ngm:iso-iec-tr-24027 ;
vc:standardizedBy ngm:nist-sp-1270 ;
vc:supports ngm:accountability ;
vc:supports ngm:ai-governance ;
vc:supports ngm:human-ai-collaboration ;
vc:supports ngm:human-oversight ;
vc:supports ngm:responsible-ai ;
vc:supports ngm:trustworthy-ai ;
vc:uses ngm:bias-detection-methods ;
vc:uses ngm:causal-inference ;
vc:uses ngm:confusion-matrix ;
vc:uses ngm:counterfactual-analysis ;
vc:uses ngm:fairness-metrics ;
vc:uses ngm:model-evaluation ;
vc:uses ngm:statistical-hypothesis-testing .
ngm:bias-auditing a skos:Concept ;
rdfs:label "Bias Auditing"@en .
ngm:bias-compensation a skos:Concept ;
rdfs:label "Bias Compensation"@en .
ngm:bias-correction a skos:Concept ;
rdfs:label "Bias Correction"@en .
ngm:bias-detection-methods a owl:Class ;
rdfs:comment "Bias Detection Methods are systematic analytical techniques for identifying algorithmic bias in AI systems through statistical hypothesis testing, fairness audits, counterfactual analysis, intersectional evaluation, and causal inference. These methods examine model predictions across protected demographic groups to detect disparate impacts, unequal error rates, and discriminatory patterns, producing bias audit reports that document severity, affected populations, and regulatory compliance status."@en ;
rdfs:label "Bias Detection Methods"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:algorithmic-auditing ;
rdfs:subClassOf ngm:fairness-assessment ;
rdfs:subClassOf _:r2990 ;
rdfs:subClassOf _:r2991 ;
rdfs:subClassOf _:r2992 ;
rdfs:subClassOf _:r2993 ;
rdfs:subClassOf _:r2994 ;
rdfs:subClassOf _:r2995 ;
rdfs:subClassOf _:r2996 ;
rdfs:subClassOf _:r2997 ;
rdfs:subClassOf _:r2998 ;
rdfs:subClassOf _:r2999 ;
rdfs:subClassOf _:r3000 ;
rdfs:subClassOf _:r3001 ;
rdfs:subClassOf _:r3002 ;
rdfs:subClassOf _:r3003 ;
rdfs:subClassOf _:r3004 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:ai-governance ;
vc:bridgesTo ngm:data-governance ;
vc:bridgesTo ngm:human-oversight ;
vc:bridgesTo ngm:regulatory-compliance ;
vc:contrastsWith ngm:automation-bias ;
vc:contrastsWith ngm:bias ;
vc:contrastsWith ngm:harmful-bias ;
vc:contrastsWith ngm:inductive-bias ;
vc:dependsOn ngm:causal-inference ;
vc:dependsOn ngm:data-governance ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:model-evaluation ;
vc:dependsOn ngm:statistical-hypothesis-testing ;
vc:enables ngm:ai-audit ;
vc:enables ngm:ai-fairness ;
vc:enables ngm:algorithmic-accountability ;
vc:enables ngm:algorithmic-impact-assessment ;
vc:enables ngm:algorithmic-transparency ;
vc:enables ngm:bias-mitigation-techniques ;
vc:enables ngm:explainability ;
vc:enables ngm:regulatory-compliance ;
vc:enables ngm:regulatory-reporting ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:algorithmic-bias ;
vc:hasPart ngm:causal-inference ;
vc:hasPart ngm:confusion-matrix ;
vc:hasPart ngm:counterfactual-analysis ;
vc:hasPart ngm:disparate-impact ;
vc:hasPart ngm:fairness-auditing-tools ;
vc:hasPart ngm:fairness-metrics ;
vc:hasPart ngm:intersectional-fairness ;
vc:hasPart ngm:statistical-hypothesis-testing ;
vc:implements ngm:algorithmic-impact-assessment ;
vc:implements ngm:bias-and-fairness ;
vc:implements ngm:fairness-assessment ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:algorithmic-accountability ;
vc:relatedTo ngm:algorithmic-bias ;
vc:relatedTo ngm:algorithmic-bias-and-variance ;
vc:relatedTo ngm:algorithmic-transparency ;
vc:relatedTo ngm:bias-and-fairness ;
vc:relatedTo ngm:bias-in-large-language-models ;
vc:relatedTo ngm:data-quality-management ;
vc:relatedTo ngm:differential-privacy ;
vc:relatedTo ngm:explainability ;
vc:requires ngm:data-quality ;
vc:requires ngm:ground-truth-labels ;
vc:requires ngm:model-evaluation ;
vc:requires ngm:protected-attribute-data ;
vc:requires ngm:protected-attributes ;
vc:requires ngm:statistical-testing ;
vc:requires ngm:training-data ;
vc:slug "bias-detection-methods" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:ieee-p-7003-2021 ;
vc:standardizedBy ngm:iso-iec-tr-24027 ;
vc:standardizedBy ngm:nist-sp-1270 ;
vc:supports ngm:ai-audit ;
vc:supports ngm:ai-ethics ;
vc:supports ngm:ai-fairness ;
vc:supports ngm:algorithmic-governance ;
vc:supports ngm:explainable-ai ;
vc:supports ngm:responsible-ai ;
vc:supports ngm:trustworthy-ai ;
vc:uses ngm:causal-inference ;
vc:uses ngm:confusion-matrix ;
vc:uses ngm:counterfactual-analysis ;
vc:uses ngm:disparate-impact ;
vc:uses ngm:fairness-metrics ;
vc:uses ngm:intersectional-fairness ;
vc:uses ngm:model-evaluation ;
vc:uses ngm:statistical-hypothesis-testing .
ngm:bias-error-component a skos:Concept ;
rdfs:label "Bias Error Component"@en .
ngm:bias-impact-assessment a skos:Concept ;
rdfs:label "Bias Impact Assessment"@en .
ngm:bias-in-ai a owl:Class ;
rdfs:comment "The systematic and unfair skewing of artificial intelligence outputs against particular groups or outcomes, arising from unrepresentative or historically prejudiced training data, flawed problem framing, proxy variables, feedback loops, and deployment context. It manifests as measurable performance and treatment disparities — in face recognition, hiring, credit, healthcare and content moderation — and is addressed through bias auditing, fairness metrics, data curation, and governance obligations now codified in regulation such as the EU AI Act."@en ;
rdfs:label "Bias in AI"@en ;
rdfs:subClassOf ngm:ai-ethics ;
vc:bridgesTo ngm:responsible-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:algorithmic-bias ;
vc:relatedTo ngm:healthcare-ai ;
vc:relatedTo ngm:synthetic-data ;
vc:slug "bias-in-ai" ;
vc:sourceDomain "governance" .
ngm:bias-in-large-language-models a owl:Class ;
rdfs:comment "Bias in Large Language Models is the systematic skew in the outputs, representations, and decisions of transformer-based foundation models (GPT-4o/4.5, Claude 3.5/4 Sonnet/Opus, Gemini 1.5/2.0 Pro, Llama 3/4, Mistral Large, Qwen 2.5, DeepSeek-V3) toward particular social groups, viewpoints, langu..."@en ;
rdfs:label "Bias in Large Language Models"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:ai-risks ;
rdfs:subClassOf ngm:ai-safety ;
rdfs:subClassOf ngm:algorithmic-bias ;
rdfs:subClassOf ngm:harmful-bias ;
rdfs:subClassOf ngm:representational-harm ;
rdfs:subClassOf ngm:sociotechnical-harm ;
rdfs:subClassOf _:r3014 ;
rdfs:subClassOf _:r3015 ;
rdfs:subClassOf _:r3016 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:contrastsWith ngm:algorithmic-bias-and-variance ;
vc:contrastsWith ngm:confirmation-bias ;
vc:contrastsWith ngm:inductive-bias ;
vc:contrastsWith ngm:selection-bias ;
vc:dependsOn ngm:common-crawl ;
vc:dependsOn ngm:large-language-model ;
vc:dependsOn ngm:neural-network-text-tokenisation ;
vc:dependsOn ngm:reddit-corpus ;
vc:dependsOn ngm:reinforcement-learning-from-human-feedback ;
vc:dependsOn ngm:supervised-fine-tuning ;
vc:dependsOn ngm:transformer-architecture ;
vc:enables ngm:cultural-homogenization ;
vc:enables ngm:discriminatory-decision-making ;
vc:enables ngm:information-asymmetry ;
vc:enables ngm:stereotype-propagation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:age-bias ;
vc:hasPart ngm:allocational-bias ;
vc:hasPart ngm:disability-bias ;
vc:hasPart ngm:gender-bias ;
vc:hasPart ngm:linguistic-bias ;
vc:hasPart ngm:political-bias ;
vc:hasPart ngm:racial-bias ;
vc:hasPart ngm:religious-bias ;
vc:hasPart ngm:representational-bias ;
vc:hasPart ngm:socioeconomic-bias ;
vc:hasPart ngm:sycophancy-bias ;
vc:implements ngm:distributional-representation-learning ;
vc:implements ngm:implicit-association-encoding ;
vc:implements ngm:preference-aggregation ;
vc:implements ngm:statistical-pattern-reproduction ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:ai-alignment ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:ai-fairness ;
vc:relatedTo ngm:ai-risks ;
vc:relatedTo ngm:bias-detection-methods ;
vc:relatedTo ngm:bias-mitigation-techniques ;
vc:relatedTo ngm:constitutional-ai-training-methodology ;
vc:relatedTo ngm:hallucination ;
vc:requires ngm:human-rater-pool ;
vc:requires ngm:instruction-tuning-dataset ;
vc:requires ngm:pretraining-corpus ;
vc:requires ngm:rlhf ;
vc:requires ngm:tokeniser ;
vc:requires ngm:training-data-composition ;
vc:slug "bias-in-large-language-models" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:acl ;
vc:standardizedBy ngm:aies ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:facct ;
vc:standardizedBy ngm:ico-ai-guidance ;
vc:standardizedBy ngm:iso-iec-tr-24027 ;
vc:standardizedBy ngm:neur-ips ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:algorithmic-accountability ;
vc:supports ngm:bias-auditing ;
vc:supports ngm:model-evaluation ;
vc:supports ngm:red-teaming ;
vc:supports ngm:responsible-ai-reporting ;
vc:uses ngm:bbq-benchmark ;
vc:uses ngm:bold-benchmark ;
vc:uses ngm:crows-pairs ;
vc:uses ngm:honest-benchmark ;
vc:uses ngm:realtoxicityprompts ;
vc:uses ngm:stereoset ;
vc:uses ngm:winobias ;
vc:uses ngm:winoqueer ;
vc:uses ngm:word-embedding-association-test .
ngm:bias-mitigation-techniques a owl:Class ;
rdfs:comment "Methods and interventions designed to reduce algorithmic bias and improve fairness in AI systems through modifications at pre-processing (data reweighting, resampling), in-processing (fairness constraints, adversarial debiasing), and post-processing (threshold optimisation) stages of the machine learning pipeline. Each approach involves tradeoffs between fairness improvement and predictive accuracy."@en ;
rdfs:label "Bias Mitigation Techniques"@en ;
rdfs:subClassOf ngm:ai-ethics ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:responsible-ai ;
rdfs:subClassOf _:r3005 ;
rdfs:subClassOf _:r3006 ;
rdfs:subClassOf _:r3007 ;
rdfs:subClassOf _:r3008 ;
rdfs:subClassOf _:r3009 ;
rdfs:subClassOf _:r3010 ;
rdfs:subClassOf _:r3011 ;
rdfs:subClassOf _:r3012 ;
rdfs:subClassOf _:r3013 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:ai-regulation ;
vc:bridgesTo ngm:data-governance ;
vc:bridgesTo ngm:human-rights-law ;
vc:contrastsWith ngm:algorithmic-bias ;
vc:contrastsWith ngm:bias-detection-methods ;
vc:contrastsWith ngm:fairness-accuracy-tradeoffs ;
vc:dependsOn ngm:algorithmic-bias ;
vc:dependsOn ngm:feature-engineering ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:supervised-learning ;
vc:enables ngm:ai-fairness ;
vc:enables ngm:algorithmic-accountability ;
vc:enables ngm:algorithmic-fairness ;
vc:enables ngm:fairness-auditing-tools ;
vc:enables ngm:responsible-ai ;
vc:enables ngm:trustworthy-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:adversarial-debiasing ;
vc:hasPart ngm:calibrated-equalised-odds ;
vc:hasPart ngm:data-reweighting ;
vc:hasPart ngm:disparate-impact-removal ;
vc:hasPart ngm:fairness-constraints ;
vc:hasPart ngm:learning-fair-representations ;
vc:hasPart ngm:prejudice-remover ;
vc:hasPart ngm:reject-option-classification ;
vc:hasPart ngm:resampling ;
vc:hasPart ngm:reweighting ;
vc:hasPart ngm:synthetic-data-generation ;
vc:hasPart ngm:threshold-optimisation ;
vc:implements ngm:algorithmic-impact-assessment ;
vc:implements ngm:demographic-parity ;
vc:implements ngm:equalised-odds ;
vc:implements ngm:fairness-constraints ;
vc:isPartOf ngm:ai-ethics ;
vc:isPartOf ngm:ai-governance-and-ethics ;
vc:isPartOf ngm:responsible-ai ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:ai-regulation ;
vc:relatedTo ngm:algorithmic-transparency ;
vc:relatedTo ngm:bias-detection-methods ;
vc:relatedTo ngm:bias-in-large-language-models ;
vc:relatedTo ngm:differential-privacy ;
vc:relatedTo ngm:eu-ai-act-regulatory-instrument ;
vc:relatedTo ngm:explainability ;
vc:relatedTo ngm:model-evaluation ;
vc:requires ngm:constrained-optimisation ;
vc:requires ngm:data-governance ;
vc:requires ngm:fairness-metrics ;
vc:requires ngm:model-evaluation ;
vc:requires ngm:protected-attributes ;
vc:requires ngm:training-data ;
vc:slug "bias-mitigation-techniques" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:ieee-p-7003-2021 ;
vc:standardizedBy ngm:iso-iec-tr-24027 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:ai-governance ;
vc:supports ngm:algorithmic-auditing ;
vc:supports ngm:automated-decision-making ;
vc:supports ngm:data-governance ;
vc:supports ngm:trustworthy-ai ;
vc:uses ngm:causal-inference ;
vc:uses ngm:constrained-optimisation ;
vc:uses ngm:feature-engineering ;
vc:uses ngm:lagrangian-relaxation ;
vc:uses ngm:machine-learning-discipline-pipeline ;
vc:uses ngm:regularisation .
ngm:bias-testing a skos:Concept ;
rdfs:label "Bias Testing"@en .
ngm:bias-variance-tradeoff a owl:Class ;
rdfs:comment "The bias-variance tradeoff is the central principle in supervised learning describing how a model's expected generalisation error decomposes into bias, variance, and irreducible noise, and how reducing one component tends to increase the other. Bias is error from overly simplistic assumptions that cause systematic underfitting, while variance is error from excessive sensitivity to the training sample that causes overfitting. Effective model selection seeks a complexity sweet spot that minimises total expected error on unseen data, balancing these competing sources rather than eliminating either alone."@en ;
rdfs:label "Bias-Variance Tradeoff"@en ;
rdfs:subClassOf ngm:hyperparameter-tuning ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf ngm:model-evaluation ;
rdfs:subClassOf ngm:statistical-learning-theory ;
rdfs:subClassOf _:r3017 ;
rdfs:subClassOf _:r3018 ;
rdfs:subClassOf _:r3019 ;
rdfs:subClassOf _:r3020 ;
rdfs:subClassOf _:r3021 ;
rdfs:subClassOf _:r3022 ;
rdfs:subClassOf _:r3023 ;
vc:contrastsWith ngm:benign-overfitting ;
vc:contrastsWith ngm:double-descent ;
vc:contrastsWith ngm:overfitting ;
vc:contrastsWith ngm:underfitting ;
vc:dependsOn ngm:loss-function ;
vc:dependsOn ngm:model-complexity ;
vc:dependsOn ngm:supervised-learning ;
vc:dependsOn ngm:training-data ;
vc:enables ngm:hyperparameter-tuning ;
vc:enables ngm:learning-curve-analysis ;
vc:enables ngm:model-evaluation ;
vc:enables ngm:model-selection ;
vc:enables ngm:regularisation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:bias-error-component ;
vc:hasPart ngm:generalisation-error ;
vc:hasPart ngm:irreducible-error ;
vc:hasPart ngm:model-complexity ;
vc:hasPart ngm:overfitting ;
vc:hasPart ngm:underfitting ;
vc:hasPart ngm:variance-error-component ;
vc:implements ngm:complexity-penalisation ;
vc:implements ngm:generalisation-error-decomposition ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:algorithmic-bias-and-variance ;
vc:relatedTo ngm:bayesian-inference ;
vc:relatedTo ngm:boosting ;
vc:relatedTo ngm:cross-validation ;
vc:relatedTo ngm:decision-tree ;
vc:relatedTo ngm:hyperparameter-tuning ;
vc:relatedTo ngm:kernel-methods ;
vc:relatedTo ngm:pac-learning ;
vc:relatedTo ngm:random-forest ;
vc:relatedTo ngm:regularisation ;
vc:relatedTo ngm:vc-dimension ;
vc:requires ngm:cross-validation ;
vc:requires ngm:loss-function ;
vc:requires ngm:statistical-learning-theory ;
vc:requires ngm:training-data ;
vc:slug "bias-variance-tradeoff" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:statistical-learning-theory ;
vc:supports ngm:dimensionality-reduction ;
vc:supports ngm:ensemble-learning ;
vc:supports ngm:feature-selection ;
vc:supports ngm:hyperparameter-tuning ;
vc:supports ngm:model-training ;
vc:uses ngm:cross-validation ;
vc:uses ngm:dropout ;
vc:uses ngm:early-stopping ;
vc:uses ngm:ensemble-methods ;
vc:uses ngm:l1-regularization ;
vc:uses ngm:l2-regularization ;
vc:uses ngm:regularisation .
ngm:bias-vector a skos:Concept ;
rdfs:label "Bias Vector"@en .
ngm:biconnected-components a skos:Concept ;
rdfs:label "Biconnected Components"@en .
ngm:bid-ask-spread a owl:Class ;
rdfs:comment "The bid-ask spread is the difference between the highest price a buyer is willing to pay (the bid) and the lowest price a seller will accept (the ask) for an asset at a given moment. It is a core measure of market liquidity and an implicit transaction cost borne by traders who cross the spread. Narrow spreads indicate liquid, competitive markets, while wide spreads reflect thin liquidity, volatility, or elevated risk for liquidity providers."@en ;
rdfs:label "Bid Ask Spread"@en ;
rdfs:subClassOf ngm:market-microstructure ;
rdfs:subClassOf _:r3027 ;
rdfs:subClassOf _:r3028 ;
rdfs:subClassOf _:r3029 ;
vc:bridgesTo ngm:finance ;
vc:dependsOn ngm:liquidity ;
vc:enables ngm:liquidity ;
vc:enables ngm:price-discovery ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:price-discovery ;
vc:isPartOf ngm:market-microstructure ;
vc:isPartOf ngm:order-book ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:high-frequency-trading ;
vc:relatedTo ngm:market-microstructure ;
vc:relatedTo ngm:price-discovery ;
vc:requires ngm:liquidity ;
vc:requires ngm:order-book ;
vc:slug "bid-ask-spread" ;
vc:sourceDomain "finance" ;
vc:uses ngm:order-book .
ngm:bid-side a skos:Concept ;
rdfs:label "Bid Side"@en .
ngm:bidirectional-communication a skos:Concept ;
rdfs:label "Bidirectional Communication"@en .
ngm:bidirectional-data-flow a skos:Concept ;
rdfs:label "Bidirectional Data Flow"@en .
ngm:bidirectional-interaction a skos:Concept ;
rdfs:label "Bidirectional Interaction"@en .
ngm:bidirectional-path-tracing a skos:Concept ;
rdfs:label "Bidirectional Path Tracing"@en .
ngm:bidirectional-reflectance-distribution-function a owl:Class ;
rdfs:label "Bidirectional Reflectance Distribution Function"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-processing ;
vc:slug "bidirectional-reflectance-distribution-function" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:bidirectional-search a skos:Concept ;
rdfs:label "Bidirectional Search"@en .
ngm:bifold-wallet a skos:Concept ;
rdfs:label "Bifold Wallet"@en .
ngm:bifrost-protocol a owl:Class ;
rdfs:comment "Bifrost is a Bitcoin-focused protocol stack associated with RGB and client-side validation, providing transport and interoperability for off-chain smart-contract state. In the RGB ecosystem it handles the peer-to-peer exchange of consignments and validation data so that asset and contract state can move between parties without publishing it on-chain. By keeping contract data client-side, it preserves Bitcoin's scalability and privacy while enabling rich asset issuance."@en ;
rdfs:label "Bifrost Protocol"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:rgb-and-client-side-validation ;
vc:slug "bifrost-protocol" ;
vc:sourceDomain "blockchain" .
ngm:bifurcation a skos:Concept ;
rdfs:label "Bifurcation"@en .
ngm:bifurcation-analysis a skos:Concept ;
rdfs:label "Bifurcation Analysis"@en .
ngm:bifurcation-theory a skos:Concept ;
rdfs:label "Bifurcation Theory"@en .
ngm:big-bang-deployment a skos:Concept ;
rdfs:label "Big Bang Deployment"@en .
ngm:big-bang-integration a skos:Concept ;
rdfs:label "Big Bang Integration"@en .
ngm:big-bench a skos:Concept ;
rdfs:label "Big Bench"@en .
ngm:big-bench-hard a skos:Concept ;
rdfs:label "Big Bench Hard"@en .
ngm:big-data a owl:Class ;
rdfs:comment "Big data denotes datasets whose volume, velocity and variety exceed the capacity of conventional single-machine tools, demanding distributed storage and parallel computation. It is characterised by horizontally scalable architectures, schema-flexible stores, and batch or streaming processing frameworks that move computation to where data resides. The term also names the discipline of extracting value from such datasets through analytics, mining and machine learning at scale."@en ;
rdfs:label "Big Data"@en ;
rdfs:subClassOf ngm:data-processing ;
rdfs:subClassOf _:r3030 ;
rdfs:subClassOf _:r3031 ;
rdfs:subClassOf _:r3032 ;
rdfs:subClassOf _:r3033 ;
vc:bridgesTo ngm:data-engineering ;
vc:dependsOn ngm:cloud-computing ;
vc:enables ngm:data-analytics ;
vc:enables ngm:predictive-analytics ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:batch-processing ;
vc:hasPart ngm:stream-processing ;
vc:implements ngm:data-pipeline ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-lake ;
vc:relatedTo ngm:data-warehouse ;
vc:relatedTo ngm:distributed-systems ;
vc:requires ngm:distributed-computing ;
vc:requires ngm:scalability ;
vc:slug "big-data" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:data-mining ;
vc:supports ngm:machine-learning-discipline ;
vc:uses ngm:apache-spark ;
vc:uses ngm:nosql-database .
ngm:big-design-up-front a skos:Concept ;
rdfs:label "Big Design Up Front"@en .
ngm:big-tech-capex a skos:Concept ;
rdfs:label "Big Tech Capex"@en .
ngm:bigclam a skos:Concept ;
rdfs:label "Bigclam"@en .
ngm:bigcode-project a skos:Concept ;
rdfs:label "Bigcode Project"@en .
ngm:bigquery a skos:Concept ;
rdfs:label "Bigquery"@en .
ngm:bilateral-netting a skos:Concept ;
rdfs:label "Bilateral Netting"@en .
ngm:bilinear-pairing a owl:Class ;
rdfs:comment "A bilinear pairing is a mathematical map between two groups to a third group that is linear in each argument separately, commonly realised as the Weil or Tate pairing on elliptic curves over finite fields. Bilinear pairings enable advanced cryptographic constructions including identity-based encryption, short signature schemes (BLS), and zero-knowledge proof systems. They form the algebraic foundation of pairing-based cryptography, which underpins threshold signatures and SNARKs used in modern blockchain protocols."@en ;
rdfs:label "Bilinear Pairing"@en ;
rdfs:subClassOf ngm:security ;
rdfs:subClassOf _:r3034 ;
rdfs:subClassOf _:r3035 ;
vc:contrastsWith ngm:rsa ;
vc:dependsOn ngm:bls12-381-curve ;
vc:dependsOn ngm:bn254-curve ;
vc:enables ngm:bls-signature ;
vc:enables ngm:identity-based-encryption ;
vc:enables ngm:threshold-signature-scheme ;
vc:enables ngm:zero-knowledge-proof ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ate-pairing ;
vc:hasPart ngm:weil-pairing ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:cryptographic-accumulator ;
vc:relatedTo ngm:digital-signature ;
vc:relatedTo ngm:multi-party-computation ;
vc:requires ngm:elliptic-curve-cryptography ;
vc:requires ngm:finite-field-arithmetic ;
vc:slug "bilinear-pairing" ;
vc:sourceDomain "security" ;
vc:supports ngm:blockchain ;
vc:supports ngm:zk-snark ;
vc:uses ngm:pairing-based-cryptography ;
vc:uses ngm:public-key-cryptography .
ngm:bilingual-evaluation-data a skos:Concept ;
rdfs:label "Bilingual Evaluation Data"@en .
ngm:bilingual-rag-hallucination-mitigation-framework a owl:Class ;
rdfs:comment "Jing is a multi-agent AI framework designed to minimise hallucination in Chinese-English bilingual retrieval-augmented generation (RAG) pipelines, specifically applied to emotional-support chatbots for end-of-life counselling and palliative care. The system combines multiple large language models with open-source text-to-speech engines and real-time 3D avatars to deliver culturally sensitive, affectively aware conversational companions, initially targeting Japanese VR screen deployment contexts. Its multi-agent architecture distributes validation, retrieval, and generation tasks across specialised model instances to improve factual grounding and reduce hallucinated responses in high-stakes care settings."@en ;
rdfs:label "Bilingual RAG Hallucination Mitigation Framework"@en ;
rdfs:subClassOf ngm:software-engineering ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.7"^^xsd:float ;
vc:relatedTo ngm:digital-avatar ;
vc:relatedTo ngm:emotional-intelligence ;
vc:relatedTo ngm:healthcare-ai ;
vc:slug "bilingual-rag-hallucination-mitigation-framework" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:virtual-reality-applications ;
vc:uses ngm:large-language-models ;
vc:uses ngm:multi-agent-systems ;
vc:uses ngm:retrieval-augmented-generation ;
vc:uses ngm:text-to-speech .
ngm:bill-of-rights a skos:Concept ;
rdfs:label "Bill Of Rights"@en .
ngm:bim-software a owl:Class ;
rdfs:comment "Specialized applications for Building Information Modeling that enable the generation, management, and collaboration on digital representations of physical and functional characteristics of buildings and infrastructure, supporting the entire asset lifecycle from design through construction to ope..."@en ;
rdfs:label "BIM Software"@en ;
rdfs:subClassOf ngm:design-software ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf _:r2604 ;
rdfs:subClassOf _:r2605 ;
skos:broader ngm:sc-platform-and-environment ;
vc:enables ngm:3d-modelling ;
vc:enables ngm:construction-coordination ;
vc:enables ngm:facility-management ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:cad-capabilities ;
vc:requires ngm:collaboration-tools ;
vc:requires ngm:data-management ;
vc:slug "bim-software" ;
vc:sourceDomain "spatial-computing" .
ngm:bim-virtual-model a owl:Class ;
rdfs:comment "A comprehensive 3D digital representation of a building or infrastructure asset created through Building Information Modeling, containing geometric data, material specifications, and functional characteristics that enable visualization, simulation, quantity take-offs, and clash detection througho..."@en ;
rdfs:label "BIM Virtual Model"@en ;
rdfs:subClassOf ngm:3-d-model ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf _:r2606 ;
rdfs:subClassOf _:r2607 ;
rdfs:subClassOf _:r2608 ;
skos:broader ngm:sc-platform-and-environment ;
vc:enables ngm:clash-detection ;
vc:enables ngm:design-visualization ;
vc:enables ngm:simulation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:bim-software ;
vc:requires ngm:design-data ;
vc:requires ngm:standards ;
vc:slug "bim-virtual-model" ;
vc:sourceDomain "spatial-computing" .
ngm:bimanual-manipulation a skos:Concept ;
rdfs:label "Bimanual Manipulation"@en .
ngm:binance a owl:Class ;
rdfs:comment "Binance is a centralised cryptocurrency exchange founded in 2017 by Changpeng Zhao (CZ) and Yi He, which rapidly grew to become one of the highest-volume digital-asset trading venues globally. It provides spot trading, perpetual and futures derivatives, margin lending, staking, savings products, and a token launchpad across hundreds of supported assets. Binance created the BNB token as a native utility and fee-discount instrument, and subsequently developed BNB Chain, an EVM-compatible Layer-1 blockchain that hosts a substantial decentralised-finance and Web3 application ecosystem. The exchange has faced extensive regulatory scrutiny across multiple jurisdictions, including a landmark 2023 settlement with the United States Department of Justice and FinCEN, resulting in substantial financial penalties and a change in executive leadership."@en ;
rdfs:label "Binance"@en ;
rdfs:subClassOf ngm:digital-asset ;
rdfs:subClassOf _:r3036 ;
rdfs:subClassOf _:r3037 ;
rdfs:subClassOf _:r3038 ;
rdfs:subClassOf _:r3039 ;
vc:bridgesTo ngm:de-fi ;
vc:bridgesTo ngm:digital-identity ;
vc:bridgesTo ngm:non-fungible-token ;
vc:contrastsWith ngm:coinbase ;
vc:contrastsWith ngm:decentralised-exchange ;
vc:contrastsWith ngm:kraken ;
vc:dependsOn ngm:blockchain ;
vc:dependsOn ngm:proof-of-staked-authority ;
vc:dependsOn ngm:smart-contract ;
vc:enables ngm:de-fi ;
vc:enables ngm:derivatives-trading ;
vc:enables ngm:spot-trading ;
vc:enables ngm:staking ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:binance-launchpad ;
vc:hasPart ngm:binance-smart-chain ;
vc:hasPart ngm:bnb-chain ;
vc:hasPart ngm:bnb-token ;
vc:isPartOf ngm:digital-asset-domain ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:aml ;
vc:relatedTo ngm:cryptocurrency ;
vc:relatedTo ngm:digital-asset ;
vc:relatedTo ngm:financial-regulation ;
vc:relatedTo ngm:web3 ;
vc:requires ngm:kyc-aml-compliance ;
vc:requires ngm:liquidity-provision ;
vc:requires ngm:order-book ;
vc:slug "binance" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:crypto-wallet ;
vc:uses ngm:ethereum-smart-contract-platform-virtual-machine ;
vc:uses ngm:matching-engine .
ngm:binance-launchpad a skos:Concept ;
rdfs:label "Binance Launchpad"@en .
ngm:binance-settlement-2023 a skos:Concept ;
rdfs:label "Binance Settlement 2023"@en .
ngm:binance-smart-chain a skos:Concept ;
rdfs:label "Binance Smart Chain"@en .
ngm:binary-buffer a owl:Class ;
rdfs:comment "A contiguous region of memory used to temporarily store binary data during transfer, processing, or rendering operations, serving as an intermediary between data sources and destinations in graphics pipelines, network communications, and computational workflows."@en ;
rdfs:label "Binary Buffer"@en ;
rdfs:subClassOf ngm:data-structure ;
rdfs:subClassOf ngm:sc-standards-and-interop ;
skos:broader ngm:sc-standards-and-interop ;
vc:bridgesTo ngm:data-structure ;
vc:enables ngm:data-transfer ;
vc:enables ngm:graphics-rendering ;
vc:enables ngm:stream-processing ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:buffer-management ;
vc:requires ngm:data-formatting ;
vc:requires ngm:memory-allocation ;
vc:slug "binary-buffer" ;
vc:sourceDomain "spatial-computing" .
ngm:binary-classification a skos:Concept ;
rdfs:label "Binary Classification"@en .
ngm:binary-data-mask a owl:Class ;
rdfs:label "Binary Data Mask"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-data-quality ;
vc:slug "binary-data-mask" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:binary-encoding a owl:Class ;
rdfs:comment "A data representation format that converts information into sequences of binary digits (0s and 1s) for efficient storage, transmission, and processing, offering compact machine-friendly representations that optimize bandwidth, reduce latency, and enable cross-platform data exchange."@en ;
rdfs:label "Binary Encoding"@en ;
rdfs:subClassOf ngm:data-format ;
rdfs:subClassOf ngm:sc-standards-and-interop ;
rdfs:subClassOf _:r3040 ;
skos:broader ngm:sc-standards-and-interop ;
vc:bridgesTo ngm:data-format ;
vc:enables ngm:data-serialization ;
vc:enables ngm:efficient-storage ;
vc:enables ngm:transmission-network ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:encoding-rules ;
vc:requires ngm:parser-implementation ;
vc:requires ngm:schema-definition ;
vc:slug "binary-encoding" ;
vc:sourceDomain "spatial-computing" .
ngm:binary-format a skos:Concept ;
rdfs:label "Binary Format"@en .
ngm:binaural-audio a owl:Class ;
rdfs:comment "Binaural audio is two-channel sound designed to reproduce the directional and spatial cues a listener would experience naturally, delivering an immersive three-dimensional image over headphones. It can be captured with a dummy head or in-ear microphones, or synthesised by convolving sources with head-related transfer functions. By preserving interaural time and level differences and pinna spectral cues, binaural audio conveys not just left-right panning but full surrounding placement including elevation."@en ;
rdfs:label "Binaural Audio"@en ;
rdfs:subClassOf ngm:spatial-audio ;
rdfs:subClassOf _:r3041 ;
rdfs:subClassOf _:r3042 ;
vc:enables ngm:immersive-audio ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:head-related-transfer-function ;
vc:implements ngm:spatial-audio ;
vc:isPartOf ngm:spatial-audio ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:ambisonics ;
vc:relatedTo ngm:audio-codec ;
vc:relatedTo ngm:audio-system ;
vc:relatedTo ngm:microphone-array ;
vc:requires ngm:digital-signal-processor ;
vc:slug "binaural-audio" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:augmented-reality ;
vc:supports ngm:immersive-audio ;
vc:supports ngm:virtual-reality ;
vc:uses ngm:digital-signal-processing ;
vc:uses ngm:signal-processing .
ngm:binaural-rendering a owl:Class ;
rdfs:comment "Binaural rendering is the audio signal processing technique that synthesises a three-dimensional sound field deliverable over standard headphones by convolving audio sources with head-related transfer functions (HRTFs) that model the acoustic filtering imposed by the human head, pinnae, and torso. The result is the perceptual illusion of sounds emanating from specific spatial locations outside the headphones, enabling immersive audio experiences in virtual and augmented reality environments."@en ;
rdfs:label "Binaural Rendering"@en ;
rdfs:subClassOf ngm:spatial-audio ;
vc:enables ngm:immersive-audio ;
vc:enables ngm:immersive-experience ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:audio-spatialization ;
vc:relatedTo ngm:extended-reality-xr ;
vc:slug "binaural-rendering" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:audio-processing ;
vc:uses ngm:convolution .
ngm:binding-ai-regulation a skos:Concept ;
rdfs:label "Binding AI Regulation"@en .
ngm:binding-corporate-rules a owl:Class ;
rdfs:comment "Binding Corporate Rules (BCRs) are an intra-group data transfer mechanism approved by EU data protection authorities that allow multinational corporate groups to transfer personal data from the European Economic Area to group entities in third countries lacking an EU adequacy decision, provided the group adopts and enforces a comprehensive, legally binding internal data protection code. BCRs are assessed and approved by a lead supervisory authority under the GDPR framework."@en ;
rdfs:label "Binding Corporate Rules"@en ;
rdfs:subClassOf ngm:cross-border-data-transfer-rule ;
rdfs:subClassOf _:r3043 ;
rdfs:subClassOf _:r3044 ;
vc:contrastsWith ngm:standard-contractual-clauses ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:data-sovereignty ;
vc:requires ngm:data-governance-framework ;
vc:requires ngm:gdpr ;
vc:slug "binding-corporate-rules" ;
vc:sourceDomain "governance" ;
vc:supports ngm:data-protection ;
vc:supports ngm:privacy-by-design .
ngm:binding-regulation a skos:Concept ;
rdfs:label "Binding Regulation"@en .
ngm:binned-data-state a owl:Class ;
rdfs:label "Binned Data State"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-processing ;
vc:slug "binned-data-state" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:bio-inspired-robotics a skos:Concept ;
rdfs:label "Bio Inspired Robotics"@en .
ngm:bio-terror a owl:Class ;
rdfs:comment "Bioterrorism (biological terrorism) is the deliberate use, threat, or weaponisation of pathogenic microorganisms (bacteria, viruses, fungi, prions), biological toxins, or genetically engineered agents by state or non-state actors to cause mass casualties, generate fear, coerce governments, or des..."@en ;
rdfs:label "Bio Terror"@en ;
rdfs:subClassOf ngm:ai-risks ;
rdfs:subClassOf ngm:biosecurity ;
rdfs:subClassOf ngm:dual-use-research ;
rdfs:subClassOf ngm:global-catastrophic-risk ;
rdfs:subClassOf ngm:infra-legal-and-regulatory ;
rdfs:subClassOf ngm:pandemic-preparedness ;
rdfs:subClassOf ngm:weapons-of-mass-destruction ;
rdfs:subClassOf _:r3045 ;
skos:broader ngm:infra-legal-and-regulatory ;
vc:bridgesTo ngm:biosecurity ;
vc:bridgesTo ngm:governance ;
vc:contrastsWith ngm:biosafety ;
vc:contrastsWith ngm:open-science ;
vc:contrastsWith ngm:pandemic-preparedness ;
vc:contrastsWith ngm:vaccine-development ;
vc:dependsOn ngm:ai-governance ;
vc:dependsOn ngm:biological-weapons-convention ;
vc:dependsOn ngm:international-health-regulations ;
vc:dependsOn ngm:national-biosecurity-strategy ;
vc:dependsOn ngm:who-biosafety-guidelines ;
vc:enables ngm:coercive-statecraft ;
vc:enables ngm:critical-infrastructure-attack ;
vc:enables ngm:mass-casualty-event ;
vc:enables ngm:pandemic-amplification ;
vc:enables ngm:societal-disruption ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:agroterrorism ;
vc:hasPart ngm:amerithrax-2001 ;
vc:hasPart ngm:aum-shinrikyo-biological-programme ;
vc:hasPart ngm:biological-toxin ;
vc:hasPart ngm:bioweapon-delivery-system ;
vc:hasPart ngm:information-hazard ;
vc:hasPart ngm:pathogen-weaponisation ;
vc:hasPart ngm:rajneeshee-salmonella-attack-1984 ;
vc:hasPart ngm:select-agent ;
vc:hasPart ngm:soviet-biopreparat-programme ;
vc:hasPart ngm:sverdlovsk-anthrax-release-1979 ;
vc:hasPart ngm:synthetic-biology-threat ;
vc:implements ngm:barda-medical-countermeasures ;
vc:implements ngm:biodefence-stockpiling ;
vc:implements ngm:biosafety-level-bsl-1-4-framework ;
vc:implements ngm:cdc-category-a-b-c-agent-classification ;
vc:implements ngm:select-agent-programme ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:ai-risks ;
vc:relatedTo ngm:ai-scrapers ;
vc:relatedTo ngm:artificial-general-intelligence ;
vc:relatedTo ngm:australia-group ;
vc:relatedTo ngm:biosecurity ;
vc:relatedTo ngm:brain-computer-interfaces ;
vc:relatedTo ngm:cambridge-biosecurity-hub ;
vc:relatedTo ngm:cdc-biowatch-programme ;
vc:relatedTo ngm:cdc-select-agent-program ;
vc:relatedTo ngm:cognitive-ai ;
vc:relatedTo ngm:cold-chain-monitoring ;
vc:relatedTo ngm:competition-in-ai ;
vc:relatedTo ngm:constitutional-ai-training-methodology-language-model-family ;
vc:relatedTo ngm:crispr-gene-editing ;
vc:relatedTo ngm:distributed-computing ;
vc:relatedTo ngm:dstl-porton-down ;
vc:relatedTo ngm:dual-use-research ;
vc:relatedTo ngm:embodied-minds ;
vc:relatedTo ngm:federal-select-agent-program ;
vc:relatedTo ngm:global-catastrophic-risk ;
vc:relatedTo ngm:govai ;
vc:relatedTo ngm:harvard-belfer-center ;
vc:relatedTo ngm:ibbis ;
vc:relatedTo ngm:imperial-college-london ;
vc:relatedTo ngm:johns-hopkins-center-for-health-security ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:large-scale-pretrained-foundation-model ;
vc:relatedTo ngm:national-biosecurity-centre-harlow ;
vc:relatedTo ngm:nhs-syndromic-surveillance-system ;
vc:relatedTo ngm:nti-bio ;
vc:relatedTo ngm:pandemic-preparedness ;
vc:relatedTo ngm:rand-corporation ;
vc:relatedTo ngm:synthetic-biology ;
vc:relatedTo ngm:ukhsa ;
vc:relatedTo ngm:ukhsa-genomic-surveillance ;
vc:relatedTo ngm:unoda ;
vc:relatedTo ngm:who ;
vc:requires ngm:aerosol-dispersal-mechanism ;
vc:requires ngm:biosafety-level-laboratory ;
vc:requires ngm:dual-use-equipment ;
vc:requires ngm:financing ;
vc:requires ngm:pathogen-access ;
vc:requires ngm:technical-expertise ;
vc:slug "bio-terror" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:australia-group-export-controls ;
vc:standardizedBy ngm:biological-weapons-convention-bwc-1972 ;
vc:standardizedBy ngm:cartagena-protocol-on-biosafety ;
vc:standardizedBy ngm:cdc-select-agent-regulations ;
vc:standardizedBy ngm:nsabb-durc-policy ;
vc:standardizedBy ngm:un-security-council-resolution-1540 ;
vc:standardizedBy ngm:who-biosafety-guidelines ;
vc:supports ngm:biodefence-research ;
vc:supports ngm:intelligence-surveillance-reconnaissance ;
vc:supports ngm:pandemic-preparedness ;
vc:supports ngm:public-health-surveillance ;
vc:uses ngm:ai-protein-design ;
vc:uses ngm:automated-biofoundry ;
vc:uses ngm:crispr-gene-editing ;
vc:uses ngm:gain-of-function-research ;
vc:uses ngm:large-language-models ;
vc:uses ngm:synthetic-biology .
ngm:biocompatible-encapsulation a skos:Concept ;
rdfs:label "Biocompatible Encapsulation"@en .
ngm:biocompatible-engineering a skos:Concept ;
rdfs:label "Biocompatible Engineering"@en .
ngm:biocompatible-materials a skos:Concept ;
rdfs:label "Biocompatible Materials"@en .
ngm:biocomputing a skos:Concept ;
rdfs:label "Biocomputing"@en .
ngm:biodefence-research a skos:Concept ;
rdfs:label "Biodefence Research"@en .
ngm:biodefence-stockpiling a skos:Concept ;
rdfs:label "Biodefence Stockpiling"@en .
ngm:biodiversity-co-benefits a skos:Concept ;
rdfs:label "Biodiversity Co Benefits"@en .
ngm:biodiversity-conservation a owl:Class ;
rdfs:comment "Biodiversity conservation is the protection, restoration and sustainable management of the variety of life on Earth — genes, species, habitats and ecosystems — to maintain ecological function and resilience. It combines protected areas, species recovery, habitat restoration, sustainable use and policy instruments, increasingly informed by monitoring data and remote sensing. As a pillar of environmental sustainability, it is closely linked to climate change mitigation, ecosystem services and emerging biodiversity finance markets."@en ;
rdfs:label "Biodiversity Conservation"@en ;
rdfs:subClassOf ngm:environmental-sustainability ;
rdfs:subClassOf _:r3046 ;
vc:bridgesTo ngm:carbon-credits ;
vc:contrastsWith ngm:carbon-offset ;
vc:dependsOn ngm:climate-change-mitigation ;
vc:enables ngm:climate-change-mitigation ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:environmental-sustainability ;
vc:isPartOf ngm:environmental-sustainability ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:climate-finance ;
vc:relatedTo ngm:environmental-monitoring ;
vc:relatedTo ngm:esg ;
vc:requires ngm:environmental-monitoring ;
vc:slug "biodiversity-conservation" ;
vc:sourceDomain "governance" ;
vc:supports ngm:environmental-sustainability ;
vc:supports ngm:esg ;
vc:uses ngm:environmental-monitoring .
ngm:biodiversity-credit-markets a skos:Concept ;
rdfs:label "Biodiversity Credit Markets"@en .
ngm:biodiversity-credits a skos:Concept ;
rdfs:label "Biodiversity Credits"@en .
ngm:biodiversity-monitoring a owl:Class ;
rdfs:label "Biodiversity Monitoring"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-applications ;
vc:slug "biodiversity-monitoring" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:bioethics a skos:Concept ;
rdfs:label "Bioethics"@en .
ngm:biofeedback-systems a skos:Concept ;
rdfs:label "Biofeedback Systems"@en .
ngm:bioinformatics a owl:Class ;
rdfs:comment "Bioinformatics is the interdisciplinary field that develops computational methods and software to acquire, store, analyse, and interpret biological data, especially molecular sequences and structures. It combines biology, computer science, statistics, and increasingly machine learning to address problems such as genome assembly, sequence alignment, protein structure prediction, and the inference of biological networks. As high-throughput sequencing and imaging generate vast datasets, bioinformatics provides the algorithms and pipelines that turn raw measurements into testable biological insight."@en ;
rdfs:label "Bioinformatics"@en ;
rdfs:subClassOf ngm:computational-biology ;
rdfs:subClassOf ngm:data-science ;
rdfs:subClassOf ngm:scientific-computing ;
rdfs:subClassOf _:r3047 ;
rdfs:subClassOf _:r3048 ;
rdfs:subClassOf _:r3049 ;
rdfs:subClassOf _:r3050 ;
vc:bridgesTo ngm:biology ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:contrastsWith ngm:experimental-biochemistry ;
vc:contrastsWith ngm:wet-laboratory-biology ;
vc:dependsOn ngm:biology ;
vc:dependsOn ngm:computational-biology ;
vc:dependsOn ngm:computer-science ;
vc:dependsOn ngm:statistics ;
vc:enables ngm:drug-discovery ;
vc:enables ngm:genomics ;
vc:enables ngm:precision-medicine ;
vc:enables ngm:protein-structure-prediction ;
vc:enables ngm:synthetic-biology ;
vc:enables ngm:systems-biology ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:genomics ;
vc:hasPart ngm:metagenomics ;
vc:hasPart ngm:phylogenetics ;
vc:hasPart ngm:proteomics ;
vc:hasPart ngm:sequence-alignment ;
vc:hasPart ngm:structural-bioinformatics ;
vc:hasPart ngm:transcriptomics ;
vc:implements ngm:genome-assembly ;
vc:implements ngm:phylogenetic-analysis ;
vc:implements ngm:sequence-alignment ;
vc:implements ngm:variant-calling ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:alphafold ;
vc:relatedTo ngm:bert ;
vc:relatedTo ngm:computational-biology ;
vc:relatedTo ngm:data-science ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:scientific-machine-learning ;
vc:requires ngm:big-data ;
vc:requires ngm:biological-database ;
vc:requires ngm:dna-sequencing ;
vc:requires ngm:gpu ;
vc:requires ngm:high-performance-computing ;
vc:requires ngm:proteomics ;
vc:slug "bioinformatics" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:embl-ebi ;
vc:standardizedBy ngm:ncbi ;
vc:standardizedBy ngm:pdb ;
vc:standardizedBy ngm:uniprot ;
vc:supports ngm:evolutionary-biology ;
vc:supports ngm:healthcare ;
vc:supports ngm:precision-agriculture ;
vc:supports ngm:precision-medicine ;
vc:supports ngm:systems-biology ;
vc:uses ngm:data-science ;
vc:uses ngm:deep-learning ;
vc:uses ngm:graph-neural-network ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:statistics ;
vc:uses ngm:transformer-architecture .
ngm:biological-anchors-model a skos:Concept ;
rdfs:label "Biological Anchors Model"@en .
ngm:biological-database a skos:Concept ;
rdfs:label "Biological Database"@en .
ngm:biological-toxin a skos:Concept ;
rdfs:label "Biological Toxin"@en .
ngm:biological-weapons-convention a skos:Concept ;
rdfs:label "Biological Weapons Convention"@en .
ngm:biological-weapons-convention-bwc-1972 a skos:Concept ;
rdfs:label "Biological Weapons Convention Bwc 1972"@en .
ngm:biologically-inspired-robotics a skos:Concept ;
rdfs:label "Biologically Inspired Robotics"@en .
ngm:biologics-logistics a skos:Concept ;
rdfs:label "Biologics Logistics"@en .
ngm:biology a skos:Concept ;
rdfs:label "Biology"@en .
ngm:biomarker-discovery a owl:Class ;
rdfs:comment "Biomarker discovery is the process of identifying measurable biological indicators, such as gene expression patterns, proteins or metabolites, that correlate with a disease state, treatment response or physiological process. Machine learning methods applied to genomic, proteomic and clinical datasets accelerate this process by detecting patterns across high-dimensional biological data that would be impractical to find manually. Validated biomarkers underpin precision medicine and inform drug discovery by identifying targets and patient stratification criteria."@en ;
rdfs:label "Biomarker Discovery"@en ;
rdfs:subClassOf ngm:bioinformatics ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:slug "biomarker-discovery" ;
vc:sourceDomain "artificial-intelligence" .
ngm:biomass-energy a skos:Concept ;
rdfs:label "Biomass Energy"@en .
ngm:biomechanical-analysis a skos:Concept ;
rdfs:label "Biomechanical Analysis"@en .
ngm:biomechanical-data a skos:Concept ;
rdfs:label "Biomechanical Data"@en .
ngm:biomechanical-simulation a skos:Concept ;
rdfs:label "Biomechanical Simulation"@en .
ngm:biomechanics a owl:Class ;
rdfs:comment "Biomechanics is the study of the mechanical principles governing biological systems, analysing forces, motion and structure in living organisms. In robotics it informs the design of actuators, limbs and gaits that emulate or assist biological movement, bridging physiology and mechanical engineering. It supplies the models of kinematics and dynamics used to make legged, humanoid and wearable machines move efficiently and safely."@en ;
rdfs:label "Biomechanics"@en ;
rdfs:subClassOf ngm:robo-actuation-and-control ;
rdfs:subClassOf ngm:robotics ;
rdfs:subClassOf _:r3051 ;
rdfs:subClassOf _:r3052 ;
skos:broader ngm:robo-actuation-and-control ;
skos:broader ngm:robotics ;
vc:bridgesTo ngm:motion-planning ;
vc:bridgesTo ngm:robot-control ;
vc:enables ngm:exoskeleton ;
vc:enables ngm:rehabilitation-robotics ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:actuator ;
vc:relatedTo ngm:inverse-kinematics ;
vc:relatedTo ngm:torque-control ;
vc:requires ngm:dynamics ;
vc:requires ngm:kinematics ;
vc:slug "biomechanics" ;
vc:sourceDomain "robotics" ;
vc:supports ngm:locomotion ;
vc:uses ngm:force-control ;
vc:uses ngm:series-elastic-actuator .
ngm:biomedical-data a skos:Concept ;
rdfs:label "Biomedical Data"@en .
ngm:biomedical-engineering a owl:Class ;
rdfs:comment "Biomedical engineering is the discipline that applies engineering principles, materials, and computational methods to medicine and biology in order to design devices, systems, and processes that diagnose, monitor, treat, or restore human function. It spans medical instrumentation, biomaterials, prosthetics and exoskeletons, rehabilitation robotics, and biosignal processing, bridging mechanical, electrical, and control engineering with the life sciences and clinical practice."@en ;
rdfs:label "Biomedical Engineering"@en ;
rdfs:subClassOf ngm:medical-robot ;
rdfs:subClassOf ngm:robotics ;
rdfs:subClassOf _:r3053 ;
rdfs:subClassOf _:r3054 ;
skos:broader ngm:robotics ;
vc:bridgesTo ngm:control-theory ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:dependsOn ngm:signal-processing ;
vc:enables ngm:exoskeleton ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:prosthetics ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:rehabilitation-robotics ;
vc:relatedTo ngm:robotic-system ;
vc:requires ngm:control-theory ;
vc:slug "biomedical-engineering" ;
vc:sourceDomain "robotics" ;
vc:supports ngm:prosthetics ;
vc:supports ngm:rehabilitation-robotics ;
vc:uses ngm:sensor-fusion ;
vc:uses ngm:signal-processing .
ngm:biomedical-informatics a skos:Concept ;
rdfs:label "Biomedical Informatics"@en .
ngm:biomedical-nlp a skos:Concept ;
rdfs:label "Biomedical NLP"@en .
ngm:biomedical-ontology a skos:Concept ;
rdfs:label "Biomedical Ontology"@en .
ngm:biomedical-research a skos:Concept ;
rdfs:label "Biomedical Research"@en .
ngm:biomedical-text-mining a skos:Concept ;
rdfs:label "Biomedical Text Mining"@en .
ngm:biomedical-trec a skos:Concept ;
rdfs:label "Biomedical Trec"@en .
ngm:biometric-analysis a skos:Concept ;
rdfs:label "Biometric Analysis"@en .
ngm:biometric-authentication a owl:Class ;
rdfs:comment "Biometric authentication is an identity verification method that uses measurable, unique physiological or behavioural characteristics of an individual — such as fingerprints, facial geometry, iris patterns, voice, or behavioural signals like keystroke dynamics — to confirm the claimed identity of a subject. Unlike password-based or token-based mechanisms, biometric credentials are inherent to the individual and cannot be forgotten, shared, or easily replicated, though they introduce irreversibility concerns because compromised biometric data cannot be reset. A complete system comprises enrolment, secure template storage (typically on-device in a secure enclave), a matching engine evaluated by false acceptance rate and false rejection rate, and presentation attack detection to counter spoofing. Biometric authentication underpins modern identity assurance frameworks such as FIDO2/WebAuthn, eIDAS 2.0 digital identity wallets, and biometric border control systems worldwide."@en ;
rdfs:label "Biometric Authentication"@en ;
rdfs:subClassOf ngm:authentication ;
rdfs:subClassOf _:r3055 ;
rdfs:subClassOf _:r3056 ;
rdfs:subClassOf _:r3057 ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:bridgesTo ngm:on-device-inference ;
vc:contrastsWith ngm:password-authentication ;
vc:contrastsWith ngm:token-based-authentication ;
vc:enables ngm:continuous-authentication ;
vc:enables ngm:digital-identity-verification ;
vc:enables ngm:multi-factor-authentication ;
vc:enables ngm:passwordless-authentication ;
vc:enables ngm:zero-trust-architecture ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:fido2 ;
vc:implements ngm:web-authn ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:facial-recognition ;
vc:relatedTo ngm:gdpr ;
vc:relatedTo ngm:identity-management ;
vc:relatedTo ngm:self-sovereign-identity ;
vc:requires ngm:data-protection ;
vc:requires ngm:hardware-security-module ;
vc:requires ngm:privacy-by-design ;
vc:slug "biometric-authentication" ;
vc:sourceDomain "security" ;
vc:uses ngm:biometric-binding-mechanism ;
vc:uses ngm:biometric-verification ;
vc:uses ngm:feature-extraction ;
vc:uses ngm:presentation-attack-detection ;
vc:uses ngm:secure-enclave .
ngm:biometric-binding-mechanism a owl:Class ;
rdfs:comment "Physical hardware device that captures and verifies biometric traits (fingerprints, iris patterns, facial geometry) to bind digital identities to authenticated users."@en ;
rdfs:label "Biometric Binding Mechanism"@en ;
rdfs:subClassOf ngm:sc-governance-and-safety ;
rdfs:subClassOf _:r3058 ;
rdfs:subClassOf _:r3059 ;
rdfs:subClassOf _:r3060 ;
rdfs:subClassOf _:r3061 ;
rdfs:subClassOf _:r3062 ;
rdfs:subClassOf _:r3063 ;
rdfs:subClassOf _:r3064 ;
rdfs:subClassOf _:r3065 ;
skos:broader ngm:sc-governance-and-safety ;
vc:dependsOn ngm:authentication-server ;
vc:dependsOn ngm:biometric-template-database ;
vc:dependsOn ngm:cryptographic-infrastructure ;
vc:enables ngm:access-control ;
vc:enables ngm:identity-verification ;
vc:enables ngm:multi-factor-authentication ;
vc:enables ngm:non-repudiation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:facial-recognition ;
vc:hasPart ngm:fingerprint-scanner ;
vc:hasPart ngm:iris-recognition-camera ;
vc:hasPart ngm:secure-enclave ;
vc:hasPart ngm:template-matching-processor ;
vc:isPartOf ngm:identity-management-system ;
vc:isPartOf ngm:zero-trust-architecture ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:anti-spoofing-module ;
vc:requires ngm:encrypted-storage ;
vc:requires ngm:infrared-illuminator ;
vc:requires ngm:optical-sensor-array ;
vc:requires ngm:power-supply ;
vc:slug "biometric-binding-mechanism" ;
vc:sourceDomain "spatial-computing" .
ngm:biometric-classification a skos:Concept ;
rdfs:label "Biometric Classification"@en .
ngm:biometric-data a owl:Class ;
rdfs:comment "Biometric data is a category of personal data comprising unique physiological or behavioural characteristics of an individual — such as fingerprints, facial geometry, iris patterns, voice prints, gait, and keystroke dynamics — that can be used to identify or authenticate that person. Under data protection frameworks such as GDPR, biometric data processed for identification purposes is classified as a special category of personal data subject to heightened protection. Its irrevocable nature (an individual cannot change their biometrics) makes breaches particularly consequential."@en ;
rdfs:label "Biometric Data"@en ;
rdfs:subClassOf ngm:personal-data ;
rdfs:subClassOf _:r3066 ;
rdfs:subClassOf _:r3067 ;
vc:bridgesTo ngm:security ;
vc:contrastsWith ngm:session-key ;
vc:dependsOn ngm:data-management ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:enables ngm:digital-identity ;
vc:enables ngm:policy-information-point ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:personal-data ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:governance ;
vc:relatedTo ngm:privacy ;
vc:requires ngm:access-control ;
vc:requires ngm:data-schema ;
vc:slug "biometric-data" ;
vc:sourceDomain "governance" ;
vc:supports ngm:policy-administration-point ;
vc:supports ngm:session-management ;
vc:uses ngm:encryption ;
vc:uses ngm:statistical-analysis .
ngm:biometric-databases a skos:Concept ;
rdfs:label "Biometric Databases"@en .
ngm:biometric-identification a owl:Class ;
rdfs:comment "Biometric identification is the recognition of an individual by measuring and matching distinctive physiological or behavioural characteristics, such as fingerprints, facial geometry, iris patterns, voice or gait. It captures a sample, extracts a feature template and compares it against enrolled templates to verify a claimed identity (one-to-one) or identify an unknown subject (one-to-many). It underpins access control, border management and device authentication, and raises significant privacy considerations."@en ;
rdfs:label "Biometric Identification"@en ;
rdfs:subClassOf ngm:identity-verification ;
rdfs:subClassOf _:r3068 ;
rdfs:subClassOf _:r3069 ;
rdfs:subClassOf _:r3070 ;
rdfs:subClassOf _:r3071 ;
vc:bridgesTo ngm:authentication ;
vc:bridgesTo ngm:identity-verification ;
vc:contrastsWith ngm:privacy-preserving ;
vc:dependsOn ngm:neural-network ;
vc:enables ngm:authentication ;
vc:enables ngm:liveness-detection ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:facial-recognition ;
vc:hasPart ngm:iris-recognition ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:liveness-detection ;
vc:relatedTo ngm:privacy-preserving ;
vc:requires ngm:deep-learning ;
vc:requires ngm:liveness-detection ;
vc:slug "biometric-identification" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:identity-verification ;
vc:uses ngm:facial-recognition ;
vc:uses ngm:fingerprint-recognition .
ngm:biometric-identity a skos:Concept ;
rdfs:label "Biometric Identity"@en .
ngm:biometric-liveness-detection a skos:Concept ;
rdfs:label "Biometric Liveness Detection"@en .
ngm:biometric-matching-algorithm a skos:Concept ;
rdfs:label "Biometric Matching Algorithm"@en .
ngm:biometric-sensing a skos:Concept ;
rdfs:label "Biometric Sensing"@en .
ngm:biometric-sensor-integration a skos:Concept ;
rdfs:label "Biometric Sensor Integration"@en .
ngm:biometric-sensors a skos:Concept ;
rdfs:label "Biometric Sensors"@en .
ngm:biometric-surveillance a skos:Concept ;
rdfs:label "Biometric Surveillance"@en .
ngm:biometric-template a skos:Concept ;
rdfs:label "Biometric Template"@en .
ngm:biometric-template-database a skos:Concept ;
rdfs:label "Biometric Template Database"@en .
ngm:biometric-tracking a skos:Concept ;
rdfs:label "Biometric Tracking"@en .
ngm:biometric-verification a owl:Class ;
rdfs:comment "Biometric verification is the one-to-one matching process in which a live biometric sample presented by a claimant is compared against a single pre-enrolled template associated with the claimed identity, producing an accept or reject decision based on a similarity threshold. It is distinct from biometric identification, which performs a one-to-many search across an entire database, making verification faster and more privacy-preserving for authentication use cases."@en ;
rdfs:label "Biometric Verification"@en ;
rdfs:subClassOf ngm:identity-verification ;
rdfs:subClassOf _:r3072 ;
rdfs:subClassOf _:r3073 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:contrastsWith ngm:biometric-identification ;
vc:contrastsWith ngm:password-authentication ;
vc:enables ngm:access-control ;
vc:enables ngm:biometric-authentication ;
vc:enables ngm:identity-proofing ;
vc:enables ngm:kyc ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:aml-kyc-compliance ;
vc:relatedTo ngm:digital-identity-verification ;
vc:relatedTo ngm:face-recognition ;
vc:relatedTo ngm:privacy-preserving-authentication ;
vc:requires ngm:data-protection ;
vc:requires ngm:presentation-attack-detection ;
vc:slug "biometric-verification" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:iso-iec ;
vc:supports ngm:digital-identity ;
vc:supports ngm:zero-trust-architecture ;
vc:uses ngm:biometric-binding-mechanism ;
vc:uses ngm:feature-extraction ;
vc:uses ngm:liveness-detection ;
vc:uses ngm:tee .
ngm:biometrics a skos:Concept ;
rdfs:label "Biometrics"@en .
ngm:biometrika a skos:Concept ;
rdfs:label "Biometrika"@en .
ngm:bionlp-shared-task a skos:Concept ;
rdfs:label "Bionlp Shared Task"@en .
ngm:biosafety a skos:Concept ;
rdfs:label "Biosafety"@en .
ngm:biosafety-level-bsl-1-4-framework a skos:Concept ;
rdfs:label "Biosafety Level Bsl 1 4 Framework"@en .
ngm:biosafety-level-framework a skos:Concept ;
rdfs:label "Biosafety Level Framework"@en .
ngm:biosafety-level-laboratory a skos:Concept ;
rdfs:label "Biosafety Level Laboratory"@en .
ngm:biosecurity a owl:Class ;
rdfs:comment "Biosecurity is the set of policies, practices, and controls aimed at preventing the accidental or deliberate misuse of biological agents, including pathogens, toxins, and biotechnology. It spans laboratory containment, pathogen access controls, dual-use research oversight, and increasingly the governance of AI tools that could lower barriers to engineering dangerous organisms. As a field, it is central to mitigating biological existential and catastrophic risks."@en ;
rdfs:label "Biosecurity"@en ;
rdfs:subClassOf ngm:governance ;
rdfs:subClassOf _:r3074 ;
rdfs:subClassOf _:r3075 ;
vc:bridgesTo ngm:ai-safety ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:cybersecurity ;
vc:contrastsWith ngm:bio-terror ;
vc:dependsOn ngm:regulatory-compliance ;
vc:enables ngm:pandemic-preparedness ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:bioethics ;
vc:relatedTo ngm:existential-risk ;
vc:relatedTo ngm:gain-of-function-research ;
vc:relatedTo ngm:synthetic-biology ;
vc:requires ngm:access-control ;
vc:requires ngm:international-treaty ;
vc:requires ngm:risk-assessment ;
vc:slug "biosecurity" ;
vc:sourceDomain "governance" .
ngm:biosensing-interface a owl:Class ;
rdfs:comment "Physical sensor hardware system that detects physiological signals such as heart rate, electroencephalography (EEG), galvanic skin response (GSR), and electromyography (EMG) to enable real-time adaptation of virtual interaction and user experience."@en ;
rdfs:label "Biosensing Interface"@en ;
rdfs:subClassOf ngm:human-robot-interaction ;
rdfs:subClassOf ngm:sensor-system ;
rdfs:subClassOf _:r3076 ;
rdfs:subClassOf _:r3077 ;
rdfs:subClassOf _:r3078 ;
vc:bridgesTo ngm:neurotechnology ;
vc:bridgesTo ngm:sensor-system ;
vc:bridgesTo ngm:wearable-computing ;
vc:dependsOn ngm:cloud-analytics-service ;
vc:dependsOn ngm:wearable-computing-platform ;
vc:dependsOn ngm:xr-headset ;
vc:enables ngm:adaptive-virtual-experience ;
vc:enables ngm:biofeedback-systems ;
vc:enables ngm:emotional-state-detection ;
vc:enables ngm:stress-monitoring ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:electrocardiogram-sensor ;
vc:hasPart ngm:electroencephalography-sensor ;
vc:hasPart ngm:galvanic-skin-response-sensor ;
vc:hasPart ngm:pulse-oximeter ;
vc:hasPart ngm:signal-processing-unit ;
vc:isPartOf ngm:affective-computing ;
vc:isPartOf ngm:physiological-computing-system ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:analog-to-digital-converter ;
vc:requires ngm:power-supply ;
vc:requires ngm:skin-contact-electrodes ;
vc:requires ngm:wireless-communication-module ;
vc:slug "biosensing-interface" ;
vc:sourceDomain "robotics" .
ngm:biosignature a owl:Class ;
rdfs:label "Biosignature"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:planetary-science ;
vc:slug "biosignature" ;
vc:sourceDomain "space-science-and-systems" .
ngm:biospecimen a owl:Class ;
rdfs:label "Biospecimen"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:space-life-sciences ;
vc:slug "biospecimen" ;
vc:sourceDomain "space-science-and-systems" .
ngm:biotech-commercialisation a skos:Concept ;
rdfs:label "Biotech Commercialisation"@en .
ngm:bioweapon-delivery-system a skos:Concept ;
rdfs:label "Bioweapon Delivery System"@en .
ngm:bip-11 a skos:Concept ;
rdfs:label "BIP 11"@en .
ngm:bip-141 a skos:Concept ;
rdfs:label "BIP 141"@en .
ngm:bip-141-segwit a skos:Concept ;
rdfs:label "BIP 141 Segwit"@en .
ngm:bip-16 a owl:Class ;
rdfs:comment "BIP-16 is the Bitcoin Improvement Proposal that introduced Pay-to-Script-Hash (P2SH), allowing funds to be sent to the hash of a redeem script rather than to a full script. The spender supplies the matching script and its satisfying inputs at redemption time, shifting the burden of specifying complex spending conditions from sender to recipient. P2SH made multi-signature and other complex scripts practical and is the standard mechanism behind multi-sig wallet addresses."@en ;
rdfs:label "BIP-16"@en ;
rdfs:subClassOf ngm:technical-standard ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:multi-sig-governance ;
vc:slug "bip-16" ;
vc:sourceDomain "blockchain" .
ngm:bip-173 a skos:Concept ;
rdfs:label "BIP 173"@en .
ngm:bip-173-bech32 a skos:Concept ;
rdfs:label "BIP 173 Bech32"@en .
ngm:bip-32 a skos:Concept ;
rdfs:label "BIP 32"@en .
ngm:bip-32-hd-wallet a skos:Concept ;
rdfs:label "BIP 32 Hd Wallet"@en .
ngm:bip-32-hd-wallets a skos:Concept ;
rdfs:label "BIP 32 Hd Wallets"@en .
ngm:bip-327 a owl:Class ;
rdfs:comment "BIP-327 is a Bitcoin Improvement Proposal that specifies MuSig2, a two-round multi-party Schnorr signature protocol that enables a group of n signers to collaboratively produce a single aggregated Schnorr signature indistinguishable from a single-party signature. BIP-327 provides a cryptographically secure specification for key aggregation and signature combination compatible with BIP-340 Schnorr signatures and the Taproot upgrade, enabling private and efficient threshold custody and collaborative signing workflows on Bitcoin."@en ;
rdfs:label "BIP-327"@en ;
rdfs:subClassOf ngm:bitcoin-proof-of-work-protocol-improvement-proposals ;
vc:enables ngm:multisignature ;
vc:enables ngm:multisignature-wallets ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:bip-340-schnorr-keypair ;
vc:relatedTo ngm:bip-342 ;
vc:slug "bip-327" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:schnorr-signature ;
vc:uses ngm:taproot .
ngm:bip-328 a owl:Class ;
rdfs:comment "BIP-328 is a Bitcoin Improvement Proposal defining the Hierarchical Deterministic Keys (HD Keys) using the Silent Payments-related and descriptor key formats for derivation, standardising how extended keys and key origins are encoded. It supports the unambiguous representation of key paths and fingerprints used by descriptor-based and Taproot-aware wallets. By standardising key encoding, it improves interoperability between wallets handling Taproot assets and multi-party setups."@en ;
rdfs:label "BIP-328"@en ;
rdfs:subClassOf ngm:technical-standard ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:taproot-assets ;
vc:slug "bip-328" ;
vc:sourceDomain "blockchain" .
ngm:bip-329 a owl:Class ;
rdfs:comment "BIP-329 is a Bitcoin Improvement Proposal that specifies a standard, wallet-agnostic format for exporting and importing wallet labels. It defines a JSONL structure associating human-readable labels and metadata with transactions, addresses, inputs, outputs, and extended public keys. The standard improves portability of bookkeeping and provenance information between wallets, which is valuable for asset tracking and compliance in Taproot-asset and multi-wallet workflows."@en ;
rdfs:label "BIP-329"@en ;
rdfs:subClassOf ngm:technical-standard ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:taproot-assets ;
vc:slug "bip-329" ;
vc:sourceDomain "blockchain" .
ngm:bip-330 a owl:Class ;
rdfs:comment "BIP-330 is a Bitcoin Improvement Proposal that introduces Erlay-style transaction reconciliation (the 'sendtxrcncl' protocol) to make mempool synchronisation between nodes more bandwidth-efficient. Instead of announcing every transaction to every peer, nodes use set-reconciliation sketches to identify only the transactions a peer is missing. This reduces redundant relay traffic, improving the scalability and privacy of the peer-to-peer network that supports applications like Taproot assets."@en ;
rdfs:label "BIP-330"@en ;
rdfs:subClassOf ngm:technical-standard ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:taproot-assets ;
vc:slug "bip-330" ;
vc:sourceDomain "blockchain" .
ngm:bip-34 a skos:Concept ;
rdfs:label "BIP 34"@en .
ngm:bip-340 a owl:Class ;
rdfs:comment "BIP-340 is the Bitcoin Improvement Proposal that standardises Schnorr signatures for use on the Bitcoin network using the secp256k1 elliptic curve, defining a deterministic 64-byte signature scheme that is provably secure in the random oracle model. It introduces x-only 32-byte public key encoding, a tagged hash nonce-generation procedure, and rigorous test vectors to guarantee cross-implementation compatibility. BIP-340 is a strict prerequisite for Taproot (BIP-341) and Tapscript (BIP-342), enabling key aggregation via MuSig2 and linear signature composition that makes multisignature spends indistinguishable on-chain from single-key spends. The proposal represents the most significant cryptographic upgrade to Bitcoin since its inception, substantially improving privacy, efficiency, and the expressiveness of multi-party signing protocols."@en ;
rdfs:label "BIP-340"@en ;
rdfs:subClassOf ngm:cryptographic-protocol ;
rdfs:subClassOf _:r2611 ;
rdfs:subClassOf _:r2612 ;
rdfs:subClassOf _:r2613 ;
vc:bridgesTo ngm:secure-multi-party-computation ;
vc:bridgesTo ngm:zero-knowledge-proof ;
vc:contrastsWith ngm:ecdsa ;
vc:contrastsWith ngm:ed25519 ;
vc:enables ngm:bip-341 ;
vc:enables ngm:bip-342 ;
vc:enables ngm:mu-sig-2 ;
vc:enables ngm:point-time-locked-contracts ;
vc:enables ngm:taproot ;
vc:enables ngm:taproot-assets ;
vc:enables ngm:threshold-signature-scheme ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:schnorr-signature ;
vc:implements ngm:x-only-public-key ;
vc:isPartOf ngm:taproot ;
vc:qualityScore "0.78"^^xsd:float ;
vc:relatedTo ngm:cryptographic-signature ;
vc:relatedTo ngm:digital-signature ;
vc:relatedTo ngm:elliptic-curve-cryptography ;
vc:relatedTo ngm:random-oracle-model ;
vc:relatedTo ngm:schnorr-signature ;
vc:relatedTo ngm:secp256k1 ;
vc:requires ngm:elliptic-curve-cryptography ;
vc:requires ngm:secp256k1 ;
vc:requires ngm:tagged-hash ;
vc:slug "bip-340" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:bitcoin-proof-of-work-protocol-core ;
vc:supports ngm:bitcoin-privacy ;
vc:supports ngm:lightning-network ;
vc:supports ngm:multi-signature ;
vc:uses ngm:bip-32-hd-wallets ;
vc:uses ngm:bitcoin-proof-of-work-protocol-improvement-proposals ;
vc:uses ngm:sha-256 .
ngm:bip-340-schnorr-keypair a owl:Class ;
rdfs:comment "A BIP-340 Schnorr Keypair is the 32-byte public key and associated private key pairing defined by Bitcoin Improvement Proposal 340, which introduced Schnorr signature support to Bitcoin via the Taproot upgrade activated in November 2021. Unlike the earlier ECDSA scheme used in Bitcoin, BIP-340 uses x-only public keys — just the x-coordinate of the secp256k1 curve point — reducing on-chain byte footprint and simplifying key aggregation. The scheme is provably secure under the discrete logarithm assumption and supports native key and signature aggregation via protocols such as MuSig2, enabling multi-party signing that is indistinguishable from single-party signing on-chain. BIP-340 keypairs are the cryptographic foundation for Taproot outputs, Tapscript, and the Nostr identity protocol."@en ;
rdfs:label "BIP-340 Schnorr Keypair"@en ;
rdfs:subClassOf ngm:cryptographic-keys ;
rdfs:subClassOf _:r2609 ;
rdfs:subClassOf _:r2610 ;
vc:bridgesTo ngm:decentralized-identifier ;
vc:bridgesTo ngm:digital-identity ;
vc:contrastsWith ngm:ecdsa ;
vc:dependsOn ngm:hash-function ;
vc:dependsOn ngm:tagged-hash ;
vc:enables ngm:bip-342-tapscript ;
vc:enables ngm:key-aggregation ;
vc:enables ngm:mu-sig-2 ;
vc:enables ngm:multi-sig-governance ;
vc:enables ngm:nostr-protocol ;
vc:enables ngm:taproot-assets ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:bitcoin-proof-of-work-protocol-improvement-proposals ;
vc:isPartOf ngm:taproot ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:bip-327 ;
vc:relatedTo ngm:bip-340 ;
vc:relatedTo ngm:bip-341 ;
vc:relatedTo ngm:discrete-logarithm-problem ;
vc:relatedTo ngm:schnorr-signature ;
vc:relatedTo ngm:secp256k1 ;
vc:requires ngm:private-key ;
vc:requires ngm:secp256k1-elliptic-curve ;
vc:slug "bip-340-schnorr-keypair" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:bitcoin-proof-of-work-protocol-core ;
vc:uses ngm:elliptic-curve-cryptography ;
vc:uses ngm:random-oracle-model ;
vc:uses ngm:x-only-public-key .
ngm:bip-340-schnorr-signatures a skos:Concept ;
rdfs:label "BIP 340 Schnorr Signatures"@en .
ngm:bip-341 a owl:Class ;
rdfs:comment "BIP-341 is the Bitcoin Improvement Proposal that specifies the Taproot upgrade, introducing Pay-to-Taproot (P2TR) as a native SegWit version 1 output type that unifies key-path and script-path spending under a single Schnorr-based commitment. It integrates Merklised Alternative Script Trees (MAST) so that only the executed spending branch is revealed on-chain, preserving the privacy of unexplored script conditions. BIP-341 activated on the Bitcoin mainnet at block 709,632 in November 2021 via the Speedy Trial soft-fork mechanism, requiring 90% miner signalling. It forms part of the Taproot bundle alongside BIP-340 (Schnorr signatures for Bitcoin) and BIP-342 (Tapscript), collectively the largest upgrade to Bitcoin's scripting system since SegWit."@en ;
rdfs:label "BIP-341"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf _:r2615 ;
rdfs:subClassOf _:r2616 ;
rdfs:subClassOf _:r2617 ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:bridgesTo ngm:smart-contract ;
vc:bridgesTo ngm:zero-knowledge-proof ;
vc:contrastsWith ngm:ecdsa ;
vc:contrastsWith ngm:pay-to-script-hash ;
vc:dependsOn ngm:bitcoin-consensus ;
vc:dependsOn ngm:utxo-model ;
vc:enables ngm:bitcoin-script ;
vc:enables ngm:bitcoin-smart-contracts ;
vc:enables ngm:lightning-network ;
vc:enables ngm:multisignature ;
vc:enables ngm:taproot-assets ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:merklised-alternative-script-tree ;
vc:hasPart ngm:pay-to-taproot ;
vc:isPartOf ngm:bitcoin-soft-fork ;
vc:isPartOf ngm:taproot ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:bitcoin-fungibility ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol-core ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol-network ;
vc:relatedTo ngm:coinjoin ;
vc:requires ngm:bip-340 ;
vc:requires ngm:bip-342 ;
vc:requires ngm:seg-wit ;
vc:slug "bip-341" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:bitcoin-proof-of-work-protocol-improvement-proposals ;
vc:uses ngm:cryptographic-commitment ;
vc:uses ngm:elliptic-curve-cryptography ;
vc:uses ngm:merkle-tree ;
vc:uses ngm:schnorr-signature ;
vc:uses ngm:tagged-hash .
ngm:bip-341-taproot a owl:Class ;
rdfs:comment "A Bitcoin Improvement Proposal defining Taproot, an upgrade introducing a new output type using Schnorr signatures and Merkle-branch script commitments. It improves privacy and flexibility of Bitcoin transactions."@en ;
rdfs:label "BIP-341 Taproot"@en ;
rdfs:subClassOf ngm:technical-standard ;
rdfs:subClassOf _:r2614 ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:bitcoin-proof-of-work-protocol ;
vc:slug "bip-341-taproot" ;
vc:sourceDomain "standards" .
ngm:bip-342 a owl:Class ;
rdfs:comment "BIP-342 specifies Tapscript, the updated Bitcoin scripting language that replaces legacy script in the script-path spending branch of Taproot (BIP-341) outputs. Tapscript updates the signature opcodes to use BIP-340 Schnorr signatures, introduces the OP_CHECKSIGADD opcode to enable efficient threshold multisignature constructions, relaxes script resource limits, and establishes an extensible opcode upgrade mechanism via OP_SUCCESS opcodes for future soft forks."@en ;
rdfs:label "BIP-342"@en ;
rdfs:subClassOf ngm:bitcoin-proof-of-work-protocol-improvement-proposals ;
rdfs:subClassOf _:r2619 ;
rdfs:subClassOf _:r2620 ;
vc:bridgesTo ngm:smart-contract ;
vc:bridgesTo ngm:zero-knowledge-proof ;
vc:contrastsWith ngm:ecdsa ;
vc:enables ngm:multisignature ;
vc:enables ngm:soft-fork ;
vc:enables ngm:taproot ;
vc:enables ngm:threshold-signature-scheme ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:merkelised-abstract-syntax-tree ;
vc:isPartOf ngm:bitcoin-proof-of-work-protocol-improvement-proposals ;
vc:isPartOf ngm:taproot ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:bip-327 ;
vc:relatedTo ngm:bip-340-schnorr-keypair ;
vc:requires ngm:bip-340-schnorr-keypair ;
vc:requires ngm:bip-341 ;
vc:slug "bip-342" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:discreet-log-contracts ;
vc:supports ngm:lightning-network ;
vc:supports ngm:time-lock ;
vc:uses ngm:bitcoin-script ;
vc:uses ngm:merkle-tree ;
vc:uses ngm:schnorr-signature ;
vc:uses ngm:stack-machine .
ngm:bip-342-tapscript a owl:Class ;
rdfs:comment "A Bitcoin Improvement Proposal defining Tapscript, the scripting semantics used within Taproot spends. It specifies the validation rules for scripts committed under the Taproot output type."@en ;
rdfs:label "BIP-342 Tapscript"@en ;
rdfs:subClassOf ngm:technical-standard ;
rdfs:subClassOf _:r2618 ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:bitcoin-proof-of-work-protocol ;
vc:slug "bip-342-tapscript" ;
vc:sourceDomain "standards" .
ngm:bip-373 a skos:Concept ;
rdfs:label "BIP 373"@en .
ngm:bip-39-mnemonic a skos:Concept ;
rdfs:label "BIP 39 Mnemonic"@en .
ngm:bip-9 a skos:Concept ;
rdfs:label "BIP 9"@en .
ngm:bip-91 a skos:Concept ;
rdfs:label "BIP 91"@en .
ngm:bip-process a owl:Class ;
rdfs:comment "The Bitcoin Improvement Proposal (BIP) process is the standardised social and technical workflow by which proposed changes to the Bitcoin protocol, best practices, and informational standards are drafted, reviewed, debated, and either accepted or rejected by the Bitcoin developer community. It defines the lifecycle of a proposal from Draft through Proposed, Final, Active, Withdrawn, or Rejected, providing a structured mechanism for decentralised protocol governance without a centralised authority."@en ;
rdfs:label "BIP Process"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:enables ngm:bitcoin-proof-of-work-protocol-improvement-proposals ;
vc:enables ngm:nakamoto-consensus ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:bip-327 ;
vc:relatedTo ngm:bip-342 ;
vc:relatedTo ngm:nakamoto-coefficient ;
vc:slug "bip-process" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:bitcoin-proof-of-work-protocol-core .
ngm:bip32 a skos:Concept ;
rdfs:label "Bip32"@en .
ngm:bip32-hd-wallets a skos:Concept ;
rdfs:label "Bip32 Hd Wallets"@en .
ngm:bip39 a owl:Class ;
rdfs:comment "BIP-39 is a Bitcoin Improvement Proposal that defines how to encode wallet entropy as a human-readable mnemonic seed phrase and how to derive a binary seed from it. It maps random entropy plus a checksum onto words drawn from a fixed wordlist, then stretches the phrase and an optional passphrase into a seed via a key derivation function. The resulting seed feeds hierarchical deterministic wallets, making secrets easier to back up and transcribe."@en ;
rdfs:label "BIP-39"@en ;
rdfs:subClassOf ngm:seed-phrase ;
rdfs:subClassOf _:r2621 ;
rdfs:subClassOf _:r2622 ;
vc:dependsOn ngm:private-key ;
vc:enables ngm:hierarchical-deterministic-wallet ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:key-derivation-function ;
vc:implements ngm:seed-phrase ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:bitcoin ;
vc:relatedTo ngm:elliptic-curve-cryptography ;
vc:relatedTo ngm:wallet ;
vc:requires ngm:entropy ;
vc:requires ngm:hash-function ;
vc:slug "bip39" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:cryptocurrency-wallet ;
vc:supports ngm:hardware-wallet ;
vc:uses ngm:key-derivation-function .
ngm:bip44 a skos:Concept ;
rdfs:label "Bip44"@en .
ngm:bipartite-graph-detection a skos:Concept ;
rdfs:label "Bipartite Graph Detection"@en .
ngm:bipartite-matching a skos:Concept ;
rdfs:label "Bipartite Matching"@en .
ngm:bipedal-balance a owl:Class ;
rdfs:comment "Bipedal Balance is the set of sensing, computation, and actuation mechanisms that enable a two-legged robot or agent to maintain postural stability during standing, walking, and dynamic manoeuvres. It encompasses whole-body control strategies, inertial sensing, and real-time torque control to keep the centre of mass within a supportable base of support. The field integrates mechanics, control theory, and machine learning to achieve robust locomotion across uneven terrain."@en ;
rdfs:label "Bipedal Balance"@en ;
rdfs:subClassOf ngm:legged-locomotion ;
rdfs:subClassOf _:r3079 ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:reinforcement-learning-for-robotics ;
vc:requires ngm:robot-dynamics ;
vc:slug "bipedal-balance" ;
vc:sourceDomain "robotics" ;
vc:uses ngm:inertial-measurement-unit ;
vc:uses ngm:inverse-kinematics ;
vc:uses ngm:torque-control ;
vc:uses ngm:whole-body-control .
ngm:bipedal-locomotion a skos:Concept ;
rdfs:label "Bipedal Locomotion"@en .
ngm:bipedal-robot a skos:Concept ;
rdfs:label "Bipedal Robot"@en .
ngm:bipropellant-propulsion a owl:Class ;
rdfs:label "Bipropellant Propulsion"@en ;
rdfs:subClassOf ngm:chemical-propulsion ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:spacecraft-propulsion ;
vc:slug "bipropellant-propulsion" ;
vc:sourceDomain "space-science-and-systems" .
ngm:bird-eye-view a skos:Concept ;
rdfs:label "Bird Eye View"@en .
ngm:bird-s-eye-view a skos:Concept ;
rdfs:label "Bird S Eye View"@en .
ngm:bird-s-eye-view-perception a skos:Concept ;
rdfs:label "Bird S Eye View Perception"@en .
ngm:birdbath-optics a skos:Concept ;
rdfs:label "Birdbath Optics"@en .
ngm:birkhoff-ergodic-theorem a skos:Concept ;
rdfs:label "Birkhoff Ergodic Theorem"@en .
ngm:birthday-attack a skos:Concept ;
rdfs:label "Birthday Attack"@en .
ngm:bis a owl:Class ;
rdfs:comment "The Bank for International Settlements (BIS) is an international financial institution owned by 63 member central banks, founded in 1930 and headquartered in Basel, Switzerland. It acts as banker to central banks, providing settlement, custody, and asset management services while fostering monetary and financial cooperation through research, policy forums, and standard-setting committees. The BIS hosts the Basel Committee on Banking Supervision, the Financial Stability Board secretariat, and the Committee on Payments and Market Infrastructures, which together produce globally binding prudential and operational standards such as the Basel Accords and CPMI principles. Through the BIS Innovation Hub it actively researches central bank digital currencies, tokenisation of financial assets, and cyber resilience for financial market infrastructures."@en ;
rdfs:label "BIS"@en ;
rdfs:subClassOf ngm:infra-legal-and-regulatory ;
rdfs:subClassOf _:r2625 ;
rdfs:subClassOf _:r2626 ;
rdfs:subClassOf _:r2627 ;
skos:broader ngm:infra-legal-and-regulatory ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:cyber-resilience ;
vc:bridgesTo ngm:regtech ;
vc:contrastsWith ngm:commercial-bank ;
vc:enables ngm:cross-border-payments ;
vc:enables ngm:financial-stability ;
vc:enables ngm:monetary-policy-implementation ;
vc:enables ngm:prudential-regulation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:basel-committee-on-banking-supervision ;
vc:hasPart ngm:bis-innovation-hub ;
vc:hasPart ngm:committee-on-payments-and-market-infrastructures ;
vc:hasPart ngm:financial-stability-board ;
vc:implements ngm:basel-accords ;
vc:implements ngm:capital-adequacy ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:central-bank-digital-currency-cbdc ;
vc:relatedTo ngm:financial-regulation ;
vc:relatedTo ngm:financial-technology ;
vc:relatedTo ngm:imf ;
vc:relatedTo ngm:payment-system ;
vc:relatedTo ngm:world-bank ;
vc:slug "bis" ;
vc:sourceDomain "finance" ;
vc:supports ngm:central-bank ;
vc:supports ngm:financial-infrastructure ;
vc:supports ngm:financial-system ;
vc:supports ngm:systemic-risk-management ;
vc:uses ngm:distributed-ledger-technology ;
vc:uses ngm:neural-network-text-tokenisation ;
vc:uses ngm:tokenization .
ngm:bis-basel-iii-hqla-classification a skos:Concept ;
rdfs:label "Bis Basel Iii Hqla Classification"@en .
ngm:bis-cbdc-design-principles-2020 a skos:Concept ;
rdfs:label "Bis CBDC Design Principles 2020"@en .
ngm:bis-cbdc-principles a skos:Concept ;
rdfs:label "Bis CBDC Principles"@en .
ngm:bis-cpmi a skos:Concept ;
rdfs:label "Bis Cpmi"@en .
ngm:bis-cpmi-standards a skos:Concept ;
rdfs:label "Bis Cpmi Standards"@en .
ngm:bis-crypto-risk-assessment-framework a skos:Concept ;
rdfs:label "Bis Crypto Risk Assessment Framework"@en .
ngm:bis-green-finance-standards a skos:Concept ;
rdfs:label "Bis Green Finance Standards"@en .
ngm:bis-innovation-hub a owl:Class ;
rdfs:comment "The innovation arm of the Bank for International Settlements, established to develop public goods for central banks and explore financial technology including CBDCs, cross-border payments, tokenisation, and regulatory technology."@en ;
rdfs:label "BIS Innovation Hub"@en ;
rdfs:subClassOf ngm:bis ;
rdfs:subClassOf _:r2623 ;
rdfs:subClassOf _:r2624 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:central-bank ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:bridgesTo ngm:hong-kong ;
vc:enables ngm:central-bank-digital-currency-cbdc ;
vc:enables ngm:cross-border-payments ;
vc:enables ngm:tokenization ;
vc:enables ngm:wholesale-cbdc ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:project-m-bridge ;
vc:hasPart ngm:project-nexus ;
vc:implements ngm:financial-infrastructure ;
vc:isPartOf ngm:bis ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:financial-technology ;
vc:relatedTo ngm:interoperability ;
vc:relatedTo ngm:payment-system ;
vc:slug "bis-innovation-hub" ;
vc:sourceDomain "finance" ;
vc:supports ngm:central-bank ;
vc:supports ngm:financial-stability ;
vc:supports ngm:monetary-policy ;
vc:uses ngm:distributed-ledger-technology ;
vc:uses ngm:open-source-software ;
vc:uses ngm:regulatory-technology .
ngm:bis-project-tourbillon a skos:Concept ;
rdfs:label "Bis Project Tourbillon"@en .
ngm:biss-c-protocol a skos:Concept ;
rdfs:label "Biss C Protocol"@en .
ngm:bit-error-rate a owl:Class ;
rdfs:label "Bit Error Rate"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:satellite-communication ;
vc:slug "bit-error-rate" ;
vc:sourceDomain "space-science-and-systems" .
ngm:bit-go a owl:Class ;
rdfs:comment "BitGo is a company that provides digital asset custody, wallet, and security services, including multi-signature wallet technology, for institutional clients."@en ;
rdfs:label "BitGo"@en ;
rdfs:subClassOf ngm:institutional-custody ;
rdfs:subClassOf _:r3080 ;
vc:bridgesTo ngm:key-management ;
vc:enables ngm:institutional-custody ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:multisignature ;
vc:slug "bit-go" ;
vc:sourceDomain "blockchain" .
ngm:bit-vm a owl:Class ;
rdfs:comment "BitVM is a proposed approach for expressing complex computations that can be verified on Bitcoin without changing its consensus rules. It uses fraud proofs and challenge-response interactions."@en ;
rdfs:label "BitVM"@en ;
rdfs:subClassOf ngm:bitcoin-script ;
rdfs:subClassOf _:r3081 ;
rdfs:subClassOf _:r3082 ;
vc:bridgesTo ngm:smart-contract ;
vc:enables ngm:layer-2-scaling ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:fraud-proof ;
vc:requires ngm:taproot ;
vc:slug "bit-vm" ;
vc:sourceDomain "blockchain" .
ngm:bitcoin a owl:Class ;
rdfs:comment "Bitcoin is the first decentralised, permissionless, peer-to-peer electronic cash system, introduced by the pseudonymous Satoshi Nakamoto in a 2008 whitepaper and launched as open-source software in January 2009. It maintains a globally shared, tamper-evident ledger — the blockchain — through a proof-of-work consensus mechanism called Nakamoto Consensus, in which miners compete to extend the chain by finding nonces satisfying a difficulty-adjusted SHA-256 hash target, earning new bitcoin and transaction fees as reward. The monetary supply is strictly bounded by a 21 million coin cap enforced deterministically via a halving schedule that reduces the block subsidy approximately every four years, conferring programmatic scarcity and censorship-resistant value transfer without reliance on any trusted intermediary. Bitcoin's UTXO model, Script-based transaction authorisation, and secp256k1 elliptic-curve cryptography together form the foundational substrate upon which Lightning Network payment channels, Taproot smart contracting, and a growing ecosystem of Layer 2 protocols are built."@en ;
rdfs:label "Bitcoin"@en ;
rdfs:subClassOf ngm:cryptocurrency ;
rdfs:subClassOf _:r3238 ;
rdfs:subClassOf _:r3239 ;
rdfs:subClassOf _:r3240 ;
rdfs:subClassOf _:r3241 ;
rdfs:subClassOf _:r3242 ;
rdfs:subClassOf _:r3243 ;
vc:bridgesTo ngm:decentralised-identity ;
vc:bridgesTo ngm:fedimint ;
vc:bridgesTo ngm:nostr ;
vc:contrastsWith ngm:digital-currency ;
vc:contrastsWith ngm:ethereum-smart-contract-platform ;
vc:contrastsWith ngm:monetary-system ;
vc:contrastsWith ngm:solana ;
vc:enables ngm:censorship-resistance ;
vc:enables ngm:de-fi ;
vc:enables ngm:financial-inclusion ;
vc:enables ngm:lightning-network ;
vc:enables ngm:self-custody ;
vc:enables ngm:store-of-value ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:bitcoin-proof-of-work-protocol-core ;
vc:hasPart ngm:bitcoin-proof-of-work-protocol-halving ;
vc:hasPart ngm:bitcoin-proof-of-work-protocol-layer-2 ;
vc:hasPart ngm:bitcoin-proof-of-work-protocol-mining ;
vc:hasPart ngm:bitcoin-proof-of-work-protocol-whitepaper ;
vc:hasPart ngm:bitcoin-script ;
vc:implements ngm:blockchain ;
vc:implements ngm:consensus-mechanism ;
vc:implements ngm:distributed-ledger-technology ;
vc:implements ngm:sound-money ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:blockchain-scalability ;
vc:relatedTo ngm:digital-asset ;
vc:relatedTo ngm:mining-pool ;
vc:slug "bitcoin" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:bip-341-taproot ;
vc:standardizedBy ngm:bitcoin-proof-of-work-protocol-improvement-proposals ;
vc:uses ngm:cryptographic-hash-function ;
vc:uses ngm:elliptic-curve-cryptography ;
vc:uses ngm:merkle-tree ;
vc:uses ngm:nakamoto-consensus ;
vc:uses ngm:peer-to-peer-network ;
vc:uses ngm:proof-of-work ;
vc:uses ngm:utxo-model .
ngm:bitcoin-consensus a skos:Concept ;
rdfs:label "Bitcoin Consensus"@en .
ngm:bitcoin-fungibility a skos:Concept ;
rdfs:label "Bitcoin Fungibility"@en .
ngm:bitcoin-improvement-proposal a skos:Concept ;
rdfs:label "Bitcoin Improvement Proposal"@en .
ngm:bitcoin-inclusion-in-model-portfolio a skos:Concept ;
rdfs:label "Bitcoin Inclusion In Model Portfolio"@en .
ngm:bitcoin-issuance a skos:Concept ;
rdfs:label "Bitcoin Issuance"@en .
ngm:bitcoin-layer-3-ecosystem a skos:Concept ;
rdfs:label "Bitcoin Layer 3 Ecosystem"@en .
ngm:bitcoin-lightning-wallet a skos:Concept ;
rdfs:label "Bitcoin Lightning Wallet"@en .
ngm:bitcoin-liquidity a skos:Concept ;
rdfs:label "Bitcoin Liquidity"@en .
ngm:bitcoin-miners a skos:Concept ;
rdfs:label "Bitcoin Miners"@en .
ngm:bitcoin-mining-council a skos:Concept ;
rdfs:label "Bitcoin Mining Council"@en .
ngm:bitcoin-mining-equity a skos:Concept ;
rdfs:label "Bitcoin Mining Equity"@en .
ngm:bitcoin-native-defi a skos:Concept ;
rdfs:label "Bitcoin Native DeFi"@en .
ngm:bitcoin-native-stablecoins a skos:Concept ;
rdfs:label "Bitcoin Native Stablecoins"@en .
ngm:bitcoin-network-security a skos:Concept ;
rdfs:label "Bitcoin Network Security"@en .
ngm:bitcoin-node a skos:Concept ;
rdfs:label "Bitcoin Node"@en .
ngm:bitcoin-optech a skos:Concept ;
rdfs:label "Bitcoin Optech"@en .
ngm:bitcoin-options a skos:Concept ;
rdfs:label "Bitcoin Options"@en .
ngm:bitcoin-payment a skos:Concept ;
rdfs:label "Bitcoin Payment"@en .
ngm:bitcoin-payment-routing a skos:Concept ;
rdfs:label "Bitcoin Payment Routing"@en .
ngm:bitcoin-privacy a skos:Concept ;
rdfs:label "Bitcoin Privacy"@en .
ngm:bitcoin-proof-of-work-protocol a owl:Class ;
rdfs:comment "Bitcoin is the first decentralised peer-to-peer electronic cash system, introduced by the pseudonymous Satoshi Nakamoto in a 2008 white paper and launched in January 2009. It operates on a public, permissionless blockchain secured by proof-of-work consensus, with a fixed supply cap of 21 million BTC enforced by its protocol. Bitcoin is simultaneously a payment network, a monetary asset, and the foundational reference implementation for the broader cryptocurrency and blockchain industry."@en ;
rdfs:label "Bitcoin Proof-of-Work Protocol"@en ;
rdfs:subClassOf ngm:cryptocurrency ;
rdfs:subClassOf _:r3170 ;
rdfs:subClassOf _:r3171 ;
rdfs:subClassOf _:r3172 ;
vc:contrastsWith ngm:51-attack ;
vc:contrastsWith ngm:bitcoin-proof-of-work-protocol-centralisation-risks ;
vc:enables ngm:bitcoin-proof-of-work-protocol-as-money ;
vc:enables ngm:bitcoin-proof-of-work-protocol-standard ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:bitcoin-proof-of-work-protocol-mining ;
vc:hasPart ngm:bitcoin-proof-of-work-protocol-technical-overview ;
vc:hasPart ngm:bitcoin-proof-of-work-protocol-value-proposition ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol-etf ;
vc:relatedTo ngm:blockchain ;
vc:relatedTo ngm:blockchain-economics ;
vc:relatedTo ngm:blockchain-energy-consumption ;
vc:relatedTo ngm:decentralized-finance-de-fi ;
vc:relatedTo ngm:distributed-ledger-technology ;
vc:slug "bitcoin-proof-of-work-protocol" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:blockchain-network ;
vc:uses ngm:consensus-mechanism ;
vc:uses ngm:cryptography .
ngm:bitcoin-proof-of-work-protocol-as-money a owl:Class ;
rdfs:comment "Bitcoin As Money is the analytical framework within monetary economics and philosophy that interrogates wher Bitcoin — the fixed-supply, decentralised, proof-of-work-secured digital commodity created by Satoshi Nakamoto — satisfies the classical three functions of money: medium of exchang..."@en ;
rdfs:label "Bitcoin As Money"@en ;
rdfs:subClassOf ngm:austrian-economics ;
rdfs:subClassOf ngm:bc-defi-and-economics ;
rdfs:subClassOf ngm:bc-token-and-asset ;
rdfs:subClassOf ngm:cryptocurrency-economics ;
rdfs:subClassOf ngm:digital-asset-economics ;
rdfs:subClassOf ngm:monetary-theory ;
rdfs:subClassOf ngm:sound-money ;
rdfs:subClassOf _:r3083 ;
rdfs:subClassOf _:r3084 ;
rdfs:subClassOf _:r3085 ;
rdfs:subClassOf _:r3086 ;
rdfs:subClassOf _:r3087 ;
rdfs:subClassOf _:r3088 ;
rdfs:subClassOf _:r3089 ;
skos:broader ngm:bc-defi-and-economics ;
skos:broader ngm:bc-token-and-asset ;
vc:bridgesTo ngm:austrian-economics ;
vc:contrastsWith ngm:central-bank-digital-currency-cbdc ;
vc:contrastsWith ngm:fiat-money ;
vc:contrastsWith ngm:gold-standard ;
vc:contrastsWith ngm:keynesian-economics ;
vc:contrastsWith ngm:stablecoin ;
vc:contrastsWith ngm:traditional-banking ;
vc:dependsOn ngm:bitcoin-proof-of-work-protocol ;
vc:dependsOn ngm:lightning-network ;
vc:dependsOn ngm:merchant-adoption ;
vc:dependsOn ngm:network-effects ;
vc:dependsOn ngm:price-stability ;
vc:dependsOn ngm:regulatory-clarity ;
vc:dependsOn ngm:social-consensus ;
vc:enables ngm:ai-agent-payments ;
vc:enables ngm:censorship-resistant-payments ;
vc:enables ngm:circular-bitcoin-economy ;
vc:enables ngm:cross-border-payments ;
vc:enables ngm:financial-inclusion ;
vc:enables ngm:machine-commerce ;
vc:enables ngm:micropayments ;
vc:enables ngm:sovereign-reserve-asset ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:bitcoin-proof-of-work-protocol-standard ;
vc:hasPart ngm:circular-economy ;
vc:hasPart ngm:greshams-law-application ;
vc:hasPart ngm:layered-bitcoin-architecture ;
vc:hasPart ngm:lightning-network ;
vc:hasPart ngm:medium-of-exchange ;
vc:hasPart ngm:store-of-value ;
vc:hasPart ngm:unit-of-account ;
vc:hasPart ngm:velocity-of-money-analysis ;
vc:implements ngm:austrian-hard-money-theory ;
vc:implements ngm:commodity-money-model ;
vc:implements ngm:fixed-supply-monetary-policy ;
vc:implements ngm:programmable-money ;
vc:implements ngm:sound-money-principles ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:austrian-economics ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol ;
vc:relatedTo ngm:digital-gold ;
vc:relatedTo ngm:el-salvador ;
vc:relatedTo ngm:financial-inclusion ;
vc:relatedTo ngm:hyperbitcoinization ;
vc:relatedTo ngm:micro-strategy ;
vc:relatedTo ngm:monetary-policy ;
vc:relatedTo ngm:remittances ;
vc:relatedTo ngm:sound-money ;
vc:requires ngm:bitcoin-proof-of-work-protocol ;
vc:requires ngm:bitcoin-proof-of-work-protocol-network ;
vc:requires ngm:lightning-network ;
vc:requires ngm:merchant-adoption ;
vc:requires ngm:monetary-consensus ;
vc:requires ngm:price-stability-analysis ;
vc:slug "bitcoin-as-money" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:bip32-hd-wallets ;
vc:standardizedBy ngm:bolt-specifications ;
vc:standardizedBy ngm:fasb-asu-2023-08 ;
vc:standardizedBy ngm:imf-crypto-asset-classification-framework ;
vc:standardizedBy ngm:nakamoto-2008-bitcoin-whitepaper ;
vc:supports ngm:bitcoin-proof-of-work-protocol-standard ;
vc:supports ngm:bitcoin-treasury-strategy ;
vc:supports ngm:financial-sovereignty ;
vc:supports ngm:hyperbitcoinization ;
vc:supports ngm:self-custody ;
vc:supports ngm:separation-of-money-and-state ;
vc:supports ngm:sound-money ;
vc:uses ngm:cashu ;
vc:uses ngm:chivo-wallet ;
vc:uses ngm:fedimint ;
vc:uses ngm:l-402-protocol ;
vc:uses ngm:lightning-network ;
vc:uses ngm:rgb-protocol ;
vc:uses ngm:stablesats ;
vc:uses ngm:strike-payment-infrastructure .
ngm:bitcoin-proof-of-work-protocol-cash a owl:Class ;
rdfs:comment "A cryptocurrency and blockchain created in 2017 as a hard fork of Bitcoin, with a larger block size intended to increase on-chain transaction throughput. It uses the same proof-of-work consensus model as Bitcoin."@en ;
rdfs:label "Bitcoin Cash"@en ;
rdfs:subClassOf ngm:cryptocurrency ;
rdfs:subClassOf _:r3090 ;
rdfs:subClassOf _:r3091 ;
vc:bridgesTo ngm:bitcoin-proof-of-work-protocol ;
vc:bridgesTo ngm:bitcoin-proof-of-work-protocol-network ;
vc:enables ngm:payment-channel ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:hash-function ;
vc:requires ngm:mining ;
vc:slug "bitcoin-cash" ;
vc:sourceDomain "blockchain" .
ngm:bitcoin-proof-of-work-protocol-centralisation-risks a owl:Class ;
rdfs:comment "Bitcoin Centralisation Risks refers to the ensemble of systemic vulnerabilities arising from the progressive concentration of economic power, computational control, physical infrastructure, custody arrangements, development authority, and payment routing within Bitcoin's nominally decentralised e..."@en ;
rdfs:label "Bitcoin Centralisation Risks"@en ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf ngm:blockchain-governance-risk ;
rdfs:subClassOf ngm:concentration-risk ;
rdfs:subClassOf ngm:decentralisation ;
rdfs:subClassOf ngm:network-security ;
rdfs:subClassOf ngm:systemic-risk ;
rdfs:subClassOf _:r3092 ;
rdfs:subClassOf _:r3093 ;
rdfs:subClassOf _:r3094 ;
rdfs:subClassOf _:r3095 ;
rdfs:subClassOf _:r3096 ;
rdfs:subClassOf _:r3097 ;
rdfs:subClassOf _:r3098 ;
skos:broader ngm:bc-governance-and-regulation ;
skos:broader ngm:blockchain ;
vc:contrastsWith ngm:censorship-resistance ;
vc:contrastsWith ngm:decentralisation ;
vc:contrastsWith ngm:permissionlessness ;
vc:contrastsWith ngm:self-custody ;
vc:contrastsWith ngm:trustless-system ;
vc:dependsOn ngm:asic ;
vc:dependsOn ngm:bitcoin-proof-of-work-protocol ;
vc:dependsOn ngm:bitcoin-proof-of-work-protocol-core ;
vc:dependsOn ngm:exchange ;
vc:dependsOn ngm:lightning-network ;
vc:dependsOn ngm:mining ;
vc:dependsOn ngm:proof-of-work ;
vc:enables ngm:51-attack ;
vc:enables ngm:eclipse-attack ;
vc:enables ngm:protocol-capture ;
vc:enables ngm:regulatory-capture ;
vc:enables ngm:supply-chain-attack ;
vc:enables ngm:sybil-attack ;
vc:enables ngm:transaction-censorship ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:asic-manufacturer-duopoly ;
vc:hasPart ngm:custodial-concentration ;
vc:hasPart ngm:developer-centralisation ;
vc:hasPart ngm:geographic-hashrate-concentration ;
vc:hasPart ngm:institutional-holder-concentration ;
vc:hasPart ngm:lightning-network-hub-centralisation ;
vc:hasPart ngm:mining-pool-concentration ;
vc:implements ngm:gini-coefficient ;
vc:implements ngm:hashrate-distribution-analysis ;
vc:implements ngm:herfindahl-hirschman-index ;
vc:implements ngm:nakamoto-coefficient ;
vc:implements ngm:network-topology-analysis ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:51-attack ;
vc:relatedTo ngm:ant-pool ;
vc:relatedTo ngm:asic ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol-core ;
vc:relatedTo ngm:bitmain ;
vc:relatedTo ngm:black-rock ;
vc:relatedTo ngm:coinbase ;
vc:relatedTo ngm:exchange ;
vc:relatedTo ngm:foundry-usa ;
vc:relatedTo ngm:lightning-network ;
vc:relatedTo ngm:micro-bt ;
vc:relatedTo ngm:micro-strategy ;
vc:relatedTo ngm:mining ;
vc:relatedTo ngm:mining-pool ;
vc:relatedTo ngm:proof-of-work ;
vc:relatedTo ngm:regulatory-risk ;
vc:relatedTo ngm:stratum-v2 ;
vc:relatedTo ngm:sybil-attack ;
vc:requires ngm:asic ;
vc:requires ngm:bitcoin-proof-of-work-protocol-core ;
vc:requires ngm:bitcoin-proof-of-work-protocol-network ;
vc:requires ngm:full-node ;
vc:requires ngm:lightning-network ;
vc:requires ngm:mining-pool ;
vc:requires ngm:proof-of-work ;
vc:slug "bitcoin-centralisation-risks" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:bis-crypto-risk-assessment-framework ;
vc:standardizedBy ngm:cambridge-centre-for-alternative-finance-mining-reports ;
vc:standardizedBy ngm:fsb-crypto-asset-monitoring-framework ;
vc:standardizedBy ngm:nakamoto-coefficient ;
vc:supports ngm:decentralisation-monitoring ;
vc:supports ngm:governance-reform ;
vc:supports ngm:network-security-analysis ;
vc:supports ngm:self-custody ;
vc:supports ngm:stratum-v2 ;
vc:uses ngm:custodial-wallet ;
vc:uses ngm:hash-power ;
vc:uses ngm:institutional-custody ;
vc:uses ngm:lightning-channel ;
vc:uses ngm:mining-pool ;
vc:uses ngm:open-source-development .
ngm:bitcoin-proof-of-work-protocol-core a owl:Class ;
rdfs:comment "Bitcoin Core is the canonical, open-source reference implementation of the Bitcoin protocol, written primarily in C++, which full nodes run to independently validate transactions, enforce consensus rules, and maintain a complete local copy of the blockchain. Originally released by Satoshi Nakamoto in January 2009 and subsequently maintained by a global community of contributors, it establishes the authoritative behaviour of the Bitcoin network through its codebase. The software bundles a peer-to-peer networking layer, a UTXO-based scripting engine, a deterministic wallet, a mining interface, and a JSON-RPC API for integration with higher-level applications. Protocol changes are introduced exclusively via Bitcoin Improvement Proposals, requiring broad community review and backward-compatible soft-fork activation to preserve network cohesion."@en ;
rdfs:label "Bitcoin Core"@en ;
rdfs:subClassOf ngm:blockchain-protocol ;
rdfs:subClassOf _:r3099 ;
rdfs:subClassOf _:r3100 ;
rdfs:subClassOf _:r3101 ;
rdfs:subClassOf _:r3102 ;
vc:bridgesTo ngm:cryptography ;
vc:bridgesTo ngm:distributed-systems ;
vc:contrastsWith ngm:ethereum ;
vc:contrastsWith ngm:proof-of-stake ;
vc:dependsOn ngm:bitcoin-proof-of-work-protocol-network ;
vc:dependsOn ngm:open-source-software ;
vc:enables ngm:de-fi ;
vc:enables ngm:digital-asset-custody ;
vc:enables ngm:lightning-network ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:bitcoin-scripting-language ;
vc:hasPart ngm:bitcoin-wallet ;
vc:hasPart ngm:json-data-interchange-format-rpc ;
vc:implements ngm:consensus-mechanism ;
vc:implements ngm:nakamoto-consensus ;
vc:implements ngm:proof-of-work ;
vc:implements ngm:utxo-model ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol-improvement-proposals ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol-mining ;
vc:relatedTo ngm:segregated-witness ;
vc:relatedTo ngm:soft-fork ;
vc:relatedTo ngm:taproot ;
vc:requires ngm:distributed-ledger ;
vc:requires ngm:full-node ;
vc:slug "bitcoin-core" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:cryptographic-hash-function ;
vc:uses ngm:digital-signature ;
vc:uses ngm:elliptic-curve-cryptography ;
vc:uses ngm:merkle-tree ;
vc:uses ngm:peer-to-peer-network .
ngm:bitcoin-proof-of-work-protocol-custody a owl:Class ;
rdfs:comment "Bitcoin custody is the practice and infrastructure for securely holding the private keys that control bitcoin, spanning self-custody, collaborative custody, and qualified institutional custodians. Approaches differ in how they distribute key control and recovery, using techniques such as multi-signature, hardware security modules, and multi-party computation to balance security against operational availability. Custody design is foundational to wallets, federations, and regulated products such as exchange-traded funds."@en ;
rdfs:label "Bitcoin Custody"@en ;
rdfs:subClassOf ngm:digital-asset ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol-etf ;
vc:relatedTo ngm:fedimint ;
vc:slug "bitcoin-custody" ;
vc:sourceDomain "blockchain" .
ngm:bitcoin-proof-of-work-protocol-de-fi a owl:Class ;
rdfs:comment "Bitcoin DeFi is the emerging set of decentralised finance applications, such as lending, swaps, and stablecoins, built on or anchored to the Bitcoin network. Because Bitcoin's base layer has limited scripting, these applications typically rely on layers and sidechains, including Lightning, Taproot assets, RGB, and Layer-3 protocols, to add programmability. The goal is to bring DeFi functionality to Bitcoin's liquidity and security while preserving its conservative base-layer design."@en ;
rdfs:label "Bitcoin DeFi"@en ;
rdfs:subClassOf ngm:de-fi ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:btc-layer-3 ;
vc:slug "bitcoin-de-fi" ;
vc:sourceDomain "blockchain" .
ngm:bitcoin-proof-of-work-protocol-distribution a owl:Class ;
rdfs:comment "Bitcoin Distribution is the sub-field of Blockchain economics that measures, models, and interprets the allocation of Bitcoin's circulating supply across identifiable holder categories — individuals, corporations, governments, miners, exchanges, custodians, and the permanently lost or provabl..."@en ;
rdfs:label "Bitcoin Distribution"@en ;
rdfs:subClassOf ngm:bc-defi-and-economics ;
rdfs:subClassOf ngm:bitcoin-proof-of-work-protocol ;
rdfs:subClassOf ngm:bitcoin-proof-of-work-protocol-as-money ;
rdfs:subClassOf ngm:bitcoin-proof-of-work-protocol-environmental-issues ;
rdfs:subClassOf ngm:bitcoin-proof-of-work-protocol-technical-overview ;
rdfs:subClassOf ngm:bitcoin-proof-of-work-protocol-value-proposition ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf _:r3103 ;
rdfs:subClassOf _:r3104 ;
rdfs:subClassOf _:r3105 ;
rdfs:subClassOf _:r3106 ;
rdfs:subClassOf _:r3107 ;
rdfs:subClassOf _:r3108 ;
rdfs:subClassOf _:r3109 ;
rdfs:subClassOf _:r3110 ;
rdfs:subClassOf _:r3111 ;
rdfs:subClassOf _:r3112 ;
rdfs:subClassOf _:r3113 ;
rdfs:subClassOf _:r3114 ;
skos:broader ngm:bc-defi-and-economics ;
skos:broader ngm:blockchain ;
vc:contrastsWith ngm:algorithmic-bias-and-variance ;
vc:contrastsWith ngm:bitcoin-proof-of-work-protocol-centralisation-risks ;
vc:contrastsWith ngm:bitcoin-proof-of-work-protocol-environmental-issues ;
vc:contrastsWith ngm:blockchain-as-a-service ;
vc:contrastsWith ngm:cbdc-frameworks ;
vc:dependsOn ngm:bitcoin-proof-of-work-protocol-halving ;
vc:dependsOn ngm:bitcoin-proof-of-work-protocol-mining ;
vc:dependsOn ngm:bitcoin-proof-of-work-protocol-technical-overview ;
vc:dependsOn ngm:blockchain-network ;
vc:dependsOn ngm:cryptographic-addresses ;
vc:dependsOn ngm:proof-of-work ;
vc:dependsOn ngm:utxo-model ;
vc:enables ngm:aml-kyc-compliance ;
vc:enables ngm:bitcoin-proof-of-work-protocol ;
vc:enables ngm:bitcoin-proof-of-work-protocol-as-money ;
vc:enables ngm:bitcoin-proof-of-work-protocol-centralisation-risks ;
vc:enables ngm:bitcoin-proof-of-work-protocol-etf ;
vc:enables ngm:bitcoin-proof-of-work-protocol-value-proposition ;
vc:enables ngm:micro-strategy ;
vc:enables ngm:strategic-bitcoin-reserve ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:bitcoin-proof-of-work-protocol-halving ;
vc:hasPart ngm:dormant-supply ;
vc:hasPart ngm:gini-coefficient ;
vc:hasPart ngm:hodl-waves ;
vc:hasPart ngm:long-term-holders ;
vc:hasPart ngm:lost-coins ;
vc:hasPart ngm:nakamoto-coefficient ;
vc:hasPart ngm:satoshi-nakamoto ;
vc:hasPart ngm:short-term-holders ;
vc:hasPart ngm:utxo-model ;
vc:hasPart ngm:whale-addresses ;
vc:implements ngm:bitcoin-proof-of-work-protocol-etf ;
vc:implements ngm:bitcoin-proof-of-work-protocol-halving ;
vc:implements ngm:blockchain-analysis ;
vc:implements ngm:gini-coefficient ;
vc:implements ngm:hodl-waves ;
vc:implements ngm:nakamoto-coefficient ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol-centralisation-risks ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol-environmental-issues ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol-etf ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol-mining ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol-technical-overview ;
vc:relatedTo ngm:blockchain-interoperability ;
vc:relatedTo ngm:blockchain-network ;
vc:relatedTo ngm:btc-layer-3 ;
vc:relatedTo ngm:cashu ;
vc:relatedTo ngm:cbdcs ;
vc:requires ngm:aml-kyc-compliance ;
vc:requires ngm:bitcoin-proof-of-work-protocol-mining ;
vc:requires ngm:bitcoin-proof-of-work-protocol-technical-overview ;
vc:requires ngm:blockchain-analysis ;
vc:requires ngm:cryptographic-addresses ;
vc:requires ngm:on-chain-data ;
vc:requires ngm:utxo-model ;
vc:slug "bitcoin-distribution" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:aml-kyc-compliance ;
vc:standardizedBy ngm:bitcoin-proof-of-work-protocol-technical-overview ;
vc:standardizedBy ngm:blockchain ;
vc:standardizedBy ngm:blockchain-network ;
vc:supports ngm:aml-kyc-compliance ;
vc:supports ngm:bitcoin-proof-of-work-protocol-as-money ;
vc:supports ngm:bitcoin-proof-of-work-protocol-centralisation-risks ;
vc:supports ngm:bitcoin-proof-of-work-protocol-environmental-issues ;
vc:supports ngm:bitcoin-proof-of-work-protocol-etf ;
vc:supports ngm:bitcoin-proof-of-work-protocol-value-proposition ;
vc:supports ngm:cbdc-frameworks ;
vc:supports ngm:micro-strategy ;
vc:uses ngm:bitcoin-proof-of-work-protocol-halving ;
vc:uses ngm:bitinfocharts ;
vc:uses ngm:blockchain-analysis ;
vc:uses ngm:chainalysis ;
vc:uses ngm:cryptoquant ;
vc:uses ngm:glassnode .
ngm:bitcoin-proof-of-work-protocol-environmental-issues a owl:Class ;
rdfs:comment "Bitcoin Environmental Issues refers to the multi-dimensional ecological footprint generated by Bitcoin's Proof of Work (PoW) consensus mechanism and the extensive ASIC mining hardware infrastructure that sustains it."@en ;
rdfs:label "Bitcoin Environmental Issues"@en ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
rdfs:subClassOf ngm:blockchain-sustainability ;
rdfs:subClassOf ngm:climate-finance ;
rdfs:subClassOf ngm:digital-asset-ecology ;
rdfs:subClassOf ngm:energy-economics ;
rdfs:subClassOf ngm:environmental-assessment ;
rdfs:subClassOf _:r3117 ;
rdfs:subClassOf _:r3118 ;
rdfs:subClassOf _:r3119 ;
rdfs:subClassOf _:r3120 ;
rdfs:subClassOf _:r3121 ;
rdfs:subClassOf _:r3122 ;
rdfs:subClassOf _:r3123 ;
rdfs:subClassOf _:r3124 ;
rdfs:subClassOf _:r3125 ;
rdfs:subClassOf _:r3126 ;
rdfs:subClassOf _:r3127 ;
rdfs:subClassOf _:r3128 ;
rdfs:subClassOf _:r3129 ;
rdfs:subClassOf _:r3130 ;
skos:broader ngm:bc-governance-and-regulation ;
vc:bridgesTo ngm:sustainability ;
vc:contrastsWith ngm:data-center-energy ;
vc:contrastsWith ngm:ethereum-smart-contract-platform ;
vc:contrastsWith ngm:gold-mining-energy ;
vc:contrastsWith ngm:proof-of-stake ;
vc:contrastsWith ngm:traditional-financial-infrastructure-energy ;
vc:dependsOn ngm:asic-hardware ;
vc:dependsOn ngm:bitcoin-proof-of-work-protocol ;
vc:dependsOn ngm:electricity-markets ;
vc:dependsOn ngm:fossil-fuel-infrastructure ;
vc:dependsOn ngm:mining ;
vc:dependsOn ngm:proof-of-work ;
vc:dependsOn ngm:renewable-energy-capacity ;
vc:enables ngm:demand-response ;
vc:enables ngm:heat-reuse-applications ;
vc:enables ngm:methane-emissions-reduction ;
vc:enables ngm:renewable-energy-integration ;
vc:enables ngm:stranded-energy-monetisation ;
vc:enables ngm:sustainable-bitcoin-certificates ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:asic-e-waste ;
vc:hasPart ngm:carbon-credits ;
vc:hasPart ngm:cbeci ;
vc:hasPart ngm:demand-response-mining ;
vc:hasPart ngm:heat-reuse ;
vc:hasPart ngm:methane-mitigation-mining ;
vc:hasPart ngm:proof-of-work-energy-consumption ;
vc:hasPart ngm:stranded-energy-monetisation ;
vc:hasPart ngm:sustainable-bitcoin-protocol ;
vc:implements ngm:carbon-footprint-measurement ;
vc:implements ngm:demand-response ;
vc:implements ngm:digital-flare-mitigation ;
vc:implements ngm:esg-disclosure-framework ;
vc:implements ngm:life-cycle-assessment ;
vc:qualityScore "0.54"^^xsd:float ;
vc:relatedTo ngm:carbon-footprint ;
vc:relatedTo ngm:cbeci ;
vc:relatedTo ngm:climate-policy ;
vc:relatedTo ngm:e-waste ;
vc:relatedTo ngm:energy-markets ;
vc:relatedTo ngm:esg-investing ;
vc:relatedTo ngm:methane-emissions ;
vc:relatedTo ngm:mining-economics ;
vc:relatedTo ngm:proof-of-work ;
vc:relatedTo ngm:renewable-energy ;
vc:relatedTo ngm:stranded-energy ;
vc:relatedTo ngm:sustainability ;
vc:requires ngm:asic-hardware ;
vc:requires ngm:carbon-accounting ;
vc:requires ngm:cooling-system ;
vc:requires ngm:energy-data-reporting ;
vc:requires ngm:grid-infrastructure ;
vc:requires ngm:hash-rate ;
vc:slug "bitcoin-environmental-issues" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:bc-0482-eu-mica-regulation ;
vc:standardizedBy ngm:cambridge-centre-for-alternative-finance ;
vc:standardizedBy ngm:eu-mi-ca-regulation ;
vc:standardizedBy ngm:fasb-asu-2023-08 ;
vc:standardizedBy ngm:iso-14040 ;
vc:standardizedBy ngm:sustainable-bitcoin-protocol ;
vc:supports ngm:carbon-neutrality ;
vc:supports ngm:district-heating ;
vc:supports ngm:esg-investing ;
vc:supports ngm:grid-stability ;
vc:supports ngm:methane-abatement ;
vc:supports ngm:renewable-energy ;
vc:uses ngm:carbon-accounting ;
vc:uses ngm:cbeci ;
vc:uses ngm:demand-response ;
vc:uses ngm:heat-recovery-systems ;
vc:uses ngm:immersion-cooling ;
vc:uses ngm:life-cycle-assessment ;
vc:uses ngm:sustainable-bitcoin-protocol .
ngm:bitcoin-proof-of-work-protocol-etf a owl:Class ;
rdfs:comment "A Bitcoin ETF (Bitcoin Exchange-Traded Fund) is a regulated, exchange-listed pooled investment vehicle providing investors fungible share-based exposure to the spot price of Bitcoin (or, in the case of futures-based variants, to rolling CME Bitcoin futures contracts) through traditional broke..."@en ;
rdfs:label "Bitcoin ETF"@en ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
rdfs:subClassOf ngm:bc-token-and-asset ;
rdfs:subClassOf ngm:bitcoin-exposure-product ;
rdfs:subClassOf ngm:exchange-traded-fund ;
rdfs:subClassOf ngm:passive-index-product ;
rdfs:subClassOf ngm:pooled-investment-vehicle ;
rdfs:subClassOf ngm:regulated-investment-company ;
rdfs:subClassOf _:r3115 ;
rdfs:subClassOf _:r3116 ;
skos:broader ngm:bc-governance-and-regulation ;
skos:broader ngm:bc-token-and-asset ;
vc:contrastsWith ngm:bitcoin-lightning-wallet ;
vc:contrastsWith ngm:bitcoin-mining-equity ;
vc:contrastsWith ngm:grayscale-bitcoin-trust ;
vc:contrastsWith ngm:micro-strategy ;
vc:contrastsWith ngm:proshares-bito ;
vc:contrastsWith ngm:self-custody-bitcoin ;
vc:contrastsWith ngm:spot-bitcoin-holdings ;
vc:dependsOn ngm:authorized-participant-network ;
vc:dependsOn ngm:bitcoin-proof-of-work-protocol ;
vc:dependsOn ngm:bitcoin-proof-of-work-protocol-network ;
vc:dependsOn ngm:cme-bitcoin-reference-rate ;
vc:dependsOn ngm:market-maker-network ;
vc:dependsOn ngm:qualified-custodian ;
vc:dependsOn ngm:stock-exchange ;
vc:enables ngm:bitcoin-inclusion-in-model-portfolio ;
vc:enables ngm:brokerage-account-bitcoin-access ;
vc:enables ngm:options-on-bitcoin-etf ;
vc:enables ngm:pension-fund-bitcoin-allocation ;
vc:enables ngm:retirement-account-bitcoin-allocation ;
vc:enables ngm:tax-advantaged-bitcoin-exposure ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:authorized-participant ;
vc:hasPart ngm:bitcoin-proof-of-work-protocol-custody ;
vc:hasPart ngm:bitcoin-reference-rate ;
vc:hasPart ngm:creation-unit-basket ;
vc:hasPart ngm:fund-administrator ;
vc:hasPart ngm:net-asset-value-calculation ;
vc:hasPart ngm:trust-agreement ;
vc:implements ngm:cash-creation-process ;
vc:implements ngm:daily-creation-redemption-mechanism ;
vc:implements ngm:in-kind-creation-process ;
vc:implements ngm:investment-company-act-1940-wrapper ;
vc:implements ngm:nav-based-pricing ;
vc:implements ngm:passive-bitcoin-tracking ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:bitcoin-options ;
vc:relatedTo ngm:european-bitcoin-etp ;
vc:relatedTo ngm:grayscale-v-sec ;
vc:relatedTo ngm:hong-kong-spot-bitcoin-etf ;
vc:relatedTo ngm:monochrome-ibtc ;
vc:relatedTo ngm:purpose-bitcoin-etf ;
vc:relatedTo ngm:spot-ethereum-etf ;
vc:requires ngm:fund-sponsor ;
vc:requires ngm:independent-trustee ;
vc:requires ngm:qualified-custodian ;
vc:requires ngm:rule-19b-4-approval ;
vc:requires ngm:sec-form-s-1-registration ;
vc:requires ngm:stock-exchange-listing ;
vc:requires ngm:surveillance-sharing-agreement ;
vc:slug "bitcoin-etf" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:cftc-commodity-classification ;
vc:standardizedBy ngm:fasb-asu-2023-08 ;
vc:standardizedBy ngm:fca-cryptoasset-promotions-regime ;
vc:standardizedBy ngm:investment-company-act-1940 ;
vc:standardizedBy ngm:sec-form-s-1 ;
vc:standardizedBy ngm:sec-rule-19b-4 ;
vc:standardizedBy ngm:securities-act-1933 ;
vc:standardizedBy ngm:securities-exchange-act-1934 ;
vc:supports ngm:bitcoin-liquidity ;
vc:supports ngm:institutional-bitcoin-adoption ;
vc:supports ngm:price-discovery ;
vc:supports ngm:regulated-bitcoin-market ;
vc:supports ngm:retail-bitcoin-access ;
vc:supports ngm:wealth-manager-distribution ;
vc:uses ngm:anchorage-digital ;
vc:uses ngm:bit-go ;
vc:uses ngm:cme-brr ;
vc:uses ngm:coinbase-custody ;
vc:uses ngm:cold-storage ;
vc:uses ngm:fidelity-digital-assets ;
vc:uses ngm:gemini-custody ;
vc:uses ngm:multi-signature-wallet ;
vc:uses ngm:multi-signature-wallets .
ngm:bitcoin-proof-of-work-protocol-etf-custody a owl:Class ;
rdfs:comment "Bitcoin ETF custody is the institutional safekeeping of the bitcoin backing a spot exchange-traded fund, performed by qualified custodians under regulatory and audit requirements. It typically uses cold storage with multi-signature or multi-party-computation key management, segregation of client assets, insurance, and proof-of-reserves attestation. This custody model bridges traditional regulated finance and on-chain asset control, and is central to the integrity of spot Bitcoin ETFs."@en ;
rdfs:label "Bitcoin ETF Custody"@en ;
rdfs:subClassOf ngm:digital-asset ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:multi-sig-governance ;
vc:slug "bitcoin-etf-custody" ;
vc:sourceDomain "blockchain" .
ngm:bitcoin-proof-of-work-protocol-fungible-token-protocols a owl:Class ;
rdfs:comment "Runes and Glyphs refers to two complementary Bitcoin token protocols: Runes, which encodes fungible token balances directly in Bitcoin transaction outputs using OP_RETURN data, and Glyphs, a related protocol developed by Melvin Carvalho that encodes token metadata as on-chain inscriptions compatible with the Ordinals framework. Together they extend Bitcoin's base layer with native fungible asset issuance without requiring a separate blockchain, enabling DAOs, project tokens, and programmable digital objects on Bitcoin testnet and mainnet."@en ;
rdfs:label "Bitcoin Fungible Token Protocols"@en ;
rdfs:subClassOf ngm:software-engineering ;
vc:enables ngm:asset-tokenisation ;
vc:enables ngm:digital-asset ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:isPartOf ngm:blockchain ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:decentralised-autonomous-organisation ;
vc:slug "bitcoin-fungible-token-protocols" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:digital-objects ;
vc:uses ngm:nft .
ngm:bitcoin-proof-of-work-protocol-halving a owl:Class ;
rdfs:comment "The Bitcoin halving is a protocol-enforced event, occurring approximately every 210,000 blocks (roughly four years), at which the block subsidy paid to miners is cut in half. It implements Bitcoin's disinflationary monetary policy, capping total supply at 21 million coins and progressively reducing new issuance until it reaches zero around the year 2140. Halvings have historically preceded major shifts in mining economics and market price, and they are central to Bitcoin's narrative as a scarce, predictably issued digital asset."@en ;
rdfs:label "Bitcoin Halving"@en ;
rdfs:subClassOf ngm:mechanism-design ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol ;
vc:relatedTo ngm:mining-pool ;
vc:relatedTo ngm:proof-of-work ;
vc:slug "bitcoin-halving" ;
vc:sourceDomain "blockchain" .
ngm:bitcoin-proof-of-work-protocol-improvement-proposals a owl:Class ;
rdfs:comment "Bitcoin Improvement Proposals (BIPs) are the formal design documents through which changes, enhancements, and new features are proposed and ratified for the Bitcoin protocol and its broader ecosystem. First introduced by Amir Taaki in 2011, modelled on Python's PEP and Python Enhancement Proposal process, BIPs serve as the primary coordination mechanism for a decentralised developer community that lacks any central authority. Each BIP progresses through a defined lifecycle — draft, proposed, final, and optionally superseded — and must achieve rough consensus among economic nodes, miners, and users before activation. BIPs are organised into three tracks: Standards Track (protocol-level changes requiring network-wide adoption), Informational (guidelines and best practices), and Process (procedural rules governing the BIP process itself)."@en ;
rdfs:label "Bitcoin Improvement Proposals"@en ;
rdfs:subClassOf ngm:blockchain-governance ;
rdfs:subClassOf _:r3131 ;
rdfs:subClassOf _:r3132 ;
rdfs:subClassOf _:r3133 ;
rdfs:subClassOf _:r3134 ;
rdfs:subClassOf _:r3135 ;
vc:bridgesTo ngm:cryptographic-protocol ;
vc:bridgesTo ngm:distributed-systems-governance ;
vc:contrastsWith ngm:eip ;
vc:contrastsWith ngm:ethereum-improvement-proposal ;
vc:contrastsWith ngm:ietf-rfc ;
vc:contrastsWith ngm:w3c-recommendation ;
vc:dependsOn ngm:bitcoin-proof-of-work-protocol-core ;
vc:dependsOn ngm:bitcoin-proof-of-work-protocol-network ;
vc:dependsOn ngm:consensus-rule ;
vc:enables ngm:bitcoin-proof-of-work-protocol-technical-overview ;
vc:enables ngm:hard-fork ;
vc:enables ngm:protocol-upgrade ;
vc:enables ngm:protocol-upgrades ;
vc:enables ngm:schnorr-signatures ;
vc:enables ngm:soft-fork ;
vc:enables ngm:taproot ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:bip-141 ;
vc:hasPart ngm:bip-141-segwit ;
vc:hasPart ngm:bip-173 ;
vc:hasPart ngm:bip-173-bech32 ;
vc:hasPart ngm:bip-32 ;
vc:hasPart ngm:bip-32-hd-wallets ;
vc:hasPart ngm:bip-340 ;
vc:hasPart ngm:bip-340-schnorr-signatures ;
vc:hasPart ngm:bip-341 ;
vc:hasPart ngm:bip-341-taproot ;
vc:implements ngm:decentralised-governance ;
vc:implements ngm:standards-process ;
vc:isPartOf ngm:open-source-governance ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:digital-signature ;
vc:relatedTo ngm:hd-wallet ;
vc:relatedTo ngm:lightning-network ;
vc:relatedTo ngm:segregated-witness ;
vc:requires ngm:peer-review ;
vc:requires ngm:rough-consensus ;
vc:slug "bitcoin-improvement-proposals" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:blockchain-protocol ;
vc:uses ngm:git-hub ;
vc:uses ngm:miner-signalling ;
vc:uses ngm:user-activated-soft-fork .
ngm:bitcoin-proof-of-work-protocol-layer-2 a owl:Class ;
rdfs:comment "Bitcoin Layer 2 refers to protocols built on top of the Bitcoin base chain that increase transaction throughput, reduce fees, or add functionality while inheriting Bitcoin's security. Examples include the Lightning Network for fast payments and federated systems such as Fedimint and Cashu for custodial and ecash-style scaling. These layers settle to the base chain periodically, trading some on-chain finality for speed and cost efficiency."@en ;
rdfs:label "Bitcoin Layer 2"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:cashu ;
vc:relatedTo ngm:fedimint ;
vc:slug "bitcoin-layer-2" ;
vc:sourceDomain "blockchain" .
ngm:bitcoin-proof-of-work-protocol-lightning-network a owl:Class ;
rdfs:comment "The Bitcoin Lightning Network is a layer-two payment protocol built on top of Bitcoin that enables fast, low-cost transactions through bidirectional payment channels. Two parties lock funds in a multisignature channel and exchange signed balance updates off-chain, settling the final state on the Bitcoin blockchain only when the channel closes. Payments can be routed across a network of connected channels, allowing transfers between parties that do not share a direct channel."@en ;
rdfs:label "Bitcoin Lightning Network"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf ngm:blockchain-domain ;
rdfs:subClassOf _:r3136 ;
rdfs:subClassOf _:r3137 ;
rdfs:subClassOf _:r3138 ;
rdfs:subClassOf _:r3139 ;
rdfs:subClassOf _:r3140 ;
rdfs:subClassOf _:r3141 ;
rdfs:subClassOf _:r3142 ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:bridgesTo ngm:bc-defi-and-economics ;
vc:bridgesTo ngm:de-fi ;
vc:bridgesTo ngm:liquid-network ;
vc:bridgesTo ngm:payment-systems-domain ;
vc:contrastsWith ngm:bitcoin-proof-of-work-protocol ;
vc:contrastsWith ngm:state-channel ;
vc:dependsOn ngm:channel-liquidity ;
vc:dependsOn ngm:utxo-model ;
vc:enables ngm:atomic-swap ;
vc:enables ngm:instant-settlement ;
vc:enables ngm:micropayments ;
vc:enables ngm:streaming-payments ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:channel-factory ;
vc:hasPart ngm:htlc ;
vc:hasPart ngm:onion-routing ;
vc:hasPart ngm:payment-channel ;
vc:implements ngm:bolt-specifications ;
vc:implements ngm:source-routing ;
vc:isPartOf ngm:bitcoin ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:routing-algorithm ;
vc:relatedTo ngm:watchtower-service ;
vc:requires ngm:bitcoin-proof-of-work-protocol ;
vc:requires ngm:multisignature ;
vc:requires ngm:segregated-witness ;
vc:slug "bitcoin-lightning-network" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:cryptographic-hash-function ;
vc:uses ngm:elliptic-curve-cryptography .
ngm:bitcoin-proof-of-work-protocol-mining a owl:Class ;
rdfs:comment "Bitcoin Mining is the proof-of-work Nakamoto consensus process by which the Bitcoin blockchain is extended, secured, and monetised through competitive computation of SHA-256 double-hash preimages whose output, interpreted as a 256-bit unsigned integer, falls below a network-ad..."@en ;
rdfs:label "Bitcoin Mining"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf ngm:bc-token-and-asset ;
rdfs:subClassOf ngm:consensus-mechanism ;
rdfs:subClassOf ngm:cryptographic-mining ;
rdfs:subClassOf ngm:distributed-computing ;
rdfs:subClassOf ngm:industrial-process ;
rdfs:subClassOf ngm:proof-of-work ;
rdfs:subClassOf _:r3143 ;
rdfs:subClassOf _:r3144 ;
rdfs:subClassOf _:r3145 ;
rdfs:subClassOf _:r3146 ;
rdfs:subClassOf _:r3147 ;
rdfs:subClassOf _:r3148 ;
rdfs:subClassOf _:r3149 ;
rdfs:subClassOf _:r3150 ;
rdfs:subClassOf _:r3151 ;
rdfs:subClassOf _:r3152 ;
rdfs:subClassOf _:r3153 ;
rdfs:subClassOf _:r3154 ;
rdfs:subClassOf _:r3155 ;
rdfs:subClassOf _:r3156 ;
skos:broader ngm:bc-protocol-and-consensus ;
skos:broader ngm:bc-token-and-asset ;
vc:bridgesTo ngm:infra-security-and-identity ;
vc:contrastsWith ngm:cpu-mining ;
vc:contrastsWith ngm:gpu-mining-ethereum ;
vc:contrastsWith ngm:kaspa-mining ;
vc:contrastsWith ngm:monero-randomx ;
vc:contrastsWith ngm:proof-of-authority ;
vc:contrastsWith ngm:proof-of-space ;
vc:contrastsWith ngm:proof-of-stake ;
vc:dependsOn ngm:bitcoin-protocol ;
vc:dependsOn ngm:electrical-grid ;
vc:dependsOn ngm:internet-infrastructure ;
vc:dependsOn ngm:power-purchase-agreement ;
vc:dependsOn ngm:semiconductor-fabrication ;
vc:dependsOn ngm:sha-256 ;
vc:enables ngm:bitcoin-issuance ;
vc:enables ngm:blockchain-security ;
vc:enables ngm:demand-response ;
vc:enables ngm:double-spend-prevention ;
vc:enables ngm:permissionless-settlement ;
vc:enables ngm:transaction-confirmation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:asic ;
vc:hasPart ngm:block-header ;
vc:hasPart ngm:coinbase-transaction ;
vc:hasPart ngm:difficulty-target ;
vc:hasPart ngm:mempool ;
vc:hasPart ngm:merkle-tree ;
vc:hasPart ngm:mining-pool ;
vc:hasPart ngm:nonce-search ;
vc:hasPart ngm:sha-256-hashing ;
vc:implements ngm:coinbase-reward-distribution ;
vc:implements ngm:difficulty-adjustment ;
vc:implements ngm:halving-schedule ;
vc:implements ngm:longest-chain-rule ;
vc:implements ngm:nakamoto-consensus ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:ai-hpc-pivot ;
vc:relatedTo ngm:asic-manufacturer ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol ;
vc:relatedTo ngm:demand-response ;
vc:relatedTo ngm:halving ;
vc:relatedTo ngm:hash-rate ;
vc:relatedTo ngm:mining-pool ;
vc:relatedTo ngm:renewable-energy ;
vc:relatedTo ngm:stranded-gas ;
vc:requires ngm:asic-hardware ;
vc:requires ngm:cooling-system ;
vc:requires ngm:electricity ;
vc:requires ngm:full-node ;
vc:requires ngm:network-connectivity ;
vc:requires ngm:stratum-protocol ;
vc:slug "bitcoin-mining" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:bip-34 ;
vc:standardizedBy ngm:bip-9 ;
vc:standardizedBy ngm:bip-91 ;
vc:standardizedBy ngm:bitcoin-proof-of-work-protocol-core ;
vc:standardizedBy ngm:cbeci-methodology ;
vc:standardizedBy ngm:stratum-v2 ;
vc:supports ngm:bitcoin-network-security ;
vc:supports ngm:decentralisation ;
vc:supports ngm:energy-grid-stability ;
vc:supports ngm:sound-money ;
vc:supports ngm:stranded-energy-monetisation ;
vc:uses ngm:double-hashing ;
vc:uses ngm:hashboards ;
vc:uses ngm:immersion-cooling ;
vc:uses ngm:merkle-root ;
vc:uses ngm:sha-256 ;
vc:uses ngm:stratum-v1 ;
vc:uses ngm:stratum-v2 .
ngm:bitcoin-proof-of-work-protocol-native-de-fi a skos:Concept ;
rdfs:label "Bitcoin Proof Of Work Protocol Native De Fi"@en .
ngm:bitcoin-proof-of-work-protocol-network a owl:Class ;
rdfs:comment "The Bitcoin Network is the global, permissionless peer-to-peer infrastructure underpinning the Bitcoin cryptocurrency, comprising full nodes, mining nodes, and the gossip protocol that propagates signed transactions and mined blocks across the internet without central coordination. It employs the Nakamoto consensus mechanism—proof-of-work mining on the SHA-256 hash function—to achieve Byzantine-fault-tolerant agreement on a single shared transaction ledger among mutually distrusting participants. The network enforces deterministic monetary policy through its protocol rules, automatically adjusting mining difficulty every 2,016 blocks to target a ten-minute inter-block interval and capping total issuance at 21 million BTC via a geometric halving schedule. Launched in January 2009, it is the longest-continuously-operated public blockchain and the foundational reference implementation for decentralised digital value transfer."@en ;
rdfs:label "Bitcoin Network"@en ;
rdfs:subClassOf ngm:peer-to-peer-network ;
rdfs:subClassOf _:r3157 ;
rdfs:subClassOf _:r3158 ;
rdfs:subClassOf _:r3159 ;
rdfs:subClassOf _:r3160 ;
rdfs:subClassOf _:r3161 ;
rdfs:subClassOf _:r3162 ;
rdfs:subClassOf _:r3163 ;
vc:bridgesTo ngm:central-bank-digital-currency-cbdc ;
vc:bridgesTo ngm:financial-infrastructure ;
vc:contrastsWith ngm:ethereum ;
vc:contrastsWith ngm:proof-of-stake ;
vc:dependsOn ngm:merkle-tree ;
vc:dependsOn ngm:public-key-cryptography ;
vc:enables ngm:cryptocurrency ;
vc:enables ngm:de-fi ;
vc:enables ngm:digital-asset-custody ;
vc:enables ngm:lightning-network ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:bitcoin-proof-of-work-protocol-mining ;
vc:hasPart ngm:bitcoin-script ;
vc:hasPart ngm:full-node ;
vc:hasPart ngm:mempool ;
vc:hasPart ngm:utxo-model ;
vc:implements ngm:bitcoin-proof-of-work-protocol-improvement-proposals ;
vc:implements ngm:segregated-witness ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol-technical-overview ;
vc:relatedTo ngm:blockchain ;
vc:relatedTo ngm:digital-currency ;
vc:requires ngm:distributed-ledger-technology ;
vc:requires ngm:internet-protocol ;
vc:slug "bitcoin-network" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:multisignature ;
vc:supports ngm:spv-verification ;
vc:uses ngm:cryptographic-primitive ;
vc:uses ngm:elliptic-curve-cryptography ;
vc:uses ngm:gossip-protocol ;
vc:uses ngm:nakamoto-consensus ;
vc:uses ngm:proof-of-work ;
vc:uses ngm:sha-256 .
ngm:bitcoin-proof-of-work-protocol-ordinals a owl:Class ;
rdfs:comment "Bitcoin Ordinals is a numbering scheme and inscription protocol that assigns a unique serial number to every individual satoshi on the Bitcoin network based on the order of its mining, enabling arbitrary content — text, images, code — to be embedded directly into Bitcoin transactions via the witness data introduced by SegWit and Taproot. Each inscription is permanently stored on-chain without requiring a separate token contract, making it a native non-fungible artefact within the Bitcoin base layer. The protocol was introduced by Casey Rodarmor in January 2023."@en ;
rdfs:label "Bitcoin Ordinals"@en ;
rdfs:subClassOf ngm:bitcoin-proof-of-work-protocol-network ;
rdfs:subClassOf _:r3164 ;
rdfs:subClassOf _:r3165 ;
rdfs:subClassOf _:r3166 ;
rdfs:subClassOf _:r3167 ;
rdfs:subClassOf _:r3168 ;
rdfs:subClassOf _:r3169 ;
vc:bridgesTo ngm:digital-collectible ;
vc:bridgesTo ngm:metaverse ;
vc:contrastsWith ngm:erc-721-standard ;
vc:contrastsWith ngm:nft ;
vc:contrastsWith ngm:smart-contract ;
vc:enables ngm:digital-ownership ;
vc:enables ngm:on-chain-storage ;
vc:enables ngm:tokenization ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:brc-20 ;
vc:hasPart ngm:inscription ;
vc:hasPart ngm:satoshi ;
vc:isPartOf ngm:blockchain ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:digital-art ;
vc:relatedTo ngm:digital-asset ;
vc:relatedTo ngm:mining ;
vc:relatedTo ngm:transaction-fee ;
vc:requires ngm:bitcoin-proof-of-work-protocol-core ;
vc:requires ngm:proof-of-work ;
vc:requires ngm:witness-data ;
vc:slug "bitcoin-ordinals" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:bitcoin-script ;
vc:uses ngm:blockchain-transaction ;
vc:uses ngm:seg-wit ;
vc:uses ngm:taproot ;
vc:uses ngm:utxo .
ngm:bitcoin-proof-of-work-protocol-related-links a owl:Class ;
rdfs:comment "Bitcoin Related Links is a curated reference collection aggregating news, technical resources, regulatory developments, and community analysis pertaining to the Bitcoin blockchain ecosystem. It encompasses coverage of Bitcoin as money, mining economics, environmental debates, ETF instruments, and the broader cryptocurrency landscape."@en ;
rdfs:label "Bitcoin related links"@en ;
rdfs:subClassOf ngm:bc-token-and-asset ;
rdfs:subClassOf _:r3235 ;
rdfs:subClassOf _:r3236 ;
rdfs:subClassOf _:r3237 ;
skos:broader ngm:bc-token-and-asset ;
vc:bridgesTo ngm:bitcoin-proof-of-work-protocol-environmental-issues ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:lightning-network ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:bitcoin-proof-of-work-protocol-as-money ;
vc:hasPart ngm:bitcoin-proof-of-work-protocol-etf ;
vc:hasPart ngm:bitcoin-proof-of-work-protocol-mining ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:blockchain ;
vc:relatedTo ngm:cryptocurrency ;
vc:slug "bitcoin-related-links" ;
vc:sourceDomain "blockchain" .
ngm:bitcoin-proof-of-work-protocol-standard a owl:Class ;
rdfs:comment "The Bitcoin Standard is an economic and monetary thesis proposing that Bitcoin's algorithmically enforced fixed supply of 21 million units, its decentralised Proof of Work consensus mechanism, and its censorship-resistant disinflationary issuance schedule collectively make it a superior store of value and the basis for a new international monetary order analogous to the historical gold standard. Drawing heavily on Austrian economics — particularly Ludwig von Mises's concept of sound money and Saifedean Ammous's eponymous 2018 treatise — the thesis holds that Bitcoin's predictable, politically immutable monetary policy immunises it against the purchasing-power erosion endemic to fiat currencies managed by central banks. In practice the standard informs corporate treasury reserve strategies, nation-state legal-tender experiments, and the design of Bitcoin ETF and custody infrastructure."@en ;
rdfs:label "Bitcoin Standard"@en ;
rdfs:subClassOf ngm:bc-token-and-asset ;
rdfs:subClassOf _:r3185 ;
rdfs:subClassOf _:r3186 ;
rdfs:subClassOf _:r3187 ;
skos:broader ngm:bc-token-and-asset ;
vc:bridgesTo ngm:digital-asset-governance ;
vc:bridgesTo ngm:macroeconomics ;
vc:contrastsWith ngm:central-bank-digital-currency-cbdc ;
vc:contrastsWith ngm:fiat-currency ;
vc:contrastsWith ngm:inflation ;
vc:dependsOn ngm:network-effects ;
vc:dependsOn ngm:public-key-cryptography ;
vc:enables ngm:bitcoin-proof-of-work-protocol-etf ;
vc:enables ngm:sovereign-bitcoin-adoption ;
vc:enables ngm:strategic-bitcoin-reserve ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:austrian-economics ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol-as-money ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol-value-proposition ;
vc:relatedTo ngm:monetary-sovereignty ;
vc:relatedTo ngm:monetary-system ;
vc:relatedTo ngm:sound-money ;
vc:requires ngm:blockchain ;
vc:requires ngm:cryptographic-security ;
vc:requires ngm:decentralisation ;
vc:slug "bitcoin-standard" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:bitcoin-proof-of-work-protocol-mining ;
vc:uses ngm:cryptocurrency ;
vc:uses ngm:halving ;
vc:uses ngm:proof-of-work .
ngm:bitcoin-proof-of-work-protocol-technical-overview a owl:Class ;
rdfs:comment "Bitcoin Technical Overview is the canonical ontological concept encapsulating the complete technical architecture of the Bitcoin protocol — the first decentralised, permissionless, proof-of-work secured, UTXO-based peer-to-peer electronic cash system described by Satoshi Nakamoto in the 2008 whit..."@en ;
rdfs:label "Bitcoin Technical Overview"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf ngm:consensus-mechanism ;
rdfs:subClassOf ngm:cryptographic-protocol ;
rdfs:subClassOf ngm:distributed-ledger-technology ;
rdfs:subClassOf ngm:peer-to-peer-network ;
rdfs:subClassOf _:r3188 ;
rdfs:subClassOf _:r3189 ;
rdfs:subClassOf _:r3190 ;
rdfs:subClassOf _:r3191 ;
rdfs:subClassOf _:r3192 ;
rdfs:subClassOf _:r3193 ;
rdfs:subClassOf _:r3194 ;
rdfs:subClassOf _:r3195 ;
rdfs:subClassOf _:r3196 ;
rdfs:subClassOf _:r3197 ;
rdfs:subClassOf _:r3198 ;
rdfs:subClassOf _:r3199 ;
rdfs:subClassOf _:r3200 ;
rdfs:subClassOf _:r3201 ;
rdfs:subClassOf _:r3202 ;
rdfs:subClassOf _:r3203 ;
rdfs:subClassOf _:r3204 ;
rdfs:subClassOf _:r3205 ;
rdfs:subClassOf _:r3206 ;
rdfs:subClassOf _:r3207 ;
rdfs:subClassOf _:r3208 ;
rdfs:subClassOf _:r3209 ;
skos:broader ngm:bc-protocol-and-consensus ;
skos:broader ngm:blockchain ;
vc:contrastsWith ngm:account-model ;
vc:contrastsWith ngm:central-bank-digital-currency-cbdc ;
vc:contrastsWith ngm:ethereum-smart-contract-platform ;
vc:contrastsWith ngm:permissioned-blockchain ;
vc:contrastsWith ngm:proof-of-stake ;
vc:dependsOn ngm:cryptographic-hash ;
vc:dependsOn ngm:cryptographic-infrastructure ;
vc:dependsOn ngm:distributed-systems ;
vc:dependsOn ngm:elliptic-curve-cryptography ;
vc:dependsOn ngm:game-theory ;
vc:dependsOn ngm:network-theory ;
vc:enables ngm:de-fi ;
vc:enables ngm:digital-currency ;
vc:enables ngm:layer-2-protocols ;
vc:enables ngm:micropayments ;
vc:enables ngm:programmable-money ;
vc:enables ngm:smart-contracts ;
vc:enables ngm:trustless-payments ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:bip-process ;
vc:hasPart ngm:bitcoin-script ;
vc:hasPart ngm:block-structure ;
vc:hasPart ngm:cryptographic-hash ;
vc:hasPart ngm:difficulty-adjustment ;
vc:hasPart ngm:digital-signatures ;
vc:hasPart ngm:lightning-network ;
vc:hasPart ngm:mempool ;
vc:hasPart ngm:merkle-tree ;
vc:hasPart ngm:proof-of-work ;
vc:hasPart ngm:seg-wit ;
vc:hasPart ngm:taproot ;
vc:hasPart ngm:utxo-model ;
vc:implements ngm:difficulty-adjustment ;
vc:implements ngm:gossip-protocol ;
vc:implements ngm:halving-schedule ;
vc:implements ngm:merkle-tree ;
vc:implements ngm:nakamoto-consensus ;
vc:implements ngm:proof-of-work ;
vc:implements ngm:utxo-model ;
vc:qualityScore "0.54"^^xsd:float ;
vc:relatedTo ngm:blockchain ;
vc:relatedTo ngm:cryptocurrency ;
vc:relatedTo ngm:cryptography ;
vc:relatedTo ngm:decentralisation ;
vc:relatedTo ngm:digital-gold ;
vc:relatedTo ngm:monetary-policy ;
vc:relatedTo ngm:open-source-software ;
vc:requires ngm:digital-signatures ;
vc:requires ngm:elliptic-curve-cryptography ;
vc:requires ngm:hash-function ;
vc:requires ngm:mining ;
vc:requires ngm:peer-to-peer-network ;
vc:requires ngm:schnorr-signature ;
vc:requires ngm:schnorr-signatures ;
vc:requires ngm:secp256k1 ;
vc:requires ngm:sha-256 ;
vc:slug "bitcoin-technical-overview" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:bip-340 ;
vc:standardizedBy ngm:bip-341 ;
vc:standardizedBy ngm:bip-342 ;
vc:standardizedBy ngm:bip-process ;
vc:standardizedBy ngm:bitcoin-optech ;
vc:standardizedBy ngm:bitcoin-proof-of-work-protocol-core ;
vc:standardizedBy ngm:bolt-specifications ;
vc:supports ngm:lightning-network ;
vc:supports ngm:multisignature ;
vc:supports ngm:ordinals ;
vc:supports ngm:payment-channels ;
vc:supports ngm:rgb-protocol ;
vc:supports ngm:seg-wit ;
vc:supports ngm:taproot ;
vc:supports ngm:time-locked-contracts ;
vc:uses ngm:bloom-filter ;
vc:uses ngm:bloom-filters ;
vc:uses ngm:compact-block-relay ;
vc:uses ngm:ecdsa ;
vc:uses ngm:merkle-tree ;
vc:uses ngm:ripemd-160 ;
vc:uses ngm:schnorr-signature ;
vc:uses ngm:schnorr-signatures ;
vc:uses ngm:secp256k1 ;
vc:uses ngm:sha-256 .
ngm:bitcoin-proof-of-work-protocol-value-proposition a owl:Class ;
rdfs:comment "Bitcoin Value Proposition is the aggregate set of economic, monetary, and philosophical arguments that justify holding, using, or building on Bitcoin as a distinct and superior form of money, property, or network infrastructure."@en ;
rdfs:label "Bitcoin Value Proposition"@en ;
rdfs:subClassOf ngm:bc-defi-and-economics ;
rdfs:subClassOf ngm:bitcoin-proof-of-work-protocol ;
rdfs:subClassOf ngm:digital-asset ;
rdfs:subClassOf ngm:economic-philosophy ;
rdfs:subClassOf ngm:monetary-theory ;
rdfs:subClassOf ngm:sound-money ;
rdfs:subClassOf ngm:store-of-value ;
rdfs:subClassOf _:r3214 ;
rdfs:subClassOf _:r3215 ;
rdfs:subClassOf _:r3216 ;
rdfs:subClassOf _:r3217 ;
rdfs:subClassOf _:r3218 ;
rdfs:subClassOf _:r3219 ;
rdfs:subClassOf _:r3220 ;
rdfs:subClassOf _:r3221 ;
rdfs:subClassOf _:r3222 ;
rdfs:subClassOf _:r3223 ;
rdfs:subClassOf _:r3224 ;
rdfs:subClassOf _:r3225 ;
rdfs:subClassOf _:r3226 ;
rdfs:subClassOf _:r3227 ;
rdfs:subClassOf _:r3228 ;
rdfs:subClassOf _:r3229 ;
rdfs:subClassOf _:r3230 ;
skos:broader ngm:bc-defi-and-economics ;
vc:contrastsWith ngm:cbdcs ;
vc:contrastsWith ngm:de-fi ;
vc:contrastsWith ngm:ethereum-smart-contract-platform ;
vc:contrastsWith ngm:fiat-currency ;
vc:contrastsWith ngm:fractional-reserve-banking ;
vc:contrastsWith ngm:gold ;
vc:contrastsWith ngm:inflation ;
vc:contrastsWith ngm:monetary-debasement ;
vc:contrastsWith ngm:traditional-banking ;
vc:dependsOn ngm:asic-hardware ;
vc:dependsOn ngm:bitcoin-proof-of-work-protocol ;
vc:dependsOn ngm:bitcoin-proof-of-work-protocol-network ;
vc:dependsOn ngm:cryptographic-hash-function ;
vc:dependsOn ngm:global-internet-infrastructure ;
vc:dependsOn ngm:nakamoto-consensus ;
vc:dependsOn ngm:proof-of-work ;
vc:enables ngm:ai-agent-payments ;
vc:enables ngm:censorship-resistant-payments ;
vc:enables ngm:corporate-treasury-strategy ;
vc:enables ngm:financial-inclusion ;
vc:enables ngm:financial-sovereignty ;
vc:enables ngm:inflation-hedging ;
vc:enables ngm:machine-to-machine-payments ;
vc:enables ngm:remittances ;
vc:enables ngm:rural-electrification-subsidy ;
vc:enables ngm:self-custody ;
vc:enables ngm:store-of-value ;
vc:enables ngm:strategic-bitcoin-reserve ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:block-reward-halving ;
vc:hasPart ngm:censorship-resistance ;
vc:hasPart ngm:digital-scarcity ;
vc:hasPart ngm:financial-sovereignty ;
vc:hasPart ngm:hyperbitcoinization ;
vc:hasPart ngm:inflation-hedge ;
vc:hasPart ngm:lightning-network ;
vc:hasPart ngm:lindy-effect ;
vc:hasPart ngm:network-effects ;
vc:hasPart ngm:proof-of-work-security ;
vc:hasPart ngm:self-custody ;
vc:hasPart ngm:supply-cap ;
vc:implements ngm:austrian-economics ;
vc:implements ngm:bitcoin-proof-of-work-protocol-standard ;
vc:implements ngm:gresham-s-law ;
vc:implements ngm:hayek-denationalisation ;
vc:implements ngm:mises-regression-theorem ;
vc:implements ngm:nakamoto-consensus ;
vc:implements ngm:sound-money-principles ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:austrian-economics ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol-mining ;
vc:relatedTo ngm:black-rock-bitcoin-etf ;
vc:relatedTo ngm:block-reward-halving ;
vc:relatedTo ngm:digital-gold ;
vc:relatedTo ngm:financial-nihilism ;
vc:relatedTo ngm:hyperbitcoinization ;
vc:relatedTo ngm:lindy-effect ;
vc:relatedTo ngm:micro-strategy ;
vc:relatedTo ngm:network-effects ;
vc:relatedTo ngm:sound-money ;
vc:relatedTo ngm:stock-to-flow-model ;
vc:requires ngm:bitcoin-miners ;
vc:requires ngm:bitcoin-proof-of-work-protocol-network ;
vc:requires ngm:cryptographic-security ;
vc:requires ngm:decentralisation ;
vc:requires ngm:full-node ;
vc:requires ngm:open-source-protocol ;
vc:requires ngm:proof-of-work ;
vc:slug "bitcoin-value-proposition" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:bitcoin-proof-of-work-protocol-improvement-proposals ;
vc:standardizedBy ngm:bitcoin-proof-of-work-protocol-whitepaper ;
vc:standardizedBy ngm:fasb-asu-2023-08 ;
vc:standardizedBy ngm:sec-spot-bitcoin-etf-approval-2024 ;
vc:standardizedBy ngm:us-strategic-bitcoin-reserve-executive-order-2025 ;
vc:supports ngm:bitcoin-standard-adoption ;
vc:supports ngm:black-rock-bitcoin-etf ;
vc:supports ngm:el-salvador-bitcoin-adoption ;
vc:supports ngm:gridless ;
vc:supports ngm:human-rights-foundation-bitcoin-fund ;
vc:supports ngm:lightning-network ;
vc:supports ngm:micro-strategy ;
vc:supports ngm:strategic-bitcoin-reserve ;
vc:uses ngm:bitcoin-proof-of-work-protocol-etf ;
vc:uses ngm:cold-storage ;
vc:uses ngm:corporate-treasury-reserve ;
vc:uses ngm:l-402 ;
vc:uses ngm:lightning-network ;
vc:uses ngm:multisignature-wallets ;
vc:uses ngm:self-custody ;
vc:uses ngm:spot-bitcoin-etf ;
vc:uses ngm:spot-bitcoin-etfs ;
vc:uses ngm:x-402 .
ngm:bitcoin-proof-of-work-protocol-whitepaper a owl:Class ;
rdfs:comment "The October 2008 technical paper by pseudonymous author Satoshi Nakamoto, titled 'Bitcoin: A Peer-to-Peer Electronic Cash System', which introduced the design of a decentralised digital currency that eliminates reliance on trusted third parties. It proposed a chain of cryptographically linked blocks secured by proof-of-work consensus to prevent double-spending without a central authority. The paper synthesised prior work on digital cash, cryptographic hash functions, and distributed timestamps into a coherent, deployable protocol that was subsequently realised in the January 2009 Bitcoin genesis block launch."@en ;
rdfs:label "Bitcoin Whitepaper"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf _:r3231 ;
rdfs:subClassOf _:r3232 ;
rdfs:subClassOf _:r3233 ;
rdfs:subClassOf _:r3234 ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:bridgesTo ngm:decentralised-autonomous-organisation ;
vc:bridgesTo ngm:smart-contract ;
vc:bridgesTo ngm:zero-knowledge-proof ;
vc:contrastsWith ngm:centralised-payment-system ;
vc:contrastsWith ngm:proof-of-stake ;
vc:enables ngm:bitcoin-proof-of-work-protocol ;
vc:enables ngm:bitcoin-protocol ;
vc:enables ngm:blockchain-technology ;
vc:enables ngm:cryptocurrency ;
vc:enables ngm:de-fi ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:distributed-ledger ;
vc:implements ngm:peer-to-peer-network ;
vc:implements ngm:proof-of-work ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:byzantine-fault-tolerance ;
vc:relatedTo ngm:cypherpunk-movement ;
vc:relatedTo ngm:double-spending ;
vc:relatedTo ngm:genesis-block ;
vc:relatedTo ngm:lightning-network ;
vc:relatedTo ngm:satoshi-nakamoto ;
vc:requires ngm:cryptographic-hash-function ;
vc:requires ngm:digital-signature ;
vc:requires ngm:hashcash ;
vc:requires ngm:merkle-tree ;
vc:slug "bitcoin-whitepaper" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:elliptic-curve-cryptography ;
vc:uses ngm:sha-256 ;
vc:uses ngm:unspent-transaction-output .
ngm:bitcoin-protocol a owl:Class ;
rdfs:comment "The set of rules governing how Bitcoin transactions are formed, validated, and ordered into blocks by proof-of-work consensus, including the UTXO model, scripting system, block reward schedule, and difficulty adjustment mechanism."@en ;
rdfs:label "Bitcoin Protocol"@en ;
rdfs:subClassOf ngm:bitcoin-proof-of-work-protocol ;
rdfs:subClassOf _:r3173 ;
rdfs:subClassOf _:r3174 ;
rdfs:subClassOf _:r3175 ;
rdfs:subClassOf _:r3176 ;
rdfs:subClassOf _:r3177 ;
rdfs:subClassOf _:r3178 ;
rdfs:subClassOf _:r3179 ;
rdfs:subClassOf _:r3180 ;
rdfs:subClassOf _:r3181 ;
vc:bridgesTo ngm:block-reward ;
vc:bridgesTo ngm:de-fi ;
vc:bridgesTo ngm:digital-currency ;
vc:contrastsWith ngm:ethereum ;
vc:contrastsWith ngm:proof-of-stake ;
vc:enables ngm:bitcoin-script ;
vc:enables ngm:lightning-network ;
vc:enables ngm:peer-to-peer-payment ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:bitcoin-script ;
vc:hasPart ngm:block-reward ;
vc:hasPart ngm:difficulty-adjustment ;
vc:hasPart ngm:mempool ;
vc:implements ngm:byzantine-fault-tolerance ;
vc:implements ngm:nakamoto-consensus ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:blockchain ;
vc:relatedTo ngm:distributed-ledger ;
vc:relatedTo ngm:mining ;
vc:requires ngm:consensus-protocol ;
vc:requires ngm:cryptographic-hash-function ;
vc:requires ngm:digital-signature ;
vc:requires ngm:proof-of-work ;
vc:requires ngm:utxo ;
vc:slug "bitcoin-protocol" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:elliptic-curve-cryptography ;
vc:uses ngm:merkle-tree ;
vc:uses ngm:sha-256 .
ngm:bitcoin-reference-rate a skos:Concept ;
rdfs:label "Bitcoin Reference Rate"@en .
ngm:bitcoin-scalability a skos:Concept ;
rdfs:label "Bitcoin Scalability"@en .
ngm:bitcoin-script a owl:Class ;
rdfs:comment "Bitcoin Script is a non-Turing-complete, stack-based scripting language embedded in every Bitcoin transaction that defines the conditions under which unspent transaction outputs (UTXOs) may be spent. It consists of a constrained set of opcodes operating on a last-in-first-out (LIFO) stack, deliberately designed without loops or unbounded recursion to ensure guaranteed termination and predictable resource consumption. Script programs are expressed as paired locking scripts (scriptPubKey) and unlocking scripts (scriptSig or SegWit witness data) that encode spending conditions including digital signature verification, multisignature requirements, hash pre-image revelation, and time locks. Standard output templates — P2PKH, P2SH, P2WPKH, P2WSH, and P2TR — formalise the most common spending patterns used across the Bitcoin network."@en ;
rdfs:label "Bitcoin Script"@en ;
rdfs:subClassOf ngm:scripting-language ;
rdfs:subClassOf _:r3182 ;
rdfs:subClassOf _:r3183 ;
rdfs:subClassOf _:r3184 ;
vc:bridgesTo ngm:formal-verification ;
vc:bridgesTo ngm:zero-knowledge-proof ;
vc:contrastsWith ngm:ethereum-smart-contract-platform-virtual-machine ;
vc:contrastsWith ngm:solidity ;
vc:contrastsWith ngm:turing-complete-language ;
vc:enables ngm:atomic-swap ;
vc:enables ngm:bitcoin ;
vc:enables ngm:bitcoin-proof-of-work-protocol-ordinals ;
vc:enables ngm:hash-time-locked-contract ;
vc:enables ngm:lightning-network ;
vc:enables ngm:multisignature-wallets ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:scriptpubkey ;
vc:hasPart ngm:scriptsig ;
vc:hasPart ngm:witness-data ;
vc:implements ngm:pay-to-public-key-hash ;
vc:implements ngm:pay-to-script-hash ;
vc:implements ngm:taproot ;
vc:isPartOf ngm:bitcoin-proof-of-work-protocol-core ;
vc:isPartOf ngm:utxo-model ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:merklised-abstract-syntax-tree ;
vc:relatedTo ngm:programming-language ;
vc:relatedTo ngm:segregated-witness ;
vc:requires ngm:bitcoin-transaction ;
vc:requires ngm:stack-machine ;
vc:slug "bitcoin-script" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:bitcoin-proof-of-work-protocol-improvement-proposals ;
vc:uses ngm:cryptographic-hash-function ;
vc:uses ngm:digital-signature ;
vc:uses ngm:elliptic-curve-cryptography ;
vc:uses ngm:opcodes ;
vc:uses ngm:schnorr-signature .
ngm:bitcoin-scripting-language a skos:Concept ;
rdfs:label "Bitcoin Scripting Language"@en .
ngm:bitcoin-smart-contracts a skos:Concept ;
rdfs:label "Bitcoin Smart Contracts"@en .
ngm:bitcoin-soft-fork a skos:Concept ;
rdfs:label "Bitcoin Soft Fork"@en .
ngm:bitcoin-standard-adoption a skos:Concept ;
rdfs:label "Bitcoin Standard Adoption"@en .
ngm:bitcoin-testnet3 a skos:Concept ;
rdfs:label "Bitcoin Testnet3"@en .
ngm:bitcoin-trading-bot a skos:Concept ;
rdfs:label "Bitcoin Trading Bot"@en .
ngm:bitcoin-transaction a owl:Class ;
rdfs:comment "A Bitcoin transaction is a signed data structure that transfers value on the Bitcoin network by consuming unspent transaction outputs (UTXOs) and creating new ones. Each transaction references prior outputs, provides cryptographic signatures satisfying their spending conditions, and specifies new outputs locked to recipient scripts. Validated transactions are broadcast to the mempool and ultimately confirmed when included in a mined block."@en ;
rdfs:label "Bitcoin Transaction"@en ;
rdfs:subClassOf ngm:bitcoin ;
rdfs:subClassOf ngm:blockchain-transaction ;
rdfs:subClassOf _:r3210 ;
rdfs:subClassOf _:r3211 ;
rdfs:subClassOf _:r3212 ;
rdfs:subClassOf _:r3213 ;
vc:dependsOn ngm:mining ;
vc:dependsOn ngm:proof-of-work ;
vc:enables ngm:lightning-network ;
vc:enables ngm:rgb-protocol ;
vc:enables ngm:runes-protocol ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:transaction-fee ;
vc:hasPart ngm:utxo ;
vc:isPartOf ngm:bitcoin ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:blockchain-transaction ;
vc:requires ngm:bitcoin-script ;
vc:requires ngm:digital-signature ;
vc:slug "bitcoin-transaction" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:mempool ;
vc:uses ngm:wallet .
ngm:bitcoin-treasury-strategy a skos:Concept ;
rdfs:label "Bitcoin Treasury Strategy"@en .
ngm:bitcoin-wallet a skos:Concept ;
rdfs:label "Bitcoin Wallet"@en .
ngm:bitfinex a owl:Class ;
rdfs:comment "Bitfinex is a cryptocurrency exchange that allows trading of digital assets and is associated with the issuer of the Tether stablecoin. It is operated by iFinex."@en ;
rdfs:label "Bitfinex"@en ;
rdfs:subClassOf ngm:cryptocurrency ;
rdfs:subClassOf _:r3244 ;
vc:bridgesTo ngm:tether ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:bitcoin-proof-of-work-protocol ;
vc:slug "bitfinex" ;
vc:sourceDomain "blockchain" .
ngm:bitinfocharts a skos:Concept ;
rdfs:label "Bitinfocharts"@en .
ngm:bitmain a owl:Class ;
rdfs:comment "Bitmain is a Chinese company that designs and manufactures application-specific integrated circuit mining hardware, best known for its Antminer product line. It also operates mining services."@en ;
rdfs:label "Bitmain"@en ;
rdfs:subClassOf ngm:asic ;
rdfs:subClassOf _:r3245 ;
vc:bridgesTo ngm:hardware ;
vc:enables ngm:ant-pool ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:bitcoin-proof-of-work-protocol-mining ;
vc:slug "bitmain" ;
vc:sourceDomain "blockchain" .
ngm:bitmask a skos:Concept ;
rdfs:label "Bitmask"@en .
ngm:bitmask-wallet a skos:Concept ;
rdfs:label "Bitmask Wallet"@en .
ngm:bitrate a owl:Class ;
rdfs:comment "Bitrate is the rate at which bits are transmitted, encoded or processed per unit of time, typically expressed in kilobits or megabits per second. It determines the bandwidth a signal consumes and, for audio and video, the trade-off between file size or transmission cost and perceptual quality. Bitrate is a fundamental parameter in broadcast systems and adaptive streaming, where it is dynamically adjusted, and in video compression, where techniques such as motion estimation influence how efficiently a target bitrate is achieved."@en ;
rdfs:label "Bitrate"@en ;
rdfs:subClassOf ngm:infra-network-and-comms ;
skos:broader ngm:infra-network-and-comms ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.55"^^xsd:float ;
vc:relatedTo ngm:video-compression ;
vc:slug "bitrate" ;
vc:sourceDomain "infrastructure" .
ngm:bitrate-ladder a skos:Concept ;
rdfs:label "Bitrate Ladder"@en .
ngm:bitsandbytes a skos:Concept ;
rdfs:label "Bitsandbytes"@en .
ngm:bitstring-status-list a owl:Class ;
rdfs:comment "Bitstring Status List is a W3C specification for expressing the revocation or suspension status of Verifiable Credentials through a compressed, publicly-hosted bitstring in which each credential is assigned a position index; setting that bit to 1 indicates revocation without disclosing which specific credential holder triggered the change. The mechanism is privacy-preserving because verifiers observe only a large compressed list, not individual credential identifiers. It supersedes the earlier Credential Status List 2021 specification and is designed to be bandwidth-efficient and herd-privacy-compatible."@en ;
rdfs:label "Bitstring Status List"@en ;
rdfs:subClassOf ngm:revocation-mechanism ;
vc:enables ngm:credential-verification ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:decentralised-identity ;
vc:relatedTo ngm:revocation-registry ;
vc:slug "bitstring-status-list" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:verifiable-credential-standard ;
vc:uses ngm:cryptographic-hash ;
vc:uses ngm:verifiable-credentials .
ngm:bitswap a skos:Concept ;
rdfs:label "Bitswap"@en .
ngm:bitswap-protocol a skos:Concept ;
rdfs:label "Bitswap Protocol"@en .
ngm:bittensor a owl:Class ;
rdfs:comment "A decentralised network that uses blockchain-based incentives to coordinate and reward the contribution of machine learning models and compute by independent participants."@en ;
rdfs:label "Bittensor"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf ngm:decentralised-system ;
rdfs:subClassOf ngm:distributed-training ;
rdfs:subClassOf ngm:peer-to-peer-network ;
rdfs:subClassOf _:r3246 ;
rdfs:subClassOf _:r3247 ;
rdfs:subClassOf _:r3248 ;
rdfs:subClassOf _:r3249 ;
rdfs:subClassOf _:r3250 ;
rdfs:subClassOf _:r3251 ;
rdfs:subClassOf _:r3252 ;
rdfs:subClassOf _:r3253 ;
rdfs:subClassOf _:r3254 ;
rdfs:subClassOf _:r3255 ;
skos:broader ngm:artificial-intelligence ;
vc:contrastsWith ngm:centralised-ai ;
vc:contrastsWith ngm:cloud-computing ;
vc:contrastsWith ngm:federated-learning ;
vc:contrastsWith ngm:hugging-face ;
vc:contrastsWith ngm:openai-research-organisation ;
vc:dependsOn ngm:blockchain ;
vc:dependsOn ngm:cryptographic-hash-function ;
vc:dependsOn ngm:distributed-consensus ;
vc:dependsOn ngm:peer-to-peer-network ;
vc:dependsOn ngm:token-economics ;
vc:enables ngm:de-fi ;
vc:enables ngm:distributed-computing ;
vc:enables ngm:federated-learning ;
vc:enables ngm:large-language-models ;
vc:enables ngm:machine-learning-discipline ;
vc:enables ngm:permissionless-ai-training ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:alpha-token ;
vc:hasPart ngm:consensus-mechanism ;
vc:hasPart ngm:incentive-mechanism ;
vc:hasPart ngm:miner ;
vc:hasPart ngm:smart-contract ;
vc:hasPart ngm:subnet ;
vc:hasPart ngm:token-economics ;
vc:hasPart ngm:validator ;
vc:implements ngm:consensus-mechanism ;
vc:implements ngm:incentive-mechanism ;
vc:implements ngm:peer-to-peer-network ;
vc:implements ngm:token-economics ;
vc:qualityScore "0.6"^^xsd:float ;
vc:relatedTo ngm:ai-agent-system ;
vc:relatedTo ngm:blockchain ;
vc:relatedTo ngm:cryptocurrency ;
vc:relatedTo ngm:de-fi ;
vc:relatedTo ngm:ethereum ;
vc:relatedTo ngm:token-economics ;
vc:requires ngm:blockchain ;
vc:requires ngm:cryptographic-hash-function ;
vc:requires ngm:distributed-computing ;
vc:requires ngm:proof-of-intelligence ;
vc:requires ngm:token-economics ;
vc:slug "bittensor" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:opentensor-foundation ;
vc:supports ngm:artificial-intelligence ;
vc:supports ngm:de-fi ;
vc:supports ngm:machine-learning-discipline ;
vc:supports ngm:open-source-ai ;
vc:uses ngm:digital-asset ;
vc:uses ngm:proof-of-intelligence ;
vc:uses ngm:smart-contract ;
vc:uses ngm:substrate ;
vc:uses ngm:yuma-consensus .
ngm:bitter-lesson a skos:Concept ;
rdfs:label "Bitter Lesson"@en .
ngm:bittorrent a owl:Class ;
rdfs:comment "BitTorrent is a peer-to-peer protocol for distributing files by splitting them into pieces that participants download from and upload to one another rather than from a single server. Each participant who holds the complete file can seed it, while downloaders simultaneously share the pieces they already have, so aggregate capacity grows with demand. The protocol uses content hashing to verify pieces and a tracker or distributed hash table to help peers discover one another."@en ;
rdfs:label "Bittorrent"@en ;
rdfs:subClassOf ngm:peer-to-peer-network ;
rdfs:subClassOf _:r3256 ;
rdfs:subClassOf _:r3257 ;
vc:contrastsWith ngm:cdn ;
vc:enables ngm:decentralized-storage ;
vc:enables ngm:replication ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:gossip-protocol ;
vc:relatedTo ngm:ipfs ;
vc:requires ngm:bandwidth ;
vc:requires ngm:network-protocol ;
vc:slug "bittorrent" ;
vc:sourceDomain "distributed-systems" ;
vc:supports ngm:data-distribution ;
vc:supports ngm:distributed-storage ;
vc:supports ngm:file-sharing ;
vc:uses ngm:content-addressing ;
vc:uses ngm:distributed-hash-table ;
vc:uses ngm:overlay-network .
ngm:bittorrent-protocol a skos:Concept ;
rdfs:label "Bittorrent Protocol"@en .
ngm:bitwise-operations a skos:Concept ;
rdfs:label "Bitwise Operations"@en .
ngm:black-box-ai a skos:Concept ;
rdfs:label "Black Box AI"@en .
ngm:black-box-machine-learning a skos:Concept ;
rdfs:label "Black Box Machine Learning"@en .
ngm:black-box-model a owl:Class ;
rdfs:comment "A black-box model is a predictive system whose internal decision logic is opaque or too complex for a human to inspect directly, so it can only be understood through its inputs and outputs. Many high-performing machine-learning systems, such as deep neural networks and large ensembles, are black-box in nature, trading interpretability for accuracy. This opacity motivates post-hoc explanation techniques and contrasts with inherently interpretable white-box models where the reasoning is transparent."@en ;
rdfs:label "Black-Box Model"@en ;
rdfs:subClassOf ngm:machine-learning-model ;
rdfs:subClassOf ngm:model-interpretability ;
rdfs:subClassOf ngm:predictive-model ;
rdfs:subClassOf _:r3258 ;
rdfs:subClassOf _:r3259 ;
rdfs:subClassOf _:r3260 ;
rdfs:subClassOf _:r3261 ;
rdfs:subClassOf _:r3262 ;
rdfs:subClassOf _:r3263 ;
rdfs:subClassOf _:r3264 ;
rdfs:subClassOf _:r3265 ;
rdfs:subClassOf _:r3266 ;
rdfs:subClassOf _:r3267 ;
vc:bridgesTo ngm:lime ;
vc:bridgesTo ngm:shap ;
vc:contrastsWith ngm:decision-tree ;
vc:contrastsWith ngm:explainable-ai ;
vc:contrastsWith ngm:explainable-boosting-machine ;
vc:contrastsWith ngm:interpretability ;
vc:contrastsWith ngm:interpretable-ai ;
vc:contrastsWith ngm:intrinsic-interpretability ;
vc:contrastsWith ngm:logistic-regression ;
vc:contrastsWith ngm:model-transparency ;
vc:contrastsWith ngm:regression ;
vc:contrastsWith ngm:white-box-model ;
vc:dependsOn ngm:accountability ;
vc:dependsOn ngm:hyperparameter-tuning ;
vc:dependsOn ngm:loss-function ;
vc:dependsOn ngm:objective-function ;
vc:dependsOn ngm:optimisation-algorithm ;
vc:dependsOn ngm:training-data ;
vc:dependsOn ngm:trust ;
vc:enables ngm:complex-pattern-recognition ;
vc:enables ngm:high-accuracy-prediction ;
vc:enables ngm:large-scale-automation ;
vc:enables ngm:non-linear-function-approximation ;
vc:enables ngm:scalable-inference ;
vc:enables ngm:transfer-learning ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:feature-representation ;
vc:hasPart ngm:input-output-mapping ;
vc:hasPart ngm:loss-function ;
vc:hasPart ngm:model-parameters ;
vc:hasPart ngm:opaque-internal-logic ;
vc:hasPart ngm:prediction-interface ;
vc:hasPart ngm:training-procedure ;
vc:implements ngm:boosting ;
vc:implements ngm:deep-learning ;
vc:implements ngm:ensemble-methods ;
vc:implements ngm:neural-network ;
vc:implements ngm:random-forest ;
vc:implements ngm:transformer-architecture ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:accountability ;
vc:relatedTo ngm:adversarial-attack ;
vc:relatedTo ngm:ai-alignment ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:ai-model-card ;
vc:relatedTo ngm:attention-mechanism ;
vc:relatedTo ngm:bias ;
vc:relatedTo ngm:counterfactual-explanation ;
vc:relatedTo ngm:cybersecurity ;
vc:relatedTo ngm:deep-learning ;
vc:relatedTo ngm:eu-ai-act-regulatory-instrument ;
vc:relatedTo ngm:explainability ;
vc:relatedTo ngm:explainable-ai ;
vc:relatedTo ngm:fairness ;
vc:relatedTo ngm:feature-attribution ;
vc:relatedTo ngm:feature-importance ;
vc:relatedTo ngm:gdpr ;
vc:relatedTo ngm:lime ;
vc:relatedTo ngm:mechanistic-interpretability ;
vc:relatedTo ngm:model-transparency ;
vc:relatedTo ngm:neural-network ;
vc:relatedTo ngm:responsible-ai ;
vc:relatedTo ngm:robustness ;
vc:relatedTo ngm:saliency-map ;
vc:relatedTo ngm:shap ;
vc:relatedTo ngm:trust ;
vc:relatedTo ngm:uncertainty-quantification ;
vc:requires ngm:accountability ;
vc:requires ngm:audit-mechanism ;
vc:requires ngm:explainable-ai ;
vc:requires ngm:feature-importance ;
vc:requires ngm:model-evaluation ;
vc:requires ngm:model-interpretability ;
vc:requires ngm:post-hoc-explanation ;
vc:requires ngm:training-data ;
vc:requires ngm:validation-protocol ;
vc:slug "black-box-model" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:gdpr-article-22 ;
vc:standardizedBy ngm:ieee-p7001 ;
vc:standardizedBy ngm:iso-iec-22989 ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:supports ngm:predictive-accuracy ;
vc:supports ngm:scalability ;
vc:supports ngm:transfer-learning ;
vc:uses ngm:attention-mechanism ;
vc:uses ngm:backpropagation ;
vc:uses ngm:convolutional-neural-network ;
vc:uses ngm:stochastic-gradient-descent .
ngm:black-forest-labs a skos:Concept ;
rdfs:label "Black Forest Labs"@en .
ngm:black-forest-labs-flux-api a skos:Concept ;
rdfs:label "Black Forest Labs Flux API"@en .
ngm:black-hole a owl:Class ;
rdfs:label "Black Hole"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:astronomy ;
vc:slug "black-hole" ;
vc:sourceDomain "space-science-and-systems" .
ngm:black-rock a owl:Class ;
rdfs:comment "BlackRock is the world's largest asset management firm, providing investment management, risk advisory, and financial technology services to institutional investors, sovereign wealth funds, pension funds, and retail clients globally. The firm operates Aladdin, a proprietary risk management and operating system platform that processes risk analytics for trillions of dollars in assets across thousands of financial institutions. BlackRock has expanded beyond traditional asset management into digital assets, sustainable investing, and multi-asset solutions, including launching spot Bitcoin and Ethereum ETFs that attracted significant institutional capital. Its scale and systemic importance across public equities, fixed income, alternatives, and infrastructure positions it as a central node in global capital markets."@en ;
rdfs:label "BlackRock"@en ;
rdfs:subClassOf ngm:asset-management ;
rdfs:subClassOf _:r3270 ;
rdfs:subClassOf _:r3271 ;
rdfs:subClassOf _:r3272 ;
vc:bridgesTo ngm:bitcoin-proof-of-work-protocol-etf ;
vc:bridgesTo ngm:esg ;
vc:bridgesTo ngm:neural-network-text-tokenisation ;
vc:bridgesTo ngm:tokenization ;
vc:contrastsWith ngm:fidelity-investments ;
vc:contrastsWith ngm:state-street ;
vc:contrastsWith ngm:vanguard ;
vc:enables ngm:index-investing ;
vc:enables ngm:institutional-investment ;
vc:enables ngm:investment-management ;
vc:enables ngm:sustainable-finance ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:aladdin-platform ;
vc:hasPart ngm:blackrock-solutions ;
vc:hasPart ngm:ishares ;
vc:isPartOf ngm:financial-system ;
vc:isPartOf ngm:global-capital-markets ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:alternative-investments ;
vc:relatedTo ngm:exchange-traded-fund ;
vc:relatedTo ngm:fixed-income ;
vc:requires ngm:portfolio-management ;
vc:requires ngm:regulatory-compliance ;
vc:requires ngm:risk-management ;
vc:slug "black-rock" ;
vc:sourceDomain "finance" ;
vc:supports ngm:endowment-fund ;
vc:supports ngm:pension-fund ;
vc:supports ngm:sovereign-wealth-fund ;
vc:uses ngm:data-infrastructure ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:quantitative-finance ;
vc:uses ngm:risk-analytics .
ngm:black-rock-bitcoin-etf a owl:Class ;
rdfs:comment "The BlackRock Bitcoin ETF (iShares Bitcoin Trust, ticker IBIT) is a spot Bitcoin exchange-traded fund issued by BlackRock and approved by the US SEC in January 2024. It holds bitcoin in qualified custody and tracks the spot price, giving traditional investors regulated, brokerage-accessible exposure to bitcoin without managing keys. As one of the largest and fastest-growing spot Bitcoin ETFs, it is frequently cited as evidence of institutional adoption."@en ;
rdfs:label "BlackRock Bitcoin ETF"@en ;
rdfs:subClassOf ngm:digital-asset ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol-value-proposition ;
vc:slug "black-rock-bitcoin-etf" ;
vc:sourceDomain "blockchain" .
ngm:black-rock-buidl a owl:Class ;
rdfs:comment "BlackRock BUIDL is a tokenised money market fund issued by BlackRock on public blockchains that invests in cash, US Treasury bills, and repurchase agreements."@en ;
rdfs:label "BlackRock BUIDL"@en ;
rdfs:subClassOf ngm:asset-tokenisation ;
rdfs:subClassOf _:r3268 ;
rdfs:subClassOf _:r3269 ;
vc:bridgesTo ngm:institutional-adoption ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:asset-tokenisation ;
vc:requires ngm:neural-network-text-tokenisation ;
vc:slug "black-rock-buidl" ;
vc:sourceDomain "finance" .
ngm:black-scholes-model a skos:Concept ;
rdfs:label "Black Scholes Model"@en .
ngm:blackboard a skos:Concept ;
rdfs:label "Blackboard"@en .
ngm:blackboard-pattern a owl:Class ;
rdfs:comment "A coordination architecture in which multiple specialised agents collaborate not by messaging each other directly but by reading from and writing to a shared, structured workspace — the blackboard. Each agent watches the blackboard for a state it can act on, contributes its partial result back to the shared space, and lets other agents build on that contribution in turn, so a solution accretes incrementally through many opportunistic updates rather than through a fixed pipeline. The pattern decouples the collaborators from one another: an agent needs to understand only the blackboard's contents, not the identity, order, or availability of its peers."@en ;
rdfs:label "Blackboard Pattern"@en ;
rdfs:subClassOf ngm:multi-agent-orchestration ;
rdfs:subClassOf ngm:multiagentorchestration ;
rdfs:subClassOf _:r3273 ;
rdfs:subClassOf _:r3274 ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:supervisor-worker-pattern ;
vc:relatedTo ngm:supervisorworkerpattern ;
vc:relatedTo ngm:task-delegation ;
vc:relatedTo ngm:taskdelegation ;
vc:requires ngm:multi-agent-system ;
vc:slug "blackboard-pattern" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:memory-bank ;
vc:uses ngm:memorybank .
ngm:blackboard-system a skos:Concept ;
rdfs:label "Blackboard System"@en .
ngm:blackrock-solutions a skos:Concept ;
rdfs:label "Blackrock Solutions"@en .
ngm:blake2 a owl:Class ;
rdfs:comment "BLAKE2 is a high-performance cryptographic hash function designed as a faster, simpler alternative to SHA-2 and SHA-3 while preserving equivalent security guarantees. Introduced in 2012 by Jean-Philippe Aumasson, Samuel Neves, Zooko Wilcox-O'Hearn, and Christian Winnerlein, it produces digests of up to 512 bits (BLAKE2b) or 256 bits (BLAKE2s) and is widely adopted in blockchain systems, password-hashing schemes, and data integrity verification due to its speed advantage over SHA-256 on modern 64-bit processors. Its resistance to length-extension attacks and configurability—including personalisation, salting, and variable digest length—make it a versatile drop-in for many cryptographic protocol requirements."@en ;
rdfs:label "BLAKE2"@en ;
rdfs:subClassOf ngm:blockchain-entity ;
rdfs:subClassOf ngm:cryptographic-primitive ;
vc:contrastsWith ngm:sha-256 ;
vc:enables ngm:blockchain-infrastructure ;
vc:enables ngm:data-integrity ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:cryptographic-primitive ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:cryptographic-hash ;
vc:relatedTo ngm:cryptographic-hash-function ;
vc:relatedTo ngm:digital-signatures ;
vc:relatedTo ngm:merkle-tree ;
vc:relatedTo ngm:sha-256 ;
vc:slug "blake2" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:hash-function .
ngm:blake2b a skos:Concept ;
rdfs:label "Blake2b"@en .
ngm:blake2b-hashing a skos:Concept ;
rdfs:label "Blake2b Hashing"@en .
ngm:blake3 a owl:Class ;
rdfs:comment "BLAKE3 is a cryptographic hash function released in 2020 that achieves exceptional speed through a tree-hashing construction enabling unlimited parallelism across SIMD lanes and CPU cores, while simultaneously functioning as a keyed hash, a key derivation function, and an extendable-output function (XOF). It is derived from the BLAKE2 family, inheriting its ARX (add-rotate-XOR) ChaCha-based compression function, and extends it with a Bao-style binary tree that allows verified streaming and incremental hashing. BLAKE3 produces digests of arbitrary length (defaulting to 256 bits), is formally specified under a Creative Commons public-domain dedication, and is designed to be faster than SHA-256 on modern hardware by factors of five to ten on multi-core systems. Its unified API replaces the need for separate HMAC, HKDF, or KDF constructions."@en ;
rdfs:label "BLAKE3"@en ;
rdfs:subClassOf ngm:cryptographic-hash-function ;
vc:enables ngm:content-addressing ;
vc:enables ngm:cryptographic-verification ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:blake2 ;
vc:relatedTo ngm:cryptographic-hash ;
vc:relatedTo ngm:data-integrity ;
vc:relatedTo ngm:merkle-tree ;
vc:slug "blake3" ;
vc:sourceDomain "security" ;
vc:uses ngm:cryptographic-primitive ;
vc:uses ngm:hardware-acceleration .
ngm:blas a skos:Concept ;
rdfs:label "Blas"@en .
ngm:blast-radius-control a skos:Concept ;
rdfs:label "Blast Radius Control"@en .
ngm:ble-mesh a skos:Concept ;
rdfs:label "Ble Mesh"@en .
ngm:blei-et-al-2017-vi-review a skos:Concept ;
rdfs:label "Blei Et Al 2017 Vi Review"@en .
ngm:blend-shape a owl:Class ;
rdfs:comment "A blend shape, also called a morph target, is a stored deformation of a 3D mesh that is blended with a base shape by a weighted interpolation of vertex positions. By combining multiple blend shapes at varying weights, animators produce smooth transitions between expressions and poses without altering the mesh topology. Blend shapes are central to facial animation, where subtle muscle movements are captured as named targets driven by animation rigs or performance capture."@en ;
rdfs:label "Blend Shape"@en ;
rdfs:subClassOf ngm:facial-animation ;
rdfs:subClassOf _:r3275 ;
vc:contrastsWith ngm:skeletal-animation ;
vc:enables ngm:character-animation ;
vc:enables ngm:facial-animation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:point-cloud ;
vc:isPartOf ngm:animation ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:avatar ;
vc:relatedTo ngm:character-animation ;
vc:relatedTo ngm:facial-animation ;
vc:slug "blend-shape" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:avatar ;
vc:supports ngm:real-time-rendering ;
vc:uses ngm:animation-rig ;
vc:uses ngm:skeletal-animation .
ngm:blend-tree a owl:Class ;
rdfs:comment "A blend tree is a structure within an animation system that smoothly blends multiple animation clips according to one or more continuous parameters, producing a single output pose. It is commonly used for locomotion, where clips such as idle, walk and run are interpolated by speed and direction to avoid abrupt transitions. Blend trees are typically composed within an animation controller alongside state machines that govern when each tree is active."@en ;
rdfs:label "Blend Tree"@en ;
rdfs:subClassOf ngm:animation ;
rdfs:subClassOf _:r3276 ;
rdfs:subClassOf _:r3277 ;
vc:dependsOn ngm:game-engine ;
vc:enables ngm:locomotion ;
vc:enables ngm:procedural-animation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:keyframe-animation ;
vc:implements ngm:real-time-rendering ;
vc:isPartOf ngm:animation-controller ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:inverse-kinematics ;
vc:relatedTo ngm:motion-capture ;
vc:relatedTo ngm:unity ;
vc:relatedTo ngm:unreal-engine ;
vc:requires ngm:animation-controller ;
vc:slug "blend-tree" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:character-animation ;
vc:uses ngm:keyframe-animation ;
vc:uses ngm:skeletal-animation .
ngm:blended-finance a owl:Class ;
rdfs:comment "Blended finance is the strategic use of concessional public or philanthropic capital to mobilise additional private investment toward development and sustainability goals. By absorbing early-stage or disproportionate risk, the concessional tranche improves the risk-adjusted return of a project enough to attract commercial investors who would not otherwise participate. It is widely applied to fund infrastructure, climate, and social projects in markets perceived as too risky for purely commercial capital."@en ;
rdfs:label "Blended Finance"@en ;
rdfs:subClassOf ngm:finance ;
rdfs:subClassOf _:r3278 ;
rdfs:subClassOf _:r3279 ;
rdfs:subClassOf _:r3280 ;
vc:bridgesTo ngm:green-finance ;
vc:contrastsWith ngm:impact-investing ;
vc:enables ngm:impact-investing ;
vc:enables ngm:social-impact ;
vc:enables ngm:sustainable-development ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:capital-allocation ;
vc:hasPart ngm:risk-management ;
vc:implements ngm:capital-allocation ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:esg ;
vc:relatedTo ngm:impact-investing ;
vc:relatedTo ngm:interest-rate ;
vc:requires ngm:risk-management ;
vc:slug "blended-finance" ;
vc:sourceDomain "finance" ;
vc:supports ngm:green-finance ;
vc:supports ngm:sustainable-development ;
vc:uses ngm:capital-allocation ;
vc:uses ngm:risk-management .
ngm:blended-learning a skos:Concept ;
rdfs:label "Blended Learning"@en .
ngm:blender-3d-creation-suite a owl:Class ;
rdfs:comment "Blender is a free and open-source 3D creation suite supporting modelling, animation, rendering, and related workflows."@en ;
rdfs:label "Blender 3D Creation Suite"@en ;
rdfs:subClassOf ngm:open-source-software ;
rdfs:subClassOf _:r3281 ;
vc:bridgesTo ngm:game-engine ;
vc:enables ngm:animation ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:open-source-software ;
vc:slug "blender-3d-creation-suite" ;
vc:sourceDomain "metaverse" .
ngm:blending-module a skos:Concept ;
rdfs:label "Blending Module"@en .
ngm:bletchley-declaration a owl:Class ;
rdfs:comment "The Bletchley Declaration is a multilateral political agreement signed in November 2023 by 28 nations and the European Union at the inaugural AI Safety Summit at Bletchley Park, UK, establishing the first intergovernmental consensus on the risks of frontier AI models. Signatories committed to international cooperation on safety evaluation, information sharing among national AI safety institutes, and the development of governance frameworks to address potentially catastrophic risks from highly capable foundation models. The declaration catalysed the formation of AI safety institutes in the UK, United States, and other signatory nations, and set the precedent for government-coordinated pre-deployment evaluations of frontier AI systems. It was followed by the Seoul AI Safety Summit in 2024, which extended commitments toward operational safety testing requirements for frontier model developers."@en ;
rdfs:label "Bletchley Declaration"@en ;
rdfs:subClassOf ngm:ai-governance ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:international-agreement ;
rdfs:subClassOf ngm:policy-instrument ;
rdfs:subClassOf _:r3282 ;
rdfs:subClassOf _:r3283 ;
rdfs:subClassOf _:r3284 ;
rdfs:subClassOf _:r3285 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:capability-evaluation ;
vc:bridgesTo ngm:interpretability ;
vc:bridgesTo ngm:model-evaluation ;
vc:contrastsWith ngm:binding-regulation ;
vc:contrastsWith ngm:domestic-ai-regulation ;
vc:contrastsWith ngm:eu-ai-act-regulatory-instrument ;
vc:contrastsWith ngm:hard-law ;
vc:contrastsWith ngm:treaty-obligation ;
vc:dependsOn ngm:diplomatic-engagement ;
vc:dependsOn ngm:frontier-model-developer-access ;
vc:dependsOn ngm:political-will ;
vc:dependsOn ngm:uk-government-leadership ;
vc:enables ngm:ai-safety-institute ;
vc:enables ngm:ai-safety-summit-series ;
vc:enables ngm:capability-evaluation ;
vc:enables ngm:frontier-ai-safety-commitments ;
vc:enables ngm:international-network-of-ai-safety-institutes ;
vc:enables ngm:model-evaluation ;
vc:enables ngm:pre-deployment-evaluation ;
vc:enables ngm:red-teaming ;
vc:enables ngm:risk-assessment ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:ai-safety-institute-mandate ;
vc:hasPart ngm:bletchley-declaration-signatories ;
vc:hasPart ngm:information-sharing-commitment ;
vc:hasPart ngm:national-governance-guidance ;
vc:hasPart ngm:pre-deployment-evaluation-principle ;
vc:hasPart ngm:risk-acknowledgement-provision ;
vc:hasPart ngm:safety-research-agenda ;
vc:implements ngm:ai-governance ;
vc:implements ngm:international-cooperation ;
vc:implements ngm:multilateral-governance ;
vc:implements ngm:norm-setting ;
vc:implements ngm:soft-law ;
vc:implements ngm:summit-diplomacy ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:ai-alignment ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:ai-regulation ;
vc:relatedTo ngm:ai-risk-management ;
vc:relatedTo ngm:aisi-frontier-ai-safety-framework ;
vc:relatedTo ngm:biosecurity ;
vc:relatedTo ngm:black-box-model ;
vc:relatedTo ngm:cybersecurity ;
vc:relatedTo ngm:dual-use-technology ;
vc:relatedTo ngm:existential-risk ;
vc:relatedTo ngm:foundation-model ;
vc:relatedTo ngm:frontier-model-forum ;
vc:relatedTo ngm:g7-hiroshima-ai-process ;
vc:relatedTo ngm:gdpr ;
vc:relatedTo ngm:interpretability ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:oecd-ai-principles ;
vc:relatedTo ngm:paris-ai-action-summit ;
vc:relatedTo ngm:seoul-ai-safety-summit ;
vc:relatedTo ngm:unesco-recommendation-on-the-ethics-of-ai ;
vc:requires ngm:ai-safety-research ;
vc:requires ngm:foundation-model ;
vc:requires ngm:frontier-ai ;
vc:requires ngm:frontier-model-developer-cooperation ;
vc:requires ngm:government-commitment ;
vc:requires ngm:multilateral-diplomacy ;
vc:slug "bletchley-declaration" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:dsit ;
vc:standardizedBy ngm:international-network-of-ai-safety-institutes ;
vc:standardizedBy ngm:uk-department-for-science-innovation-and-technology ;
vc:supports ngm:ai-alignment ;
vc:supports ngm:ai-governance ;
vc:supports ngm:ai-safety-research ;
vc:supports ngm:biosecurity ;
vc:supports ngm:cybersecurity ;
vc:supports ngm:existential-risk-reduction ;
vc:supports ngm:international-cooperation ;
vc:supports ngm:interpretability ;
vc:supports ngm:model-evaluation ;
vc:supports ngm:responsible-ai ;
vc:uses ngm:information-sharing ;
vc:uses ngm:pre-deployment-evaluation ;
vc:uses ngm:red-teaming ;
vc:uses ngm:risk-assessment ;
vc:uses ngm:voluntary-commitment .
ngm:bletchley-declaration-signatories a skos:Concept ;
rdfs:label "Bletchley Declaration Signatories"@en .
ngm:bleu-score a owl:Class ;
rdfs:comment "BLEU Score (Bilingual Evaluation Understudy) is an automatic evaluation metric for machine translation and text generation quality that measures the overlap of n-gram sequences between a candidate output and one or more human reference translations, applying a brevity penalty to discourage pathologically short outputs. Scores range from 0 to 1 (or 0 to 100 in percentage form), with higher values indicating closer correspondence to the reference. BLEU correlates moderately with human judgement at the corpus level but is known to be unreliable for single-sentence evaluation and insufficient alone for capturing semantic adequacy."@en ;
rdfs:label "BLEU Score"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:evaluation-metric ;
rdfs:subClassOf ngm:performance-metrics ;
rdfs:subClassOf _:r2628 ;
rdfs:subClassOf _:r2629 ;
rdfs:subClassOf _:r2630 ;
rdfs:subClassOf _:r2631 ;
rdfs:subClassOf _:r2632 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:benchmark-dataset ;
vc:bridgesTo ngm:evaluation-harness ;
vc:bridgesTo ngm:large-language-models ;
vc:contrastsWith ngm:bert-score ;
vc:contrastsWith ngm:bertscore ;
vc:contrastsWith ngm:comet-metric ;
vc:contrastsWith ngm:evaluation-harness ;
vc:contrastsWith ngm:human-evaluation ;
vc:contrastsWith ngm:meteor ;
vc:contrastsWith ngm:meteor-metric ;
vc:contrastsWith ngm:rouge ;
vc:dependsOn ngm:corpus ;
vc:dependsOn ngm:neural-network-text-tokenisation ;
vc:dependsOn ngm:reference-translation ;
vc:enables ngm:automated-evaluation ;
vc:enables ngm:benchmark-evaluation ;
vc:enables ngm:model-comparison ;
vc:enables ngm:regression-testing ;
vc:enables ngm:reproducible-research ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:brevity-penalty ;
vc:hasPart ngm:geometric-mean ;
vc:hasPart ngm:modified-precision ;
vc:hasPart ngm:n-gram-overlap ;
vc:hasPart ngm:neural-network-text-tokenisation ;
vc:implements ngm:evaluation-metric ;
vc:implements ngm:modified-precision ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:benchmarks ;
vc:relatedTo ngm:bert ;
vc:relatedTo ngm:bert-score ;
vc:relatedTo ngm:bertscore ;
vc:relatedTo ngm:comet-metric ;
vc:relatedTo ngm:evaluation-benchmarks-and-leaderboards ;
vc:relatedTo ngm:language-model ;
vc:relatedTo ngm:meteor ;
vc:relatedTo ngm:meteor-metric ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:rouge ;
vc:relatedTo ngm:rouge-metric ;
vc:relatedTo ngm:sacrebleu ;
vc:relatedTo ngm:text-generation ;
vc:relatedTo ngm:wmt-benchmark ;
vc:requires ngm:neural-network-text-tokenisation ;
vc:requires ngm:parallel-corpus ;
vc:requires ngm:reference-translation ;
vc:requires ngm:test-dataset ;
vc:requires ngm:tokenization ;
vc:slug "bleu-score" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:benchmark-evaluation ;
vc:standardizedBy ngm:sacrebleu ;
vc:supports ngm:benchmark-evaluation ;
vc:supports ngm:machine-translation ;
vc:supports ngm:natural-language-processing ;
vc:supports ngm:text-generation ;
vc:supports ngm:text-summarisation ;
vc:uses ngm:geometric-mean ;
vc:uses ngm:machine-translation ;
vc:uses ngm:n-gram-overlap ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:neural-network-text-tokenisation ;
vc:uses ngm:reference-translation .
ngm:bleurt a skos:Concept ;
rdfs:label "Bleurt"@en .
ngm:blind-image-restoration a skos:Concept ;
rdfs:label "Blind Image Restoration"@en .
ngm:blind-signatures a owl:Class ;
rdfs:comment "Blind Signatures are a cryptographic primitive invented by David Chaum in 1982 that allow a signer to sign a message without being able to see its content, enabling the message author to later unblind the signature and present a valid signature from the signer without the signer being able to link the signing event to the subsequent presentation. The scheme preserves the unlinkability property — the signer cannot correlate a signing request with a later use of that signature — making it foundational for privacy-preserving payment systems and anonymous credential issuance."@en ;
rdfs:label "Blind Signatures"@en ;
rdfs:subClassOf ngm:cryptographic-primitive ;
rdfs:subClassOf _:r3286 ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:bridgesTo ngm:finance ;
vc:contrastsWith ngm:ring-signature ;
vc:contrastsWith ngm:threshold-signature-scheme ;
vc:enables ngm:anonymous-credential ;
vc:enables ngm:ecash ;
vc:enables ngm:privacy-enhancing-technologies ;
vc:enables ngm:unlinkability ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:blinding-factor ;
vc:implements ngm:unlinkability ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:post-quantum-cryptography ;
vc:relatedTo ngm:selective-disclosure ;
vc:relatedTo ngm:verifiable-credentials ;
vc:relatedTo ngm:zero-knowledge-proof ;
vc:requires ngm:public-key-cryptography ;
vc:requires ngm:rsa-cryptosystem ;
vc:slug "blind-signatures" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:ietf-rfc ;
vc:standardizedBy ngm:w3-c-verifiable-credentials ;
vc:uses ngm:cryptographic-algorithm ;
vc:uses ngm:digital-signature ;
vc:uses ngm:hash-function .
ngm:blinding-factor a skos:Concept ;
rdfs:label "Blinding Factor"@en .
ngm:blip-2 a skos:Concept ;
rdfs:label "Blip 2"@en .
ngm:blip-2-captioner a owl:Class ;
rdfs:comment "BLIP-2 is a vision-language model that bridges a frozen image encoder and a frozen large language model with a lightweight Querying Transformer (Q-Former), and a BLIP-2 captioner uses this model to generate natural-language descriptions of images. It produces high-quality captions efficiently because only the Q-Former is trained, leaving the heavy backbones fixed. Such captioners are commonly used to auto-label image datasets for training diffusion models and fine-tuning pipelines."@en ;
rdfs:label "BLIP-2 Captioner"@en ;
rdfs:subClassOf ngm:computer-vision ;
rdfs:subClassOf ngm:multimodal-ai-architecture ;
rdfs:subClassOf ngm:multimodal-ai-architecture-learning ;
rdfs:subClassOf _:r2633 ;
rdfs:subClassOf _:r2634 ;
rdfs:subClassOf _:r2635 ;
rdfs:subClassOf _:r2636 ;
rdfs:subClassOf _:r2637 ;
rdfs:subClassOf _:r2638 ;
rdfs:subClassOf _:r2639 ;
rdfs:subClassOf _:r2640 ;
rdfs:subClassOf _:r2641 ;
vc:contrastsWith ngm:flamingo ;
vc:contrastsWith ngm:full-fine-tuning ;
vc:contrastsWith ngm:gemini-multimodal-language-model ;
vc:contrastsWith ngm:llava ;
vc:contrastsWith ngm:minigpt-4 ;
vc:dependsOn ngm:attention-mechanism ;
vc:dependsOn ngm:clip-encoder ;
vc:dependsOn ngm:contrastive-learning ;
vc:dependsOn ngm:transformer-architecture ;
vc:dependsOn ngm:vision-transformer ;
vc:enables ngm:cross-modal-retrieval ;
vc:enables ngm:diffusion-model ;
vc:enables ngm:fine-tuning ;
vc:enables ngm:image-captioning ;
vc:enables ngm:multimodal-ai-architecture-reasoning ;
vc:enables ngm:multimodal-ai-architecture-understanding ;
vc:enables ngm:visual-question-answering ;
vc:enables ngm:zero-shot-learning ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:attention-mechanism ;
vc:hasPart ngm:causal-language-modelling ;
vc:hasPart ngm:contrastive-learning ;
vc:hasPart ngm:image-text-contrastive-loss ;
vc:hasPart ngm:large-language-model ;
vc:hasPart ngm:learnable-query-tokens ;
vc:hasPart ngm:linear-projection-layer ;
vc:hasPart ngm:q-former ;
vc:hasPart ngm:transformer-architecture ;
vc:hasPart ngm:vision-transformer ;
vc:implements ngm:causal-language-modelling ;
vc:implements ngm:contrastive-learning ;
vc:implements ngm:parameter-efficient-fine-tuning ;
vc:implements ngm:transformer-architecture ;
vc:qualityScore "0.93"^^xsd:float ;
vc:relatedTo ngm:clip ;
vc:relatedTo ngm:cross-modal-retrieval ;
vc:relatedTo ngm:gemini-multimodal-language-model ;
vc:relatedTo ngm:instruct-blip ;
vc:relatedTo ngm:kohya-dreambooth-and-similar ;
vc:relatedTo ngm:lo-ra-fine-tuning ;
vc:relatedTo ngm:multimodal-ai-architecture ;
vc:relatedTo ngm:multimodal-ai-architecture-learning ;
vc:relatedTo ngm:multimodal-ai-architecture-reasoning ;
vc:relatedTo ngm:multimodal-ai-architecture-understanding ;
vc:relatedTo ngm:stable-diffusion-image-model ;
vc:requires ngm:clip-encoder ;
vc:requires ngm:frozen-image-encoder ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:image-text-paired-corpus ;
vc:requires ngm:training-data ;
vc:slug "blip-2-captioner" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:huggingface-transformers ;
vc:standardizedBy ngm:lavis-library ;
vc:standardizedBy ngm:salesforce-research ;
vc:supports ngm:diffusion-models ;
vc:supports ngm:diffusion-transformer ;
vc:supports ngm:kohya-dreambooth-and-similar ;
vc:supports ngm:lo-ra-do-ra-etc ;
vc:supports ngm:lo-ra-fine-tuning ;
vc:uses ngm:attention-mechanism ;
vc:uses ngm:causal-language-modelling ;
vc:uses ngm:clip-encoder ;
vc:uses ngm:contrastive-learning ;
vc:uses ngm:parameter-efficient-fine-tuning ;
vc:uses ngm:transformer-architecture ;
vc:uses ngm:vision-transformer .
ngm:blob-transaction a owl:Class ;
rdfs:comment "A blob transaction is an Ethereum transaction type introduced by EIP-4844 (Proto-Danksharding) that carries a large binary payload of 'blob' data alongside the standard transaction fields, priced separately from calldata gas. Blobs are stored by consensus nodes for a limited retention window rather than persisted in perpetuity by the EVM, which keeps the cost of posting rollup data far lower than embedding it as ordinary calldata. Blob transactions are the mechanism by which layer-2 rollups post the data needed for fraud or validity proofs back to layer 1."@en ;
rdfs:label "Blob Transaction"@en ;
rdfs:subClassOf ngm:transaction ;
rdfs:subClassOf _:r3287 ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:danksharding ;
vc:qualityScore "0.65"^^xsd:float ;
vc:requires ngm:transaction ;
vc:slug "blob-transaction" ;
vc:sourceDomain "blockchain" .
ngm:block a owl:Class ;
rdfs:comment "The fundamental unit of a blockchain: a cryptographically linked, immutable data container that batches a set of transactions together with a block header containing the Merkle root of those transactions, a timestamp, the previous block's hash, and consensus-specific fields such as a nonce or validator signature. Sequential blocks form the chain that provides an append-only audit trail."@en ;
rdfs:label "Block"@en ;
rdfs:subClassOf ngm:blockchain-entity ;
rdfs:subClassOf ngm:distributed-data-structure ;
rdfs:subClassOf _:r3329 ;
rdfs:subClassOf _:r3330 ;
rdfs:subClassOf _:r3331 ;
rdfs:subClassOf _:r3332 ;
rdfs:subClassOf _:r3333 ;
rdfs:subClassOf _:r3334 ;
rdfs:subClassOf _:r3335 ;
rdfs:subClassOf _:r3336 ;
vc:bridgesTo ngm:data-integrity ;
vc:bridgesTo ngm:distributed-ledger-technology ;
vc:bridgesTo ngm:telecollaboration ;
vc:contrastsWith ngm:orphan-block ;
vc:contrastsWith ngm:uncle-block ;
vc:dependsOn ngm:peer-to-peer-network ;
vc:enables ngm:finality ;
vc:enables ngm:immutability ;
vc:enables ngm:smart-contract-execution ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:block-header ;
vc:hasPart ngm:blockchain-transaction ;
vc:hasPart ngm:coinbase-transaction ;
vc:hasPart ngm:merkle-root ;
vc:hasPart ngm:nonce ;
vc:hasPart ngm:timestamp ;
vc:isPartOf ngm:blockchain ;
vc:isPartOf ngm:blockchain-ledger ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:block-propagation ;
vc:relatedTo ngm:block-reward ;
vc:relatedTo ngm:block-size ;
vc:relatedTo ngm:block-time ;
vc:relatedTo ngm:fork ;
vc:relatedTo ngm:genesis-block ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:digital-signature ;
vc:slug "block" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:cryptographic-hash-function ;
vc:uses ngm:merkle-tree .
ngm:block-based-editor a skos:Concept ;
rdfs:label "Block Based Editor"@en .
ngm:block-cipher a owl:Class ;
rdfs:comment "A block cipher is a deterministic symmetric-key encryption algorithm that transforms a fixed-size block of plaintext, such as 128 bits, into a ciphertext block of the same size under a shared secret key, with the same key correctly reversing the transformation. Algorithms such as AES operate this way, and block ciphers are combined with a mode of operation to encrypt messages longer than a single block. As a primitive, a block cipher underlies symmetric encryption schemes and is a common building block for constructing message authentication codes."@en ;
rdfs:label "Block Cipher"@en ;
rdfs:subClassOf ngm:cryptography ;
vc:enables ngm:symmetric-encryption ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:isPartOf ngm:cryptography ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "block-cipher" ;
vc:sourceDomain "security" .
ngm:block-confirmation a skos:Concept ;
rdfs:label "Block Confirmation"@en .
ngm:block-explorer a owl:Class ;
rdfs:comment "A Block Explorer is a web-based or API-accessible tool that indexes and presents the contents of a blockchain in human-readable form, enabling users to search, inspect, and verify blocks, transactions, addresses, smart contracts, and network statistics without operating a full node locally. Block explorers ingest raw node data, parse it according to the chain's consensus rules, and expose it through search interfaces and REST or GraphQL APIs. They are the primary transparency and audit interface for blockchain networks."@en ;
rdfs:label "Block Explorer"@en ;
rdfs:subClassOf ngm:blockchain-analytics ;
vc:enables ngm:audit-trail ;
vc:enables ngm:transparency ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:blockchain-network ;
vc:relatedTo ngm:mempool ;
vc:slug "block-explorer" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:blockchain-transaction ;
vc:uses ngm:data-visualisation ;
vc:uses ngm:full-node .
ngm:block-header a owl:Class ;
rdfs:comment "The fixed-size metadata section of a blockchain block that encodes the previous block hash, Merkle root of transactions, timestamp, difficulty target, and nonce. The block header is the unit that miners and validators hash during proof-of-work or verify during proof-of-stake, and it commits to the complete block body via the Merkle root without including raw transactions."@en ;
rdfs:label "Block Header"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf ngm:blockchain-entity ;
rdfs:subClassOf ngm:distributed-data-structure ;
rdfs:subClassOf _:r3288 ;
rdfs:subClassOf _:r3289 ;
rdfs:subClassOf _:r3290 ;
rdfs:subClassOf _:r3291 ;
rdfs:subClassOf _:r3292 ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:bridgesTo ngm:ai-energy-optimisation ;
vc:bridgesTo ngm:distributed-systems ;
vc:bridgesTo ngm:security ;
vc:dependsOn ngm:consensus-mechanism ;
vc:dependsOn ngm:peer-to-peer-network ;
vc:enables ngm:light-client ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:difficulty ;
vc:hasPart ngm:merkle-root ;
vc:hasPart ngm:nonce ;
vc:hasPart ngm:timestamp ;
vc:isPartOf ngm:block ;
vc:isPartOf ngm:blockchain ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:block ;
vc:relatedTo ngm:block-height ;
vc:relatedTo ngm:genesis-block ;
vc:relatedTo ngm:merkle-tree ;
vc:requires ngm:cryptographic-hash-function ;
vc:slug "block-header" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:ieee-2418-1 ;
vc:standardizedBy ngm:iso-iec-23257-2021 ;
vc:supports ngm:merkle-proof ;
vc:supports ngm:simplified-payment-verification ;
vc:uses ngm:proof-of-stake ;
vc:uses ngm:proof-of-work ;
vc:uses ngm:sha-256 .
ngm:block-height a owl:Class ;
rdfs:comment "Block Height is a monotonically increasing integer representing the position of a specific block in a blockchain, defined as the count of confirmed blocks preceding it in the canonical chain (the genesis block has height 0). Block height serves as the primary temporal reference for blockchain state: smart contracts use it for time-locked operations, miners use it to calculate block rewards and halving events, and consensus rules use it to enforce protocol upgrade activation thresholds. In the presence of forks, two competing chains may share block height values; the canonical chain is determined by the fork choice rule applied at the point of divergence."@en ;
rdfs:label "Block Height"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf ngm:blockchain-entity ;
rdfs:subClassOf ngm:distributed-data-structure ;
rdfs:subClassOf _:r3293 ;
rdfs:subClassOf _:r3294 ;
rdfs:subClassOf _:r3295 ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:dependsOn ngm:proof-of-work ;
vc:enables ngm:blockchain-governance ;
vc:enables ngm:fork-choice-rule ;
vc:enables ngm:smart-contract ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:block ;
vc:hasPart ngm:genesis-block ;
vc:isPartOf ngm:blockchain ;
vc:isPartOf ngm:blockchain-protocol ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:block-reward ;
vc:relatedTo ngm:block-time ;
vc:relatedTo ngm:chain-reorganization ;
vc:relatedTo ngm:mining-reward ;
vc:requires ngm:consensus-mechanism ;
vc:slug "block-height" ;
vc:sourceDomain "blockchain" .
ngm:block-indexed-time-reference a skos:Concept ;
rdfs:label "Block Indexed Time Reference"@en .
ngm:block-matching a skos:Concept ;
rdfs:label "Block Matching"@en .
ngm:block-number-as-discrete-time a skos:Concept ;
rdfs:label "Block Number As Discrete Time"@en .
ngm:block-producer a skos:Concept ;
rdfs:label "Block Producer"@en .
ngm:block-production a owl:Class ;
rdfs:comment "Block production is the process by which a blockchain network assembles pending transactions into a new block, orders them, and proposes that block for inclusion in the canonical chain. In proof-of-stake and similar systems, validators are selected to produce blocks for given slots or epochs, executing the consensus protocol that determines who may extend the chain and when. Block production is the heartbeat of a blockchain, governing throughput, latency and the fair ordering of transactions."@en ;
rdfs:label "Block Production"@en ;
rdfs:subClassOf ngm:blockchain-consensus ;
rdfs:subClassOf _:r3296 ;
rdfs:subClassOf _:r3297 ;
rdfs:subClassOf _:r3298 ;
vc:dependsOn ngm:proof-of-work ;
vc:enables ngm:block-reward ;
vc:enables ngm:finality ;
vc:enables ngm:throughput ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:blockchain-consensus ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:block ;
vc:relatedTo ngm:blockchain ;
vc:relatedTo ngm:epoch ;
vc:relatedTo ngm:ethereum ;
vc:relatedTo ngm:gas-fee ;
vc:relatedTo ngm:ledger ;
vc:relatedTo ngm:mev ;
vc:relatedTo ngm:solana ;
vc:requires ngm:consensus ;
vc:requires ngm:staking ;
vc:requires ngm:validator ;
vc:slug "block-production" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:fork-choice-rule ;
vc:uses ngm:mempool ;
vc:uses ngm:transaction .
ngm:block-propagation a owl:Class ;
rdfs:comment "Block Propagation is the process by which a newly mined or validated block is broadcast across a blockchain peer-to-peer network so that all full nodes can update their local copy of the chain. Propagation latency directly influences the orphan/stale block rate, security against selfish mining, and the degree of centralisation pressure towards large, well-connected mining pools. Techniques such as Compact Block Relay (Bitcoin BIP 152) and Graphene reduce bandwidth requirements by sending block sketches rather than full transaction lists, exploiting the fact that recipient nodes already hold most transactions in their mempools."@en ;
rdfs:label "Block Propagation"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf ngm:blockchain-entity ;
rdfs:subClassOf ngm:consensus-protocol ;
rdfs:subClassOf _:r3302 ;
rdfs:subClassOf _:r3303 ;
rdfs:subClassOf _:r3304 ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:contrastsWith ngm:light-node ;
vc:dependsOn ngm:blockchain-protocol ;
vc:enables ngm:blockchain-scalability ;
vc:enables ngm:consensus-mechanism ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:block-propagation-time ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:block-size ;
vc:relatedTo ngm:block-time ;
vc:relatedTo ngm:mempool ;
vc:relatedTo ngm:miner ;
vc:requires ngm:blockchain-network ;
vc:requires ngm:full-node ;
vc:slug "block-propagation" ;
vc:sourceDomain "blockchain" .
ngm:block-propagation-time a owl:Class ;
rdfs:comment "Block Propagation Time is the latency metric measuring how long it takes for a newly mined or validated block to be disseminated to all (or a target percentage of) nodes in a blockchain peer-to-peer network after its initial announcement. It is a critical determinant of blockchain security and throughput: long propagation times increase the probability of temporary forks (stale/orphan blocks), waste miner effort, and reduce effective network throughput. Bitcoin historically achieved median propagation times of approximately 1–2 seconds to reach 50% of nodes, while Ethereum's uncle mechanism tolerated higher latency by including competing blocks in the canonical chain."@en ;
rdfs:label "Block Propagation Time"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf ngm:blockchain-entity ;
rdfs:subClassOf ngm:network-component ;
rdfs:subClassOf ngm:networkcomponent ;
rdfs:subClassOf _:r3299 ;
rdfs:subClassOf _:r3300 ;
rdfs:subClassOf _:r3301 ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:contrastsWith ngm:proof-of-stake ;
vc:enables ngm:consensus-mechanism ;
vc:enables ngm:fork-choice-rule ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:block-propagation ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:blockchain-infrastructure ;
vc:relatedTo ngm:blockchain-network ;
vc:relatedTo ngm:blockchain-scalability ;
vc:relatedTo ngm:consensus-algorithm ;
vc:relatedTo ngm:network-latency ;
vc:relatedTo ngm:proof-of-work ;
vc:requires ngm:gossip-protocol ;
vc:requires ngm:peer-to-peer-network ;
vc:slug "block-propagation-time" ;
vc:sourceDomain "blockchain" .
ngm:block-proposal a owl:Class ;
rdfs:comment "Block proposal is the step in a blockchain consensus protocol where a designated participant assembles a candidate block of ordered transactions and broadcasts it to the network for validation and agreement. The proposer selects transactions from the mempool, constructs the block header referencing the prior block, and signs the proposal so peers can verify its authorship. In proof-of-stake systems the proposer is chosen by a leader-election procedure for each slot, after which validators attest to the proposed block."@en ;
rdfs:label "Block Proposal"@en ;
rdfs:subClassOf ngm:consensus-mechanism ;
rdfs:subClassOf _:r3305 ;
rdfs:subClassOf _:r3306 ;
rdfs:subClassOf _:r3307 ;
rdfs:subClassOf _:r3308 ;
rdfs:subClassOf _:r3309 ;
vc:contrastsWith ngm:attestation ;
vc:dependsOn ngm:fork-choice-rule ;
vc:dependsOn ngm:proof-of-stake ;
vc:enables ngm:attestation ;
vc:enables ngm:finality-gadget ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:block ;
vc:hasPart ngm:cryptographic-signature ;
vc:isPartOf ngm:consensus-mechanism ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:blockchain ;
vc:relatedTo ngm:slashing ;
vc:requires ngm:leader-election ;
vc:requires ngm:mempool ;
vc:requires ngm:validator ;
vc:slug "block-proposal" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:digital-signature .
ngm:block-proposer a skos:Concept ;
rdfs:label "Block Proposer"@en .
ngm:block-proposer-selection a skos:Concept ;
rdfs:label "Block Proposer Selection"@en .
ngm:block-reward a owl:Class ;
rdfs:comment "A Block Reward is the cryptoeconomic incentive paid to the producer of a valid block—comprising a protocol-specified subsidy (newly minted tokens) plus the aggregate transaction fees included in that block—which compensates validators or miners for expending resources to extend the canonical chain and maintain network security. Block reward schedules are a core parameter of a blockchain's monetary policy, directly governing token inflation, miner revenue, and the long-run security budget of the network."@en ;
rdfs:label "Block Reward"@en ;
rdfs:subClassOf ngm:bc-defi-and-economics ;
rdfs:subClassOf ngm:blockchain-entity ;
rdfs:subClassOf ngm:distributed-data-structure ;
rdfs:subClassOf _:r3310 ;
rdfs:subClassOf _:r3311 ;
rdfs:subClassOf _:r3312 ;
rdfs:subClassOf _:r3313 ;
skos:broader ngm:bc-defi-and-economics ;
vc:enables ngm:blockchain-economics ;
vc:enables ngm:mining ;
vc:enables ngm:tokenomics ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:mining-reward ;
vc:hasPart ngm:transaction-fee ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:blockchain-transaction ;
vc:relatedTo ngm:cryptocurrency ;
vc:relatedTo ngm:proof-of-stake ;
vc:relatedTo ngm:validator-node ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:proof-of-work ;
vc:slug "block-reward" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:blockchain-governance .
ngm:block-reward-halving a owl:Class ;
rdfs:comment "The block reward halving is the protocol rule in Bitcoin and similar proof-of-work chains that cuts the newly minted coin subsidy paid to miners in half at fixed block intervals, roughly every four years for Bitcoin. This geometric reduction enforces a predictable, disinflationary issuance schedule that converges on a fixed total supply of 21 million bitcoin. Halvings are central to Bitcoin's scarcity narrative and have historically been focal points for market and security-budget analysis."@en ;
rdfs:label "Block Reward Halving"@en ;
rdfs:subClassOf ngm:economic-mechanism ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol-value-proposition ;
vc:slug "block-reward-halving" ;
vc:sourceDomain "blockchain" .
ngm:block-science a skos:Concept ;
rdfs:label "Block Science"@en .
ngm:block-science-theory a skos:Concept ;
rdfs:label "Block Science Theory"@en .
ngm:block-size a owl:Class ;
rdfs:comment "Block Size is the maximum data capacity—measured in bytes or weight units—that a single block in a blockchain may contain, governing how many transactions can be confirmed per block and therefore setting a fundamental upper bound on network throughput. Larger blocks increase per-block transaction capacity but raise propagation latency, orphan-block rates, and hardware requirements for full nodes, while smaller blocks favour decentralisation and faster propagation at the cost of throughput and higher fee markets when demand exceeds capacity. The Bitcoin block-size debate (resulting in the SegWit upgrade and eventual Bitcoin Cash fork) made block size one of the most consequential and politically contentious protocol parameters in blockchain history."@en ;
rdfs:label "Block Size"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf ngm:blockchain-entity ;
rdfs:subClassOf ngm:distributed-data-structure ;
rdfs:subClassOf _:r3314 ;
rdfs:subClassOf _:r3315 ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:bridgesTo ngm:ai-energy-optimisation ;
vc:enables ngm:finality ;
vc:enables ngm:transaction ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:block-time ;
vc:relatedTo ngm:distributed-ledger ;
vc:relatedTo ngm:gas ;
vc:relatedTo ngm:latency ;
vc:relatedTo ngm:network-protocol ;
vc:relatedTo ngm:sidechain ;
vc:requires ngm:block ;
vc:requires ngm:blockchain ;
vc:slug "block-size" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:consensus-mechanism ;
vc:uses ngm:merkle-tree ;
vc:uses ngm:node .
ngm:block-snapshot a owl:Class ;
rdfs:comment "A block snapshot is a record of on-chain state, typically token balances or governance weights, captured at a specific block height. In decentralised governance it freezes voting power at a chosen block so that token holdings used to weight votes cannot be manipulated by transfers during the voting window. Snapshots underpin gasless off-chain voting systems and fair airdrop distributions by providing a tamper-evident, reproducible baseline state."@en ;
rdfs:label "Block Snapshot"@en ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
skos:broader ngm:bc-governance-and-regulation ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:on-chain-voting ;
vc:slug "block-snapshot" ;
vc:sourceDomain "blockchain" .
ngm:block-stm a skos:Concept ;
rdfs:label "Block Stm"@en .
ngm:block-storage a owl:Class ;
rdfs:comment "Block Storage is an infrastructure storage paradigm that presents raw fixed-size blocks of data to a host operating system or hypervisor, which then manages formatting, file system placement, and I/O scheduling directly. Unlike object storage or file storage, block storage exposes a low-level disk abstraction enabling high-performance, low-latency random read/write operations suitable for databases, virtual machine boot disks, and transactional workloads. Cloud providers implement block storage as network-attached volumes (e.g., AWS EBS, GCP Persistent Disk) that can be dynamically provisioned and attached to compute instances."@en ;
rdfs:label "Block Storage"@en ;
rdfs:subClassOf ngm:storage-systems ;
vc:contrastsWith ngm:distributed-storage ;
vc:contrastsWith ngm:object-storage ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:cloud-storage ;
vc:relatedTo ngm:data-storage-layer ;
vc:slug "block-storage" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:database-system ;
vc:supports ngm:persistent-storage ;
vc:uses ngm:file-system .
ngm:block-structure a owl:Class ;
rdfs:comment "Block structure is the internal data layout of a block in a blockchain or distributed ledger, specifying the fields, encoding formats, and cryptographic commitments that constitute a valid unit of the chain. A block consists of a header containing metadata — including the parent block hash, timestamp, nonce, and Merkle root of the transaction set — and a body containing the ordered list of transactions or state transitions. The specific fields, size limits, and serialisation rules of the block structure are defined by the network's consensus protocol and directly govern the chain's security properties, throughput, and upgrade path."@en ;
rdfs:label "Block Structure"@en ;
rdfs:subClassOf ngm:block ;
rdfs:subClassOf _:r3316 ;
rdfs:subClassOf _:r3317 ;
rdfs:subClassOf _:r3318 ;
rdfs:subClassOf _:r3319 ;
rdfs:subClassOf _:r3320 ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:block-header ;
vc:hasPart ngm:merkle-root ;
vc:hasPart ngm:merkle-tree ;
vc:hasPart ngm:nonce ;
vc:hasPart ngm:transaction ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:block-size ;
vc:relatedTo ngm:block-time ;
vc:relatedTo ngm:blockchain ;
vc:slug "block-structure" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:cryptographic-hash .
ngm:block-time a owl:Class ;
rdfs:comment "Block Time is the average elapsed time between the creation of consecutive blocks on a blockchain, governed by the network's consensus mechanism and difficulty adjustment algorithm. Shorter block times increase transaction throughput and reduce confirmation latency but raise the risk of forks due to block propagation delays, creating a fundamental tradeoff between speed and chain security."@en ;
rdfs:label "Block Time"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf ngm:blockchain-entity ;
rdfs:subClassOf ngm:distributed-data-structure ;
rdfs:subClassOf _:r3321 ;
rdfs:subClassOf _:r3322 ;
rdfs:subClassOf _:r3323 ;
rdfs:subClassOf _:r3324 ;
rdfs:subClassOf _:r3325 ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:bridgesTo ngm:ai-energy-optimisation ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:contrastsWith ngm:block-size ;
vc:contrastsWith ngm:blockchain-scalability ;
vc:dependsOn ngm:mining-pool ;
vc:dependsOn ngm:network-latency ;
vc:dependsOn ngm:peer-to-peer-network ;
vc:enables ngm:transaction-confirmation ;
vc:enables ngm:transaction-finality ;
vc:enables ngm:uncle-block ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:difficulty-adjustment ;
vc:implements ngm:nakamoto-consensus ;
vc:isPartOf ngm:blockchain-protocol ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:block-height ;
vc:relatedTo ngm:block-size ;
vc:relatedTo ngm:blockchain-scalability ;
vc:relatedTo ngm:finality ;
vc:relatedTo ngm:mempool ;
vc:relatedTo ngm:mining ;
vc:relatedTo ngm:orphan-block ;
vc:requires ngm:block-propagation ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:hash-rate ;
vc:requires ngm:proof-of-work ;
vc:slug "block-time" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:ieee-2418-1 ;
vc:standardizedBy ngm:iso-iec-23257-2021 ;
vc:supports ngm:blockchain-security ;
vc:supports ngm:double-spend-prevention ;
vc:uses ngm:cryptographic-hash-function ;
vc:uses ngm:merkle-tree .
ngm:block-timestamp a owl:Class ;
rdfs:comment "A block timestamp is the time value that a block producer embeds in a blockchain block header, recording when the block was created according to that producer's clock. Because it is set by the block producer rather than a trusted external clock, it is only approximately accurate and is bounded by consensus rules to prevent large manipulation; difficulty adjustment algorithms and timelocks both depend on it. It provides the ordering and timing primitive on which many on-chain time-dependent mechanisms are built."@en ;
rdfs:label "Block Timestamp"@en ;
rdfs:subClassOf ngm:block ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:slug "block-timestamp" ;
vc:sourceDomain "blockchain" .
ngm:block-trails a owl:Class ;
rdfs:comment "Block Trails is a minimal Bitcoin-native state-anchoring primitive that records an evolving sequence of states as a cryptographic chain of key tweaks mirroring a Bitcoin spend chain. Each state transition derives a tweak t_i = SHA256(state_i) mod n which is scalar-added to the previous key (d_i = d_(i-1) + t_i), producing a fresh pay-to-Taproot (P2TR) key-path output; spending that output to create the next commitment makes every UTXO a single-use seal. The state bytes themselves live off-chain on IPFS, Git, or Nostr relays, while Bitcoin's UTXO model supplies ordering and double-spend protection so that exactly one valid history can exist. Because trails use full secp256k1 keys, existing Nostr identities can own and advance a trail without key conversion. Application semantics are defined by Profiles such as MRC20 (a fungible-token ledger) and Git-mark (anchoring Git commits)."@en ;
rdfs:label "Block Trails"@en ;
rdfs:subClassOf ngm:client-side-validation ;
rdfs:subClassOf _:r3326 ;
vc:bridgesTo ngm:content-addressed-storage ;
vc:bridgesTo ngm:git ;
vc:bridgesTo ngm:nostr ;
vc:contrastsWith ngm:rgb-protocol ;
vc:contrastsWith ngm:taproot-assets ;
vc:dependsOn ngm:bitcoin-proof-of-work-protocol-network ;
vc:dependsOn ngm:proof-of-publication ;
vc:dependsOn ngm:utxo-model ;
vc:enables ngm:asset-tokenisation ;
vc:enables ngm:fungible-token ;
vc:enables ngm:provenance-tracking ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:single-use-seals ;
vc:implements ngm:client-side-validation ;
vc:implements ngm:single-use-seals ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:decentralised-application ;
vc:relatedTo ngm:layer-2-scaling ;
vc:relatedTo ngm:rgb-and-client-side-validation ;
vc:slug "block-trails" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:cryptographic-commitment ;
vc:uses ngm:schnorr-signature ;
vc:uses ngm:secp256k1 ;
vc:uses ngm:sha-256 ;
vc:uses ngm:taproot .
ngm:block-validation a owl:Class ;
rdfs:comment "Block Validation is the process by which a blockchain node verifies that a candidate block satisfies all protocol rules before accepting it into the chain. It checks the proof-of-work or consensus proof, the block header structure, the Merkle root, and the validity of every contained transaction including signatures, double-spend constraints, and balances. Successful validation is the precondition for extending the canonical chain and is central to trustless consensus."@en ;
rdfs:label "Block Validation"@en ;
rdfs:subClassOf ngm:consensus-mechanism ;
rdfs:subClassOf _:r3327 ;
rdfs:subClassOf _:r3328 ;
vc:bridgesTo ngm:distributed-ledger ;
vc:dependsOn ngm:consensus-mechanism ;
vc:enables ngm:consensus-mechanism ;
vc:enables ngm:transaction-validation ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:blockchain ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:byzantine-fault-tolerance ;
vc:relatedTo ngm:full-node ;
vc:relatedTo ngm:transaction-validation ;
vc:requires ngm:block-header ;
vc:requires ngm:proof-of-work ;
vc:slug "block-validation" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:full-node ;
vc:uses ngm:digital-signature ;
vc:uses ngm:hash-function ;
vc:uses ngm:merkle-tree .
ngm:blockchain a owl:Class ;
a skos:Concept ;
rdfs:comment "A blockchain is a distributed, cryptographically-secured data structure consisting of an ordered chain of blocks, where each block contains a cryptographic hash of the previous block, a timestamp, and transaction data, maintained through a consensus mechanism across a peer-to-peer network without..."@en ;
rdfs:label "Blockchain"@en ;
rdfs:subClassOf ngm:cryptographic-system ;
rdfs:subClassOf ngm:distributed-data-structure ;
rdfs:subClassOf ngm:distributed-ledger ;
rdfs:subClassOf ngm:thing ;
rdfs:subClassOf _:r3555 ;
rdfs:subClassOf _:r3556 ;
rdfs:subClassOf _:r3557 ;
rdfs:subClassOf _:r3558 ;
rdfs:subClassOf _:r3559 ;
rdfs:subClassOf _:r3560 ;
rdfs:subClassOf _:r3561 ;
rdfs:subClassOf _:r3562 ;
rdfs:subClassOf _:r3563 ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:ai-energy-optimisation ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:telecollaboration ;
vc:enables ngm:cryptocurrency ;
vc:enables ngm:de-fi ;
vc:enables ngm:digital-asset ;
vc:enables ngm:supply-chain-transparency ;
vc:enables ngm:token-economics ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:block ;
vc:hasPart ngm:consensus-mechanism ;
vc:hasPart ngm:mining ;
vc:hasPart ngm:node ;
vc:hasPart ngm:smart-contract ;
vc:hasPart ngm:transaction ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:cryptographic-hash-function ;
vc:requires ngm:distributed-consensus ;
vc:requires ngm:peer-to-peer-network ;
vc:slug "blockchain" ;
vc:sourceDomain "blockchain" .
ngm:blockchain-address-attribution a skos:Concept ;
rdfs:label "Blockchain Address Attribution"@en .
ngm:blockchain-analysis a owl:Class ;
rdfs:comment "Blockchain analysis is the systematic examination of distributed ledger transaction data to identify patterns, trace fund flows, attribute addresses to entities, and detect illicit activity. It applies graph analytics, heuristic clustering, and machine-learning techniques to publicly available on-chain records to support compliance, law enforcement, and financial intelligence functions."@en ;
rdfs:label "Blockchain Analysis"@en ;
rdfs:subClassOf ngm:digital-forensics ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:blockchain-analytics-platform ;
vc:slug "blockchain-analysis" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:aml-kyc-compliance ;
vc:supports ngm:kyc-aml ;
vc:uses ngm:blockchain-analytics ;
vc:uses ngm:heuristic-methods .
ngm:blockchain-analytics a owl:Class ;
rdfs:comment "Blockchain Analytics is the application of data-science, graph-analysis, and heuristic-clustering techniques to the publicly visible transaction records of distributed ledgers, with the aim of tracing fund flows, identifying entities, detecting illicit activity, and producing compliance intelligence for regulators and financial institutions. It encompasses on-chain transaction monitoring, address clustering, cross-chain tracing, DeFi flow analysis, and risk-scoring of wallets and counterparties. Leading commercial providers include Chainalysis, Elliptic, and TRM Labs, whose tooling has become integral to AML compliance programmes worldwide."@en ;
rdfs:label "Blockchain Analytics"@en ;
rdfs:subClassOf ngm:data-analytics ;
vc:dependsOn ngm:ethereum-smart-contract-platform ;
vc:dependsOn ngm:high-performance-computing ;
vc:enables ngm:aml-kyc-compliance ;
vc:enables ngm:compliance-audit-trail ;
vc:enables ngm:compliance-monitoring ;
vc:enables ngm:fatf-travel-rule ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:bc-0482-eu-mica-regulation ;
vc:relatedTo ngm:blockchain ;
vc:relatedTo ngm:blockchain-governance ;
vc:relatedTo ngm:blockchain-transaction ;
vc:relatedTo ngm:decentralized-finance-de-fi ;
vc:slug "blockchain-analytics" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:cryptographic-hash ;
vc:uses ngm:data-governance ;
vc:uses ngm:distributed-ledger-technology ;
vc:uses ngm:knowledge-graph .
ngm:blockchain-analytics-platform a owl:Class ;
rdfs:comment "A blockchain analytics platform is software that ingests, clusters, and analyses on-chain transaction data to trace fund flows, attribute addresses to entities, and assess risk. Platforms such as Chainalysis and Elliptic apply heuristics, machine learning, and labelled datasets to support anti-money-laundering, sanctions screening, and investigations. They are central tooling for exchange compliance teams, regulators, and law-enforcement agencies."@en ;
rdfs:label "Blockchain Analytics Platform"@en ;
rdfs:subClassOf ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:aml-kyc-compliance ;
vc:relatedTo ngm:blockchain-analysis ;
vc:slug "blockchain-analytics-platform" ;
vc:sourceDomain "blockchain" .
ngm:blockchain-anchoring a owl:Class ;
rdfs:comment "Blockchain Anchoring is a technique for binding external data or documents to a blockchain by embedding a cryptographic hash of that data in a blockchain transaction, thereby creating a tamper-evident, timestamped proof of existence and integrity that can be independently verified by any party with access to the document and the chain. The blockchain's immutability and distributed consensus guarantee that the anchoring transaction cannot be altered retroactively, providing a trust anchor without requiring the document itself to be stored on-chain. Applications span document notarisation, supply chain provenance, audit logs, and verifiable credential revocation."@en ;
rdfs:label "Blockchain Anchoring"@en ;
rdfs:subClassOf ngm:blockchain-infrastructure ;
rdfs:subClassOf ngm:cryptographic-hash-function ;
vc:enables ngm:audit-trail ;
vc:enables ngm:data-integrity ;
vc:enables ngm:immutable-record ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:cryptographic-proof ;
vc:relatedTo ngm:timestamp ;
vc:slug "blockchain-anchoring" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:blockchain-transaction ;
vc:uses ngm:cryptographic-hash-function ;
vc:uses ngm:merkle-tree .
ngm:blockchain-api-gateway a skos:Concept ;
rdfs:label "Blockchain API Gateway"@en .
ngm:blockchain-application a owl:Class ;
rdfs:comment "A decentralized application (dApp) that runs on a blockchain or peer-to-peer network rather than centralized servers, combining smart contract backend logic with frontend interfaces to provide enhanced security, transparency, censorship resistance, and zero downtime through distributed execution."@en ;
rdfs:label "Blockchain Application"@en ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf ngm:distributed-application ;
rdfs:subClassOf ngm:network-component ;
rdfs:subClassOf _:r3337 ;
rdfs:subClassOf _:r3338 ;
rdfs:subClassOf _:r3339 ;
rdfs:subClassOf _:r3340 ;
rdfs:subClassOf _:r3341 ;
rdfs:subClassOf _:r3342 ;
skos:broader ngm:blockchain ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:bridgesTo ngm:supply-chain-management ;
vc:contrastsWith ngm:centralized-application ;
vc:dependsOn ngm:blockchain-infrastructure ;
vc:dependsOn ngm:consensus-mechanism ;
vc:dependsOn ngm:cryptographic-hash-function ;
vc:dependsOn ngm:peer-to-peer-network ;
vc:enables ngm:non-fungible-token ;
vc:enables ngm:tokenization ;
vc:enables ngm:web3 ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:blockchain-oracle ;
vc:hasPart ngm:decentralized-storage ;
vc:hasPart ngm:smart-contracts ;
vc:implements ngm:distributed-ledger ;
vc:implements ngm:smart-contracts ;
vc:isPartOf ngm:decentralized-finance-de-fi ;
vc:isPartOf ngm:web3 ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:dao ;
vc:relatedTo ngm:decentralized-finance-de-fi ;
vc:relatedTo ngm:smart-contracts ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:cryptocurrency-wallet ;
vc:requires ngm:gas-fee ;
vc:slug "blockchain-application" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:decentralized-governance ;
vc:supports ngm:digital-identity ;
vc:uses ngm:blockchain-infrastructure ;
vc:uses ngm:ethereum-smart-contract-platform-virtual-machine ;
vc:uses ngm:layer-2-scaling .
ngm:blockchain-as-a-service a owl:Class ;
rdfs:comment "Blockchain as a Service (BaaS) is a managed cloud delivery model in which a third-party provider provisions, operates, and maintains the distributed ledger infrastructure, consensus-node orchestration, cryptographic identity services, smart contract deployment pipelines, and monitoring tooling re..."@en ;
rdfs:label "Blockchain As A Service"@en ;
rdfs:subClassOf ngm:cloud-service-model ;
rdfs:subClassOf ngm:distributed-ledger-technology ;
rdfs:subClassOf ngm:enterprise-software-platform ;
rdfs:subClassOf ngm:managed-service ;
rdfs:subClassOf ngm:network-component ;
rdfs:subClassOf ngm:platform-as-a-service ;
rdfs:subClassOf _:r3343 ;
rdfs:subClassOf _:r3344 ;
rdfs:subClassOf _:r3345 ;
rdfs:subClassOf _:r3346 ;
rdfs:subClassOf _:r3347 ;
rdfs:subClassOf _:r3348 ;
rdfs:subClassOf _:r3349 ;
rdfs:subClassOf _:r3350 ;
rdfs:subClassOf _:r3351 ;
rdfs:subClassOf _:r3352 ;
rdfs:subClassOf _:r3353 ;
rdfs:subClassOf _:r3354 ;
vc:bridgesTo ngm:enterprise-software-platform ;
vc:bridgesTo ngm:infra-network-and-comms ;
vc:contrastsWith ngm:de-fi ;
vc:contrastsWith ngm:permissionless-blockchain ;
vc:contrastsWith ngm:proof-of-work ;
vc:contrastsWith ngm:public-blockchain ;
vc:contrastsWith ngm:public-cloud-blockchain ;
vc:contrastsWith ngm:self-hosted-blockchain-infrastructure ;
vc:dependsOn ngm:api-gateway ;
vc:dependsOn ngm:cloud-computing ;
vc:dependsOn ngm:container-orchestration ;
vc:dependsOn ngm:cryptographic-infrastructure ;
vc:dependsOn ngm:devops ;
vc:dependsOn ngm:hardware-security-module ;
vc:dependsOn ngm:microservices ;
vc:enables ngm:asset-tokenisation ;
vc:enables ngm:cbdc-infrastructure ;
vc:enables ngm:consortium-governance ;
vc:enables ngm:cross-border-payments ;
vc:enables ngm:digital-identity-verification ;
vc:enables ngm:permissioned-blockchain ;
vc:enables ngm:smart-contract-execution ;
vc:enables ngm:supply-chain-traceability ;
vc:enables ngm:trade-finance-automation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:blockchain-api-gateway ;
vc:hasPart ngm:certificate-authority ;
vc:hasPart ngm:consensus-service ;
vc:hasPart ngm:identity-management ;
vc:hasPart ngm:ledger-storage ;
vc:hasPart ngm:managed-node-hosting ;
vc:hasPart ngm:monitoring-dashboard ;
vc:hasPart ngm:network-provisioning-templates ;
vc:hasPart ngm:smart-contract-deployment-pipeline ;
vc:implements ngm:byzantine-fault-tolerance ;
vc:implements ngm:crash-fault-tolerance ;
vc:implements ngm:ethereum-smart-contract-platform ;
vc:implements ngm:fisco-bcos ;
vc:implements ngm:hyperledger-besu ;
vc:implements ngm:hyperledger-fabric ;
vc:implements ngm:quorum ;
vc:implements ngm:r3-corda ;
vc:implements ngm:raft-consensus ;
vc:implements ngm:smart-bft ;
vc:implements ngm:smartbft ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:api-management ;
vc:relatedTo ngm:cbdcs ;
vc:relatedTo ngm:cloud-computing ;
vc:relatedTo ngm:confidential-computing ;
vc:relatedTo ngm:decentralised-identity ;
vc:relatedTo ngm:devops ;
vc:relatedTo ngm:digital-asset ;
vc:relatedTo ngm:distributed-ledger-technology ;
vc:relatedTo ngm:enterprise-blockchain ;
vc:relatedTo ngm:neural-network-text-tokenisation ;
vc:relatedTo ngm:smart-contracts ;
vc:relatedTo ngm:zero-knowledge-proof ;
vc:requires ngm:blockchain-protocol ;
vc:requires ngm:cloud-infrastructure ;
vc:requires ngm:consensus-algorithm ;
vc:requires ngm:container-orchestration ;
vc:requires ngm:cryptographic-key-management ;
vc:requires ngm:identity-provider ;
vc:requires ngm:tls-encryption ;
vc:slug "blockchain-as-a-service" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:enterprise-ethereum-alliance ;
vc:standardizedBy ngm:hyperledger-foundation ;
vc:standardizedBy ngm:ietf-satp ;
vc:standardizedBy ngm:iso-tc-307 ;
vc:standardizedBy ngm:lf-decentralized-trust ;
vc:standardizedBy ngm:nist-sp-800-235 ;
vc:standardizedBy ngm:w3-c-did-specification ;
vc:supports ngm:enterprise-blockchain ;
vc:supports ngm:financial-services-compliance ;
vc:supports ngm:gdpr-compliance ;
vc:supports ngm:hipaa ;
vc:supports ngm:multi-cloud-deployment ;
vc:supports ngm:permissioned-blockchain ;
vc:supports ngm:sovereign-cloud ;
vc:supports ngm:supply-chain-management ;
vc:uses ngm:aws-iam ;
vc:uses ngm:azure-active-directory ;
vc:uses ngm:couchdb ;
vc:uses ngm:docker-containerisation-platform ;
vc:uses ngm:g-rpc ;
vc:uses ngm:hardware-security-module ;
vc:uses ngm:json-data-interchange-format-rpc ;
vc:uses ngm:kubernetes ;
vc:uses ngm:leveldb ;
vc:uses ngm:postgre-sql ;
vc:uses ngm:rest-api .
ngm:blockchain-attestation a skos:Concept ;
rdfs:label "Blockchain Attestation"@en .
ngm:blockchain-carbon-credits a skos:Concept ;
rdfs:label "Blockchain Carbon Credits"@en .
ngm:blockchain-carbon-tokens a skos:Concept ;
rdfs:label "Blockchain Carbon Tokens"@en .
ngm:blockchain-collaboration a owl:Class ;
rdfs:comment "\"The use of blockchain distributed ledger technology, smart contracts, and cryptocurrency systems to coordinate, govern, and compensate geographically distributed teams, enabling trustless collaboration through cryptographic verification, automated enforcement of agreements, and transparent recor..."@en ;
rdfs:label "Blockchain Collaboration"@en ;
rdfs:subClassOf ngm:dc-protocol-and-infra ;
rdfs:subClassOf ngm:telecollaboration ;
rdfs:subClassOf _:r3355 ;
rdfs:subClassOf _:r3356 ;
skos:broader ngm:dc-protocol-and-infra ;
vc:enables ngm:transparent-decision-making ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:consensus-protocol ;
vc:slug "blockchain-collaboration" ;
vc:sourceDomain "distributed-collaboration" .
ngm:blockchain-compliance a owl:Class ;
rdfs:comment "The framework of regulatory requirements, technical controls, and operational procedures ensuring blockchain systems and crypto-asset service providers comply with applicable laws including AML/KYC, GDPR, securities regulations, and jurisdiction-specific mandates while maintaining transparency and security."@en ;
rdfs:label "Blockchain Compliance"@en ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
rdfs:subClassOf ngm:regulatory-compliance ;
rdfs:subClassOf _:r3357 ;
rdfs:subClassOf _:r3358 ;
rdfs:subClassOf _:r3359 ;
rdfs:subClassOf _:r3360 ;
rdfs:subClassOf _:r3361 ;
skos:broader ngm:bc-governance-and-regulation ;
vc:bridgesTo ngm:financial-crime-prevention ;
vc:bridgesTo ngm:regulatory-compliance ;
vc:bridgesTo ngm:telecollaboration ;
vc:contrastsWith ngm:de-fi ;
vc:contrastsWith ngm:privacy-coin ;
vc:dependsOn ngm:audit-trail ;
vc:dependsOn ngm:blockchain ;
vc:enables ngm:institutional-adoption ;
vc:enables ngm:regulatory-clarity ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:data-protection ;
vc:implements ngm:financial-regulation ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:aml ;
vc:relatedTo ngm:blockchain ;
vc:relatedTo ngm:kyc ;
vc:relatedTo ngm:regulatory-reporting ;
vc:relatedTo ngm:regulatory-technology ;
vc:relatedTo ngm:securities-regulation ;
vc:requires ngm:aml ;
vc:requires ngm:counter-terrorist-financing ;
vc:requires ngm:identity-verification ;
vc:requires ngm:kyc ;
vc:requires ngm:transaction-monitoring ;
vc:slug "blockchain-compliance" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:bc-0484-markets-in-crypto-assets ;
vc:standardizedBy ngm:fatf ;
vc:uses ngm:blockchain-analytics ;
vc:uses ngm:decentralized-identity ;
vc:uses ngm:smart-contract ;
vc:uses ngm:zero-knowledge-proof .
ngm:blockchain-consensus a owl:Class ;
rdfs:comment "Blockchain Consensus refers to the family of distributed agreement protocols by which independent, potentially adversarial nodes in a blockchain network reach agreement on a single canonical version of the transaction ledger, including the ordering, validity, and finality of all blocks. These protocols must tolerate Byzantine faults — nodes that may behave maliciously or arbitrarily — and operate across open, permissionless networks without a trusted coordinator. The choice of consensus mechanism fundamentally shapes a blockchain's security model, throughput, energy consumption, and degree of decentralisation."@en ;
rdfs:label "Blockchain Consensus"@en ;
rdfs:subClassOf ngm:consensus-mechanism ;
rdfs:subClassOf _:r3362 ;
rdfs:subClassOf _:r3363 ;
rdfs:subClassOf _:r3364 ;
rdfs:subClassOf _:r3365 ;
rdfs:subClassOf _:r3366 ;
rdfs:subClassOf _:r3367 ;
rdfs:subClassOf _:r3368 ;
rdfs:subClassOf _:r3369 ;
rdfs:subClassOf _:r3370 ;
vc:bridgesTo ngm:decentralised-governance ;
vc:bridgesTo ngm:distributed-systems ;
vc:contrastsWith ngm:centralised-database ;
vc:contrastsWith ngm:paxos ;
vc:contrastsWith ngm:raft-consensus ;
vc:dependsOn ngm:byzantine-fault-tolerance ;
vc:dependsOn ngm:cryptographic-hash-function ;
vc:dependsOn ngm:merkle-tree ;
vc:enables ngm:double-spend-prevention ;
vc:enables ngm:finality ;
vc:enables ngm:permissionless-participation ;
vc:enables ngm:sybil-resistance ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:delegated-proof-of-stake ;
vc:hasPart ngm:nakamoto-consensus ;
vc:hasPart ngm:practical-byzantine-fault-tolerance ;
vc:hasPart ngm:proof-of-stake ;
vc:hasPart ngm:proof-of-work ;
vc:hasPart ngm:tendermint ;
vc:isPartOf ngm:blockchain-protocol ;
vc:isPartOf ngm:distributed-ledger-technology ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:block-production ;
vc:relatedTo ngm:blockchain-ledger ;
vc:relatedTo ngm:fork-choice-rule ;
vc:relatedTo ngm:slashing ;
vc:requires ngm:digital-signature ;
vc:requires ngm:peer-to-peer-network ;
vc:requires ngm:validator-node ;
vc:slug "blockchain-consensus" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:game-theory ;
vc:uses ngm:public-key-cryptography .
ngm:blockchain-core a owl:Class ;
rdfs:comment "Blockchain core denotes the foundational base-layer components of a blockchain system: the consensus protocol, the append-only ledger data structure, the peer-to-peer network, and the validation rules that together produce a shared, tamper-resistant state. It is the substrate on which higher-level constructs such as tokens, wallets, and smart contracts are built. As the trust anchor of a chain, its design dictates the network's security, decentralisation, and throughput."@en ;
rdfs:label "Blockchain Core"@en ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf ngm:blockchain-protocol ;
skos:broader ngm:blockchain ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:digital-wallet ;
vc:relatedTo ngm:token-economics ;
vc:slug "blockchain-core" ;
vc:sourceDomain "blockchain" .
ngm:blockchain-core-concepts a owl:Class ;
rdfs:comment "The foundational technical concepts of blockchain and distributed ledger technology, encompassing consensus mechanisms (PoW, PoS), cryptographic primitives (public-key encryption, digital signatures, hash functions, Merkle trees), smart contracts, tokens, and governance frameworks. These concepts collectively enable trustless transaction validation, DeFi, NFTs, and metaverse digital economies."@en ;
rdfs:label "blockchain core concepts"@en ;
rdfs:subClassOf ngm:infra-computing-and-cloud ;
rdfs:subClassOf _:r22775 ;
rdfs:subClassOf _:r22776 ;
rdfs:subClassOf _:r22777 ;
rdfs:subClassOf _:r22778 ;
skos:broader ngm:infra-computing-and-cloud ;
vc:enables ngm:dao ;
vc:enables ngm:layer2-scaling ;
vc:enables ngm:zero-knowledge ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:consensus-algorithm ;
vc:hasPart ngm:hash-function ;
vc:hasPart ngm:merkle-tree ;
vc:hasPart ngm:smart-contract ;
vc:qualityScore "0.4"^^xsd:float ;
vc:slug "blockchain-core-concepts" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:digital-signature ;
vc:uses ngm:distributed-ledger .
ngm:blockchain-credentialing a skos:Concept ;
rdfs:label "Blockchain Credentialing"@en .
ngm:blockchain-data a owl:Class ;
rdfs:comment "Blockchain Data refers to the structured information stored on a distributed ledger, comprising transaction records, state data, smart contract bytecode, event logs, and cryptographic proofs organised into immutable, hash-linked blocks. It is characterised by append-only semantics, cryptographic integrity, and public verifiability. The data model differs fundamentally from traditional databases in that history cannot be altered without recomputing the entire subsequent chain."@en ;
rdfs:label "Blockchain Data"@en ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf ngm:network-component ;
rdfs:subClassOf _:r3371 ;
rdfs:subClassOf _:r3372 ;
rdfs:subClassOf _:r3373 ;
rdfs:subClassOf _:r3374 ;
skos:broader ngm:blockchain ;
vc:bridgesTo ngm:data-analytics ;
vc:contrastsWith ngm:centralised-database ;
vc:dependsOn ngm:peer-to-peer-network ;
vc:enables ngm:asset-tokenisation ;
vc:enables ngm:audit-trail ;
vc:enables ngm:neural-network-text-tokenisation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:merkle-tree ;
vc:hasPart ngm:transaction ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:consensus-mechanism ;
vc:relatedTo ngm:data ;
vc:relatedTo ngm:immutability ;
vc:requires ngm:cryptographic-hash ;
vc:requires ngm:distributed-ledger ;
vc:slug "blockchain-data" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:data-provenance ;
vc:supports ngm:decentralised-application ;
vc:supports ngm:smart-contract .
ngm:blockchain-data-sharing a skos:Concept ;
rdfs:label "Blockchain Data Sharing"@en .
ngm:blockchain-document-trail-infrastructure a owl:Class ;
rdfs:comment "A concept node representing resource trails related to blockchain exploration tools and Nostr-based document sharing infrastructure. In the NarrativeGoldmine context, blocktrails links to split-screen markdown editing and decentralised document storage via NosDAV and the Nostr protocol."@en ;
rdfs:label "Blockchain Document Trail Infrastructure"@en ;
rdfs:subClassOf ngm:infra-computing-and-cloud ;
skos:broader ngm:infra-computing-and-cloud ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:blockchain-core-concepts ;
vc:relatedTo ngm:decentralised-identity ;
vc:slug "blockchain-document-trail-infrastructure" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:knowledge-base ;
vc:uses ngm:web-technology .
ngm:blockchain-domain a skos:Concept ;
rdfs:label "Blockchain Domain"@en .
ngm:blockchain-economics a owl:Class ;
rdfs:comment "The study and design of economic mechanisms governing blockchain networks, including incentive structures for validators, fee markets, token supply schedules, governance models, and the emergent macro-economic properties of decentralised systems. Blockchain economics integrates mechanism design, game theory, and monetary theory to sustain network security and participant alignment."@en ;
rdfs:label "Blockchain Economics"@en ;
rdfs:subClassOf ngm:token-economics ;
rdfs:subClassOf _:r3375 ;
rdfs:subClassOf _:r3376 ;
rdfs:subClassOf _:r3377 ;
rdfs:subClassOf _:r3378 ;
rdfs:subClassOf _:r3379 ;
rdfs:subClassOf _:r3380 ;
vc:bridgesTo ngm:decentralised-autonomous-organisation ;
vc:bridgesTo ngm:supply-chain-finance ;
vc:contrastsWith ngm:monetary-policy ;
vc:dependsOn ngm:cryptographic-primitive ;
vc:dependsOn ngm:distributed-ledger-technology ;
vc:enables ngm:de-fi ;
vc:enables ngm:digital-asset-market ;
vc:enables ngm:proof-of-stake ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:consensus-mechanism ;
vc:hasPart ngm:emission-schedule ;
vc:hasPart ngm:fee-market ;
vc:hasPart ngm:governance-token ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:blockchain-governance ;
vc:relatedTo ngm:cryptocurrency-token ;
vc:relatedTo ngm:miner-extractable-value ;
vc:relatedTo ngm:staking ;
vc:requires ngm:game-theory ;
vc:requires ngm:mechanism-design ;
vc:slug "blockchain-economics" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:network-security ;
vc:supports ngm:on-chain-governance ;
vc:uses ngm:auction-theory ;
vc:uses ngm:monetary-theory .
ngm:blockchain-economy a skos:Concept ;
rdfs:label "Blockchain Economy"@en .
ngm:blockchain-energy-consumption a owl:Class ;
rdfs:comment "The electrical power and computational resources consumed by blockchain networks during transaction validation, block creation, and network security operations, varying significantly across consensus mechanisms from energy-intensive Proof-of-Work (Bitcoin: ~140 TWh/year, 0.65% of global electricity) to energy-efficient Proof-of-Stake (Ethereum post-Merge: 99.95% reduction), with ongoing research into sustainable consensus algorithms, renewable energy mining, carbon credit tokenization, and environmental impact measurement frameworks."@en ;
rdfs:label "Blockchain Energy Consumption"@en ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
rdfs:subClassOf ngm:blockchainperformance ;
rdfs:subClassOf ngm:environmentalimpact ;
rdfs:subClassOf ngm:sustainability ;
rdfs:subClassOf _:r3381 ;
rdfs:subClassOf _:r3382 ;
rdfs:subClassOf _:r3383 ;
rdfs:subClassOf _:r3384 ;
skos:broader ngm:bc-governance-and-regulation ;
vc:bridgesTo ngm:ai-energy-optimisation ;
vc:bridgesTo ngm:sustainability ;
vc:contrastsWith ngm:directed-acyclic-graph ;
vc:contrastsWith ngm:proof-of-stake ;
vc:dependsOn ngm:consensus-mechanism ;
vc:dependsOn ngm:energy-source ;
vc:dependsOn ngm:energysource ;
vc:dependsOn ngm:mining-hardware ;
vc:dependsOn ngm:mininghardware ;
vc:dependsOn ngm:networksize ;
vc:enables ngm:renewable-energy-certificates ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:carbonemissions ;
vc:hasPart ngm:computationalpower ;
vc:hasPart ngm:e-waste ;
vc:hasPart ngm:electricity-consumption ;
vc:hasPart ngm:electricityconsumption ;
vc:hasPart ngm:hash-rate ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:bitcoin-mining-council ;
vc:relatedTo ngm:cambridge-bitcoin-electricity-consumption-index ;
vc:relatedTo ngm:layer-2-scaling ;
vc:slug "blockchain-energy-consumption" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:crypto-climate-accord ;
vc:standardizedBy ngm:greenhouse-gas-protocol ;
vc:standardizedBy ngm:iso-14064 ;
vc:uses ngm:application-specific-integrated-circuit ;
vc:uses ngm:proof-of-stake ;
vc:uses ngm:proof-of-work .
ngm:blockchain-entity a owl:Class ;
rdfs:comment "A Blockchain Entity is the foundational abstract conceptual class representing any distinct component, construct, or participant within a blockchain ecosystem."@en ;
rdfs:label "Blockchain Entity"@en ;
rdfs:subClassOf ngm:network-component ;
rdfs:subClassOf _:r3385 ;
rdfs:subClassOf _:r3386 ;
rdfs:subClassOf _:r3387 ;
rdfs:subClassOf _:r3388 ;
rdfs:subClassOf _:r3389 ;
rdfs:subClassOf _:r3390 ;
rdfs:subClassOf _:r3391 ;
rdfs:subClassOf _:r3392 ;
rdfs:subClassOf _:r3393 ;
rdfs:subClassOf _:r3394 ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:digital-twin ;
vc:enables ngm:audit-trail ;
vc:enables ngm:autonomous-governance ;
vc:enables ngm:decentralised-coordination ;
vc:enables ngm:distributed-trust ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:block ;
vc:hasPart ngm:consensus-mechanism ;
vc:hasPart ngm:cryptographic-key ;
vc:hasPart ngm:cryptographic-keys ;
vc:hasPart ngm:node ;
vc:hasPart ngm:smart-contract ;
vc:hasPart ngm:transaction ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:cryptographic-security ;
vc:requires ngm:distributed-protocol ;
vc:requires ngm:network-participation ;
vc:slug "blockchain-entity" ;
vc:sourceDomain "blockchain" .
ngm:blockchain-environmental-impact-assessment a owl:Class ;
rdfs:comment "A systematic emodology for measuring, analyzing, and reporting the environmental consequences of blockchain network operations, encompassing energy consumption measurement (electricity usage per transaction, annual network consumption), carbon emissions calculation (CO₂e from electricity generati..."@en ;
rdfs:label "Blockchain Environmental Impact Assessment"@en ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
rdfs:subClassOf ngm:blockchain-governance ;
rdfs:subClassOf ngm:environmental-assessment ;
rdfs:subClassOf ngm:life-cycle-assessment ;
rdfs:subClassOf ngm:sustainabilitymetric ;
rdfs:subClassOf _:r3395 ;
rdfs:subClassOf _:r3396 ;
rdfs:subClassOf _:r3397 ;
rdfs:subClassOf _:r3398 ;
rdfs:subClassOf _:r3399 ;
rdfs:subClassOf _:r3400 ;
rdfs:subClassOf _:r3401 ;
rdfs:subClassOf _:r3402 ;
rdfs:subClassOf _:r3403 ;
rdfs:subClassOf _:r3404 ;
rdfs:subClassOf _:r3405 ;
rdfs:subClassOf _:r3406 ;
rdfs:subClassOf _:r3407 ;
skos:broader ngm:bc-governance-and-regulation ;
vc:bridgesTo ngm:ai-energy-optimisation ;
vc:bridgesTo ngm:governance ;
vc:bridgesTo ngm:life-cycle-assessment ;
vc:enables ngm:carbon-accounting ;
vc:enables ngm:investor-disclosure ;
vc:enables ngm:investordisclosure ;
vc:enables ngm:regulatory-compliance ;
vc:enables ngm:sustainability-reporting ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:carbon-accounting ;
vc:hasPart ngm:energy-consumption ;
vc:hasPart ngm:ewasteanalysis ;
vc:hasPart ngm:scope-definition ;
vc:hasPart ngm:scopedefinition ;
vc:hasPart ngm:waterusagetracking ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:consensus-algorithm ;
vc:requires ngm:datacentermetrics ;
vc:requires ngm:energy-management ;
vc:requires ngm:hardware ;
vc:requires ngm:network-hash-rate ;
vc:slug "blockchain-environmental-impact-assessment" ;
vc:sourceDomain "blockchain" .
ngm:blockchain-gaming a owl:Class ;
rdfs:comment "A gaming paradigm in which in-game assets, economies, and ownership records are managed on distributed ledgers, enabling players to hold verifiable ownership of digital items as NFTs, participate in play-to-earn economies, and trade assets across compatible platforms without relying on centralised game servers for provenance or scarcity guarantees."@en ;
rdfs:label "Blockchain Gaming"@en ;
rdfs:subClassOf ngm:decentralised-application ;
rdfs:subClassOf _:r3408 ;
rdfs:subClassOf _:r3409 ;
rdfs:subClassOf _:r3410 ;
rdfs:subClassOf _:r3411 ;
vc:bridgesTo ngm:de-fi ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:metaverse ;
vc:contrastsWith ngm:gaming ;
vc:dependsOn ngm:blockchain-protocol ;
vc:dependsOn ngm:layer-2-scaling ;
vc:dependsOn ngm:nft-marketplace ;
vc:enables ngm:asset-portability ;
vc:enables ngm:digital-ownership ;
vc:enables ngm:virtual-currency ;
vc:enables ngm:virtual-economy ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:game-asset-generation ;
vc:hasPart ngm:play-to-earn-p2-e ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:governance-token ;
vc:relatedTo ngm:interoperability ;
vc:relatedTo ngm:tokenization ;
vc:requires ngm:crypto-wallet ;
vc:requires ngm:gas-fee ;
vc:slug "blockchain-gaming" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:blockchain ;
vc:uses ngm:decentralised-autonomous-organisation ;
vc:uses ngm:nft ;
vc:uses ngm:smart-contract ;
vc:uses ngm:token .
ngm:blockchain-governance a owl:Class ;
rdfs:comment "Blockchain Governance refers to the mechanisms, processes, and structures through which decisions are made about the development, operation, and evolution of blockchain networks and protocols, encompassing on-chain voting systems, decentralised autonomous organisations, and community-driven decision-making frameworks."@en ;
rdfs:label "Blockchain Governance"@en ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
rdfs:subClassOf ngm:blockchain-entity ;
rdfs:subClassOf ngm:decentralized-autonomous-organization ;
rdfs:subClassOf _:r3412 ;
rdfs:subClassOf _:r3413 ;
rdfs:subClassOf _:r3414 ;
rdfs:subClassOf _:r3415 ;
rdfs:subClassOf _:r3416 ;
rdfs:subClassOf _:r3417 ;
rdfs:subClassOf _:r3418 ;
rdfs:subClassOf _:r3419 ;
rdfs:subClassOf _:r3420 ;
rdfs:subClassOf _:r3421 ;
rdfs:subClassOf _:r3422 ;
rdfs:subClassOf _:r3423 ;
rdfs:subClassOf _:r3424 ;
skos:broader ngm:bc-governance-and-regulation ;
vc:bridgesTo ngm:collective-intelligence ;
vc:bridgesTo ngm:digital-democracy ;
vc:bridgesTo ngm:telecollaboration ;
vc:contrastsWith ngm:centralised-governance ;
vc:contrastsWith ngm:corporate-governance ;
vc:dependsOn ngm:blockchain-technology ;
vc:dependsOn ngm:distributed-ledger ;
vc:enables ngm:community-alignment ;
vc:enables ngm:decentralised-decision-making ;
vc:enables ngm:protocol-evolution ;
vc:enables ngm:protocol-upgrades ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:blockchain-entity ;
vc:hasPart ngm:dao ;
vc:hasPart ngm:delegation-system ;
vc:hasPart ngm:on-chain-voting ;
vc:hasPart ngm:proposal-system ;
vc:hasPart ngm:quadratic-voting ;
vc:qualityScore "0.68"^^xsd:float ;
vc:relatedTo ngm:network-effects ;
vc:relatedTo ngm:stakeholder-coordination ;
vc:relatedTo ngm:token-economics ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:smart-contract ;
vc:requires ngm:token ;
vc:requires ngm:voting-mechanism ;
vc:slug "blockchain-governance" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:cryptographic-proof ;
vc:uses ngm:smart-contracts ;
vc:uses ngm:token .
ngm:blockchain-hash-function a skos:Concept ;
rdfs:label "Blockchain Hash Function"@en .
ngm:blockchain-hash-functions a skos:Concept ;
rdfs:label "Blockchain Hash Functions"@en .
ngm:blockchain-health-data a skos:Concept ;
rdfs:label "Blockchain Health Data"@en .
ngm:blockchain-identity a owl:Class ;
rdfs:comment "Blockchain Identity is an approach to digital identity in which identifiers, credentials and attestations are anchored to a distributed ledger rather than a single central authority. It gives users cryptographic control over their identity through key pairs, enables verifiable claims that any party can check against on-chain or anchored data, and underpins self-sovereign identity models. By decentralising the registry of identifiers, it reduces reliance on intermediaries and supports portable, tamper-evident identity across services."@en ;
rdfs:label "Blockchain Identity"@en ;
rdfs:subClassOf ngm:decentralized-identity ;
rdfs:subClassOf _:r3425 ;
rdfs:subClassOf _:r3426 ;
rdfs:subClassOf _:r3427 ;
rdfs:subClassOf _:r3428 ;
vc:bridgesTo ngm:blockchain ;
vc:contrastsWith ngm:identity-management ;
vc:dependsOn ngm:did ;
vc:enables ngm:self-sovereign-identity ;
vc:enables ngm:single-sign-on ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:decentralized-identifier ;
vc:hasPart ngm:verifiable-credentials ;
vc:isPartOf ngm:decentralized-identity ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:digital-identity ;
vc:requires ngm:cryptographic-infrastructure ;
vc:requires ngm:distributed-ledger ;
vc:slug "blockchain-identity" ;
vc:sourceDomain "security" ;
vc:supports ngm:access-control ;
vc:supports ngm:authentication ;
vc:supports ngm:privacy ;
vc:uses ngm:digital-certificate ;
vc:uses ngm:smart-contract ;
vc:uses ngm:zero-knowledge-proof .
ngm:blockchain-immutability a skos:Concept ;
rdfs:label "Blockchain Immutability"@en .
ngm:blockchain-infrastructure a owl:Class ;
rdfs:comment "The foundational technical components enabling blockchain networks to operate, including nodes, networking protocols, consensus mechanisms, storage systems, and cryptographic primitives that together provide the physical and logical substrate for distributed ledger operation and decentralized application execution."@en ;
rdfs:label "Blockchain Infrastructure"@en ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf ngm:distributed-systems ;
rdfs:subClassOf ngm:network-component ;
rdfs:subClassOf _:r3429 ;
rdfs:subClassOf _:r3430 ;
rdfs:subClassOf _:r3431 ;
rdfs:subClassOf _:r3432 ;
rdfs:subClassOf _:r3433 ;
rdfs:subClassOf _:r3434 ;
rdfs:subClassOf _:r3435 ;
skos:broader ngm:blockchain ;
vc:bridgesTo ngm:ai-energy-optimisation ;
vc:bridgesTo ngm:decentralized-identity ;
vc:bridgesTo ngm:internet-of-things ;
vc:contrastsWith ngm:centralised-database ;
vc:contrastsWith ngm:financial-infrastructure ;
vc:dependsOn ngm:digital-signature ;
vc:dependsOn ngm:hash-function ;
vc:dependsOn ngm:network-protocol ;
vc:enables ngm:blockchain-application ;
vc:enables ngm:de-fi ;
vc:enables ngm:layer-2-scaling ;
vc:enables ngm:smart-contracts ;
vc:enables ngm:tokenization ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:blockchain-node ;
vc:hasPart ngm:consensus-mechanism ;
vc:hasPart ngm:cross-chain-bridge ;
vc:hasPart ngm:smart-contracts ;
vc:implements ngm:proof-of-stake ;
vc:implements ngm:proof-of-work ;
vc:isPartOf ngm:distributed-systems ;
vc:isPartOf ngm:web-3-infrastructure ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:blockchain ;
vc:relatedTo ngm:consensus-mechanism ;
vc:relatedTo ngm:modular-blockchain ;
vc:requires ngm:cryptography ;
vc:requires ngm:distributed-ledger ;
vc:requires ngm:peer-to-peer-network ;
vc:slug "blockchain-infrastructure" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:dao ;
vc:supports ngm:non-fungible-token ;
vc:uses ngm:merkle-tree ;
vc:uses ngm:peer-to-peer-network ;
vc:uses ngm:zero-knowledge-proof .
ngm:blockchain-interoperability a owl:Class ;
rdfs:comment "Blockchain Interoperability is the technical and economic capability for distinct, sovereign blockchain networks to securely communicate state, transfer assets, invoke smart contracts, and propagate consensus across heterogeneous trust domains without relinquishing each chain's independent finali..."@en ;
rdfs:label "Blockchain Interoperability"@en ;
rdfs:subClassOf ngm:blockchain-infrastructure ;
rdfs:subClassOf ngm:cross-chain-communication ;
rdfs:subClassOf ngm:cryptographic-protocol ;
rdfs:subClassOf ngm:distributed-systems-protocol ;
rdfs:subClassOf ngm:network-component ;
rdfs:subClassOf ngm:network-interoperability ;
rdfs:subClassOf _:r3436 ;
rdfs:subClassOf _:r3437 ;
rdfs:subClassOf _:r3438 ;
rdfs:subClassOf _:r3439 ;
rdfs:subClassOf _:r3440 ;
rdfs:subClassOf _:r3441 ;
rdfs:subClassOf _:r3442 ;
rdfs:subClassOf _:r3443 ;
rdfs:subClassOf _:r3444 ;
rdfs:subClassOf _:r3445 ;
rdfs:subClassOf _:r3446 ;
rdfs:subClassOf _:r3447 ;
rdfs:subClassOf _:r3448 ;
rdfs:subClassOf _:r3449 ;
vc:bridgesTo ngm:network-interoperability ;
vc:contrastsWith ngm:centralised-exchange-bridging ;
vc:contrastsWith ngm:custodial-asset-transfer ;
vc:contrastsWith ngm:notary-scheme ;
vc:contrastsWith ngm:single-chain-architecture ;
vc:contrastsWith ngm:wrapped-token-custodian-model ;
vc:dependsOn ngm:blockchain-consensus ;
vc:dependsOn ngm:cryptographic-hash-function ;
vc:dependsOn ngm:digital-signature ;
vc:dependsOn ngm:liquidity-provider ;
vc:dependsOn ngm:merkle-proof ;
vc:dependsOn ngm:smart-contract-platform ;
vc:enables ngm:cross-chain-asset-transfer ;
vc:enables ngm:cross-chain-governance ;
vc:enables ngm:modular-blockchain-architecture ;
vc:enables ngm:multi-chain-de-fi ;
vc:enables ngm:omnichain-application ;
vc:enables ngm:token-standard ;
vc:enables ngm:unified-liquidity ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:bridge-contract ;
vc:hasPart ngm:cryptographic-proof-system ;
vc:hasPart ngm:light-client ;
vc:hasPart ngm:message-passing ;
vc:hasPart ngm:relayer ;
vc:hasPart ngm:state-verification-mechanism ;
vc:hasPart ngm:trust-assumption-model ;
vc:hasPart ngm:validator-set ;
vc:implements ngm:atomic-swap ;
vc:implements ngm:burn-and-mint-bridge ;
vc:implements ngm:hash-time-locked-contract ;
vc:implements ngm:intent-based-settlement ;
vc:implements ngm:light-client-verification ;
vc:implements ngm:lock-and-mint-bridge ;
vc:implements ngm:optimistic-verification ;
vc:implements ngm:zero-knowledge-proof-bridge ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:across-protocol ;
vc:relatedTo ngm:arbitrum ;
vc:relatedTo ngm:axelar ;
vc:relatedTo ngm:celestia ;
vc:relatedTo ngm:chainlink-ccip ;
vc:relatedTo ngm:cosmos ;
vc:relatedTo ngm:eigen-layer ;
vc:relatedTo ngm:hyperlane ;
vc:relatedTo ngm:ibc ;
vc:relatedTo ngm:layer-zero ;
vc:relatedTo ngm:optimism ;
vc:relatedTo ngm:polkadot ;
vc:relatedTo ngm:polygon-agg-layer ;
vc:relatedTo ngm:rollup ;
vc:relatedTo ngm:rollups ;
vc:relatedTo ngm:wormhole ;
vc:relatedTo ngm:xcm ;
vc:requires ngm:chain-state ;
vc:requires ngm:cryptographic-verification ;
vc:requires ngm:destination-chain-execution ;
vc:requires ngm:economic-security ;
vc:requires ngm:finality ;
vc:requires ngm:message-ordering ;
vc:slug "blockchain-interoperability" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:erc-7683 ;
vc:standardizedBy ngm:ibc-specification ;
vc:standardizedBy ngm:iso-20022 ;
vc:standardizedBy ngm:itu-cross-chain-reference-architecture ;
vc:standardizedBy ngm:open-bridge-standard ;
vc:standardizedBy ngm:xcm-format-specification ;
vc:supports ngm:cbdc-cross-border-settlement ;
vc:supports ngm:cross-chain-dex ;
vc:supports ngm:cross-chain-governance ;
vc:supports ngm:cross-chain-nft ;
vc:supports ngm:interchain-identity ;
vc:supports ngm:tokenised-real-world-asset-transfer ;
vc:supports ngm:wrapped-token ;
vc:uses ngm:hash-time-locked-contract ;
vc:uses ngm:multi-party-computation ;
vc:uses ngm:multi-signature ;
vc:uses ngm:optimistic-oracle ;
vc:uses ngm:restaked-validator ;
vc:uses ngm:threshold-signature-scheme ;
vc:uses ngm:zk-snark ;
vc:uses ngm:zk-snarks .
ngm:blockchain-key-custody a skos:Concept ;
rdfs:label "Blockchain Key Custody"@en .
ngm:blockchain-keypair a skos:Concept ;
rdfs:label "Blockchain Keypair"@en .
ngm:blockchain-knowledge a skos:Concept ;
rdfs:label "Blockchain Knowledge"@en .
ngm:blockchain-ledger a owl:Class ;
rdfs:comment "A Blockchain Ledger is the authoritative, append-only register of all validated transactions and state changes maintained collectively by participants in a blockchain network, representing the shared ground truth from which account balances, ownership records, and contract states are derived. Unlike a traditional centralised ledger maintained by a single institution, a blockchain ledger is replicated across potentially thousands of nodes, with consensus rules ensuring that all honest participants converge on the same view of history. Its integrity derives from cryptographic chaining rather than institutional trust."@en ;
rdfs:label "Blockchain Ledger"@en ;
rdfs:subClassOf ngm:distributed-ledger ;
rdfs:subClassOf _:r3450 ;
rdfs:subClassOf _:r3451 ;
rdfs:subClassOf _:r3452 ;
rdfs:subClassOf _:r3453 ;
rdfs:subClassOf _:r3454 ;
rdfs:subClassOf _:r3455 ;
rdfs:subClassOf _:r3456 ;
rdfs:subClassOf _:r3457 ;
rdfs:subClassOf _:r3458 ;
vc:bridgesTo ngm:data-provenance ;
vc:bridgesTo ngm:supply-chain-traceability ;
vc:contrastsWith ngm:centralised-database ;
vc:contrastsWith ngm:record-keeping-system ;
vc:enables ngm:audit-trail ;
vc:enables ngm:de-fi ;
vc:enables ngm:smart-contract ;
vc:enables ngm:tokenization ;
vc:enables ngm:transparency ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:blockchain-transaction ;
vc:hasPart ngm:genesis-block ;
vc:hasPart ngm:immutable-record ;
vc:hasPart ngm:merkle-tree ;
vc:hasPart ngm:utxo ;
vc:implements ngm:append-only-log ;
vc:implements ngm:byzantine-fault-tolerance ;
vc:isPartOf ngm:blockchain ;
vc:isPartOf ngm:peer-to-peer-network ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:proof-of-work ;
vc:relatedTo ngm:state-channel ;
vc:requires ngm:blockchain-consensus ;
vc:requires ngm:cryptographic-hash ;
vc:requires ngm:digital-signature ;
vc:requires ngm:node ;
vc:slug "blockchain-ledger" ;
vc:sourceDomain "blockchain" .
ngm:blockchain-naming a skos:Concept ;
rdfs:label "Blockchain Naming"@en .
ngm:blockchain-network a owl:Class ;
rdfs:comment "A Blockchain Network is a permissionless or permissioned peer-to-peer (P2P) overlay network through which participating nodes collectively maintain, validate, and propagate a shared append-only ledger (the blockchain) without relying on any central coordinator, achieving agreement through a deter..."@en ;
rdfs:label "Blockchain Network"@en ;
rdfs:subClassOf ngm:byzantine-fault-tolerant-system ;
rdfs:subClassOf ngm:distributed-system ;
rdfs:subClassOf ngm:fault-tolerance-system ;
rdfs:subClassOf ngm:network-component ;
rdfs:subClassOf ngm:overlay-network ;
rdfs:subClassOf ngm:peer-to-peer-network ;
rdfs:subClassOf _:r3459 ;
rdfs:subClassOf _:r3460 ;
rdfs:subClassOf _:r3461 ;
rdfs:subClassOf _:r3462 ;
rdfs:subClassOf _:r3463 ;
rdfs:subClassOf _:r3464 ;
rdfs:subClassOf _:r3465 ;
rdfs:subClassOf _:r3466 ;
rdfs:subClassOf _:r3467 ;
rdfs:subClassOf _:r3468 ;
rdfs:subClassOf _:r3469 ;
rdfs:subClassOf _:r3470 ;
rdfs:subClassOf _:r3471 ;
rdfs:subClassOf _:r3472 ;
rdfs:subClassOf _:r3473 ;
rdfs:subClassOf _:r3474 ;
rdfs:subClassOf _:r3475 ;
rdfs:subClassOf _:r3476 ;
rdfs:subClassOf _:r3477 ;
rdfs:subClassOf _:r3478 ;
vc:contrastsWith ngm:centralised-database ;
vc:contrastsWith ngm:client-server-architecture ;
vc:contrastsWith ngm:federated-network ;
vc:contrastsWith ngm:traditional-financial-network ;
vc:dependsOn ngm:cryptography ;
vc:dependsOn ngm:distributed-systems-theory ;
vc:dependsOn ngm:game-theory ;
vc:dependsOn ngm:network-theory ;
vc:dependsOn ngm:quic ;
vc:dependsOn ngm:tcp-ip ;
vc:enables ngm:censorship-resistance ;
vc:enables ngm:decentralized-finance-de-fi ;
vc:enables ngm:distributed-ledger-technology ;
vc:enables ngm:immutability ;
vc:enables ngm:smart-contract ;
vc:enables ngm:tokenization ;
vc:enables ngm:trustless-settlement ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:archive-node ;
vc:hasPart ngm:bootstrap-node ;
vc:hasPart ngm:finality ;
vc:hasPart ngm:fork-choice-rule ;
vc:hasPart ngm:full-node ;
vc:hasPart ngm:gossip-protocol ;
vc:hasPart ngm:light-client ;
vc:hasPart ngm:mempool ;
vc:hasPart ngm:mining-node ;
vc:hasPart ngm:peer-discovery ;
vc:hasPart ngm:validator ;
vc:implements ngm:casper-ffg ;
vc:implements ngm:gossip-protocol ;
vc:implements ngm:kademlia-dht ;
vc:implements ngm:lmd-ghost ;
vc:implements ngm:nakamoto-consensus ;
vc:implements ngm:proof-of-stake ;
vc:implements ngm:proof-of-work ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:blockchain ;
vc:relatedTo ngm:eclipse-attack ;
vc:relatedTo ngm:finality ;
vc:relatedTo ngm:fork ;
vc:relatedTo ngm:mining ;
vc:relatedTo ngm:network-topology ;
vc:relatedTo ngm:node ;
vc:relatedTo ngm:sharding ;
vc:relatedTo ngm:sybil-attack ;
vc:relatedTo ngm:validator ;
vc:requires ngm:byzantine-fault-tolerance ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:cryptographic-hash-function ;
vc:requires ngm:digital-signature ;
vc:requires ngm:peer-discovery ;
vc:requires ngm:public-key-cryptography ;
vc:requires ngm:transport-protocol ;
vc:slug "blockchain-network" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:bitcoin-proof-of-work-protocol-improvement-proposals ;
vc:standardizedBy ngm:ethereum-foundation-eips ;
vc:standardizedBy ngm:ieee-blockchain-initiative ;
vc:standardizedBy ngm:iso-tc-307 ;
vc:standardizedBy ngm:nist-sp-800-188 ;
vc:supports ngm:bitcoin-proof-of-work-protocol ;
vc:supports ngm:cosmos ;
vc:supports ngm:ethereum-smart-contract-platform ;
vc:supports ngm:hyperledger-fabric ;
vc:supports ngm:layer-2-solutions ;
vc:supports ngm:lightning-network ;
vc:supports ngm:polkadot ;
vc:supports ngm:solana ;
vc:uses ngm:devp2p ;
vc:uses ngm:discv5 ;
vc:uses ngm:dns-seed-bootstrap ;
vc:uses ngm:libp2p ;
vc:uses ngm:nat-traversal ;
vc:uses ngm:noise-protocol ;
vc:uses ngm:tls-encryption .
ngm:blockchain-node a owl:Class ;
rdfs:comment "A blockchain node is a computer running the protocol software of a blockchain network that maintains a copy of the ledger, validates transactions and blocks, and relays them to peers. Nodes collectively enforce the consensus rules and provide the decentralisation and redundancy that make the network trustworthy. They range from full nodes that store and verify the complete chain to light clients that verify selectively, and validator nodes that additionally participate in block production."@en ;
rdfs:label "Blockchain Node"@en ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf ngm:network-component ;
rdfs:subClassOf _:r3479 ;
rdfs:subClassOf _:r3480 ;
rdfs:subClassOf _:r3481 ;
skos:broader ngm:blockchain ;
vc:bridgesTo ngm:distributed-systems ;
vc:dependsOn ngm:consensus-mechanism ;
vc:dependsOn ngm:peer-to-peer-network ;
vc:enables ngm:validator ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:full-node ;
vc:hasPart ngm:mempool ;
vc:implements ngm:block-propagation ;
vc:isPartOf ngm:blockchain ;
vc:isPartOf ngm:peer-to-peer-network ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:consensus ;
vc:relatedTo ngm:full-node ;
vc:relatedTo ngm:light-client ;
vc:requires ngm:transaction-validation ;
vc:slug "blockchain-node" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:decentralisation ;
vc:supports ngm:distributed-ledger ;
vc:uses ngm:state-synchronisation .
ngm:blockchain-only-web3 a skos:Concept ;
rdfs:label "Blockchain Only Web3"@en .
ngm:blockchain-oracle a owl:Class ;
rdfs:comment "A decentralized service that bridges blockchain smart contracts with external real-world data, enabling smart contracts to access off-chain information, execute based on real-world events, and interact with traditional systems while maintaining trustless verification and data integrity."@en ;
rdfs:label "Blockchain Oracle"@en ;
rdfs:subClassOf ngm:network-component ;
rdfs:subClassOf _:r3482 ;
rdfs:subClassOf _:r3483 ;
rdfs:subClassOf _:r3484 ;
rdfs:subClassOf _:r3485 ;
rdfs:subClassOf _:r3486 ;
rdfs:subClassOf _:r3487 ;
vc:bridgesTo ngm:internet-of-things ;
vc:bridgesTo ngm:supply-chain-management ;
vc:bridgesTo ngm:traditional-finance ;
vc:contrastsWith ngm:on-chain-data-feed ;
vc:contrastsWith ngm:oracle ;
vc:dependsOn ngm:blockchain-network ;
vc:dependsOn ngm:external-data-source ;
vc:dependsOn ngm:smart-contracts ;
vc:enables ngm:decentralized-finance-de-fi ;
vc:enables ngm:parametric-insurance ;
vc:enables ngm:prediction-markets ;
vc:enables ngm:smart-contract ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:data-aggregation ;
vc:hasPart ngm:oracle-network ;
vc:hasPart ngm:oracle-node ;
vc:hasPart ngm:price-oracle ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:oracle-extractable-value ;
vc:relatedTo ngm:reputation-system ;
vc:relatedTo ngm:smart-contract-platform ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:cryptographic-verification ;
vc:requires ngm:staking ;
vc:slug "blockchain-oracle" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:data-aggregation ;
vc:uses ngm:digital-signatures ;
vc:uses ngm:tee ;
vc:uses ngm:zero-knowledge-proof .
ngm:blockchain-payment a skos:Concept ;
rdfs:label "Blockchain Payment"@en .
ngm:blockchain-process a owl:Class ;
rdfs:comment "Blockchain Process encompasses the operational workflows and procedural mechanisms that govern blockchain network functioning, including consensus execution, block validation, transaction verification, mempool management, state transitions, and protocol upgrade procedures. These processes collectively maintain network integrity and enable trustless distributed agreement."@en ;
rdfs:label "Blockchain Process"@en ;
rdfs:subClassOf ngm:network-component ;
rdfs:subClassOf _:r3488 ;
rdfs:subClassOf _:r3489 ;
vc:bridgesTo ngm:blockchain ;
vc:enables ngm:blockchain-scalability ;
vc:enables ngm:blockchain-transaction ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:isPartOf ngm:blockchain ;
vc:isPartOf ngm:blockchain-domain ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:cryptographic-primitive ;
vc:slug "blockchain-process" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:blockchain-network ;
vc:uses ngm:consensus-protocol .
ngm:blockchain-proof a skos:Concept ;
rdfs:label "Blockchain Proof"@en .
ngm:blockchain-protocol a owl:Class ;
rdfs:comment "Foundational rule set governing distributed ledger system operation comprising consensus mechanisms (algorithmic procedures enabling network-wide agreement on canonical state without centralized authority including Proof of Work PoW SHA-256 hash puzzles requiring computational expenditure Bitcoin..."@en ;
rdfs:label "Blockchain Protocol"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf ngm:consensus-algorithm ;
rdfs:subClassOf ngm:cryptographic-protocol ;
rdfs:subClassOf ngm:distributed-system-protocol ;
rdfs:subClassOf ngm:network-protocol ;
rdfs:subClassOf ngm:peerto-peer-protocol ;
rdfs:subClassOf ngm:state-machine-replication ;
rdfs:subClassOf _:r3490 ;
rdfs:subClassOf _:r3491 ;
rdfs:subClassOf _:r3492 ;
rdfs:subClassOf _:r3493 ;
rdfs:subClassOf _:r3494 ;
rdfs:subClassOf _:r3495 ;
rdfs:subClassOf _:r3496 ;
rdfs:subClassOf _:r3497 ;
rdfs:subClassOf _:r3498 ;
rdfs:subClassOf _:r3499 ;
rdfs:subClassOf _:r3500 ;
rdfs:subClassOf _:r3501 ;
rdfs:subClassOf _:r3502 ;
rdfs:subClassOf _:r3503 ;
rdfs:subClassOf _:r3504 ;
rdfs:subClassOf _:r3505 ;
rdfs:subClassOf _:r3506 ;
rdfs:subClassOf _:r3507 ;
rdfs:subClassOf _:r3508 ;
rdfs:subClassOf _:r3509 ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:distributed-system-protocol ;
vc:dependsOn ngm:database-system ;
vc:dependsOn ngm:digital-signature-scheme ;
vc:dependsOn ngm:economic-model ;
vc:dependsOn ngm:hash-function ;
vc:dependsOn ngm:merkle-tree ;
vc:dependsOn ngm:networking-stack ;
vc:dependsOn ngm:public-key-cryptography ;
vc:dependsOn ngm:virtual-machine ;
vc:enables ngm:byzantine-fault-tolerance ;
vc:enables ngm:censorship-resistance ;
vc:enables ngm:cross-chain-interoperability ;
vc:enables ngm:decentralized-consensus ;
vc:enables ngm:defi-applications ;
vc:enables ngm:double-spend-prevention ;
vc:enables ngm:nft-standards ;
vc:enables ngm:permissionless-participation ;
vc:enables ngm:smart-contract-execution ;
vc:enables ngm:tokenization ;
vc:enables ngm:trustless-execution ;
vc:enables ngm:value-transfer ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:block-propagation ;
vc:hasPart ngm:block-structure ;
vc:hasPart ngm:consensus-mechanism ;
vc:hasPart ngm:digital-signature ;
vc:hasPart ngm:fee-market ;
vc:hasPart ngm:governance-system ;
vc:hasPart ngm:hash-function ;
vc:hasPart ngm:merkle-tree ;
vc:hasPart ngm:network-protocol ;
vc:hasPart ngm:peer-discovery ;
vc:hasPart ngm:state-storage ;
vc:hasPart ngm:state-transition-function ;
vc:hasPart ngm:transaction-format ;
vc:hasPart ngm:transaction-validation ;
vc:hasPart ngm:virtual-machine ;
vc:implements ngm:bft-consensus ;
vc:implements ngm:consensus-algorithm ;
vc:implements ngm:fee-mechanism ;
vc:implements ngm:governance-voting ;
vc:implements ngm:merkle-proof ;
vc:implements ngm:nakamoto-consensus ;
vc:implements ngm:slashing-conditions ;
vc:implements ngm:state-machine-replication ;
vc:implements ngm:transaction-ordering ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:block-validation ;
vc:requires ngm:consensus-algorithm ;
vc:requires ngm:cryptographic-primitive ;
vc:requires ngm:economic-incentives ;
vc:requires ngm:network-synchronization ;
vc:requires ngm:peer-to-peer-network ;
vc:requires ngm:state-database ;
vc:requires ngm:transaction-pool ;
vc:slug "blockchain-protocol" ;
vc:sourceDomain "blockchain" .
ngm:blockchain-provenance a owl:Class ;
rdfs:comment "Blockchain Provenance is the application of distributed ledger technology to record and verify the complete historical lineage of an asset, document, or data artefact, such that its origin, custody chain, and transformations are cryptographically authenticated and tamper-resistant. Each provenance event is anchored as an immutable transaction on-chain, enabling any party to independently reconstruct and audit the full lifecycle of the item without relying on a central authority."@en ;
rdfs:label "Blockchain Provenance"@en ;
rdfs:subClassOf ngm:blockchain-technology ;
rdfs:subClassOf _:r3510 ;
rdfs:subClassOf _:r3511 ;
rdfs:subClassOf _:r3512 ;
vc:bridgesTo ngm:verifiable-data-registry ;
vc:bridgesTo ngm:zero-knowledge-proof ;
vc:contrastsWith ngm:centralised-database ;
vc:dependsOn ngm:decentralised-network ;
vc:dependsOn ngm:immutability ;
vc:enables ngm:audit-trail ;
vc:enables ngm:chain-of-custody ;
vc:enables ngm:digital-product-passport ;
vc:enables ngm:non-fungible-token ;
vc:enables ngm:supply-chain-traceability ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:data-integrity ;
vc:implements ngm:provenance-tracking ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:decentralized-identifier ;
vc:relatedTo ngm:interplanetary-file-system ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:cryptographic-infrastructure ;
vc:requires ngm:oracle-network ;
vc:slug "blockchain-provenance" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:gs1-epcis ;
vc:standardizedBy ngm:w3-c-verifiable-credentials ;
vc:supports ngm:intellectual-property-rights ;
vc:supports ngm:regulatory-compliance ;
vc:uses ngm:content-addressed-storage ;
vc:uses ngm:cryptographic-hash ;
vc:uses ngm:digital-signature ;
vc:uses ngm:distributed-ledger-technology ;
vc:uses ngm:merkle-tree ;
vc:uses ngm:smart-contract .
ngm:blockchain-record a skos:Concept ;
rdfs:label "Blockchain Record"@en .
ngm:blockchain-records a skos:Concept ;
rdfs:label "Blockchain Records"@en .
ngm:blockchain-reference-architecture a skos:Concept ;
rdfs:label "Blockchain Reference Architecture"@en .
ngm:blockchain-regulation a skos:Concept ;
rdfs:label "Blockchain Regulation"@en .
ngm:blockchain-research a skos:Concept ;
rdfs:label "Blockchain Research"@en .
ngm:blockchain-scalability a owl:Class ;
rdfs:comment "Blockchain Scalability encompasses the technical solutions and architectural approaches designed to increase the transaction throughput, reduce latency, and improve the efficiency of blockchain networks while maintaining security and decentralisation."@en ;
rdfs:label "Blockchain Scalability"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf ngm:blockchain-entity ;
rdfs:subClassOf ngm:performance ;
rdfs:subClassOf ngm:protocol-architecture ;
rdfs:subClassOf _:r3513 ;
rdfs:subClassOf _:r3514 ;
rdfs:subClassOf _:r3515 ;
rdfs:subClassOf _:r3516 ;
rdfs:subClassOf _:r3517 ;
rdfs:subClassOf _:r3518 ;
rdfs:subClassOf _:r3519 ;
rdfs:subClassOf _:r3520 ;
rdfs:subClassOf _:r3521 ;
rdfs:subClassOf _:r3522 ;
rdfs:subClassOf _:r3523 ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:bridgesTo ngm:ai-energy-optimisation ;
vc:bridgesTo ngm:data-compression ;
vc:bridgesTo ngm:internet-of-things ;
vc:bridgesTo ngm:performance ;
vc:contrastsWith ngm:blockchain-trilemma ;
vc:contrastsWith ngm:on-chain-transaction ;
vc:dependsOn ngm:cryptographic-proof ;
vc:dependsOn ngm:data-compression ;
vc:dependsOn ngm:peer-to-peer-network ;
vc:enables ngm:de-fi ;
vc:enables ngm:high-throughput ;
vc:enables ngm:low-latency ;
vc:enables ngm:mass-adoption ;
vc:enables ngm:micropayment ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:layer-2-solution ;
vc:hasPart ngm:layer-2-solutions ;
vc:hasPart ngm:optimistic-rollup ;
vc:hasPart ngm:payment-channel ;
vc:hasPart ngm:rollup ;
vc:hasPart ngm:sharding ;
vc:hasPart ngm:state-channel ;
vc:hasPart ngm:zero-knowledge-rollup ;
vc:implements ngm:fraud-proof ;
vc:isPartOf ngm:blockchain-technology ;
vc:isPartOf ngm:distributed-ledger-technology ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:blockchain-interoperability ;
vc:relatedTo ngm:danksharding ;
vc:relatedTo ngm:lightning-network ;
vc:relatedTo ngm:transaction-finality ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:data-availability ;
vc:requires ngm:network-infrastructure ;
vc:requires ngm:smart-contract ;
vc:slug "blockchain-scalability" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:merkle-tree ;
vc:uses ngm:zero-knowledge-proof .
ngm:blockchain-security a owl:Class ;
rdfs:comment "Blockchain security is the multidisciplinary field concerned with protecting distributed ledger systems against attacks on their consensus mechanisms, smart contract logic, cryptographic primitives, and network topology, while preserving the properties of immutability, censorship resistance, and trustless operation. It encompasses threat modelling, formal verification of on-chain code, cryptographic auditing, and economic game-theory analysis to prevent incentive manipulation. The discipline extends across permissionless and permissioned blockchain architectures, addressing layer-specific attack surfaces from peer-to-peer networking through execution environments to cross-chain interoperability bridges."@en ;
rdfs:label "Blockchain Security"@en ;
rdfs:subClassOf ngm:cybersecurity ;
rdfs:subClassOf _:r3524 ;
rdfs:subClassOf _:r3525 ;
rdfs:subClassOf _:r3526 ;
rdfs:subClassOf _:r3527 ;
rdfs:subClassOf _:r3528 ;
vc:bridgesTo ngm:ai-security ;
vc:bridgesTo ngm:post-quantum-cryptography ;
vc:contrastsWith ngm:51-attack ;
vc:contrastsWith ngm:double-spending ;
vc:contrastsWith ngm:reentrancy-attack ;
vc:contrastsWith ngm:sybil-attack ;
vc:enables ngm:de-fi ;
vc:enables ngm:immutability ;
vc:enables ngm:trustless-system ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:consensus-security ;
vc:hasPart ngm:cryptographic-key-management ;
vc:hasPart ngm:smart-contract-audit ;
vc:isPartOf ngm:cybersecurity ;
vc:isPartOf ngm:distributed-systems-security ;
vc:qualityScore "0.76"^^xsd:float ;
vc:relatedTo ngm:blockchain ;
vc:relatedTo ngm:cryptographic-security ;
vc:relatedTo ngm:miner-extractable-value ;
vc:relatedTo ngm:smart-contract ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:cryptographic-protocol ;
vc:requires ngm:formal-verification ;
vc:slug "blockchain-security" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:nist-cybersecurity-framework ;
vc:uses ngm:multi-signature ;
vc:uses ngm:oracle-network ;
vc:uses ngm:zero-knowledge-proof .
ngm:blockchain-standards a skos:Concept ;
rdfs:label "Blockchain Standards"@en .
ngm:blockchain-storage a skos:Concept ;
rdfs:label "Blockchain Storage"@en .
ngm:blockchain-sustainability a owl:Class ;
rdfs:comment "The practice of designing, operating, and evolving blockchain networks to minimize environmental impact through energy-efficient consensus mechanisms, renewable energy integration, and carbon offset strategies, encompassing metrics, governance, and cross-sector environmental accountability."@en ;
rdfs:label "Blockchain Sustainability"@en ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf _:r3529 ;
rdfs:subClassOf _:r3530 ;
rdfs:subClassOf _:r3531 ;
rdfs:subClassOf _:r3532 ;
skos:broader ngm:bc-governance-and-regulation ;
skos:broader ngm:blockchain ;
vc:bridgesTo ngm:ai-energy-optimisation ;
vc:bridgesTo ngm:environmental-verification ;
vc:contrastsWith ngm:proof-of-work ;
vc:enables ngm:carbon-credits ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:carbon-offset-programme ;
vc:hasPart ngm:layer-2-scaling ;
vc:hasPart ngm:renewable-energy-integration ;
vc:implements ngm:delegated-proof-of-stake ;
vc:implements ngm:proof-of-authority ;
vc:implements ngm:proof-of-stake ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:crypto-climate-accord ;
vc:relatedTo ngm:esg-compliance ;
vc:relatedTo ngm:green-finance ;
vc:requires ngm:consensus-mechanism ;
vc:slug "blockchain-sustainability" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:greenwashing-prevention ;
vc:supports ngm:supply-chain-transparency ;
vc:uses ngm:green-finance ;
vc:uses ngm:state-channel ;
vc:uses ngm:zero-knowledge-rollup .
ngm:blockchain-technology a owl:Class ;
rdfs:comment "Blockchain Technology is a class of distributed ledger systems in which validated transactions are grouped into blocks that are cryptographically linked in an append-only sequence, maintained by a peer-to-peer network through a consensus mechanism. Each block header includes the cryptographic hash of its predecessor, a timestamp, and a Merkle root of its transaction set, ensuring that altering any historical record requires re-computing all subsequent proofs, which is computationally or economically prohibitive. The design eliminates the need for a trusted central authority by replacing it with algorithmic agreement, enabling trustless settlement, programmable value transfer via smart contracts, and tamper-evident audit trails across diverse application domains."@en ;
rdfs:label "Blockchain Technology"@en ;
rdfs:subClassOf ngm:distributed-ledger-technology ;
rdfs:subClassOf _:r3534 ;
rdfs:subClassOf _:r3535 ;
rdfs:subClassOf _:r3536 ;
rdfs:subClassOf _:r3537 ;
rdfs:subClassOf _:r3538 ;
rdfs:subClassOf _:r3539 ;
rdfs:subClassOf _:r3540 ;
vc:bridgesTo ngm:digital-identity ;
vc:bridgesTo ngm:federated-learning ;
vc:bridgesTo ngm:supply-chain-management ;
vc:contrastsWith ngm:centralised-database ;
vc:contrastsWith ngm:traditional-financial-system ;
vc:enables ngm:blockchain-provenance ;
vc:enables ngm:de-fi ;
vc:enables ngm:decentralised-autonomous-organisation ;
vc:enables ngm:neural-network-text-tokenisation ;
vc:enables ngm:non-fungible-token ;
vc:enables ngm:smart-contract ;
vc:enables ngm:tokenization ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:block-header ;
vc:hasPart ngm:genesis-block ;
vc:hasPart ngm:mempool ;
vc:qualityScore "0.76"^^xsd:float ;
vc:relatedTo ngm:cross-chain-interoperability ;
vc:relatedTo ngm:cryptocurrency ;
vc:relatedTo ngm:layer-2-scaling ;
vc:relatedTo ngm:sidechain ;
vc:relatedTo ngm:zero-knowledge-proof ;
vc:requires ngm:byzantine-fault-tolerance ;
vc:requires ngm:immutability ;
vc:requires ngm:network-node ;
vc:requires ngm:node ;
vc:slug "blockchain-technology" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:consensus-mechanism ;
vc:uses ngm:cryptographic-hash ;
vc:uses ngm:digital-signature ;
vc:uses ngm:merkle-tree ;
vc:uses ngm:peer-to-peer-network ;
vc:uses ngm:public-key-cryptography .
ngm:blockchain-technology-laboratory a owl:Class ;
rdfs:comment "An academic or institutional research unit dedicated to the study, prototyping and evaluation of distributed ledger systems and their applications. Such laboratories produce experimental implementations, measurements and analyses rather than production services."@en ;
rdfs:label "Blockchain Technology Laboratory"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf ngm:blockchain-domain ;
rdfs:subClassOf _:r3533 ;
skos:broader ngm:bc-protocol-and-consensus ;
skos:broader ngm:blockchain ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:scalability ;
vc:enables ngm:consensus-mechanism ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:distributed-ledger-technology ;
vc:slug "blockchain-technology-laboratory" ;
vc:sourceDomain "blockchain" .
ngm:blockchain-terminology a skos:Concept ;
rdfs:label "Blockchain Terminology"@en .
ngm:blockchain-token a skos:Concept ;
rdfs:label "Blockchain Token"@en .
ngm:blockchain-tokenisation a skos:Concept ;
rdfs:label "Blockchain Tokenisation"@en .
ngm:blockchain-transaction a owl:Class ;
rdfs:comment "A Blockchain Transaction is an atomic, cryptographically signed instruction that encodes a state-change on a distributed ledger — such as a transfer of digital assets, invocation of a smart contract function, or mutation of on-chain data. Transactions are broadcast to a peer-to-peer network, validated against protocol rules and the active consensus mechanism, and permanently recorded in an ordered block once accepted. The transaction model differs fundamentally between UTXO-based chains (e.g. Bitcoin) and account-based chains (e.g. Ethereum), affecting parallelism, privacy, and composability."@en ;
rdfs:label "Blockchain Transaction"@en ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf ngm:network-component ;
rdfs:subClassOf _:r3541 ;
rdfs:subClassOf _:r3542 ;
rdfs:subClassOf _:r3543 ;
rdfs:subClassOf _:r3544 ;
rdfs:subClassOf _:r3545 ;
rdfs:subClassOf _:r3546 ;
rdfs:subClassOf _:r3547 ;
rdfs:subClassOf _:r3548 ;
rdfs:subClassOf _:r3549 ;
rdfs:subClassOf _:r3550 ;
skos:broader ngm:blockchain ;
vc:bridgesTo ngm:digital-identity ;
vc:bridgesTo ngm:supply-chain-traceability ;
vc:contrastsWith ngm:traditional-payment ;
vc:contrastsWith ngm:transaction ;
vc:enables ngm:atomic-swap ;
vc:enables ngm:de-fi ;
vc:enables ngm:neural-network-text-tokenisation ;
vc:enables ngm:payment-system ;
vc:enables ngm:smart-contract ;
vc:enables ngm:tokenization ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:merkle-tree ;
vc:hasPart ngm:nonce ;
vc:hasPart ngm:transaction-input ;
vc:hasPart ngm:transaction-output ;
vc:hasPart ngm:utxo ;
vc:hasPart ngm:utxo-unspent-transaction-output ;
vc:isPartOf ngm:blockchain ;
vc:isPartOf ngm:distributed-ledger ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:block ;
vc:relatedTo ngm:layer-2-protocol ;
vc:relatedTo ngm:transaction-throughput ;
vc:requires ngm:consensus-algorithm ;
vc:requires ngm:cryptographic-hash-function ;
vc:requires ngm:digital-signature ;
vc:requires ngm:public-key-cryptography ;
vc:requires ngm:transaction-fee ;
vc:slug "blockchain-transaction" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:elliptic-curve-cryptography ;
vc:uses ngm:mempool ;
vc:uses ngm:zero-knowledge-proof .
ngm:blockchain-transaction-integrity a skos:Concept ;
rdfs:label "Blockchain Transaction Integrity"@en .
ngm:blockchain-transaction-log a skos:Concept ;
rdfs:label "Blockchain Transaction Log"@en .
ngm:blockchain-trilemma a skos:Concept ;
rdfs:label "Blockchain Trilemma"@en .
ngm:blockchain-validation a skos:Concept ;
rdfs:label "Blockchain Validation"@en .
ngm:blockchain-validator a skos:Concept ;
rdfs:label "Blockchain Validator"@en .
ngm:blockchain-verification a skos:Concept ;
rdfs:label "Blockchain Verification"@en .
ngm:blockchain-wallet a owl:Class ;
rdfs:comment "A blockchain wallet is software or hardware that manages the cryptographic keys used to control assets and identities on a blockchain. Rather than storing assets directly, a wallet stores private keys, derives public addresses, and signs transactions that authorise the movement of on-chain assets. Wallets range from custodial services that hold keys on a user's behalf to self-custody solutions where the user retains exclusive control."@en ;
rdfs:label "Blockchain Wallet"@en ;
rdfs:subClassOf ngm:key-management ;
rdfs:subClassOf _:r3551 ;
rdfs:subClassOf _:r3552 ;
rdfs:subClassOf _:r3553 ;
rdfs:subClassOf _:r3554 ;
vc:bridgesTo ngm:de-fi ;
vc:bridgesTo ngm:smart-contract ;
vc:dependsOn ngm:blockchain ;
vc:dependsOn ngm:transaction-signing ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:de-fi ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:cryptocurrency ;
vc:relatedTo ngm:custody ;
vc:relatedTo ngm:digital-asset ;
vc:relatedTo ngm:hardware-wallet ;
vc:relatedTo ngm:self-custody ;
vc:requires ngm:digital-signature ;
vc:requires ngm:private-key ;
vc:requires ngm:public-key-cryptography ;
vc:requires ngm:seed-phrase ;
vc:slug "blockchain-wallet" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:asset-management ;
vc:supports ngm:blockchain-transaction .
ngm:blocking a skos:Concept ;
rdfs:label "Blocking"@en .
ngm:blockstream a owl:Class ;
rdfs:comment "Blockstream is a Bitcoin-focused technology company founded in 2014 that develops open-source infrastructure and commercial products for the Bitcoin ecosystem, including the Liquid Network federated sidechain, c-lightning (now Core Lightning), and satellite-based blockchain distribution via Blockstream Satellite. The company is led by co-founders including Adam Back (inventor of Hashcash) and is a major contributor to Bitcoin Core protocol development. Blockstream's work spans cryptographic research, Layer 2 payment channels, hardware security modules, and institutional-grade Bitcoin financial products such as Blockstream AMP (Asset Management Platform)."@en ;
rdfs:label "Blockstream"@en ;
rdfs:subClassOf ngm:blockchain-infrastructure ;
rdfs:subClassOf ngm:network-component ;
rdfs:subClassOf _:r3564 ;
rdfs:subClassOf _:r3565 ;
rdfs:subClassOf _:r3566 ;
rdfs:subClassOf _:r3567 ;
vc:bridgesTo ngm:de-fi ;
vc:bridgesTo ngm:digital-asset-custody ;
vc:contrastsWith ngm:ethereum ;
vc:contrastsWith ngm:ethereum-smart-contract-platform-virtual-machine ;
vc:dependsOn ngm:bitcoin-proof-of-work-protocol-core ;
vc:dependsOn ngm:cryptographic-hash-function ;
vc:enables ngm:confidential-transactions ;
vc:enables ngm:federated-peg ;
vc:enables ngm:lightning-network ;
vc:enables ngm:sidechain ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:blockstream-amp ;
vc:hasPart ngm:blockstream-satellite ;
vc:hasPart ngm:core-lightning ;
vc:hasPart ngm:liquid-network ;
vc:implements ngm:elements-project ;
vc:implements ngm:schnorr-signature ;
vc:implements ngm:taproot ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:layer-2-scaling ;
vc:relatedTo ngm:multisig ;
vc:relatedTo ngm:payment-channel-network ;
vc:requires ngm:bitcoin ;
vc:requires ngm:proof-of-work ;
vc:slug "blockstream" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:bitcoin-proof-of-work-protocol-core ;
vc:supports ngm:open-source-development ;
vc:uses ngm:hardware-security-module ;
vc:uses ngm:hashcash ;
vc:uses ngm:satellite-communication .
ngm:blockstream-amp a skos:Concept ;
rdfs:label "Blockstream Amp"@en .
ngm:blockstream-satellite a skos:Concept ;
rdfs:label "Blockstream Satellite"@en .
ngm:blockweave a skos:Concept ;
rdfs:label "Blockweave"@en .
ngm:bloom a skos:Concept ;
rdfs:label "Bloom"@en .
ngm:bloom-filter a owl:Class ;
rdfs:comment "A Bloom Filter is a space-efficient probabilistic data structure that tests whether an element is a member of a set, accepting a controllable false-positive rate while guaranteeing zero false negatives. Invented by Burton Howard Bloom in 1970, the structure uses multiple hash functions to map elements to bit positions within a fixed-size bit array. Membership queries are answered in constant time regardless of set size, making Bloom Filters indispensable in high-throughput systems where exact lookup is prohibitively expensive. They are widely deployed in databases, networking, distributed caches, and blockchain nodes."@en ;
rdfs:label "Bloom Filter"@en ;
rdfs:subClassOf ngm:data-structure ;
vc:contrastsWith ngm:spatial-data-structure ;
vc:enables ngm:latency ;
vc:enables ngm:membership-inference ;
vc:enables ngm:privacy-filter ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:distributed-data-structure ;
vc:relatedTo ngm:hash-function ;
vc:relatedTo ngm:probabilistic-model ;
vc:slug "bloom-filter" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:cryptographic-hash-function ;
vc:uses ngm:hash-collision .
ngm:bloom-filters a skos:Concept ;
rdfs:label "Bloom Filters"@en .
ngm:bloom-s-taxonomy a skos:Concept ;
rdfs:label "Bloom S Taxonomy"@en .
ngm:bloom-taxonomy a skos:Concept ;
rdfs:label "Bloom Taxonomy"@en .
ngm:bls-signature a owl:Class ;
rdfs:comment "A BLS Signature (Boneh–Lynn–Shacham signature) is a cryptographic signature scheme built on bilinear pairings over elliptic curves that permits multiple individual signatures to be aggregated into a single constant-size signature, which can be verified against the aggregate of the corresponding public keys in a single pairing operation. This aggregation property drastically reduces bandwidth and verification cost when many parties must co-sign a message or attest to a block."@en ;
rdfs:label "BLS Signature"@en ;
rdfs:subClassOf ngm:digital-signature ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:bridgesTo ngm:infrastructure ;
vc:contrastsWith ngm:ecdsa ;
vc:contrastsWith ngm:schnorr-signature ;
vc:dependsOn ngm:discrete-logarithm-problem ;
vc:enables ngm:consensus-mechanism ;
vc:enables ngm:distributed-validator-technology ;
vc:enables ngm:signature-aggregation ;
vc:enables ngm:threshold-signature-scheme ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:digital-signature ;
vc:implements ngm:proof-of-stake ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:key-management ;
vc:relatedTo ngm:multi-party-computation ;
vc:relatedTo ngm:zero-knowledge-proof ;
vc:relatedTo ngm:zk-snark ;
vc:slug "bls-signature" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:distributed-key-generation ;
vc:supports ngm:validator-attestation ;
vc:uses ngm:bilinear-pairing ;
vc:uses ngm:elliptic-curve-cryptography ;
vc:uses ngm:hash-function ;
vc:uses ngm:public-key-cryptography .
ngm:bls12-381 a skos:Concept ;
rdfs:label "Bls12 381"@en .
ngm:bls12-381-curve a skos:Concept ;
rdfs:label "Bls12 381 Curve"@en .
ngm:blu-ray-disc-association a skos:Concept ;
rdfs:label "Blu Ray Disc Association"@en .
ngm:blu-ray-disc-standards a skos:Concept ;
rdfs:label "Blu Ray Disc Standards"@en .
ngm:blue-green-deployment a skos:Concept ;
rdfs:label "Blue Green Deployment"@en .
ngm:blue-yonder-luminate a skos:Concept ;
rdfs:label "Blue Yonder Luminate"@en .
ngm:bluesky-at-protocol a skos:Concept ;
rdfs:label "Bluesky At Protocol"@en .
ngm:bluesky-pbc a skos:Concept ;
rdfs:label "Bluesky Pbc"@en .
ngm:bluetooth a owl:Class ;
rdfs:comment "A short-range wireless communication standard for exchanging data between devices over radio frequencies in the 2.4 gigahertz band. It is widely used for peripherals, audio, and low-power sensors."@en ;
rdfs:label "Bluetooth"@en ;
rdfs:subClassOf ngm:infra-network-and-comms ;
rdfs:subClassOf ngm:owl-thing ;
skos:broader ngm:infra-network-and-comms ;
vc:bridgesTo ngm:internet-of-things ;
vc:enables ngm:bluetooth-low-energy ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:slug "bluetooth" ;
vc:sourceDomain "infrastructure" .
ngm:bluetooth-core-specification a skos:Concept ;
rdfs:label "Bluetooth Core Specification"@en .
ngm:bluetooth-le a owl:Class ;
rdfs:comment "Bluetooth LE (Low Energy), also known as Bluetooth Smart, is a short-range wireless communication protocol introduced in Bluetooth 4.0 (2010) and standardised by the Bluetooth SIG, designed to transmit small amounts of data at low duty cycles while consuming a fraction of the power of Classic Bluetooth. It operates in the 2.4 GHz ISM band with 40 channels, using frequency-hopping spread spectrum, and is optimised for battery-constrained devices that need to remain active for months or years on a coin cell."@en ;
rdfs:label "Bluetooth LE"@en ;
rdfs:subClassOf ngm:bluetooth-low-energy ;
vc:enables ngm:internet-of-things ;
vc:enables ngm:proximity-detection ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:embedded-systems ;
vc:relatedTo ngm:near-field-communication ;
vc:relatedTo ngm:zigbee ;
vc:slug "bluetooth-le" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:bluetooth-sig ;
vc:uses ngm:low-energy-consumption .
ngm:bluetooth-low-energy a owl:Class ;
rdfs:comment "Bluetooth Low Energy (BLE) is the formal designation of the low-power wireless communication mode introduced in the Bluetooth 4.0 Core Specification (2010), standardised by the Bluetooth SIG, enabling battery-constrained devices to communicate over short ranges (typically 10–100 m) using duty-cycled radio bursts with peak currents measured in milliamps. It defines a complete protocol stack from physical layer through application profiles, and has become the dominant short-range radio for wearable, medical, industrial, and IoT devices."@en ;
rdfs:label "Bluetooth Low Energy"@en ;
rdfs:subClassOf ngm:internet-of-things ;
rdfs:subClassOf _:r3568 ;
vc:bridgesTo ngm:robotics ;
vc:bridgesTo ngm:spatial-computing ;
vc:contrastsWith ngm:wi-fi ;
vc:enables ngm:asset-tracking ;
vc:enables ngm:sensor-technology ;
vc:enables ngm:service-discovery ;
vc:enables ngm:wearable-computing ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:bluetooth-le ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:matter-protocol ;
vc:relatedTo ngm:near-field-communication ;
vc:relatedTo ngm:thread-protocol ;
vc:relatedTo ngm:ultra-wideband ;
vc:relatedTo ngm:zigbee ;
vc:slug "bluetooth-low-energy" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:bluetooth-sig ;
vc:uses ngm:embedded-systems ;
vc:uses ngm:mesh-networking .
ngm:bluetooth-mesh a skos:Concept ;
rdfs:label "Bluetooth Mesh"@en .
ngm:bluetooth-sig a owl:Class ;
rdfs:comment "The Bluetooth Special Interest Group (Bluetooth SIG) is the non-profit trade association responsible for developing, maintaining, and licensing the Bluetooth wireless communication standard. Founded in 1998 by Ericsson, IBM, Intel, Nokia, and Toshiba, it governs the Bluetooth Core Specification and the library of Bluetooth profiles, managing qualification and branding programmes that ensure interoperability among the over 50,000 member companies worldwide."@en ;
rdfs:label "Bluetooth SIG"@en ;
rdfs:subClassOf ngm:standards-body ;
vc:enables ngm:bluetooth-le ;
vc:enables ngm:bluetooth-low-energy ;
vc:enables ngm:interoperability ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:embedded-systems ;
vc:relatedTo ngm:internet-of-things ;
vc:slug "bluetooth-sig" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:ieee-standards-association .
ngm:blur a skos:Concept ;
rdfs:label "Blur"@en .
ngm:bm25 a owl:Class ;
rdfs:comment "BM25 (Best Match 25) is a probabilistic bag-of-words ranking function used in information retrieval to score documents against a query based on term frequency saturation, document length normalisation, and inverse document frequency weighting. Derived from the BM family of retrieval functions developed at the Robertson-Spärck Jones framework in the 1970s-1990s, BM25 extends TF-IDF by applying a saturation parameter (k1) that prevents very high term frequencies from dominating relevance scores and a length normalisation parameter (b) that adjusts for document verbosity. It remains the dominant sparse lexical retrieval baseline in modern information retrieval systems."@en ;
rdfs:label "BM25"@en ;
rdfs:subClassOf ngm:information-retrieval ;
rdfs:subClassOf ngm:keyword-search ;
rdfs:subClassOf ngm:probabilistic-relevance-model ;
rdfs:subClassOf ngm:search-algorithm ;
rdfs:subClassOf _:r2642 ;
rdfs:subClassOf _:r2643 ;
rdfs:subClassOf _:r2644 ;
rdfs:subClassOf _:r2645 ;
rdfs:subClassOf _:r2646 ;
rdfs:subClassOf _:r2647 ;
rdfs:subClassOf _:r2648 ;
rdfs:subClassOf _:r2649 ;
rdfs:subClassOf _:r2650 ;
rdfs:subClassOf _:r2651 ;
vc:bridgesTo ngm:large-language-model ;
vc:bridgesTo ngm:vector-database ;
vc:contrastsWith ngm:dense-passage-retrieval ;
vc:contrastsWith ngm:dense-retrieval ;
vc:contrastsWith ngm:embeddings ;
vc:contrastsWith ngm:semantic-search ;
vc:dependsOn ngm:information-retrieval ;
vc:dependsOn ngm:inverted-index ;
vc:dependsOn ngm:natural-language-processing ;
vc:dependsOn ngm:neural-network-text-tokenisation ;
vc:enables ngm:agentic-rag ;
vc:enables ngm:ai-search ;
vc:enables ngm:document-retrieval ;
vc:enables ngm:enterprise-search ;
vc:enables ngm:hybrid-retrieval ;
vc:enables ngm:keyword-search ;
vc:enables ngm:knowledge-retrieval ;
vc:enables ngm:retrieval-augmented-generation-rag ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:document-retrieval ;
vc:hasPart ngm:inverted-index ;
vc:hasPart ngm:natural-language-processing ;
vc:hasPart ngm:neural-network-text-tokenisation ;
vc:hasPart ngm:tf-idf ;
vc:implements ngm:inverted-index ;
vc:implements ngm:natural-language-processing ;
vc:implements ngm:neural-network-text-tokenisation ;
vc:implements ngm:tf-idf ;
vc:qualityScore "0.93"^^xsd:float ;
vc:relatedTo ngm:agentic-rag ;
vc:relatedTo ngm:ai-search ;
vc:relatedTo ngm:cross-encoder-reranking ;
vc:relatedTo ngm:dense-passage-retrieval ;
vc:relatedTo ngm:document-retrieval ;
vc:relatedTo ngm:information-retrieval ;
vc:relatedTo ngm:inverted-index ;
vc:relatedTo ngm:keyword-search ;
vc:relatedTo ngm:knowledge-retrieval ;
vc:relatedTo ngm:search-index ;
vc:relatedTo ngm:semantic-search ;
vc:relatedTo ngm:splade ;
vc:relatedTo ngm:tf-idf ;
vc:relatedTo ngm:vector-database ;
vc:requires ngm:document-corpus ;
vc:requires ngm:inverted-index ;
vc:requires ngm:knowledge-retrieval ;
vc:requires ngm:natural-language-processing ;
vc:requires ngm:neural-network-text-tokenisation ;
vc:requires ngm:tokenization ;
vc:slug "bm25" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:beir-benchmark ;
vc:standardizedBy ngm:sigir-community ;
vc:standardizedBy ngm:trec-evaluation-programme ;
vc:supports ngm:agentic-rag ;
vc:supports ngm:cross-encoder-reranking ;
vc:supports ngm:keyword-search ;
vc:supports ngm:large-language-model ;
vc:supports ngm:reciprocal-rank-fusion ;
vc:supports ngm:vector-database ;
vc:uses ngm:document-retrieval ;
vc:uses ngm:inverted-index ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:neural-network-text-tokenisation ;
vc:uses ngm:tf-idf ;
vc:uses ngm:tokenization .
ngm:bmaltais-kohya-gui a skos:Concept ;
rdfs:label "Bmaltais Kohya Gui"@en .
ngm:bn254-curve a skos:Concept ;
rdfs:label "Bn254 Curve"@en .
ngm:bnb-chain a owl:Class ;
rdfs:comment "A blockchain compatible with the Ethereum Virtual Machine, operated with a delegated Proof-of-Staked-Authority validator set and used widely for decentralised trading, lending, token issuance, and other on-chain applications within the Binance ecosystem."@en ;
rdfs:label "BNB Chain"@en ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf ngm:blockchain-network ;
rdfs:subClassOf _:r2652 ;
rdfs:subClassOf _:r2653 ;
rdfs:subClassOf _:r2654 ;
rdfs:subClassOf _:r2655 ;
rdfs:subClassOf _:r2656 ;
skos:broader ngm:blockchain ;
vc:bridgesTo ngm:binance ;
vc:bridgesTo ngm:decentralised-application ;
vc:bridgesTo ngm:smart-contract ;
vc:bridgesTo ngm:web3 ;
vc:contrastsWith ngm:ethereum ;
vc:contrastsWith ngm:solana ;
vc:dependsOn ngm:binance ;
vc:dependsOn ngm:consensus-mechanism ;
vc:enables ngm:de-fi ;
vc:enables ngm:non-fungible-token ;
vc:enables ngm:token-issuance ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:decentralised-exchange ;
vc:hasPart ngm:smart-contract ;
vc:implements ngm:delegated-proof-of-stake ;
vc:implements ngm:evm-compatibility ;
vc:isPartOf ngm:blockchain ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:cryptocurrency ;
vc:relatedTo ngm:layer-1-blockchain ;
vc:requires ngm:evm ;
vc:requires ngm:proof-of-stake ;
vc:requires ngm:validator-node ;
vc:slug "bnb-chain" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:bnb-token ;
vc:uses ngm:cross-chain-bridge ;
vc:uses ngm:gas-fee .
ngm:bnb-token a skos:Concept ;
rdfs:label "Bnb Token"@en .
ngm:board-level-oversight a owl:Class ;
rdfs:comment "Board-Level Oversight refers to the governance responsibility of a corporate or institutional board of directors to monitor, evaluate, and guide the organisation's strategic direction, risk appetite, executive conduct, and compliance posture. It encompasses the board's duty to act as an informed check on executive management, reviewing material risks—including operational, financial, legal, reputational, and increasingly technology risks such as AI adoption—on behalf of shareholders and other stakeholders."@en ;
rdfs:label "Board-Level Oversight"@en ;
rdfs:subClassOf ngm:governance ;
vc:enables ngm:accountability ;
vc:enables ngm:transparency ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:boardroom ;
vc:relatedTo ngm:compliance ;
vc:relatedTo ngm:governance-framework ;
vc:slug "board-level-oversight" ;
vc:sourceDomain "governance" ;
vc:uses ngm:audit ;
vc:uses ngm:risk-management .
ngm:board-of-directors a skos:Concept ;
rdfs:label "Board Of Directors"@en .
ngm:boardroom a owl:Class ;
rdfs:comment "The Boardroom is the physical or virtual environment in which a company's board of directors convenes to exercise its governance responsibilities, encompassing both the formal meeting space and the institutional setting—including procedures, information flows, and power dynamics—that shape board decision-making. As a governance construct, it represents the apex deliberative forum where strategy, risk, and oversight responsibilities are discharged."@en ;
rdfs:label "Boardroom"@en ;
rdfs:subClassOf ngm:governance ;
rdfs:subClassOf _:r3569 ;
rdfs:subClassOf _:r3570 ;
rdfs:subClassOf _:r3571 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:enables ngm:accountability ;
vc:enables ngm:board-level-oversight ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:audit-committee ;
vc:isPartOf ngm:corporate-governance ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:compliance ;
vc:relatedTo ngm:shareholder-rights ;
vc:relatedTo ngm:stakeholder ;
vc:relatedTo ngm:transparency ;
vc:requires ngm:fiduciary-duty ;
vc:requires ngm:quorum ;
vc:slug "boardroom" ;
vc:sourceDomain "governance" ;
vc:supports ngm:executive-compensation ;
vc:uses ngm:governance-framework ;
vc:uses ngm:risk-management .
ngm:bob-protocol a skos:Concept ;
rdfs:label "Bob Protocol"@en .
ngm:bode-plot a owl:Class ;
rdfs:comment "A Bode Plot is a pair of frequency-domain graphs used in control engineering and signal analysis to characterise the frequency response of a linear time-invariant system: one graph plots the magnitude of the system's transfer function in decibels against log-frequency, and the second plots the phase angle in degrees against log-frequency. Together they reveal gain margins, phase margins, bandwidth, and resonant behaviour, making Bode plots the primary graphical tool for assessing open-loop stability and designing compensators."@en ;
rdfs:label "Bode Plot"@en ;
rdfs:subClassOf ngm:control-system ;
vc:enables ngm:pid-controller ;
vc:enables ngm:stability-analysis ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:feedback-control ;
vc:relatedTo ngm:feedback-loop ;
vc:slug "bode-plot" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:signal-processing ;
vc:uses ngm:transfer-function .
ngm:body-area-network a skos:Concept ;
rdfs:label "Body Area Network"@en .
ngm:body-estimation-networks a skos:Concept ;
rdfs:label "Body Estimation Networks"@en .
ngm:body-prior a skos:Concept ;
rdfs:label "Body Prior"@en .
ngm:body-rig a skos:Concept ;
rdfs:label "Body Rig"@en .
ngm:body-schema a skos:Concept ;
rdfs:label "Body Schema"@en .
ngm:body-segmentation a skos:Concept ;
rdfs:label "Body Segmentation"@en .
ngm:body-shape-models a skos:Concept ;
rdfs:label "Body Shape Models"@en .
ngm:body-tracking a skos:Concept ;
rdfs:label "Body Tracking"@en .
ngm:bokeh-rendering a skos:Concept ;
rdfs:label "Bokeh Rendering"@en .
ngm:bokeh-simulation a skos:Concept ;
rdfs:label "Bokeh Simulation"@en .
ngm:bokolo-cash a skos:Concept ;
rdfs:label "Bokolo Cash"@en .
ngm:bola-algorithm a skos:Concept ;
rdfs:label "Bola Algorithm"@en .
ngm:bold-benchmark a skos:Concept ;
rdfs:label "Bold Benchmark"@en .
ngm:bolt a owl:Class ;
rdfs:comment "BOLT, the Basis of Lightning Technology, is the set of specifications that define how Lightning Network implementations interoperate. The documents cover channels, routing, and messaging."@en ;
rdfs:label "BOLT"@en ;
rdfs:subClassOf ngm:lightning-network ;
rdfs:subClassOf _:r2657 ;
rdfs:subClassOf _:r2658 ;
rdfs:subClassOf _:r2659 ;
rdfs:subClassOf _:r2660 ;
rdfs:subClassOf _:r2661 ;
rdfs:subClassOf _:r2662 ;
rdfs:subClassOf _:r2663 ;
rdfs:subClassOf _:r2664 ;
vc:bridgesTo ngm:cryptographic-protocol ;
vc:bridgesTo ngm:distributed-systems ;
vc:bridgesTo ngm:payment-channel ;
vc:contrastsWith ngm:on-chain-transaction ;
vc:contrastsWith ngm:state-channel ;
vc:enables ngm:bolt-11 ;
vc:enables ngm:bolt12-offers ;
vc:enables ngm:micropayment ;
vc:enables ngm:peer-to-peer-payment ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:bolt-11 ;
vc:hasPart ngm:bolt12-offers ;
vc:hasPart ngm:gossip-protocol ;
vc:hasPart ngm:onion-routing ;
vc:implements ngm:layer-2-protocol ;
vc:implements ngm:payment-channel-network ;
vc:isPartOf ngm:blockchain ;
vc:isPartOf ngm:lightning-network ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:invoice ;
vc:requires ngm:bitcoin ;
vc:requires ngm:hashed-timelock-contract ;
vc:requires ngm:lightning ;
vc:requires ngm:payment-channel ;
vc:slug "bolt" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:lightning-network-specification .
ngm:bolt-11 a owl:Class ;
rdfs:comment "BOLT11 is the Lightning Network specification for the invoice format used to request a single payment. It encodes payment amount, payment hash, description, expiry, and optional routing hints into a bech32-encoded string that the payer scans or pastes to initiate an off-chain payment."@en ;
rdfs:label "BOLT11"@en ;
rdfs:subClassOf ngm:bolt ;
rdfs:subClassOf _:r2665 ;
rdfs:subClassOf _:r2666 ;
rdfs:subClassOf _:r2667 ;
vc:bridgesTo ngm:bolt12-offers ;
vc:bridgesTo ngm:distributed-systems ;
vc:bridgesTo ngm:finance ;
vc:contrastsWith ngm:bolt12-offers ;
vc:contrastsWith ngm:on-chain-transaction ;
vc:dependsOn ngm:bitcoin ;
vc:dependsOn ngm:hash-time-locked-contract ;
vc:dependsOn ngm:payment-channel ;
vc:enables ngm:lightning ;
vc:enables ngm:micropayment ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:payment-request ;
vc:isPartOf ngm:lightning-network ;
vc:qualityScore "0.72"^^xsd:float ;
vc:requires ngm:bolt ;
vc:requires ngm:lightning-network ;
vc:requires ngm:payment-preimage ;
vc:slug "bolt-11" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:lightning-network-specification ;
vc:supports ngm:point-of-sale ;
vc:supports ngm:qr-code ;
vc:uses ngm:secp256k1 ;
vc:uses ngm:sha-256 .
ngm:bolt-12 a owl:Class ;
rdfs:comment "BOLT12 is a Lightning Network specification that defines offers, a reusable payment request format that improves on single-use invoices. It supports recurring and static payment requests, onion messaging for invoice fetching, and improved privacy through blinded paths."@en ;
rdfs:label "BOLT12"@en ;
rdfs:subClassOf ngm:bolt ;
rdfs:subClassOf _:r2668 ;
rdfs:subClassOf _:r2669 ;
rdfs:subClassOf _:r2670 ;
vc:bridgesTo ngm:bolt-11 ;
vc:bridgesTo ngm:de-fi ;
vc:bridgesTo ngm:digital-identity ;
vc:contrastsWith ngm:bolt-11 ;
vc:contrastsWith ngm:payment-request ;
vc:dependsOn ngm:bitcoin ;
vc:dependsOn ngm:payment-channel ;
vc:enables ngm:phoenix ;
vc:enables ngm:privacy-preserving ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:lightning-network-specification ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:invoice ;
vc:relatedTo ngm:payment-protocol ;
vc:requires ngm:bolt ;
vc:requires ngm:lightning-network ;
vc:requires ngm:onion-routing ;
vc:slug "bolt-12" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:lightning-network-specification ;
vc:supports ngm:micropayment ;
vc:uses ngm:tlv-encoding .
ngm:bolt-specifications a owl:Class ;
rdfs:comment "The BOLT (Basis of Lightning Technology) specifications are the open, community-maintained set of documents defining the Lightning Network protocol, covering peer messaging, channel establishment and closure, commitment transactions, onion-routed payments, and invoice formats. By specifying the wire protocol and behaviour precisely, BOLTs ensure that independently developed Lightning implementations interoperate on a single payment network layered atop Bitcoin. They are the normative reference that makes the Lightning Network a multi-implementation open standard rather than a single product."@en ;
rdfs:label "BOLT Specifications"@en ;
rdfs:subClassOf ngm:technical-standard ;
vc:enables ngm:interoperability ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol ;
vc:relatedTo ngm:lightning-network ;
vc:slug "bolt-specifications" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:network-protocol .
ngm:bolt11-invoice a skos:Concept ;
rdfs:label "Bolt11 Invoice"@en .
ngm:bolt12-offers a owl:Class ;
rdfs:comment "BOLT12 Offers is a Lightning Network specification defining reusable, static payment requests called offers, improving on single-use BOLT11 invoices. An offer is a long-lived, shareable code from which payers fetch a fresh invoice on demand via onion messages, enabling recurring payments, refunds, and donation links without a server issuing each invoice. It also improves privacy through blinded paths that hide the recipient's node identity."@en ;
rdfs:label "BOLT12 Offers"@en ;
rdfs:subClassOf ngm:lightning-network ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:lightning-network ;
vc:slug "bolt12-offers" ;
vc:sourceDomain "blockchain" .
ngm:boltzmann-distribution a skos:Concept ;
rdfs:label "Boltzmann Distribution"@en .
ngm:boltzmann-exploration a skos:Concept ;
rdfs:label "Boltzmann Exploration"@en .
ngm:bonded-stake a skos:Concept ;
rdfs:label "Bonded Stake"@en .
ngm:bonding a skos:Concept ;
rdfs:label "Bonding"@en .
ngm:bonding-mechanism a skos:Concept ;
rdfs:label "Bonding Mechanism"@en .
ngm:booking-agents a skos:Concept ;
rdfs:label "Booking Agents"@en .
ngm:boolean-algebra a skos:Concept ;
rdfs:label "Boolean Algebra"@en .
ngm:boolean-circuit a skos:Concept ;
rdfs:label "Boolean Circuit"@en .
ngm:boolean-logic a skos:Concept ;
rdfs:label "Boolean Logic"@en .
ngm:boolean-retrieval a skos:Concept ;
rdfs:label "Boolean Retrieval"@en .
ngm:boolean-satisfiability a skos:Concept ;
rdfs:label "Boolean Satisfiability"@en .
ngm:boolean-search a skos:Concept ;
rdfs:label "Boolean Search"@en .
ngm:boosting a owl:Class ;
rdfs:comment "A sequential ensemble learning technique that combines multiple weak learners into a strong predictor by iteratively training each new model to correct the errors of its predecessors. Instance weights are adjusted after each round so that misclassified examples receive more attention; the final prediction is a weighted vote across all weak learners. Key algorithms include AdaBoost, Gradient Boosting, XGBoost, LightGBM, and CatBoost."@en ;
rdfs:label "Boosting"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:ensemble-methods ;
rdfs:subClassOf _:r3572 ;
rdfs:subClassOf _:r3573 ;
skos:broader ngm:ai-technique ;
vc:contrastsWith ngm:deep-learning ;
vc:enables ngm:overfitting ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:requires ngm:machine-learning-discipline ;
vc:requires ngm:training-data ;
vc:slug "boosting" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:gradient-descent ;
vc:uses ngm:regularisation .
ngm:bootloader a skos:Concept ;
rdfs:label "Bootloader"@en .
ngm:bootstrap a skos:Concept ;
rdfs:label "Bootstrap"@en .
ngm:bootstrap-node a owl:Class ;
rdfs:comment "A Bootstrap Node is a well-known, stable network entry point that newly joining peers contact to obtain their initial list of active participants in a peer-to-peer blockchain network. By providing a curated, long-lived set of peer addresses, bootstrap nodes solve the cold-start problem: without them a new client would have no means of discovering the network. They do not typically validate or store blocks themselves; their function is purely topological—seeding new participants into the gossip network so that subsequent peer discovery can proceed organically."@en ;
rdfs:label "Bootstrap Node"@en ;
rdfs:subClassOf ngm:blockchain-entity ;
rdfs:subClassOf _:r3574 ;
rdfs:subClassOf _:r3575 ;
vc:enables ngm:blockchain-network ;
vc:enables ngm:peer-to-peer-network ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:blockchain-infrastructure ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:full-node ;
vc:relatedTo ngm:gossip-protocol ;
vc:relatedTo ngm:light-node ;
vc:relatedTo ngm:validator-node ;
vc:requires ngm:cryptographic-protocol ;
vc:requires ngm:distributed-system ;
vc:slug "bootstrap-node" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:blockchain-scalability .
ngm:bootstrap-protocol a skos:Concept ;
rdfs:label "Bootstrap Protocol"@en .
ngm:bootstrap-resampling a skos:Concept ;
rdfs:label "Bootstrap Resampling"@en .
ngm:bootstrapfewshot a skos:Concept ;
rdfs:label "Bootstrapfewshot"@en .
ngm:bop-benchmark a skos:Concept ;
rdfs:label "Bop Benchmark"@en .
ngm:border-control a skos:Concept ;
rdfs:label "Border Control"@en .
ngm:bossware a skos:Concept ;
rdfs:label "Bossware"@en .
ngm:boston-dynamics-atlas a skos:Concept ;
rdfs:label "Boston Dynamics Atlas"@en .
ngm:boston-dynamics-bigdog a skos:Concept ;
rdfs:label "Boston Dynamics Bigdog"@en .
ngm:boston-dynamics-spot a owl:Class ;
rdfs:comment "Spot is a quadruped mobile robot developed by Boston Dynamics, designed for inspection and data collection across varied terrain."@en ;
rdfs:label "Boston Dynamics Spot"@en ;
rdfs:subClassOf ngm:mobile-robotics ;
rdfs:subClassOf ngm:robo-robot-type ;
rdfs:subClassOf _:r3576 ;
rdfs:subClassOf _:r3577 ;
skos:broader ngm:robo-robot-type ;
vc:bridgesTo ngm:sensors ;
vc:enables ngm:robot-perception ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:legged-locomotion ;
vc:requires ngm:slam ;
vc:slug "boston-dynamics-spot" ;
vc:sourceDomain "robotics" .
ngm:bot-detection a skos:Concept ;
rdfs:label "Bot Detection"@en .
ngm:bot-management a skos:Concept ;
rdfs:label "Bot Management"@en .
ngm:bot-marketplaces a skos:Concept ;
rdfs:label "Bot Marketplaces"@en .
ngm:bot-orchestration a skos:Concept ;
rdfs:label "Bot Orchestration"@en .
ngm:bot-prevention a skos:Concept ;
rdfs:label "Bot Prevention"@en .
ngm:bot-traffic a skos:Concept ;
rdfs:label "Bot Traffic"@en .
ngm:botorch a skos:Concept ;
rdfs:label "Botorch"@en .
ngm:bouncy-particle-sampler a skos:Concept ;
rdfs:label "Bouncy Particle Sampler"@en .
ngm:boundary-definition a skos:Concept ;
rdfs:label "Boundary Definition"@en .
ngm:boundary-setting a skos:Concept ;
rdfs:label "Boundary Setting"@en .
ngm:boundary-value-problem a skos:Concept ;
rdfs:label "Boundary Value Problem"@en .
ngm:bounded-rationality a owl:Class ;
rdfs:comment "Bounded rationality is the principle that decision-makers are constrained by limited information, finite cognitive resources and time pressure, and therefore seek satisfactory rather than optimal outcomes. It contrasts with the idealised fully rational agent of classical economics and informs models of human and artificial decision behaviour. The concept grounds heuristics, satisficing and resource-rational approaches to reasoning."@en ;
rdfs:label "Bounded Rationality"@en ;
rdfs:subClassOf ngm:behavioural-economics ;
rdfs:subClassOf ngm:cognitive-science ;
rdfs:subClassOf ngm:decision-making ;
rdfs:subClassOf _:r3578 ;
rdfs:subClassOf _:r3579 ;
rdfs:subClassOf _:r3580 ;
rdfs:subClassOf _:r3581 ;
rdfs:subClassOf _:r3582 ;
rdfs:subClassOf _:r3583 ;
vc:bridgesTo ngm:ai-ethics ;
vc:bridgesTo ngm:ai-safety ;
vc:bridgesTo ngm:behavioural-economics ;
vc:bridgesTo ngm:choice-architecture ;
vc:bridgesTo ngm:governance ;
vc:bridgesTo ngm:human-computer-interaction ;
vc:contrastsWith ngm:bayesian-decision-theory ;
vc:contrastsWith ngm:expected-utility-theory ;
vc:contrastsWith ngm:homo-economicus ;
vc:contrastsWith ngm:optimisation ;
vc:contrastsWith ngm:rational-choice-theory ;
vc:dependsOn ngm:cognitive-constraints ;
vc:dependsOn ngm:probability-theory ;
vc:dependsOn ngm:uncertainty-quantification ;
vc:dependsOn ngm:working-memory ;
vc:enables ngm:agent-based-modelling ;
vc:enables ngm:autonomous-agent ;
vc:enables ngm:decision-support ;
vc:enables ngm:llm-alignment ;
vc:enables ngm:nudge-theory ;
vc:enables ngm:planning ;
vc:enables ngm:reinforcement-learning ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:adaptive-toolbox ;
vc:hasPart ngm:aspiration-level ;
vc:hasPart ngm:cognitive-constraints ;
vc:hasPart ngm:fast-and-frugal-heuristics ;
vc:hasPart ngm:heuristics ;
vc:hasPart ngm:information-asymmetry ;
vc:hasPart ngm:satisficing ;
vc:implements ngm:approximate-inference ;
vc:implements ngm:fast-and-frugal-heuristics ;
vc:implements ngm:resource-rational-computation ;
vc:implements ngm:satisficing ;
vc:isPartOf ngm:behavioural-economics ;
vc:isPartOf ngm:decision-making ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:cognitive-science ;
vc:relatedTo ngm:dual-process-theory ;
vc:relatedTo ngm:economics ;
vc:relatedTo ngm:knowledge-representation ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:markov-decision-process ;
vc:relatedTo ngm:neuroscience ;
vc:relatedTo ngm:operations-research ;
vc:relatedTo ngm:prospect-theory ;
vc:relatedTo ngm:reinforcement-learning ;
vc:relatedTo ngm:risk-assessment ;
vc:relatedTo ngm:utility-theory ;
vc:requires ngm:cognitive-science ;
vc:requires ngm:probability-theory ;
vc:requires ngm:reasoning ;
vc:requires ngm:uncertainty-quantification ;
vc:slug "bounded-rationality" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:iso-31000 ;
vc:supports ngm:ai-alignment ;
vc:supports ngm:ai-ethics ;
vc:supports ngm:autonomous-agent ;
vc:supports ngm:behavioural-economics ;
vc:supports ngm:decision-support ;
vc:supports ngm:public-policy ;
vc:uses ngm:game-theory ;
vc:uses ngm:markov-decision-process ;
vc:uses ngm:monte-carlo-tree-search ;
vc:uses ngm:probability-theory ;
vc:uses ngm:reasoning ;
vc:uses ngm:utility-theory .
ngm:bounding-box a skos:Concept ;
rdfs:label "Bounding Box"@en .
ngm:bounding-box-regression a owl:Class ;
rdfs:comment "Bounding Box Regression is the supervised learning task within object detection of predicting the precise coordinates of axis-aligned rectangular boxes that tightly enclose detected objects. A model outputs four continuous values — typically centre x, centre y, width, and height relative to an anchor — and is trained using smooth-L1 or IoU-based loss functions that penalise deviation from ground-truth boxes. It is jointly trained with an object classification head and combined with [[Non Maximum Suppression]] to produce the final detections. Accurate regression is critical for downstream tasks such as instance segmentation and 3-D pose estimation that consume the predicted boxes."@en ;
rdfs:label "Bounding Box Regression"@en ;
rdfs:subClassOf ngm:computer-vision-task ;
rdfs:subClassOf ngm:object-detection ;
rdfs:subClassOf ngm:regression ;
rdfs:subClassOf ngm:supervised-learning ;
rdfs:subClassOf _:r3584 ;
rdfs:subClassOf _:r3585 ;
rdfs:subClassOf _:r3586 ;
rdfs:subClassOf _:r3587 ;
rdfs:subClassOf _:r3588 ;
rdfs:subClassOf _:r3589 ;
rdfs:subClassOf _:r3590 ;
rdfs:subClassOf _:r3591 ;
rdfs:subClassOf _:r3592 ;
rdfs:subClassOf _:r3593 ;
rdfs:subClassOf _:r3594 ;
vc:contrastsWith ngm:heatmap-regression ;
vc:contrastsWith ngm:image-classification ;
vc:contrastsWith ngm:panoptic-segmentation ;
vc:contrastsWith ngm:regression-testing ;
vc:contrastsWith ngm:semantic-segmentation ;
vc:dependsOn ngm:anchor-assignment ;
vc:dependsOn ngm:backpropagation ;
vc:dependsOn ngm:convolutional-neural-network ;
vc:dependsOn ngm:gradient-descent ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:training-data ;
vc:dependsOn ngm:transfer-learning ;
vc:enables ngm:3d-object-detection ;
vc:enables ngm:augmented-reality ;
vc:enables ngm:autonomous-driving ;
vc:enables ngm:computer-vision-system ;
vc:enables ngm:instance-segmentation ;
vc:enables ngm:object-detection-and-tracking ;
vc:enables ngm:panoptic-segmentation ;
vc:enables ngm:pose-estimation ;
vc:enables ngm:scene-understanding ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:anchor-box ;
vc:hasPart ngm:ciou-loss ;
vc:hasPart ngm:feature-pyramid-network ;
vc:hasPart ngm:giou-loss ;
vc:hasPart ngm:heatmap-regression ;
vc:hasPart ngm:iou-loss ;
vc:hasPart ngm:non-maximum-suppression ;
vc:hasPart ngm:regression-head ;
vc:hasPart ngm:roi-pooling ;
vc:implements ngm:localisation ;
vc:implements ngm:object-detection ;
vc:implements ngm:region-proposal-network ;
vc:implements ngm:spatial-localisation ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:bounding-volume ;
vc:relatedTo ngm:bounding-volume-hierarchy ;
vc:relatedTo ngm:centernet ;
vc:relatedTo ngm:deep-learning ;
vc:relatedTo ngm:detr ;
vc:relatedTo ngm:faster-r-cnn ;
vc:relatedTo ngm:fcos ;
vc:relatedTo ngm:gaussian-process-regression ;
vc:relatedTo ngm:image-classification ;
vc:relatedTo ngm:neural-network ;
vc:relatedTo ngm:retinanet ;
vc:relatedTo ngm:semantic-segmentation ;
vc:relatedTo ngm:ssd ;
vc:relatedTo ngm:transfer-learning ;
vc:relatedTo ngm:yolo ;
vc:requires ngm:benchmark-dataset ;
vc:requires ngm:computer-vision ;
vc:requires ngm:deep-learning ;
vc:requires ngm:gpu-computing ;
vc:requires ngm:loss-function ;
vc:requires ngm:regression ;
vc:requires ngm:training-data ;
vc:slug "bounding-box-regression" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:coco-dataset ;
vc:standardizedBy ngm:nuscenes ;
vc:standardizedBy ngm:open-images ;
vc:standardizedBy ngm:pascal-voc ;
vc:standardizedBy ngm:waymo-open-dataset ;
vc:supports ngm:augmented-reality ;
vc:supports ngm:autonomous-driving-perception ;
vc:supports ngm:industrial-inspection ;
vc:supports ngm:medical-image-analysis ;
vc:supports ngm:real-time-ai ;
vc:supports ngm:real-time-ai-inference ;
vc:supports ngm:robotics-perception ;
vc:uses ngm:attention-mechanism ;
vc:uses ngm:bipartite-matching ;
vc:uses ngm:computer-vision-task ;
vc:uses ngm:feature-pyramid-network ;
vc:uses ngm:gradient-descent ;
vc:uses ngm:regression ;
vc:uses ngm:stochastic-gradient-descent ;
vc:uses ngm:transformer-architecture .
ngm:bounding-volume a owl:Class ;
rdfs:comment "A Bounding Volume is a simple geometric shape—typically a sphere, axis-aligned bounding box (AABB), oriented bounding box (OBB), or convex hull—that encloses a more complex geometric object or set of objects. By testing intersections or containment against the bounding volume rather than the full geometry, real-time rendering engines, physics simulators, and spatial query systems achieve orders-of-magnitude speedups during broad-phase culling and collision detection."@en ;
rdfs:label "Bounding Volume"@en ;
rdfs:subClassOf ngm:spatial-data-structure ;
rdfs:subClassOf _:r3597 ;
vc:enables ngm:collision-detection ;
vc:enables ngm:frustum-culling ;
vc:enables ngm:occlusion-culling ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:bounding-volume-hierarchy ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:scene-graph ;
vc:relatedTo ngm:spatial-index ;
vc:slug "bounding-volume" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:physics-simulation ;
vc:uses ngm:real-time-rendering .
ngm:bounding-volume-hierarchy a owl:Class ;
rdfs:comment "A tree-structured acceleration data structure that recursively organizes geometric objects within nested bounding volumes, enabling efficient spatial queries, collision detection, and ray-scene intersection testing by rapidly culling large portions of geometry that cannot intersect with a query."@en ;
rdfs:label "Bounding Volume Hierarchy"@en ;
rdfs:subClassOf ngm:sc-display-and-rendering ;
rdfs:subClassOf ngm:spatial-data-structure ;
rdfs:subClassOf _:r3595 ;
rdfs:subClassOf _:r3596 ;
skos:broader ngm:sc-display-and-rendering ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:bridgesTo ngm:robotics ;
vc:bridgesTo ngm:spatial-data-structure ;
vc:contrastsWith ngm:kd-tree ;
vc:contrastsWith ngm:octree-spatial-index ;
vc:contrastsWith ngm:uniform-grid ;
vc:dependsOn ngm:geometric-primitive ;
vc:dependsOn ngm:scene-graph ;
vc:enables ngm:collision-detection ;
vc:enables ngm:frustum-culling ;
vc:enables ngm:global-illumination ;
vc:enables ngm:occlusion-culling ;
vc:enables ngm:ray-tracing ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:bounding-volume ;
vc:hasPart ngm:internal-node ;
vc:hasPart ngm:leaf-node ;
vc:implements ngm:spatial-partitioning ;
vc:isPartOf ngm:rendering-pipeline ;
vc:isPartOf ngm:spatial-data-structure ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:gpu-acceleration ;
vc:relatedTo ngm:neural-radiance-field ;
vc:requires ngm:bounding-volume ;
vc:requires ngm:traversal-algorithm ;
vc:requires ngm:tree-construction ;
vc:slug "bounding-volume-hierarchy" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:physics-simulation ;
vc:supports ngm:real-time-rendering ;
vc:supports ngm:virtual-reality ;
vc:uses ngm:depth-first-search ;
vc:uses ngm:surface-area-heuristic .
ngm:bow-shock a owl:Class ;
rdfs:label "Bow Shock"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:heliophysics ;
vc:slug "bow-shock" ;
vc:sourceDomain "space-science-and-systems" .
ngm:bow-tie-analysis a skos:Concept ;
rdfs:label "Bow Tie Analysis"@en .
ngm:box2-d a skos:Concept ;
rdfs:label "Box2 D"@en .
ngm:box2d a skos:Concept ;
rdfs:label "Box2d"@en .
ngm:bpe-vocabulary a skos:Concept ;
rdfs:label "Bpe Vocabulary"@en .
ngm:bpmn a skos:Concept ;
rdfs:label "Bpmn"@en .
ngm:bpmn-orchestration a skos:Concept ;
rdfs:label "Bpmn Orchestration"@en .
ngm:bpmn-standard a skos:Concept ;
rdfs:label "Bpmn Standard"@en .
ngm:bradford a skos:Concept ;
rdfs:label "Bradford"@en .
ngm:bradley-terry-aggregation a skos:Concept ;
rdfs:label "Bradley Terry Aggregation"@en .
ngm:bradley-terry-model a owl:Class ;
rdfs:comment "The Bradley-Terry model is a probabilistic model for paired comparisons that estimates a latent strength or quality score for each item and predicts the probability that one item beats another via the logistic of their score difference. Fitted by maximum-likelihood from observed comparison outcomes, it produces a global ranking from local pairwise data. In machine learning it underpins preference modelling and reward learning from human comparisons."@en ;
rdfs:label "Bradley Terry Model"@en ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf ngm:probabilistic-model ;
rdfs:subClassOf ngm:reward-modelling ;
rdfs:subClassOf ngm:statistical-model ;
rdfs:subClassOf _:r3598 ;
rdfs:subClassOf _:r3599 ;
rdfs:subClassOf _:r3600 ;
rdfs:subClassOf _:r3601 ;
vc:bridgesTo ngm:constitutional-ai-training-methodology ;
vc:bridgesTo ngm:dpo ;
vc:bridgesTo ngm:ipo ;
vc:bridgesTo ngm:rlaif ;
vc:bridgesTo ngm:rlhf ;
vc:bridgesTo ngm:simpo ;
vc:contrastsWith ngm:elo-rating-system ;
vc:contrastsWith ngm:identity-preference-optimisation ;
vc:contrastsWith ngm:kahneman-tversky-optimisation ;
vc:contrastsWith ngm:plackett-luce-model ;
vc:contrastsWith ngm:thurstone-model ;
vc:contrastsWith ngm:trueskill ;
vc:dependsOn ngm:convex-optimisation ;
vc:dependsOn ngm:iterative-scaling ;
vc:dependsOn ngm:logistic-regression ;
vc:dependsOn ngm:maximum-likelihood-estimation ;
vc:dependsOn ngm:newton-raphson-method ;
vc:enables ngm:ai-alignment ;
vc:enables ngm:crowdsourcing-aggregation ;
vc:enables ngm:direct-preference-optimisation ;
vc:enables ngm:human-preference-ranking ;
vc:enables ngm:llm-evaluation ;
vc:enables ngm:reward-model ;
vc:enables ngm:sports-ranking ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:comparison-outcome-matrix ;
vc:hasPart ngm:latent-strength-parameter ;
vc:hasPart ngm:log-likelihood-function ;
vc:hasPart ngm:logistic-function ;
vc:hasPart ngm:pairwise-comparison ;
vc:hasPart ngm:strength-parameter-vector ;
vc:implements ngm:choice-model ;
vc:implements ngm:paired-comparison-model ;
vc:implements ngm:preference-learning ;
vc:implements ngm:ranking-algorithm ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:bayesian-inference ;
vc:relatedTo ngm:crowdsourcing ;
vc:relatedTo ngm:discrete-choice-model ;
vc:relatedTo ngm:human-feedback ;
vc:relatedTo ngm:logistic-regression ;
vc:relatedTo ngm:luce-choice-axiom ;
vc:relatedTo ngm:preference-learning ;
vc:relatedTo ngm:probabilistic-model ;
vc:relatedTo ngm:sports-ranking ;
vc:relatedTo ngm:statistical-model ;
vc:requires ngm:connected-comparison-graph ;
vc:requires ngm:maximum-likelihood-estimation ;
vc:requires ngm:optimisation ;
vc:requires ngm:pairwise-comparison ;
vc:slug "bradley-terry-model" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:biometrika ;
vc:standardizedBy ngm:icml ;
vc:standardizedBy ngm:neur-ips ;
vc:supports ngm:constitutional-ai-training-methodology ;
vc:supports ngm:process-reward-model ;
vc:supports ngm:reinforcement-learning-from-human-feedback ;
vc:supports ngm:reward-model ;
vc:supports ngm:rlhf ;
vc:uses ngm:convex-optimisation ;
vc:uses ngm:iterative-scaling ;
vc:uses ngm:logistic-function ;
vc:uses ngm:maximum-likelihood-estimation ;
vc:uses ngm:newton-raphson-method ;
vc:uses ngm:pairwise-comparison .
ngm:brain-computer-interface a skos:Concept ;
rdfs:label "Brain Computer Interface"@en .
ngm:brain-computer-interfaces a owl:Class ;
rdfs:comment "Brain-Computer Interfaces (BCIs), also termed brain-machine interfaces (BMIs) or direct neural interfaces, are biomedical and neurotechnological systems establishing a direct, real-time bidirectional or unidirectional communication channel between the central nervous system (predominantly the cer..."@en ;
rdfs:label "Brain Computer Interfaces"@en ;
rdfs:subClassOf ngm:assistive-technology ;
rdfs:subClassOf ngm:biomedical-device ;
rdfs:subClassOf ngm:human-computer-interface ;
rdfs:subClassOf ngm:infra-computing-and-cloud ;
rdfs:subClassOf ngm:neural-interface ;
rdfs:subClassOf ngm:neuroprosthetic-system ;
rdfs:subClassOf _:r3602 ;
rdfs:subClassOf _:r3603 ;
rdfs:subClassOf _:r3604 ;
rdfs:subClassOf _:r3605 ;
rdfs:subClassOf _:r3606 ;
rdfs:subClassOf _:r3607 ;
rdfs:subClassOf _:r3608 ;
rdfs:subClassOf _:r3609 ;
rdfs:subClassOf _:r3610 ;
rdfs:subClassOf _:r3611 ;
rdfs:subClassOf _:r3612 ;
skos:broader ngm:infra-computing-and-cloud ;
vc:bridgesTo ngm:assistive-technology ;
vc:bridgesTo ngm:governance ;
vc:contrastsWith ngm:emg-wristband ;
vc:contrastsWith ngm:eye-tracking ;
vc:contrastsWith ngm:keyboard ;
vc:contrastsWith ngm:mouse ;
vc:contrastsWith ngm:peripheral-nerve-interface ;
vc:contrastsWith ngm:spinal-cord-stimulator ;
vc:contrastsWith ngm:voice-recognition ;
vc:dependsOn ngm:biocompatible-engineering ;
vc:dependsOn ngm:computational-neuroscience ;
vc:dependsOn ngm:electrophysiology ;
vc:dependsOn ngm:information-theory ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:neuroscience ;
vc:dependsOn ngm:signal-processing ;
vc:dependsOn ngm:surgical-robotics ;
vc:enables ngm:closed-loop-neuromodulation ;
vc:enables ngm:cognitive-augmentation ;
vc:enables ngm:communication-for-locked-in-patients ;
vc:enables ngm:direct-neural-control ;
vc:enables ngm:motor-restoration ;
vc:enables ngm:neurofeedback-therapy ;
vc:enables ngm:sensory-restoration ;
vc:enables ngm:speech-restoration ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:analog-to-digital-converter ;
vc:hasPart ngm:battery-or-inductive-power-link ;
vc:hasPart ngm:biocompatible-encapsulation ;
vc:hasPart ngm:microelectrode-array ;
vc:hasPart ngm:neural-decoder ;
vc:hasPart ngm:signal-amplifier ;
vc:hasPart ngm:spike-sorter ;
vc:hasPart ngm:stimulation-driver ;
vc:hasPart ngm:surgical-robot ;
vc:hasPart ngm:wireless-telemetry-module ;
vc:implements ngm:action-potential-recording ;
vc:implements ngm:closed-loop-control ;
vc:implements ngm:electrocorticography ;
vc:implements ngm:electroencephalography ;
vc:implements ngm:functional-near-infrared-spectroscopy ;
vc:implements ngm:intracortical-microstimulation ;
vc:implements ngm:local-field-potential-recording ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:ai-agent-system ;
vc:relatedTo ngm:augmented-reality ;
vc:relatedTo ngm:cognitive-enhancement ;
vc:relatedTo ngm:cyborg ;
vc:relatedTo ngm:neuromodulation ;
vc:relatedTo ngm:neuroprosthetics ;
vc:relatedTo ngm:neurorights ;
vc:relatedTo ngm:wearable-computing ;
vc:requires ngm:biocompatible-materials ;
vc:requires ngm:clinical-trials ;
vc:requires ngm:informed-consent ;
vc:requires ngm:low-noise-analog-electronics ;
vc:requires ngm:machine-learning ;
vc:requires ngm:machine-learning-discipline ;
vc:requires ngm:neurosurgical-procedure ;
vc:requires ngm:real-time-computing ;
vc:requires ngm:regulatory-approval ;
vc:slug "brain-computer-interfaces" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:bci-society ;
vc:standardizedBy ngm:eu-medical-device-regulation ;
vc:standardizedBy ngm:fda-bci-guidance-2021 ;
vc:standardizedBy ngm:ieee-2731 ;
vc:standardizedBy ngm:ieee-3209 ;
vc:standardizedBy ngm:iso-14708-active-implantable-medical-devices ;
vc:standardizedBy ngm:unesco-neurotech-recommendation ;
vc:supports ngm:als-communication ;
vc:supports ngm:locked-in-syndrome-communication ;
vc:supports ngm:parkinson-s-disease-treatment ;
vc:supports ngm:refractory-epilepsy-treatment ;
vc:supports ngm:spinal-cord-injury-recovery ;
vc:supports ngm:stroke-rehabilitation ;
vc:supports ngm:tetraplegia-rehabilitation ;
vc:supports ngm:treatment-resistant-depression ;
vc:uses ngm:common-spatial-patterns ;
vc:uses ngm:independent-component-analysis ;
vc:uses ngm:kalman-filter ;
vc:uses ngm:linear-discriminant-analysis ;
vc:uses ngm:recurrent-neural-network ;
vc:uses ngm:riemannian-geometry ;
vc:uses ngm:state-space-model ;
vc:uses ngm:transformer-architecture ;
vc:uses ngm:wiener-filter .
ngm:branch-and-bound a owl:Class ;
rdfs:comment "An exact algorithmic paradigm for combinatorial optimisation that systematically explores a tree of candidate solution subsets, using bounds from relaxations of the problem to prune any branch that provably cannot contain a solution better than the best one found so far. Introduced by Land and Doig in 1960 for integer programming, branch and bound guarantees optimality while often avoiding exhaustive enumeration, and remains the backbone of modern mixed-integer programming and constraint solvers."@en ;
rdfs:label "Branch and Bound"@en ;
rdfs:subClassOf ngm:search-algorithm ;
vc:contrastsWith ngm:dynamic-programming ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:combinatorial-optimisation ;
vc:isPartOf ngm:constraint-solver ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:constraint-satisfaction ;
vc:slug "branch-and-bound" ;
vc:sourceDomain "artificial-intelligence" .
ngm:branching-path a skos:Concept ;
rdfs:label "Branching Path"@en .
ngm:branching-strategy a skos:Concept ;
rdfs:label "Branching Strategy"@en .
ngm:brand-asset-generation a skos:Concept ;
rdfs:label "Brand Asset Generation"@en .
ngm:brand-asset-management a skos:Concept ;
rdfs:label "Brand Asset Management"@en .
ngm:brand-engagement a skos:Concept ;
rdfs:label "Brand Engagement"@en .
ngm:brand-guidelines a skos:Concept ;
rdfs:label "Brand Guidelines"@en .
ngm:brand-identity a owl:Class ;
rdfs:comment "Brand identity is the collection of visible and conceptual elements through which an organisation presents itself and is recognised, including its name, logo, colour palette, typography, voice, and the values it communicates. It is the deliberately constructed expression of a brand that aims to shape how audiences perceive and remember it, distinguishing it from competitors. A coherent brand identity aligns visual design, messaging, and behaviour so that experiences across channels reinforce a consistent and trusted impression."@en ;
rdfs:label "Brand Identity"@en ;
rdfs:subClassOf ngm:digital-marketing ;
rdfs:subClassOf _:r3613 ;
vc:bridgesTo ngm:digital-economy ;
vc:enables ngm:storytelling ;
vc:enables ngm:trust ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:digital-marketing ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:customer-experience ;
vc:relatedTo ngm:digital-economy ;
vc:relatedTo ngm:digital-marketing ;
vc:relatedTo ngm:storytelling ;
vc:relatedTo ngm:user-experience ;
vc:requires ngm:user-experience ;
vc:slug "brand-identity" ;
vc:sourceDomain "data" ;
vc:supports ngm:digital-marketing ;
vc:supports ngm:user-experience ;
vc:uses ngm:content-creation ;
vc:uses ngm:storytelling .
ngm:brand-loyalty-nfts a skos:Concept ;
rdfs:label "Brand Loyalty Nfts"@en .
ngm:brand-management a skos:Concept ;
rdfs:label "Brand Management"@en .
ngm:brax a skos:Concept ;
rdfs:label "Brax"@en .
ngm:brazil-ai-bill-pl-2338 a skos:Concept ;
rdfs:label "Brazil AI Bill Pl 2338"@en .
ngm:brc-20 a owl:Class ;
rdfs:comment "BRC-20 is an experimental fungible token standard on the Bitcoin blockchain that encodes deploy, mint, and transfer operations as JSON-formatted Ordinals inscriptions written onto individual satoshis. Token balances are not enforced by Bitcoin consensus rules but are instead computed off-chain by indexers that parse inscription data in sequential ordinal order. Proposed by the pseudonymous developer @domo in March 2023, BRC-20 was the first widely adopted approach to creating transferable fungible tokens natively on Bitcoin without requiring a sidechain or layer-2 network. Its simplicity and permissionless nature drove rapid experimentation but also exposed limitations around scalability, indexer consensus, and on-chain fee pressure."@en ;
rdfs:label "BRC-20"@en ;
rdfs:subClassOf ngm:token-standard ;
rdfs:subClassOf _:r2671 ;
rdfs:subClassOf _:r2672 ;
rdfs:subClassOf _:r2673 ;
rdfs:subClassOf _:r2674 ;
vc:bridgesTo ngm:de-fi ;
vc:bridgesTo ngm:neural-network-text-tokenisation ;
vc:bridgesTo ngm:tokenization ;
vc:contrastsWith ngm:erc-20-token-standard ;
vc:contrastsWith ngm:runes-protocol ;
vc:contrastsWith ngm:spl-token ;
vc:contrastsWith ngm:src-20 ;
vc:dependsOn ngm:bitcoin-node ;
vc:dependsOn ngm:ordinals-indexer ;
vc:enables ngm:decentralised-exchange ;
vc:enables ngm:fungible-token ;
vc:enables ngm:minting ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:isPartOf ngm:bitcoin ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:bitcoin-script ;
vc:relatedTo ngm:digital-asset ;
vc:relatedTo ngm:layer-2-protocol ;
vc:relatedTo ngm:mempool ;
vc:relatedTo ngm:non-fungible-token ;
vc:requires ngm:bitcoin-proof-of-work-protocol ;
vc:requires ngm:ordinals ;
vc:requires ngm:seg-wit ;
vc:requires ngm:taproot ;
vc:slug "brc-20" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:inscription ;
vc:uses ngm:json-data-interchange-format ;
vc:uses ngm:satoshi ;
vc:uses ngm:utxo-model .
ngm:brc-20-tokens a skos:Concept ;
rdfs:label "Brc 20 Tokens"@en .
ngm:brdf a owl:Class ;
rdfs:comment "A Bidirectional Reflectance Distribution Function (BRDF) is a function that defines how light is reflected at an opaque surface, giving the ratio of reflected radiance to incident irradiance for each pair of incoming and outgoing directions. It encodes material appearance such as diffuse, glossy, and specular behaviour and is the core of physically based shading. Renderers evaluate the BRDF at surface intersections to compute realistic light transport."@en ;
rdfs:label "BRDF"@en ;
rdfs:subClassOf ngm:rendering-technique ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:ray-tracing ;
vc:slug "brdf" ;
vc:sourceDomain "metaverse" .
ngm:breach-containment a skos:Concept ;
rdfs:label "Breach Containment"@en .
ngm:breach-detection a skos:Concept ;
rdfs:label "Breach Detection"@en .
ngm:breach-notification a skos:Concept ;
rdfs:label "Breach Notification"@en .
ngm:breach-of-duty a skos:Concept ;
rdfs:label "Breach Of Duty"@en .
ngm:breadth-first-search a owl:Class ;
rdfs:comment "Breadth-first search (BFS) is a graph and tree traversal algorithm that explores all neighbours of a node before moving to nodes at the next depth level, expanding the search frontier in order of increasing distance from the source. It is implemented with a first-in-first-out queue and, on unweighted graphs, finds the shortest path in terms of edge count from the start vertex to every reachable vertex. BFS runs in time linear in the number of vertices and edges and is foundational to pathfinding, connectivity analysis and level-order processing."@en ;
rdfs:label "Breadth-First Search"@en ;
rdfs:subClassOf ngm:graph-algorithms ;
rdfs:subClassOf ngm:graph-search ;
rdfs:subClassOf ngm:search-algorithm ;
rdfs:subClassOf ngm:uninformed-search ;
rdfs:subClassOf _:r3614 ;
rdfs:subClassOf _:r3615 ;
vc:contrastsWith ngm:a-star-algorithm ;
vc:contrastsWith ngm:beam-search-decoding ;
vc:contrastsWith ngm:depth-first-search ;
vc:contrastsWith ngm:dijkstra-algorithm ;
vc:contrastsWith ngm:greedy-best-first-search ;
vc:contrastsWith ngm:iterative-deepening-dfs ;
vc:dependsOn ngm:adjacency-list ;
vc:dependsOn ngm:graph-representation ;
vc:dependsOn ngm:graph-theory ;
vc:dependsOn ngm:queue-data-structure ;
vc:dependsOn ngm:visited-set ;
vc:enables ngm:bipartite-graph-detection ;
vc:enables ngm:connected-components ;
vc:enables ngm:level-order-traversal ;
vc:enables ngm:path-planning ;
vc:enables ngm:pathfinding ;
vc:enables ngm:reachability-analysis ;
vc:enables ngm:social-network-analysis ;
vc:enables ngm:topological-sort ;
vc:enables ngm:web-crawling ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:adjacency-representation ;
vc:hasPart ngm:distance-array ;
vc:hasPart ngm:frontier ;
vc:hasPart ngm:parent-pointer-array ;
vc:hasPart ngm:queue-data-structure ;
vc:hasPart ngm:visited-set ;
vc:implements ngm:complete-search ;
vc:implements ngm:graph-search ;
vc:implements ngm:level-order-traversal ;
vc:implements ngm:search-algorithm ;
vc:implements ngm:uninformed-search ;
vc:isPartOf ngm:graph-algorithms ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:ai-search ;
vc:relatedTo ngm:beam-search ;
vc:relatedTo ngm:computer-science ;
vc:relatedTo ngm:dijkstra-algorithm ;
vc:relatedTo ngm:graph-neural-network ;
vc:relatedTo ngm:monte-carlo-tree-search ;
vc:relatedTo ngm:node ;
vc:relatedTo ngm:path-planning ;
vc:relatedTo ngm:pathfinding ;
vc:relatedTo ngm:search-algorithms ;
vc:relatedTo ngm:state-space-search ;
vc:requires ngm:adjacency-list ;
vc:requires ngm:data-structure ;
vc:requires ngm:graph-theory ;
vc:requires ngm:queue-data-structure ;
vc:requires ngm:visited-marker ;
vc:slug "breadth-first-search" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:clrs-introduction-to-algorithms ;
vc:standardizedBy ngm:knuth-art-of-computer-programming ;
vc:supports ngm:a-star-algorithm ;
vc:supports ngm:beam-search ;
vc:supports ngm:dijkstra-algorithm ;
vc:supports ngm:hopcroft-karp-algorithm ;
vc:supports ngm:kahn-algorithm ;
vc:supports ngm:network-flow ;
vc:supports ngm:prim-algorithm ;
vc:uses ngm:adjacency-representation ;
vc:uses ngm:algorithm ;
vc:uses ngm:bfs-tree ;
vc:uses ngm:graph-theory ;
vc:uses ngm:queue-data-structure .
ngm:breakout-board a skos:Concept ;
rdfs:label "Breakout Board"@en .
ngm:breakout-room a owl:Class ;
rdfs:comment "Breakout rooms are temporary, parallel sub-session spaces embedded within a primary virtual meeting or conferencing environment that partition a large group of participants into smaller, purpose-bounded clusters for focused collaborative work, deliberation, or learning activities, enabling concur..."@en ;
rdfs:label "Breakout Room"@en ;
rdfs:subClassOf ngm:collaborative-learning-infrastructure ;
rdfs:subClassOf ngm:dc-communication ;
rdfs:subClassOf ngm:group-facilitation-tools ;
rdfs:subClassOf ngm:remote-work-technology ;
rdfs:subClassOf ngm:synchronous-communication ;
rdfs:subClassOf ngm:virtual-meeting-structure ;
rdfs:subClassOf _:r3616 ;
rdfs:subClassOf _:r3617 ;
rdfs:subClassOf _:r3618 ;
rdfs:subClassOf _:r3619 ;
skos:broader ngm:dc-communication ;
vc:contrastsWith ngm:asynchronous-discussion-forum ;
vc:contrastsWith ngm:broadcast-webinar ;
vc:contrastsWith ngm:plenary-session ;
vc:contrastsWith ngm:town-hall-meeting ;
vc:dependsOn ngm:cloud-infrastructure ;
vc:dependsOn ngm:real-time-communication-protocol ;
vc:dependsOn ngm:session-layer-protocol ;
vc:dependsOn ngm:videoconferencing-platform ;
vc:dependsOn ngm:web-rtc ;
vc:enables ngm:cooperative-learning ;
vc:enables ngm:cross-functional-team-collaboration ;
vc:enables ngm:focused-sub-team-discussions ;
vc:enables ngm:parallel-problem-solving ;
vc:enables ngm:participation-equity ;
vc:enables ngm:scaled-workshop-facilitation ;
vc:enables ngm:think-pair-share-pedagogy ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ai-group-formation ;
vc:hasPart ngm:automatic-grouping ;
vc:hasPart ngm:host-broadcast-channel ;
vc:hasPart ngm:manual-room-assignment ;
vc:hasPart ngm:participant-assignment-interface ;
vc:hasPart ngm:return-to-main-signalling ;
vc:hasPart ngm:room-level-recording ;
vc:hasPart ngm:room-state-tracking ;
vc:hasPart ngm:timer-and-notifications ;
vc:implements ngm:active-learning ;
vc:implements ngm:fishbowl-dialogue ;
vc:implements ngm:flipped-classroom ;
vc:implements ngm:jigsaw-cooperative-learning ;
vc:implements ngm:problem-based-learning ;
vc:implements ngm:think-pair-share ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:active-learning ;
vc:relatedTo ngm:collaborative-systems-modality-whiteboard ;
vc:relatedTo ngm:cooperative-learning ;
vc:relatedTo ngm:fishbowl-dialogue ;
vc:relatedTo ngm:flipped-classroom ;
vc:relatedTo ngm:ieee-802-11 ;
vc:relatedTo ngm:ietf-rfc-3550-rtp ;
vc:relatedTo ngm:iso-iec-25010-software-quality ;
vc:relatedTo ngm:jigsaw-cooperative-learning ;
vc:relatedTo ngm:learning-management-system ;
vc:relatedTo ngm:meeting-ai-assistant ;
vc:relatedTo ngm:peer-learning ;
vc:relatedTo ngm:presence-indicator ;
vc:relatedTo ngm:problem-based-learning ;
vc:relatedTo ngm:team-communication-platform ;
vc:relatedTo ngm:think-pair-share ;
vc:relatedTo ngm:virtual-event-platform ;
vc:relatedTo ngm:web-rtc-w-3-c-specification ;
vc:requires ngm:hosting-privileges ;
vc:requires ngm:media-routing-infrastructure ;
vc:requires ngm:multiple-concurrent-video-streams ;
vc:requires ngm:room-state-tracking ;
vc:requires ngm:session-multiplexing ;
vc:requires ngm:user-identity-management ;
vc:slug "breakout-room" ;
vc:sourceDomain "distributed-collaboration" ;
vc:standardizedBy ngm:ieee-802-11 ;
vc:standardizedBy ngm:ietf-rfc-3550-rtp ;
vc:standardizedBy ngm:web-rtc-w-3-c-specification ;
vc:supports ngm:conference-facilitation ;
vc:supports ngm:corporate-training ;
vc:supports ngm:distributed-team-collaboration ;
vc:supports ngm:hackathon-events ;
vc:supports ngm:remote-education ;
vc:supports ngm:virtual-workshop ;
vc:uses ngm:ai-group-formation ;
vc:uses ngm:collaborative-systems-modality-whiteboard ;
vc:uses ngm:instant-messaging ;
vc:uses ngm:meeting-ai-assistant ;
vc:uses ngm:presence-indicator ;
vc:uses ngm:screen-sharing .
ngm:breez a owl:Class ;
rdfs:comment "Breez is a company and open-source platform providing a non-custodial [[Lightning Network]] wallet and a [[Software Development Kit]] (SDK) that enables developers to embed Bitcoin Lightning payments into applications without managing node infrastructure. Breez operates as a Lightning Service Provider (LSP), handling inbound liquidity and channel management on behalf of users while users retain sole custody of their private keys. The Breez SDK abstracts away the complexity of [[Payment Channel]] lifecycle management, splicing, and [[Liquidity]] provisioning, exposing a clean API for instant, low-fee Bitcoin payments. Its architecture is grounded in the [[LNURL]] protocol suite and [[Greenlight]] node-as-a-service infrastructure from Blockstream."@en ;
rdfs:label "Breez"@en ;
rdfs:subClassOf ngm:lightning-network ;
rdfs:subClassOf _:r3620 ;
rdfs:subClassOf _:r3621 ;
rdfs:subClassOf _:r3622 ;
vc:bridgesTo ngm:de-fi ;
vc:bridgesTo ngm:open-banking ;
vc:contrastsWith ngm:custodial-wallet ;
vc:contrastsWith ngm:strike ;
vc:dependsOn ngm:bitcoin ;
vc:dependsOn ngm:lightning-network ;
vc:enables ngm:instant-payment ;
vc:enables ngm:non-custodial-wallet ;
vc:enables ngm:self-custody ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:just-in-time-liquidity ;
vc:implements ngm:lightning-service-provider ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:core-lightning ;
vc:relatedTo ngm:lnd ;
vc:relatedTo ngm:phoenix-wallet ;
vc:requires ngm:bitcoin ;
vc:requires ngm:liquidity ;
vc:requires ngm:payment-channel ;
vc:slug "breez" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:bolt-11 ;
vc:uses ngm:bolt12-offers ;
vc:uses ngm:greenlight ;
vc:uses ngm:lnurl ;
vc:uses ngm:submarine-swap .
ngm:bretton-woods-system a skos:Concept ;
rdfs:label "Bretton Woods System"@en .
ngm:brevity-penalty a skos:Concept ;
rdfs:label "Brevity Penalty"@en .
ngm:bribe-economy a skos:Concept ;
rdfs:label "Bribe Economy"@en .
ngm:bribe-market a skos:Concept ;
rdfs:label "Bribe Market"@en .
ngm:bribery-market a skos:Concept ;
rdfs:label "Bribery Market"@en .
ngm:brics-payment-system a skos:Concept ;
rdfs:label "Brics Payment System"@en .
ngm:bridge a owl:Class ;
rdfs:comment "A protocol that transfers assets or messages between separate ledgers by locking, burning, or attesting value on one chain and reproducing a representation on another."@en ;
rdfs:label "Bridge"@en ;
rdfs:subClassOf ngm:blockchain-interoperability ;
rdfs:subClassOf _:r3623 ;
rdfs:subClassOf _:r3624 ;
rdfs:subClassOf _:r3625 ;
rdfs:subClassOf _:r3626 ;
rdfs:subClassOf _:r3627 ;
rdfs:subClassOf _:r3628 ;
vc:bridgesTo ngm:cross-chain-bridge ;
vc:bridgesTo ngm:cross-chain-messaging ;
vc:bridgesTo ngm:interoperability-protocol ;
vc:contrastsWith ngm:atomic-swap ;
vc:contrastsWith ngm:rollup ;
vc:dependsOn ngm:consensus-mechanism ;
vc:dependsOn ngm:finality ;
vc:enables ngm:cross-chain-asset-transfer ;
vc:enables ngm:cross-chain-messaging ;
vc:enables ngm:de-fi ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:lock-and-mint-mechanism ;
vc:hasPart ngm:relayer ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:trusted-bridge ;
vc:relatedTo ngm:trustless-bridge ;
vc:requires ngm:cryptographic-proof ;
vc:requires ngm:oracle ;
vc:requires ngm:smart-contract ;
vc:requires ngm:validator-set ;
vc:slug "bridge" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:decentralised-exchange ;
vc:supports ngm:liquidity-pool ;
vc:uses ngm:hash-time-locked-contract ;
vc:uses ngm:multi-signature ;
vc:uses ngm:zero-knowledge-proof .
ngm:bridge-contract a owl:Class ;
rdfs:comment "A Bridge Contract is a smart contract deployed on one or more blockchain networks that facilitates the transfer of tokens, messages, or state between two separate chains by locking or burning assets on the source chain and minting or releasing equivalent assets on the destination chain. Bridge contracts are the on-chain components of cross-chain bridge protocols, enforcing custody, verifying cryptographic proofs of source-chain events, and coordinating with off-chain relayers or decentralised oracle networks."@en ;
rdfs:label "Bridge Contract"@en ;
rdfs:subClassOf ngm:smart-contract ;
vc:enables ngm:cross-chain-asset-transfer ;
vc:enables ngm:cross-chain-bridge ;
vc:enables ngm:wrapped-token ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:cross-chain-interoperability ;
vc:relatedTo ngm:layer-2-scaling ;
vc:relatedTo ngm:sidechain ;
vc:slug "bridge-contract" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:cryptographic-hash ;
vc:uses ngm:relayer .
ngm:bridge-protocol a skos:Concept ;
rdfs:label "Bridge Protocol"@en .
ngm:bright-id a owl:Class ;
rdfs:comment "BrightID is a decentralised social identity network that establishes the uniqueness of human participants by analysing the topology of a peer-to-peer social connection graph, without collecting personally identifying information. Each user creates an account identified solely by a public key, then builds mutual verification links with trusted contacts; graph-analysis algorithms infer whether an account corresponds to a distinct human rather than a bot or duplicate. The system provides applications with a binary or graded uniqueness signal usable for Sybil-resistant resource allocation, quadratic voting, and universal basic income distribution without requiring biometric data or a central identity authority."@en ;
rdfs:label "BrightID"@en ;
rdfs:subClassOf ngm:digital-identity ;
rdfs:subClassOf _:r3629 ;
rdfs:subClassOf _:r3630 ;
rdfs:subClassOf _:r3631 ;
rdfs:subClassOf _:r3632 ;
vc:bridgesTo ngm:federated-learning ;
vc:bridgesTo ngm:privacy-preserving-computation ;
vc:bridgesTo ngm:reputation-system ;
vc:contrastsWith ngm:biometric-identity ;
vc:contrastsWith ngm:centralised-identity ;
vc:contrastsWith ngm:sybil-attack ;
vc:enables ngm:decentralised-governance ;
vc:enables ngm:quadratic-voting ;
vc:enables ngm:sybil-resistance ;
vc:enables ngm:universal-basic-income ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:airdrop ;
vc:relatedTo ngm:decentralised-identifier ;
vc:relatedTo ngm:proof-of-personhood ;
vc:relatedTo ngm:self-sovereign-identity ;
vc:relatedTo ngm:token-distribution ;
vc:relatedTo ngm:web-of-trust ;
vc:requires ngm:peer-to-peer-network ;
vc:requires ngm:public-key-cryptography ;
vc:requires ngm:social-network-graph ;
vc:slug "bright-id" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:decentralised-application ;
vc:uses ngm:graph-analytics ;
vc:uses ngm:zero-knowledge-proof .
ngm:brightness-temperature a owl:Class ;
rdfs:label "Brightness Temperature"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-processing ;
vc:slug "brightness-temperature" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:bristol-robotics-laboratory a skos:Concept ;
rdfs:label "Bristol Robotics Laboratory"@en .
ngm:british-computer-society a skos:Concept ;
rdfs:label "British Computer Society"@en .
ngm:british-psychological-society a skos:Concept ;
rdfs:label "British Psychological Society"@en .
ngm:broad-phase-detection a skos:Concept ;
rdfs:label "Broad Phase Detection"@en .
ngm:broadband-connectivity a owl:Class ;
rdfs:comment "Broadband Connectivity is high-capacity, always-on access to the internet delivered over fixed or wireless infrastructure such as fibre, cable, DSL, or cellular networks, characterised by data rates substantially higher than legacy dial-up. It provides the underlying transport for digital services, remote work, streaming, cloud applications, and the Internet of Things. Universal broadband is treated as essential infrastructure, and disparities in its availability constitute the digital divide. Its delivery depends on telecommunications infrastructure, network protocols, and last-mile access technologies."@en ;
rdfs:label "Broadband Connectivity"@en ;
rdfs:subClassOf ngm:network-infrastructure ;
rdfs:subClassOf _:r3633 ;
rdfs:subClassOf _:r3634 ;
rdfs:subClassOf _:r3635 ;
vc:contrastsWith ngm:digital-divide ;
vc:dependsOn ngm:network-infrastructure ;
vc:dependsOn ngm:telecommunications ;
vc:enables ngm:edge-computing ;
vc:enables ngm:internet-of-things ;
vc:enables ngm:smart-city ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:ip-addressing ;
vc:hasPart ngm:routing-protocol ;
vc:isPartOf ngm:network-infrastructure ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:dns ;
vc:requires ngm:network-protocol ;
vc:slug "broadband-connectivity" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:digital-infrastructure ;
vc:supports ngm:urban-computing ;
vc:uses ngm:internet-protocol ;
vc:uses ngm:packet-switching ;
vc:uses ngm:tcp-ip .
ngm:broadband-infrastructure a skos:Concept ;
rdfs:label "Broadband Infrastructure"@en .
ngm:broadband-internet a skos:Concept ;
rdfs:label "Broadband Internet"@en .
ngm:broadband-network a skos:Concept ;
rdfs:label "Broadband Network"@en .
ngm:broadcast-media a skos:Concept ;
rdfs:label "Broadcast Media"@en .
ngm:broadcast-production a owl:Class ;
rdfs:comment "Broadcast Production is the end-to-end process of creating, processing, and distributing audio-visual content for transmission to audiences over television, radio, or internet broadcast channels, encompassing pre-production planning, live or recorded acquisition, signal processing, editing, graphics integration, encoding, and playout to distribution networks. It operates under stringent real-time constraints and technical quality standards defined by regulatory and industry bodies."@en ;
rdfs:label "Broadcast Production"@en ;
rdfs:subClassOf ngm:production-pipeline ;
vc:enables ngm:cdn ;
vc:enables ngm:video-streaming ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:asset-management ;
vc:relatedTo ngm:audio-processing ;
vc:relatedTo ngm:latency ;
vc:slug "broadcast-production" ;
vc:sourceDomain "metaverse" ;
vc:uses ngm:encoder ;
vc:uses ngm:signal-processing ;
vc:uses ngm:video-codec ;
vc:uses ngm:video-encoding .
ngm:broadcast-television a owl:Class ;
rdfs:comment "Broadcast television is the distribution of moving-image and audio content to a general audience over terrestrial, satellite, or cable channels, in which a single signal is transmitted simultaneously to many passive receivers. It evolved from analogue standards such as PAL and NTSC to digital systems like DVB and ATSC that carry compressed video over the same spectrum. As a one-to-many medium with scheduled programming, it contrasts with on-demand internet streaming."@en ;
rdfs:label "Broadcast Television"@en ;
rdfs:subClassOf ngm:infra-network-and-comms ;
rdfs:subClassOf ngm:infrastructure ;
rdfs:subClassOf _:r3636 ;
rdfs:subClassOf _:r3637 ;
rdfs:subClassOf _:r3638 ;
rdfs:subClassOf _:r3639 ;
skos:broader ngm:infra-network-and-comms ;
skos:broader ngm:infrastructure ;
vc:bridgesTo ngm:entropy-coding ;
vc:contrastsWith ngm:metaverse ;
vc:dependsOn ngm:hevc ;
vc:dependsOn ngm:video-compression ;
vc:enables ngm:bitrate ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:signal-processing ;
vc:hasPart ngm:video-codec ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:bitrate ;
vc:relatedTo ngm:codec ;
vc:relatedTo ngm:motion-estimation ;
vc:requires ngm:infrastructure ;
vc:requires ngm:video-compression ;
vc:slug "broadcast-television" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:standards ;
vc:supports ngm:standards ;
vc:uses ngm:signal-processing ;
vc:uses ngm:video-codec ;
vc:uses ngm:video-compression .
ngm:broadcast-webinar a skos:Concept ;
rdfs:label "Broadcast Webinar"@en .
ngm:broadcasting a owl:Class ;
rdfs:comment "The one-to-many distribution of a signal or message from a single source to all receivers within reach, in contrast to unicast (one-to-one) and multicast (one-to-selected-group) delivery. In telecommunications it denotes terrestrial and satellite radio and television transmission over allocated spectrum, and by extension the broadcast primitives of computer networks, where a frame or packet is addressed to every node on a segment. The same word names a distinct but analogous mechanism in array computing, where NumPy-style broadcasting stretches arrays of differing shapes to a common shape so that element-wise operations apply one value across many without copying data."@en ;
rdfs:label "Broadcasting"@en ;
rdfs:subClassOf ngm:telecommunications ;
vc:dependsOn ngm:spectrum-allocation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:numpy ;
vc:relatedTo ngm:satellite-communication ;
vc:slug "broadcasting" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:wireless-communication .
ngm:broader-user-base a skos:Concept ;
rdfs:label "Broader User Base"@en .
ngm:broker-dealer-registration a skos:Concept ;
rdfs:label "Broker Dealer Registration"@en .
ngm:brokerage-account-bitcoin-access a skos:Concept ;
rdfs:label "Brokerage Account Bitcoin Access"@en .
ngm:brown-conrady-distortion-model a skos:Concept ;
rdfs:label "Brown Conrady Distortion Model"@en .
ngm:brown-dwarf a owl:Class ;
rdfs:label "Brown Dwarf"@en ;
rdfs:subClassOf ngm:astronomical-body ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:stellar-astrophysics ;
vc:slug "brown-dwarf" ;
vc:sourceDomain "space-science-and-systems" .
ngm:brownian-motion a skos:Concept ;
rdfs:label "Brownian Motion"@en .
ngm:brownie a skos:Concept ;
rdfs:label "Brownie"@en .
ngm:browser-agents a skos:Concept ;
rdfs:label "Browser Agents"@en .
ngm:browser-automation a owl:Class ;
rdfs:comment "Browser Automation is the programmatic control of web browsers to execute tasks—navigation, form submission, data extraction, and UI interaction—without direct human input. It spans a spectrum from low-level Chrome DevTools Protocol (CDP) scripting and WebDriver-based frameworks to high-level tools such as Playwright and Puppeteer, as well as AI-driven computer-use agents that perceive and act upon rendered page content. Browser automation underpins modern software testing pipelines, robotic process automation, and agentic AI workflows that must interact with web-based services. The field has evolved rapidly with the emergence of large language model agents capable of interpreting visual page state and generating action sequences autonomously."@en ;
rdfs:label "Browser Automation"@en ;
rdfs:subClassOf ngm:process-automation ;
rdfs:subClassOf ngm:software-engineering ;
rdfs:subClassOf ngm:workflow-automation ;
rdfs:subClassOf _:r3640 ;
rdfs:subClassOf _:r3641 ;
rdfs:subClassOf _:r3642 ;
rdfs:subClassOf _:r3643 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:security ;
vc:contrastsWith ngm:api-testing ;
vc:contrastsWith ngm:manual-testing ;
vc:contrastsWith ngm:mobile-automation ;
vc:contrastsWith ngm:static-analysis ;
vc:contrastsWith ngm:unit-testing ;
vc:dependsOn ngm:browser-engine ;
vc:dependsOn ngm:dom-api ;
vc:dependsOn ngm:infrastructure ;
vc:dependsOn ngm:java-script ;
vc:dependsOn ngm:operating-system ;
vc:enables ngm:accessibility-audit-tool ;
vc:enables ngm:agentic-workflow ;
vc:enables ngm:continuous-integration ;
vc:enables ngm:customer-service-automation ;
vc:enables ngm:data-pipeline ;
vc:enables ngm:end-to-end-testing ;
vc:enables ngm:performance-testing ;
vc:enables ngm:regression-testing ;
vc:enables ngm:robotic-process-automation ;
vc:enables ngm:software-testing ;
vc:enables ngm:testing-infrastructure ;
vc:enables ngm:web-scraping ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:accessibility-tree ;
vc:hasPart ngm:browser-context ;
vc:hasPart ngm:chrome-devtools-protocol ;
vc:hasPart ngm:css-selectors ;
vc:hasPart ngm:headless-browser ;
vc:hasPart ngm:playwright ;
vc:hasPart ngm:puppeteer ;
vc:hasPart ngm:selenium ;
vc:hasPart ngm:selenium-grid ;
vc:hasPart ngm:webdriver-bidi ;
vc:hasPart ngm:xpath ;
vc:implements ngm:chrome-devtools-protocol ;
vc:implements ngm:http-protocol ;
vc:implements ngm:w3c-webdriver-standard ;
vc:implements ngm:web-socket-protocol ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:bot-detection ;
vc:relatedTo ngm:captcha ;
vc:relatedTo ngm:computer-use ;
vc:relatedTo ngm:computer-use-and-browser-agents ;
vc:relatedTo ngm:continuous-delivery ;
vc:relatedTo ngm:devops ;
vc:relatedTo ngm:headless-browser ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:model-context-protocol ;
vc:relatedTo ngm:robotic-process-automation ;
vc:relatedTo ngm:security ;
vc:relatedTo ngm:software-testing ;
vc:relatedTo ngm:web-scraping ;
vc:requires ngm:browser-engine ;
vc:requires ngm:dom-api ;
vc:requires ngm:javascript-runtime ;
vc:requires ngm:network-protocol ;
vc:requires ngm:web-browser ;
vc:slug "browser-automation" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:ieee ;
vc:standardizedBy ngm:w3-c ;
vc:standardizedBy ngm:whatwg ;
vc:supports ngm:accessibility-audit-tool ;
vc:supports ngm:adversarial-testing ;
vc:supports ngm:end-to-end-testing ;
vc:supports ngm:industrial-automation ;
vc:supports ngm:regression-testing ;
vc:supports ngm:security-testing ;
vc:supports ngm:visual-regression-testing ;
vc:uses ngm:accessibility-tree ;
vc:uses ngm:css-selectors ;
vc:uses ngm:dom-api ;
vc:uses ngm:http-protocol ;
vc:uses ngm:java-script ;
vc:uses ngm:model-context-protocol ;
vc:uses ngm:testing-process ;
vc:uses ngm:web-socket-protocol ;
vc:uses ngm:xpath .
ngm:browser-based-games a skos:Concept ;
rdfs:label "Browser Based Games"@en .
ngm:browser-based-screen-capture a owl:Class ;
rdfs:comment "Browser-based screen capture is the in-browser acquisition of screen, window, or tab video using web APIs such as the Screen Capture API (getDisplayMedia), without installing native software. The captured MediaStream can be recorded locally, encoded, or streamed in real time over WebRTC, making it the foundation for web conferencing, asynchronous video messaging, and screen recording tools. It runs under explicit user permission and within the browser's security sandbox."@en ;
rdfs:label "Browser-Based Screen Capture"@en ;
rdfs:subClassOf ngm:telepresence ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:asynchronous-video ;
vc:relatedTo ngm:screen-recording ;
vc:slug "browser-based-screen-capture" ;
vc:sourceDomain "infrastructure" .
ngm:browser-centric-internet a skos:Concept ;
rdfs:label "Browser Centric Internet"@en .
ngm:browser-context a skos:Concept ;
rdfs:label "Browser Context"@en .
ngm:browser-engine a owl:Class ;
rdfs:comment "A browser engine is the software component that parses and renders web content, implementing the HTML, CSS and JavaScript execution semantics defined by web standards to turn markup and script into an interactive display. Examples include Blink, Gecko and WebKit, each of which independently implements the same standards with varying levels of conformance and performance. Browser engines form the runtime substrate on which web applications, and automated agents that operate a browser, ultimately depend."@en ;
rdfs:label "Browser Engine"@en ;
rdfs:subClassOf ngm:runtime-environment ;
rdfs:subClassOf _:r3644 ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.65"^^xsd:float ;
vc:requires ngm:runtime-environment ;
vc:slug "browser-engine" ;
vc:sourceDomain "standards" .
ngm:browser-graphics-pipeline a skos:Concept ;
rdfs:label "Browser Graphics Pipeline"@en .
ngm:browser-graphics-rendering a skos:Concept ;
rdfs:label "Browser Graphics Rendering"@en .
ngm:browser-plugin a skos:Concept ;
rdfs:label "Browser Plugin"@en .
ngm:browser-rendering-engine a skos:Concept ;
rdfs:label "Browser Rendering Engine"@en .
ngm:browser-runtime a skos:Concept ;
rdfs:label "Browser Runtime"@en .
ngm:brussels-effect a skos:Concept ;
rdfs:label "Brussels Effect"@en .
ngm:brute-force-collision a skos:Concept ;
rdfs:label "Brute Force Collision"@en .
ngm:brute-force-search a skos:Concept ;
rdfs:label "Brute Force Search"@en .
ngm:bs-8878 a skos:Concept ;
rdfs:label "Bs 8878"@en .
ngm:bs-en-iso-9241-210 a skos:Concept ;
rdfs:label "Bs En Iso 9241 210"@en .
ngm:bsi-bs-en-iso-15552-2021 a skos:Concept ;
rdfs:label "Bsi Bs En Iso 15552 2021"@en .
ngm:bsi-design-standards a skos:Concept ;
rdfs:label "Bsi Design Standards"@en .
ngm:bsi-germany a owl:Class ;
rdfs:comment "The Bundesamt für Sicherheit in der Informationstechnik (BSI), or Federal Office for Information Security, is Germany's national authority for cybersecurity, responsible for protecting digital infrastructure, certifying IT products, and developing security standards. It functions as a central advisory, regulatory, and technical body for both public administration and the private sector across Germany and the European Union."@en ;
rdfs:label "BSI Germany"@en ;
rdfs:subClassOf ngm:standards-body ;
vc:enables ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:gdpr ;
vc:relatedTo ngm:information-security ;
vc:relatedTo ngm:iso-27001 ;
vc:slug "bsi-germany" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:cybersecurity-standard ;
vc:supports ngm:data-protection .
ngm:bsi-pas-19668 a skos:Concept ;
rdfs:label "Bsi Pas 19668"@en .
ngm:bsp-tree a skos:Concept ;
rdfs:label "Bsp Tree"@en .
ngm:bt-sport a skos:Concept ;
rdfs:label "Bt Sport"@en .
ngm:btc a owl:Class ;
rdfs:comment "The ticker for bitcoin, the native unit of the Bitcoin network and the first widely adopted decentralised digital currency."@en ;
rdfs:label "BTC"@en ;
rdfs:subClassOf ngm:cryptocurrency ;
rdfs:subClassOf _:r2691 ;
vc:bridgesTo ngm:bitcoin-proof-of-work-protocol ;
vc:bridgesTo ngm:store-of-value ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:bitcoin-proof-of-work-protocol-network ;
vc:slug "btc" ;
vc:sourceDomain "blockchain" .
ngm:btc-layer-3 a owl:Class ;
rdfs:comment "Layer 3 (Bitcoin Layer 3) designates the application-layer stratum of the Bitcoin protocol stack — a collection of protocols, virtual machines, asset-issuance systems, and programmability frameworks constructed atop Layer 2 scaling networks (principally the Lightning Network and emerging"@en ;
rdfs:label "BTC Layer 3"@en ;
rdfs:subClassOf ngm:application-layer-protocol ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf ngm:bitcoin-protocol-stack ;
rdfs:subClassOf ngm:blockchain-scalability-solution ;
rdfs:subClassOf ngm:distributed-ledger-technology ;
rdfs:subClassOf ngm:network-component ;
rdfs:subClassOf ngm:smart-contract-platform ;
rdfs:subClassOf _:r2675 ;
rdfs:subClassOf _:r2676 ;
rdfs:subClassOf _:r2677 ;
rdfs:subClassOf _:r2678 ;
rdfs:subClassOf _:r2679 ;
rdfs:subClassOf _:r2680 ;
rdfs:subClassOf _:r2681 ;
rdfs:subClassOf _:r2682 ;
rdfs:subClassOf _:r2683 ;
rdfs:subClassOf _:r2684 ;
rdfs:subClassOf _:r2685 ;
rdfs:subClassOf _:r2686 ;
rdfs:subClassOf _:r2687 ;
rdfs:subClassOf _:r2688 ;
rdfs:subClassOf _:r2689 ;
rdfs:subClassOf _:r2690 ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:contrastsWith ngm:cardano-smart-contracts ;
vc:contrastsWith ngm:cosmos-ibc ;
vc:contrastsWith ngm:ethereum-layer-2 ;
vc:contrastsWith ngm:ethereum-smart-contract-platform-smart-contracts ;
vc:contrastsWith ngm:polkadot-parachains ;
vc:contrastsWith ngm:solana-programs ;
vc:dependsOn ngm:bitcoin-proof-of-work-protocol ;
vc:dependsOn ngm:bitcoin-script ;
vc:dependsOn ngm:cryptographic-hash-function ;
vc:dependsOn ngm:lightning-network ;
vc:dependsOn ngm:schnorr-signatures ;
vc:dependsOn ngm:seg-wit ;
vc:dependsOn ngm:taproot ;
vc:enables ngm:ai-agent-smart-contracts ;
vc:enables ngm:atomic-swap ;
vc:enables ngm:bitcoin-proof-of-work-protocol-de-fi ;
vc:enables ngm:cross-chain-bridges ;
vc:enables ngm:de-fi ;
vc:enables ngm:non-fungible-token ;
vc:enables ngm:non-fungible-tokens ;
vc:enables ngm:smart-contracts ;
vc:enables ngm:stablecoins-on-bitcoin ;
vc:enables ngm:token-issuance ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:babylon-protocol ;
vc:hasPart ngm:bit-vm ;
vc:hasPart ngm:bob-protocol ;
vc:hasPart ngm:brc-20 ;
vc:hasPart ngm:citrea ;
vc:hasPart ngm:discreet-log-contracts ;
vc:hasPart ngm:merlin-chain ;
vc:hasPart ngm:ordinals ;
vc:hasPart ngm:rgb-protocol ;
vc:hasPart ngm:rootstock ;
vc:hasPart ngm:runes-protocol ;
vc:hasPart ngm:stacks ;
vc:hasPart ngm:taproot-assets ;
vc:implements ngm:client-side-validation ;
vc:implements ngm:fraud-proof ;
vc:implements ngm:mining ;
vc:implements ngm:optimistic-rollup ;
vc:implements ngm:ordinal-theory ;
vc:implements ngm:proof-of-transfer ;
vc:implements ngm:zero-knowledge-rollup ;
vc:qualityScore "0.54"^^xsd:float ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol-standard ;
vc:relatedTo ngm:de-fi-protocol ;
vc:relatedTo ngm:defi-protocols ;
vc:relatedTo ngm:digital-asset-risks ;
vc:relatedTo ngm:layer-2-solutions ;
vc:relatedTo ngm:lightning-network ;
vc:relatedTo ngm:scalability-solutions ;
vc:relatedTo ngm:state-channel ;
vc:requires ngm:bitcoin-proof-of-work-protocol ;
vc:requires ngm:bitcoin-script ;
vc:requires ngm:cryptographic-commitment ;
vc:requires ngm:cryptographic-commitments ;
vc:requires ngm:lightning-network ;
vc:requires ngm:seg-wit ;
vc:requires ngm:taproot ;
vc:requires ngm:utxo-model ;
vc:slug "btc-layer-3" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:bip-341-taproot ;
vc:standardizedBy ngm:bip-342-tapscript ;
vc:standardizedBy ngm:bitcoin-proof-of-work-protocol-improvement-proposals ;
vc:standardizedBy ngm:lightning-network-specification ;
vc:standardizedBy ngm:lnp-bp-standards-association ;
vc:supports ngm:bitcoin-proof-of-work-protocol ;
vc:supports ngm:bitcoin-proof-of-work-protocol-de-fi ;
vc:supports ngm:bitcoin-scalability ;
vc:supports ngm:cross-chain-interoperability ;
vc:supports ngm:financial-privacy ;
vc:supports ngm:programmable-finance ;
vc:supports ngm:stablecoin ;
vc:uses ngm:alu-vm ;
vc:uses ngm:hash-time-locked-contract ;
vc:uses ngm:hash-time-locked-contracts ;
vc:uses ngm:merkle-proof ;
vc:uses ngm:merkle-proofs ;
vc:uses ngm:point-time-locked-contracts ;
vc:uses ngm:schnorr-signature ;
vc:uses ngm:schnorr-signatures ;
vc:uses ngm:taproot ;
vc:uses ngm:utxo ;
vc:uses ngm:zero-knowledge-proof .
ngm:btcpayserver a skos:Concept ;
rdfs:label "Btcpayserver"@en .
ngm:buffer-management a skos:Concept ;
rdfs:label "Buffer Management"@en .
ngm:buffer-manager a skos:Concept ;
rdfs:label "Buffer Manager"@en .
ngm:buffering-only-adaptation a skos:Concept ;
rdfs:label "Buffering Only Adaptation"@en .
ngm:bug-bounty-programme a skos:Concept ;
rdfs:label "Bug Bounty Programme"@en .
ngm:bug-discovery a skos:Concept ;
rdfs:label "Bug Discovery"@en .
ngm:bug-tracking a skos:Concept ;
rdfs:label "Bug Tracking"@en .
ngm:build-automation a skos:Concept ;
rdfs:label "Build Automation"@en .
ngm:build-internally-only-posture a skos:Concept ;
rdfs:label "Build Internally Only Posture"@en .
ngm:build-pipeline a skos:Concept ;
rdfs:label "Build Pipeline"@en .
ngm:build-server a skos:Concept ;
rdfs:label "Build Server"@en .
ngm:build-system a skos:Concept ;
rdfs:label "Build System"@en .
ngm:building-automation a owl:Class ;
rdfs:comment "Building Automation refers to the centralised monitoring and control of a building's mechanical, electrical, and environmental systems — including heating, ventilation, air conditioning, lighting, access control, and fire safety — through networked sensor-actuator architectures and programmable control logic. It aims to optimise occupant comfort, reduce energy consumption, and enable remote facility management via integrated software platforms."@en ;
rdfs:label "Building Automation"@en ;
rdfs:subClassOf ngm:industrial-automation ;
vc:enables ngm:digital-twin ;
vc:enables ngm:energy-management ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:access-control-system ;
vc:slug "building-automation" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:actuators ;
vc:uses ngm:embedded-systems ;
vc:uses ngm:zigbee .
ngm:building-information-modelling a owl:Class ;
rdfs:comment "Building Information Modelling (BIM) is a collaborative process for creating and managing a shared digital representation of the physical and functional characteristics of a built asset across its lifecycle. A BIM model is an object-oriented, parametric 3D database in which geometry is enriched with semantic data such as materials, costs, schedules and performance properties. It supports coordinated design, clash detection, quantity take-off and facility management by allowing architects, engineers and contractors to work against a single federated source of truth. BIM underpins the convergence of construction practice with digital twin and spatial computing technologies."@en ;
rdfs:label "Building Information Modelling"@en ;
rdfs:subClassOf ngm:digital-twin ;
rdfs:subClassOf ngm:spatial-computing ;
rdfs:subClassOf _:r3645 ;
rdfs:subClassOf _:r3646 ;
skos:broader ngm:spatial-computing ;
vc:bridgesTo ngm:geographic-information-system ;
vc:dependsOn ngm:interoperability ;
vc:enables ngm:digital-twin-technology ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:point-cloud ;
vc:isPartOf ngm:digital-twin ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:photogrammetry ;
vc:relatedTo ngm:point-cloud ;
vc:relatedTo ngm:spatial-computing ;
vc:requires ngm:interoperability ;
vc:slug "building-information-modelling" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:standards ;
vc:supports ngm:digital-twin ;
vc:uses ngm:lidar ;
vc:uses ngm:photogrammetry .
ngm:building-lifecycle-management a skos:Concept ;
rdfs:label "Building Lifecycle Management"@en .
ngm:buildroot a skos:Concept ;
rdfs:label "Buildroot"@en .
ngm:built-environment a skos:Concept ;
rdfs:label "Built Environment"@en .
ngm:bulk-material a skos:Concept ;
rdfs:label "Bulk Material"@en .
ngm:bulk-modulus a skos:Concept ;
rdfs:label "Bulk Modulus"@en .
ngm:bulk-synchronous-parallel a skos:Concept ;
rdfs:label "Bulk Synchronous Parallel"@en .
ngm:bulkhead-pattern a skos:Concept ;
rdfs:label "Bulkhead Pattern"@en .
ngm:bullet-physics a owl:Class ;
rdfs:comment "Bullet Physics is an open-source, real-time physics simulation library that provides collision detection, rigid body dynamics, and soft body simulation for use in games, robotics, visual effects, and scientific computing. Originally developed by Erwin Coumans, it implements discrete and continuous collision detection alongside a constraint solver, enabling physically plausible interactions between complex 3D geometries at interactive frame rates."@en ;
rdfs:label "Bullet Physics"@en ;
rdfs:subClassOf ngm:physics-engine ;
vc:enables ngm:fluid-simulation ;
vc:enables ngm:rigid-body-dynamics ;
vc:enables ngm:soft-body-dynamics ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:game-development ;
vc:relatedTo ngm:game-engine ;
vc:slug "bullet-physics" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:collision-detection ;
vc:uses ngm:constraint-solver .
ngm:bulletproof a skos:Concept ;
rdfs:label "Bulletproof"@en .
ngm:bulletproofs a owl:Class ;
rdfs:comment "Bulletproofs are a class of short, non-interactive zero-knowledge proof system that enables efficient range proofs and arbitrary arithmetic circuit satisfiability without a trusted setup. Based on the discrete logarithm assumption over elliptic curves, they produce logarithmically-sized proofs that can be aggregated and batched, making them particularly well-suited to confidential transaction systems in public blockchains where proof size and verification cost are critical constraints."@en ;
rdfs:label "Bulletproofs"@en ;
rdfs:subClassOf ngm:zero-knowledge-proof ;
rdfs:subClassOf _:r3647 ;
vc:bridgesTo ngm:distributed-systems ;
vc:bridgesTo ngm:security ;
vc:contrastsWith ngm:groth-16 ;
vc:contrastsWith ngm:zk-snark ;
vc:contrastsWith ngm:zk-starks ;
vc:enables ngm:batch-verification ;
vc:enables ngm:confidential-transactions ;
vc:enables ngm:cryptographic-proof ;
vc:enables ngm:privacy-preserving-computation ;
vc:enables ngm:range-proof ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:non-interactive-proof ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:multi-party-computation ;
vc:relatedTo ngm:privacy-preserving-blockchain ;
vc:relatedTo ngm:proof-aggregation ;
vc:requires ngm:computational-hardness-assumption ;
vc:slug "bulletproofs" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:de-fi ;
vc:supports ngm:monero ;
vc:uses ngm:commitment-scheme ;
vc:uses ngm:elliptic-curve-cryptography ;
vc:uses ngm:fiat-shamir-transform ;
vc:uses ngm:pedersen-commitment ;
vc:uses ngm:schnorr-signature .
ngm:bump-mapping a skos:Concept ;
rdfs:label "Bump Mapping"@en .
ngm:bundle-adjustment a owl:Class ;
rdfs:comment "Bundle adjustment is a non-linear least-squares optimisation technique in computer vision and photogrammetry that simultaneously refines estimates of 3-D structure (point cloud positions) and camera parameters (extrinsics and intrinsics) so that reprojected 3-D points best match their observed 2-D image locations across all views. The name derives from the bundle of light rays connecting each camera centre to visible scene points; optimising the geometry tightens these bundles. It is the gold-standard global refinement step in structure-from-motion pipelines, visual SLAM, and aerial photogrammetry, producing metrically accurate 3-D reconstructions from overlapping images or video frames. Computationally it exploits the sparse block structure of the Jacobian via Schur complement elimination and is typically solved with the Levenberg-Marquardt algorithm."@en ;
rdfs:label "Bundle Adjustment"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf _:r3648 ;
rdfs:subClassOf _:r3649 ;
rdfs:subClassOf _:r3650 ;
rdfs:subClassOf _:r3651 ;
rdfs:subClassOf _:r3652 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:augmented-reality ;
vc:bridgesTo ngm:autonomous-vehicle ;
vc:contrastsWith ngm:3-d-reconstruction ;
vc:contrastsWith ngm:pose-graph ;
vc:enables ngm:3-d-reconstruction ;
vc:enables ngm:map-building ;
vc:enables ngm:photogrammetry ;
vc:enables ngm:point-cloud ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:levenberg-marquardt-algorithm ;
vc:hasPart ngm:reprojection-error ;
vc:hasPart ngm:schur-complement-elimination ;
vc:isPartOf ngm:structure-from-motion ;
vc:isPartOf ngm:visual-slam ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:camera-pose-estimation ;
vc:relatedTo ngm:epipolar-geometry ;
vc:relatedTo ngm:simultaneous-localisation-and-mapping ;
vc:requires ngm:camera-calibration ;
vc:requires ngm:feature-extraction ;
vc:requires ngm:feature-matching ;
vc:requires ngm:ransac ;
vc:slug "bundle-adjustment" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:ceres-solver ;
vc:uses ngm:sift-features ;
vc:uses ngm:sparse-matrix .
ngm:bundler a skos:Concept ;
rdfs:label "Bundler"@en .
ngm:bundler-network a skos:Concept ;
rdfs:label "Bundler Network"@en .
ngm:bundlr-network a skos:Concept ;
rdfs:label "Bundlr Network"@en .
ngm:buoy a owl:Class ;
rdfs:label "Buoy"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation ;
vc:slug "buoy" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:burn-and-mint-bridge a owl:Class ;
rdfs:comment "A Burn-and-Mint Bridge is a cross-chain asset transfer mechanism in which tokens are irreversibly destroyed (burned) on the source blockchain and an equivalent quantity of canonical tokens is newly created (minted) on the destination blockchain, ensuring that the total circulating supply across chains remains constant. This contrasts with lock-and-mint approaches by eliminating custodial reserves, instead relying on protocol-level guarantees and verifiable burn proofs to authorise minting on the receiving chain."@en ;
rdfs:label "Burn-and-Mint Bridge"@en ;
rdfs:subClassOf ngm:cross-chain-bridge ;
vc:contrastsWith ngm:lock-and-mint-bridge ;
vc:enables ngm:blockchain-interoperability ;
vc:enables ngm:cross-chain-asset-transfer ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:tokenomics ;
vc:slug "burn-and-mint-bridge" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:cross-chain-messaging ;
vc:uses ngm:cryptographic-proof .
ngm:burn-and-release a skos:Concept ;
rdfs:label "Burn And Release"@en .
ngm:burned-area-mapping a owl:Class ;
rdfs:label "Burned Area Mapping"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-applications ;
vc:slug "burned-area-mapping" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:burning a skos:Concept ;
rdfs:label "Burning"@en .
ngm:burning-mechanism a owl:Class ;
rdfs:comment "A Burning Mechanism is an economic design pattern in tokenised blockchain systems whereby tokens are permanently removed from circulating supply by sending them to an unspendable address (a null or black-hole address) or by protocol-enforced destruction, permanently contracting the total token supply. Token burning is deployed as a deflationary monetary policy tool to counteract inflationary issuance, to create token scarcity as a value-accrual mechanism, to implement fee markets (as in Ethereum's EIP-1559 base fee burn), and to regulate supply in algorithmic stablecoins and tokenomics models. The economic effect depends critically on the rate and predictability of burning relative to issuance."@en ;
rdfs:label "Burning Mechanism"@en ;
rdfs:subClassOf ngm:bc-defi-and-economics ;
rdfs:subClassOf ngm:blockchain-entity ;
rdfs:subClassOf ngm:economic-mechanism ;
rdfs:subClassOf _:r3653 ;
rdfs:subClassOf _:r3654 ;
rdfs:subClassOf _:r3655 ;
skos:broader ngm:bc-defi-and-economics ;
vc:contrastsWith ngm:block-reward ;
vc:contrastsWith ngm:inflationary-token ;
vc:dependsOn ngm:eip-1559 ;
vc:dependsOn ngm:token-economics ;
vc:enables ngm:deflationary-token ;
vc:enables ngm:inflation-control ;
vc:enables ngm:tokenomics ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:base-fee ;
vc:isPartOf ngm:tokenomics-governance ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:blockchain-economics ;
vc:relatedTo ngm:fee-market ;
vc:relatedTo ngm:market-capitalization ;
vc:relatedTo ngm:virtual-economy ;
vc:requires ngm:blockchain-transaction ;
vc:requires ngm:smart-contract ;
vc:slug "burning-mechanism" ;
vc:sourceDomain "blockchain" .
ngm:bus-interface a skos:Concept ;
rdfs:label "Bus Interface"@en .
ngm:business-architecture a skos:Concept ;
rdfs:label "Business Architecture"@en .
ngm:business-continuity a owl:Class ;
rdfs:comment "Business continuity is the discipline of ensuring that an organisation's critical functions can continue, or be rapidly restored, during and after a disruptive event such as an outage, disaster, or cyber-incident. It combines planning, redundancy, recovery procedures, and testing to limit downtime and data loss against defined objectives. In technical infrastructure it is realised through high availability, disaster recovery, fault tolerance, and resilient architecture, and is closely coupled with risk management."@en ;
rdfs:label "Business Continuity"@en ;
rdfs:subClassOf ngm:resilience ;
rdfs:subClassOf _:r3656 ;
rdfs:subClassOf _:r3657 ;
vc:contrastsWith ngm:disaster-recovery ;
vc:dependsOn ngm:infrastructure ;
vc:enables ngm:high-availability ;
vc:enables ngm:operational-resilience ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:operational-resilience ;
vc:isPartOf ngm:risk-management ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:high-availability ;
vc:relatedTo ngm:resilience ;
vc:relatedTo ngm:risk-management ;
vc:requires ngm:disaster-recovery ;
vc:requires ngm:redundancy ;
vc:slug "business-continuity" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:incident-response ;
vc:uses ngm:fault-tolerance ;
vc:uses ngm:service-level-agreement .
ngm:business-continuity-planning a skos:Concept ;
rdfs:label "Business Continuity Planning"@en .
ngm:business-cycle a skos:Concept ;
rdfs:label "Business Cycle"@en .
ngm:business-email-compromise a skos:Concept ;
rdfs:label "Business Email Compromise"@en .
ngm:business-glossary a skos:Concept ;
rdfs:label "Business Glossary"@en .
ngm:business-identifier-code a skos:Concept ;
rdfs:label "Business Identifier Code"@en .
ngm:business-innovation a skos:Concept ;
rdfs:label "Business Innovation"@en .
ngm:business-intelligence a owl:Class ;
rdfs:comment "Business intelligence is the set of technologies, processes, and practices for collecting, integrating, analysing, and presenting business data to support managerial decision-making. It encompasses data warehousing, reporting, dashboards, online analytical processing (OLAP), and ad-hoc querying that turn raw operational records into actionable insight. BI matters because it converts dispersed enterprise data into a coherent, queryable foundation for performance monitoring and strategic planning."@en ;
rdfs:label "Business Intelligence"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r3658 ;
rdfs:subClassOf _:r3659 ;
rdfs:subClassOf _:r3660 ;
rdfs:subClassOf _:r3661 ;
rdfs:subClassOf _:r3662 ;
rdfs:subClassOf _:r3663 ;
rdfs:subClassOf _:r3664 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:enterprise-resource-planning ;
vc:contrastsWith ngm:advanced-analytics ;
vc:contrastsWith ngm:data-science ;
vc:dependsOn ngm:data-engineering ;
vc:dependsOn ngm:data-lake ;
vc:dependsOn ngm:metadata-management ;
vc:enables ngm:decision-support ;
vc:enables ngm:kpi-monitoring ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:data-warehousing ;
vc:hasPart ngm:etl-pipeline ;
vc:hasPart ngm:monitoring-dashboard ;
vc:hasPart ngm:olap ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:data-engineering ;
vc:relatedTo ngm:metadata-management ;
vc:relatedTo ngm:self-service-analytics ;
vc:requires ngm:data-governance ;
vc:requires ngm:data-integration ;
vc:requires ngm:data-quality ;
vc:slug "business-intelligence" ;
vc:sourceDomain "data" ;
vc:uses ngm:semantic-layer ;
vc:uses ngm:sql .
ngm:business-intelligence-dashboard a skos:Concept ;
rdfs:label "Business Intelligence Dashboard"@en .
ngm:business-logic-layer a owl:Class ;
rdfs:comment "The Business Logic Layer (BLL) is the architectural tier in a multi-tier application that encapsulates domain rules, workflows, and computations specific to the problem domain, sitting between the presentation layer and the data access layer. It is responsible for validating inputs, enforcing business constraints, orchestrating data transformations, and coordinating service calls, ensuring that domain invariants are maintained independently of user interface or persistence concerns."@en ;
rdfs:label "Business Logic Layer"@en ;
rdfs:subClassOf ngm:service-layer ;
vc:dependsOn ngm:data-layer ;
vc:enables ngm:workflow-automation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:microservices-architecture ;
vc:relatedTo ngm:service-oriented-architecture ;
vc:slug "business-logic-layer" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:application-layer ;
vc:uses ngm:middleware .
ngm:business-orchestration-and-automation-technology a skos:Concept ;
rdfs:label "Business Orchestration And Automation Technology"@en .
ngm:business-process-automation a owl:Class ;
rdfs:comment "The use of technology to automate complex, multi-step business processes beyond individual tasks, integrating systems and people to streamline operations. It targets end-to-end workflows rather than isolated actions."@en ;
rdfs:label "Business Process Automation"@en ;
rdfs:subClassOf ngm:process-automation ;
rdfs:subClassOf _:r3665 ;
vc:bridgesTo ngm:robotic-process-automation ;
vc:enables ngm:automation ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:workflow-automation ;
vc:slug "business-process-automation" ;
vc:sourceDomain "robotics" .
ngm:business-process-management a owl:Class ;
rdfs:comment "Business Process Management (BPM) is a discipline that uses methods, techniques, and software tools to discover, model, analyse, measure, improve, and automate business processes — end-to-end workflows that produce value for internal stakeholders or external customers. It combines organisational management practice with process automation technology to make organisational operations more efficient, agile, and aligned with strategic goals."@en ;
rdfs:label "Business Process Management"@en ;
rdfs:subClassOf ngm:enterprise-architecture ;
rdfs:subClassOf _:r3666 ;
rdfs:subClassOf _:r3667 ;
rdfs:subClassOf _:r3668 ;
rdfs:subClassOf _:r3669 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:low-code-platform ;
vc:enables ngm:continuous-improvement ;
vc:enables ngm:digital-transformation ;
vc:enables ngm:operational-efficiency ;
vc:enables ngm:process-automation ;
vc:enables ngm:workflow-automation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:business-rules-engine ;
vc:hasPart ngm:case-management ;
vc:hasPart ngm:process-mining ;
vc:isPartOf ngm:enterprise-architecture ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:enterprise-resource-planning ;
vc:relatedTo ngm:supply-chain-management ;
vc:requires ngm:event-driven-architecture ;
vc:slug "business-process-management" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:bpmn ;
vc:supports ngm:audit-trail ;
vc:supports ngm:compliance-management ;
vc:supports ngm:risk-management ;
vc:uses ngm:middleware ;
vc:uses ngm:robotic-process-automation ;
vc:uses ngm:service-oriented-architecture .
ngm:business-rules a skos:Concept ;
rdfs:label "Business Rules"@en .
ngm:business-rules-engine a owl:Class ;
rdfs:comment "A Business Rules Engine (BRE) is a software component that externalises and executes business logic as declarative rules separate from application code. Rules are authored by domain experts in natural-language-like syntax and evaluated against facts at runtime using algorithms such as the Rete network. BREs enable non-technical stakeholders to modify organisational policies without redeploying software, making them a key enabler of agile governance and compliance automation."@en ;
rdfs:label "Business Rules Engine"@en ;
rdfs:subClassOf ngm:governance ;
rdfs:subClassOf _:r3670 ;
vc:bridgesTo ngm:ai-decision-system ;
vc:contrastsWith ngm:hardcoded-logic ;
vc:contrastsWith ngm:machine-learning-discipline ;
vc:dependsOn ngm:knowledge-representation ;
vc:dependsOn ngm:reasoning-engine ;
vc:enables ngm:compliance-automation ;
vc:enables ngm:decision-management ;
vc:enables ngm:policy-enforcement ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:fact-model ;
vc:hasPart ngm:inference-engine ;
vc:hasPart ngm:rule-repository ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:smart-contract ;
vc:relatedTo ngm:workflow-automation ;
vc:slug "business-rules-engine" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:dmn ;
vc:standardizedBy ngm:drools ;
vc:supports ngm:regulatory-compliance ;
vc:supports ngm:risk-management ;
vc:uses ngm:decision-table ;
vc:uses ngm:rete-algorithm .
ngm:business-services a skos:Concept ;
rdfs:label "Business Services"@en .
ngm:business-strategy a skos:Concept ;
rdfs:label "Business Strategy"@en .
ngm:buy-now-pay-later a skos:Concept ;
rdfs:label "Buy Now Pay Later"@en .
ngm:buyback-and-burn a skos:Concept ;
rdfs:label "Buyback And Burn"@en .
ngm:bvh-acceleration-structure a owl:Class ;
rdfs:comment "A bounding volume hierarchy (BVH) is a tree-based spatial data structure that recursively partitions scene geometry into nested bounding volumes to accelerate ray-geometry intersection queries. By testing rays against coarse parent volumes before descending into child nodes, a BVH reduces intersection complexity from linear in primitive count to roughly logarithmic. It is the dominant acceleration structure in modern ray tracing because it supports fast rebuilds for dynamic scenes and maps efficiently to GPU hardware."@en ;
rdfs:label "BVH Acceleration Structure"@en ;
rdfs:subClassOf ngm:rendering-technique ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:ray-tracing ;
vc:slug "bvh-acceleration-structure" ;
vc:sourceDomain "metaverse" .
ngm:bvh-construction a skos:Concept ;
rdfs:label "Bvh Construction"@en .
ngm:bvh-format a skos:Concept ;
rdfs:label "Bvh Format"@en .
ngm:bvi-limited-company a skos:Concept ;
rdfs:label "Bvi Limited Company"@en .
ngm:bylaws a skos:Concept ;
rdfs:label "Bylaws"@en .
ngm:byol a skos:Concept ;
rdfs:label "Byol"@en .
ngm:byte-pair-encoding a owl:Class ;
rdfs:comment "A subword tokenisation algorithm that iteratively merges the most frequent pairs of characters or character sequences to build a vocabulary, originally developed for data compression and widely adopted in neural language models."@en ;
rdfs:label "Byte Pair Encoding"@en ;
rdfs:subClassOf ngm:sc-content-and-assets ;
rdfs:subClassOf _:r3671 ;
rdfs:subClassOf _:r3672 ;
skos:broader ngm:sc-content-and-assets ;
vc:bridgesTo ngm:data-compression ;
vc:bridgesTo ngm:information-theory ;
vc:contrastsWith ngm:sentence-piece ;
vc:contrastsWith ngm:word-piece ;
vc:enables ngm:natural-language-processing ;
vc:enables ngm:neural-machine-translation ;
vc:enables ngm:text-generation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:vocabulary ;
vc:implements ngm:data-compression ;
vc:isPartOf ngm:neural-network-text-tokenisation ;
vc:isPartOf ngm:subword-tokenisation ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:gpt ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:ro-berta ;
vc:relatedTo ngm:tokenization ;
vc:requires ngm:training-corpus ;
vc:slug "byte-pair-encoding" ;
vc:sourceDomain "machine-learning" ;
vc:supports ngm:natural-language-processing ;
vc:uses ngm:transformer .
ngm:bytecode a owl:Class ;
rdfs:comment "Bytecode is a compact, platform-independent instruction set produced by compiling source code, designed to be executed by a virtual machine rather than directly by hardware. In blockchain systems, smart contracts written in high-level languages such as Solidity are compiled to bytecode that the Ethereum Virtual Machine deterministically executes across every node. Bytecode strikes a balance between the portability of source code and the efficiency of native machine code."@en ;
rdfs:label "Bytecode"@en ;
rdfs:subClassOf ngm:smart-contract-execution ;
rdfs:subClassOf _:r3673 ;
rdfs:subClassOf _:r3674 ;
rdfs:subClassOf _:r3675 ;
vc:bridgesTo ngm:runtime-environment ;
vc:dependsOn ngm:evm ;
vc:enables ngm:smart-contract-execution ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:smart-contract ;
vc:isPartOf ngm:smart-contract-execution ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:compiler ;
vc:relatedTo ngm:evm ;
vc:relatedTo ngm:smart-contract ;
vc:requires ngm:compiler ;
vc:requires ngm:runtime-environment ;
vc:slug "bytecode" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:solidity ;
vc:uses ngm:compiler ;
vc:uses ngm:virtual-machine .
ngm:byzantine-agreement a owl:Class ;
rdfs:comment "Byzantine Agreement is a class of distributed consensus protocols that guarantee correct operation even when a subset of participating nodes behave arbitrarily — sending conflicting, malicious, or unpredictable messages. Originating from the Byzantine Generals Problem formalised by Lamport, Shostak, and Pease in 1982, these protocols ensure that all honest nodes reach the same decision provided the number of faulty nodes does not exceed one-third of the total. Byzantine Agreement is foundational to blockchain consensus mechanisms and safety-critical distributed systems."@en ;
rdfs:label "Byzantine Agreement"@en ;
rdfs:subClassOf ngm:consensus-mechanism ;
rdfs:subClassOf _:r3676 ;
vc:bridgesTo ngm:security ;
vc:contrastsWith ngm:crash-fault-tolerance ;
vc:dependsOn ngm:cryptographic-hash ;
vc:enables ngm:blockchain-data ;
vc:enables ngm:smart-contract ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:voting-round ;
vc:implements ngm:consensus-mechanism ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:blockchain ;
vc:relatedTo ngm:distributed-systems ;
vc:relatedTo ngm:fault-tolerance ;
vc:slug "byzantine-agreement" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:distributed-computing-research ;
vc:uses ngm:cryptographic-signature ;
vc:uses ngm:peer-to-peer-network .
ngm:byzantine-fault-tolerance a owl:Class ;
rdfs:comment "The feature of a distributed network to reach consensus on the same value even when some nodes fail to respond or respond with incorrect information. Enables networks to function correctly despite malicious or faulty nodes comprising less than one-third of the network. Derived from the Byzantine Generals Problem; the fundamental theorem states consensus is achievable if and only if more than two-thirds of participants are honest."@en ;
rdfs:label "Byzantine Fault Tolerance"@en ;
rdfs:subClassOf ngm:consensus-mechanism ;
rdfs:subClassOf ngm:distributed-agreement ;
rdfs:subClassOf _:r3677 ;
rdfs:subClassOf _:r3678 ;
rdfs:subClassOf _:r3679 ;
rdfs:subClassOf _:r3680 ;
rdfs:subClassOf _:r3681 ;
rdfs:subClassOf _:r3682 ;
vc:bridgesTo ngm:ai-energy-optimisation ;
vc:bridgesTo ngm:distributed-systems ;
vc:bridgesTo ngm:multi-agent-systems ;
vc:contrastsWith ngm:crash-fault-tolerance ;
vc:contrastsWith ngm:proof-of-work ;
vc:dependsOn ngm:network-synchrony ;
vc:dependsOn ngm:public-key-cryptography ;
vc:enables ngm:consensus ;
vc:enables ngm:deterministic-finality ;
vc:enables ngm:fault-tolerance ;
vc:enables ngm:malicious-node-handling ;
vc:enables ngm:state-machine-replication ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:finality-gadget ;
vc:hasPart ngm:leader-election ;
vc:hasPart ngm:voting-round ;
vc:implements ngm:hotstuff-protocol ;
vc:implements ngm:practical-byzantine-fault-tolerance ;
vc:isPartOf ngm:blockchain ;
vc:isPartOf ngm:distributed-systems ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:casper-ffg ;
vc:relatedTo ngm:proof-of-stake ;
vc:relatedTo ngm:validator-set ;
vc:requires ngm:cryptographic-signature ;
vc:requires ngm:distributed-agreement ;
vc:requires ngm:message-authentication ;
vc:requires ngm:quorum ;
vc:slug "byzantine-fault-tolerance" ;
vc:sourceDomain "distributed-systems" .
ngm:byzantine-fault-tolerant-system a owl:Class ;
rdfs:comment "A Byzantine Fault Tolerant System is a distributed computing system designed to continue operating correctly even when a fraction of its nodes exhibit arbitrary, potentially malicious failures — including sending conflicting, incorrect, or no messages to different peers. Such systems implement consensus protocols that guarantee safety (agreement) and liveness (progress) provided strictly fewer than one-third of participating nodes are faulty, a bound established by the foundational Byzantine Generals Problem. BFT systems underpin the security of permissioned and permissionless blockchain networks, replicated state machines, and safety-critical distributed infrastructure where adversarial behaviour must be tolerated without compromising overall correctness."@en ;
rdfs:label "Byzantine Fault Tolerant System"@en ;
rdfs:subClassOf ngm:infra-computing-and-cloud ;
rdfs:subClassOf _:r3683 ;
rdfs:subClassOf _:r3684 ;
rdfs:subClassOf _:r3685 ;
rdfs:subClassOf _:r3686 ;
rdfs:subClassOf _:r3687 ;
skos:broader ngm:infra-computing-and-cloud ;
vc:bridgesTo ngm:de-fi ;
vc:bridgesTo ngm:smart-contract-platform ;
vc:contrastsWith ngm:crash-fault-tolerant-system ;
vc:contrastsWith ngm:paxos ;
vc:contrastsWith ngm:raft-consensus ;
vc:dependsOn ngm:cryptographic-signature ;
vc:dependsOn ngm:network-communication ;
vc:dependsOn ngm:peer-to-peer-network ;
vc:enables ngm:atomic-broadcast ;
vc:enables ngm:consensus-mechanism ;
vc:enables ngm:consensus-protocol ;
vc:enables ngm:distributed-ledger ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:leader-election ;
vc:hasPart ngm:two-phase-commit ;
vc:hasPart ngm:view-change-protocol ;
vc:implements ngm:byzantine-fault-tolerance ;
vc:implements ngm:state-machine-replication ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:byzantine-generals-problem ;
vc:relatedTo ngm:hotstuff-protocol ;
vc:relatedTo ngm:pbft ;
vc:relatedTo ngm:practical-byzantine-fault-tolerance ;
vc:relatedTo ngm:tendermint ;
vc:requires ngm:consensus-algorithm ;
vc:requires ngm:message-authentication ;
vc:requires ngm:quorum-system ;
vc:slug "byzantine-fault-tolerant-system" ;
vc:sourceDomain "distributed-systems" ;
vc:supports ngm:blockchain-network ;
vc:supports ngm:permissioned-blockchain ;
vc:supports ngm:state-machine-replication .
ngm:byzantine-generals-problem a owl:Class ;
rdfs:comment "The Byzantine Generals Problem is a foundational thought experiment in distributed computing describing how loyal participants can reach agreement when some participants are traitorous and may send arbitrary or conflicting messages. It formalises the difficulty of achieving consensus in the presence of arbitrary (Byzantine) faults, where faulty nodes behave maliciously rather than merely crashing. The problem establishes that agreement is solvable only when fewer than one-third of participants are faulty."@en ;
rdfs:label "Byzantine Generals Problem"@en ;
rdfs:subClassOf ngm:fault-tolerance ;
rdfs:subClassOf _:r3688 ;
vc:bridgesTo ngm:proof-of-stake ;
vc:bridgesTo ngm:tendermint ;
vc:contrastsWith ngm:atomic-broadcast ;
vc:contrastsWith ngm:crash-fault-tolerance ;
vc:dependsOn ngm:distributed-system ;
vc:dependsOn ngm:fault-tolerance ;
vc:enables ngm:byzantine-fault-tolerance ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:byzantine-fault-tolerance ;
vc:relatedTo ngm:consensus ;
vc:relatedTo ngm:distributed-systems ;
vc:requires ngm:message-passing ;
vc:slug "byzantine-generals-problem" ;
vc:sourceDomain "distributed-systems" ;
vc:supports ngm:blockchain-consensus ;
vc:supports ngm:practical-byzantine-fault-tolerance .
ngm:byzantine-quorum-without-total-order a skos:Concept ;
rdfs:label "Byzantine Quorum Without Total Order"@en .
ngm:c a skos:Concept ;
rdfs:label "C"@en .
ngm:c-api a skos:Concept ;
rdfs:label "C API"@en .
ngm:c-chain a skos:Concept ;
rdfs:label "C Chain"@en .
ngm:c-mapss-dataset a skos:Concept ;
rdfs:label "C Mapss Dataset"@en .
ngm:c-plus-plus a skos:Concept ;
rdfs:label "C Plus Plus"@en .
ngm:c-rclcpp a skos:Concept ;
rdfs:label "C Rclcpp"@en .
ngm:c-runtime a skos:Concept ;
rdfs:label "C Runtime"@en .
ngm:c2-pa a owl:Class ;
rdfs:comment "C2PA (Coalition for Content Provenance and Authenticity) is a cross-industry open technical standards body and specification that cryptographically binds signed provenance metadata — covering capture origin, editing history, and AI generation disclosure — to digital media assets including images, video, audio, and documents. Founded by Adobe, Arm, BBC, Intel, Microsoft, and Truepic under the Joint Development Foundation, the C2PA specification defines the manifest container format (JUMBF/ISO 19566-5), assertion vocabularies, COSE-based signing mechanism, X.509 PKI trust model, and the resulting Content Credentials artefact. C2PA consolidates two prior initiatives — Adobe's Content Authenticity Initiative (CAI) and the BBC-led Project Origin — into a single interoperable standard for end-to-end media provenance across capture, editing, distribution, and verification stages."@en ;
rdfs:label "C2PA"@en ;
rdfs:subClassOf ngm:sc-standards-and-interop ;
rdfs:subClassOf _:r3693 ;
rdfs:subClassOf _:r3694 ;
rdfs:subClassOf _:r3695 ;
rdfs:subClassOf _:r3696 ;
skos:broader ngm:sc-standards-and-interop ;
vc:bridgesTo ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:provenance-ontology-prov-o ;
vc:bridgesTo ngm:watermarking-service ;
vc:contrastsWith ngm:deepfakes ;
vc:contrastsWith ngm:synthetic-media ;
vc:enables ngm:ai-generated-content-disclosure ;
vc:enables ngm:media-authentication ;
vc:enables ngm:provenance-verification ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:c2-pa-content-credentials ;
vc:hasPart ngm:c2pa-assertion ;
vc:hasPart ngm:c2pa-manifest ;
vc:hasPart ngm:c2pa-trust-list ;
vc:implements ngm:content-authenticity ;
vc:implements ngm:project-origin ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:joint-development-foundation ;
vc:relatedTo ngm:open-media-alliance ;
vc:relatedTo ngm:w3-c-verifiable-credentials ;
vc:requires ngm:certificate-authority ;
vc:requires ngm:cryptographic-infrastructure ;
vc:requires ngm:digital-signature ;
vc:slug "c2-pa" ;
vc:sourceDomain "standards" ;
vc:supports ngm:disinformation-countermeasures ;
vc:supports ngm:media-integrity ;
vc:supports ngm:supply-chain-transparency ;
vc:uses ngm:cose ;
vc:uses ngm:jumbf ;
vc:uses ngm:provenance-tracking ;
vc:uses ngm:x-509-certificate .
ngm:c2-pa-content-credentials a owl:Class ;
rdfs:comment "C2PA Content Credentials are cryptographically signed metadata manifests, defined by the Coalition for Content Provenance and Authenticity (C2PA) technical specification, that are embedded in or bound to digital media assets to record their origin, capture conditions, AI generation provenance, and editing history in a tamper-evident chain. Each Content Credential is a JUMBF-structured (JPEG Universal Metadata Box Format) assertion set signed using the COSE (CBOR Object Signing and Encryption) standard, anchored to the asset via a cryptographic hash binding that detects post-signing modifications. Verifiers — including browser extensions, social media platforms, AI disclosure tools, and editing software — can retrieve and display the full credential chain, enabling transparent and auditable provenance for photographs, video, audio, documents, and AI-generated synthetic content. The mechanism serves as the primary interoperability layer between hardware capture devices, editing software, AI generation systems, and distribution platforms participating in the broader content authenticity ecosystem."@en ;
rdfs:label "C2PA Content Credentials"@en ;
rdfs:subClassOf ngm:infra-security-and-identity ;
rdfs:subClassOf _:r3689 ;
rdfs:subClassOf _:r3690 ;
skos:broader ngm:infra-security-and-identity ;
vc:bridgesTo ngm:ai-regulation ;
vc:bridgesTo ngm:generative-ai ;
vc:contrastsWith ngm:ai-watermarking ;
vc:contrastsWith ngm:deepfakes ;
vc:contrastsWith ngm:steganography ;
vc:enables ngm:ai-transparency-framework ;
vc:enables ngm:creator-attribution ;
vc:enables ngm:supply-chain-traceability ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:c2-pa-standard ;
vc:implements ngm:cryptographic-signing ;
vc:implements ngm:jumbf-container-format ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:content-authenticity ;
vc:relatedTo ngm:iptc-photo-metadata ;
vc:relatedTo ngm:metadata ;
vc:relatedTo ngm:provenance ;
vc:relatedTo ngm:w3-c-verifiable-credentials ;
vc:requires ngm:certificate-authority ;
vc:requires ngm:hardware-security-module ;
vc:slug "c2-pa-content-credentials" ;
vc:sourceDomain "security" ;
vc:supports ngm:ai-generated-content-disclosure ;
vc:supports ngm:disinformation-countermeasures ;
vc:supports ngm:media-authenticity ;
vc:supports ngm:provenance-verification ;
vc:supports ngm:trust-and-safety ;
vc:uses ngm:cryptographic-hash ;
vc:uses ngm:cryptographic-infrastructure ;
vc:uses ngm:digital-signature ;
vc:uses ngm:provenance-tracking ;
vc:uses ngm:x-509-certificate .
ngm:c2-pa-standard a owl:Class ;
rdfs:comment "An open technical standard developed by the Coalition for Content Provenance and Authenticity that establishes cryptographically-signed Content Credentials to certify the origin, history, and authenticity of digital media, functioning like a tamper-evident nutrition label for digital content."@en ;
rdfs:label "C2PA Standard"@en ;
rdfs:subClassOf ngm:sc-standards-and-interop ;
rdfs:subClassOf ngm:technical-standard ;
rdfs:subClassOf _:r3691 ;
rdfs:subClassOf _:r3692 ;
skos:broader ngm:sc-standards-and-interop ;
vc:bridgesTo ngm:technical-standard ;
vc:enables ngm:authenticity-certification ;
vc:enables ngm:content-provenance ;
vc:enables ngm:media-verification ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:cryptographic-signing ;
vc:requires ngm:metadata-framework ;
vc:requires ngm:trust-model ;
vc:slug "c2-pa-standard" ;
vc:sourceDomain "spatial-computing" .
ngm:c2pa-assertion a skos:Concept ;
rdfs:label "C2pa Assertion"@en .
ngm:c2pa-coalition-for-content-provenance-and-authenticity a skos:Concept ;
rdfs:label "C2pa Coalition For Content Provenance And Authenticity"@en .
ngm:c2pa-manifest a skos:Concept ;
rdfs:label "C2pa Manifest"@en .
ngm:c2pa-provenance-standard a skos:Concept ;
rdfs:label "C2pa Provenance Standard"@en .
ngm:c2pa-trust-list a skos:Concept ;
rdfs:label "C2pa Trust List"@en .
ngm:c4-dataset a skos:Concept ;
rdfs:label "C4 Dataset"@en .
ngm:c4-model a owl:Class ;
rdfs:comment "The C4 Model is a hierarchical software architecture notation system developed by Simon Brown that uses four abstraction levels — Context, Containers, Components, and Code — to describe and communicate the structure of a software system at progressively increasing levels of technical detail. Each level targets a different audience, from non-technical stakeholders at the Context level to developers at the Code level, using a minimal, tool-agnostic set of diagram elements that are easy to reason about and keep up to date."@en ;
rdfs:label "C4 Model"@en ;
rdfs:subClassOf ngm:software-architecture ;
vc:enables ngm:documentation-generation ;
vc:enables ngm:documentation-standards ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:enterprise-architecture ;
vc:slug "c4-model" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:diagrams-as-code ;
vc:uses ngm:structurizr-dsl .
ngm:ca-browser-forum a owl:Class ;
rdfs:comment "The CA/Browser Forum (CA/B Forum) is a voluntary industry consortium of Certification Authorities (CAs), web browser vendors, and other relying parties that collaboratively develops and enforces minimum standards for the issuance and management of X.509 digital certificates used in TLS/HTTPS, code signing, and S/MIME email. Its Baseline Requirements documents define mandatory technical and procedural controls that CAs must meet to remain trusted by member browsers such as Chrome, Firefox, Safari, and Edge. Compliance is a prerequisite for inclusion in browser root stores, giving the Forum significant de facto regulatory power over internet PKI."@en ;
rdfs:label "Ca Browser Forum"@en ;
rdfs:subClassOf ngm:security ;
rdfs:subClassOf _:r3822 ;
vc:contrastsWith ngm:ietf ;
vc:contrastsWith ngm:w3-c ;
vc:enables ngm:code-signing ;
vc:enables ngm:http ;
vc:enables ngm:web-security ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:certificate-transparency ;
vc:relatedTo ngm:extended-validation ;
vc:relatedTo ngm:root-store ;
vc:relatedTo ngm:x-509-certificate ;
vc:relatedTo ngm:x509 ;
vc:requires ngm:audit-compliance ;
vc:requires ngm:cryptography ;
vc:slug "ca-browser-forum" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:certificate-authority ;
vc:standardizedBy ngm:standards ;
vc:supports ngm:digital-identity ;
vc:supports ngm:internet-security ;
vc:uses ngm:cryptographic-infrastructure .
ngm:cable-drive a owl:Class ;
rdfs:comment "A cable drive (cable-driven transmission) is a mechanical actuation mechanism that transmits force and motion through tensioned cables, tendons, or belts routed over pulleys, rather than through rigid gear trains. It allows actuators to be located remotely from the joint they drive, reducing distal mass and inertia in robotic limbs and surgical instruments. Cable drives matter in robotics because they enable lightweight, compliant, backdrivable joints with low backlash."@en ;
rdfs:label "Cable Drive"@en ;
rdfs:subClassOf ngm:robo-actuation-and-control ;
skos:broader ngm:robo-actuation-and-control ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:mechanical-component ;
vc:slug "cable-drive" ;
vc:sourceDomain "robotics" .
ngm:cable-plant a skos:Concept ;
rdfs:label "Cable Plant"@en .
ngm:cache-coherence a skos:Concept ;
rdfs:label "Cache Coherence"@en .
ngm:cache-layer a owl:Class ;
rdfs:comment "A cache layer is an intermediate storage tier interposed between a data consumer and an authoritative data source, holding frequently or recently accessed data in faster storage to reduce latency, decrease load on origin systems, and improve overall system throughput. Cache layers operate at multiple levels of a computing stack—CPU caches, in-process memory caches, distributed shared caches, and edge CDN caches—each exploiting temporal or spatial locality of access patterns. Correctness requires coherence protocols or explicit invalidation strategies to prevent stale data from being served."@en ;
rdfs:label "Cache Layer"@en ;
rdfs:subClassOf ngm:storage-layer ;
vc:enables ngm:performance-optimization ;
vc:enables ngm:scalability ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:content-delivery-network-cdn ;
vc:relatedTo ngm:database-system ;
vc:relatedTo ngm:latency ;
vc:slug "cache-layer" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:data-storage ;
vc:uses ngm:kv-cache .
ngm:cached-latent-encoding a skos:Concept ;
rdfs:label "Cached Latent Encoding"@en .
ngm:caching a owl:Class ;
rdfs:comment "Caching is the technique of storing copies of frequently accessed data or computed results in a faster, closer storage tier so that subsequent requests can be served without repeating the expensive original operation. It trades additional memory or storage for reduced latency and lower load on backend systems, governed by policies for placement, expiry and invalidation. Caches appear at every layer of a system, from CPU registers and operating systems to content delivery networks and application-level stores."@en ;
rdfs:label "Caching"@en ;
rdfs:subClassOf ngm:performance-optimization ;
rdfs:subClassOf _:r3823 ;
vc:bridgesTo ngm:cdn ;
vc:contrastsWith ngm:in-memory-computing ;
vc:dependsOn ngm:memory-management ;
vc:enables ngm:latency ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:cdn ;
vc:isPartOf ngm:performance-optimization ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-pipeline ;
vc:relatedTo ngm:distributed-systems ;
vc:relatedTo ngm:edge-computing ;
vc:relatedTo ngm:load-balancing ;
vc:slug "caching" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:scalability ;
vc:supports ngm:throughput ;
vc:uses ngm:memory-management ;
vc:uses ngm:state-management .
ngm:caching-infrastructure a skos:Concept ;
rdfs:label "Caching Infrastructure"@en .
ngm:cad-capabilities a skos:Concept ;
rdfs:label "Cad Capabilities"@en .
ngm:cad-software a owl:Class ;
rdfs:comment "Computer-Aided Design (CAD) software is a category of application that enables engineers, architects, and designers to create, modify, analyse, and optimise two-dimensional drawings and three-dimensional geometric models of physical artefacts and structures. CAD tools encode geometry using boundary representation (B-rep) or constructive solid geometry (CSG) methods, support parametric constraint-based modelling, and produce outputs usable in manufacturing, simulation, and visualisation pipelines."@en ;
rdfs:label "CAD Software"@en ;
rdfs:subClassOf ngm:design-software ;
rdfs:subClassOf _:r3697 ;
rdfs:subClassOf _:r3698 ;
vc:bridgesTo ngm:bim-virtual-model ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:robotics ;
vc:dependsOn ngm:computer-graphics ;
vc:dependsOn ngm:geometric-kernel ;
vc:enables ngm:additive-manufacturing ;
vc:enables ngm:finite-element-analysis ;
vc:enables ngm:generative-design ;
vc:enables ngm:manufacturing-process ;
vc:enables ngm:parametric-design-methodology-modeling ;
vc:enables ngm:product-design ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:constraint-solver ;
vc:hasPart ngm:geometric-kernel ;
vc:implements ngm:computational-geometry ;
vc:implements ngm:constraint-solver ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:electronic-design-automation ;
vc:relatedTo ngm:manufacturing-automation ;
vc:requires ngm:computational-geometry ;
vc:slug "cad-software" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:iso-10303-step ;
vc:supports ngm:cnc-machining ;
vc:supports ngm:simulation ;
vc:uses ngm:3-d-file-format ;
vc:uses ngm:mesh-data .
ngm:cadcad-reference-model a skos:Concept ;
rdfs:label "Cadcad Reference Model"@en .
ngm:cadcad-simulation a skos:Concept ;
rdfs:label "Cadcad Simulation"@en .
ngm:cades a skos:Concept ;
rdfs:label "Cades"@en .
ngm:cai-coalition-for-content-provenance-and-authenticity a skos:Concept ;
rdfs:label "Cai Coalition For Content Provenance And Authenticity"@en .
ngm:cairo-language a skos:Concept ;
rdfs:label "Cairo Language"@en .
ngm:calculation-methodology a skos:Concept ;
rdfs:label "Calculation Methodology"@en .
ngm:calculation-parameters a owl:Class ;
rdfs:comment "Configurable variables and settings that control the behavior, accuracy, and performance of computational simulations and models, including solver options, convergence criteria, time steps, and optimization constraints that fine-tune simulation outputs."@en ;
rdfs:label "Calculation Parameters"@en ;
rdfs:subClassOf ngm:configuration-setting ;
rdfs:subClassOf ngm:sc-content-and-assets ;
rdfs:subClassOf _:r3824 ;
rdfs:subClassOf _:r3825 ;
skos:broader ngm:sc-content-and-assets ;
vc:enables ngm:model-calibration ;
vc:enables ngm:performance-tuning ;
vc:enables ngm:simulation-control ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:parameter-definition ;
vc:requires ngm:sensitivity-analysis ;
vc:requires ngm:validation-rules ;
vc:slug "calculation-parameters" ;
vc:sourceDomain "spatial-computing" .
ngm:calculation-timestamp a skos:Concept ;
rdfs:label "Calculation Timestamp"@en .
ngm:calculus a owl:Class ;
rdfs:comment "Calculus is the branch of mathematics concerned with continuous change, comprising differential calculus (rates of change and slopes via derivatives) and integral calculus (accumulation and areas via integrals). In machine learning it provides the foundational machinery for optimisation: gradients computed through differentiation drive parameter updates, while integration underpins probability, expectation and continuous-time models. It is indispensable for understanding how learning algorithms adjust models to minimise loss."@en ;
rdfs:label "Calculus"@en ;
rdfs:subClassOf ngm:applied-mathematics ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf ngm:mathematical-science ;
rdfs:subClassOf ngm:mathematics ;
rdfs:subClassOf _:r3826 ;
rdfs:subClassOf _:r3827 ;
rdfs:subClassOf _:r3828 ;
rdfs:subClassOf _:r3829 ;
vc:contrastsWith ngm:boolean-logic ;
vc:contrastsWith ngm:combinatorics ;
vc:contrastsWith ngm:discrete-mathematics ;
vc:contrastsWith ngm:symbolic-computation ;
vc:dependsOn ngm:measure-theory ;
vc:dependsOn ngm:numerical-methods ;
vc:dependsOn ngm:probability-theory ;
vc:dependsOn ngm:real-analysis ;
vc:enables ngm:automatic-differentiation ;
vc:enables ngm:backpropagation ;
vc:enables ngm:convex-optimisation ;
vc:enables ngm:diffusion-models ;
vc:enables ngm:gradient-descent ;
vc:enables ngm:natural-gradient ;
vc:enables ngm:neural-tangent-kernel ;
vc:enables ngm:optimisation ;
vc:enables ngm:stochastic-gradient-descent ;
vc:enables ngm:variational-inference ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:chain-rule ;
vc:hasPart ngm:differential-calculus ;
vc:hasPart ngm:functional-analysis ;
vc:hasPart ngm:hessian ;
vc:hasPart ngm:integral-calculus ;
vc:hasPart ngm:jacobian ;
vc:hasPart ngm:multivariable-calculus ;
vc:hasPart ngm:stochastic-calculus ;
vc:hasPart ngm:taylor-series ;
vc:hasPart ngm:variational-calculus ;
vc:hasPart ngm:vector-calculus ;
vc:implements ngm:differentiable-programming ;
vc:implements ngm:gradient-based-learning ;
vc:implements ngm:sensitivity-analysis ;
vc:implements ngm:variational-methods ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:activation-function ;
vc:relatedTo ngm:differential-equations ;
vc:relatedTo ngm:functional-analysis ;
vc:relatedTo ngm:information-theory ;
vc:relatedTo ngm:linear-algebra ;
vc:relatedTo ngm:loss-function ;
vc:relatedTo ngm:measure-theory ;
vc:relatedTo ngm:statistics ;
vc:relatedTo ngm:topology ;
vc:requires ngm:limits-and-continuity ;
vc:requires ngm:linear-algebra ;
vc:requires ngm:real-analysis ;
vc:requires ngm:set-theory ;
vc:slug "calculus" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:acm ;
vc:standardizedBy ngm:ieee ;
vc:standardizedBy ngm:siam ;
vc:supports ngm:deep-learning ;
vc:supports ngm:engineering ;
vc:supports ngm:large-language-models ;
vc:supports ngm:machine-learning-discipline ;
vc:supports ngm:neural-network ;
vc:supports ngm:physics ;
vc:supports ngm:probability-theory ;
vc:supports ngm:reinforcement-learning ;
vc:supports ngm:statistics ;
vc:uses ngm:automatic-differentiation ;
vc:uses ngm:computational-graphs ;
vc:uses ngm:linear-algebra ;
vc:uses ngm:numerical-methods .
ngm:calculus-of-variations a skos:Concept ;
rdfs:label "Calculus Of Variations"@en .
ngm:calendar-api a skos:Concept ;
rdfs:label "Calendar API"@en .
ngm:calendar-data a skos:Concept ;
rdfs:label "Calendar Data"@en .
ngm:calendar-integration a skos:Concept ;
rdfs:label "Calendar Integration"@en .
ngm:calibrated-data-state a owl:Class ;
rdfs:label "Calibrated Data State"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-processing ;
vc:slug "calibrated-data-state" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:calibrated-equalised-odds a skos:Concept ;
rdfs:label "Calibrated Equalised Odds"@en .
ngm:calibration a owl:Class ;
rdfs:comment "Calibration is the systematic process of establishing, verifying, and correcting the quantitative relationship between a measurement instrument's or computational model's output and a known reference standard, encompassing intrinsic parameter estimation (gain, offset, nonlinearity, bias), extrinsic parameter determination (spatial pose and orientation relative to a reference frame), and inter-device consistency alignment. In physical systems it removes systematic error between raw sensor readings and true physical quantities; in machine learning it aligns predicted probability distributions to empirical frequencies. Calibration is a prerequisite for metrically accurate perception, reliable closed-loop control, trustworthy probabilistic inference, and coherent multi-modal data fusion across robotics, spatial computing, and AI systems."@en ;
rdfs:label "Calibration"@en ;
rdfs:subClassOf ngm:robo-perception ;
rdfs:subClassOf _:r3837 ;
rdfs:subClassOf _:r3838 ;
rdfs:subClassOf _:r3839 ;
rdfs:subClassOf _:r3840 ;
skos:broader ngm:robo-perception ;
vc:bridgesTo ngm:model-calibration ;
vc:bridgesTo ngm:probabilistic-calibration ;
vc:bridgesTo ngm:uncertainty-quantification ;
vc:contrastsWith ngm:validation-process ;
vc:contrastsWith ngm:verification ;
vc:dependsOn ngm:least-squares ;
vc:dependsOn ngm:optimisation ;
vc:enables ngm:augmented-reality ;
vc:enables ngm:pose-estimation ;
vc:enables ngm:robot-control ;
vc:enables ngm:sensor-fusion ;
vc:enables ngm:slam ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:camera-calibration ;
vc:hasPart ngm:extrinsic-calibration ;
vc:hasPart ngm:imu-calibration ;
vc:hasPart ngm:temporal-calibration ;
vc:isPartOf ngm:quality-assurance ;
vc:isPartOf ngm:sensor-pipeline ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:kinematic-calibration ;
vc:relatedTo ngm:sensor-noise ;
vc:relatedTo ngm:systematic-error ;
vc:requires ngm:error-model ;
vc:requires ngm:ground-truth-labels ;
vc:requires ngm:reference-standard ;
vc:slug "calibration" ;
vc:sourceDomain "robotics" ;
vc:supports ngm:autonomous-driving ;
vc:supports ngm:medical-imaging ;
vc:supports ngm:robotic-manipulation ;
vc:uses ngm:checkerboard-pattern ;
vc:uses ngm:fiducial-marker ;
vc:uses ngm:imu ;
vc:uses ngm:lidar .
ngm:calibration-data a skos:Concept ;
rdfs:label "Calibration Data"@en .
ngm:calibration-equipment a owl:Class ;
rdfs:comment "Physical instruments and reference artefacts used to measure, adjust, and verify the accuracy of sensors, displays, and tracking systems in spatial computing deployments. Calibration equipment includes colour reference targets, IMU calibration boards, structured-light patterns, and photometric probes, all of which underpin the geometric and radiometric correctness of XR pipelines."@en ;
rdfs:label "Calibration Equipment"@en ;
rdfs:subClassOf ngm:sc-display-and-rendering ;
skos:broader ngm:sc-display-and-rendering ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:display-metrology ;
vc:relatedTo ngm:photogrammetry ;
vc:slug "calibration-equipment" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:computer-vision ;
vc:supports ngm:sensor-fusion ;
vc:uses ngm:calibration ;
vc:uses ngm:calibration-target .
ngm:calibration-set a skos:Concept ;
rdfs:label "Calibration Set"@en .
ngm:calibration-standards a owl:Class ;
rdfs:comment "Documented specifications and reference materials that establish measurement accuracy requirements, traceability to national standards, and systematic procedures for aligning sensors, displays, and imaging systems to known reference values in XR and computer vision applications."@en ;
rdfs:label "Calibration Standards"@en ;
rdfs:subClassOf ngm:sc-standards-and-interop ;
rdfs:subClassOf ngm:technical-standard ;
rdfs:subClassOf _:r3830 ;
rdfs:subClassOf _:r3831 ;
skos:broader ngm:sc-standards-and-interop ;
vc:bridgesTo ngm:technical-standard ;
vc:enables ngm:accuracy ;
vc:enables ngm:device-alignment ;
vc:enables ngm:quality-assurance ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:reference-materials ;
vc:requires ngm:traceability ;
vc:requires ngm:validation-procedures ;
vc:slug "calibration-standards" ;
vc:sourceDomain "spatial-computing" .
ngm:calibration-system a owl:Class ;
rdfs:comment "A Calibration System is an integrated assembly of hardware targets, measurement instruments, algorithms, and software workflows used to determine and correct systematic errors in sensors, cameras, and measurement devices, establishing a known and traceable relationship between a sensor's raw outputs and the physical quantities they represent. Calibration systems are essential preconditions for accurate spatial measurement, computer vision, robotics, and extended reality applications."@en ;
rdfs:label "Calibration System"@en ;
rdfs:subClassOf ngm:calibration-equipment ;
vc:enables ngm:computer-vision ;
vc:enables ngm:photogrammetry ;
vc:enables ngm:sensor-fusion ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:slam ;
vc:slug "calibration-system" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:imu ;
vc:uses ngm:optical-calibration-target ;
vc:uses ngm:sensor-calibration .
ngm:calibration-target a owl:Class ;
rdfs:comment "A physical or displayed reference pattern with precisely known geometric, photometric, or colorimetric properties used to determine camera intrinsic and extrinsic parameters, enabling accurate lens distortion correction, spatial measurement, and color reproduction in imaging systems."@en ;
rdfs:label "Calibration Target"@en ;
rdfs:subClassOf ngm:reference-standard ;
rdfs:subClassOf ngm:sc-standards-and-interop ;
rdfs:subClassOf _:r3832 ;
rdfs:subClassOf _:r3833 ;
rdfs:subClassOf _:r3834 ;
rdfs:subClassOf _:r3835 ;
skos:broader ngm:sc-standards-and-interop ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:bridgesTo ngm:reference-standard ;
vc:bridgesTo ngm:robotics ;
vc:contrastsWith ngm:scene-geometry ;
vc:enables ngm:3-d-reconstruction ;
vc:enables ngm:camera-calibration ;
vc:enables ngm:color-accuracy ;
vc:enables ngm:lens-distortion-correction ;
vc:enables ngm:pose-estimation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:checkerboard-pattern ;
vc:hasPart ngm:circle-grid ;
vc:hasPart ngm:fiducial-marker ;
vc:isPartOf ngm:camera-calibration-pipeline ;
vc:isPartOf ngm:photogrammetry ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:extrinsic-parameters ;
vc:relatedTo ngm:ground-truth-labels ;
vc:relatedTo ngm:intrinsic-parameters ;
vc:requires ngm:controlled-illumination ;
vc:requires ngm:flatness-control ;
vc:requires ngm:pattern-definition ;
vc:requires ngm:precision-manufacturing ;
vc:slug "calibration-target" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:augmented-reality ;
vc:supports ngm:machine-vision ;
vc:supports ngm:spatial-mapping ;
vc:uses ngm:computer-vision ;
vc:uses ngm:image-processing .
ngm:calibration-tools a owl:Class ;
rdfs:comment "Software and hardware utilities used to align, tune, and verify the accuracy of XR sensors, displays, and tracking systems. Calibration establishes ground-truth references for IMUs, cameras, optical tracking arrays, and display geometry, ensuring that virtual content is correctly registered to the physical world and that tracking data is within acceptable error tolerances."@en ;
rdfs:label "Calibration Tools"@en ;
rdfs:subClassOf ngm:sc-display-and-rendering ;
rdfs:subClassOf _:r3836 ;
skos:broader ngm:sc-display-and-rendering ;
vc:enables ngm:augmented-reality ;
vc:enables ngm:mixed-reality ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:requires ngm:rendering-pipeline ;
vc:slug "calibration-tools" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:environmental-verification ;
vc:supports ngm:optical-tracking ;
vc:supports ngm:xr-runtime-environment ;
vc:uses ngm:imu ;
vc:uses ngm:photogrammetry .
ngm:calibration-traceability a owl:Class ;
rdfs:label "Calibration Traceability"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-data-quality ;
vc:slug "calibration-traceability" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:california-ai-bill a owl:Class ;
rdfs:comment "California AI bill is the collective designation for a sequence of California state legislative instruments enacted or proposed between 2023 and 2026 to regulate the development, deployment, and disclosure obligations of large-scale Frontier Models — most prominently Senate Bill 1047 (SB 1047..."@en ;
rdfs:label "California AI bill"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:ai-regulation ;
rdfs:subClassOf ngm:frontier-model-governance ;
rdfs:subClassOf ngm:legislative-instrument ;
rdfs:subClassOf ngm:state-law ;
rdfs:subClassOf ngm:technology-policy ;
rdfs:subClassOf _:r3841 ;
rdfs:subClassOf _:r3842 ;
rdfs:subClassOf _:r3843 ;
rdfs:subClassOf _:r3844 ;
rdfs:subClassOf _:r3845 ;
rdfs:subClassOf _:r3846 ;
rdfs:subClassOf _:r3847 ;
rdfs:subClassOf _:r3848 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:contrastsWith ngm:eu-ai-act-regulatory-instrument ;
vc:contrastsWith ngm:federal-ai-policy ;
vc:contrastsWith ngm:nist-ai-rmf ;
vc:contrastsWith ngm:risk-based-regulation ;
vc:contrastsWith ngm:self-regulation ;
vc:contrastsWith ngm:voluntary-ai-commitments ;
vc:dependsOn ngm:california-department-of-justice ;
vc:dependsOn ngm:california-legislature ;
vc:dependsOn ngm:california-office-of-emergency-services ;
vc:dependsOn ngm:ccpa ;
vc:dependsOn ngm:governor-of-california ;
vc:dependsOn ngm:iso-iec-42001 ;
vc:dependsOn ngm:nist-ai-rmf ;
vc:enables ngm:ai-safety-transparency ;
vc:enables ngm:algorithmic-accountability ;
vc:enables ngm:consumer-privacy-in-ai ;
vc:enables ngm:healthcare-ai-accountability ;
vc:enables ngm:incident-reporting ;
vc:enables ngm:training-data-disclosure ;
vc:enables ngm:whistleblower-protection ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ab-1008 ;
vc:hasPart ngm:ab-2013 ;
vc:hasPart ngm:ab-489 ;
vc:hasPart ngm:compliance ;
vc:hasPart ngm:frontier-ai-framework ;
vc:hasPart ngm:frontier-model-division ;
vc:hasPart ngm:incident-reporting ;
vc:hasPart ngm:kill-switch-mandate ;
vc:hasPart ngm:sb-1047 ;
vc:hasPart ngm:sb-53 ;
vc:hasPart ngm:sb-942 ;
vc:hasPart ngm:whistleblower-protection ;
vc:implements ngm:ai-governance ;
vc:implements ngm:critical-harm-framework ;
vc:implements ngm:dual-threshold-regulation ;
vc:implements ngm:pre-deployment-safety-checks ;
vc:implements ngm:transparency ;
vc:implements ngm:whistleblower-protection ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:ai-alliance ;
vc:relatedTo ngm:ai-regulation ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:algorithmic-accountability ;
vc:relatedTo ngm:anthropic ;
vc:relatedTo ngm:california-attorney-general ;
vc:relatedTo ngm:california-effect ;
vc:relatedTo ngm:california-legislature ;
vc:relatedTo ngm:california-office-of-emergency-services ;
vc:relatedTo ngm:center-for-ai-safety ;
vc:relatedTo ngm:compute-threshold ;
vc:relatedTo ngm:dan-hendrycks ;
vc:relatedTo ngm:dario-amodei ;
vc:relatedTo ngm:elon-musk ;
vc:relatedTo ngm:eu-ai-act-regulatory-instrument ;
vc:relatedTo ngm:federal-preemption ;
vc:relatedTo ngm:frontier-models ;
vc:relatedTo ngm:gavin-newsom ;
vc:relatedTo ngm:gdpr ;
vc:relatedTo ngm:geoffrey-hinton ;
vc:relatedTo ngm:google-ai-technology-corporation ;
vc:relatedTo ngm:google-ai-technology-corporation-deep-mind ;
vc:relatedTo ngm:iso-iec-jtc-1-sc-42 ;
vc:relatedTo ngm:kill-switch ;
vc:relatedTo ngm:liability ;
vc:relatedTo ngm:machine-unlearning ;
vc:relatedTo ngm:marc-andreessen ;
vc:relatedTo ngm:meta-ai ;
vc:relatedTo ngm:nist ;
vc:relatedTo ngm:nist-ai-rmf ;
vc:relatedTo ngm:open-source-ai ;
vc:relatedTo ngm:openai-research-organisation ;
vc:relatedTo ngm:regulatory-capture ;
vc:relatedTo ngm:sb-1047 ;
vc:relatedTo ngm:sb-53 ;
vc:relatedTo ngm:scaling-laws ;
vc:relatedTo ngm:scott-wiener ;
vc:relatedTo ngm:technology-policy ;
vc:relatedTo ngm:training-data-transparency ;
vc:relatedTo ngm:whistleblower-protection ;
vc:relatedTo ngm:yann-lecun ;
vc:relatedTo ngm:yoshua-bengio ;
vc:requires ngm:attorney-general-enforcement ;
vc:requires ngm:compute-threshold ;
vc:requires ngm:frontier-models ;
vc:requires ngm:liability-framework ;
vc:requires ngm:revenue-threshold ;
vc:requires ngm:safety-evaluation ;
vc:requires ngm:training-data-documentation ;
vc:slug "california-ai-bill" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:california-attorney-general ;
vc:standardizedBy ngm:california-legislature ;
vc:standardizedBy ngm:california-office-of-emergency-services ;
vc:standardizedBy ngm:iso-iec-jtc1-sc42 ;
vc:standardizedBy ngm:nist ;
vc:supports ngm:ai-safety ;
vc:supports ngm:algorithmic-accountability ;
vc:supports ngm:consumer-protection ;
vc:supports ngm:federal-preemption-debate ;
vc:supports ngm:open-source-ai ;
vc:supports ngm:startup-ecosystem ;
vc:uses ngm:c2-pa-content-credentials ;
vc:uses ngm:catastrophic-risk-assessment ;
vc:uses ngm:flop-threshold ;
vc:uses ngm:iso-iec-42001 ;
vc:uses ngm:nist-sp-800-series ;
vc:uses ngm:revenue-threshold ;
vc:uses ngm:third-party-safety-audit .
ngm:california-attorney-general a skos:Concept ;
rdfs:label "California Attorney General"@en .
ngm:california-department-of-justice a skos:Concept ;
rdfs:label "California Department Of Justice"@en .
ngm:california-effect a skos:Concept ;
rdfs:label "California Effect"@en .
ngm:california-legislature a skos:Concept ;
rdfs:label "California Legislature"@en .
ngm:california-office-of-emergency-services a skos:Concept ;
rdfs:label "California Office Of Emergency Services"@en .
ngm:california-sb53 a skos:Concept ;
rdfs:label "California Sb53"@en .
ngm:call-centres a owl:Class ;
rdfs:comment "Call Centres (contact centres — the operationally preferred modern term reflecting multichannel reality) are coordinated operational environments in which human agents and increasingly autonomous AI Agents handle inbound and outbound customer communications across voice, chat, email, social m..."@en ;
rdfs:label "Call Centres"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:conversational-ai ;
rdfs:subClassOf ngm:customer-service-automation ;
rdfs:subClassOf ngm:enterprise-ai ;
rdfs:subClassOf ngm:human-in-the-loop-learning ;
rdfs:subClassOf ngm:operational-ai ;
rdfs:subClassOf _:r3849 ;
rdfs:subClassOf _:r3850 ;
rdfs:subClassOf _:r3851 ;
rdfs:subClassOf _:r3852 ;
rdfs:subClassOf _:r3853 ;
rdfs:subClassOf _:r3854 ;
rdfs:subClassOf _:r3855 ;
rdfs:subClassOf _:r3856 ;
rdfs:subClassOf _:r3857 ;
rdfs:subClassOf _:r3858 ;
rdfs:subClassOf _:r3859 ;
rdfs:subClassOf _:r3860 ;
rdfs:subClassOf _:r3861 ;
rdfs:subClassOf _:r3862 ;
rdfs:subClassOf _:r3863 ;
rdfs:subClassOf _:r3864 ;
rdfs:subClassOf _:r3865 ;
skos:broader ngm:ai-application ;
vc:contrastsWith ngm:manual-quality-assurance ;
vc:contrastsWith ngm:on-premises-pbx ;
vc:contrastsWith ngm:outsourcing ;
vc:contrastsWith ngm:random-call-sampling ;
vc:contrastsWith ngm:traditional-ivr ;
vc:dependsOn ngm:cloud-infrastructure ;
vc:dependsOn ngm:dialogue-state-tracking ;
vc:dependsOn ngm:intent-classification ;
vc:dependsOn ngm:large-language-models ;
vc:dependsOn ngm:natural-language-processing ;
vc:dependsOn ngm:speech-recognition ;
vc:dependsOn ngm:telephony-infrastructure ;
vc:dependsOn ngm:transformer-architecture ;
vc:enables ngm:24-7-customer-service ;
vc:enables ngm:agent-productivity-augmentation ;
vc:enables ngm:automated-quality-monitoring ;
vc:enables ngm:customer-support ;
vc:enables ngm:proactive-customer-outreach ;
vc:enables ngm:tier-1-contact-deflection ;
vc:enables ngm:workforce-scheduling-optimisation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:agent-assist ;
vc:hasPart ngm:automatic-call-distribution ;
vc:hasPart ngm:contact-centre-as-a-service ;
vc:hasPart ngm:crm-integration ;
vc:hasPart ngm:intent-classification ;
vc:hasPart ngm:interactive-voice-response ;
vc:hasPart ngm:knowledge-base ;
vc:hasPart ngm:omnichannel ;
vc:hasPart ngm:quality-assurance ;
vc:hasPart ngm:real-time-transcription ;
vc:hasPart ngm:sentiment-analysis ;
vc:hasPart ngm:workforce-management ;
vc:implements ngm:ai-agents ;
vc:implements ngm:conversational-ai ;
vc:implements ngm:crm ;
vc:implements ngm:natural-language-processing ;
vc:implements ngm:omnichannel-routing ;
vc:implements ngm:robotic-process-automation ;
vc:implements ngm:sentiment-analysis ;
vc:implements ngm:speech-recognition ;
vc:implements ngm:workforce-management ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:ai-agents ;
vc:relatedTo ngm:automatic-speech-recognition ;
vc:relatedTo ngm:chatbots ;
vc:relatedTo ngm:contact-centre-as-a-service ;
vc:relatedTo ngm:conversational-ai ;
vc:relatedTo ngm:crm ;
vc:relatedTo ngm:customer-service-automation ;
vc:relatedTo ngm:digital-transformation ;
vc:relatedTo ngm:knowledge-management ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:omnichannel ;
vc:relatedTo ngm:predictive-analytics ;
vc:relatedTo ngm:real-time-transcription ;
vc:relatedTo ngm:robotic-process-automation ;
vc:relatedTo ngm:sentiment-analysis ;
vc:relatedTo ngm:speech-recognition ;
vc:relatedTo ngm:text-to-speech ;
vc:relatedTo ngm:workforce-management ;
vc:requires ngm:cloud-infrastructure ;
vc:requires ngm:identity-verification ;
vc:requires ngm:intent-classification ;
vc:requires ngm:large-language-models ;
vc:requires ngm:natural-language-processing ;
vc:requires ngm:real-time-transcription ;
vc:requires ngm:speech-recognition ;
vc:requires ngm:telephony-infrastructure ;
vc:slug "call-centres" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:fca-consumer-duty ;
vc:standardizedBy ngm:fca-sysc-rules ;
vc:standardizedBy ngm:gdpr ;
vc:standardizedBy ngm:ico-workplace-monitoring-guidance ;
vc:standardizedBy ngm:iso-18295-contact-centre-standard ;
vc:standardizedBy ngm:pci-dss ;
vc:standardizedBy ngm:uk-gdpr ;
vc:supports ngm:agent-wellbeing ;
vc:supports ngm:average-handle-time-reduction ;
vc:supports ngm:compliance-monitoring ;
vc:supports ngm:csat-improvement ;
vc:supports ngm:customer-experience ;
vc:supports ngm:first-contact-resolution ;
vc:supports ngm:regulatory-reporting ;
vc:uses ngm:ai-agents ;
vc:uses ngm:biometric-authentication ;
vc:uses ngm:chatbots ;
vc:uses ngm:conversational-ai ;
vc:uses ngm:crm ;
vc:uses ngm:knowledge-base ;
vc:uses ngm:omnichannel ;
vc:uses ngm:real-time-transcription ;
vc:uses ngm:robotic-process-automation ;
vc:uses ngm:sentiment-analysis ;
vc:uses ngm:workforce-management .
ngm:call-graph-analysis a skos:Concept ;
rdfs:label "Call Graph Analysis"@en .
ngm:callback-system a skos:Concept ;
rdfs:label "Callback System"@en .
ngm:calldata a owl:Class ;
rdfs:comment "Calldata is the read-only, immutable byte array supplied with a transaction or message call on the Ethereum Virtual Machine, carrying the function selector and ABI-encoded arguments that tell a smart contract what to execute. Because it lives outside contract storage and is comparatively cheap to include, calldata is the primary channel through which external inputs reach contracts. It is especially significant for rollups, which post compressed transaction batches as calldata to the base layer to inherit its data availability and security."@en ;
rdfs:label "Calldata"@en ;
rdfs:subClassOf ngm:transaction ;
rdfs:subClassOf _:r3866 ;
vc:contrastsWith ngm:eip-4844 ;
vc:dependsOn ngm:ethereum ;
vc:enables ngm:data-availability ;
vc:enables ngm:rollup ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:transaction ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-availability ;
vc:relatedTo ngm:transaction ;
vc:requires ngm:gas ;
vc:slug "calldata" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:optimistic-rollup ;
vc:supports ngm:smart-contract ;
vc:uses ngm:ethereum-smart-contract-platform-virtual-machine ;
vc:uses ngm:gas .
ngm:calldata-compression a owl:Class ;
rdfs:comment "Calldata compression is the practice of encoding transaction data more compactly before posting it as calldata to a base-layer blockchain, reducing the number of bytes that must be paid for and stored. Rollups such as Arbitrum and Base apply techniques including signature aggregation, zero-byte-heavy encoding and custom serialisation formats to shrink batch size. Because calldata gas cost dominates rollup transaction fees, compression directly reduces the cost of settling Layer 2 state on the base chain."@en ;
rdfs:label "Calldata Compression"@en ;
rdfs:subClassOf ngm:calldata ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "calldata-compression" ;
vc:sourceDomain "blockchain" .
ngm:calldata-execution a skos:Concept ;
rdfs:label "Calldata Execution"@en .
ngm:calle-callebtc a skos:Concept ;
rdfs:label "Calle Callebtc"@en .
ngm:calvin a skos:Concept ;
rdfs:label "Calvin"@en .
ngm:cambridge-biosecurity-hub a skos:Concept ;
rdfs:label "Cambridge Biosecurity Hub"@en .
ngm:cambridge-bitcoin-electricity-consumption-index a owl:Class ;
rdfs:comment "An index published by the University of Cambridge that estimates the electricity consumption of the Bitcoin network from mining hardware efficiency and network hashrate. It provides a transparent methodology and range of estimates rather than a single fixed figure."@en ;
rdfs:label "Cambridge Bitcoin Electricity Consumption Index"@en ;
rdfs:subClassOf ngm:bitcoin-proof-of-work-protocol-mining ;
rdfs:subClassOf _:r3867 ;
vc:bridgesTo ngm:bitcoin-proof-of-work-protocol-network ;
vc:bridgesTo ngm:sustainability ;
vc:enables ngm:carbon-accounting ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:mining ;
vc:slug "cambridge-bitcoin-electricity-consumption-index" ;
vc:sourceDomain "blockchain" .
ngm:cambridge-centre-for-ai-in-medicine a skos:Concept ;
rdfs:label "Cambridge Centre For AI In Medicine"@en .
ngm:cambridge-centre-for-alternative-finance a owl:Class ;
rdfs:comment "The Cambridge Centre for Alternative Finance (CCAF) is an interdisciplinary research centre at the University of Cambridge Judge Business School that conducts empirical studies on financial instruments and channels operating outside conventional banking systems. It is globally recognised for producing landmark indices and benchmark datasets on cryptoasset markets, distributed ledger technology adoption, digital payments, and the energy consumption of proof-of-work networks. CCAF research informs regulatory policy, industry strategy, and academic discourse through rigorous survey-based methodologies and open data publications. Its work bridges fintech innovation, environmental sustainability analysis, and international financial governance."@en ;
rdfs:label "Cambridge Centre for Alternative Finance"@en ;
rdfs:subClassOf ngm:financial-infrastructure ;
rdfs:subClassOf _:r3868 ;
rdfs:subClassOf _:r3869 ;
rdfs:subClassOf _:r3870 ;
rdfs:subClassOf _:r3871 ;
rdfs:subClassOf _:r3872 ;
vc:bridgesTo ngm:bitcoin-proof-of-work-protocol-environmental-issues ;
vc:bridgesTo ngm:de-fi ;
vc:bridgesTo ngm:energy-consumption ;
vc:contrastsWith ngm:financial-system ;
vc:contrastsWith ngm:traditional-banking ;
vc:dependsOn ngm:blockchain-network ;
vc:dependsOn ngm:open-data ;
vc:enables ngm:cryptoasset-regulatory-framework ;
vc:enables ngm:cryptocurrency-regulation ;
vc:enables ngm:fintech-benchmarking ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:cambridge-bitcoin-electricity-consumption-index ;
vc:hasPart ngm:global-alternative-finance-market-benchmarking-report ;
vc:hasPart ngm:global-cryptoasset-benchmarking-study ;
vc:isPartOf ngm:cambridge-judge-business-school ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:alternative-finance ;
vc:relatedTo ngm:crowdfunding ;
vc:relatedTo ngm:cryptocurrency ;
vc:requires ngm:data-collection ;
vc:requires ngm:research-methods ;
vc:slug "cambridge-centre-for-alternative-finance" ;
vc:sourceDomain "finance" ;
vc:supports ngm:central-bank-digital-currency-cbdc ;
vc:supports ngm:financial-regulation ;
vc:supports ngm:sustainable-finance ;
vc:uses ngm:distributed-ledger-technology ;
vc:uses ngm:peer-to-peer-trading ;
vc:uses ngm:proof-of-work .
ngm:cambridge-centre-for-alternative-finance-mining-reports a skos:Concept ;
rdfs:label "Cambridge Centre For Alternative Finance Mining Reports"@en .
ngm:cambridge-cluster a skos:Concept ;
rdfs:label "Cambridge Cluster"@en .
ngm:cambridge-cser a skos:Concept ;
rdfs:label "Cambridge Cser"@en .
ngm:cambridge-judge-business-school a owl:Class ;
rdfs:comment "Cambridge Judge Business School is the business school of the University of Cambridge, located in Cambridge, England. It conducts research and teaching in management, finance and alternative finance."@en ;
rdfs:label "Cambridge Judge Business School"@en ;
rdfs:subClassOf ngm:university-of-cambridge ;
vc:bridgesTo ngm:economics ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:slug "cambridge-judge-business-school" ;
vc:sourceDomain "finance" .
ngm:cambridge-university-press-ergodic-theory-and-dynamical-systems-journal a skos:Concept ;
rdfs:label "Cambridge University Press Ergodic Theory And Dynamical Systems Journal"@en .
ngm:camenisch-lysyanskaya-signature a skos:Concept ;
rdfs:label "Camenisch Lysyanskaya Signature"@en .
ngm:camenisch-lysyanskaya-signatures a skos:Concept ;
rdfs:label "Camenisch Lysyanskaya Signatures"@en .
ngm:camera a owl:Class ;
rdfs:comment "An imaging sensor device that captures visual information in robotics and spatial-computing systems, enabling computer vision applications including object detection, SLAM, 3D reconstruction, visual servoing, and semantic scene understanding through various modalities (RGB, depth, thermal, event-based) and sensor technologies (CCD, CMOS, ToF, structured light)."@en ;
rdfs:label "Camera"@en ;
rdfs:subClassOf ngm:sensor ;
rdfs:subClassOf ngm:visualperception ;
rdfs:subClassOf _:r3884 ;
rdfs:subClassOf _:r3885 ;
rdfs:subClassOf _:r3886 ;
rdfs:subClassOf _:r3887 ;
vc:bridgesTo ngm:augmented-reality ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:spatial-computing ;
vc:contrastsWith ngm:lidar ;
vc:contrastsWith ngm:radar ;
vc:dependsOn ngm:computer-vision ;
vc:enables ngm:3-d-reconstruction ;
vc:enables ngm:3dreconstruction ;
vc:enables ngm:depth-estimation ;
vc:enables ngm:object-detection ;
vc:enables ngm:semantic-segmentation ;
vc:enables ngm:slam ;
vc:enables ngm:visual-odometry ;
vc:enables ngm:visual-servoing ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:camera-calibration ;
vc:hasPart ngm:image-sensor ;
vc:hasPart ngm:imagesensor ;
vc:hasPart ngm:lens ;
vc:hasPart ngm:processingunit ;
vc:implements ngm:visual-perception ;
vc:isPartOf ngm:robot-perception ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:neural-radiance-field ;
vc:relatedTo ngm:structure-from-motion ;
vc:requires ngm:optical-systems ;
vc:slug "camera" ;
vc:sourceDomain "robotics" ;
vc:standardizedBy ngm:ieee ;
vc:standardizedBy ngm:iso-iec ;
vc:uses ngm:convolutional-neural-network .
ngm:camera-actuators a skos:Concept ;
rdfs:label "Camera Actuators"@en .
ngm:camera-array a skos:Concept ;
rdfs:label "Camera Array"@en .
ngm:camera-calibration a owl:Class ;
rdfs:comment "Camera calibration is the process of estimating a camera's intrinsic parameters — focal length, principal point, pixel skew, and radial and tangential distortion coefficients — and, when multiple sensors are involved, extrinsic parameters describing the rigid-body transformation (rotation and translation) between coordinate frames. Accurate calibration is a prerequisite for metrically correct 3D reconstruction, stereo depth estimation, augmented-reality overlay registration, and robot visual servoing. The Zhang method, which solves for camera parameters from multiple images of a planar chessboard target via non-linear reprojection-error minimisation, is the dominant practical technique and is standardised in OpenCV and MATLAB's Computer Vision Toolbox. Calibration quality must be maintained over a device's operational lifetime, driving development of online self-calibration methods that exploit ego-motion and scene structure."@en ;
rdfs:label "Camera Calibration"@en ;
rdfs:subClassOf ngm:computer-vision ;
rdfs:subClassOf _:r3873 ;
rdfs:subClassOf _:r3874 ;
rdfs:subClassOf _:r3875 ;
vc:bridgesTo ngm:autonomous-vehicle ;
vc:bridgesTo ngm:lidar ;
vc:bridgesTo ngm:robotics-perception ;
vc:contrastsWith ngm:calibration ;
vc:contrastsWith ngm:radiometric-calibration ;
vc:dependsOn ngm:corner-detection ;
vc:dependsOn ngm:feature-detection ;
vc:enables ngm:3-d-reconstruction ;
vc:enables ngm:augmented-reality ;
vc:enables ngm:depth-estimation ;
vc:enables ngm:photogrammetry ;
vc:enables ngm:pose-estimation ;
vc:enables ngm:visual-odometry ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:epipolar-geometry ;
vc:relatedTo ngm:open-cv ;
vc:relatedTo ngm:projective-geometry ;
vc:requires ngm:camera ;
vc:requires ngm:image-processing ;
vc:requires ngm:optimisation ;
vc:slug "camera-calibration" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:sensor-fusion ;
vc:supports ngm:slam ;
vc:supports ngm:stereo-vision ;
vc:supports ngm:structure-from-motion ;
vc:uses ngm:chessboard-pattern ;
vc:uses ngm:homography ;
vc:uses ngm:non-linear-least-squares .
ngm:camera-calibration-pipeline a skos:Concept ;
rdfs:label "Camera Calibration Pipeline"@en .
ngm:camera-definition a skos:Concept ;
rdfs:label "Camera Definition"@en .
ngm:camera-extrinsics a skos:Concept ;
rdfs:label "Camera Extrinsics"@en .
ngm:camera-hardware a skos:Concept ;
rdfs:label "Camera Hardware"@en .
ngm:camera-intrinsics a owl:Class ;
rdfs:comment "Camera Intrinsics are the internal optical and geometric parameters of a camera that define the mathematical relationship between 3D points in the camera's coordinate frame and their 2D projections onto the image sensor. The intrinsic parameter matrix encodes focal length in pixel units along each image axis, the principal point (optical axis intersection with the sensor), and skew, whilst associated distortion coefficients correct for lens aberrations that cause deviations from the ideal pinhole projection model."@en ;
rdfs:label "Camera Intrinsics"@en ;
rdfs:subClassOf ngm:computer-vision ;
rdfs:subClassOf _:r3876 ;
vc:bridgesTo ngm:augmented-reality ;
vc:bridgesTo ngm:robotics ;
vc:contrastsWith ngm:camera-extrinsics ;
vc:enables ngm:depth-estimation ;
vc:enables ngm:photogrammetry ;
vc:enables ngm:pose-estimation ;
vc:enables ngm:stereo-vision ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:lens-distortion-model ;
vc:isPartOf ngm:camera-model ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:epipolar-geometry ;
vc:relatedTo ngm:optical-flow ;
vc:relatedTo ngm:simultaneous-localisation-and-mapping ;
vc:relatedTo ngm:structure-from-motion ;
vc:requires ngm:camera-calibration ;
vc:slug "camera-intrinsics" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:optical-calibration-target ;
vc:uses ngm:pinhole-camera-model ;
vc:uses ngm:projective-geometry ;
vc:uses ngm:sensor-calibration .
ngm:camera-model a owl:Class ;
rdfs:comment "A camera model is a mathematical description that maps three-dimensional scene points to two-dimensional image coordinates, capturing the geometry of how a camera projects the world. It encodes intrinsic parameters such as focal length and principal point alongside extrinsic parameters describing pose, and may model lens distortion. Camera models underpin calibration, reconstruction and pose estimation in computer vision and spatial computing."@en ;
rdfs:label "Camera Model"@en ;
rdfs:subClassOf ngm:computer-vision ;
rdfs:subClassOf _:r3877 ;
rdfs:subClassOf _:r3878 ;
vc:dependsOn ngm:linear-algebra ;
vc:enables ngm:depth-estimation ;
vc:enables ngm:pose-estimation ;
vc:enables ngm:structure-from-motion ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:computer-vision ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:computer-vision ;
vc:relatedTo ngm:photogrammetry ;
vc:relatedTo ngm:stereo-vision ;
vc:requires ngm:camera-calibration ;
vc:requires ngm:linear-algebra ;
vc:slug "camera-model" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:augmented-reality ;
vc:supports ngm:slam ;
vc:uses ngm:photogrammetry .
ngm:camera-models a skos:Concept ;
rdfs:label "Camera Models"@en .
ngm:camera-node a skos:Concept ;
rdfs:label "Camera Node"@en .
ngm:camera-parameters a owl:Class ;
rdfs:comment "The intrinsic and extrinsic mathematical values that define a camera's optical characteristics and spatial positioning, comprising focal length, optical center, distortion coefficients (intrinsic) and rotation/translation relative to world coordinates (extrinsic), essential for 3D reconstruction ..."@en ;
rdfs:label "Camera Parameters"@en ;
rdfs:subClassOf ngm:imaging-parameters ;
rdfs:subClassOf ngm:sc-display-and-rendering ;
rdfs:subClassOf _:r3879 ;
rdfs:subClassOf _:r3880 ;
rdfs:subClassOf _:r3881 ;
skos:broader ngm:sc-display-and-rendering ;
vc:bridgesTo ngm:computer-vision ;
vc:enables ngm:3-d-reconstruction ;
vc:enables ngm:object-measurement ;
vc:enables ngm:scene-localization ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:calibration-target ;
vc:requires ngm:camera-calibration ;
vc:requires ngm:optimisation-algorithm ;
vc:slug "camera-parameters" ;
vc:sourceDomain "spatial-computing" .
ngm:camera-pose-estimation a skos:Concept ;
rdfs:label "Camera Pose Estimation"@en .
ngm:camera-sensor a owl:Class ;
rdfs:comment "A camera sensor is the photosensitive component, typically a CMOS or CCD array, that converts incident light focused by the optics into an electrical signal forming an image. Its characteristics, including resolution, pixel size, dynamic range, noise and frame rate, determine the quality of the captured imagery and shutter behaviour. It is the primary exteroceptive vision input for robots, autonomous vehicles and immersive devices, and is frequently fused with complementary sensors such as lidar."@en ;
rdfs:label "Camera Sensor"@en ;
rdfs:subClassOf ngm:sensor ;
rdfs:subClassOf _:r3882 ;
rdfs:subClassOf _:r3883 ;
vc:bridgesTo ngm:sensor-fusion ;
vc:contrastsWith ngm:lidar ;
vc:enables ngm:computer-vision ;
vc:enables ngm:perception ;
vc:enables ngm:visual-perception ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:camera ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:sensor ;
vc:relatedTo ngm:stereo-camera ;
vc:requires ngm:camera-calibration ;
vc:requires ngm:image-sensor ;
vc:slug "camera-sensor" ;
vc:sourceDomain "robotics" ;
vc:supports ngm:hand-tracking ;
vc:supports ngm:object-detection ;
vc:uses ngm:image-processing .
ngm:camera-systems a skos:Concept ;
rdfs:label "Camera Systems"@en .
ngm:camera-tracking a owl:Class ;
rdfs:comment "Camera Tracking is the process of continuously estimating the position and orientation (pose) of a camera in 3D space relative to a fixed reference frame or scene, typically using image feature analysis, optical flow, or fiducial marker detection. It underpins augmented reality, visual effects compositing, robotic navigation, and autonomous vehicle perception by enabling virtual or computed elements to be correctly registered to the physical world as the camera moves."@en ;
rdfs:label "Camera Tracking"@en ;
rdfs:subClassOf ngm:motion-tracking ;
vc:enables ngm:augmented-reality ;
vc:enables ngm:slam ;
vc:enables ngm:visual-odometry ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:epipolar-geometry ;
vc:relatedTo ngm:pose-estimation ;
vc:slug "camera-tracking" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:feature-detection ;
vc:uses ngm:marker-based-tracking ;
vc:uses ngm:optical-flow .
ngm:camera-tracking-system a owl:Class ;
rdfs:comment "A camera tracking system is a hardware and software assembly that continuously records the position, orientation, and lens parameters of a physical camera in three-dimensional space, transmitting this data in real time to rendering or compositing engines so that computer-generated imagery can be seamlessly integrated with live-action footage. Such systems underpin virtual production stages, augmented reality overlays, broadcast graphics, and visual effects pipelines. Tracking technologies include optical encoder arrays, inertial measurement units, infrared LED constellations, machine vision fiducial markers, and LiDAR-based spatial mapping."@en ;
rdfs:label "Camera Tracking System"@en ;
rdfs:subClassOf ngm:camera-tracking ;
vc:enables ngm:augmented-reality ;
vc:enables ngm:spatial-anchoring ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:camera-parameters ;
vc:slug "camera-tracking-system" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:camera-calibration ;
vc:uses ngm:camera-intrinsics ;
vc:uses ngm:motion-capture .
ngm:can-bus a owl:Class ;
rdfs:comment "CAN Bus (Controller Area Network) is a reliable serial communication standard that lets microcontrollers and devices exchange messages over a shared two-wire bus without a host computer, widely used in vehicles and robotics."@en ;
rdfs:label "CAN Bus"@en ;
rdfs:subClassOf ngm:communication-protocol ;
rdfs:subClassOf _:r3699 ;
vc:bridgesTo ngm:micro-ros ;
vc:bridgesTo ngm:power-electronics ;
vc:enables ngm:motor-driver ;
vc:enables ngm:real-time-control ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:embedded-systems ;
vc:slug "can-bus" ;
vc:sourceDomain "robotics" .
ngm:can-fd-bus a skos:Concept ;
rdfs:label "Can Fd Bus"@en .
ngm:can-fd-protocol a skos:Concept ;
rdfs:label "Can Fd Protocol"@en .
ngm:canaan a owl:Class ;
rdfs:comment "Canaan is a Chinese company that designs and produces Bitcoin mining hardware under the Avalon brand. It is a publicly listed manufacturer of ASIC machines."@en ;
rdfs:label "Canaan"@en ;
rdfs:subClassOf ngm:asic ;
rdfs:subClassOf _:r3888 ;
vc:bridgesTo ngm:hardware ;
vc:enables ngm:transaction-validation ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:bitcoin-proof-of-work-protocol-mining ;
vc:slug "canaan" ;
vc:sourceDomain "blockchain" .
ngm:canada-aida a skos:Concept ;
rdfs:label "Canada Aida"@en .
ngm:canary-deployment a owl:Class ;
rdfs:comment "Canary deployment is a progressive release strategy in which a new version of a service or model is exposed to a small subset of traffic before being rolled out more widely. Operators monitor health, performance and quality metrics on the canary cohort, promoting the release only if it behaves acceptably and otherwise rolling back. It limits the blast radius of a faulty change and is widely used in continuous delivery pipelines and in serving machine-learning models."@en ;
rdfs:label "Canary Deployment"@en ;
rdfs:subClassOf ngm:continuous-deployment ;
rdfs:subClassOf ngm:deployment-strategy ;
rdfs:subClassOf ngm:progressive-delivery ;
rdfs:subClassOf ngm:release-engineering ;
rdfs:subClassOf _:r3889 ;
rdfs:subClassOf _:r3890 ;
rdfs:subClassOf _:r3891 ;
rdfs:subClassOf _:r3892 ;
rdfs:subClassOf _:r3893 ;
rdfs:subClassOf _:r3894 ;
rdfs:subClassOf _:r3895 ;
rdfs:subClassOf _:r3896 ;
rdfs:subClassOf _:r3897 ;
rdfs:subClassOf _:r3898 ;
vc:contrastsWith ngm:a-b-testing ;
vc:contrastsWith ngm:big-bang-deployment ;
vc:contrastsWith ngm:blue-green-deployment ;
vc:contrastsWith ngm:rolling-deployment ;
vc:contrastsWith ngm:shadow-deployment ;
vc:dependsOn ngm:ci-cd ;
vc:dependsOn ngm:container-orchestration ;
vc:dependsOn ngm:kubernetes ;
vc:dependsOn ngm:prometheus ;
vc:dependsOn ngm:service-mesh ;
vc:dependsOn ngm:telemetry ;
vc:enables ngm:automated-promotion ;
vc:enables ngm:blast-radius-control ;
vc:enables ngm:continuous-deployment ;
vc:enables ngm:controlled-rollout ;
vc:enables ngm:model-serving ;
vc:enables ngm:risk-mitigation ;
vc:enables ngm:zero-downtime-deployment ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:a-b-testing ;
vc:hasPart ngm:analysis-template ;
vc:hasPart ngm:canary-weight-configuration ;
vc:hasPart ngm:metric-collection ;
vc:hasPart ngm:observability ;
vc:hasPart ngm:promotion-gate ;
vc:hasPart ngm:rollback-mechanism ;
vc:hasPart ngm:traffic-splitting ;
vc:implements ngm:continuous-deployment ;
vc:implements ngm:progressive-delivery ;
vc:implements ngm:release-strategy ;
vc:implements ngm:staged-rollout ;
vc:isPartOf ngm:ci-cd ;
vc:isPartOf ngm:continuous-deployment ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:a-b-testing ;
vc:relatedTo ngm:dark-launch ;
vc:relatedTo ngm:devops ;
vc:relatedTo ngm:dora-metrics ;
vc:relatedTo ngm:feature-flags ;
vc:relatedTo ngm:gitops ;
vc:relatedTo ngm:infrastructure-as-code ;
vc:relatedTo ngm:kubernetes ;
vc:relatedTo ngm:ring-deployment ;
vc:relatedTo ngm:shadow-deployment ;
vc:requires ngm:automated-testing ;
vc:requires ngm:ci-cd ;
vc:requires ngm:continuous-integration ;
vc:requires ngm:monitoring ;
vc:requires ngm:observability ;
vc:requires ngm:service-mesh ;
vc:requires ngm:telemetry ;
vc:requires ngm:version-control ;
vc:slug "canary-deployment" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:argo-project ;
vc:standardizedBy ngm:cncf ;
vc:standardizedBy ngm:do-ra ;
vc:standardizedBy ngm:google-sre ;
vc:supports ngm:devops ;
vc:supports ngm:gitops ;
vc:supports ngm:mlops ;
vc:supports ngm:model-deployment ;
vc:supports ngm:platform-engineering ;
vc:supports ngm:site-reliability-engineering ;
vc:uses ngm:argo-rollouts ;
vc:uses ngm:datadog ;
vc:uses ngm:feature-flags ;
vc:uses ngm:flagger ;
vc:uses ngm:istio ;
vc:uses ngm:kserve ;
vc:uses ngm:kubernetes ;
vc:uses ngm:observability ;
vc:uses ngm:prometheus ;
vc:uses ngm:seldon-core .
ngm:canary-weight-configuration a skos:Concept ;
rdfs:label "Canary Weight Configuration"@en .
ngm:cancer-detection a skos:Concept ;
rdfs:label "Cancer Detection"@en .
ngm:cancer-genomics a skos:Concept ;
rdfs:label "Cancer Genomics"@en .
ngm:candidate-generation a skos:Concept ;
rdfs:label "Candidate Generation"@en .
ngm:canny-edge-detection a skos:Concept ;
rdfs:label "Canny Edge Detection"@en .
ngm:canonical-json a owl:Class ;
rdfs:comment "Canonical JSON is a normalised serialisation form of JSON that specifies a unique, deterministic byte-level representation for any given JSON value, enabling reliable hashing, digital signatures, and binary equality comparisons over JSON documents. Because RFC 8259 JSON permits equivalent representations that differ in whitespace, key ordering, and number formatting, canonical forms such as JCS (JSON Canonicalization Scheme, RFC 8785) and earlier proposals impose rules including lexicographic key sorting, no insignificant whitespace, and IEEE 754 double-precision serialisation for numbers. This determinism is essential in cryptographic contexts where the same logical object must produce the same digest regardless of which implementation serialised it."@en ;
rdfs:label "Canonical JSON"@en ;
rdfs:subClassOf ngm:data-format ;
vc:enables ngm:interoperability ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:data-format-standard ;
vc:relatedTo ngm:interoperability-standard ;
vc:slug "canonical-json" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:standards-body ;
vc:uses ngm:cryptography ;
vc:uses ngm:hash-function .
ngm:canva a skos:Concept ;
rdfs:label "Canva"@en .
ngm:canvas-2d a skos:Concept ;
rdfs:label "Canvas 2d"@en .
ngm:canvas-api a skos:Concept ;
rdfs:label "Canvas API"@en .
ngm:cap-theorem a owl:Class ;
rdfs:comment "The CAP Theorem states that a distributed data store cannot simultaneously guarantee all three of consistency, availability and partition tolerance. When a network partition occurs and messages between nodes are lost or delayed, a system must choose between remaining available, by serving possibly stale data, and remaining consistent, by refusing requests it cannot safely satisfy. Formulated by Eric Brewer and later proved formally by Gilbert and Lynch, it frames a fundamental trade-off in distributed systems design."@en ;
rdfs:label "CAP Theorem"@en ;
rdfs:subClassOf ngm:infra-computing-and-cloud ;
rdfs:subClassOf ngm:owl-thing ;
rdfs:subClassOf _:r3700 ;
rdfs:subClassOf _:r3701 ;
skos:broader ngm:infra-computing-and-cloud ;
vc:bridgesTo ngm:blockchain-consensus ;
vc:bridgesTo ngm:consensus ;
vc:bridgesTo ngm:distributed-systems-domain ;
vc:bridgesTo ngm:eventual-consistency ;
vc:bridgesTo ngm:federated-learning ;
vc:contrastsWith ngm:acid-properties ;
vc:contrastsWith ngm:base-properties ;
vc:dependsOn ngm:consensus ;
vc:dependsOn ngm:replication ;
vc:enables ngm:distributed-database-design ;
vc:enables ngm:fault-tolerance ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:partition-tolerance ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:eventual-consistency ;
vc:relatedTo ngm:linearizability ;
vc:relatedTo ngm:nosql-database ;
vc:relatedTo ngm:paxos ;
vc:relatedTo ngm:raft-consensus ;
vc:relatedTo ngm:strong-consistency ;
vc:relatedTo ngm:two-phase-commit ;
vc:requires ngm:network-partition ;
vc:slug "cap-theorem" ;
vc:sourceDomain "distributed-systems" .
ngm:capability-advertisement a owl:Class ;
rdfs:comment "Capability Advertisement is the mechanism by which an autonomous agent publishes machine-readable metadata describing the skills, tools and interfaces it exposes, allowing other agents or an orchestrator to discover what it can do without prior hard-coded knowledge. It typically takes the form of a structured manifest, such as an agent card, exchanged during a discovery or handshake phase. It underpins dynamic task routing in multi-agent systems built on protocols such as the Agent Communication Protocol and Agent-to-Agent Protocol."@en ;
rdfs:label "Capability Advertisement"@en ;
rdfs:subClassOf ngm:service-discovery ;
rdfs:subClassOf _:r3899 ;
vc:enables ngm:agent-orchestrator ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:agent-communication-protocol ;
vc:qualityScore "0.55"^^xsd:float ;
vc:relatedTo ngm:agent-to-agent-protocol ;
vc:requires ngm:service-discovery ;
vc:slug "capability-advertisement" ;
vc:sourceDomain "artificial-intelligence" .
ngm:capability-attestation a skos:Concept ;
rdfs:label "Capability Attestation"@en .
ngm:capability-based-security a skos:Concept ;
rdfs:label "Capability Based Security"@en .
ngm:capability-discovery a skos:Concept ;
rdfs:label "Capability Discovery"@en .
ngm:capability-elicitation a owl:Class ;
rdfs:comment "Capability elicitation is the systematic process of designing prompts, scaffolding, and evaluation protocols to uncover the true maximum performance of an AI model on a given task or domain, distinguishing what a model is genuinely capable of from what it demonstrates under default conditions. It is a central concern in AI safety research and frontier model evaluation because models may possess latent capabilities — such as the ability to reason about dangerous knowledge, produce deceptive outputs, or autonomously pursue goals — that are not revealed by standard benchmarks but can be surfaced through carefully constructed elicitation methods including chain-of-thought prompting, multi-step scaffolding, and adversarial jailbreaking."@en ;
rdfs:label "Capability Elicitation"@en ;
rdfs:subClassOf ngm:ai-evaluation ;
rdfs:subClassOf ngm:ai-safety-research ;
rdfs:subClassOf ngm:benchmark-evaluation ;
rdfs:subClassOf ngm:model-evaluation ;
rdfs:subClassOf ngm:safety-evaluation ;
rdfs:subClassOf _:r3900 ;
rdfs:subClassOf _:r3901 ;
rdfs:subClassOf _:r3902 ;
rdfs:subClassOf _:r3903 ;
rdfs:subClassOf _:r3904 ;
rdfs:subClassOf _:r3905 ;
rdfs:subClassOf _:r3906 ;
vc:contrastsWith ngm:capability-suppression ;
vc:contrastsWith ngm:default-prompting ;
vc:contrastsWith ngm:naive-evaluation ;
vc:contrastsWith ngm:standard-benchmark-evaluation ;
vc:contrastsWith ngm:surface-level-safety-evaluation ;
vc:dependsOn ngm:alignment ;
vc:dependsOn ngm:benchmarking ;
vc:dependsOn ngm:chain-of-thought-reasoning ;
vc:dependsOn ngm:few-shot-prompting ;
vc:dependsOn ngm:large-language-model ;
vc:dependsOn ngm:prompt-engineering ;
vc:enables ngm:ai-governance ;
vc:enables ngm:dangerous-capability-detection ;
vc:enables ngm:deployment-decision-making ;
vc:enables ngm:frontier-ai-oversight ;
vc:enables ngm:model-evaluation-results ;
vc:enables ngm:regulatory-compliance ;
vc:enables ngm:responsible-scaling-policy ;
vc:enables ngm:safety-assessment ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:adversarial-jailbreaking ;
vc:hasPart ngm:agentic-evaluation ;
vc:hasPart ngm:best-of-n-sampling ;
vc:hasPart ngm:chain-of-thought ;
vc:hasPart ngm:few-shot-prompting ;
vc:hasPart ngm:fine-tuning-elicitation ;
vc:hasPart ngm:red-teaming ;
vc:hasPart ngm:scaffolded-evaluation ;
vc:hasPart ngm:tool-augmented-evaluation ;
vc:implements ngm:ai-safety-research ;
vc:implements ngm:aisi-frontier-ai-safety-framework ;
vc:implements ngm:model-evaluation ;
vc:implements ngm:risk-assessment ;
vc:implements ngm:safety-evaluation ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:ai-benchmark-epistemological-critique ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:alignment ;
vc:relatedTo ngm:benchmarks ;
vc:relatedTo ngm:chain-of-thought ;
vc:relatedTo ngm:constitutional-ai-training-methodology ;
vc:relatedTo ngm:emergent-capabilities ;
vc:relatedTo ngm:eu-ai-act-regulatory-instrument ;
vc:relatedTo ngm:frontier-ai ;
vc:relatedTo ngm:large-language-model ;
vc:relatedTo ngm:mechanistic-interpretability ;
vc:relatedTo ngm:mesa-optimisation ;
vc:relatedTo ngm:model-evaluation ;
vc:relatedTo ngm:nist-ai-rmf ;
vc:relatedTo ngm:reward-hacking ;
vc:relatedTo ngm:safety-evaluation ;
vc:relatedTo ngm:scalable-oversight ;
vc:requires ngm:benchmark-dataset ;
vc:requires ngm:chain-of-thought-reasoning ;
vc:requires ngm:expert-evaluators ;
vc:requires ngm:model-access ;
vc:requires ngm:prompt-engineering ;
vc:requires ngm:red-teaming ;
vc:slug "capability-elicitation" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:ai-safety-institute ;
vc:standardizedBy ngm:anthropic-responsible-scaling-policy ;
vc:standardizedBy ngm:google-deepmind-frontier-safety-framework ;
vc:standardizedBy ngm:metr ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:standardizedBy ngm:openai-preparedness-framework ;
vc:supports ngm:ai-governance ;
vc:supports ngm:ai-safety ;
vc:supports ngm:aisi-frontier-ai-safety-framework ;
vc:supports ngm:alignment ;
vc:supports ngm:eu-ai-act-regulatory-instrument ;
vc:supports ngm:human-oversight ;
vc:supports ngm:responsible-ai ;
vc:supports ngm:scalable-oversight ;
vc:uses ngm:adversarial-machine-learning ;
vc:uses ngm:chain-of-thought ;
vc:uses ngm:few-shot-prompting ;
vc:uses ngm:mechanistic-interpretability ;
vc:uses ngm:red-teaming ;
vc:uses ngm:reinforcement-learning-from-human-feedback ;
vc:uses ngm:scaffolded-evaluation .
ngm:capability-evaluation a owl:Class ;
rdfs:comment "Capability evaluation is the systematic measurement of what an AI model can do, especially the elicitation and assessment of potentially dangerous capabilities such as autonomous replication, cyber-offence, or assistance with weapons. It combines benchmarks, structured tasks, and adversarial elicitation (including red-teaming) to establish upper bounds on model behaviour under best-effort prompting and tooling. Results feed safety cases and trigger the thresholds defined in responsible scaling and preparedness frameworks."@en ;
rdfs:label "Capability Evaluation"@en ;
rdfs:subClassOf ngm:ai-evaluation ;
rdfs:subClassOf _:r3907 ;
rdfs:subClassOf _:r3908 ;
vc:bridgesTo ngm:responsible-scaling-policy ;
vc:bridgesTo ngm:safety-evaluation ;
vc:contrastsWith ngm:safety-evaluation ;
vc:enables ngm:ai-safety ;
vc:enables ngm:responsible-scaling-policy ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:isPartOf ngm:ai-evaluation ;
vc:isPartOf ngm:ai-safety ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:ai-agent ;
vc:relatedTo ngm:alignment ;
vc:relatedTo ngm:large-language-model ;
vc:requires ngm:model-evaluation ;
vc:requires ngm:red-teaming ;
vc:slug "capability-evaluation" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:alignment ;
vc:supports ngm:interpretability ;
vc:uses ngm:model-evaluation ;
vc:uses ngm:red-teaming ;
vc:uses ngm:safety-evaluation .
ngm:capability-forecasting a owl:Class ;
rdfs:comment "Capability forecasting is the practice of predicting the future capabilities of AI systems before they are built or deployed, typically by extrapolating from scaling laws, benchmark trends, and historical progress. It aims to anticipate when models will reach particular performance thresholds so that safety, governance, and deployment decisions can be made proactively. Forecasts are inherently uncertain because of emergent behaviour and discontinuous jumps in capability."@en ;
rdfs:label "Capability Forecasting"@en ;
rdfs:subClassOf ngm:ai-governance ;
rdfs:subClassOf ngm:anticipatory-governance ;
rdfs:subClassOf ngm:risk-assessment ;
rdfs:subClassOf _:r3909 ;
rdfs:subClassOf _:r3910 ;
rdfs:subClassOf _:r3911 ;
rdfs:subClassOf _:r3912 ;
rdfs:subClassOf _:r3913 ;
rdfs:subClassOf _:r3914 ;
rdfs:subClassOf _:r3915 ;
rdfs:subClassOf _:r3916 ;
rdfs:subClassOf _:r3917 ;
vc:contrastsWith ngm:benchmark-saturation ;
vc:contrastsWith ngm:emergent-capabilities ;
vc:contrastsWith ngm:reactive-risk-management ;
vc:dependsOn ngm:compute-budget ;
vc:dependsOn ngm:evaluation-benchmarks-and-leaderboards ;
vc:dependsOn ngm:foundation-model ;
vc:dependsOn ngm:model-evaluation ;
vc:dependsOn ngm:scaling-laws ;
vc:dependsOn ngm:training-data ;
vc:enables ngm:ai-regulation ;
vc:enables ngm:ai-safety ;
vc:enables ngm:catastrophic-risk-assessment ;
vc:enables ngm:dangerous-capability-evaluation ;
vc:enables ngm:export-control ;
vc:enables ngm:human-oversight ;
vc:enables ngm:responsible-scaling-policy ;
vc:enables ngm:risk-assessment ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:benchmark-trend-analysis ;
vc:hasPart ngm:biological-anchors-model ;
vc:hasPart ngm:emergent-capabilities ;
vc:hasPart ngm:expert-elicitation ;
vc:hasPart ngm:prediction-markets ;
vc:hasPart ngm:scaling-laws ;
vc:hasPart ngm:threshold-estimation ;
vc:hasPart ngm:uncertainty-quantification ;
vc:implements ngm:benchmark-trend-extrapolation ;
vc:implements ngm:biological-anchors-model ;
vc:implements ngm:expert-elicitation ;
vc:implements ngm:prediction-markets ;
vc:implements ngm:probabilistic-risk-assessment ;
vc:isPartOf ngm:ai-governance ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:ai-safety-level ;
vc:relatedTo ngm:ai-timelines ;
vc:relatedTo ngm:alignment ;
vc:relatedTo ngm:benchmark-saturation ;
vc:relatedTo ngm:capability-evaluation ;
vc:relatedTo ngm:compute-budget ;
vc:relatedTo ngm:dangerous-capability-evaluation ;
vc:relatedTo ngm:emergent-capabilities ;
vc:relatedTo ngm:epochai ;
vc:relatedTo ngm:foundation-model ;
vc:relatedTo ngm:metaculus ;
vc:relatedTo ngm:metr ;
vc:relatedTo ngm:red-teaming ;
vc:relatedTo ngm:responsible-scaling-policy ;
vc:relatedTo ngm:test-time-compute ;
vc:relatedTo ngm:transformative-ai ;
vc:requires ngm:compute-budget ;
vc:requires ngm:evaluation-benchmarks-and-leaderboards ;
vc:requires ngm:foundation-model ;
vc:requires ngm:model-evaluation ;
vc:requires ngm:scaling-laws ;
vc:requires ngm:training-data ;
vc:slug "capability-forecasting" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:california-sb53 ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:ai-alignment ;
vc:supports ngm:ai-governance ;
vc:supports ngm:ai-safety ;
vc:supports ngm:catastrophic-risk-assessment ;
vc:supports ngm:eu-ai-act-regulatory-instrument ;
vc:supports ngm:human-oversight ;
vc:supports ngm:responsible-ai ;
vc:supports ngm:responsible-scaling-policy ;
vc:supports ngm:risk-assessment ;
vc:uses ngm:benchmark-trend-analysis ;
vc:uses ngm:dangerous-capability-evaluation ;
vc:uses ngm:evaluation-benchmarks-and-leaderboards ;
vc:uses ngm:expert-elicitation ;
vc:uses ngm:model-evaluation ;
vc:uses ngm:prediction-markets ;
vc:uses ngm:red-teaming ;
vc:uses ngm:scaling-laws .
ngm:capability-manifest a skos:Concept ;
rdfs:label "Capability Manifest"@en .
ngm:capability-model a skos:Concept ;
rdfs:label "Capability Model"@en .
ngm:capability-negotiation a skos:Concept ;
rdfs:label "Capability Negotiation"@en .
ngm:capability-overhang a owl:Class ;
rdfs:comment "The disparity between the technical capability of an AI system to perform a task and the actual rate of adoption or deployment of that capability in practice."@en ;
rdfs:label "Capability Overhang"@en ;
rdfs:subClassOf ngm:enterprise-ai ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-adoption ;
vc:relatedTo ngm:enterprise-ai ;
vc:slug "capability-overhang" ;
vc:sourceDomain "artificial-intelligence" .
ngm:capability-suppression a skos:Concept ;
rdfs:label "Capability Suppression"@en .
ngm:capability-token a skos:Concept ;
rdfs:label "Capability Token"@en .
ngm:capabilityadvertisement a skos:Concept ;
rdfs:label "Capabilityadvertisement"@en .
ngm:capacitive-sensor a skos:Concept ;
rdfs:label "Capacitive Sensor"@en .
ngm:capacity-control a skos:Concept ;
rdfs:label "Capacity Control"@en .
ngm:capacity-factor a skos:Concept ;
rdfs:label "Capacity Factor"@en .
ngm:capacity-market a skos:Concept ;
rdfs:label "Capacity Market"@en .
ngm:capacity-markets a skos:Concept ;
rdfs:label "Capacity Markets"@en .
ngm:capacity-planning a owl:Class ;
rdfs:comment "Capacity planning is the process of determining the production, infrastructure, or service capacity required by an organisation to meet changing demand over a defined time horizon, balancing the cost of over-provisioned resources against the risk of under-provisioned systems that cannot meet service-level objectives. In technology contexts, capacity planning encompasses compute, storage, network bandwidth, and human resources, employing demand forecasting models, utilisation metrics, and growth projections to derive procurement and scaling roadmaps. In manufacturing, the same principles apply to machine-hours, floor space, and workforce shifts."@en ;
rdfs:label "Capacity Planning"@en ;
rdfs:subClassOf ngm:cloud-infrastructure ;
rdfs:subClassOf _:r3918 ;
vc:bridgesTo ngm:carbon-aware-computing ;
vc:bridgesTo ngm:supply-chain-management ;
vc:contrastsWith ngm:reactive-scaling ;
vc:dependsOn ngm:infrastructure-as-code ;
vc:dependsOn ngm:observability ;
vc:enables ngm:cloud-computing ;
vc:enables ngm:resource-optimisation ;
vc:enables ngm:scalability ;
vc:enables ngm:service-level-objective ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:autoscaling ;
vc:relatedTo ngm:cloud-native ;
vc:relatedTo ngm:kubernetes ;
vc:relatedTo ngm:scalability-pattern ;
vc:requires ngm:performance-monitoring ;
vc:requires ngm:workload-management ;
vc:slug "capacity-planning" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:cost-optimisation ;
vc:supports ngm:finops ;
vc:supports ngm:site-reliability-engineering ;
vc:uses ngm:demand-forecasting ;
vc:uses ngm:queuing-theory ;
vc:uses ngm:time-series-analysis ;
vc:uses ngm:utilisation-monitoring .
ngm:capacity-utilisation a skos:Concept ;
rdfs:label "Capacity Utilisation"@en .
ngm:caparo-three-stage-test a skos:Concept ;
rdfs:label "Caparo Three Stage Test"@en .
ngm:capital-adequacy a owl:Class ;
rdfs:comment "Capital adequacy is the regulatory and risk management requirement that financial institutions maintain a minimum level of capital relative to their risk-weighted assets, ensuring they can absorb losses without becoming insolvent and thereby protecting depositors, counterparties, and the broader financial system. The Basel Committee on Banking Supervision (BCBS) has codified capital adequacy requirements through successive accords — Basel I (1988), Basel II (2004), Basel III (2010, phased through 2028) — specifying the composition of qualifying capital (Common Equity Tier 1, Additional Tier 1, Tier 2) and the risk-weighting methodologies for credit, market, and operational risk exposures."@en ;
rdfs:label "Capital Adequacy"@en ;
rdfs:subClassOf ngm:compliance-framework ;
rdfs:subClassOf _:r3919 ;
rdfs:subClassOf _:r3920 ;
vc:bridgesTo ngm:climate-financial-risk ;
vc:dependsOn ngm:credit-risk ;
vc:dependsOn ngm:market-risk ;
vc:dependsOn ngm:operational-risk ;
vc:enables ngm:compliance-monitoring ;
vc:enables ngm:financial-stability ;
vc:enables ngm:systemic-risk ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:capital-conservation-buffer ;
vc:hasPart ngm:common-equity-tier-1 ;
vc:hasPart ngm:countercyclical-capital-buffer ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:compliance ;
vc:relatedTo ngm:liquidity-coverage-ratio ;
vc:relatedTo ngm:risk-management ;
vc:requires ngm:risk-weighted-assets ;
vc:requires ngm:stress-testing ;
vc:slug "capital-adequacy" ;
vc:sourceDomain "finance" ;
vc:standardizedBy ngm:basel-committee-on-banking-supervision ;
vc:standardizedBy ngm:basel-iii ;
vc:standardizedBy ngm:prudential-regulation ;
vc:supports ngm:systemic-risk ;
vc:uses ngm:risk-assessment .
ngm:capital-allocation a owl:Class ;
rdfs:comment "Capital allocation is the process by which firms, investors and markets distribute scarce financial resources across competing uses to maximise risk-adjusted return or strategic value. It spans corporate decisions about investing, returning capital and funding, as well as investor decisions about deploying funds across assets and opportunities. Effective allocation channels capital towards its most productive uses, making it central to both firm performance and the efficiency of the wider financial system."@en ;
rdfs:label "Capital Allocation"@en ;
rdfs:subClassOf ngm:investment-management ;
rdfs:subClassOf _:r3921 ;
rdfs:subClassOf _:r3922 ;
vc:bridgesTo ngm:financial-services ;
vc:dependsOn ngm:liquidity ;
vc:enables ngm:capital-efficiency ;
vc:enables ngm:price-discovery ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:portfolio-management ;
vc:isPartOf ngm:investment-management ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:financial-system ;
vc:relatedTo ngm:risk-management ;
vc:requires ngm:portfolio-management ;
vc:requires ngm:risk-management ;
vc:slug "capital-allocation" ;
vc:sourceDomain "finance" ;
vc:supports ngm:capital-markets ;
vc:uses ngm:resource-allocation .
ngm:capital-allocation-efficiency a skos:Concept ;
rdfs:label "Capital Allocation Efficiency"@en .
ngm:capital-base a skos:Concept ;
rdfs:label "Capital Base"@en .
ngm:capital-conservation-buffer a skos:Concept ;
rdfs:label "Capital Conservation Buffer"@en .
ngm:capital-controls a skos:Concept ;
rdfs:label "Capital Controls"@en .
ngm:capital-efficiency a owl:Class ;
rdfs:comment "Capital efficiency is the degree to which deployed capital is put to productive use to generate returns or provide a service, maximising output per unit of locked or committed funds. In decentralised finance it describes designs such as concentrated liquidity and over-collateralisation tuning that let liquidity providers and protocols achieve more depth or yield from less capital. Higher capital efficiency reduces idle assets and lowers the cost of providing liquidity and credit."@en ;
rdfs:label "Capital Efficiency"@en ;
rdfs:subClassOf ngm:de-fi ;
rdfs:subClassOf _:r3923 ;
rdfs:subClassOf _:r3924 ;
vc:bridgesTo ngm:market-microstructure ;
vc:contrastsWith ngm:risk-management ;
vc:dependsOn ngm:liquidity-pool ;
vc:enables ngm:liquidity ;
vc:enables ngm:liquidity-pool ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:de-fi ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:collateral ;
vc:relatedTo ngm:de-fi ;
vc:relatedTo ngm:liquidity ;
vc:relatedTo ngm:risk-management ;
vc:requires ngm:collateral ;
vc:requires ngm:liquidity ;
vc:slug "capital-efficiency" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:market-maker ;
vc:supports ngm:trade-execution ;
vc:uses ngm:decentralized-exchange .
ngm:capital-formation a owl:Class ;
rdfs:comment "Capital formation is the economic and financial process by which savings are channelled into productive investment, raising the stock of capital goods and funding enterprises. In capital markets it refers specifically to the issuance and sale of securities — equity and debt — that allow firms to raise funds from investors. Efficient capital formation underpins economic growth and is a central policy objective of securities regulation, which balances investor protection against ease of raising capital."@en ;
rdfs:label "Capital Formation"@en ;
rdfs:subClassOf ngm:economic-mechanism ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:bc-defi-and-economics ;
vc:relatedTo ngm:securities-regulation ;
vc:slug "capital-formation" ;
vc:sourceDomain "governance" .
ngm:capital-investment a skos:Concept ;
rdfs:label "Capital Investment"@en .
ngm:capital-markets a owl:Class ;
rdfs:comment "Capital markets are the financial markets in which long-term debt and equity instruments are issued and traded, channelling savings from investors to issuers such as companies and governments. They comprise primary markets, where new securities are issued, and secondary markets, where existing securities trade among investors. They are central to capital formation, price discovery and liquidity, and are increasingly intersecting with tokenisation and blockchain-based settlement."@en ;
rdfs:label "Capital Markets"@en ;
rdfs:subClassOf ngm:traditional-finance ;
rdfs:subClassOf _:r3925 ;
rdfs:subClassOf _:r3926 ;
rdfs:subClassOf _:r3927 ;
rdfs:subClassOf _:r3928 ;
vc:bridgesTo ngm:financial-infrastructure ;
vc:dependsOn ngm:financial-infrastructure ;
vc:enables ngm:capital-formation ;
vc:enables ngm:liquidity ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:financial-instruments ;
vc:hasPart ngm:liquidity ;
vc:isPartOf ngm:traditional-finance ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:financial-instruments ;
vc:relatedTo ngm:financial-regulation ;
vc:relatedTo ngm:institutional-adoption ;
vc:requires ngm:financial-infrastructure ;
vc:requires ngm:financial-regulation ;
vc:slug "capital-markets" ;
vc:sourceDomain "finance" ;
vc:supports ngm:institutional-adoption ;
vc:uses ngm:financial-instruments .
ngm:capital-markets-and-technology-association-cmtat a skos:Concept ;
rdfs:label "Capital Markets And Technology Association Cmtat"@en .
ngm:capital-preservation a skos:Concept ;
rdfs:label "Capital Preservation"@en .
ngm:capital-requirements a skos:Concept ;
rdfs:label "Capital Requirements"@en .
ngm:capital-requirements-regulation a skos:Concept ;
rdfs:label "Capital Requirements Regulation"@en .
ngm:captcha a skos:Concept ;
rdfs:label "Captcha"@en .
ngm:caption-files a skos:Concept ;
rdfs:label "Caption Files"@en .
ngm:captioning-pipeline a skos:Concept ;
rdfs:label "Captioning Pipeline"@en .
ngm:capture-device a skos:Concept ;
rdfs:label "Capture Device"@en .
ngm:car-file a skos:Concept ;
rdfs:label "Car File"@en .
ngm:carbon-accounting a owl:Class ;
rdfs:comment "The systematic process of measuring, recording, and reporting an organization's greenhouse gas emissions across direct operations (Scope 1), purchased energy (Scope 2), and value chain activities (Scope 3), expressed in CO2 equivalent units to quantify climate impact and enable reduction strategies."@en ;
rdfs:label "Carbon Accounting"@en ;
rdfs:subClassOf ngm:environmental-accounting ;
rdfs:subClassOf _:r3929 ;
rdfs:subClassOf _:r3930 ;
rdfs:subClassOf _:r3931 ;
rdfs:subClassOf _:r3932 ;
rdfs:subClassOf _:r3933 ;
rdfs:subClassOf _:r3934 ;
rdfs:subClassOf _:r3935 ;
rdfs:subClassOf _:r3936 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:supply-chain-management ;
vc:contrastsWith ngm:carbon-footprint ;
vc:enables ngm:carbon-offsetting ;
vc:enables ngm:climate-action-planning ;
vc:enables ngm:emissions-reporting ;
vc:enables ngm:esg-reporting ;
vc:enables ngm:net-zero-target-setting ;
vc:enables ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:scope-1-emissions ;
vc:hasPart ngm:scope-2-emissions ;
vc:hasPart ngm:scope-3-emissions ;
vc:isPartOf ngm:climate-risk-management ;
vc:isPartOf ngm:corporate-sustainability-reporting ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:carbon-credits ;
vc:relatedTo ngm:science-based-targets ;
vc:requires ngm:data-collection ;
vc:requires ngm:emission-factors ;
vc:requires ngm:greenhouse-gas-protocol ;
vc:requires ngm:materiality-assessment ;
vc:requires ngm:verification-process ;
vc:slug "carbon-accounting" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:ifrs-s2 ;
vc:standardizedBy ngm:iso-14064 ;
vc:uses ngm:life-cycle-assessment ;
vc:uses ngm:supply-chain-data .
ngm:carbon-accounting-software a owl:Class ;
rdfs:comment "Carbon accounting software is a category of enterprise application that automates the collection, calculation, and reporting of an organisation's greenhouse gas (GHG) emissions across Scope 1 (direct), Scope 2 (purchased energy), and Scope 3 (value chain) categories in accordance with established standards such as the GHG Protocol Corporate Standard and ISO 14064. These platforms ingest activity data from financial systems, energy bills, logistics records, and supplier databases; apply emission factors; and produce auditable emissions inventories aligned with regulatory disclosure frameworks including the EU Corporate Sustainability Reporting Directive (CSRD) and the SEC Climate Disclosure Rule."@en ;
rdfs:label "Carbon Accounting Software"@en ;
rdfs:subClassOf ngm:carbon-accounting ;
vc:enables ngm:carbon-neutrality ;
vc:enables ngm:esg-reporting ;
vc:enables ngm:sustainability-reporting ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:carbon-footprint-measurement ;
vc:relatedTo ngm:scope-3-emissions ;
vc:slug "carbon-accounting-software" ;
vc:sourceDomain "governance" ;
vc:uses ngm:emission-factors ;
vc:uses ngm:ghg-protocol .
ngm:carbon-accounting-standards a skos:Concept ;
rdfs:label "Carbon Accounting Standards"@en .
ngm:carbon-allowance a skos:Concept ;
rdfs:label "Carbon Allowance"@en .
ngm:carbon-aware-computing a owl:Class ;
rdfs:comment "Carbon-aware computing is the practice of scheduling and placing computational workloads to minimise their associated greenhouse-gas emissions by responding to the time-varying and location-varying carbon intensity of electricity. Rather than only reducing energy use, it shifts flexible work to periods and regions where the grid is cleaner. The approach combines real-time grid carbon-intensity signals with workload orchestration to lower the carbon footprint of data centres and cloud services."@en ;
rdfs:label "Carbon-Aware Computing"@en ;
rdfs:subClassOf ngm:green-computing ;
rdfs:subClassOf _:r4017 ;
vc:bridgesTo ngm:renewable-energy ;
vc:contrastsWith ngm:energy-efficiency ;
vc:dependsOn ngm:demand-response ;
vc:dependsOn ngm:renewable-energy ;
vc:enables ngm:carbon-footprint ;
vc:enables ngm:net-zero ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:isPartOf ngm:green-computing ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:carbon-accounting ;
vc:relatedTo ngm:cloud-computing ;
vc:relatedTo ngm:lifecycle-assessment ;
vc:requires ngm:energy-efficiency ;
vc:slug "carbon-aware-computing" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:carbon-footprint ;
vc:supports ngm:environmental-sustainability ;
vc:uses ngm:cloud-computing ;
vc:uses ngm:demand-response .
ngm:carbon-border-adjustment a skos:Concept ;
rdfs:label "Carbon Border Adjustment"@en .
ngm:carbon-border-adjustment-compliance a skos:Concept ;
rdfs:label "Carbon Border Adjustment Compliance"@en .
ngm:carbon-border-adjustment-mechanism a skos:Concept ;
rdfs:label "Carbon Border Adjustment Mechanism"@en .
ngm:carbon-calculator a owl:Class ;
rdfs:comment "A digital tool or software application that estimates greenhouse gas emissions from activities such as energy consumption, transportation, and production by applying standardized emission factors to user-provided data, enabling individuals and organizations to quantify and understand their carbon..."@en ;
rdfs:label "Carbon Calculator"@en ;
rdfs:subClassOf ngm:sc-governance-and-safety ;
rdfs:subClassOf ngm:sustainability-tool ;
rdfs:subClassOf _:r3937 ;
rdfs:subClassOf _:r3938 ;
skos:broader ngm:sc-governance-and-safety ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:sustainability-tool ;
vc:enables ngm:emissions-estimation ;
vc:enables ngm:footprint-awareness ;
vc:enables ngm:reduction-planning ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:activity-data ;
vc:requires ngm:calculation-methodology ;
vc:requires ngm:emission-factors ;
vc:slug "carbon-calculator" ;
vc:sourceDomain "spatial-computing" .
ngm:carbon-credit-retirement a owl:Class ;
rdfs:comment "Carbon credit retirement is the permanent cancellation of a carbon credit in a registry so that it can no longer be sold, transferred, or double-counted, formally claiming the underlying emission reduction or removal. Retirement is the terminal step that converts a tradable credit into a fulfilled offset claim against a specific buyer's emissions. It is fundamental to carbon market integrity because it guarantees that each tonne of avoided or removed CO2 is claimed only once."@en ;
rdfs:label "Carbon Credit Retirement"@en ;
rdfs:subClassOf ngm:economic-mechanism ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:climate-action-dao ;
vc:relatedTo ngm:icvcm-core-carbon-principles ;
vc:slug "carbon-credit-retirement" ;
vc:sourceDomain "governance" .
ngm:carbon-credit-token a owl:Class ;
rdfs:comment "Digital token representing verified carbon-offset value tradeable across platforms for emissions reduction and environmental sustainability."@en ;
rdfs:label "Carbon Credit Token"@en ;
rdfs:subClassOf ngm:bc-token-and-asset ;
rdfs:subClassOf ngm:virtual-economy ;
rdfs:subClassOf _:r3939 ;
rdfs:subClassOf _:r3940 ;
rdfs:subClassOf _:r3941 ;
rdfs:subClassOf _:r3942 ;
rdfs:subClassOf _:r3943 ;
rdfs:subClassOf _:r3944 ;
skos:broader ngm:bc-token-and-asset ;
vc:bridgesTo ngm:virtual-economy ;
vc:dependsOn ngm:carbon-registry ;
vc:dependsOn ngm:trading-platform ;
vc:dependsOn ngm:verification-standard ;
vc:enables ngm:carbon-offset-trading ;
vc:enables ngm:emissions-trading ;
vc:enables ngm:environmental-compliance ;
vc:enables ngm:sustainability-reporting ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:blockchain-record ;
vc:hasPart ngm:carbon-offset-certificate ;
vc:hasPart ngm:smart-contract ;
vc:hasPart ngm:verification-metadata ;
vc:isPartOf ngm:environmental-asset-market ;
vc:isPartOf ngm:sustainability-framework ;
vc:isPartOf ngm:virtual-economy ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:blockchain ;
vc:requires ngm:digital-wallet ;
vc:requires ngm:smart-contract ;
vc:requires ngm:verification-authority ;
vc:slug "carbon-credit-token" ;
vc:sourceDomain "blockchain" .
ngm:carbon-credit-tracking a owl:Class ;
rdfs:comment "Carbon Credit Tracking is the application of Blockchain and distributed ledger technology to record, verify, transfer, and permanently retire carbon emission reduction credits across their full lifecycle — from project origination through third-party verification to final environmental claim ..."@en ;
rdfs:label "Carbon Credit Tracking"@en ;
rdfs:subClassOf ngm:carbon-markets ;
rdfs:subClassOf ngm:distributed-ledger-application ;
rdfs:subClassOf ngm:environmental-finance ;
rdfs:subClassOf ngm:green-finance ;
rdfs:subClassOf ngm:network-component ;
rdfs:subClassOf ngm:real-world-asset-tokenisation ;
rdfs:subClassOf _:r3945 ;
rdfs:subClassOf _:r3946 ;
rdfs:subClassOf _:r3947 ;
rdfs:subClassOf _:r3948 ;
rdfs:subClassOf _:r3949 ;
rdfs:subClassOf _:r3950 ;
rdfs:subClassOf _:r3951 ;
rdfs:subClassOf _:r3952 ;
vc:bridgesTo ngm:carbon-markets ;
vc:contrastsWith ngm:centralised-carbon-exchange ;
vc:contrastsWith ngm:compliance-cap-and-trade-registry ;
vc:contrastsWith ngm:offset-broker ;
vc:contrastsWith ngm:redd-paper-certificates ;
vc:contrastsWith ngm:traditional-carbon-registry ;
vc:dependsOn ngm:blockchain ;
vc:dependsOn ngm:carbon-registries ;
vc:dependsOn ngm:io-t-sensors ;
vc:dependsOn ngm:mrv ;
vc:dependsOn ngm:oracle-networks ;
vc:dependsOn ngm:satellite-remote-sensing ;
vc:dependsOn ngm:smart-contracts ;
vc:enables ngm:article-6-compliance ;
vc:enables ngm:automated-carbon-accounting ;
vc:enables ngm:carbon-neutrality ;
vc:enables ngm:carbon-price-discovery ;
vc:enables ngm:fractional-carbon-credit-ownership ;
vc:enables ngm:real-time-carbon-offsetting ;
vc:enables ngm:voluntary-carbon-market ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:carbon-credit-token ;
vc:hasPart ngm:carbon-registry-bridge ;
vc:hasPart ngm:corresponding-adjustment-record ;
vc:hasPart ngm:credit-issuance-engine ;
vc:hasPart ngm:mrv-oracle ;
vc:hasPart ngm:permanence-buffer-pool ;
vc:hasPart ngm:retirement-smart-contract ;
vc:implements ngm:corsia-aviation-offsets ;
vc:implements ngm:eu-taxonomy-green-finance ;
vc:implements ngm:gold-standard-certification ;
vc:implements ngm:icvcm-core-carbon-principles ;
vc:implements ngm:paris-agreement-article-6 ;
vc:implements ngm:verra-vcs-methodology ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:carbon-credits ;
vc:relatedTo ngm:carbon-neutral-blockchain ;
vc:relatedTo ngm:environmental-finance ;
vc:relatedTo ngm:esg-investing ;
vc:relatedTo ngm:green-finance ;
vc:relatedTo ngm:mrv ;
vc:relatedTo ngm:neural-network-text-tokenisation ;
vc:relatedTo ngm:nft ;
vc:relatedTo ngm:smart-contracts ;
vc:relatedTo ngm:voluntary-carbon-market ;
vc:requires ngm:audit-trail ;
vc:requires ngm:blockchain-infrastructure ;
vc:requires ngm:carbon-standard-certification ;
vc:requires ngm:kyc-aml-compliance ;
vc:requires ngm:oracle-network ;
vc:requires ngm:smart-contracts ;
vc:requires ngm:verified-emissions-data ;
vc:slug "carbon-credit-tracking" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:corsia ;
vc:standardizedBy ngm:eu-corporate-sustainability-reporting-directive ;
vc:standardizedBy ngm:gold-standard ;
vc:standardizedBy ngm:icvcm-core-carbon-principles ;
vc:standardizedBy ngm:paris-agreement-article-6 ;
vc:standardizedBy ngm:verra-vcs-standard ;
vc:supports ngm:biodiversity-credits ;
vc:supports ngm:climate-tech ;
vc:supports ngm:corporate-climate-commitments ;
vc:supports ngm:esg-investing ;
vc:supports ngm:nature-based-solutions ;
vc:supports ngm:net-zero-targets ;
vc:supports ngm:sustainability ;
vc:uses ngm:chainlink-oracles ;
vc:uses ngm:de-fi ;
vc:uses ngm:erc-20-tokens ;
vc:uses ngm:erc-721 ;
vc:uses ngm:erc-721-standard ;
vc:uses ngm:ethereum-smart-contract-platform ;
vc:uses ngm:hedera-hashgraph ;
vc:uses ngm:polygon .
ngm:carbon-credits a owl:Class ;
rdfs:comment "Carbon credits are tradeable instruments, each representing the verified reduction or removal of one tonne of carbon dioxide equivalent (tCO₂e) from the atmosphere, used in both compliance and voluntary markets to incentivise greenhouse gas mitigation. In compliance cap-and-trade systems, regulators issue a capped total of allowances and require regulated emitters to surrender one allowance per tonne emitted, creating a price signal for abatement. Voluntary carbon markets allow organisations to purchase credits from validated offset projects — such as reforestation, renewable energy deployment, or methane capture — to offset residual emissions. Market integrity depends on independently certified additionality, permanence, and measurability, overseen by standards bodies such as Verra, Gold Standard, and the American Carbon Registry."@en ;
rdfs:label "Carbon Credits"@en ;
rdfs:subClassOf ngm:infra-legal-and-regulatory ;
rdfs:subClassOf _:r3953 ;
rdfs:subClassOf _:r3954 ;
rdfs:subClassOf _:r3955 ;
skos:broader ngm:infra-legal-and-regulatory ;
vc:bridgesTo ngm:blockchain-tokenisation ;
vc:bridgesTo ngm:de-fi ;
vc:bridgesTo ngm:smart-contract ;
vc:contrastsWith ngm:carbon-tax ;
vc:contrastsWith ngm:direct-air-capture ;
vc:dependsOn ngm:greenhouse-gas-protocol ;
vc:dependsOn ngm:third-party-verification ;
vc:enables ngm:carbon-accounting ;
vc:enables ngm:carbon-credit-token ;
vc:enables ngm:net-zero-targets ;
vc:enables ngm:scope-3-emissions ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:carbon-allowance ;
vc:hasPart ngm:carbon-offset ;
vc:hasPart ngm:verified-emission-reduction ;
vc:isPartOf ngm:carbon-markets ;
vc:isPartOf ngm:emissions-trading-scheme ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:carbon-offset-trading ;
vc:relatedTo ngm:esg-investing ;
vc:requires ngm:additionality ;
vc:requires ngm:carbon-registry ;
vc:requires ngm:measurement-reporting-and-verification ;
vc:requires ngm:measurement-reporting-verification ;
vc:slug "carbon-credits" ;
vc:sourceDomain "finance" ;
vc:standardizedBy ngm:gold-standard ;
vc:standardizedBy ngm:paris-agreement-article-6 ;
vc:standardizedBy ngm:verified-carbon-standard ;
vc:supports ngm:corporate-sustainability-reporting ;
vc:supports ngm:environmental-accounting ;
vc:supports ngm:paris-agreement ;
vc:uses ngm:io-t-sensors ;
vc:uses ngm:remote-sensing ;
vc:uses ngm:satellite-monitoring .
ngm:carbon-cycle-monitoring a owl:Class ;
rdfs:label "Carbon Cycle Monitoring"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-applications ;
vc:slug "carbon-cycle-monitoring" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:carbon-disclosure a skos:Concept ;
rdfs:label "Carbon Disclosure"@en .
ngm:carbon-emissions-reduction a skos:Concept ;
rdfs:label "Carbon Emissions Reduction"@en .
ngm:carbon-fibre-composite a skos:Concept ;
rdfs:label "Carbon Fibre Composite"@en .
ngm:carbon-fibre-reinforcement a skos:Concept ;
rdfs:label "Carbon Fibre Reinforcement"@en .
ngm:carbon-footprint a owl:Class ;
rdfs:comment "A carbon footprint is the total quantity of greenhouse gases, expressed as carbon dioxide equivalent (CO2e), emitted directly and indirectly by an individual, organisation, product, or activity over a defined period. It aggregates scope 1, 2, and 3 emissions to provide a single comparable measure of climate impact. Carbon footprints matter because they are the baseline metric for emissions reduction targets, disclosure, and offsetting strategies."@en ;
rdfs:label "Carbon Footprint"@en ;
rdfs:subClassOf ngm:sustainability ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol-environmental-issues ;
vc:relatedTo ngm:sustainability ;
vc:slug "carbon-footprint" ;
vc:sourceDomain "governance" .
ngm:carbon-footprint-assessment a owl:Class ;
rdfs:comment "A comprehensive emodology that quantifies total greenhouse gas emissions associated with a product, service, or organization across its entire lifecycle using Life Cycle Assessment principles, expressed in CO2 equivalent units to identify emission hotspots and reduction opportunities."@en ;
rdfs:label "Carbon Footprint Assessment"@en ;
rdfs:subClassOf ngm:environmental-assessment ;
rdfs:subClassOf ngm:sc-governance-and-safety ;
rdfs:subClassOf _:r3956 ;
skos:broader ngm:sc-governance-and-safety ;
vc:bridgesTo ngm:blockchain ;
vc:enables ngm:hotspot-identification ;
vc:enables ngm:impact-quantification ;
vc:enables ngm:reduction-strategy ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:boundary-definition ;
vc:requires ngm:emission-factors ;
vc:requires ngm:lifecycle-data ;
vc:slug "carbon-footprint-assessment" ;
vc:sourceDomain "spatial-computing" .
ngm:carbon-footprint-indicator a owl:Class ;
rdfs:comment "A quantitative environmental performance metric that measures and tracks an organization's greenhouse gas emissions in CO2 equivalent units, serving as a key sustainability KPI for monitoring progress toward emission reduction targets and enabling comparative analysis across operations."@en ;
rdfs:label "Carbon Footprint Indicator"@en ;
rdfs:subClassOf ngm:environmental-k-p-i ;
rdfs:subClassOf ngm:environmental-kpi ;
rdfs:subClassOf ngm:sc-governance-and-safety ;
rdfs:subClassOf _:r3957 ;
skos:broader ngm:sc-governance-and-safety ;
vc:bridgesTo ngm:blockchain ;
vc:enables ngm:benchmarking ;
vc:enables ngm:performance-monitoring ;
vc:enables ngm:target-tracking ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:emissions-data ;
vc:requires ngm:measurement-methodology ;
vc:requires ngm:reporting-framework ;
vc:slug "carbon-footprint-indicator" ;
vc:sourceDomain "spatial-computing" .
ngm:carbon-footprint-measurement a owl:Class ;
rdfs:comment "Systematic quantitative modology for calculating the total greenhouse gas (GHG) emissions attributable to an organisation, product, service, or activity across its full operational and value-chain scope, expressed in tonnes of carbon dioxide equivalent (tCO₂e), applying IPCC Sixth Assessment Repo..."@en ;
rdfs:label "Carbon Footprint Measurement"@en ;
rdfs:subClassOf ngm:climate-risk-management ;
rdfs:subClassOf ngm:corporate-disclosure ;
rdfs:subClassOf ngm:environmental-accounting ;
rdfs:subClassOf ngm:infra-legal-and-regulatory ;
rdfs:subClassOf ngm:infra-security-and-identity ;
rdfs:subClassOf ngm:measurement-frameworks ;
rdfs:subClassOf ngm:sustainability-reporting ;
rdfs:subClassOf _:r3958 ;
rdfs:subClassOf _:r3959 ;
rdfs:subClassOf _:r3960 ;
rdfs:subClassOf _:r3961 ;
rdfs:subClassOf _:r3962 ;
rdfs:subClassOf _:r3963 ;
rdfs:subClassOf _:r3964 ;
rdfs:subClassOf _:r3965 ;
rdfs:subClassOf _:r3966 ;
rdfs:subClassOf _:r3967 ;
rdfs:subClassOf _:r3968 ;
rdfs:subClassOf _:r3969 ;
rdfs:subClassOf _:r3970 ;
rdfs:subClassOf _:r3971 ;
skos:broader ngm:infra-legal-and-regulatory ;
skos:broader ngm:infra-security-and-identity ;
vc:contrastsWith ngm:carbon-offsetting ;
vc:contrastsWith ngm:greenwashing ;
vc:contrastsWith ngm:voluntary-carbon-market ;
vc:dependsOn ngm:activity-data ;
vc:dependsOn ngm:ai ;
vc:dependsOn ngm:emission-factors ;
vc:dependsOn ngm:erp-systems ;
vc:dependsOn ngm:satellite-data ;
vc:dependsOn ngm:supply-chain-transparency ;
vc:enables ngm:carbon-credits ;
vc:enables ngm:csrd-compliance ;
vc:enables ngm:decarbonisation ;
vc:enables ngm:digital-product-passport ;
vc:enables ngm:esg-investing ;
vc:enables ngm:net-zero-target-setting ;
vc:enables ngm:science-based-targets ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:boundary-setting ;
vc:hasPart ngm:carbon-accounting-software ;
vc:hasPart ngm:emission-factors ;
vc:hasPart ngm:emission-inventory ;
vc:hasPart ngm:life-cycle-assessment ;
vc:hasPart ngm:lifecycle-assessment ;
vc:hasPart ngm:satellite-monitoring ;
vc:hasPart ngm:scope-classification ;
vc:hasPart ngm:verification ;
vc:implements ngm:carbon-footprint ;
vc:implements ngm:location-based-accounting ;
vc:implements ngm:market-based-accounting ;
vc:implements ngm:scope-1-emissions ;
vc:implements ngm:scope-2-emissions ;
vc:implements ngm:scope-3-emissions ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:circular-economy ;
vc:relatedTo ngm:climate-tech ;
vc:relatedTo ngm:digital-product-passport ;
vc:relatedTo ngm:esg-investing ;
vc:relatedTo ngm:ghg-protocol ;
vc:relatedTo ngm:regulatory-technology ;
vc:relatedTo ngm:supply-chain ;
vc:relatedTo ngm:sustainability ;
vc:requires ngm:activity-data ;
vc:requires ngm:emission-factors ;
vc:requires ngm:ghg-protocol ;
vc:requires ngm:iso-14064 ;
vc:requires ngm:iso-14067 ;
vc:requires ngm:organisational-boundary-definition ;
vc:requires ngm:supply-chain-data ;
vc:slug "carbon-footprint-measurement" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:esrs-e1 ;
vc:standardizedBy ngm:ghg-protocol ;
vc:standardizedBy ngm:iso-14040 ;
vc:standardizedBy ngm:iso-14064 ;
vc:standardizedBy ngm:iso-14067 ;
vc:standardizedBy ngm:streamlined-energy-and-carbon-reporting ;
vc:standardizedBy ngm:tcfd ;
vc:supports ngm:carbon-credits ;
vc:supports ngm:circular-economy ;
vc:supports ngm:climate-tech ;
vc:supports ngm:esg-investing ;
vc:supports ngm:regulatory-technology ;
vc:supports ngm:supply-chain ;
vc:supports ngm:sustainability-reporting ;
vc:uses ngm:ai ;
vc:uses ngm:artificial-intelligence ;
vc:uses ngm:blockchain ;
vc:uses ngm:digital-product-passport ;
vc:uses ngm:life-cycle-assessment ;
vc:uses ngm:lifecycle-assessment ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:remote-sensing ;
vc:uses ngm:satellite-data .
ngm:carbon-footprint-reduction a skos:Concept ;
rdfs:label "Carbon Footprint Reduction"@en .
ngm:carbon-intensity a skos:Concept ;
rdfs:label "Carbon Intensity"@en .
ngm:carbon-market-design a skos:Concept ;
rdfs:label "Carbon Market Design"@en .
ngm:carbon-markets a owl:Class ;
rdfs:comment "Carbon markets are regulated or voluntary trading systems in which carbon credits or allowances — each representing one metric tonne of CO₂ equivalent avoided, reduced, or removed — are issued, bought, sold, and retired to place a price on greenhouse gas emissions and channel investment towards least-cost mitigation activities. Compliance markets operate under mandatory emissions-trading schemes (ETS) such as the EU ETS, California Cap-and-Trade, and the Article 6 mechanisms of the Paris Agreement, where regulated emitters must surrender allowances matching verified output. Voluntary carbon markets (VCMs) allow organisations and individuals outside regulatory caps to purchase independently verified credits from projects ranging from avoided deforestation to direct air capture, enabling net-zero and carbon-neutrality claims. Market integrity depends on robust project standards, third-party verification, transparent registry infrastructure, and governance frameworks to prevent double counting and ensure additionality."@en ;
rdfs:label "Carbon Markets"@en ;
rdfs:subClassOf ngm:environmental-asset-market ;
rdfs:subClassOf _:r3972 ;
rdfs:subClassOf _:r3973 ;
rdfs:subClassOf _:r3974 ;
rdfs:subClassOf _:r3975 ;
rdfs:subClassOf _:r3976 ;
vc:bridgesTo ngm:carbon-credit-token ;
vc:bridgesTo ngm:distributed-ledger-technology ;
vc:bridgesTo ngm:environmental-monitoring ;
vc:enables ngm:carbon-neutrality ;
vc:enables ngm:carbon-offset-trading ;
vc:enables ngm:emissions-reduction ;
vc:enables ngm:net-zero-targets ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:carbon-price-discovery ;
vc:hasPart ngm:compliance-carbon-market ;
vc:hasPart ngm:voluntary-carbon-market ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:carbon-tax ;
vc:relatedTo ngm:climate-finance ;
vc:relatedTo ngm:emissions-trading-scheme ;
vc:relatedTo ngm:paris-agreement ;
vc:requires ngm:additionality-assessment ;
vc:requires ngm:carbon-accounting ;
vc:requires ngm:third-party-verification ;
vc:slug "carbon-markets" ;
vc:sourceDomain "finance" ;
vc:standardizedBy ngm:gold-standard ;
vc:standardizedBy ngm:icvcm-core-carbon-principles ;
vc:standardizedBy ngm:verified-carbon-standard ;
vc:uses ngm:carbon-credits ;
vc:uses ngm:carbon-offset ;
vc:uses ngm:carbon-registry ;
vc:uses ngm:emissions-allowance .
ngm:carbon-neutral-blockchain a owl:Class ;
rdfs:comment "Carbon Neutral Blockchain is any distributed ledger infrastructure that achieves net-zero or carbon-negative lifecycle greenhouse gas emissions through one or more of three principal mechanisms: (1) Consensus mechanism transition: Adoption of low-energy Consensus Mechanisms — pre-eminently"@en ;
rdfs:label "Carbon Neutral Blockchain"@en ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf ngm:climate-aligned-finance ;
rdfs:subClassOf ngm:distributed-ledger-technology ;
rdfs:subClassOf ngm:green-infrastructure ;
rdfs:subClassOf ngm:sustainable-technology ;
rdfs:subClassOf _:r3977 ;
rdfs:subClassOf _:r3978 ;
rdfs:subClassOf _:r3979 ;
rdfs:subClassOf _:r3980 ;
rdfs:subClassOf _:r3981 ;
rdfs:subClassOf _:r3982 ;
rdfs:subClassOf _:r3983 ;
rdfs:subClassOf _:r3984 ;
rdfs:subClassOf _:r3985 ;
rdfs:subClassOf _:r3986 ;
rdfs:subClassOf _:r3987 ;
rdfs:subClassOf _:r3988 ;
rdfs:subClassOf _:r3989 ;
rdfs:subClassOf _:r3990 ;
rdfs:subClassOf _:r3991 ;
rdfs:subClassOf _:r3992 ;
rdfs:subClassOf _:r3993 ;
rdfs:subClassOf _:r3994 ;
rdfs:subClassOf _:r3995 ;
rdfs:subClassOf _:r3996 ;
skos:broader ngm:bc-governance-and-regulation ;
skos:broader ngm:blockchain ;
vc:bridgesTo ngm:sustainability ;
vc:contrastsWith ngm:bitcoin-proof-of-work-protocol-mining ;
vc:contrastsWith ngm:centralised-carbon-market ;
vc:contrastsWith ngm:energy-intensive-blockchain ;
vc:contrastsWith ngm:high-carbon-consensus ;
vc:contrastsWith ngm:proof-of-work ;
vc:contrastsWith ngm:traditional-carbon-registry ;
vc:dependsOn ngm:blockchain ;
vc:dependsOn ngm:carbon-credits ;
vc:dependsOn ngm:decentralised-network ;
vc:dependsOn ngm:energy-metering ;
vc:dependsOn ngm:oracle-network ;
vc:dependsOn ngm:proof-of-stake ;
vc:dependsOn ngm:renewable-energy ;
vc:dependsOn ngm:smart-contract ;
vc:enables ngm:carbon-credit-tracking ;
vc:enables ngm:carbon-credits ;
vc:enables ngm:carbon-markets ;
vc:enables ngm:climate-disclosure ;
vc:enables ngm:csrd-compliance ;
vc:enables ngm:esg-investing ;
vc:enables ngm:green-finance ;
vc:enables ngm:science-based-targets ;
vc:enables ngm:sustainable-supply-chain ;
vc:enables ngm:voluntary-carbon-market ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:carbon-credits ;
vc:hasPart ngm:carbon-offset-programme ;
vc:hasPart ngm:carbon-registry ;
vc:hasPart ngm:energy-metering-system ;
vc:hasPart ngm:ghg-protocol-accounting ;
vc:hasPart ngm:proof-of-stake ;
vc:hasPart ngm:renewable-energy-certificates ;
vc:hasPart ngm:renewable-energy-integration ;
vc:hasPart ngm:sustainability-reporting ;
vc:hasPart ngm:validator-node ;
vc:implements ngm:carbon-neutrality ;
vc:implements ngm:corporate-sustainability-reporting ;
vc:implements ngm:environmental-accounting ;
vc:implements ngm:iso-14064 ;
vc:implements ngm:net-zero-commitment ;
vc:implements ngm:paris-agreement ;
vc:implements ngm:science-based-targets ;
vc:qualityScore "0.53"^^xsd:float ;
vc:relatedTo ngm:algorand ;
vc:relatedTo ngm:blockchain ;
vc:relatedTo ngm:carbon-credits ;
vc:relatedTo ngm:carbon-markets ;
vc:relatedTo ngm:cardano ;
vc:relatedTo ngm:de-fi ;
vc:relatedTo ngm:energy-consumption ;
vc:relatedTo ngm:ethereum-smart-contract-platform ;
vc:relatedTo ngm:green-finance ;
vc:relatedTo ngm:hedera-hashgraph ;
vc:relatedTo ngm:polkadot ;
vc:relatedTo ngm:smart-contract ;
vc:relatedTo ngm:solana ;
vc:relatedTo ngm:tezos ;
vc:requires ngm:carbon-accounting ;
vc:requires ngm:carbon-registry ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:energy-audit ;
vc:requires ngm:renewable-energy-certificates ;
vc:requires ngm:scope-1-emissions ;
vc:requires ngm:scope-2-emissions ;
vc:requires ngm:scope-3-emissions ;
vc:requires ngm:third-party-verification ;
vc:slug "carbon-neutral-blockchain" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:energy-attribute-certificates ;
vc:standardizedBy ngm:ghg-protocol ;
vc:standardizedBy ngm:ghg-protocol-corporate-standard ;
vc:standardizedBy ngm:gold-standard ;
vc:standardizedBy ngm:integrity-council-for-the-voluntary-carbon-market ;
vc:standardizedBy ngm:iso-14064 ;
vc:standardizedBy ngm:pas-2060 ;
vc:standardizedBy ngm:verra-vcs-standard ;
vc:supports ngm:carbon-neutrality ;
vc:supports ngm:climate-commitments ;
vc:supports ngm:decarbonisation ;
vc:supports ngm:environmental-sustainability ;
vc:supports ngm:esg-reporting ;
vc:supports ngm:green-bond-market ;
vc:supports ngm:impact-investing ;
vc:supports ngm:sustainability ;
vc:supports ngm:task-force-on-climate-related-financial-disclosures ;
vc:uses ngm:carbon-offset ;
vc:uses ngm:climatetrade ;
vc:uses ngm:energy-attribute-certificates ;
vc:uses ngm:hashgraph-consensus ;
vc:uses ngm:klima-dao ;
vc:uses ngm:liquid-proof-of-stake ;
vc:uses ngm:proof-of-stake ;
vc:uses ngm:pure-proof-of-stake ;
vc:uses ngm:renewable-energy-certificates ;
vc:uses ngm:toucan-protocol .
ngm:carbon-neutral-certification a skos:Concept ;
rdfs:label "Carbon Neutral Certification"@en .
ngm:carbon-neutrality a owl:Class ;
rdfs:comment "Carbon neutrality is a state in which an entity — an organisation, product, event, or country — achieves a net-zero balance between its greenhouse gas emissions and the carbon dioxide it removes or offsets, such that its net contribution to atmospheric CO₂ concentration is zero over a defined accounting period. It is typically achieved through a combination of direct emissions reductions, procurement of renewable energy, and the purchase and retirement of independently verified carbon credits representing emissions avoided or removed elsewhere. Carbon neutrality is distinct from net-zero emissions, which generally requires deeper reductions and limits the role of offsets, and from climate positivity, which requires net negative emissions."@en ;
rdfs:label "Carbon Neutrality"@en ;
rdfs:subClassOf ngm:climate-policy ;
rdfs:subClassOf _:r4003 ;
rdfs:subClassOf _:r4004 ;
rdfs:subClassOf _:r4005 ;
rdfs:subClassOf _:r4006 ;
rdfs:subClassOf _:r4007 ;
vc:bridgesTo ngm:corporate-sustainability-reporting ;
vc:bridgesTo ngm:supply-chain-decarbonisation ;
vc:dependsOn ngm:science-based-targets ;
vc:dependsOn ngm:voluntary-carbon-market ;
vc:enables ngm:esg-reporting ;
vc:enables ngm:net-zero-targets ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:carbon-footprint-measurement ;
vc:hasPart ngm:carbon-neutrality-planning ;
vc:hasPart ngm:carbon-neutrality-verification ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:carbon-neutrality-verification ;
vc:relatedTo ngm:direct-air-capture ;
vc:relatedTo ngm:eu-green-claims-directive ;
vc:requires ngm:greenhouse-gas-accounting ;
vc:requires ngm:scope-3-emissions ;
vc:requires ngm:third-party-assurance ;
vc:slug "carbon-neutrality" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:paris-agreement ;
vc:standardizedBy ngm:pas-2060 ;
vc:uses ngm:carbon-credits ;
vc:uses ngm:carbon-offset-programme .
ngm:carbon-neutrality-planning a owl:Class ;
rdfs:comment "The strategic process of developing a comprehensive roadmap to achieve net-zero greenhouse gas emissions, encompassing emission measurement, science-based reduction targets, interim milestones, decarbonization actions, and residual emission neutralization through permanent carbon removal."@en ;
rdfs:label "Carbon Neutrality Planning"@en ;
rdfs:subClassOf ngm:sc-governance-and-safety ;
rdfs:subClassOf ngm:strategic-planning ;
rdfs:subClassOf _:r3997 ;
rdfs:subClassOf _:r3998 ;
rdfs:subClassOf _:r3999 ;
rdfs:subClassOf _:r4000 ;
skos:broader ngm:sc-governance-and-safety ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:infrastructure ;
vc:bridgesTo ngm:supply-chain ;
vc:contrastsWith ngm:carbon-offsetting ;
vc:enables ngm:carbon-offset ;
vc:enables ngm:climate-action ;
vc:enables ngm:decarbonization ;
vc:enables ngm:esg-reporting ;
vc:enables ngm:net-zero-targets ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:carbon-removal ;
vc:hasPart ngm:scope-1-emissions ;
vc:hasPart ngm:scope-2-emissions ;
vc:hasPart ngm:scope-3-emissions ;
vc:implements ngm:paris-agreement ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:corporate-governance ;
vc:relatedTo ngm:regulatory-compliance ;
vc:relatedTo ngm:sustainability-reporting ;
vc:requires ngm:ghg-baseline ;
vc:requires ngm:implementation-strategy ;
vc:requires ngm:reduction-targets ;
vc:requires ngm:science-based-targets ;
vc:slug "carbon-neutrality-planning" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:ghg-protocol ;
vc:uses ngm:carbon-accounting ;
vc:uses ngm:renewable-energy .
ngm:carbon-neutrality-verification a owl:Class ;
rdfs:comment "The independent third-party audit process that validates an organization's carbon neutrality claims by verifying emission calculations, reduction measures, and offset quality against established standards such as ISO 14068-1 and PAS 2060."@en ;
rdfs:label "Carbon Neutrality Verification"@en ;
rdfs:subClassOf ngm:environmental-verification ;
rdfs:subClassOf ngm:sc-governance-and-safety ;
rdfs:subClassOf _:r4001 ;
rdfs:subClassOf _:r4002 ;
skos:broader ngm:sc-governance-and-safety ;
vc:bridgesTo ngm:blockchain ;
vc:enables ngm:credibility-assurance ;
vc:enables ngm:greenwashing-prevention ;
vc:enables ngm:stakeholder-trust ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:documentation-package ;
vc:requires ngm:third-party-auditor ;
vc:requires ngm:verification-standard ;
vc:slug "carbon-neutrality-verification" ;
vc:sourceDomain "spatial-computing" .
ngm:carbon-offset a owl:Class ;
rdfs:comment "A carbon offset is a tradable instrument representing a measurable reduction, avoidance, or removal of one tonne of CO2-equivalent emissions, purchased to compensate for emissions occurring elsewhere. Offsets are generated by certified projects such as reforestation, renewable energy, or direct air capture and verified against recognised methodologies. They matter as a market mechanism for funding mitigation, though their credibility hinges on additionality, permanence, and avoidance of double-counting."@en ;
rdfs:label "Carbon Offset"@en ;
rdfs:subClassOf ngm:economic-mechanism ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:carbon-neutral-blockchain ;
vc:relatedTo ngm:ghg-protocol-corporate-standard ;
vc:slug "carbon-offset" ;
vc:sourceDomain "governance" .
ngm:carbon-offset-certificate a owl:Class ;
rdfs:comment "A verified document representing the reduction or removal of one metric ton of CO2 equivalent emissions, issued by recognized standards bodies after independent validation that confirms the underlying project's additionality, permanence, and measurability."@en ;
rdfs:label "Carbon Offset Certificate"@en ;
rdfs:subClassOf ngm:environmental-certificate ;
rdfs:subClassOf ngm:sc-governance-and-safety ;
skos:broader ngm:sc-governance-and-safety ;
vc:bridgesTo ngm:blockchain ;
vc:enables ngm:carbon-neutrality ;
vc:enables ngm:climate-investment ;
vc:enables ngm:emissions-compensation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:project-verification ;
vc:requires ngm:registry-issuance ;
vc:requires ngm:third-party-validation ;
vc:slug "carbon-offset-certificate" ;
vc:sourceDomain "spatial-computing" .
ngm:carbon-offset-programme a owl:Class ;
rdfs:comment "A carbon offset programme is a structured scheme that generates, certifies, issues, and retires carbon credits representing greenhouse gas emissions reductions or removals achieved by specific projects or activities, providing a mechanism by which organisations or individuals can compensate for their own emissions by financing equivalent climate action elsewhere. Programmes operate under standards bodies — including the Verified Carbon Standard (Verra), Gold Standard, American Carbon Registry (ACR), and Climate Action Reserve — that define methodologies for quantifying emissions impacts, require independent verification, and maintain public registries to prevent double-counting of credits. Projects include avoided deforestation (REDD+), renewable energy, methane capture, reforestation, and engineered carbon removal."@en ;
rdfs:label "Carbon Offset Programme"@en ;
rdfs:subClassOf ngm:carbon-offset-trading ;
vc:enables ngm:carbon-neutrality ;
vc:enables ngm:voluntary-carbon-market ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:environmental-certificate ;
vc:relatedTo ngm:esg-reporting ;
vc:slug "carbon-offset-programme" ;
vc:sourceDomain "governance" ;
vc:uses ngm:carbon-credits ;
vc:uses ngm:carbon-offset-certificate ;
vc:uses ngm:carbon-registry .
ngm:carbon-offset-trading a owl:Class ;
rdfs:comment "The buying and selling of verified carbon credits on voluntary and compliance markets through exchanges and over-the-counter transactions, enabling price discovery, liquidity provision, and efficient allocation of climate finance to emission reduction projects."@en ;
rdfs:label "Carbon Offset Trading"@en ;
rdfs:subClassOf ngm:environmental-trading ;
rdfs:subClassOf ngm:sc-governance-and-safety ;
rdfs:subClassOf _:r4008 ;
skos:broader ngm:sc-governance-and-safety ;
vc:bridgesTo ngm:blockchain ;
vc:enables ngm:carbon-price-discovery ;
vc:enables ngm:climate-finance ;
vc:enables ngm:offset-liquidity ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:carbon-registry ;
vc:requires ngm:market-infrastructure ;
vc:requires ngm:trading-platform ;
vc:slug "carbon-offset-trading" ;
vc:sourceDomain "spatial-computing" .
ngm:carbon-offsetting a owl:Class ;
rdfs:comment "Carbon offsetting is the practice whereby an entity compensates for its greenhouse gas emissions by financing or undertaking activities that achieve an equivalent reduction or removal of carbon dioxide equivalent (CO2e) elsewhere in the global economy. Offsets are quantified in standardised units — typically one tonne of CO2e per credit — and must satisfy criteria of additionality, permanence, measurability, and independent verification to be considered credible. The mechanism operates across compliance markets (e.g. the EU Emissions Trading System) and voluntary markets (e.g. Gold Standard, Verra VCS), and spans project types including afforestation, improved cookstoves, methane capture, and direct air capture. Controversy around offset quality, permanence risks, and potential for greenwashing has driven increasing scrutiny from regulators, standards bodies, and civil society."@en ;
rdfs:label "Carbon Offsetting"@en ;
rdfs:subClassOf ngm:sustainability ;
rdfs:subClassOf _:r4009 ;
rdfs:subClassOf _:r4010 ;
rdfs:subClassOf _:r4011 ;
rdfs:subClassOf _:r4012 ;
rdfs:subClassOf _:r4013 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:smart-contracts ;
vc:contrastsWith ngm:carbon-reduction ;
vc:contrastsWith ngm:greenwashing ;
vc:enables ngm:carbon-neutrality ;
vc:enables ngm:climate-finance ;
vc:enables ngm:net-zero ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:carbon-credits ;
vc:hasPart ngm:carbon-offset ;
vc:hasPart ngm:carbon-registry ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:climate-change ;
vc:relatedTo ngm:esg ;
vc:relatedTo ngm:paris-agreement ;
vc:relatedTo ngm:scope-3-emissions ;
vc:requires ngm:additionality ;
vc:requires ngm:carbon-accounting ;
vc:requires ngm:measurement-reporting-and-verification ;
vc:slug "carbon-offsetting" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:gold-standard ;
vc:standardizedBy ngm:iso-14064 ;
vc:standardizedBy ngm:verified-carbon-standard ;
vc:uses ngm:emissions-trading-scheme ;
vc:uses ngm:life-cycle-assessment ;
vc:uses ngm:voluntary-carbon-market .
ngm:carbon-price-discovery a owl:Class ;
rdfs:comment "Carbon price discovery is the process by which market participants collectively determine the equilibrium price of carbon emission allowances or credits through the interaction of supply and demand in regulated compliance markets and voluntary carbon markets. It encompasses the mechanisms, venues, and information flows that translate abatement costs, regulatory constraints, and economic activity into observable carbon prices. Transparent price signals are essential for directing investment towards emissions reduction and for evaluating the economic cost of decarbonisation."@en ;
rdfs:label "Carbon Price Discovery"@en ;
rdfs:subClassOf ngm:carbon-markets ;
vc:enables ngm:carbon-offset-trading ;
vc:enables ngm:environmental-asset-market ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:asset-liquidity ;
vc:relatedTo ngm:carbon-credits ;
vc:relatedTo ngm:environmental-trading ;
vc:slug "carbon-price-discovery" ;
vc:sourceDomain "finance" ;
vc:uses ngm:automated-market-maker ;
vc:uses ngm:decentralized-exchange .
ngm:carbon-pricing a skos:Concept ;
rdfs:label "Carbon Pricing"@en .
ngm:carbon-project-developers a skos:Concept ;
rdfs:label "Carbon Project Developers"@en .
ngm:carbon-reduction a skos:Concept ;
rdfs:label "Carbon Reduction"@en .
ngm:carbon-registries a skos:Concept ;
rdfs:label "Carbon Registries"@en .
ngm:carbon-registry a owl:Class ;
rdfs:comment "A centralized database system that tracks the issuance, ownership, transfer, and retirement of carbon credits, assigning unique serial numbers to each credit for full lifecycle traceability and preventing double-counting across voluntary and compliance carbon markets."@en ;
rdfs:label "Carbon Registry"@en ;
rdfs:subClassOf ngm:environmental-registry ;
rdfs:subClassOf _:r4014 ;
rdfs:subClassOf _:r4015 ;
rdfs:subClassOf _:r4016 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:smart-contract ;
vc:contrastsWith ngm:compliance-carbon-market ;
vc:contrastsWith ngm:voluntary-carbon-market ;
vc:enables ngm:carbon-credit-retirement ;
vc:enables ngm:carbon-offsetting ;
vc:enables ngm:credit-tracking ;
vc:enables ngm:double-counting-prevention ;
vc:enables ngm:market-transparency ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:gold-standard ;
vc:implements ngm:verra-vcs-standard ;
vc:isPartOf ngm:carbon-markets ;
vc:qualityScore "0.65"^^xsd:float ;
vc:relatedTo ngm:greenhouse-gas-accounting ;
vc:relatedTo ngm:redd-plus ;
vc:requires ngm:database-infrastructure ;
vc:requires ngm:regulatory-compliance ;
vc:requires ngm:third-party-auditing ;
vc:requires ngm:unique-identifiers ;
vc:requires ngm:verification-process ;
vc:slug "carbon-registry" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:corsia .
ngm:carbon-registry-bridge a skos:Concept ;
rdfs:label "Carbon Registry Bridge"@en .
ngm:carbon-removal a skos:Concept ;
rdfs:label "Carbon Removal"@en .
ngm:carbon-sequestration a skos:Concept ;
rdfs:label "Carbon Sequestration"@en .
ngm:carbon-standard-certification a owl:Class ;
rdfs:comment "Carbon standard certification is the process by which carbon-reduction projects and the credits they generate are independently validated and verified against a recognised standard such as Verra VCS, Gold Standard, or the ICVCM framework. Certification confirms that claimed emission reductions are real, additional, permanent, and properly quantified before credits are issued into a registry. It is the trust anchor of voluntary and compliance carbon markets, distinguishing high-integrity credits from low-quality ones."@en ;
rdfs:label "Carbon Standard Certification"@en ;
rdfs:subClassOf ngm:technical-standard ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:carbon-credit-tracking ;
vc:relatedTo ngm:icvcm-core-carbon-principles ;
vc:slug "carbon-standard-certification" ;
vc:sourceDomain "governance" .
ngm:carbon-tax a owl:Class ;
rdfs:comment "A carbon tax is a government levy charged per tonne of carbon dioxide (or CO2-equivalent) emitted, putting an explicit, predictable price on greenhouse-gas pollution so that emitters internalise the climate damage their activities cause. Unlike an emissions trading scheme, which caps the quantity of emissions and lets the price float, a carbon tax fixes the price and lets emitted quantities adjust; examples include Sweden's levy of over 100 euros per tonne and carbon taxes in Canada, Singapore and South Africa."@en ;
rdfs:label "Carbon Tax"@en ;
rdfs:subClassOf ngm:climate-policy ;
vc:contrastsWith ngm:carbon-credits ;
vc:contrastsWith ngm:emissions-trading-scheme ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:carbon-markets ;
vc:relatedTo ngm:compliance-carbon-market ;
vc:relatedTo ngm:voluntary-carbon-market ;
vc:slug "carbon-tax" ;
vc:sourceDomain "governance" .
ngm:carbon-token-standard a skos:Concept ;
rdfs:label "Carbon Token Standard"@en .
ngm:carbon-tokenisation a skos:Concept ;
rdfs:label "Carbon Tokenisation"@en .
ngm:carboncreditretirement a skos:Concept ;
rdfs:label "Carboncreditretirement"@en .
ngm:carbonemissions a skos:Concept ;
rdfs:label "Carbonemissions"@en .
ngm:card-network a skos:Concept ;
rdfs:label "Card Network"@en .
ngm:cardano a owl:Class ;
rdfs:comment "Cardano is a public proof-of-stake blockchain platform launched in 2017 by IOHK, with Charles Hoskinson, a co-founder of Ethereum, among its founders. It is distinctive for its emphasis on peer-reviewed academic research and formal methods, and its consensus protocol Ouroboros was the first proof-of-stake protocol with published security proofs. The platform separates a settlement layer for its ADA cryptocurrency from a computation layer for smart contracts, which were enabled through the Alonzo upgrade in 2021. Cardano uses an extended UTXO accounting model and the functional language Plutus for on-chain logic."@en ;
rdfs:label "Cardano"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf ngm:blockchain-domain ;
rdfs:subClassOf _:r4018 ;
rdfs:subClassOf _:r4019 ;
rdfs:subClassOf _:r4020 ;
rdfs:subClassOf _:r4021 ;
skos:broader ngm:bc-protocol-and-consensus ;
skos:broader ngm:blockchain ;
vc:bridgesTo ngm:decentralised-identity ;
vc:bridgesTo ngm:ethereum-smart-contract-platform ;
vc:bridgesTo ngm:supply-chain-traceability ;
vc:contrastsWith ngm:bitcoin ;
vc:contrastsWith ngm:ethereum ;
vc:contrastsWith ngm:solana ;
vc:enables ngm:de-fi ;
vc:enables ngm:native-token ;
vc:enables ngm:on-chain-governance ;
vc:enables ngm:smart-contract ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:settlement-layer ;
vc:implements ngm:formal-verification ;
vc:implements ngm:ouroboros-consensus ;
vc:implements ngm:utxo-model ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:consensus-mechanism ;
vc:relatedTo ngm:layer-1-blockchain ;
vc:requires ngm:cryptocurrency ;
vc:requires ngm:proof-of-stake ;
vc:requires ngm:utxo ;
vc:slug "cardano" ;
vc:sourceDomain "blockchain" .
ngm:cardano-smart-contracts a skos:Concept ;
rdfs:label "Cardano Smart Contracts"@en .
ngm:career-strategy a owl:Class ;
rdfs:comment "The deliberate planning and adaptation of individual professional skills, roles, and trajectories in response to technological and market shifts."@en ;
rdfs:label "Career Strategy"@en ;
rdfs:subClassOf ngm:ai-adoption ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-adoption ;
vc:relatedTo ngm:ai-talent ;
vc:relatedTo ngm:change-management ;
vc:slug "career-strategy" ;
vc:sourceDomain "governance" .
ngm:carnegie-learning-mathia a skos:Concept ;
rdfs:label "Carnegie Learning Mathia"@en .
ngm:carnegie-mellon-university a skos:Concept ;
rdfs:label "Carnegie Mellon University"@en .
ngm:carrier-to-noise-ratio a owl:Class ;
rdfs:label "Carrier-to-noise Ratio"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:satellite-communication ;
vc:slug "carrier-to-noise-ratio" ;
vc:sourceDomain "space-science-and-systems" .
ngm:carroll-proportional-representation a skos:Concept ;
rdfs:label "Carroll Proportional Representation"@en .
ngm:carry-over-mechanism a skos:Concept ;
rdfs:label "Carry Over Mechanism"@en .
ngm:cartagena-protocol-on-biosafety a skos:Concept ;
rdfs:label "Cartagena Protocol On Biosafety"@en .
ngm:cartesian-dualism a skos:Concept ;
rdfs:label "Cartesian Dualism"@en .
ngm:cartesian-space a skos:Concept ;
rdfs:label "Cartesian Space"@en .
ngm:cartographic-generalisation a owl:Class ;
rdfs:label "Cartographic Generalisation"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-processing ;
vc:relatedTo ngm:geographic-information-system ;
vc:slug "cartographic-generalisation" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:cartography a skos:Concept ;
rdfs:label "Cartography"@en .
ngm:casadi a skos:Concept ;
rdfs:label "Casadi"@en .
ngm:cascade-control a skos:Concept ;
rdfs:label "Cascade Control"@en .
ngm:cascadecontrol a skos:Concept ;
rdfs:label "Cascadecontrol"@en .
ngm:cascadeur a skos:Concept ;
rdfs:label "Cascadeur"@en .
ngm:cascading-water a owl:Class ;
rdfs:label "Cascading Water"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-system-phenomena ;
vc:slug "cascading-water" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:case-based-reasoning a skos:Concept ;
rdfs:label "Case Based Reasoning"@en .
ngm:case-management a owl:Class ;
rdfs:comment "A business-process discipline for handling unstructured, knowledge-intensive work items — 'cases' — whose resolution path cannot be fully predetermined, such as compliance investigations, insurance claims, legal matters, and customer disputes. Each case aggregates documents, tasks, participants, deadlines, and an audit trail around a single subject, and progresses through investigation, decision, and resolution stages guided by worker judgement rather than a rigid predefined flow."@en ;
rdfs:label "Case Management"@en ;
rdfs:subClassOf ngm:business-process-management ;
vc:enables ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:transaction-monitoring ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:case-management-system ;
vc:relatedTo ngm:records-management ;
vc:relatedTo ngm:workflow-automation ;
vc:slug "case-management" ;
vc:sourceDomain "governance" .
ngm:case-management-system a owl:Class ;
rdfs:comment "A software platform that tracks discrete units of investigative or remedial work—cases—from intake through triage, assignment, evidence gathering, escalation, and resolution, providing structured workflows, deadline management, and a complete audit trail. In compliance and legal operations, a case management system is the destination for alerts raised by monitoring controls, ensuring each potential breach is documented, investigated by accountable owners, and closed with a defensible record for regulators."@en ;
rdfs:label "Case Management System"@en ;
rdfs:subClassOf ngm:enterprise-software ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:case-management ;
vc:isPartOf ngm:compliance-monitoring ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:legal-technology ;
vc:relatedTo ngm:regulatory-compliance ;
vc:slug "case-management-system" ;
vc:sourceDomain "governance" ;
vc:uses ngm:audit-trail ;
vc:uses ngm:workflow-automation .
ngm:cash-app a owl:Class ;
rdfs:comment "Cash App is a mobile payment service operated by Block, Inc. that lets users send money, hold balances, and buy and sell bitcoin and stocks."@en ;
rdfs:label "Cash App"@en ;
rdfs:subClassOf ngm:payment-system ;
rdfs:subClassOf _:r4022 ;
vc:bridgesTo ngm:bitcoin-proof-of-work-protocol ;
vc:bridgesTo ngm:block ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:payment-system ;
vc:slug "cash-app" ;
vc:sourceDomain "finance" .
ngm:cash-creation-process a skos:Concept ;
rdfs:label "Cash Creation Process"@en .
ngm:cash-transaction a skos:Concept ;
rdfs:label "Cash Transaction"@en .
ngm:cashu a owl:Class ;
rdfs:comment "Cashu is a free and open-source Chaumian ecash protocol designed for Bitcoin and the Lightning Network, first released in October 2022 by the pseudonymous developer Calle (alias @calle), a PhD physicist and Bitcoin developer."@en ;
rdfs:label "Cashu"@en ;
rdfs:subClassOf ngm:bc-token-and-asset ;
rdfs:subClassOf ngm:bearer-instrument ;
rdfs:subClassOf ngm:bitcoin-proof-of-work-protocol-layer-2 ;
rdfs:subClassOf ngm:bitcoinprivacytools ;
rdfs:subClassOf ngm:chaumian-ecash ;
rdfs:subClassOf ngm:chaumianecash ;
rdfs:subClassOf ngm:digital-cash ;
rdfs:subClassOf ngm:lightningapplications ;
rdfs:subClassOf ngm:privacy-protocol ;
rdfs:subClassOf _:r4023 ;
rdfs:subClassOf _:r4024 ;
rdfs:subClassOf _:r4025 ;
rdfs:subClassOf _:r4026 ;
rdfs:subClassOf _:r4027 ;
rdfs:subClassOf _:r4028 ;
rdfs:subClassOf _:r4029 ;
rdfs:subClassOf _:r4030 ;
rdfs:subClassOf _:r4031 ;
rdfs:subClassOf _:r4032 ;
skos:broader ngm:bc-token-and-asset ;
vc:bridgesTo ngm:chaumian-ecash ;
vc:contrastsWith ngm:ark-protocol ;
vc:contrastsWith ngm:fedimint ;
vc:contrastsWith ngm:lightning-network-privacy ;
vc:contrastsWith ngm:monero ;
vc:contrastsWith ngm:on-chain-bitcoin ;
vc:contrastsWith ngm:zcash ;
vc:dependsOn ngm:bitcoin-proof-of-work-protocol ;
vc:dependsOn ngm:elliptic-curve-cryptography ;
vc:dependsOn ngm:lightning-network ;
vc:dependsOn ngm:opensats ;
vc:dependsOn ngm:secp256k1 ;
vc:enables ngm:anonymous-payments ;
vc:enables ngm:bearer-token-transfer ;
vc:enables ngm:financial-privacy ;
vc:enables ngm:micropayments ;
vc:enables ngm:multi-mint-payments ;
vc:enables ngm:offline-transactions ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:blind-signatures ;
vc:hasPart ngm:cashu-mint ;
vc:hasPart ngm:cashu-nut-specifications ;
vc:hasPart ngm:ecash ;
vc:hasPart ngm:keyset ;
vc:hasPart ngm:lightning-invoice ;
vc:hasPart ngm:proof ;
vc:hasPart ngm:spent-token-registry ;
vc:implements ngm:bearer-token-model ;
vc:implements ngm:blind-signatures ;
vc:implements ngm:cryptographic-proofs ;
vc:implements ngm:nut-protocol-specifications ;
vc:implements ngm:pay-to-pubkey-spending-conditions ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:bearer-tokens ;
vc:relatedTo ngm:bis-project-tourbillon ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol ;
vc:relatedTo ngm:blind-signatures ;
vc:relatedTo ngm:btcpayserver ;
vc:relatedTo ngm:calle-callebtc ;
vc:relatedTo ngm:cashu-development-kit ;
vc:relatedTo ngm:chaumian-ecash ;
vc:relatedTo ngm:cryptographic-protocols ;
vc:relatedTo ngm:david-chaum ;
vc:relatedTo ngm:deterministicsecrets ;
vc:relatedTo ngm:digicash ;
vc:relatedTo ngm:digital-cash ;
vc:relatedTo ngm:dleqproofs ;
vc:relatedTo ngm:ecash ;
vc:relatedTo ngm:ecb-digital-euro-ecash-track ;
vc:relatedTo ngm:egge ;
vc:relatedTo ngm:elliptic-curve-cryptography ;
vc:relatedTo ngm:enuts ;
vc:relatedTo ngm:fedimint ;
vc:relatedTo ngm:financial-privacy ;
vc:relatedTo ngm:gandlaf ;
vc:relatedTo ngm:htlcs ;
vc:relatedTo ngm:lightning-network ;
vc:relatedTo ngm:lollerfirst ;
vc:relatedTo ngm:minibits ;
vc:relatedTo ngm:misovan ;
vc:relatedTo ngm:nostr ;
vc:relatedTo ngm:nutshell ;
vc:relatedTo ngm:opensats ;
vc:relatedTo ngm:pablof7z ;
vc:relatedTo ngm:paytopublickey ;
vc:relatedTo ngm:privacy ;
vc:relatedTo ngm:swiss-national-bank-ecash-research ;
vc:relatedTo ngm:thesimplekid-m1sterc001guy ;
vc:relatedTo ngm:vnprc ;
vc:relatedTo ngm:zero-knowledge-proof ;
vc:requires ngm:bitcoin-proof-of-work-protocol ;
vc:requires ngm:blind-signatures ;
vc:requires ngm:elliptic-curve-cryptography ;
vc:requires ngm:hash-function ;
vc:requires ngm:hash-functions ;
vc:requires ngm:lightning-network ;
vc:slug "cashu" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:nut-00-cryptography-and-models ;
vc:standardizedBy ngm:nut-01-mint-public-keys ;
vc:standardizedBy ngm:nut-02-keysets-and-fees ;
vc:standardizedBy ngm:nut-03-swapping-tokens ;
vc:standardizedBy ngm:nut-04-minting-tokens ;
vc:standardizedBy ngm:nut-05-melting-tokens ;
vc:supports ngm:ai-agent-payments ;
vc:supports ngm:censorship-resistance ;
vc:supports ngm:financial-privacy ;
vc:supports ngm:merchant-payments ;
vc:supports ngm:nostr ;
vc:supports ngm:self-custody ;
vc:uses ngm:blind-signatures ;
vc:uses ngm:bolt-11 ;
vc:uses ngm:bolt12-offers ;
vc:uses ngm:lightning-invoices ;
vc:uses ngm:nfc-payments ;
vc:uses ngm:qr-codes ;
vc:uses ngm:web-sockets .
ngm:cashu-development-kit a skos:Concept ;
rdfs:label "Cashu Development Kit"@en .
ngm:cashu-mint a skos:Concept ;
rdfs:label "Cashu Mint"@en .
ngm:cashu-nut-specifications a skos:Concept ;
rdfs:label "Cashu Nut Specifications"@en .
ngm:casper-ffg a owl:Class ;
rdfs:comment "Casper FFG (the Friendly Finality Gadget) is a proof-of-stake finality mechanism that overlays a checkpoint-based voting protocol on an underlying block proposal chain. Validators stake deposits and vote in two rounds to justify and then finalise checkpoints, after which reverting them would require destroying at least one third of the total stake. It introduces economic finality with slashing penalties for equivocation, providing strong accountability without requiring a full consensus overhaul."@en ;
rdfs:label "Casper Ffg"@en ;
rdfs:subClassOf ngm:finality-gadget ;
rdfs:subClassOf _:r4033 ;
rdfs:subClassOf _:r4034 ;
vc:contrastsWith ngm:byzantine-fault-tolerance ;
vc:enables ngm:blockchain-security ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:finality ;
vc:implements ngm:proof-of-stake ;
vc:isPartOf ngm:consensus-mechanism ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:ethereum ;
vc:relatedTo ngm:finality ;
vc:relatedTo ngm:slashing ;
vc:requires ngm:staking ;
vc:requires ngm:validator ;
vc:slug "casper-ffg" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:ethereum ;
vc:supports ngm:pos-consensus ;
vc:supports ngm:proof-of-stake ;
vc:uses ngm:slashing ;
vc:uses ngm:validator-set .
ngm:cast a skos:Concept ;
rdfs:label "Cast"@en .
ngm:caster-wheel a skos:Concept ;
rdfs:label "Caster Wheel"@en .
ngm:castle-and-moat-architecture a skos:Concept ;
rdfs:label "Castle And Moat Architecture"@en .
ngm:cat-ai-infrastructure a owl:Class ;
a skos:Concept ;
rdfs:comment "Intermediate category of the Artificial Intelligence domain covering the compute, data, tooling, and platform infrastructure that supports training, fine-tuning, serving, and orchestration of machine-learning and foundation-model systems — including accelerators, distributed-training frameworks, model registries, and inference platforms."@en ;
rdfs:label "AI Infrastructure (Artificial Intelligence)"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.85"^^xsd:float ;
vc:slug "cat-ai-infrastructure" ;
vc:sourceDomain "artificial-intelligence" .
ngm:catapult-network a skos:Concept ;
rdfs:label "Catapult Network"@en .
ngm:catastrophic-ai-risk a skos:Concept ;
rdfs:label "Catastrophic AI Risk"@en .
ngm:catastrophic-forgetting a skos:Concept ;
rdfs:label "Catastrophic Forgetting"@en .
ngm:catastrophic-risk a skos:Concept ;
rdfs:label "Catastrophic Risk"@en .
ngm:catastrophic-risk-assessment a owl:Class ;
rdfs:comment "Catastrophic risk assessment is the systematic evaluation of low-probability, high-severity hazards that could cause widespread harm, including the danger that advanced AI systems may enable mass casualties or societal-scale disruption. In AI governance it involves measuring a model's potential to contribute to chemical, biological, cyber, or autonomous-weapon threats before deployment. It matters because frontier-AI regulation, such as proposed state safety bills, conditions release on credible assessment and mitigation of these tail risks."@en ;
rdfs:label "Catastrophic Risk Assessment"@en ;
rdfs:subClassOf ngm:ai-safety ;
rdfs:subClassOf ngm:probabilistic-risk-assessment ;
rdfs:subClassOf ngm:risk-assessment ;
rdfs:subClassOf _:r4035 ;
rdfs:subClassOf _:r4036 ;
rdfs:subClassOf _:r4037 ;
rdfs:subClassOf _:r4038 ;
rdfs:subClassOf _:r4039 ;
rdfs:subClassOf _:r4040 ;
rdfs:subClassOf _:r4041 ;
rdfs:subClassOf _:r4042 ;
vc:contrastsWith ngm:ai-ethics ;
vc:contrastsWith ngm:beneficial-ai-risk ;
vc:contrastsWith ngm:narrow-ai-risk ;
vc:contrastsWith ngm:near-term-ai-risk ;
vc:dependsOn ngm:ai-safety ;
vc:dependsOn ngm:capability-forecasting ;
vc:dependsOn ngm:expert-elicitation ;
vc:dependsOn ngm:foundation-model ;
vc:dependsOn ngm:model-evaluation ;
vc:dependsOn ngm:red-teaming ;
vc:dependsOn ngm:scaling-laws ;
vc:enables ngm:ai-governance ;
vc:enables ngm:ai-regulation ;
vc:enables ngm:biosecurity ;
vc:enables ngm:catastrophic-risk-reduction ;
vc:enables ngm:existential-risk ;
vc:enables ngm:human-oversight ;
vc:enables ngm:responsible-scaling-policy ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:adversarial-elicitation ;
vc:hasPart ngm:cbrn-risk-assessment ;
vc:hasPart ngm:dangerous-capability-evaluation ;
vc:hasPart ngm:emergency-response ;
vc:hasPart ngm:expert-elicitation ;
vc:hasPart ngm:fault-tree-analysis ;
vc:hasPart ngm:red-teaming ;
vc:hasPart ngm:threat-modelling ;
vc:hasPart ngm:uplift-quantification ;
vc:implements ngm:failure-mode-effects-analysis ;
vc:implements ngm:fault-tree-analysis ;
vc:implements ngm:probabilistic-risk-assessment ;
vc:implements ngm:red-teaming ;
vc:implements ngm:threat-modelling ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:ai-alignment ;
vc:relatedTo ngm:ai-safety-level ;
vc:relatedTo ngm:ai-security-institute ;
vc:relatedTo ngm:apollo-research ;
vc:relatedTo ngm:biosecurity ;
vc:relatedTo ngm:california-ai-bill ;
vc:relatedTo ngm:capability-forecasting ;
vc:relatedTo ngm:cbrn-risk ;
vc:relatedTo ngm:corrigibility ;
vc:relatedTo ngm:cybersecurity ;
vc:relatedTo ngm:dangerous-capability-evaluation ;
vc:relatedTo ngm:emergency-response ;
vc:relatedTo ngm:eu-ai-act-regulatory-instrument ;
vc:relatedTo ngm:existential-risk ;
vc:relatedTo ngm:global-catastrophic-risk ;
vc:relatedTo ngm:mesa-optimisation ;
vc:relatedTo ngm:metr ;
vc:relatedTo ngm:responsible-scaling-policy ;
vc:requires ngm:capability-forecasting ;
vc:requires ngm:dangerous-capability-evaluation ;
vc:requires ngm:expert-elicitation ;
vc:requires ngm:foundation-model ;
vc:requires ngm:model-evaluation ;
vc:requires ngm:red-teaming ;
vc:requires ngm:scaling-laws ;
vc:slug "catastrophic-risk-assessment" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:california-sb53 ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:ai-governance ;
vc:supports ngm:ai-safety ;
vc:supports ngm:alignment ;
vc:supports ngm:biosecurity ;
vc:supports ngm:catastrophic-risk-reduction ;
vc:supports ngm:eu-ai-act-regulatory-instrument ;
vc:supports ngm:existential-risk ;
vc:supports ngm:responsible-ai ;
vc:supports ngm:responsible-scaling-policy ;
vc:uses ngm:adversarial-machine-learning ;
vc:uses ngm:capability-forecasting ;
vc:uses ngm:dangerous-capability-evaluation ;
vc:uses ngm:evaluation-benchmarks-and-leaderboards ;
vc:uses ngm:expert-elicitation ;
vc:uses ngm:harmbench ;
vc:uses ngm:model-evaluation ;
vc:uses ngm:red-teaming ;
vc:uses ngm:wmdp .
ngm:catastrophic-risk-reduction a owl:Class ;
rdfs:comment "Catastrophic risk reduction is the set of interventions, controls, and governance measures aimed at lowering the probability or severity of large-scale harms, particularly those posed by advanced AI systems. It spans technical safeguards such as alignment and capability control, organisational measures such as staged deployment and incident response, and policy measures such as compute governance. It is a core goal of AI safety and alignment work because it targets the tail risks that could threaten societal stability or human survival."@en ;
rdfs:label "Catastrophic Risk Reduction"@en ;
rdfs:subClassOf ngm:ai-safety ;
rdfs:subClassOf ngm:global-catastrophic-risk ;
rdfs:subClassOf ngm:risk-management ;
rdfs:subClassOf _:r4043 ;
rdfs:subClassOf _:r4044 ;
rdfs:subClassOf _:r4045 ;
rdfs:subClassOf _:r4046 ;
rdfs:subClassOf _:r4047 ;
rdfs:subClassOf _:r4048 ;
rdfs:subClassOf _:r4049 ;
rdfs:subClassOf _:r4050 ;
rdfs:subClassOf _:r4051 ;
rdfs:subClassOf _:r4052 ;
rdfs:subClassOf _:r4053 ;
rdfs:subClassOf _:r4054 ;
rdfs:subClassOf _:r4055 ;
rdfs:subClassOf _:r4056 ;
vc:contrastsWith ngm:ai-capabilities-research ;
vc:contrastsWith ngm:mesa-optimisation ;
vc:contrastsWith ngm:reward-hacking ;
vc:dependsOn ngm:ai-alignment ;
vc:dependsOn ngm:constitutional-ai-training-methodology ;
vc:dependsOn ngm:existential-risk ;
vc:dependsOn ngm:reinforcement-learning-from-human-feedback ;
vc:enables ngm:ai-ethics ;
vc:enables ngm:ai-governance ;
vc:enables ngm:eu-ai-act-regulatory-instrument ;
vc:enables ngm:responsible-ai ;
vc:enables ngm:trustworthy-ai ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:ai-safety-institute ;
vc:hasPart ngm:capability-evaluation ;
vc:hasPart ngm:compute-governance ;
vc:hasPart ngm:corrigibility ;
vc:hasPart ngm:interpretability ;
vc:hasPart ngm:red-teaming ;
vc:hasPart ngm:responsible-scaling-policy ;
vc:hasPart ngm:scalable-oversight ;
vc:implements ngm:ai-governance-framework ;
vc:implements ngm:ai-safety ;
vc:implements ngm:value-alignment ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:ai-alignment ;
vc:relatedTo ngm:ai-existential-risk-probability-estimate ;
vc:relatedTo ngm:ai-governance-law-and-privacy ;
vc:relatedTo ngm:bletchley-declaration ;
vc:relatedTo ngm:compute-governance ;
vc:relatedTo ngm:existential-risk ;
vc:relatedTo ngm:global-catastrophic-risk ;
vc:relatedTo ngm:iso-iec-42001 ;
vc:relatedTo ngm:nist-ai-rmf ;
vc:relatedTo ngm:safety-and-alignment ;
vc:requires ngm:ai-alignment ;
vc:requires ngm:ai-safety ;
vc:requires ngm:formal-verification ;
vc:requires ngm:human-oversight ;
vc:requires ngm:interpretability ;
vc:requires ngm:model-evaluation ;
vc:slug "catastrophic-risk-reduction" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:ai-safety-institute ;
vc:standardizedBy ngm:aisi-frontier-ai-safety-framework ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:ai-system ;
vc:supports ngm:deep-learning ;
vc:supports ngm:frontier-ai ;
vc:supports ngm:large-language-model ;
vc:uses ngm:adversarial-machine-learning ;
vc:uses ngm:distributional-shift ;
vc:uses ngm:mechanistic-interpretability ;
vc:uses ngm:red-teaming .
ngm:categorical-emotion-classification a skos:Concept ;
rdfs:label "Categorical Emotion Classification"@en .
ngm:categorical-emotion-model a skos:Concept ;
rdfs:label "Categorical Emotion Model"@en .
ngm:categorical-encoding a skos:Concept ;
rdfs:label "Categorical Encoding"@en .
ngm:category-hierarchies a owl:Class ;
rdfs:comment "A structured classification system that organizes concepts, objects, or information into parent-child relationships forming a tree-like taxonomy, enabling logical navigation from broad categories to specific subcategories for knowledge organization and content management."@en ;
rdfs:label "Category Hierarchies"@en ;
rdfs:subClassOf ngm:knowledge-organization-system ;
rdfs:subClassOf ngm:sc-standards-and-interop ;
rdfs:subClassOf _:r4057 ;
skos:broader ngm:sc-standards-and-interop ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:knowledge-organization-system ;
vc:enables ngm:content-classification ;
vc:enables ngm:navigation-structure ;
vc:enables ngm:semantic-organization ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:classification-rules ;
vc:requires ngm:taxonomy-design ;
vc:requires ngm:term-relationships ;
vc:slug "category-hierarchies" ;
vc:sourceDomain "spatial-computing" .
ngm:category-theory a skos:Concept ;
rdfs:label "Category Theory"@en .
ngm:causal-attention a owl:Class ;
rdfs:comment "Causal Attention (also called masked self-attention) is an attention mechanism where each token position attends only to itself and earlier positions in the sequence, enforced via an upper-triangular mask applied before softmax. This unidirectional constraint is essential for autoregressive language model training and inference, ensuring predictions at position i depend only on positions less than i."@en ;
rdfs:label "Causal Attention"@en ;
rdfs:subClassOf ngm:ai-model-architecture ;
rdfs:subClassOf ngm:attention-mechanism ;
rdfs:subClassOf _:r4058 ;
skos:broader ngm:ai-model-architecture ;
vc:bridgesTo ngm:computer-vision ;
vc:contrastsWith ngm:transformer-architecture ;
vc:enables ngm:gpt ;
vc:enables ngm:language-modeling ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:isPartOf ngm:decoder ;
vc:isPartOf ngm:transformer ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:self-attention ;
vc:slug "causal-attention" ;
vc:sourceDomain "artificial-intelligence" .
ngm:causal-broadcast a skos:Concept ;
rdfs:label "Causal Broadcast"@en .
ngm:causal-broadcast-protocol a skos:Concept ;
rdfs:label "Causal Broadcast Protocol"@en .
ngm:causal-consistency a skos:Concept ;
rdfs:label "Causal Consistency"@en .
ngm:causal-delivery a skos:Concept ;
rdfs:label "Causal Delivery"@en .
ngm:causal-forest a skos:Concept ;
rdfs:label "Causal Forest"@en .
ngm:causal-history a skos:Concept ;
rdfs:label "Causal History"@en .
ngm:causal-history-graph a skos:Concept ;
rdfs:label "Causal History Graph"@en .
ngm:causal-inference a owl:Class ;
rdfs:comment "Causal inference is the scientific and statistical discipline concerned with drawing conclusions about cause-and-effect relationships from data, distinguishing genuine causal mechanisms from mere statistical association. It employs frameworks such as potential outcomes (Rubin causal model), structural causal models (Pearl's do-calculus), and graphical models (directed acyclic graphs) to formalise interventions and reason about counterfactuals. Applications span medicine, economics, social science, and AI alignment, wherever understanding the effect of an action — not merely its correlation with outcomes — is required."@en ;
rdfs:label "Causal Inference"@en ;
rdfs:subClassOf ngm:bayesian-inference ;
rdfs:subClassOf ngm:inference ;
rdfs:subClassOf ngm:mathematical-reasoning ;
rdfs:subClassOf ngm:statistical-learning-theory ;
rdfs:subClassOf _:r4059 ;
rdfs:subClassOf _:r4060 ;
rdfs:subClassOf _:r4061 ;
rdfs:subClassOf _:r4062 ;
rdfs:subClassOf _:r4063 ;
vc:bridgesTo ngm:econometrics ;
vc:bridgesTo ngm:epidemiology ;
vc:contrastsWith ngm:associative-learning ;
vc:contrastsWith ngm:correlation-analysis ;
vc:contrastsWith ngm:pattern-recognition ;
vc:dependsOn ngm:bayesian-optimisation ;
vc:dependsOn ngm:directed-acyclic-graph ;
vc:dependsOn ngm:probability-theory ;
vc:dependsOn ngm:statistical-learning-theory ;
vc:enables ngm:algorithmic-fairness ;
vc:enables ngm:causal-language-modelling ;
vc:enables ngm:causal-representation-learning ;
vc:enables ngm:chain-of-thought-reasoning ;
vc:enables ngm:counterfactual-reasoning ;
vc:enables ngm:policy-evaluation ;
vc:enables ngm:reinforcement-learning ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:causal-forest ;
vc:hasPart ngm:counterfactual-reasoning ;
vc:hasPart ngm:difference-in-differences ;
vc:hasPart ngm:directed-acyclic-graph ;
vc:hasPart ngm:do-calculus ;
vc:hasPart ngm:instrumental-variables ;
vc:hasPart ngm:potential-outcomes-framework ;
vc:hasPart ngm:propensity-score-matching ;
vc:hasPart ngm:structural-causal-model ;
vc:implements ngm:automated-reasoning ;
vc:implements ngm:bayesian-inference ;
vc:implements ngm:inference-algorithm ;
vc:implements ngm:mathematical-reasoning ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:bayesian-decision-theory ;
vc:relatedTo ngm:bayesian-deep-learning ;
vc:relatedTo ngm:bayesian-knowledge-tracing ;
vc:relatedTo ngm:econometrics ;
vc:relatedTo ngm:epidemiology ;
vc:relatedTo ngm:inference ;
vc:relatedTo ngm:mathematical-reasoning ;
vc:relatedTo ngm:randomised-controlled-trial ;
vc:relatedTo ngm:reinforcement-learning ;
vc:requires ngm:confounding-variable ;
vc:requires ngm:graph-theory ;
vc:requires ngm:observational-data ;
vc:requires ngm:probability-theory ;
vc:requires ngm:randomised-controlled-trial ;
vc:slug "causal-inference" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:mathematical-reasoning ;
vc:standardizedBy ngm:probability-theory ;
vc:standardizedBy ngm:statistical-learning-theory ;
vc:supports ngm:ai-safety ;
vc:supports ngm:algorithmic-fairness ;
vc:supports ngm:causal-language-modelling ;
vc:supports ngm:deep-reinforcement-learning ;
vc:supports ngm:reinforcement-learning-from-human-feedback ;
vc:uses ngm:automated-reasoning ;
vc:uses ngm:bayesian-optimisation ;
vc:uses ngm:directed-acyclic-graph ;
vc:uses ngm:instrumental-variables ;
vc:uses ngm:mathematical-reasoning .
ngm:causal-language-modelling a owl:Class ;
rdfs:comment "Causal language modelling is a self-supervised pre-training objective in which a neural network learns to predict the next token in a sequence given all preceding tokens, modelling the joint probability of text as an autoregressive product of conditional distributions. The term 'causal' refers to the unidirectional (left-to-right) attention mask that enforces the temporal ordering of tokens, preventing the model from attending to future context. This objective is the foundation of decoder-only transformer architectures such as GPT, LLaMA, and Claude, which power the majority of state-of-the-art large language models."@en ;
rdfs:label "Causal Language Modelling"@en ;
rdfs:subClassOf ngm:language-modelling ;
rdfs:subClassOf ngm:large-language-model-training ;
rdfs:subClassOf ngm:pre-training ;
rdfs:subClassOf ngm:self-supervised-learning ;
rdfs:subClassOf _:r4064 ;
rdfs:subClassOf _:r4065 ;
rdfs:subClassOf _:r4066 ;
rdfs:subClassOf _:r4067 ;
rdfs:subClassOf _:r4068 ;
rdfs:subClassOf _:r4069 ;
rdfs:subClassOf _:r4070 ;
rdfs:subClassOf _:r4071 ;
rdfs:subClassOf _:r4072 ;
rdfs:subClassOf _:r4073 ;
vc:contrastsWith ngm:bert ;
vc:contrastsWith ngm:diffusion-language-model ;
vc:contrastsWith ngm:encoder-decoder-architecture ;
vc:contrastsWith ngm:masked-language-modelling ;
vc:contrastsWith ngm:state-space-model ;
vc:dependsOn ngm:attention-mechanism ;
vc:dependsOn ngm:embedding ;
vc:dependsOn ngm:feed-forward-network ;
vc:dependsOn ngm:layer-normalisation ;
vc:dependsOn ngm:self-attention ;
vc:enables ngm:chain-of-thought ;
vc:enables ngm:code-generation ;
vc:enables ngm:foundation-model ;
vc:enables ngm:gpt ;
vc:enables ngm:in-context-learning ;
vc:enables ngm:large-language-models ;
vc:enables ngm:meta-llama-model-family ;
vc:enables ngm:reasoning ;
vc:enables ngm:text-generation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:autoregressive-decoding ;
vc:hasPart ngm:causal-attention ;
vc:hasPart ngm:cross-entropy-loss ;
vc:hasPart ngm:perplexity-ai-search-platform ;
vc:hasPart ngm:teacher-forcing ;
vc:implements ngm:autoregressive-factorisation ;
vc:implements ngm:backpropagation ;
vc:implements ngm:gradient-descent ;
vc:implements ngm:multi-head-attention ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:fill-in-the-middle ;
vc:relatedTo ngm:in-context-learning ;
vc:relatedTo ngm:instruction-tuning ;
vc:relatedTo ngm:mixture-of-experts ;
vc:relatedTo ngm:retrieval-augmented-generation ;
vc:relatedTo ngm:speculative-decoding ;
vc:requires ngm:attention-mechanism ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:positional-encoding ;
vc:requires ngm:tokenization ;
vc:requires ngm:training-data ;
vc:requires ngm:transformer-architecture ;
vc:slug "causal-language-modelling" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:radford-et-al-2018 ;
vc:standardizedBy ngm:vaswani-et-al-2017 ;
vc:supports ngm:few-shot-learning ;
vc:supports ngm:fine-tuning ;
vc:supports ngm:instruction-tuning ;
vc:supports ngm:prompt-engineering ;
vc:supports ngm:reinforcement-learning-from-human-feedback ;
vc:supports ngm:zero-shot-learning ;
vc:uses ngm:attention-mechanism ;
vc:uses ngm:byte-pair-encoding ;
vc:uses ngm:causal-attention ;
vc:uses ngm:softmax-function .
ngm:causal-linkage a skos:Concept ;
rdfs:label "Causal Linkage"@en .
ngm:causal-loop-diagram a owl:Class ;
rdfs:comment "A causal loop diagram (CLD) is a system-dynamics visualisation tool that maps variables as nodes connected by directed causal links, each marked with a positive or negative polarity. Closed chains of links form reinforcing or balancing feedback loops that reveal the structural drivers of a system's behaviour over time. CLDs matter because they expose feedback structure and delays that linear cause-effect thinking misses, supporting qualitative analysis before quantitative simulation."@en ;
rdfs:label "Causal Loop Diagram"@en ;
rdfs:subClassOf ngm:system-architecture ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:feedback-loop ;
vc:slug "causal-loop-diagram" ;
vc:sourceDomain "data" .
ngm:causal-mask a skos:Concept ;
rdfs:label "Causal Mask"@en .
ngm:causal-model a skos:Concept ;
rdfs:label "Causal Model"@en .
ngm:causal-ordering a skos:Concept ;
rdfs:label "Causal Ordering"@en .
ngm:causal-reasoning a skos:Concept ;
rdfs:label "Causal Reasoning"@en .
ngm:causal-representation-learning a skos:Concept ;
rdfs:label "Causal Representation Learning"@en .
ngm:causal-tracing a skos:Concept ;
rdfs:label "Causal Tracing"@en .
ngm:causality-tracking a skos:Concept ;
rdfs:label "Causality Tracking"@en .
ngm:causation a skos:Concept ;
rdfs:label "Causation"@en .
ngm:causation-doctrine a skos:Concept ;
rdfs:label "Causation Doctrine"@en .
ngm:caustics a skos:Concept ;
rdfs:label "Caustics"@en .
ngm:cavendish-laboratory a skos:Concept ;
rdfs:label "Cavendish Laboratory"@en .
ngm:cayman-foundation-companies-act-2017 a skos:Concept ;
rdfs:label "Cayman Foundation Companies Act 2017"@en .
ngm:cayman-foundation-company a skos:Concept ;
rdfs:label "Cayman Foundation Company"@en .
ngm:cbdc-api a skos:Concept ;
rdfs:label "CBDC API"@en .
ngm:cbdc-cross-border-settlement a owl:Class ;
rdfs:comment "CBDC cross-border settlement refers to the use of central bank digital currencies to settle payments between parties in different jurisdictions. It aims to reduce cost and delay in international transfers."@en ;
rdfs:label "CBDC Cross-Border Settlement"@en ;
rdfs:subClassOf ngm:central-bank-digital-currency-cbdc ;
rdfs:subClassOf _:r3702 ;
vc:bridgesTo ngm:digital-pound ;
vc:enables ngm:payment-system ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:settlement ;
vc:slug "cbdc-cross-border-settlement" ;
vc:sourceDomain "blockchain" .
ngm:cbdc-frameworks a owl:Class ;
rdfs:comment "CBDC Frameworks are the integrated bodies of technical specifications, regulatory governance structures, design principles, and interoperability standards that central banks and international monetary institutions use to research, pilot, and deploy Central Bank Digital Currencies — sovereign digi..."@en ;
rdfs:label "CBDC Frameworks"@en ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
rdfs:subClassOf ngm:central-bank-infrastructure ;
rdfs:subClassOf ngm:digital-money ;
rdfs:subClassOf ngm:financial-regulation ;
rdfs:subClassOf ngm:monetary-policy-framework ;
rdfs:subClassOf ngm:payment-system-standard ;
rdfs:subClassOf _:r3703 ;
rdfs:subClassOf _:r3704 ;
rdfs:subClassOf _:r3705 ;
rdfs:subClassOf _:r3706 ;
rdfs:subClassOf _:r3707 ;
rdfs:subClassOf _:r3708 ;
rdfs:subClassOf _:r3709 ;
rdfs:subClassOf _:r3710 ;
rdfs:subClassOf _:r3711 ;
rdfs:subClassOf _:r3712 ;
rdfs:subClassOf _:r3713 ;
rdfs:subClassOf _:r3714 ;
rdfs:subClassOf _:r3715 ;
rdfs:subClassOf _:r3716 ;
rdfs:subClassOf _:r3717 ;
skos:broader ngm:bc-governance-and-regulation ;
vc:bridgesTo ngm:central-bank-infrastructure ;
vc:bridgesTo ngm:infra-security-and-identity ;
vc:contrastsWith ngm:correspondent-banking ;
vc:contrastsWith ngm:cryptocurrency ;
vc:contrastsWith ngm:physical-cash ;
vc:contrastsWith ngm:private-digital-money ;
vc:contrastsWith ngm:stablecoin ;
vc:contrastsWith ngm:swift-messaging ;
vc:dependsOn ngm:aml-cft-regulation ;
vc:dependsOn ngm:central-bank ;
vc:dependsOn ngm:commercial-bank ;
vc:dependsOn ngm:dlt ;
vc:dependsOn ngm:fast-payment-system ;
vc:dependsOn ngm:interoperability-standard ;
vc:dependsOn ngm:payment-service-provider ;
vc:dependsOn ngm:smart-contract ;
vc:dependsOn ngm:zero-knowledge-proof ;
vc:enables ngm:atomic-delivery-versus-payment ;
vc:enables ngm:cross-border-payments ;
vc:enables ngm:financial-inclusion ;
vc:enables ngm:machine-to-machine-payments ;
vc:enables ngm:monetary-policy-transmission ;
vc:enables ngm:privacy-preserving-compliance ;
vc:enables ngm:programmable-money ;
vc:enables ngm:retail-cbdc ;
vc:enables ngm:targeted-fiscal-transfers ;
vc:enables ngm:wholesale-cbdc ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:compliance-layer ;
vc:hasPart ngm:core-ledger ;
vc:hasPart ngm:cross-border-protocol ;
vc:hasPart ngm:holding-limit-mechanism ;
vc:hasPart ngm:interoperability ;
vc:hasPart ngm:kyc-tier-system ;
vc:hasPart ngm:offline-payment-capability ;
vc:hasPart ngm:privacy-framework ;
vc:hasPart ngm:programmability-layer ;
vc:hasPart ngm:two-tier-cbdc-architecture ;
vc:implements ngm:bis-cbdc-principles ;
vc:implements ngm:cpmi-cross-border-payment-standards ;
vc:implements ngm:fsb-financial-stability-recommendations ;
vc:implements ngm:g7-public-policy-principles-for-retail-cbdcs ;
vc:implements ngm:imf-5p-methodology ;
vc:implements ngm:privacy-by-design ;
vc:implements ngm:two-tier-distribution-model ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:bis ;
vc:relatedTo ngm:cbdcs ;
vc:relatedTo ngm:central-bank ;
vc:relatedTo ngm:cross-border-payments ;
vc:relatedTo ngm:digital-euro ;
vc:relatedTo ngm:e-cny ;
vc:relatedTo ngm:financial-regulation ;
vc:relatedTo ngm:imf ;
vc:relatedTo ngm:interoperability ;
vc:relatedTo ngm:programmable-money ;
vc:relatedTo ngm:project-agora ;
vc:relatedTo ngm:project-dunbar ;
vc:relatedTo ngm:project-m-bridge ;
vc:relatedTo ngm:project-nexus ;
vc:relatedTo ngm:zero-knowledge-proof ;
vc:requires ngm:aml ;
vc:requires ngm:api-standard ;
vc:requires ngm:api-standards ;
vc:requires ngm:central-bank ;
vc:requires ngm:cryptographic-infrastructure ;
vc:requires ngm:data-protection-law ;
vc:requires ngm:dlt ;
vc:requires ngm:kyc-compliance ;
vc:requires ngm:legal-tender-designation ;
vc:requires ngm:operational-resilience ;
vc:requires ngm:regulatory-authorisation ;
vc:slug "cbdc-frameworks" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:bis-cbdc-design-principles-2020 ;
vc:standardizedBy ngm:cpmi-fast-payment-system-standards ;
vc:standardizedBy ngm:ecb-digital-euro-regulation-proposal ;
vc:standardizedBy ngm:fatf-recommendations ;
vc:standardizedBy ngm:fsb-cbdc-financial-stability-recommendations-2023 ;
vc:standardizedBy ngm:g7-public-policy-principles-for-retail-cbdcs-2021 ;
vc:standardizedBy ngm:gdpr ;
vc:standardizedBy ngm:imf-cbdc-virtual-handbook ;
vc:supports ngm:cbdcs ;
vc:supports ngm:cross-border-payments ;
vc:supports ngm:digital-euro ;
vc:supports ngm:financial-inclusion ;
vc:supports ngm:financial-stability ;
vc:supports ngm:monetary-sovereignty ;
vc:supports ngm:payment-system-efficiency ;
vc:supports ngm:privacy ;
vc:supports ngm:programmable-money ;
vc:uses ngm:api-gateway ;
vc:uses ngm:atomic-swap ;
vc:uses ngm:blind-signatures ;
vc:uses ngm:distributed-ledger-technology ;
vc:uses ngm:multi-party-computation ;
vc:uses ngm:near-field-communication ;
vc:uses ngm:neural-network-text-tokenisation ;
vc:uses ngm:smart-contracts ;
vc:uses ngm:zero-knowledge-proof .
ngm:cbdc-infrastructure a owl:Class ;
rdfs:comment "CBDC infrastructure refers to the technical systems, protocols, and institutional arrangements that underpin the issuance, distribution, settlement, and management of central bank digital currencies. It encompasses the ledger technology (centralised, distributed, or hybrid), API layers enabling interoperability with commercial banks and payment service providers, offline payment capability, and the privacy-preserving and security mechanisms required for sovereign digital money at scale. CBDC infrastructure must satisfy central bank requirements for finality, programmability, resilience, and monetary policy control that differ fundamentally from commercial digital payment systems."@en ;
rdfs:label "CBDC Infrastructure"@en ;
rdfs:subClassOf ngm:payment-infrastructure ;
vc:enables ngm:central-bank-digital-currency-cbdc ;
vc:enables ngm:cross-border-payments ;
vc:enables ngm:digital-payments ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:cbdc-frameworks ;
vc:relatedTo ngm:monetary-policy-implementation ;
vc:slug "cbdc-infrastructure" ;
vc:sourceDomain "finance" ;
vc:uses ngm:atomic-settlement ;
vc:uses ngm:cryptographic-infrastructure .
ngm:cbdc-ledger a skos:Concept ;
rdfs:label "CBDC Ledger"@en .
ngm:cbdc-wallet a skos:Concept ;
rdfs:label "CBDC Wallet"@en .
ngm:cbdcs a owl:Class ;
rdfs:comment "Central Bank Digital Currencies (CBDCs) are sovereign digital money issued directly by a nation's central bank, representing a liability of the issuing central bank rather than a commercial bank or private institution, denominated in the official unit of account and designed to function as legal ..."@en ;
rdfs:label "CBDCs"@en ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
rdfs:subClassOf ngm:bc-token-and-asset ;
rdfs:subClassOf ngm:central-bank-money ;
rdfs:subClassOf ngm:digital-currency ;
rdfs:subClassOf ngm:legal-tender ;
rdfs:subClassOf ngm:payment-instrument ;
rdfs:subClassOf ngm:sovereign-money ;
rdfs:subClassOf _:r3718 ;
rdfs:subClassOf _:r3719 ;
rdfs:subClassOf _:r3720 ;
rdfs:subClassOf _:r3721 ;
rdfs:subClassOf _:r3722 ;
rdfs:subClassOf _:r3723 ;
rdfs:subClassOf _:r3724 ;
rdfs:subClassOf _:r3725 ;
rdfs:subClassOf _:r3726 ;
rdfs:subClassOf _:r3727 ;
skos:broader ngm:bc-governance-and-regulation ;
skos:broader ngm:bc-token-and-asset ;
vc:contrastsWith ngm:commercial-bank-deposits ;
vc:contrastsWith ngm:cryptocurrency ;
vc:contrastsWith ngm:e-money ;
vc:contrastsWith ngm:fednow ;
vc:contrastsWith ngm:physical-cash ;
vc:contrastsWith ngm:stable-coins ;
vc:dependsOn ngm:central-bank ;
vc:dependsOn ngm:cryptographic-standards ;
vc:dependsOn ngm:digital-infrastructure ;
vc:dependsOn ngm:financial-regulation ;
vc:dependsOn ngm:legal-framework ;
vc:dependsOn ngm:monetary-policy ;
vc:enables ngm:cross-border-payments ;
vc:enables ngm:financial-inclusion ;
vc:enables ngm:micropayments ;
vc:enables ngm:monetary-policy-transmission ;
vc:enables ngm:offline-payments ;
vc:enables ngm:programmable-money ;
vc:enables ngm:real-time-settlement ;
vc:enables ngm:smart-contract-execution ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:cbdc-api ;
vc:hasPart ngm:cbdc-ledger ;
vc:hasPart ngm:cbdc-wallet ;
vc:hasPart ngm:distribution-tier ;
vc:hasPart ngm:offline-cbdc ;
vc:hasPart ngm:programmable-money ;
vc:hasPart ngm:retail-cbdc ;
vc:hasPart ngm:wholesale-cbdc ;
vc:implements ngm:centralised-ledger-design ;
vc:implements ngm:distributed-ledger-technology-dlt ;
vc:implements ngm:interoperability-protocol ;
vc:implements ngm:privacy-by-design ;
vc:implements ngm:tiered-anonymity ;
vc:implements ngm:two-tier-distribution-model ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:cross-border-payments ;
vc:relatedTo ngm:digital-euro ;
vc:relatedTo ngm:digital-pound ;
vc:relatedTo ngm:digital-yuan ;
vc:relatedTo ngm:financial-inclusion ;
vc:relatedTo ngm:financial-regulation ;
vc:relatedTo ngm:m-bridge ;
vc:relatedTo ngm:mbridge ;
vc:relatedTo ngm:monetary-policy ;
vc:relatedTo ngm:privacy ;
vc:relatedTo ngm:programmable-money ;
vc:relatedTo ngm:project-nexus ;
vc:requires ngm:aml-kyc-compliance ;
vc:requires ngm:central-bank ;
vc:requires ngm:cryptographic-security ;
vc:requires ngm:digital-identity ;
vc:requires ngm:financial-regulation ;
vc:requires ngm:monetary-sovereignty ;
vc:requires ngm:payment-infrastructure ;
vc:slug "cbdcs" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:basel-committee ;
vc:standardizedBy ngm:bis-cpmi-standards ;
vc:standardizedBy ngm:ecb-digital-euro-regulation ;
vc:standardizedBy ngm:fatf-guidance-on-virtual-assets ;
vc:standardizedBy ngm:fsb-cross-border-payments-roadmap ;
vc:standardizedBy ngm:imf-cbdc-framework ;
vc:supports ngm:aml ;
vc:supports ngm:currency-internationalisation ;
vc:supports ngm:financial-stability ;
vc:supports ngm:monetary-sovereignty ;
vc:supports ngm:payment-efficiency ;
vc:supports ngm:sanctions-enforcement ;
vc:uses ngm:api-standard ;
vc:uses ngm:api-standards ;
vc:uses ngm:dlt ;
vc:uses ngm:neural-network-text-tokenisation ;
vc:uses ngm:permissioned-blockchain ;
vc:uses ngm:privacy-enhancing-technologies ;
vc:uses ngm:zero-knowledge-proof .
ngm:cbeci a owl:Class ;
rdfs:comment "The Cambridge Bitcoin Electricity Consumption Index (CBECI) is a real-time model produced by the Cambridge Centre for Alternative Finance that estimates the annualised electricity consumption and carbon footprint of the Bitcoin proof-of-work mining network. It aggregates hardware efficiency data from known ASIC models, network hash rate, and electricity price assumptions to produce lower-, central-, and upper-bound estimates."@en ;
rdfs:label "CBECI"@en ;
rdfs:subClassOf ngm:benchmark-evaluation ;
rdfs:subClassOf ngm:electricity-consumption ;
vc:bridgesTo ngm:governance ;
vc:bridgesTo ngm:infrastructure ;
vc:contrastsWith ngm:proof-of-stake ;
vc:dependsOn ngm:blockchain ;
vc:dependsOn ngm:proof-of-work ;
vc:enables ngm:carbon-accounting ;
vc:enables ngm:renewable-energy-certificates ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol-environmental-issues ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol-mining ;
vc:relatedTo ngm:cambridge-centre-for-alternative-finance ;
vc:relatedTo ngm:carbon-footprint ;
vc:relatedTo ngm:proof-of-work-energy-consumption ;
vc:relatedTo ngm:sustainable-bitcoin-protocol ;
vc:slug "cbeci" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:bc-0482-eu-mica-regulation ;
vc:supports ngm:cryptocurrency-regulation ;
vc:uses ngm:asic-hardware ;
vc:uses ngm:cbeci-methodology ;
vc:uses ngm:difficulty ;
vc:uses ngm:electricity-consumption ;
vc:uses ngm:hash-rate ;
vc:uses ngm:mining-pool .
ngm:cbeci-methodology a owl:Class ;
rdfs:comment "The CBECI methodology is the estimation framework underlying the Cambridge Bitcoin Electricity Consumption Index, used to model the Bitcoin network's real-time electricity demand. It derives a plausible consumption range by combining network hashrate, a profitability-weighted mix of mining hardware efficiencies, data-centre overheads, and assumptions about miner economics. The methodology matters because it provides the most widely cited, transparent academic estimate of Bitcoin's energy use and the basis for its carbon analysis."@en ;
rdfs:label "CBECI Methodology"@en ;
rdfs:subClassOf ngm:blockchain-environmental-impact-assessment ;
rdfs:subClassOf ngm:evaluation-metric ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol-mining ;
vc:relatedTo ngm:cbeci ;
vc:slug "cbeci-methodology" ;
vc:sourceDomain "blockchain" .
ngm:cbor a owl:Class ;
rdfs:comment "Concise Binary Object Representation (CBOR) is a binary data serialisation format specified in RFC 7049 (superseded by RFC 8949) designed to enable extremely compact encoding of structured data with a data model that is a superset of JSON. CBOR encodes values using a type-length-value scheme, eliminating the overhead of textual delimiters and key quotation, which makes it particularly well-suited for constrained environments such as IoT devices, embedded systems, and low-bandwidth protocols where minimising message size and parsing complexity is critical."@en ;
rdfs:label "CBOR"@en ;
rdfs:subClassOf ngm:data-serialization ;
rdfs:subClassOf _:r3728 ;
vc:bridgesTo ngm:hardware-security-module ;
vc:bridgesTo ngm:linked-data ;
vc:enables ngm:credential-format-standard ;
vc:enables ngm:embedded-systems ;
vc:enables ngm:remote-attestation ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:cose ;
vc:implements ngm:deterministic-encoding ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:data-format-standard ;
vc:relatedTo ngm:json-data-interchange-format ;
vc:relatedTo ngm:messagepack ;
vc:relatedTo ngm:protocol-buffer ;
vc:requires ngm:internet-of-things ;
vc:slug "cbor" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:internet-engineering-task-force ;
vc:standardizedBy ngm:iso-iec-18013-5-m-dl ;
vc:supports ngm:decentralised-identity ;
vc:supports ngm:verifiable-credentials ;
vc:uses ngm:binary-encoding .
ngm:cbrn-risk a skos:Concept ;
rdfs:label "Cbrn Risk"@en .
ngm:cbrn-risk-assessment a skos:Concept ;
rdfs:label "Cbrn Risk Assessment"@en .
ngm:cbrn-uplift-risk a skos:Concept ;
rdfs:label "Cbrn Uplift Risk"@en .
ngm:ccaligned-dataset a skos:Concept ;
rdfs:label "Ccaligned Dataset"@en .
ngm:ccpa a owl:Class ;
rdfs:comment "The California Consumer Privacy Act (CCPA), a California state statute enacted in 2018 that grants California residents rights over the personal information that businesses collect about them, including the right to know, the right to delete, the right to opt out of sale, and the right to non-discrimination."@en ;
rdfs:label "CCPA"@en ;
rdfs:subClassOf ngm:data-protection-law ;
rdfs:subClassOf _:r3729 ;
rdfs:subClassOf _:r3730 ;
rdfs:subClassOf _:r3731 ;
rdfs:subClassOf _:r3732 ;
rdfs:subClassOf _:r3733 ;
rdfs:subClassOf _:r3734 ;
vc:bridgesTo ngm:ai-regulation ;
vc:bridgesTo ngm:data-governance ;
vc:bridgesTo ngm:data-privacy ;
vc:bridgesTo ngm:digital-identity ;
vc:bridgesTo ngm:gdpr ;
vc:contrastsWith ngm:gdpr ;
vc:contrastsWith ngm:hipaa ;
vc:dependsOn ngm:data-privacy ;
vc:dependsOn ngm:regulatory-compliance ;
vc:enables ngm:consumer-protection ;
vc:enables ngm:data-subject-rights ;
vc:enables ngm:privacy ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:privacy-disclosure ;
vc:hasPart ngm:right-to-be-forgotten ;
vc:implements ngm:data-protection-law ;
vc:implements ngm:privacy-regulation ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:data-breach-notification ;
vc:relatedTo ngm:privacy-policy ;
vc:requires ngm:consent-management ;
vc:requires ngm:data-inventory ;
vc:requires ngm:data-protection ;
vc:requires ngm:privacy-impact-assessment ;
vc:slug "ccpa" ;
vc:sourceDomain "governance" ;
vc:supports ngm:data-minimisation ;
vc:supports ngm:privacy-by-design ;
vc:uses ngm:data-brokers .
ngm:ccri-energy-benchmarks a skos:Concept ;
rdfs:label "Ccri Energy Benchmarks"@en .
ngm:ccri-methodology a skos:Concept ;
rdfs:label "Ccri Methodology"@en .
ngm:cdc-biowatch-programme a skos:Concept ;
rdfs:label "Cdc Biowatch Programme"@en .
ngm:cdc-category-a-b-c-agent-classification a skos:Concept ;
rdfs:label "Cdc Category A B C Agent Classification"@en .
ngm:cdc-select-agent-program a skos:Concept ;
rdfs:label "Cdc Select Agent Program"@en .
ngm:cdc-select-agent-regulations a skos:Concept ;
rdfs:label "Cdc Select Agent Regulations"@en .
ngm:cdla a owl:Class ;
rdfs:comment "The Community Data License Agreement (CDLA) is a family of open data licences published by the Linux Foundation to govern the sharing and reuse of curated datasets. Its principal variants are CDLA-Permissive, which allows broad reuse with attribution, and CDLA-Sharing, which adds a copyleft-style obligation to share derived datasets under the same terms. CDLA matters for AI because it provides clear, machine-readable licensing for training-data corpora, reducing legal uncertainty over data provenance and downstream use."@en ;
rdfs:label "CDLA"@en ;
rdfs:subClassOf ngm:infra-legal-and-regulatory ;
skos:broader ngm:infra-legal-and-regulatory ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:training-data ;
vc:slug "cdla" ;
vc:sourceDomain "infrastructure" .
ngm:cdn a owl:Class ;
rdfs:comment "A Content Delivery Network (CDN) is a geographically distributed network of proxy servers and data centres that caches and serves web content from locations physically close to end users, reducing latency, relieving origin server load, and improving resilience against traffic spikes and denial-of-service attacks. CDNs operate through anycast routing, edge caching policies, and real-time traffic steering algorithms to deliver optimal user experience across diverse network conditions."@en ;
rdfs:label "CDN"@en ;
rdfs:subClassOf _:r3735 ;
rdfs:subClassOf _:r3736 ;
rdfs:subClassOf _:r3737 ;
vc:bridgesTo ngm:distributed-systems ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:contrastsWith ngm:peer-to-peer-network ;
vc:dependsOn ngm:cloud-infrastructure ;
vc:enables ngm:bandwidth-optimization ;
vc:enables ngm:ddos-mitigation ;
vc:enables ngm:latency ;
vc:enables ngm:serverless-architecture ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:point-of-presence ;
vc:hasPart ngm:web-application-firewall ;
vc:isPartOf ngm:internet-infrastructure ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:cloud-infrastructure ;
vc:relatedTo ngm:content-delivery-network-cdn ;
vc:relatedTo ngm:http-caching ;
vc:relatedTo ngm:internet-infrastructure ;
vc:requires ngm:load-balancing ;
vc:requires ngm:origin-server ;
vc:slug "cdn" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:adaptive-bitrate-streaming ;
vc:supports ngm:api-gateway ;
vc:supports ngm:video-streaming ;
vc:uses ngm:anycast-routing ;
vc:uses ngm:dns ;
vc:uses ngm:edge-computing ;
vc:uses ngm:network-protocol ;
vc:uses ngm:network-security ;
vc:uses ngm:tls .
ngm:cdn-infrastructure a skos:Concept ;
rdfs:label "Cdn Infrastructure"@en .
ngm:cdn-layer a skos:Concept ;
rdfs:label "Cdn Layer"@en .
ngm:cdn-storage a skos:Concept ;
rdfs:label "Cdn Storage"@en .
ngm:cdp a skos:Concept ;
rdfs:label "Cdp"@en .
ngm:cdp-questionnaires a skos:Concept ;
rdfs:label "Cdp Questionnaires"@en .
ngm:cdp-reporting a skos:Concept ;
rdfs:label "Cdp Reporting"@en .
ngm:cdx-index a skos:Concept ;
rdfs:label "Cdx Index"@en .
ngm:cdx-protocol a skos:Concept ;
rdfs:label "Cdx Protocol"@en .
ngm:ce-marking a owl:Class ;
rdfs:comment "CE marking is a mandatory conformity mark indicating that a product placed on the European Economic Area market meets the applicable EU health, safety, and environmental protection requirements. For machinery and robots it signals compliance with directives such as the Machinery Regulation, the EMC Directive, and relevant harmonised standards, often supported by a declaration of conformity and technical file. It matters because it is a legal precondition for market access and embeds robot safety standards into commercial deployment."@en ;
rdfs:label "CE Marking"@en ;
rdfs:subClassOf ngm:robo-safety-and-standards ;
rdfs:subClassOf _:r3738 ;
rdfs:subClassOf _:r3739 ;
rdfs:subClassOf _:r3740 ;
rdfs:subClassOf _:r3741 ;
skos:broader ngm:robo-safety-and-standards ;
vc:bridgesTo ngm:governance ;
vc:bridgesTo ngm:supply-chain ;
vc:contrastsWith ngm:safety-certification ;
vc:dependsOn ngm:emc-standard ;
vc:dependsOn ngm:regulation ;
vc:enables ngm:market-access ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:declaration-of-conformity ;
vc:hasPart ngm:risk-assessment ;
vc:implements ngm:ai-product-and-risk-framework ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:product-liability ;
vc:relatedTo ngm:robot-standard ;
vc:requires ngm:conformity-assessment ;
vc:requires ngm:harmonised-standard ;
vc:requires ngm:notified-body ;
vc:slug "ce-marking" ;
vc:sourceDomain "robotics" ;
vc:standardizedBy ngm:iec-61508 ;
vc:standardizedBy ngm:iso-12100 ;
vc:standardizedBy ngm:robot-standard .
ngm:cefi a skos:Concept ;
rdfs:label "Cefi"@en .
ngm:celeb-df-benchmark a skos:Concept ;
rdfs:label "Celeb Df Benchmark"@en .
ngm:celeste a skos:Concept ;
rdfs:label "Celeste"@en .
ngm:celestia a owl:Class ;
rdfs:comment "Celestia is a modular blockchain network that decouples data availability from execution and consensus, functioning as a dedicated data availability layer that rollups and sovereign chains can use to publish and order transaction data without requiring a monolithic execution environment. It employs data availability sampling (DAS) via erasure coding so that light nodes can probabilistically verify that block data has been published without downloading it in full, enabling Celestia nodes to scale with the number of light clients rather than validators. Celestia introduced the concept of sovereign rollups, in which chains publish data to Celestia for ordering and availability whilst handling their own execution and settlement independently."@en ;
rdfs:label "Celestia"@en ;
rdfs:subClassOf ngm:data-availability ;
rdfs:subClassOf _:r4074 ;
rdfs:subClassOf _:r4075 ;
vc:bridgesTo ngm:distributed-systems ;
vc:bridgesTo ngm:peer-to-peer-network ;
vc:contrastsWith ngm:ethereum ;
vc:contrastsWith ngm:monolithic-blockchain ;
vc:enables ngm:blockchain-scalability ;
vc:enables ngm:layer-2-scaling ;
vc:enables ngm:modular-blockchain ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:blob-transaction ;
vc:implements ngm:data-availability-sampling ;
vc:isPartOf ngm:cosmos ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:avail ;
vc:relatedTo ngm:cosmos ;
vc:relatedTo ngm:danksharding ;
vc:relatedTo ngm:proto-danksharding ;
vc:requires ngm:byzantine-fault-tolerance ;
vc:requires ngm:light-node ;
vc:slug "celestia" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:consensus-mechanism ;
vc:uses ngm:erasure-coding ;
vc:uses ngm:inter-blockchain-communication ;
vc:uses ngm:reed-solomon-erasure-coding ;
vc:uses ngm:tendermint-consensus .
ngm:celestial-mechanics a owl:Class ;
rdfs:label "Celestial Mechanics"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:orbital-dynamics ;
vc:slug "celestial-mechanics" ;
vc:sourceDomain "space-science-and-systems" .
ngm:celestial-reference-frame a owl:Class ;
rdfs:label "Celestial Reference Frame"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:space-reference-systems ;
vc:slug "celestial-reference-frame" ;
vc:sourceDomain "space-science-and-systems" .
ngm:cell-state a skos:Concept ;
rdfs:label "Cell State"@en .
ngm:cell-type-identification a skos:Concept ;
rdfs:label "Cell Type Identification"@en .
ngm:cellular-automata a owl:Class ;
rdfs:comment "A cellular automaton is a discrete computational model consisting of a regular grid of cells, each holding one of a finite set of states, that evolve over discrete time steps according to a fixed local update rule applied uniformly across the grid. The next state of a cell depends only on its current state and the states of a defined neighbourhood, yet iterated application of simple local rules can produce complex, emergent global behaviour. Cellular automata are used to study self-organisation and computational universality, and serve as lightweight simulation substrates for physical, biological and social systems."@en ;
rdfs:label "Cellular Automata"@en ;
rdfs:subClassOf ngm:computational-model ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:computational-model ;
vc:qualityScore "0.55"^^xsd:float ;
vc:relatedTo ngm:agent-based-modelling ;
vc:relatedTo ngm:complex-adaptive-systems ;
vc:slug "cellular-automata" ;
vc:sourceDomain "artificial-intelligence" .
ngm:cellular-m2m a skos:Concept ;
rdfs:label "Cellular M2m"@en .
ngm:cellular-network a owl:Class ;
rdfs:comment "A cellular network is a wireless communication system in which a geographic area is divided into cells, each served by a base station, enabling mobile devices to connect and maintain service while moving. Frequency reuse across cells and handover between base stations allow large numbers of users to share limited radio spectrum. Successive generations such as 4G LTE and 5G have progressively increased capacity, throughput and latency performance."@en ;
rdfs:label "Cellular Network"@en ;
rdfs:subClassOf ngm:telecommunications-infrastructure ;
rdfs:subClassOf _:r4076 ;
rdfs:subClassOf _:r4077 ;
rdfs:subClassOf _:r4078 ;
rdfs:subClassOf _:r4079 ;
vc:contrastsWith ngm:mesh-networking ;
vc:contrastsWith ngm:wireless-connectivity ;
vc:enables ngm:internet-of-things ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:network-protocol ;
vc:hasPart ngm:radio-transceiver ;
vc:isPartOf ngm:telecommunications ;
vc:isPartOf ngm:telecommunications-infrastructure ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:networking-infrastructure ;
vc:requires ngm:radio-access-network ;
vc:requires ngm:wireless-communication ;
vc:slug "cellular-network" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:low-latency-networking ;
vc:supports ngm:mobile-device ;
vc:uses ngm:network-transport ;
vc:uses ngm:wireless-radio .
ngm:celo a skos:Concept ;
rdfs:label "Celo"@en .
ngm:cen-cenelec a owl:Class ;
rdfs:comment "CEN-CENELEC refers to the joint operation of the European Committee for Standardization (CEN) and the European Committee for Electrotechnical Standardization (CENELEC), the recognised European Standardisation Organisations responsible for developing voluntary European Standards (EN). Together with ETSI they produce harmonised standards that support the EU single market and underpin presumption of conformity with European legislation. CEN covers general and mechanical sectors while CENELEC covers electrotechnical fields."@en ;
rdfs:label "Cen Cenelec"@en ;
rdfs:subClassOf ngm:standards-body ;
rdfs:subClassOf _:r4080 ;
vc:bridgesTo ngm:iec ;
vc:bridgesTo ngm:iso ;
vc:contrastsWith ngm:etsi ;
vc:enables ngm:conformity-assessment ;
vc:enables ngm:interoperability ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:standardisation ;
vc:isPartOf ngm:standards-body ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:etsi ;
vc:relatedTo ngm:iec ;
vc:relatedTo ngm:interoperability ;
vc:relatedTo ngm:iso ;
vc:requires ngm:technical-standard ;
vc:slug "cen-cenelec" ;
vc:sourceDomain "standards" ;
vc:standardizedBy ngm:standards-body ;
vc:supports ngm:conformity-assessment ;
vc:supports ngm:technical-standard ;
vc:uses ngm:standardisation .
ngm:censorship a skos:Concept ;
rdfs:label "Censorship"@en .
ngm:censorship-resistance a owl:Class ;
rdfs:comment "Property of blockchain networks guaranteeing that any valid transaction submitted by any participant will eventually be included in the canonical chain, preventing miners, validators, or any coordinated group from systematically excluding transactions. Achieved through decentralised consensus, permissionless participation, and economic incentive alignment."@en ;
rdfs:label "Censorship Resistance"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf ngm:blockchain-entity ;
rdfs:subClassOf ngm:networkcomponent ;
rdfs:subClassOf _:r4081 ;
rdfs:subClassOf _:r4082 ;
rdfs:subClassOf _:r4083 ;
rdfs:subClassOf _:r4084 ;
rdfs:subClassOf _:r4085 ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:bridgesTo ngm:freedom-of-speech ;
vc:bridgesTo ngm:information-security ;
vc:contrastsWith ngm:ofac-compliance ;
vc:contrastsWith ngm:permissioned-blockchain ;
vc:contrastsWith ngm:transaction ;
vc:dependsOn ngm:byzantine-fault-tolerance ;
vc:dependsOn ngm:cryptographic-hash-function ;
vc:dependsOn ngm:economic-model ;
vc:dependsOn ngm:public-key-cryptography ;
vc:enables ngm:decentralized-governance ;
vc:enables ngm:financial-inclusion ;
vc:enables ngm:immutability ;
vc:enables ngm:trustless-transaction ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:fork-choice-rule ;
vc:implements ngm:mempool ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:51-attack ;
vc:relatedTo ngm:blockchain-governance ;
vc:relatedTo ngm:double-spending ;
vc:relatedTo ngm:miner-extractable-value ;
vc:relatedTo ngm:peer-discovery ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:decentralisation ;
vc:requires ngm:peer-to-peer-network ;
vc:requires ngm:permissionless-participation ;
vc:requires ngm:sybil-resistance ;
vc:slug "censorship-resistance" ;
vc:sourceDomain "blockchain" .
ngm:censorship-resistant-communication a skos:Concept ;
rdfs:label "Censorship Resistant Communication"@en .
ngm:censorship-resistant-messaging a skos:Concept ;
rdfs:label "Censorship Resistant Messaging"@en .
ngm:censorship-resistant-payments a owl:Class ;
rdfs:comment "Censorship resistant payments are financial transactions that cannot be selectively blocked, reversed, or denied by any single authority — including governments, financial institutions, or network intermediaries — by virtue of operating on decentralised, permissionless infrastructure. Resistance to censorship is achieved through architectural properties such as open validator sets, pseudonymous addressing, and consensus rules that treat all valid transactions equally regardless of the identities or purposes of parties. Bitcoin, Monero, and decentralised finance protocols on public blockchains are archetypal examples, contrasting with traditional payment rails where correspondent banks, card networks, and processors can refuse service."@en ;
rdfs:label "Censorship Resistant Payments"@en ;
rdfs:subClassOf ngm:censorship-resistance ;
vc:enables ngm:financial-sovereignty ;
vc:enables ngm:micropayments ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:decentralized-finance-de-fi ;
vc:relatedTo ngm:monetary-sovereignty ;
vc:slug "censorship-resistant-payments" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:bitcoin-proof-of-work-protocol-network ;
vc:uses ngm:lightning-network ;
vc:uses ngm:payment-channel .
ngm:census-data a skos:Concept ;
rdfs:label "Census Data"@en .
ngm:center-for-ai-safety a skos:Concept ;
rdfs:label "Center For AI Safety"@en .
ngm:center-for-biologics-evaluation-and-research a skos:Concept ;
rdfs:label "Center For Biologics Evaluation And Research"@en .
ngm:center-for-devices-and-radiological-health a skos:Concept ;
rdfs:label "Center For Devices And Radiological Health"@en .
ngm:center-for-drug-evaluation-and-research a skos:Concept ;
rdfs:label "Center For Drug Evaluation And Research"@en .
ngm:center-for-food-safety-and-applied-nutrition a skos:Concept ;
rdfs:label "Center For Food Safety And Applied Nutrition"@en .
ngm:center-pose a skos:Concept ;
rdfs:label "Center Pose"@en .
ngm:centernet a skos:Concept ;
rdfs:label "Centernet"@en .
ngm:centerpose a skos:Concept ;
rdfs:label "Centerpose"@en .
ngm:central-bank a owl:Class ;
rdfs:comment "A central bank is a public financial institution vested with exclusive authority over a nation's or currency union's monetary base, responsible for setting benchmark interest rates, controlling the money supply, and acting as lender of last resort to the commercial banking sector. Central banks implement monetary policy to pursue macroeconomic objectives including price stability, sustainable economic growth, and full employment, typically operating with a degree of independence from short-term political influence. They hold official foreign exchange reserves, supervise the broader banking system, operate or oversee critical payment infrastructure, and increasingly research or issue Central Bank Digital Currencies as sovereign digital money. Major examples include the Federal Reserve, the European Central Bank, the Bank of England, the Bank of Japan, and the People's Bank of China."@en ;
rdfs:label "Central Bank"@en ;
rdfs:subClassOf ngm:monetary-system ;
rdfs:subClassOf _:r4101 ;
rdfs:subClassOf _:r4102 ;
rdfs:subClassOf _:r4103 ;
vc:bridgesTo ngm:distributed-ledger-technology ;
vc:bridgesTo ngm:neural-network-text-tokenisation ;
vc:bridgesTo ngm:tokenization ;
vc:contrastsWith ngm:commercial-bank ;
vc:contrastsWith ngm:de-fi ;
vc:dependsOn ngm:government-bond-market ;
vc:dependsOn ngm:interbank-market ;
vc:enables ngm:central-bank-digital-currency-cbdc ;
vc:enables ngm:inflation-control ;
vc:enables ngm:lender-of-last-resort ;
vc:enables ngm:payment-system ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:discount-window ;
vc:hasPart ngm:monetary-policy-implementation ;
vc:hasPart ngm:open-market-operations ;
vc:hasPart ngm:reserve-requirements ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:bank-for-international-settlements ;
vc:relatedTo ngm:digital-currency ;
vc:relatedTo ngm:financial-regulation ;
vc:relatedTo ngm:inflation-targeting ;
vc:relatedTo ngm:quantitative-easing ;
vc:relatedTo ngm:stablecoin ;
vc:requires ngm:central-bank-independence ;
vc:requires ngm:foreign-exchange-reserves ;
vc:slug "central-bank" ;
vc:sourceDomain "finance" ;
vc:supports ngm:basel-committee-on-banking-supervision ;
vc:supports ngm:financial-stability ;
vc:supports ngm:monetary-sovereignty .
ngm:central-bank-cooperation a skos:Concept ;
rdfs:label "Central Bank Cooperation"@en .
ngm:central-bank-digital-currency a owl:Class ;
rdfs:comment "A digital form of sovereign fiat money issued directly by a nation's central bank, representing a liability of the monetary authority that can serve as legal tender for retail payments or wholesale settlement, distinct from commercial bank deposits and decentralized cryptocurrencies."@en ;
rdfs:label "Central Bank Digital Currency"@en ;
rdfs:subClassOf ngm:digital-currency ;
rdfs:subClassOf _:r4096 ;
rdfs:subClassOf _:r4097 ;
rdfs:subClassOf _:r4098 ;
rdfs:subClassOf _:r4099 ;
rdfs:subClassOf _:r4100 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:de-fi ;
vc:bridgesTo ngm:digital-wallet ;
vc:contrastsWith ngm:commercial-bank-deposit ;
vc:contrastsWith ngm:cryptocurrency ;
vc:contrastsWith ngm:stablecoin ;
vc:enables ngm:cross-border-payments ;
vc:enables ngm:digital-payments ;
vc:enables ngm:financial-inclusion ;
vc:enables ngm:monetary-policy-transmission ;
vc:enables ngm:programmable-money ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:legal-tender ;
vc:implements ngm:monetary-sovereignty ;
vc:qualityScore "0.68"^^xsd:float ;
vc:relatedTo ngm:financial-regulation ;
vc:relatedTo ngm:monetary-policy ;
vc:requires ngm:central-bank-infrastructure ;
vc:requires ngm:digital-identity ;
vc:requires ngm:distributed-ledger-technology ;
vc:requires ngm:kyc-aml-compliance ;
vc:requires ngm:payment-network ;
vc:slug "central-bank-digital-currency" ;
vc:sourceDomain "finance" ;
vc:standardizedBy ngm:bank-for-international-settlements ;
vc:standardizedBy ngm:imf ;
vc:supports ngm:financial-stability ;
vc:uses ngm:blockchain ;
vc:uses ngm:cryptographic-key-management ;
vc:uses ngm:smart-contract .
ngm:central-bank-digital-currency-cbdc a owl:Class ;
rdfs:comment "Sovereign digital currency issued and backed by a central bank for use in retail or wholesale payment systems, functioning as legal tender in digital form."@en ;
rdfs:label "Central Bank Digital Currency (CBDC)"@en ;
rdfs:subClassOf ngm:infra-computing-and-cloud ;
rdfs:subClassOf _:r4086 ;
rdfs:subClassOf _:r4087 ;
rdfs:subClassOf _:r4088 ;
rdfs:subClassOf _:r4089 ;
rdfs:subClassOf _:r4090 ;
rdfs:subClassOf _:r4091 ;
rdfs:subClassOf _:r4092 ;
rdfs:subClassOf _:r4093 ;
rdfs:subClassOf _:r4094 ;
rdfs:subClassOf _:r4095 ;
skos:broader ngm:infra-computing-and-cloud ;
vc:bridgesTo ngm:blockchain ;
vc:dependsOn ngm:banking-infrastructure ;
vc:dependsOn ngm:cryptographic-protocol ;
vc:dependsOn ngm:settlement ;
vc:enables ngm:digital-payments ;
vc:enables ngm:financial-inclusion ;
vc:enables ngm:monetary-policy-implementation ;
vc:enables ngm:programmable-money ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:digital-currency-ledger ;
vc:hasPart ngm:identity-system ;
vc:hasPart ngm:identity-systems ;
vc:hasPart ngm:payment-protocol ;
vc:hasPart ngm:validator ;
vc:implements ngm:payment-system ;
vc:isPartOf ngm:financial-system ;
vc:isPartOf ngm:monetary-system ;
vc:isPartOf ngm:payment-infrastructure ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:central-bank ;
vc:requires ngm:digital-wallet ;
vc:requires ngm:distributed-ledger ;
vc:requires ngm:identity-verification ;
vc:requires ngm:regulatory-framework ;
vc:slug "central-bank-digital-currency-cbdc" ;
vc:sourceDomain "infrastructure" .
ngm:central-bank-gold-reserve a skos:Concept ;
rdfs:label "Central Bank Gold Reserve"@en .
ngm:central-bank-independence a skos:Concept ;
rdfs:label "Central Bank Independence"@en .
ngm:central-bank-infrastructure a owl:Class ;
rdfs:comment "Central bank infrastructure encompasses the systems, networks, and institutional arrangements through which a central bank fulfils its core functions: operating real-time gross settlement (RTGS) systems for interbank payments, managing the issuance and lifecycle of physical and digital currency, implementing monetary policy, maintaining financial stability, and serving as lender of last resort. It includes SWIFT connectivity, RTGS platforms (such as CHAPS, Fedwire, TARGET2), central securities depositories, and increasingly the digital and distributed ledger systems under evaluation for CBDC issuance. This infrastructure forms the foundation upon which all commercial banking and payment activity ultimately settles."@en ;
rdfs:label "Central Bank Infrastructure"@en ;
rdfs:subClassOf ngm:payment-infrastructure ;
vc:enables ngm:atomic-settlement ;
vc:enables ngm:cbdc-infrastructure ;
vc:enables ngm:monetary-policy-implementation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:central-bank ;
vc:relatedTo ngm:monetary-policy ;
vc:slug "central-bank-infrastructure" ;
vc:sourceDomain "finance" ;
vc:supports ngm:cross-border-settlement ;
vc:supports ngm:financial-stability .
ngm:central-bank-monetary-policy a skos:Concept ;
rdfs:label "Central Bank Monetary Policy"@en .
ngm:central-bank-policy a skos:Concept ;
rdfs:label "Central Bank Policy"@en .
ngm:central-bank-reserve-management a skos:Concept ;
rdfs:label "Central Bank Reserve Management"@en .
ngm:central-banking a owl:Class ;
rdfs:comment "Central banking is the institutional practice of managing a nation's currency, money supply, and interest rates through a designated monetary authority. It encompasses setting policy rates, managing reserve requirements, and acting as lender of last resort to the banking system. Central banking decisions propagate through interbank settlement, credit markets, and macroeconomic conditions."@en ;
rdfs:label "Central Banking"@en ;
rdfs:subClassOf ngm:central-bank ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "central-banking" ;
vc:sourceDomain "finance" .
ngm:central-controller a skos:Concept ;
rdfs:label "Central Controller"@en .
ngm:central-counterparty a skos:Concept ;
rdfs:label "Central Counterparty"@en .
ngm:central-counterparty-clearing a skos:Concept ;
rdfs:label "Central Counterparty Clearing"@en .
ngm:central-limit-theorem a owl:Class ;
rdfs:comment "The Central Limit Theorem states that, under broad conditions, the distribution of the sum or mean of a large number of independent, identically distributed random variables approaches a normal distribution regardless of the underlying distribution's shape. It explains the ubiquity of the Gaussian distribution and provides the theoretical basis for many inferential procedures, including confidence intervals and significance tests. It is foundational to statistics, machine learning, and Monte Carlo estimation."@en ;
rdfs:label "Central Limit Theorem"@en ;
rdfs:subClassOf ngm:limit-theorems ;
rdfs:subClassOf ngm:measure-theory ;
rdfs:subClassOf ngm:probability-theory ;
rdfs:subClassOf ngm:statistical-theory ;
rdfs:subClassOf _:r4104 ;
rdfs:subClassOf _:r4105 ;
rdfs:subClassOf _:r4106 ;
rdfs:subClassOf _:r4107 ;
rdfs:subClassOf _:r4108 ;
rdfs:subClassOf _:r4109 ;
vc:contrastsWith ngm:alpha-stable-processes ;
vc:contrastsWith ngm:extreme-value-theory ;
vc:contrastsWith ngm:heavy-tailed-distribution ;
vc:contrastsWith ngm:stable-distribution ;
vc:dependsOn ngm:measure-theory ;
vc:dependsOn ngm:probability-theory ;
vc:dependsOn ngm:random-variable ;
vc:dependsOn ngm:sampling ;
vc:dependsOn ngm:sigma-algebra ;
vc:enables ngm:a-b-testing ;
vc:enables ngm:bayesian-inference ;
vc:enables ngm:confidence-interval ;
vc:enables ngm:error-bar-estimation ;
vc:enables ngm:hypothesis-testing ;
vc:enables ngm:significance-testing ;
vc:enables ngm:statistical-analysis ;
vc:enables ngm:statistical-testing ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:berry-esseen-theorem ;
vc:hasPart ngm:characteristic-function ;
vc:hasPart ngm:convergence-in-distribution ;
vc:hasPart ngm:gaussian-distribution ;
vc:hasPart ngm:inference ;
vc:hasPart ngm:sampling-distribution ;
vc:hasPart ngm:standardisation ;
vc:implements ngm:gaussian-approximation ;
vc:implements ngm:law-of-large-numbers ;
vc:implements ngm:normal-approximation ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:conformal-prediction ;
vc:relatedTo ngm:data-analysis ;
vc:relatedTo ngm:information-theory ;
vc:relatedTo ngm:law-of-large-numbers ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:markov-chain-monte-carlo ;
vc:relatedTo ngm:probability-theory ;
vc:relatedTo ngm:stochastic-gradient-descent ;
vc:relatedTo ngm:uncertainty-quantification ;
vc:requires ngm:finite-variance ;
vc:requires ngm:independent-and-identically-distributed ;
vc:requires ngm:measure-theory ;
vc:requires ngm:probability-theory ;
vc:requires ngm:random-variable ;
vc:slug "central-limit-theorem" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:berry-1941 ;
vc:standardizedBy ngm:esseen-1956 ;
vc:standardizedBy ngm:kolmogorov-1933 ;
vc:standardizedBy ngm:l-vy-1937 ;
vc:supports ngm:bootstrap-resampling ;
vc:supports ngm:monte-carlo-integration ;
vc:supports ngm:monte-carlo-simulation ;
vc:supports ngm:reinforcement-learning ;
vc:supports ngm:stochastic-gradient-descent ;
vc:supports ngm:uncertainty-quantification ;
vc:uses ngm:characteristic-function ;
vc:uses ngm:fourier-analysis ;
vc:uses ngm:gaussian-distribution ;
vc:uses ngm:statistics .
ngm:central-planning a skos:Concept ;
rdfs:label "Central Planning"@en .
ngm:central-processing-unit a owl:Class ;
rdfs:comment "The central processing unit (CPU) is the primary computational component of a computer, executing the instructions of programs through arithmetic, logic, control, and input/output operations. It fetches instructions from memory, decodes them, and executes them in a repeating cycle, coordinated by a control unit and carried out by arithmetic-logic units across one or more cores. As a general-purpose processor it contrasts with specialised accelerators that optimise for narrower, highly parallel workloads."@en ;
rdfs:label "Central Processing Unit"@en ;
rdfs:subClassOf ngm:computer-hardware ;
rdfs:subClassOf _:r4110 ;
rdfs:subClassOf _:r4111 ;
vc:contrastsWith ngm:gpu ;
vc:contrastsWith ngm:graphics-processing-unit ;
vc:enables ngm:data-processing ;
vc:enables ngm:parallel-computing ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:computer-hardware ;
vc:isPartOf ngm:computer-hardware ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:edge-computing ;
vc:relatedTo ngm:infrastructure ;
vc:relatedTo ngm:parallel-computing ;
vc:requires ngm:computer-hardware ;
vc:slug "central-processing-unit" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:data-processing ;
vc:supports ngm:infrastructure .
ngm:central-securities-depository a owl:Class ;
rdfs:comment "A central securities depository (CSD) is a financial market infrastructure that holds securities in dematerialised or immobilised form and enables their transfer through book-entry, providing safekeeping and settlement of trades. It maintains the authoritative record of securities ownership and supports the final leg of post-trade processing, often in conjunction with clearing houses. By centralising custody and settlement, a CSD reduces operational risk and is foundational to the integrity of securities markets."@en ;
rdfs:label "Central Securities Depository"@en ;
rdfs:subClassOf ngm:financial-market-infrastructure ;
rdfs:subClassOf _:r4112 ;
rdfs:subClassOf _:r4113 ;
rdfs:subClassOf _:r4114 ;
rdfs:subClassOf _:r4115 ;
vc:bridgesTo ngm:blockchain ;
vc:contrastsWith ngm:blockchain ;
vc:dependsOn ngm:clearing-and-settlement ;
vc:dependsOn ngm:settlement ;
vc:enables ngm:atomic-settlement ;
vc:enables ngm:delivery-versus-payment ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:custody ;
vc:hasPart ngm:securities-settlement ;
vc:isPartOf ngm:financial-market-infrastructure ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:netting ;
vc:relatedTo ngm:trade-execution ;
vc:requires ngm:custody ;
vc:requires ngm:settlement-finality ;
vc:slug "central-securities-depository" ;
vc:sourceDomain "finance" ;
vc:supports ngm:settlement ;
vc:uses ngm:settlement .
ngm:centralised-ai a owl:Class ;
rdfs:comment "An organisational and architectural model of artificial intelligence in which training data, compute, model weights, and inference services are concentrated under a single operator in large data centres, with users accessing capability remotely through APIs; the contrast class to decentralised AI, edge inference, and multi-agent approaches that distribute computation, control, or decision-making across many independent nodes."@en ;
rdfs:label "Centralised AI"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:contrastsWith ngm:decentralised-ai ;
vc:contrastsWith ngm:edge-inference ;
vc:contrastsWith ngm:multi-agent-system ;
vc:dependsOn ngm:cloud-computing ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:compute-governance ;
vc:slug "centralised-ai" ;
vc:sourceDomain "artificial-intelligence" .
ngm:centralised-ai-inference a skos:Concept ;
rdfs:label "Centralised AI Inference"@en .
ngm:centralised-authority a skos:Concept ;
rdfs:label "Centralised Authority"@en .
ngm:centralised-bridge a skos:Concept ;
rdfs:label "Centralised Bridge"@en .
ngm:centralised-carbon-exchange a skos:Concept ;
rdfs:label "Centralised Carbon Exchange"@en .
ngm:centralised-carbon-market a skos:Concept ;
rdfs:label "Centralised Carbon Market"@en .
ngm:centralised-cloud a skos:Concept ;
rdfs:label "Centralised Cloud"@en .
ngm:centralised-cloud-computing a skos:Concept ;
rdfs:label "Centralised Cloud Computing"@en .
ngm:centralised-computing a skos:Concept ;
rdfs:label "Centralised Computing"@en .
ngm:centralised-consensus a skos:Concept ;
rdfs:label "Centralised Consensus"@en .
ngm:centralised-control a owl:Class ;
rdfs:comment "Centralised control is a governance arrangement in which decision-making authority, coordination, and enforcement are concentrated in a single entity or hierarchy rather than distributed among participants. It offers clarity of accountability and rapid, consistent decisions but introduces a single point of failure and dependence on the controlling party's competence and intentions. Centralised control is the principal foil against which decentralised and distributed governance models define themselves."@en ;
rdfs:label "Centralised Control"@en ;
rdfs:subClassOf ngm:governance ;
rdfs:subClassOf _:r4116 ;
vc:bridgesTo ngm:governance ;
vc:contrastsWith ngm:decentralisation ;
vc:contrastsWith ngm:decentralised-governance ;
vc:contrastsWith ngm:distributed-governance ;
vc:dependsOn ngm:single-point-of-failure ;
vc:enables ngm:hierarchical-organisation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:governance ;
vc:isPartOf ngm:governance ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:community-governance ;
vc:relatedTo ngm:multi-agent-coordination ;
vc:requires ngm:access-control ;
vc:slug "centralised-control" ;
vc:sourceDomain "governance" ;
vc:supports ngm:hierarchical-organisation ;
vc:uses ngm:access-control .
ngm:centralised-coordination a skos:Concept ;
rdfs:label "Centralised Coordination"@en .
ngm:centralised-corporate-governance-reporting a skos:Concept ;
rdfs:label "Centralised Corporate Governance Reporting"@en .
ngm:centralised-data-silos a skos:Concept ;
rdfs:label "Centralised Data Silos"@en .
ngm:centralised-database a owl:Class ;
rdfs:comment "A centralised database is a data management system in which all data is stored, administered, and accessed through a single physical or logical location under a single controlling authority. It provides a unified, authoritative view of data with strong consistency guarantees, simplified access control, and a single point of administration. All read and write operations are routed to this central node or cluster, making it the canonical source of truth for the entire system. The centralised model contrasts with distributed and decentralised architectures by sacrificing geographic fault-tolerance and autonomy in exchange for consistency, reduced coordination overhead, and operational simplicity."@en ;
rdfs:label "Centralised Database"@en ;
rdfs:subClassOf ngm:database-management-system ;
rdfs:subClassOf _:r4117 ;
rdfs:subClassOf _:r4118 ;
rdfs:subClassOf _:r4119 ;
rdfs:subClassOf _:r4120 ;
rdfs:subClassOf _:r4121 ;
rdfs:subClassOf _:r4122 ;
rdfs:subClassOf _:r4123 ;
rdfs:subClassOf _:r4124 ;
vc:bridgesTo ngm:cloud-storage ;
vc:bridgesTo ngm:data-lake ;
vc:bridgesTo ngm:federated-learning ;
vc:contrastsWith ngm:blockchain ;
vc:contrastsWith ngm:decentralised-storage ;
vc:contrastsWith ngm:distributed-databases ;
vc:contrastsWith ngm:peer-to-peer-network ;
vc:dependsOn ngm:infrastructure ;
vc:dependsOn ngm:operating-system ;
vc:enables ngm:access-control ;
vc:enables ngm:acid-properties ;
vc:enables ngm:data-consistency ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:access-control ;
vc:hasPart ngm:query-engine ;
vc:hasPart ngm:relational-database ;
vc:hasPart ngm:transaction-manager ;
vc:implements ngm:acid-transactions ;
vc:implements ngm:sql ;
vc:isPartOf ngm:data-management ;
vc:isPartOf ngm:information-system ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:cap-theorem ;
vc:relatedTo ngm:data-warehouse ;
vc:relatedTo ngm:nosql-database ;
vc:relatedTo ngm:single-point-of-failure ;
vc:requires ngm:backup-and-recovery ;
vc:requires ngm:data-storage ;
vc:requires ngm:network-infrastructure ;
vc:slug "centralised-database" ;
vc:sourceDomain "data" ;
vc:standardizedBy ngm:ansi-sql ;
vc:standardizedBy ngm:iso-iec-9075 ;
vc:supports ngm:audit-logging ;
vc:supports ngm:data-governance ;
vc:supports ngm:regulatory-compliance ;
vc:uses ngm:indexing ;
vc:uses ngm:optimisation ;
vc:uses ngm:replication .
ngm:centralised-decision-making a skos:Concept ;
rdfs:label "Centralised Decision Making"@en .
ngm:centralised-exchange a owl:Class ;
rdfs:comment "A centralised exchange (CEX) is a custodial trading venue operated by a single company that matches buy and sell orders for cryptocurrencies and other assets through an internal order book. Users deposit funds into accounts the operator controls, and the exchange maintains the ledger of balances off-chain, settling trades internally rather than on a public blockchain. Centralised exchanges typically enforce identity verification and provide high liquidity and fast execution, at the cost of requiring trust in the operator."@en ;
rdfs:label "Centralised Exchange"@en ;
rdfs:subClassOf ngm:financial-infrastructure ;
rdfs:subClassOf _:r4125 ;
rdfs:subClassOf _:r4126 ;
rdfs:subClassOf _:r4127 ;
vc:contrastsWith ngm:decentralised-exchange ;
vc:enables ngm:liquidity ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:order-book ;
vc:implements ngm:aml ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:binance ;
vc:relatedTo ngm:blockchain ;
vc:relatedTo ngm:coinbase ;
vc:relatedTo ngm:financial-services ;
vc:requires ngm:custody ;
vc:requires ngm:kyc ;
vc:slug "centralised-exchange" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:liquidity ;
vc:uses ngm:identity-verification .
ngm:centralised-exchange-bridging a skos:Concept ;
rdfs:label "Centralised Exchange Bridging"@en .
ngm:centralised-exchange-feed a skos:Concept ;
rdfs:label "Centralised Exchange Feed"@en .
ngm:centralised-exchange-token a skos:Concept ;
rdfs:label "Centralised Exchange Token"@en .
ngm:centralised-execution a skos:Concept ;
rdfs:label "Centralised Execution"@en .
ngm:centralised-file-server a skos:Concept ;
rdfs:label "Centralised File Server"@en .
ngm:centralised-finance a owl:Class ;
rdfs:comment "Centralised Finance (CeFi) is a model of financial service provision in which a trusted intermediary custodies user assets and operates the order books, matching engines and settlement rails on behalf of participants. In the cryptocurrency context it denotes exchanges and lending platforms that hold customer funds in pooled wallets and enforce identity verification, in contrast to non-custodial, smart-contract-mediated alternatives. CeFi platforms offer familiar account models, fiat on-ramps and regulatory compliance at the cost of counterparty trust."@en ;
rdfs:label "Centralised Finance"@en ;
rdfs:subClassOf ngm:finance ;
rdfs:subClassOf _:r4128 ;
rdfs:subClassOf _:r4129 ;
vc:bridgesTo ngm:traditional-finance ;
vc:contrastsWith ngm:de-fi ;
vc:contrastsWith ngm:self-regulation ;
vc:dependsOn ngm:authentication ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:finance ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:global-digital-finance ;
vc:relatedTo ngm:stablecoin ;
vc:relatedTo ngm:tokenomics ;
vc:requires ngm:compliance ;
vc:requires ngm:fiat-currency ;
vc:slug "centralised-finance" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:liquidity ;
vc:uses ngm:centralised-exchange ;
vc:uses ngm:custodial-wallet ;
vc:uses ngm:kyc .
ngm:centralised-governance a owl:Class ;
rdfs:comment "Centralised governance is a model in which decision-making authority over a system, protocol, or organisation is concentrated in a single entity or a small controlling group. In contrast to distributed models, changes, upgrades, and policy are determined by this authority rather than by broad stakeholder consensus, which can deliver faster, more decisive action at the cost of reduced censorship resistance and a single point of control. It is the conventional baseline against which decentralised governance defines itself."@en ;
rdfs:label "Centralised Governance"@en ;
rdfs:subClassOf ngm:governance-framework ;
rdfs:subClassOf _:r4130 ;
vc:contrastsWith ngm:dao ;
vc:contrastsWith ngm:decentralisation ;
vc:contrastsWith ngm:decentralised-governance ;
vc:enables ngm:audit ;
vc:enables ngm:compliance ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:governance ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:corporate-governance ;
vc:relatedTo ngm:governance ;
vc:relatedTo ngm:regulatory-compliance ;
vc:requires ngm:access-control ;
vc:slug "centralised-governance" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:financial-services .
ngm:centralised-identifier a owl:Class ;
rdfs:comment "An identifier issued, controlled, and resolvable only through a central authority—such as an email address bound to a provider, a username on a platform, a government-issued number, or a domain name under registry control. Centralised identifiers are the architectural opposite of decentralised identifiers: the issuing authority can revoke, reassign, surveil, or lose them, creating single points of failure and lock-in, but also offering simple governance, accountability, and recovery paths that self-sovereign schemes must engineer explicitly."@en ;
rdfs:label "Centralised Identifier"@en ;
rdfs:subClassOf ngm:identifier ;
vc:contrastsWith ngm:decentralised-identifier ;
vc:dependsOn ngm:certificate-authority ;
vc:dependsOn ngm:domain-name-system ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:digital-identity ;
vc:relatedTo ngm:identity-management ;
vc:relatedTo ngm:single-point-of-failure ;
vc:slug "centralised-identifier" ;
vc:sourceDomain "security" .
ngm:centralised-identity a owl:Class ;
rdfs:comment "Centralised identity is a digital identity model in which a single authority — such as a government, enterprise, or platform identity provider — issues, stores, and controls users' identity credentials and authenticates them on behalf of relying parties. Users authenticate against the central provider, which holds the authoritative record of their attributes and mediates access to connected services. The model is operationally simple and widely deployed, but concentrates control, data, and risk in one party, creating single points of failure, surveillance potential, and vendor lock-in that decentralised and self-sovereign identity approaches are designed to counter."@en ;
rdfs:label "Centralised Identity"@en ;
rdfs:subClassOf ngm:identity-management ;
rdfs:subClassOf _:r4131 ;
rdfs:subClassOf _:r4132 ;
rdfs:subClassOf _:r4133 ;
vc:bridgesTo ngm:verifiable-credentials ;
vc:contrastsWith ngm:decentralised-identity ;
vc:contrastsWith ngm:self-sovereign-identity ;
vc:dependsOn ngm:authentication ;
vc:enables ngm:federated-identity ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:authentication ;
vc:hasPart ngm:identity-provider ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:digital-identity ;
vc:relatedTo ngm:identity-management ;
vc:requires ngm:identity-provider ;
vc:slug "centralised-identity" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:access-control ;
vc:uses ngm:access-control ;
vc:uses ngm:oauth ;
vc:uses ngm:single-sign-on .
ngm:centralised-index a skos:Concept ;
rdfs:label "Centralised Index"@en .
ngm:centralised-inference a skos:Concept ;
rdfs:label "Centralised Inference"@en .
ngm:centralised-learning a skos:Concept ;
rdfs:label "Centralised Learning"@en .
ngm:centralised-ledger a skos:Concept ;
rdfs:label "Centralised Ledger"@en .
ngm:centralised-ledger-design a skos:Concept ;
rdfs:label "Centralised Ledger Design"@en .
ngm:centralised-machine-learning a skos:Concept ;
rdfs:label "Centralised Machine Learning"@en .
ngm:centralised-monitoring a skos:Concept ;
rdfs:label "Centralised Monitoring"@en .
ngm:centralised-oracle a skos:Concept ;
rdfs:label "Centralised Oracle"@en .
ngm:centralised-orchestration a skos:Concept ;
rdfs:label "Centralised Orchestration"@en .
ngm:centralised-payment-system a skos:Concept ;
rdfs:label "Centralised Payment System"@en .
ngm:centralised-rating-systems a skos:Concept ;
rdfs:label "Centralised Rating Systems"@en .
ngm:centralised-sensing a skos:Concept ;
rdfs:label "Centralised Sensing"@en .
ngm:centralised-single-window a skos:Concept ;
rdfs:label "Centralised Single Window"@en .
ngm:centralised-social-media a skos:Concept ;
rdfs:label "Centralised Social Media"@en .
ngm:centralised-system a skos:Concept ;
rdfs:label "Centralised System"@en .
ngm:centralised-training a skos:Concept ;
rdfs:label "Centralised Training"@en .
ngm:centralised-treasury-management a skos:Concept ;
rdfs:label "Centralised Treasury Management"@en .
ngm:centralised-version-control a skos:Concept ;
rdfs:label "Centralised Version Control"@en .
ngm:centralised-workflow a skos:Concept ;
rdfs:label "Centralised Workflow"@en .
ngm:centrality-measure a skos:Concept ;
rdfs:label "Centrality Measure"@en .
ngm:centralized-application a owl:Class ;
rdfs:comment "A software application whose logic, state, and data are operated by a single controlling entity on infrastructure it administers, typically following a client-server architecture in which users depend on the operator for availability, data custody, access control, and rule changes, in contrast to decentralised applications whose execution and state are replicated across a permissionless network."@en ;
rdfs:label "Centralised Application"@en ;
rdfs:subClassOf ngm:software-system ;
vc:contrastsWith ngm:blockchain-application ;
vc:contrastsWith ngm:decentralised-application ;
vc:contrastsWith ngm:decentralized-application ;
vc:dependsOn ngm:cloud-computing ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:single-point-of-failure ;
vc:slug "centralized-application" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:client-server-architecture .
ngm:centralized-exchange a owl:Class ;
rdfs:comment "A centralized exchange (CEX) is a digital-asset trading venue operated by a single company that custodies user funds, matches orders through an internal order book, and acts as an intermediary for every trade. Users deposit assets into accounts controlled by the operator, who maintains liquidity, settlement, and the matching engine off-chain. CEXs offer high throughput and familiar interfaces but require trust in the operator and typically enforce identity-verification and anti-money-laundering controls."@en ;
rdfs:label "Centralized Exchange"@en ;
rdfs:subClassOf ngm:bc-defi-and-economics ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf _:r4134 ;
rdfs:subClassOf _:r4135 ;
rdfs:subClassOf _:r4136 ;
rdfs:subClassOf _:r4137 ;
skos:broader ngm:bc-defi-and-economics ;
skos:broader ngm:blockchain ;
vc:bridgesTo ngm:order-book ;
vc:contrastsWith ngm:decentralized-exchange ;
vc:contrastsWith ngm:self-custody ;
vc:dependsOn ngm:custody ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:binance ;
vc:relatedTo ngm:coinbase ;
vc:relatedTo ngm:de-fi ;
vc:requires ngm:custody ;
vc:requires ngm:kyc ;
vc:requires ngm:liquidity ;
vc:requires ngm:order-book ;
vc:slug "centralized-exchange" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:liquidity ;
vc:supports ngm:stablecoin ;
vc:uses ngm:aml ;
vc:uses ngm:custodial-wallet .
ngm:centralized-identity-provider a owl:Class ;
rdfs:comment "An identity service in which a single organisation issues, stores and authenticates user credentials on behalf of relying parties. It contrasts with decentralised identity models where control rests with the user."@en ;
rdfs:label "Centralized Identity Provider"@en ;
rdfs:subClassOf ngm:identity-provider ;
rdfs:subClassOf _:r4138 ;
vc:bridgesTo ngm:decentralized-identifier ;
vc:enables ngm:identity-verification-system ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:identity-management ;
vc:slug "centralized-identity-provider" ;
vc:sourceDomain "security" .
ngm:centralized-robot-control a skos:Concept ;
rdfs:label "Centralized Robot Control"@en .
ngm:centralized-swarm-control a owl:Class ;
rdfs:comment "Swarm robotics control architecture where a central controller coordinates all robot agents, providing global optimisation but creating a single point of failure."@en ;
rdfs:label "Centralized Swarm Control"@en ;
rdfs:subClassOf ngm:centralized-control-architecture ;
rdfs:subClassOf ngm:control-system ;
rdfs:subClassOf ngm:robo-robot-type ;
rdfs:subClassOf ngm:robotics ;
rdfs:subClassOf ngm:swarm-control ;
rdfs:subClassOf _:r4139 ;
rdfs:subClassOf _:r4140 ;
rdfs:subClassOf _:r4141 ;
skos:broader ngm:robo-robot-type ;
skos:broader ngm:robotics ;
vc:bridgesTo ngm:decentralized-swarm-control ;
vc:bridgesTo ngm:hierarchical-control-systems ;
vc:bridgesTo ngm:swarm-control ;
vc:enables ngm:centralised-monitoring ;
vc:enables ngm:coordinated-swarm-behaviour ;
vc:enables ngm:global-task-optimisation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:central-controller ;
vc:hasPart ngm:communication-network ;
vc:hasPart ngm:global-state-model ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:computational-resources ;
vc:requires ngm:inter-agent-communication ;
vc:requires ngm:synchronised-timing ;
vc:slug "centralized-swarm-control" ;
vc:sourceDomain "robotics" .
ngm:centre-consortium a skos:Concept ;
rdfs:label "Centre Consortium"@en .
ngm:centre-for-data-ethics-and-innovation a skos:Concept ;
rdfs:label "Centre For Data Ethics And Innovation"@en .
ngm:centre-for-the-study-of-existential-risk a skos:Concept ;
rdfs:label "Centre For The Study Of Existential Risk"@en .
ngm:centrifuge a owl:Class ;
rdfs:comment "Centrifuge is a decentralised finance protocol that brings real-world assets such as invoices and loans on chain so they can be used as collateral for financing."@en ;
rdfs:label "Centrifuge"@en ;
rdfs:subClassOf ngm:asset-tokenisation ;
rdfs:subClassOf _:r4142 ;
rdfs:subClassOf _:r4143 ;
vc:bridgesTo ngm:de-fi ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:asset-tokenisation ;
vc:requires ngm:smart-contract ;
vc:slug "centrifuge" ;
vc:sourceDomain "blockchain" .
ngm:century-tech a skos:Concept ;
rdfs:label "Century Tech"@en .
ngm:ceo-led-ai-strategy a owl:Class ;
rdfs:comment "An organizational approach where the Chief Executive Officer provides direct, high-level oversight and strategic direction for artificial intelligence initiatives to ensure alignment with business goals."@en ;
rdfs:label "CEO-led AI Strategy"@en ;
rdfs:subClassOf ngm:ai-policy ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-governance-framework ;
vc:relatedTo ngm:ai-policy ;
vc:slug "ceo-led-ai-strategy" ;
vc:sourceDomain "governance" .
ngm:ceph a owl:Class ;
rdfs:comment "An open-source software-defined storage platform that provides object, block, and file storage from a single self-healing cluster of commodity servers, using the CRUSH algorithm to place data deterministically without a central metadata bottleneck, and protecting data through replication or erasure coding; widely deployed beneath OpenStack and Kubernetes as exabyte-scale storage infrastructure."@en ;
rdfs:label "Ceph"@en ;
rdfs:subClassOf ngm:distributed-storage ;
vc:enables ngm:high-availability ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:storage-infrastructure ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:distributed-file-system ;
vc:relatedTo ngm:kubernetes ;
vc:relatedTo ngm:object-storage ;
vc:slug "ceph" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:erasure-coding ;
vc:uses ngm:replication .
ngm:ceramic a skos:Concept ;
rdfs:label "Ceramic"@en .
ngm:ceramic-network a skos:Concept ;
rdfs:label "Ceramic Network"@en .
ngm:cerebras-wafer-scale-chips a owl:Class ;
rdfs:comment "A specialized AI hardware architecture developed by Cerebras that integrates a massive number of transistors onto a single wafer-scale integrated circuit to enable high-speed AI inference and training."@en ;
rdfs:label "Cerebras Wafer Scale Chips"@en ;
rdfs:subClassOf ngm:ai-hardware-infrastructure ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-hardware-infrastructure ;
vc:relatedTo ngm:gpt-53-codex-spark ;
vc:slug "cerebras-wafer-scale-chips" ;
vc:sourceDomain "infrastructure" .
ngm:ceremonial-space a skos:Concept ;
rdfs:label "Ceremonial Space"@en .
ngm:ceres-solver a skos:Concept ;
rdfs:label "Ceres Solver"@en .
ngm:certainty-scale a skos:Concept ;
rdfs:label "Certainty Scale"@en .
ngm:certificate-authority a owl:Class ;
rdfs:comment "A Certificate Authority (CA) is a trusted third-party organisation that issues, signs, and manages the lifecycle of X.509 digital certificates, cryptographically binding a public key to an entity's verified identity within a Public Key Infrastructure (PKI). CAs operate within a hierarchical trust model where offline root CAs delegate signing authority to online intermediate CAs, which in turn issue end-entity certificates for servers, users, clients, and devices. The CA's signing operations — governed by RFC 5280, the CA/Browser Forum Baseline Requirements, and WebTrust auditing standards — underpin the TLS handshake, code-signing pipelines, S/MIME email encryption, mutual TLS (mTLS) in service meshes, and document-signing workflows across the internet. Trust propagates via chain-of-trust verification: a relying party validates each certificate against its issuer's signature, tracing back to an implicitly trusted root embedded in OS or browser trust stores."@en ;
rdfs:label "Certificate Authority"@en ;
rdfs:subClassOf ngm:infra-security-and-identity ;
rdfs:subClassOf _:r4144 ;
rdfs:subClassOf _:r4145 ;
rdfs:subClassOf _:r4146 ;
rdfs:subClassOf _:r4147 ;
rdfs:subClassOf _:r4148 ;
rdfs:subClassOf _:r4149 ;
rdfs:subClassOf _:r4150 ;
rdfs:subClassOf _:r4151 ;
rdfs:subClassOf _:r4152 ;
skos:broader ngm:infra-security-and-identity ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:verifiable-credential-vc ;
vc:bridgesTo ngm:zero-knowledge-proof ;
vc:contrastsWith ngm:decentralised-identity ;
vc:contrastsWith ngm:self-sovereign-identity ;
vc:contrastsWith ngm:web-of-trust ;
vc:enables ngm:code-signing ;
vc:enables ngm:digital-certificate ;
vc:enables ngm:encryption ;
vc:enables ngm:tls ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:certificate-authority ;
vc:hasPart ngm:certificate-revocation-list ;
vc:hasPart ngm:online-certificate-status-protocol ;
vc:hasPart ngm:root-certificate ;
vc:isPartOf ngm:cryptographic-infrastructure ;
vc:isPartOf ngm:trust-hierarchy ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:acme-protocol ;
vc:relatedTo ngm:certificate-transparency ;
vc:relatedTo ngm:domain-validation ;
vc:relatedTo ngm:key-management ;
vc:requires ngm:asymmetric-cryptography ;
vc:requires ngm:cryptography ;
vc:requires ngm:digital-signature ;
vc:requires ngm:hardware-security-module ;
vc:slug "certificate-authority" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:ca-browser-forum ;
vc:standardizedBy ngm:rfc-5280 ;
vc:standardizedBy ngm:webtrust ;
vc:supports ngm:authentication ;
vc:supports ngm:identity-management ;
vc:supports ngm:mutual-tls ;
vc:supports ngm:zero-trust-architecture .
ngm:certificate-authority-interface a skos:Concept ;
rdfs:label "Certificate Authority Interface"@en .
ngm:certificate-lifecycle-management a skos:Concept ;
rdfs:label "Certificate Lifecycle Management"@en .
ngm:certificate-of-compliance a skos:Concept ;
rdfs:label "Certificate Of Compliance"@en .
ngm:certificate-of-origin a skos:Concept ;
rdfs:label "Certificate Of Origin"@en .
ngm:certificate-revocation a owl:Class ;
rdfs:comment "Certificate Revocation is the process by which a Certificate Authority (CA) invalidates a previously issued digital certificate before its natural expiry, typically due to key compromise, CA compromise, or change in the certificate holder's status. Revocation information is distributed via Certificate Revocation Lists (CRLs) or the Online Certificate Status Protocol (OCSP). It is a critical component of public key infrastructure (PKI) lifecycle management."@en ;
rdfs:label "Certificate Revocation"@en ;
rdfs:subClassOf ngm:security ;
rdfs:subClassOf _:r4155 ;
rdfs:subClassOf _:r4156 ;
rdfs:subClassOf _:r4157 ;
rdfs:subClassOf _:r4158 ;
vc:contrastsWith ngm:certificate-transparency ;
vc:contrastsWith ngm:short-lived-certificate ;
vc:enables ngm:identity-management ;
vc:enables ngm:zero-trust-architecture ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:certificate-revocation-list ;
vc:hasPart ngm:ocsp ;
vc:implements ngm:pki ;
vc:implements ngm:trust-management ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:certificate-authority ;
vc:relatedTo ngm:cryptographic-infrastructure ;
vc:relatedTo ngm:digital-certificate ;
vc:relatedTo ngm:incident-response ;
vc:relatedTo ngm:key-management ;
vc:requires ngm:certificate-authority ;
vc:requires ngm:cryptographic-protocol ;
vc:slug "certificate-revocation" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:rfc-5280 ;
vc:standardizedBy ngm:x-509-certificate ;
vc:standardizedBy ngm:x509 ;
vc:supports ngm:http ;
vc:supports ngm:tls .
ngm:certificate-revocation-list a owl:Class ;
rdfs:comment "A Certificate Revocation List (CRL) is a digitally signed, periodically published list of digital certificates that a certificate authority has revoked before their scheduled expiry. Each entry records the serial number of a revoked certificate, the revocation date, and an optional reason code, allowing relying parties to reject certificates that are no longer trustworthy. CRLs are a core revocation mechanism of X.509 public key infrastructure, complemented or replaced in many deployments by the Online Certificate Status Protocol."@en ;
rdfs:label "Certificate Revocation List"@en ;
rdfs:subClassOf ngm:revocation-registry ;
rdfs:subClassOf _:r4153 ;
rdfs:subClassOf _:r4154 ;
vc:contrastsWith ngm:ocsp ;
vc:dependsOn ngm:certificate-authority ;
vc:enables ngm:digital-certificate ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:digital-signature ;
vc:implements ngm:rfc-5280 ;
vc:isPartOf ngm:cryptographic-infrastructure ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:certificate-authority ;
vc:relatedTo ngm:certificate-transparency ;
vc:requires ngm:public-key-cryptography ;
vc:slug "certificate-revocation-list" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:ietf ;
vc:supports ngm:trust-anchor ;
vc:supports ngm:x-509-certificate ;
vc:uses ngm:digital-signature .
ngm:certificate-transparency a owl:Class ;
rdfs:comment "Certificate Transparency (CT) is an open framework and internet standard (RFC 6962 and RFC 9162) that creates a publicly auditable, append-only log of all TLS certificates issued by certificate authorities, enabling domain owners, browser vendors, and security researchers to detect misissued or fraudulent certificates rapidly. CT logs use Merkle hash trees to provide cryptographic proofs of inclusion and consistency, guaranteeing that any certificate added to a log cannot be subsequently removed or altered. Major browsers enforce CT by requiring certificates to carry signed certificate timestamps (SCTs) from recognised logs, making unauthorised certificate issuance immediately detectable."@en ;
rdfs:label "Certificate Transparency"@en ;
rdfs:subClassOf ngm:cryptographic-infrastructure ;
rdfs:subClassOf _:r4159 ;
rdfs:subClassOf _:r4160 ;
vc:bridgesTo ngm:distributed-systems ;
vc:bridgesTo ngm:supply-chain-security ;
vc:contrastsWith ngm:ocsp ;
vc:dependsOn ngm:domain-name-system ;
vc:enables ngm:audit-trail ;
vc:enables ngm:certificate-authority ;
vc:enables ngm:security-monitoring ;
vc:enables ngm:threat-intelligence ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:public-key-cryptography ;
vc:relatedTo ngm:tls-1-3 ;
vc:requires ngm:append-only-log ;
vc:requires ngm:cryptographic-infrastructure ;
vc:slug "certificate-transparency" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:ca-browser-forum ;
vc:standardizedBy ngm:ietf ;
vc:uses ngm:audit-log ;
vc:uses ngm:cryptographic-hash-function ;
vc:uses ngm:digital-signature ;
vc:uses ngm:merkle-tree ;
vc:uses ngm:tls ;
vc:uses ngm:x-509-certificate .
ngm:certificatemetadata a skos:Concept ;
rdfs:label "Certificatemetadata"@en .
ngm:certification a owl:Class ;
rdfs:comment "Certification is the formal process by which an independent authority attests that a product, system, process or person meets defined standards or requirements. It produces a verifiable credential or mark that signals conformance to interested parties and reduces the cost of establishing trust. Certification regimes are central to regulation, quality assurance and the safe interoperability of regulated goods and services."@en ;
rdfs:label "Certification"@en ;
rdfs:subClassOf ngm:compliance ;
rdfs:subClassOf _:r4161 ;
rdfs:subClassOf _:r4162 ;
vc:bridgesTo ngm:quality-assurance ;
vc:dependsOn ngm:quality-assurance ;
vc:enables ngm:regulatory-compliance ;
vc:enables ngm:trust ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:governance-framework ;
vc:isPartOf ngm:compliance ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:conformance ;
vc:relatedTo ngm:regulation ;
vc:requires ngm:audit ;
vc:requires ngm:conformance ;
vc:requires ngm:verification ;
vc:slug "certification" ;
vc:sourceDomain "governance" ;
vc:supports ngm:regulation ;
vc:supports ngm:safety-standard ;
vc:uses ngm:iso .
ngm:certification-criteria a skos:Concept ;
rdfs:label "Certification Criteria"@en .
ngm:certification-infrastructure a skos:Concept ;
rdfs:label "Certification Infrastructure"@en .
ngm:certification-issuance a skos:Concept ;
rdfs:label "Certification Issuance"@en .
ngm:certification-scheme a skos:Concept ;
rdfs:label "Certification Scheme"@en .
ngm:certified-defense a skos:Concept ;
rdfs:label "Certified Defense"@en .
ngm:certified-robustness a skos:Concept ;
rdfs:label "Certified Robustness"@en .
ngm:cfrp-laminate a skos:Concept ;
rdfs:label "Cfrp Laminate"@en .
ngm:cftc a owl:Class ;
rdfs:comment "The Commodity Futures Trading Commission, an independent agency of the United States government that regulates the derivatives markets, including futures, swaps and certain options."@en ;
rdfs:label "CFTC"@en ;
rdfs:subClassOf ngm:financial-regulation ;
rdfs:subClassOf _:r3742 ;
vc:bridgesTo ngm:securities-regulation ;
vc:enables ngm:consumer-protection ;
vc:enables ngm:financial-stability ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:financial-regulation ;
vc:slug "cftc" ;
vc:sourceDomain "governance" .
ngm:cftc-commodity-classification a skos:Concept ;
rdfs:label "Cftc Commodity Classification"@en .
ngm:cftc-v-ooki-dao a skos:Concept ;
rdfs:label "Cftc V Ooki DAO"@en .
ngm:cggmp21-protocol a skos:Concept ;
rdfs:label "Cggmp21 Protocol"@en .
ngm:cgi-vfx a skos:Concept ;
rdfs:label "Cgi Vfx"@en .
ngm:cgroups a skos:Concept ;
rdfs:label "Cgroups"@en .
ngm:cha-cha20-poly1305 a owl:Class ;
rdfs:comment "ChaCha20-Poly1305 is an authenticated encryption with associated data (AEAD) cipher suite combining the ChaCha20 stream cipher for encryption with the Poly1305 message authentication code, providing both confidentiality and integrity in a single construction. Designed by Daniel J. Bernstein, it offers performance advantages over AES-GCM on systems lacking hardware AES acceleration (particularly mobile and embedded devices) whilst providing equivalent or superior security margins. It is standardised in RFC 7539 (IETF) and RFC 8439, and is widely deployed in TLS 1.3, QUIC, WireGuard, SSH, and numerous cryptographic libraries as an alternative to AES-based suites."@en ;
rdfs:label "ChaCha20-Poly1305"@en ;
rdfs:subClassOf ngm:cryptographic-algorithm ;
vc:contrastsWith ngm:aes-gcm ;
vc:enables ngm:tls-1-3 ;
vc:enables ngm:tls-encryption ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:cryptographic-library ;
vc:slug "cha-cha20-poly1305" ;
vc:sourceDomain "security" ;
vc:uses ngm:cryptographic-keys ;
vc:uses ngm:nonce ;
vc:uses ngm:symmetric-encryption .
ngm:chain-abstraction a skos:Concept ;
rdfs:label "Chain Abstraction"@en .
ngm:chain-agnostic-standards-alliance a skos:Concept ;
rdfs:label "Chain Agnostic Standards Alliance"@en .
ngm:chain-of-custody a owl:Class ;
rdfs:comment "Chain of Custody is a documented, unbroken sequence of records that tracks the possession, handling, transfer, analysis, and disposition of physical or digital items from their point of origin to their ultimate use—most critically in legal proceedings and regulated industries. Each handoff event must be recorded with the identity of the parties involved, the time and location of transfer, and the state of the item, ensuring that the integrity and authenticity of the item can be demonstrated to any subsequent examiner. In digital contexts the concept extends to data provenance, AI training datasets, and blockchain-based asset transfer records."@en ;
rdfs:label "Chain of Custody"@en ;
rdfs:subClassOf ngm:provenance-tracking ;
rdfs:subClassOf _:r4172 ;
rdfs:subClassOf _:r4173 ;
rdfs:subClassOf _:r4174 ;
rdfs:subClassOf _:r4175 ;
rdfs:subClassOf _:r4176 ;
vc:bridgesTo ngm:blockchain-provenance ;
vc:bridgesTo ngm:data-lineage ;
vc:contrastsWith ngm:record-keeping ;
vc:dependsOn ngm:access-control ;
vc:dependsOn ngm:trusted-timestamping ;
vc:enables ngm:compliance-verification ;
vc:enables ngm:legal-evidence ;
vc:enables ngm:provenance-verification ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:custody ;
vc:hasPart ngm:tamper-detection ;
vc:implements ngm:non-repudiation ;
vc:isPartOf ngm:compliance-framework ;
vc:isPartOf ngm:evidence-collection ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:data-provenance ;
vc:relatedTo ngm:digital-evidence-chain-of-custody ;
vc:requires ngm:audit-logging ;
vc:requires ngm:cryptographic-hash-function ;
vc:requires ngm:identity-verification ;
vc:slug "chain-of-custody" ;
vc:sourceDomain "security" ;
vc:supports ngm:data-governance ;
vc:supports ngm:digital-forensics ;
vc:supports ngm:supply-chain-traceability ;
vc:uses ngm:audit-trail ;
vc:uses ngm:digital-signature ;
vc:uses ngm:verifiable-credential-vc .
ngm:chain-of-thought a owl:Class ;
rdfs:comment "Chain-of-Thought (CoT) prompting is a technique for eliciting explicit intermediate reasoning steps from autoregressive large language models before producing a final answer, substantially improving accuracy on arithmetic, symbolic, commonsense, and multi-hop reasoning tasks. The mechanism exploits the sequential token-generation process of transformer-based models: each generated reasoning token conditions all subsequent tokens, enabling multi-step deductions that single-pass prompting cannot reliably perform. CoT encompasses a family of variants — few-shot exemplar CoT, zero-shot CoT, self-consistency decoding, tree-of-thought search, and process reward modelling — collectively forming a foundational paradigm for inference-time compute scaling and complex reasoning in large language models."@en ;
rdfs:label "Chain of Thought"@en ;
rdfs:subClassOf ngm:in-context-learning ;
rdfs:subClassOf ngm:prompt-engineering ;
rdfs:subClassOf ngm:reasoning ;
rdfs:subClassOf _:r4177 ;
rdfs:subClassOf _:r4178 ;
rdfs:subClassOf _:r4179 ;
rdfs:subClassOf _:r4180 ;
rdfs:subClassOf _:r4181 ;
rdfs:subClassOf _:r4182 ;
rdfs:subClassOf _:r4183 ;
rdfs:subClassOf _:r4184 ;
rdfs:subClassOf _:r4185 ;
rdfs:subClassOf _:r4186 ;
rdfs:subClassOf _:r4187 ;
rdfs:subClassOf _:r4188 ;
vc:bridgesTo ngm:automated-reasoning ;
vc:bridgesTo ngm:neuro-symbolic-ai ;
vc:bridgesTo ngm:search-algorithms ;
vc:bridgesTo ngm:symbolic-ai ;
vc:contrastsWith ngm:direct-answer-prompting ;
vc:contrastsWith ngm:fine-tuning ;
vc:contrastsWith ngm:retrieval-augmented-generation ;
vc:contrastsWith ngm:standard-prompting ;
vc:dependsOn ngm:emergent-capabilities ;
vc:dependsOn ngm:model-scale ;
vc:dependsOn ngm:token-generation ;
vc:dependsOn ngm:transformer-architecture ;
vc:enables ngm:ai-agent ;
vc:enables ngm:commonsense-reasoning ;
vc:enables ngm:inference-time-compute-scaling ;
vc:enables ngm:mathematical-reasoning ;
vc:enables ngm:multi-hop-reasoning ;
vc:enables ngm:multi-step-reasoning ;
vc:enables ngm:planning ;
vc:enables ngm:reasoning ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:graph-of-thought ;
vc:hasPart ngm:least-to-most-prompting ;
vc:hasPart ngm:process-reward-model ;
vc:hasPart ngm:programme-of-thought ;
vc:hasPart ngm:react-prompting ;
vc:hasPart ngm:scratchpad-reasoning ;
vc:hasPart ngm:self-consistency ;
vc:hasPart ngm:tree-of-thoughts ;
vc:hasPart ngm:zero-shot-chain-of-thought ;
vc:implements ngm:inference-time-compute-scaling ;
vc:implements ngm:reasoning ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:ai-agent ;
vc:relatedTo ngm:automatic-prompt-optimisation ;
vc:relatedTo ngm:chain-of-thought ;
vc:relatedTo ngm:chain-of-thought-reasoning ;
vc:relatedTo ngm:neuro-symbolic-ai ;
vc:relatedTo ngm:planning ;
vc:relatedTo ngm:reinforcement-learning-from-human-feedback ;
vc:relatedTo ngm:scratchpad-reasoning ;
vc:requires ngm:autoregressive-model ;
vc:requires ngm:emergent-capabilities ;
vc:requires ngm:large-language-models ;
vc:requires ngm:model-scale ;
vc:requires ngm:prompt-engineering ;
vc:requires ngm:transformer ;
vc:slug "chain-of-thought" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:acl ;
vc:standardizedBy ngm:iclr ;
vc:standardizedBy ngm:neur-ips ;
vc:supports ngm:ai-safety ;
vc:supports ngm:explainable-ai ;
vc:supports ngm:language-model-alignment ;
vc:supports ngm:reinforcement-learning-from-human-feedback ;
vc:uses ngm:few-shot-learning ;
vc:uses ngm:few-shot-prompting ;
vc:uses ngm:foundation-model ;
vc:uses ngm:in-context-learning ;
vc:uses ngm:token-generation ;
vc:uses ngm:transformer .
ngm:chain-of-thought-prompting a owl:Class ;
rdfs:comment "Chain-of-thought (CoT) prompting is a prompt engineering technique that elicits intermediate reasoning steps from a large language model before it produces a final answer, substantially improving performance on multi-step arithmetic, commonsense reasoning, and symbolic manipulation tasks. By including exemplars that demonstrate step-by-step reasoning or by appending the instruction 'Let's think step by step' (zero-shot CoT), the technique leverages the model's autoregressive generation to decompose complex problems into tractable substeps. CoT prompting was formally characterised by Wei et al. (2022) and has become a foundational capability-elicitation method for frontier language models."@en ;
rdfs:label "Chain-of-Thought Prompting"@en ;
rdfs:subClassOf ngm:few-shot-prompting ;
rdfs:subClassOf ngm:in-context-learning ;
rdfs:subClassOf ngm:prompt-engineering ;
rdfs:subClassOf _:r4189 ;
rdfs:subClassOf _:r4190 ;
rdfs:subClassOf _:r4191 ;
rdfs:subClassOf _:r4192 ;
rdfs:subClassOf _:r4193 ;
rdfs:subClassOf _:r4194 ;
rdfs:subClassOf _:r4195 ;
rdfs:subClassOf _:r4196 ;
rdfs:subClassOf _:r4197 ;
rdfs:subClassOf _:r4198 ;
rdfs:subClassOf _:r4199 ;
vc:bridgesTo ngm:automated-reasoning ;
vc:bridgesTo ngm:explainable-ai ;
vc:bridgesTo ngm:neuro-symbolic-ai ;
vc:bridgesTo ngm:symbolic-ai ;
vc:contrastsWith ngm:direct-answer-prompting ;
vc:contrastsWith ngm:fine-tuning ;
vc:contrastsWith ngm:standard-prompting ;
vc:contrastsWith ngm:zero-shot-learning ;
vc:dependsOn ngm:emergent-capabilities ;
vc:dependsOn ngm:in-context-learning ;
vc:dependsOn ngm:large-language-models ;
vc:dependsOn ngm:model-scale ;
vc:enables ngm:ai-agent ;
vc:enables ngm:common-sense-reasoning ;
vc:enables ngm:commonsense-reasoning ;
vc:enables ngm:inference-time-compute-scaling ;
vc:enables ngm:mathematical-reasoning ;
vc:enables ngm:multi-hop-reasoning ;
vc:enables ngm:multi-step-reasoning ;
vc:enables ngm:planning ;
vc:enables ngm:symbolic-reasoning ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:automatic-chain-of-thought ;
vc:hasPart ngm:graph-of-thought ;
vc:hasPart ngm:least-to-most-prompting ;
vc:hasPart ngm:process-reward-model ;
vc:hasPart ngm:programme-of-thought ;
vc:hasPart ngm:react-prompting ;
vc:hasPart ngm:self-consistency ;
vc:hasPart ngm:tree-of-thoughts ;
vc:hasPart ngm:zero-shot-chain-of-thought ;
vc:hasPart ngm:zero-shot-prompting ;
vc:implements ngm:inference-time-compute-scaling ;
vc:implements ngm:reasoning ;
vc:implements ngm:step-by-step-decomposition ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:automatic-prompt-optimisation ;
vc:relatedTo ngm:chain-of-thought ;
vc:relatedTo ngm:chain-of-thought-reasoning ;
vc:relatedTo ngm:llm-agents ;
vc:relatedTo ngm:react-prompting ;
vc:relatedTo ngm:reasoning-engine ;
vc:relatedTo ngm:scratchpad-reasoning ;
vc:requires ngm:autoregressive-model ;
vc:requires ngm:emergent-capabilities ;
vc:requires ngm:foundation-model ;
vc:requires ngm:large-language-models ;
vc:requires ngm:transformer-architecture ;
vc:slug "chain-of-thought-prompting" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:acl-anthology ;
vc:standardizedBy ngm:iclr ;
vc:standardizedBy ngm:neur-ips ;
vc:supports ngm:ai-safety ;
vc:supports ngm:explainable-ai ;
vc:supports ngm:language-model-alignment ;
vc:supports ngm:reinforcement-learning-from-human-feedback ;
vc:uses ngm:autoregressive-model ;
vc:uses ngm:few-shot-prompting ;
vc:uses ngm:in-context-learning ;
vc:uses ngm:large-language-models ;
vc:uses ngm:reinforcement-learning-from-human-feedback ;
vc:uses ngm:token-generation ;
vc:uses ngm:transformer .
ngm:chain-of-thought-reasoning a owl:Class ;
rdfs:comment "Chain-of-Thought Reasoning is the capacity of large language models to generate coherent sequences of intermediate logical, mathematical, or factual steps as part of producing a final answer, treating each intermediate token as an active computational resource that reshapes residual stream activations for subsequent Transformer layers. Unlike the surface prompting technique that elicits it, CoT Reasoning denotes an emergent model capability — present above certain parameter-scale thresholds — whereby the model decomposes complex problems into verifiable sub-steps rather than collapsing directly to a final token. This capability underpins inference-time compute scaling strategies including self-consistency sampling, process reward models, step-level verifiers, and tree-of-thought search, and connects neural language modelling to classical AI paradigms of deductive planning and symbolic reasoning."@en ;
rdfs:label "Chain-of-Thought Reasoning"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:emergent-capabilities ;
rdfs:subClassOf ngm:inference-protocol ;
rdfs:subClassOf _:r4200 ;
rdfs:subClassOf _:r4201 ;
rdfs:subClassOf _:r4202 ;
rdfs:subClassOf _:r4203 ;
rdfs:subClassOf _:r4204 ;
rdfs:subClassOf _:r4205 ;
rdfs:subClassOf _:r4206 ;
rdfs:subClassOf _:r4207 ;
rdfs:subClassOf _:r4208 ;
rdfs:subClassOf _:r4209 ;
rdfs:subClassOf _:r4210 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:automated-theorem-proving ;
vc:bridgesTo ngm:formal-verification ;
vc:contrastsWith ngm:direct-answer-prompting ;
vc:contrastsWith ngm:retrieval-augmented-generation ;
vc:contrastsWith ngm:standard-prompting ;
vc:contrastsWith ngm:symbolic-ai ;
vc:contrastsWith ngm:system-1-thinking ;
vc:dependsOn ngm:attention-mechanism ;
vc:dependsOn ngm:backpropagation ;
vc:dependsOn ngm:model-scaling ;
vc:dependsOn ngm:residual-stream ;
vc:dependsOn ngm:transformer-architecture ;
vc:enables ngm:autonomous-agent ;
vc:enables ngm:code-generation ;
vc:enables ngm:educational-tutoring ;
vc:enables ngm:formal-verification ;
vc:enables ngm:inference-compute ;
vc:enables ngm:mathematical-reasoning ;
vc:enables ngm:multi-step-reasoning ;
vc:enables ngm:process-reward-model ;
vc:enables ngm:scientific-reasoning ;
vc:enables ngm:self-consistency ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:few-shot-exemplar ;
vc:hasPart ngm:process-reward-model ;
vc:hasPart ngm:reasoning-token ;
vc:hasPart ngm:scratchpad-reasoning ;
vc:hasPart ngm:self-consistency ;
vc:hasPart ngm:self-refinement ;
vc:hasPart ngm:step-level-verifier ;
vc:hasPart ngm:tree-of-thoughts ;
vc:implements ngm:few-shot-learning ;
vc:implements ngm:inference-time-scaling ;
vc:implements ngm:prompt-engineering ;
vc:implements ngm:reinforcement-learning ;
vc:implements ngm:zero-shot-prompting ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:aime ;
vc:relatedTo ngm:anthropic-extended-thinking ;
vc:relatedTo ngm:automated-theorem-proving ;
vc:relatedTo ngm:backpropagation ;
vc:relatedTo ngm:big-bench-hard ;
vc:relatedTo ngm:deepseek-r1 ;
vc:relatedTo ngm:formal-verification ;
vc:relatedTo ngm:google-gemini-thinking ;
vc:relatedTo ngm:gsm8k ;
vc:relatedTo ngm:humaneval ;
vc:relatedTo ngm:inference-compute ;
vc:relatedTo ngm:math-dataset ;
vc:relatedTo ngm:mechanistic-interpretability ;
vc:relatedTo ngm:multi-agent-systems ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:neural-turing-machine ;
vc:relatedTo ngm:openai-o1 ;
vc:relatedTo ngm:openai-o3 ;
vc:relatedTo ngm:reasoning ;
vc:requires ngm:attention-mechanism ;
vc:requires ngm:in-context-learning ;
vc:requires ngm:large-language-models ;
vc:requires ngm:model-scaling ;
vc:requires ngm:transformer ;
vc:requires ngm:transformer-architecture ;
vc:slug "chain-of-thought-reasoning" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:anthropic-research ;
vc:standardizedBy ngm:deepseek-research ;
vc:standardizedBy ngm:neurips-2022-proceedings ;
vc:standardizedBy ngm:openai-technical-reports ;
vc:supports ngm:ai-alignment ;
vc:supports ngm:automated-theorem-proving ;
vc:supports ngm:code-generation ;
vc:supports ngm:legal-reasoning ;
vc:supports ngm:mechanistic-interpretability ;
vc:supports ngm:medical-reasoning ;
vc:supports ngm:natural-language-processing ;
vc:uses ngm:direct-preference-optimisation ;
vc:uses ngm:few-shot-learning ;
vc:uses ngm:process-reward-model ;
vc:uses ngm:prompt-engineering ;
vc:uses ngm:reinforcement-learning ;
vc:uses ngm:reinforcement-learning-from-human-feedback ;
vc:uses ngm:zero-shot-prompting .
ngm:chain-reorganization a owl:Class ;
rdfs:comment "A Chain Reorganization (reorg) is the replacement of one or more blocks in the canonical blockchain by an alternative chain of equal or greater cumulative proof-of-work, occurring when competing miners produce valid chains of differing lengths and the network converges on the longest-chain rule to select the canonical history. Reorgs invalidate transactions confirmed only in the abandoned chain segment, enabling double-spend attacks when deliberately induced and posing settlement finality risks for exchanges and payment processors."@en ;
rdfs:label "Chain Reorganization"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf ngm:blockchain-entity ;
rdfs:subClassOf ngm:distributed-data-structure ;
rdfs:subClassOf _:r4163 ;
rdfs:subClassOf _:r4164 ;
rdfs:subClassOf _:r4165 ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:contrastsWith ngm:byzantine-fault-tolerance ;
vc:enables ngm:51-attack ;
vc:enables ngm:double-spending ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:consensus-mechanism ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:blockchain-scalability ;
vc:relatedTo ngm:finality ;
vc:relatedTo ngm:fork-choice-rule ;
vc:relatedTo ngm:selfish-mining ;
vc:relatedTo ngm:transaction-finality ;
vc:requires ngm:longest-chain-rule ;
vc:requires ngm:nakamoto-consensus ;
vc:requires ngm:proof-of-work ;
vc:slug "chain-reorganization" ;
vc:sourceDomain "blockchain" .
ngm:chain-replication a skos:Concept ;
rdfs:label "Chain Replication"@en .
ngm:chain-rule a skos:Concept ;
rdfs:label "Chain Rule"@en .
ngm:chain-rule-of-probability a skos:Concept ;
rdfs:label "Chain Rule Of Probability"@en .
ngm:chain-state a owl:Class ;
rdfs:comment "Chain State is the complete, current snapshot of all data held by a blockchain at a given block height, encompassing account balances, smart contract storage, unspent transaction outputs (UTXOs), and any other data structures committed to the ledger. It represents the authoritative, globally agreed world-state that full nodes maintain and update after each validated block, serving as the ground truth against which new transactions are validated."@en ;
rdfs:label "Chain State"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf ngm:blockchain-entity ;
rdfs:subClassOf ngm:distributed-data-structure ;
rdfs:subClassOf _:r4166 ;
rdfs:subClassOf _:r4167 ;
rdfs:subClassOf _:r4168 ;
rdfs:subClassOf _:r4169 ;
rdfs:subClassOf _:r4170 ;
rdfs:subClassOf _:r4171 ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:enables ngm:blockchain-scalability ;
vc:enables ngm:smart-contract ;
vc:enables ngm:smart-contracts ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:account-model ;
vc:hasPart ngm:merkle-root ;
vc:hasPart ngm:merkle-tree ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:blockchain ;
vc:relatedTo ngm:distributed-data-structure ;
vc:relatedTo ngm:distributed-ledger ;
vc:relatedTo ngm:distributed-ledger-technology ;
vc:requires ngm:blockchain-transaction ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:consensus-protocol ;
vc:slug "chain-state" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:block-header ;
vc:uses ngm:merkle-proof .
ngm:chain-weight a skos:Concept ;
rdfs:label "Chain Weight"@en .
ngm:chainalysis a owl:Class ;
rdfs:comment "Chainalysis is a commercial blockchain data analytics and intelligence platform founded in 2014 that provides investigative, compliance, and risk-management tools to government agencies, financial institutions, and cryptocurrency businesses for tracing, monitoring, and understanding blockchain transaction flows. It maintains a large proprietary database of attributed blockchain addresses — linking pseudonymous on-chain addresses to real-world entities through heuristic clustering, open-source intelligence, data partnerships, and legal processes — and offers products including Reactor (graph-based investigation tool), KYT (Know Your Transaction real-time compliance API), and Kryptos (market intelligence). Chainalysis is a primary contractor to agencies including the US Department of Justice, IRS Criminal Investigation, and OFAC for cryptocurrency-related law enforcement investigations, and publishes the annual Crypto Crime Report, the most widely cited source for cryptocurrency illicit finance statistics."@en ;
rdfs:label "Chainalysis"@en ;
rdfs:subClassOf ngm:blockchain-analytics ;
rdfs:subClassOf _:r4211 ;
rdfs:subClassOf _:r4212 ;
vc:bridgesTo ngm:financial-intelligence ;
vc:bridgesTo ngm:law-enforcement-technology ;
vc:bridgesTo ngm:regulatory-technology ;
vc:contrastsWith ngm:cryptocurrency-mixer ;
vc:contrastsWith ngm:privacy-coin ;
vc:contrastsWith ngm:zero-knowledge-proof ;
vc:enables ngm:aml-kyc-compliance ;
vc:enables ngm:cryptocurrency-investigation ;
vc:enables ngm:digital-forensics ;
vc:enables ngm:ransomware-attribution ;
vc:enables ngm:sanctions-compliance ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:address-attribution ;
vc:hasPart ngm:know-your-transaction ;
vc:hasPart ngm:reactor ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:blockchain-compliance ;
vc:relatedTo ngm:darknet-market ;
vc:relatedTo ngm:fatf-travel-rule ;
vc:relatedTo ngm:kyc ;
vc:relatedTo ngm:sanctions-screening ;
vc:requires ngm:blockchain-data ;
vc:requires ngm:transaction-monitoring ;
vc:slug "chainalysis" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:financial-crime-compliance ;
vc:supports ngm:vasp-regulation ;
vc:uses ngm:heuristic-clustering ;
vc:uses ngm:open-source-intelligence ;
vc:uses ngm:transaction-graph-analysis ;
vc:uses ngm:utxo-model .
ngm:chaincode a skos:Concept ;
rdfs:label "Chaincode"@en .
ngm:chaincode-container a skos:Concept ;
rdfs:label "Chaincode Container"@en .
ngm:chainlink a owl:Class ;
rdfs:comment "Chainlink is a decentralised oracle network and middleware layer that enables smart contracts on any blockchain to securely access off-chain data, computation, and cross-chain interoperability services. Founded in 2017 by Sergey Nazarov and Steve Ellis, it operates a network of independent node operators who retrieve, aggregate, and deliver external data — including price feeds, verifiable randomness, API responses, and event outcomes — to on-chain smart contracts, solving the oracle problem that prevents blockchains from natively interacting with real-world information. Its native token (LINK) provides cryptoeconomic incentives and collateral for node operators, whilst its Off-Chain Reporting protocol reduces on-chain costs through peer-to-peer consensus. Beyond data feeds, Chainlink has expanded into cross-chain messaging (CCIP), on-chain automation, and verifiable computation, positioning itself as general-purpose decentralised infrastructure for the entire blockchain ecosystem."@en ;
rdfs:label "Chainlink"@en ;
rdfs:subClassOf ngm:blockchain-oracle ;
rdfs:subClassOf _:r4214 ;
rdfs:subClassOf _:r4215 ;
rdfs:subClassOf _:r4216 ;
rdfs:subClassOf _:r4217 ;
rdfs:subClassOf _:r4218 ;
vc:bridgesTo ngm:enterprise-data-integration ;
vc:bridgesTo ngm:internet-of-things ;
vc:bridgesTo ngm:traditional-finance ;
vc:contrastsWith ngm:api3 ;
vc:contrastsWith ngm:band-protocol ;
vc:contrastsWith ngm:pyth-network ;
vc:dependsOn ngm:cryptoeconomics ;
vc:dependsOn ngm:smart-contract ;
vc:dependsOn ngm:staking ;
vc:enables ngm:cross-chain-interoperability ;
vc:enables ngm:enterprise-smart-contracts ;
vc:enables ngm:on-chain-automation ;
vc:enables ngm:verifiable-randomness ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:chainlink-automation ;
vc:hasPart ngm:chainlink-ccip ;
vc:hasPart ngm:chainlink-functions ;
vc:hasPart ngm:chainlink-oracles ;
vc:hasPart ngm:chainlink-vrf ;
vc:isPartOf ngm:decentralized-finance-de-fi ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:blockchain-interoperability ;
vc:relatedTo ngm:cross-chain-messaging ;
vc:relatedTo ngm:dao ;
vc:relatedTo ngm:decentralised-autonomous-organisation ;
vc:requires ngm:cryptographic-signature ;
vc:requires ngm:ethereum ;
vc:requires ngm:peer-to-peer-network ;
vc:slug "chainlink" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:de-fi-protocol ;
vc:supports ngm:non-fungible-token ;
vc:supports ngm:tokenization ;
vc:uses ngm:decentralized-computing ;
vc:uses ngm:off-chain-reporting ;
vc:uses ngm:threshold-signature-scheme .
ngm:chainlink-automation a skos:Concept ;
rdfs:label "Chainlink Automation"@en .
ngm:chainlink-ccip a owl:Class ;
rdfs:comment "Chainlink Cross-Chain Interoperability Protocol (CCIP) is a cross-chain messaging and token transfer standard developed by Chainlink Labs that enables smart contracts on different blockchain networks to securely send messages and transfer assets across chain boundaries, backed by a decentralised oracle network providing an independent risk management layer that monitors and validates cross-chain transactions. CCIP introduces a programmable token transfer abstraction allowing arbitrary data payloads to accompany token movements, enabling complex cross-chain application logic."@en ;
rdfs:label "Chainlink CCIP"@en ;
rdfs:subClassOf ngm:cross-chain-interoperability ;
rdfs:subClassOf _:r4213 ;
vc:bridgesTo ngm:swift-messaging ;
vc:bridgesTo ngm:traditional-finance ;
vc:contrastsWith ngm:cross-chain-bridge ;
vc:contrastsWith ngm:ibc ;
vc:contrastsWith ngm:layer-zero ;
vc:contrastsWith ngm:wormhole ;
vc:enables ngm:cross-chain-asset-transfer ;
vc:enables ngm:cross-chain-messaging ;
vc:enables ngm:tokenised-real-world-assets ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:blockchain-interoperability ;
vc:relatedTo ngm:de-fi ;
vc:relatedTo ngm:oracle-network ;
vc:relatedTo ngm:token-bridge ;
vc:requires ngm:evm-compatible-blockchain ;
vc:slug "chainlink-ccip" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:blockchain-oracle ;
vc:uses ngm:chainlink-oracles ;
vc:uses ngm:merkle-tree ;
vc:uses ngm:oracle-network ;
vc:uses ngm:smart-contract .
ngm:chainlink-functions a skos:Concept ;
rdfs:label "Chainlink Functions"@en .
ngm:chainlink-oracles a owl:Class ;
rdfs:comment "Chainlink Oracles are decentralised oracle networks operated by the Chainlink protocol that securely fetch, validate, and deliver off-chain data to on-chain smart contracts. They aggregate inputs from multiple independent node operators using cryptographic proofs and reputation systems to ensure tamper-resistant data feeds. Widely deployed for price feeds, verifiable randomness, and cross-chain communication, they form critical infrastructure for decentralised finance and Web3 applications."@en ;
rdfs:label "Chainlink Oracles"@en ;
rdfs:subClassOf ngm:oracle-network ;
vc:enables ngm:cross-chain-interoperability ;
vc:enables ngm:decentralized-finance-de-fi ;
vc:enables ngm:smart-contract ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:chainlink ;
vc:relatedTo ngm:chainlink-ccip ;
vc:relatedTo ngm:price-oracle ;
vc:slug "chainlink-oracles" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:cryptographic-proof ;
vc:uses ngm:verifiable-random-function .
ngm:chainlink-vrf a skos:Concept ;
rdfs:label "Chainlink Vrf"@en .
ngm:chainofthought a skos:Concept ;
rdfs:label "Chainofthought"@en .
ngm:challenge-period a skos:Concept ;
rdfs:label "Challenge Period"@en .
ngm:challenge-protocol a skos:Concept ;
rdfs:label "Challenge Protocol"@en .
ngm:challenge-response-protocol a owl:Class ;
rdfs:comment "A challenge-response protocol is an authentication protocol in which a verifier issues an unpredictable challenge and the claimant must return a response computed from a shared secret or private key, proving knowledge of the credential without transmitting it. Because each challenge is fresh, typically a random nonce, a valid response cannot be reused, defeating replay attacks. The pattern underpins many authentication mechanisms including CHAP, HMAC-based schemes, and public-key signature challenges."@en ;
rdfs:label "Challenge-Response Protocol"@en ;
rdfs:subClassOf ngm:authentication-protocol ;
rdfs:subClassOf _:r4219 ;
rdfs:subClassOf _:r4220 ;
vc:contrastsWith ngm:zero-knowledge-proof ;
vc:enables ngm:identity-verification ;
vc:enables ngm:mutual-authentication ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:cryptographic-protocol ;
vc:hasPart ngm:nonce ;
vc:implements ngm:authentication-protocol ;
vc:isPartOf ngm:authentication-mechanism ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:kerberos ;
vc:slug "challenge-response-protocol" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:authentication-standards ;
vc:supports ngm:authentication ;
vc:supports ngm:passwordless-authentication ;
vc:uses ngm:digital-signature ;
vc:uses ngm:encryption .
ngm:chancellor-of-the-exchequer a skos:Concept ;
rdfs:label "Chancellor Of The Exchequer"@en .
ngm:change-data-capture a owl:Class ;
rdfs:comment "Change data capture is a set of techniques for identifying and propagating row-level changes — inserts, updates, and deletes — from a source database to downstream systems in near real time. The most robust approach reads the database transaction log, turning committed mutations into an ordered stream of change events without burdening the source with polling. It underpins data replication, event streaming, and incremental data integration, keeping analytical stores, caches, and microservices consistent with operational systems."@en ;
rdfs:label "Change Data Capture"@en ;
rdfs:subClassOf ngm:data-integration ;
rdfs:subClassOf _:r4221 ;
vc:bridgesTo ngm:stream-processing ;
vc:dependsOn ngm:database ;
vc:enables ngm:data-replication ;
vc:enables ngm:event-sourcing ;
vc:enables ngm:stream-processing ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:event-streaming ;
vc:isPartOf ngm:data-integration ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-lake ;
vc:relatedTo ngm:data-warehouse ;
vc:slug "change-data-capture" ;
vc:sourceDomain "data" ;
vc:supports ngm:data-pipeline ;
vc:supports ngm:microservices ;
vc:uses ngm:apache-kafka ;
vc:uses ngm:database ;
vc:uses ngm:event-streaming .
ngm:change-detection a owl:Class ;
rdfs:label "Change Detection"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-processing ;
vc:slug "change-detection" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:change-management a owl:Class ;
rdfs:comment "Change Management is the structured discipline of guiding organisations, teams, and individuals through transitions in technology, process, or culture to achieve desired outcomes whilst minimising disruption and resistance. It encompasses planning, communication, training, stakeholder alignment, and feedback loops that collectively ensure adoption of new working methods. In technology contexts it also covers the formal control of modifications to systems and infrastructure to reduce risk. Effective change management is widely recognised as a critical determinant of whether digital transformation initiatives deliver their intended value."@en ;
rdfs:label "Change Management"@en ;
rdfs:subClassOf ngm:ai-governance-framework ;
rdfs:subClassOf _:r4222 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:bridgesTo ngm:infrastructure ;
vc:contrastsWith ngm:technical-debt ;
vc:enables ngm:ai-adoption ;
vc:enables ngm:continuous-improvement ;
vc:enables ngm:workforce-development ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:impact-assessment ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:digital-transformation ;
vc:relatedTo ngm:enterprise-architecture ;
vc:relatedTo ngm:human-factors ;
vc:relatedTo ngm:organisational-resilience ;
vc:relatedTo ngm:stakeholder-engagement ;
vc:slug "change-management" ;
vc:sourceDomain "governance" ;
vc:supports ngm:governance ;
vc:supports ngm:risk-management ;
vc:uses ngm:audit-trail ;
vc:uses ngm:compliance-monitoring ;
vc:uses ngm:risk-assessment .
ngm:change-of-variables a owl:Class ;
rdfs:comment "Change of variables is a technique for re-expressing an integral or a probability density in terms of a new set of variables related to the original ones by a differentiable, invertible transformation, with the Jacobian determinant of that transformation accounting for the resulting change in volume. Normalising flows apply this principle directly, composing a sequence of invertible transformations and tracking the accumulated Jacobian determinant to convert a simple base density into a complex target density while keeping the density exactly computable. It is a standard tool wherever a probability distribution must be transported through a differentiable map."@en ;
rdfs:label "Change of Variables"@en ;
rdfs:subClassOf ngm:calculus ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:slug "change-of-variables" ;
vc:sourceDomain "machine-learning" .
ngm:change-output a skos:Concept ;
rdfs:label "Change Output"@en .
ngm:change-point-detection a skos:Concept ;
rdfs:label "Change Point Detection"@en .
ngm:change-propagation a skos:Concept ;
rdfs:label "Change Propagation"@en .
ngm:channel a skos:Concept ;
rdfs:label "Channel"@en .
ngm:channel-capacity a skos:Concept ;
rdfs:label "Channel Capacity"@en .
ngm:channel-coding a owl:Class ;
rdfs:comment "Channel coding is the branch of coding theory that adds controlled redundancy to transmitted data so that errors introduced by a noisy communication channel can be detected and corrected at the receiver. Techniques include block codes, convolutional codes, turbo codes, and LDPC codes, with forward error correction being its dominant application. It matters because it lets systems approach the Shannon channel capacity, trading bandwidth for reliability in wireless, storage, and deep-space links."@en ;
rdfs:label "Channel Coding"@en ;
rdfs:subClassOf ngm:infra-network-and-comms ;
skos:broader ngm:infra-network-and-comms ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:forward-error-correction ;
vc:relatedTo ngm:physical-layer ;
vc:slug "channel-coding" ;
vc:sourceDomain "infrastructure" .
ngm:channel-coding-theory a skos:Concept ;
rdfs:label "Channel Coding Theory"@en .
ngm:channel-equalisation a skos:Concept ;
rdfs:label "Channel Equalisation"@en .
ngm:channel-factory a owl:Class ;
rdfs:comment "A channel factory is a Bitcoin Lightning Network scaling construction in which multiple participants share a single on-chain funding transaction (a multiparty channel) from which many off-chain payment channels can be opened, closed, and rebalanced without further on-chain transactions. By amortising one on-chain output across many channels, it reduces the on-chain footprint and cost of channel management. It matters because it improves the capital efficiency and scalability of layer-2 payments."@en ;
rdfs:label "Channel Factory"@en ;
rdfs:subClassOf ngm:lightning-network ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:lightning-network ;
vc:slug "channel-factory" ;
vc:sourceDomain "blockchain" .
ngm:channel-graph a skos:Concept ;
rdfs:label "Channel Graph"@en .
ngm:channel-isolation-pattern a skos:Concept ;
rdfs:label "Channel Isolation Pattern"@en .
ngm:channel-liquidity a skos:Concept ;
rdfs:label "Channel Liquidity"@en .
ngm:channels-and-private-data-collections a skos:Concept ;
rdfs:label "Channels And Private Data Collections"@en .
ngm:chaos-engineering a owl:Class ;
rdfs:comment "Chaos engineering is the discipline of experimenting on a software system by deliberately injecting controlled faults — such as instance termination, network latency, or resource exhaustion — in order to build confidence in the system's ability to withstand turbulent, real-world conditions. Practitioners form a hypothesis about steady-state behaviour, introduce a failure in production or production-like environments, and observe whether the system maintains its service level. Originating with Netflix's Chaos Monkey, the practice surfaces hidden dependencies and weaknesses before they cause outages, complementing observability and resilient design."@en ;
rdfs:label "Chaos Engineering"@en ;
rdfs:subClassOf ngm:site-reliability-engineering ;
rdfs:subClassOf _:r4223 ;
vc:bridgesTo ngm:disaster-recovery ;
vc:bridgesTo ngm:game-day ;
vc:contrastsWith ngm:traditional-qa-testing ;
vc:dependsOn ngm:monitoring ;
vc:dependsOn ngm:observability ;
vc:enables ngm:fault-tolerance ;
vc:enables ngm:high-availability ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:blast-radius-control ;
vc:hasPart ngm:fault-injection ;
vc:hasPart ngm:steady-state-hypothesis ;
vc:isPartOf ngm:resilience-engineering ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:reliability ;
vc:relatedTo ngm:service-level-objective ;
vc:requires ngm:incident-response ;
vc:slug "chaos-engineering" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:distributed-systems ;
vc:supports ngm:resilient-architecture ;
vc:uses ngm:chaos-monkey ;
vc:uses ngm:fault-injection .
ngm:chaos-monkey a skos:Concept ;
rdfs:label "Chaos Monkey"@en .
ngm:chaos-theory a owl:Class ;
rdfs:comment "Chaos theory is the study of deterministic dynamical systems whose long-term behaviour is highly sensitive to initial conditions, making them practically unpredictable despite obeying fixed deterministic rules. It characterises phenomena such as strange attractors, bifurcations, and the exponential divergence of nearby trajectories measured by Lyapunov exponents. It matters because it explains how simple nonlinear rules can produce complex, aperiodic behaviour, bridging deterministic dynamics and apparent randomness in physical, biological, and economic systems."@en ;
rdfs:label "Chaos Theory"@en ;
rdfs:subClassOf ngm:ai-research-area ;
skos:broader ngm:ai-research-area ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:emergence ;
vc:relatedTo ngm:self-organisation ;
vc:slug "chaos-theory" ;
vc:sourceDomain "data" .
ngm:chapman-kolmogorov-equation a owl:Class ;
rdfs:comment "The Chapman-Kolmogorov Equation is a fundamental identity in probability theory and stochastic processes that expresses the consistency condition for transition probabilities of a Markov chain or continuous stochastic process. It states that the probability of moving from state i to state j in n+m steps equals the sum over all intermediate states k of the product of the n-step and m-step transition probabilities. This equation is the cornerstone of Markov chain analysis and underlies key algorithms in machine learning, Bayesian inference, and diffusion modelling."@en ;
rdfs:label "Chapman-Kolmogorov Equation"@en ;
rdfs:subClassOf ngm:mathematical-identity ;
rdfs:subClassOf ngm:probability-theory ;
rdfs:subClassOf ngm:stochastic-process ;
rdfs:subClassOf _:r4224 ;
rdfs:subClassOf _:r4225 ;
rdfs:subClassOf _:r4226 ;
rdfs:subClassOf _:r4227 ;
vc:contrastsWith ngm:fractional-brownian-motion ;
vc:contrastsWith ngm:long-range-memory-process ;
vc:contrastsWith ngm:non-markovian-process ;
vc:contrastsWith ngm:path-dependent-process ;
vc:contrastsWith ngm:quantum-non-markovian-process ;
vc:dependsOn ngm:detailed-balance ;
vc:dependsOn ngm:ergodicity ;
vc:dependsOn ngm:markov-property ;
vc:dependsOn ngm:probability-measure ;
vc:dependsOn ngm:sigma-algebra ;
vc:enables ngm:bayesian-inference ;
vc:enables ngm:diffusion-model ;
vc:enables ngm:hidden-markov-model ;
vc:enables ngm:kalman-filter ;
vc:enables ngm:markov-chain-monte-carlo ;
vc:enables ngm:optimal-transport ;
vc:enables ngm:probabilistic-programming ;
vc:enables ngm:reinforcement-learning ;
vc:enables ngm:score-based-generative-model ;
vc:enables ngm:uncertainty-quantification ;
vc:enables ngm:value-function ;
vc:enables ngm:variational-inference ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:fokker-planck-equation ;
vc:hasPart ngm:kolmogorov-backward-equation ;
vc:hasPart ngm:markov-semigroup ;
vc:hasPart ngm:spectral-gap ;
vc:hasPart ngm:stationary-distribution ;
vc:hasPart ngm:transition-kernel ;
vc:hasPart ngm:transition-matrix ;
vc:implements ngm:bellman-equation ;
vc:implements ngm:fokker-planck-equation ;
vc:implements ngm:forward-backward-algorithm ;
vc:implements ngm:markov-chain ;
vc:implements ngm:stochastic-differential-equation ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:andrey-kolmogorov ;
vc:relatedTo ngm:bayesian-inference ;
vc:relatedTo ngm:bellman-equation ;
vc:relatedTo ngm:brownian-motion ;
vc:relatedTo ngm:diffusion-map ;
vc:relatedTo ngm:diffusion-model ;
vc:relatedTo ngm:distributional-reinforcement-learning ;
vc:relatedTo ngm:entropy-production ;
vc:relatedTo ngm:filterpy ;
vc:relatedTo ngm:financial-mathematics ;
vc:relatedTo ngm:flow-matching ;
vc:relatedTo ngm:fluctuation-theorem ;
vc:relatedTo ngm:fokker-planck-equation ;
vc:relatedTo ngm:gaussian-process ;
vc:relatedTo ngm:hamilton-jacobi-bellman-equation ;
vc:relatedTo ngm:hidden-markov-model ;
vc:relatedTo ngm:huggingface-diffusers ;
vc:relatedTo ngm:kalman-filter ;
vc:relatedTo ngm:kolmogorov-backward-equation ;
vc:relatedTo ngm:markov-chain-monte-carlo ;
vc:relatedTo ngm:markov-decision-process ;
vc:relatedTo ngm:martin-hairer ;
vc:relatedTo ngm:mixing-time ;
vc:relatedTo ngm:numpyro ;
vc:relatedTo ngm:optimal-transport ;
vc:relatedTo ngm:probabilistic-programming ;
vc:relatedTo ngm:pyemma ;
vc:relatedTo ngm:pymc ;
vc:relatedTo ngm:reinforcement-learning ;
vc:relatedTo ngm:rllib ;
vc:relatedTo ngm:schr-dinger-bridge ;
vc:relatedTo ngm:score-based-generative-model ;
vc:relatedTo ngm:stable-baselines3 ;
vc:relatedTo ngm:stan ;
vc:relatedTo ngm:state-estimation ;
vc:relatedTo ngm:stochastic-differential-equation ;
vc:relatedTo ngm:sydney-chapman ;
vc:relatedTo ngm:terry-lyons ;
vc:relatedTo ngm:time-series-analysis ;
vc:relatedTo ngm:wiener-process ;
vc:relatedTo ngm:william-feller ;
vc:requires ngm:conditional-probability ;
vc:requires ngm:linear-algebra ;
vc:requires ngm:markov-property ;
vc:requires ngm:measure-theory ;
vc:requires ngm:probability-theory ;
vc:requires ngm:sigma-algebra ;
vc:slug "chapman-kolmogorov-equation" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:feller-1949-semigroup-theory ;
vc:standardizedBy ngm:hille-yosida-theorem ;
vc:standardizedBy ngm:kolmogorov-axioms ;
vc:supports ngm:bayesian-inference ;
vc:supports ngm:climate-modelling ;
vc:supports ngm:epidemiology-modelling ;
vc:supports ngm:financial-mathematics ;
vc:supports ngm:markov-chain-monte-carlo ;
vc:supports ngm:molecular-dynamics ;
vc:supports ngm:probabilistic-programming ;
vc:supports ngm:sequential-decision-making ;
vc:supports ngm:state-estimation ;
vc:supports ngm:time-series-analysis ;
vc:uses ngm:integral-equation ;
vc:uses ngm:matrix-multiplication ;
vc:uses ngm:measure-theory ;
vc:uses ngm:probability-theory ;
vc:uses ngm:semigroup-theory .
ngm:chapter-detection a skos:Concept ;
rdfs:label "Chapter Detection"@en .
ngm:chapter-marker a skos:Concept ;
rdfs:label "Chapter Marker"@en .
ngm:character-ai a skos:Concept ;
rdfs:label "Character AI"@en .
ngm:character-animation a owl:Class ;
rdfs:comment "Character animation is the discipline of creating the illusion of life and intentional movement in digital or physical characters through the coordinated manipulation of skeletal rigs, blend shapes, and motion data across time, driven by principles derived from traditional film animation. It encompasses the full pipeline from rigging and skinning a character mesh to authoring, retargeting, and blending motion clips in real time, and extends to AI-driven procedural and physics-based approaches that generate plausible movement without manual keyframing. The field spans offline cinematic animation for film and games and real-time systems for interactive avatars, XR experiences, and virtual humans."@en ;
rdfs:label "Character Animation"@en ;
rdfs:subClassOf ngm:animation ;
rdfs:subClassOf _:r4228 ;
rdfs:subClassOf _:r4229 ;
rdfs:subClassOf _:r4230 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:bridgesTo ngm:robotics ;
vc:enables ngm:avatar-animation ;
vc:enables ngm:dynamic-character-animation ;
vc:enables ngm:facial-animation ;
vc:enables ngm:real-time-character-animation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:physics-based-animation ;
vc:hasPart ngm:procedural-animation ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:animation-retargeting ;
vc:relatedTo ngm:reinforcement-learning ;
vc:relatedTo ngm:secondary-motion ;
vc:requires ngm:animation-state-machine ;
vc:slug "character-animation" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:open-xr ;
vc:standardizedBy ngm:usd ;
vc:uses ngm:character-rigging ;
vc:uses ngm:forward-kinematics ;
vc:uses ngm:inverse-kinematics ;
vc:uses ngm:keyframe-animation ;
vc:uses ngm:motion-capture ;
vc:uses ngm:skeletal-animation .
ngm:character-attributes a skos:Concept ;
rdfs:label "Character Attributes"@en .
ngm:character-design a skos:Concept ;
rdfs:label "Character Design"@en .
ngm:character-encoding a skos:Concept ;
rdfs:label "Character Encoding"@en .
ngm:character-level-model a skos:Concept ;
rdfs:label "Character Level Model"@en .
ngm:character-level-tokenisation a skos:Concept ;
rdfs:label "Character Level Tokenisation"@en .
ngm:character-model a owl:Class ;
rdfs:comment "A 3D digital representation of a character consisting of a polygonal mesh, textures, and materials, designed with clean topology optimized for animation and real-time rendering, serving as the foundation for rigging, skinning, and character animation workflows."@en ;
rdfs:label "Character Model"@en ;
rdfs:subClassOf ngm:3-d-model ;
rdfs:subClassOf ngm:sc-content-and-assets ;
rdfs:subClassOf _:r4231 ;
rdfs:subClassOf _:r4232 ;
rdfs:subClassOf _:r4233 ;
rdfs:subClassOf _:r4234 ;
rdfs:subClassOf _:r4235 ;
rdfs:subClassOf _:r4236 ;
skos:broader ngm:sc-content-and-assets ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:digital-twin ;
vc:dependsOn ngm:level-of-detail ;
vc:enables ngm:character-animation ;
vc:enables ngm:game-characters ;
vc:enables ngm:motion-capture ;
vc:enables ngm:virtual-avatars ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:blend-shape ;
vc:hasPart ngm:skeletal-rig ;
vc:hasPart ngm:texture-mapping ;
vc:isPartOf ngm:3-d-model ;
vc:isPartOf ngm:asset-pipeline ;
vc:qualityScore "0.68"^^xsd:float ;
vc:requires ngm:3-d-modeling-software ;
vc:requires ngm:texture-mapping ;
vc:requires ngm:topology-design ;
vc:requires ngm:uv-unwrapping ;
vc:slug "character-model" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:metaverse ;
vc:supports ngm:real-time-rendering ;
vc:supports ngm:virtual-reality ;
vc:uses ngm:normal-map ;
vc:uses ngm:physically-based-rendering ;
vc:uses ngm:skinning .
ngm:character-relationship-graph a owl:Class ;
rdfs:comment "A network data structure representing narrative characters as vertices and their interactions or relationships as edges, used to model social dynamics, drive procedural story generation, and analyze narrative structure through graph theory and social network analysis."@en ;
rdfs:label "Character Relationship Graph"@en ;
rdfs:subClassOf ngm:sc-content-and-assets ;
rdfs:subClassOf ngm:social-network-graph ;
rdfs:subClassOf _:r4237 ;
skos:broader ngm:sc-content-and-assets ;
vc:bridgesTo ngm:telecollaboration ;
vc:enables ngm:character-ai ;
vc:enables ngm:narrative-generation ;
vc:enables ngm:story-analysis ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:character-attributes ;
vc:requires ngm:graph-database ;
vc:requires ngm:relationship-modeling ;
vc:slug "character-relationship-graph" ;
vc:sourceDomain "spatial-computing" .
ngm:character-rigging a owl:Class ;
rdfs:comment "The process of creating a hierarchical skeleton of interconnected bones and joints within a 3D character model, along with control systems and deformation rules, enabling animators to manipulate the mesh through inverse kinematics and forward kinematics for realistic movement."@en ;
rdfs:label "Character Rigging"@en ;
rdfs:subClassOf ngm:animation-technique ;
rdfs:subClassOf ngm:sc-content-and-assets ;
rdfs:subClassOf _:r4238 ;
rdfs:subClassOf _:r4239 ;
skos:broader ngm:sc-content-and-assets ;
vc:bridgesTo ngm:computer-vision ;
vc:enables ngm:character-animation ;
vc:enables ngm:motion-capture ;
vc:enables ngm:skeletal-animation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:character-model ;
vc:requires ngm:skinning ;
vc:requires ngm:weight-painting ;
vc:slug "character-rigging" ;
vc:sourceDomain "spatial-computing" .
ngm:character-segmentation a skos:Concept ;
rdfs:label "Character Segmentation"@en .
ngm:characterisation a skos:Concept ;
rdfs:label "Characterisation"@en .
ngm:characterisation-factors a skos:Concept ;
rdfs:label "Characterisation Factors"@en .
ngm:characteristic-function a skos:Concept ;
rdfs:label "Characteristic Function"@en .
ngm:charitable-incorporated-organisation a skos:Concept ;
rdfs:label "Charitable Incorporated Organisation"@en .
ngm:chart a skos:Concept ;
rdfs:label "Chart"@en .
ngm:charuco-board a skos:Concept ;
rdfs:label "Charuco Board"@en .
ngm:chassis-frame a skos:Concept ;
rdfs:label "Chassis Frame"@en .
ngm:chatbot a owl:Class ;
rdfs:comment "A software application designed to simulate conversation with human users, processing natural-language input through rule-based, retrieval-based, or generative mechanisms to produce contextually appropriate responses. Modern chatbots are predominantly built on large language models, enabling open-domain dialogue, multi-turn context tracking, and task execution across text and voice interfaces. They serve as the primary user-facing layer of conversational AI systems, integrating intent recognition, dialogue management, and response generation into a coherent interaction loop. Deployment contexts range from narrow-domain customer support and virtual assistants to general-purpose AI agents capable of reasoning, tool use, and multi-step problem solving."@en ;
rdfs:label "Chatbot"@en ;
rdfs:subClassOf ngm:conversational-ai ;
rdfs:subClassOf ngm:dialogue-system ;
rdfs:subClassOf _:r4240 ;
rdfs:subClassOf _:r4241 ;
rdfs:subClassOf _:r4242 ;
rdfs:subClassOf _:r4243 ;
rdfs:subClassOf _:r4244 ;
rdfs:subClassOf _:r4245 ;
rdfs:subClassOf _:r4246 ;
rdfs:subClassOf _:r4247 ;
rdfs:subClassOf _:r4248 ;
rdfs:subClassOf _:r4249 ;
rdfs:subClassOf _:r4250 ;
vc:bridgesTo ngm:api-gateway ;
vc:bridgesTo ngm:autonomous-robot ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:robotic-process-automation ;
vc:bridgesTo ngm:voice-interaction ;
vc:contrastsWith ngm:ai-agent ;
vc:contrastsWith ngm:batch-processing ;
vc:contrastsWith ngm:rule-based-systems ;
vc:dependsOn ngm:context-window ;
vc:dependsOn ngm:embedding-model ;
vc:dependsOn ngm:knowledge-base ;
vc:dependsOn ngm:language-model ;
vc:enables ngm:customer-service-automation ;
vc:enables ngm:multi-turn-dialogue ;
vc:enables ngm:personalisation ;
vc:enables ngm:question-answering ;
vc:enables ngm:virtual-assistant ;
vc:enables ngm:voice-interaction ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:context-window ;
vc:hasPart ngm:dialogue-management ;
vc:hasPart ngm:intent-recognition ;
vc:hasPart ngm:named-entity-recognition ;
vc:hasPart ngm:natural-language-understanding ;
vc:hasPart ngm:response-generation ;
vc:hasPart ngm:sentiment-analysis ;
vc:hasPart ngm:session-management ;
vc:implements ngm:conversational-ai ;
vc:implements ngm:natural-language-understanding ;
vc:qualityScore "0.73"^^xsd:float ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:information-extraction ;
vc:relatedTo ngm:machine-translation ;
vc:relatedTo ngm:named-entity-recognition ;
vc:relatedTo ngm:robotic-process-automation ;
vc:relatedTo ngm:semantic-search ;
vc:relatedTo ngm:sentiment-analysis ;
vc:relatedTo ngm:text-classification ;
vc:requires ngm:dialogue-management ;
vc:requires ngm:intent-recognition ;
vc:requires ngm:language-model ;
vc:requires ngm:natural-language-processing ;
vc:slug "chatbot" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:multi-turn-dialogue ;
vc:supports ngm:personalisation ;
vc:supports ngm:sentiment-analysis ;
vc:uses ngm:embedding-model ;
vc:uses ngm:large-language-models ;
vc:uses ngm:prompt-engineering ;
vc:uses ngm:reinforcement-learning-from-human-feedback ;
vc:uses ngm:retrieval-augmented-generation ;
vc:uses ngm:speech-recognition ;
vc:uses ngm:transformer-architecture .
ngm:chatbot-arena a skos:Concept ;
rdfs:label "Chatbot Arena"@en .
ngm:chatbots a owl:Class ;
rdfs:comment "Software systems designed to simulate conversation with human users through text or voice interfaces, spanning an architectural spectrum from rule-based pattern-matching programs (ELIZA, 1966; ALICE/AIML, 1995) through retrieval-based and intent-classification pipelines to modern"@en ;
rdfs:label "Chatbots"@en ;
rdfs:subClassOf ngm:ai-agent-system ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:conversational-ai ;
rdfs:subClassOf ngm:dialogue-system ;
rdfs:subClassOf ngm:dialogue-systems ;
rdfs:subClassOf ngm:human-computer-interaction ;
rdfs:subClassOf ngm:natural-language-processing ;
rdfs:subClassOf _:r4251 ;
rdfs:subClassOf _:r4252 ;
rdfs:subClassOf _:r4253 ;
rdfs:subClassOf _:r4254 ;
rdfs:subClassOf _:r4255 ;
rdfs:subClassOf _:r4256 ;
rdfs:subClassOf _:r4257 ;
rdfs:subClassOf _:r4258 ;
rdfs:subClassOf _:r4259 ;
rdfs:subClassOf _:r4260 ;
rdfs:subClassOf _:r4261 ;
skos:broader ngm:ai-application ;
vc:contrastsWith ngm:expert-systems ;
vc:contrastsWith ngm:form-based-interfaces ;
vc:contrastsWith ngm:rule-based-systems ;
vc:contrastsWith ngm:search-engines ;
vc:dependsOn ngm:embedding-models ;
vc:dependsOn ngm:large-language-models ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:natural-language-processing ;
vc:dependsOn ngm:vector-databases ;
vc:enables ngm:customer-service-automation ;
vc:enables ngm:knowledge-retrieval ;
vc:enables ngm:lead-generation ;
vc:enables ngm:task-automation ;
vc:enables ngm:virtual-assistant ;
vc:enables ngm:voice-interfaces ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:context-window ;
vc:hasPart ngm:dialogue-state-tracking ;
vc:hasPart ngm:intent-recognition ;
vc:hasPart ngm:natural-language-generation ;
vc:hasPart ngm:persona ;
vc:hasPart ngm:response-selection ;
vc:hasPart ngm:slot-filling ;
vc:implements ngm:intent-classification ;
vc:implements ngm:model-context-protocol ;
vc:implements ngm:multi-turn-dialogue ;
vc:implements ngm:retrieval-augmented-generation ;
vc:implements ngm:slot-filling ;
vc:implements ngm:transformer-architecture ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:claude ;
vc:relatedTo ngm:gemini-multimodal-language-model ;
vc:relatedTo ngm:instruction-following-conversational-ai-system ;
vc:relatedTo ngm:multi-turn-dialogue ;
vc:relatedTo ngm:persona ;
vc:relatedTo ngm:retrieval-augmented-generation ;
vc:relatedTo ngm:voice-interfaces ;
vc:requires ngm:api-integration ;
vc:requires ngm:inference-engine ;
vc:requires ngm:knowledge-base ;
vc:requires ngm:natural-language-understanding ;
vc:requires ngm:training-data ;
vc:slug "chatbots" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:iso ;
vc:standardizedBy ngm:model-context-protocol ;
vc:standardizedBy ngm:w3-c ;
vc:supports ngm:customer-service-automation ;
vc:supports ngm:e-commerce ;
vc:supports ngm:education-technology ;
vc:supports ngm:enterprise-search ;
vc:supports ngm:healthcare-ai ;
vc:uses ngm:bertscore ;
vc:uses ngm:bleu-score ;
vc:uses ngm:constitutional-ai-training-methodology ;
vc:uses ngm:human-evaluation ;
vc:uses ngm:reinforcement-learning-from-human-feedback .
ngm:chatgpt a skos:Concept ;
rdfs:label "Chatgpt"@en .
ngm:chaumian-ecash a owl:Class ;
rdfs:comment "Chaumian ecash is a form of digital cash, invented by David Chaum, that uses blind signatures to issue bearer tokens redeemable at a central mint while preserving payer privacy. The mint signs blinded token requests so it cannot link issued tokens to the users who later spend them, providing strong untraceability with offline-style bearer transfer. It matters as the cryptographic foundation for privacy-preserving custodial payment systems, revived in Bitcoin through mints such as Cashu and Fedimint."@en ;
rdfs:label "Chaumian Ecash"@en ;
rdfs:subClassOf ngm:cryptographic-protocol ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:cashu ;
vc:relatedTo ngm:fedimint ;
vc:slug "chaumian-ecash" ;
vc:sourceDomain "blockchain" .
ngm:cheatcodes a skos:Concept ;
rdfs:label "Cheatcodes"@en .
ngm:checkbox-compliance a skos:Concept ;
rdfs:label "Checkbox Compliance"@en .
ngm:checkerboard-pattern a owl:Class ;
rdfs:comment "A checkerboard pattern is a planar grid of alternating black and white squares used as a calibration target in computer vision. Its regularly spaced corners are easy to detect with sub-pixel accuracy and have precisely known relative positions, providing reliable correspondences for estimating camera parameters. The checkerboard is the most common target for intrinsic calibration, distortion correction, and stereo rig alignment."@en ;
rdfs:label "Checkerboard Pattern"@en ;
rdfs:subClassOf ngm:optical-calibration-target ;
rdfs:subClassOf _:r4262 ;
vc:bridgesTo ngm:spatial-computing ;
vc:contrastsWith ngm:fiducial-marker ;
vc:enables ngm:camera-calibration ;
vc:enables ngm:camera-intrinsics ;
vc:enables ngm:lens-distortion-correction ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:feature-detection ;
vc:isPartOf ngm:optical-calibration-target ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:fiducial-marker ;
vc:relatedTo ngm:homography ;
vc:slug "checkerboard-pattern" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:camera-calibration ;
vc:supports ngm:pose-estimation ;
vc:uses ngm:computer-vision ;
vc:uses ngm:feature-detection .
ngm:checkpoint-averaging a skos:Concept ;
rdfs:label "Checkpoint Averaging"@en .
ngm:checkpoint-frequency-policy a skos:Concept ;
rdfs:label "Checkpoint Frequency Policy"@en .
ngm:checkpoint-index a skos:Concept ;
rdfs:label "Checkpoint Index"@en .
ngm:checkpoint-mapping a skos:Concept ;
rdfs:label "Checkpoint Mapping"@en .
ngm:checkpoint-model a skos:Concept ;
rdfs:label "Checkpoint Model"@en .
ngm:checkpoint-recovery a owl:Class ;
rdfs:comment "Checkpoint recovery is the process of resuming a computation, most commonly a machine learning training run, from a previously saved checkpoint after an interruption such as a hardware failure, pre-emption or planned restart. It requires that checkpoints capture sufficient state, including model parameters, optimiser state and progress markers, to continue correctly without repeating completed work. Reliable checkpoint recovery is essential for large-scale and decentralised training where node failures are expected rather than exceptional."@en ;
rdfs:label "Checkpoint Recovery"@en ;
rdfs:subClassOf ngm:model-checkpoint ;
rdfs:subClassOf _:r4263 ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.65"^^xsd:float ;
vc:requires ngm:model-checkpoint ;
vc:slug "checkpoint-recovery" ;
vc:sourceDomain "ai" .
ngm:checkpoint-resharding a skos:Concept ;
rdfs:label "Checkpoint Resharding"@en .
ngm:checkpointing a owl:Class ;
rdfs:comment "A fault-tolerance technique in which a system periodically captures a consistent snapshot of its execution state — memory, variables, message queues, or conversation context — and persists it to durable storage, so that after a crash, pre-emption, or migration the computation can resume from the most recent checkpoint rather than restarting from the beginning; foundational to long-running distributed workloads, ML training, and agent runtimes."@en ;
rdfs:label "Checkpointing"@en ;
rdfs:subClassOf ngm:fault-tolerance ;
vc:enables ngm:reliability ;
vc:enables ngm:resilience ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:agent-runtime ;
vc:relatedTo ngm:distributed-systems ;
vc:slug "checkpointing" ;
vc:sourceDomain "distributed-systems" ;
vc:uses ngm:snapshot ;
vc:uses ngm:state-management .
ngm:checkpointloader a skos:Concept ;
rdfs:label "Checkpointloader"@en .
ngm:checkpointrecovery a skos:Concept ;
rdfs:label "Checkpointrecovery"@en .
ngm:checkpoints a owl:Class ;
rdfs:comment "Checkpoints are serialised snapshots of a machine-learning model's complete trainable state — weight tensors, optimiser moment accumulators, learning-rate schedules, gradient scalers, random-number-generator seeds, and epoch/step counters — persisted to durable storage at regular intervals during..."@en ;
rdfs:label "Checkpoints"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:fault-tolerance ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf ngm:model-serialisation ;
rdfs:subClassOf ngm:model-versioning ;
rdfs:subClassOf ngm:training ;
rdfs:subClassOf _:r4264 ;
rdfs:subClassOf _:r4265 ;
rdfs:subClassOf _:r4266 ;
rdfs:subClassOf _:r4267 ;
rdfs:subClassOf _:r4268 ;
rdfs:subClassOf _:r4269 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:ai-infrastructure ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:federated-learning ;
vc:bridgesTo ngm:model-versioning ;
vc:bridgesTo ngm:quantum-computation-paradigm ;
vc:bridgesTo ngm:reinforcement-learning ;
vc:contrastsWith ngm:inference ;
vc:contrastsWith ngm:knowledge-distillation ;
vc:contrastsWith ngm:on-the-fly-training ;
vc:contrastsWith ngm:stateless-execution ;
vc:dependsOn ngm:distributed-training ;
vc:dependsOn ngm:fault-tolerance ;
vc:dependsOn ngm:file-system ;
vc:dependsOn ngm:model-registry ;
vc:dependsOn ngm:optimiser ;
vc:dependsOn ngm:serialisation ;
vc:enables ngm:checkpoint-averaging ;
vc:enables ngm:distributed-training ;
vc:enables ngm:empirical-experimental-design ;
vc:enables ngm:fine-tuning ;
vc:enables ngm:model-serving ;
vc:enables ngm:model-versioning ;
vc:enables ngm:training-resumption ;
vc:enables ngm:transfer-learning ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:checkpoint-index ;
vc:hasPart ngm:ema-shadow-weights ;
vc:hasPart ngm:learning-rate-schedule ;
vc:hasPart ngm:optimiser-state ;
vc:hasPart ngm:rng-state ;
vc:hasPart ngm:shard-metadata ;
vc:hasPart ngm:step-counter ;
vc:hasPart ngm:weight-tensor ;
vc:implements ngm:deep-speed ;
vc:implements ngm:fsdp ;
vc:implements ngm:hugging-face-hub ;
vc:implements ngm:mlflow ;
vc:implements ngm:py-torch ;
vc:implements ngm:safetensors ;
vc:implements ngm:tensor-flow ;
vc:implements ngm:weights-and-biases ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:dvc ;
vc:relatedTo ngm:empirical-experimental-design-tracking ;
vc:relatedTo ngm:hugging-face-hub ;
vc:relatedTo ngm:lo-ra ;
vc:relatedTo ngm:mlflow ;
vc:relatedTo ngm:model-registry ;
vc:relatedTo ngm:onnx ;
vc:relatedTo ngm:peft ;
vc:relatedTo ngm:py-torch ;
vc:relatedTo ngm:quantisation ;
vc:relatedTo ngm:weights-and-biases ;
vc:requires ngm:checkpoint-frequency-policy ;
vc:requires ngm:file-system ;
vc:requires ngm:model-architecture ;
vc:requires ngm:persistent-storage ;
vc:requires ngm:serialisation-format ;
vc:requires ngm:training-loop ;
vc:slug "checkpoints" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:deep-speed ;
vc:standardizedBy ngm:hugging-face ;
vc:standardizedBy ngm:linux-foundation ;
vc:standardizedBy ngm:py-torch-foundation ;
vc:standardizedBy ngm:pytorch-foundation ;
vc:standardizedBy ngm:tensor-flow ;
vc:supports ngm:diffusion-models ;
vc:supports ngm:fine-tuning ;
vc:supports ngm:large-language-models ;
vc:supports ngm:large-scale-pretrained-foundation-model ;
vc:supports ngm:mlops ;
vc:supports ngm:model-serving ;
vc:supports ngm:reinforcement-learning ;
vc:supports ngm:transfer-learning ;
vc:uses ngm:dvc ;
vc:uses ngm:fsdp ;
vc:uses ngm:gguf-format ;
vc:uses ngm:onnx ;
vc:uses ngm:pickle ;
vc:uses ngm:safetensors ;
vc:uses ngm:savedmodel ;
vc:uses ngm:ze-ro ;
vc:uses ngm:zero .
ngm:checks-and-balances a skos:Concept ;
rdfs:label "Checks And Balances"@en .
ngm:checksum a skos:Concept ;
rdfs:label "Checksum"@en .
ngm:checksum-verification a skos:Concept ;
rdfs:label "Checksum Verification"@en .
ngm:checksums a skos:Concept ;
rdfs:label "Checksums"@en .
ngm:chef a skos:Concept ;
rdfs:label "Chef"@en .
ngm:chemical-logistics a skos:Concept ;
rdfs:label "Chemical Logistics"@en .
ngm:chemical-mechanical-planarisation a skos:Concept ;
rdfs:label "Chemical Mechanical Planarisation"@en .
ngm:chemical-process-control a skos:Concept ;
rdfs:label "Chemical Process Control"@en .
ngm:chemical-propulsion a owl:Class ;
rdfs:label "Chemical Propulsion"@en ;
rdfs:subClassOf ngm:spacecraft-propulsion ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:spacecraft-propulsion ;
vc:slug "chemical-propulsion" ;
vc:sourceDomain "space-science-and-systems" .
ngm:chemical-vapour-deposition a skos:Concept ;
rdfs:label "Chemical Vapour Deposition"@en .
ngm:cheminformatics a skos:Concept ;
rdfs:label "Cheminformatics"@en .
ngm:chemistry a skos:Concept ;
rdfs:label "Chemistry"@en .
ngm:chessboard-pattern a skos:Concept ;
rdfs:label "Chessboard Pattern"@en .
ngm:child-labour-prevention a skos:Concept ;
rdfs:label "Child Labour Prevention"@en .
ngm:child-online-protection a skos:Concept ;
rdfs:label "Child Online Protection"@en .
ngm:child-pays-for-parent a skos:Concept ;
rdfs:label "Child Pays For Parent"@en .
ngm:child-protection-online a skos:Concept ;
rdfs:label "Child Protection Online"@en .
ngm:child-safety-harms a skos:Concept ;
rdfs:label "Child Safety Harms"@en .
ngm:child-safety-online a skos:Concept ;
rdfs:label "Child Safety Online"@en .
ngm:china a owl:Class ;
rdfs:comment "A country in East Asia and the world's most populous nation for much of recent history, with a large economy and significant influence in technology, manufacturing, and digital currency policy."@en ;
rdfs:label "China"@en ;
rdfs:subClassOf ngm:infra-legal-and-regulatory ;
rdfs:subClassOf ngm:owl-thing ;
skos:broader ngm:infra-legal-and-regulatory ;
vc:bridgesTo ngm:singapore ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:relatedTo ngm:central-bank-digital-currency-cbdc ;
vc:relatedTo ngm:digital-currency ;
vc:relatedTo ngm:regulatory-framework ;
vc:slug "china" ;
vc:sourceDomain "governance" .
ngm:china-ai-regulation a owl:Class ;
rdfs:comment "The set of laws, guidelines, and administrative measures implemented by the Chinese government to govern the development, deployment, and use of artificial intelligence technologies."@en ;
rdfs:label "China AI Regulation"@en ;
rdfs:subClassOf ngm:regulatory-framework ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-policy ;
vc:relatedTo ngm:china ;
vc:relatedTo ngm:regulatory-framework ;
vc:slug "china-ai-regulation" ;
vc:sourceDomain "governance" .
ngm:china-deep-synthesis-provisions a skos:Concept ;
rdfs:label "China Deep Synthesis Provisions"@en .
ngm:china-tech-export-controls a owl:Class ;
rdfs:comment "Governmental policies and regulatory actions in China that restrict the transfer of technology, talent, or intellectual property to foreign entities or jurisdictions."@en ;
rdfs:label "China Tech Export Controls"@en ;
rdfs:subClassOf ngm:regulatory-framework ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:china ;
vc:relatedTo ngm:regulatory-framework ;
vc:relatedTo ngm:tech-policy ;
vc:slug "china-tech-export-controls" ;
vc:sourceDomain "governance" .
ngm:chinchilla-scaling a skos:Concept ;
rdfs:label "Chinchilla Scaling"@en .
ngm:chinese-ai-ecosystem a owl:Class ;
rdfs:comment "The interconnected network of Chinese technology companies, government policies, hardware suppliers, and research institutions that collectively drive the development and deployment of artificial intelligence within China."@en ;
rdfs:label "Chinese AI Ecosystem"@en ;
rdfs:subClassOf ngm:ai-ecosystem ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-ecosystem ;
vc:relatedTo ngm:ai-policy ;
vc:relatedTo ngm:sovereign-ai ;
vc:slug "chinese-ai-ecosystem" ;
vc:sourceDomain "economics" .
ngm:chinese-seal-art-ai-classification-pipeline a owl:Class ;
rdfs:comment "Seals, in this knowledge graph context, refers to a practical AI pipeline experiment using traditional Chinese seal art (海豹-style stamps) as a five-shot image classification and translation task. The experiment demonstrates multimodal AI capabilities: image analysis via OpenAI vision APIs, English description generation, Chinese translation, and appropriateness ranking, subsequently serialised to JSON for potential NFT metadata enrichment."@en ;
rdfs:label "Chinese Seal Art AI Classification Pipeline"@en ;
rdfs:subClassOf ngm:software-engineering ;
vc:enables ngm:digital-asset ;
vc:enables ngm:nft ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.7"^^xsd:float ;
vc:relatedTo ngm:computer-vision ;
vc:slug "chinese-seal-art-ai-classification-pipeline" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:generative-ai ;
vc:uses ngm:image-generation ;
vc:uses ngm:multimodal-ai-architecture-ai .
ngm:chip a skos:Concept ;
rdfs:label "Chip"@en .
ngm:chiplet-architecture a skos:Concept ;
rdfs:label "Chiplet Architecture"@en .
ngm:chirp-spread-spectrum a skos:Concept ;
rdfs:label "Chirp Spread Spectrum"@en .
ngm:chisel a skos:Concept ;
rdfs:label "Chisel"@en .
ngm:chit-chat-systems a skos:Concept ;
rdfs:label "Chit Chat Systems"@en .
ngm:chivo-wallet a owl:Class ;
rdfs:comment "Chivo Wallet is the state-sponsored digital wallet application launched by the government of El Salvador in 2021 to support the country's adoption of bitcoin as legal tender. It allows citizens to hold and transact in both bitcoin and US dollars, including a signup bonus paid in bitcoin, with zero transaction fees within the network. It has been central to El Salvador's Bitcoin Law rollout and is frequently cited in analyses of state-level cryptocurrency adoption."@en ;
rdfs:label "Chivo Wallet"@en ;
rdfs:subClassOf ngm:digital-wallet ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:digital-wallet ;
vc:qualityScore "0.55"^^xsd:float ;
vc:relatedTo ngm:bitcoin ;
vc:slug "chivo-wallet" ;
vc:sourceDomain "blockchain" .
ngm:choice-architecture a skos:Concept ;
rdfs:label "Choice Architecture"@en .
ngm:choice-model a skos:Concept ;
rdfs:label "Choice Model"@en .
ngm:cholesky-decomposition a skos:Concept ;
rdfs:label "Cholesky Decomposition"@en .
ngm:chord-protocol a skos:Concept ;
rdfs:label "Chord Protocol"@en .
ngm:chrf a skos:Concept ;
rdfs:label "Chrf"@en .
ngm:chroma a skos:Concept ;
rdfs:label "Chroma"@en .
ngm:chroma-vector-database a skos:Concept ;
rdfs:label "Chroma Vector Database"@en .
ngm:chrome-dev-tools-protocol a skos:Concept ;
rdfs:label "Chrome Dev Tools Protocol"@en .
ngm:chrome-devtools-protocol a skos:Concept ;
rdfs:label "Chrome Devtools Protocol"@en .
ngm:chromosphere a owl:Class ;
rdfs:label "Chromosphere"@en ;
rdfs:subClassOf ngm:stellar-atmosphere ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:astronomy ;
vc:slug "chromosphere" ;
vc:sourceDomain "space-science-and-systems" .
ngm:chunk-boundary a skos:Concept ;
rdfs:label "Chunk Boundary"@en .
ngm:chunk-metadata a skos:Concept ;
rdfs:label "Chunk Metadata"@en .
ngm:chunk-overlap a skos:Concept ;
rdfs:label "Chunk Overlap"@en .
ngm:chunked-prefill a skos:Concept ;
rdfs:label "Chunked Prefill"@en .
ngm:chunked-transfer-encoding a skos:Concept ;
rdfs:label "Chunked Transfer Encoding"@en .
ngm:chunking a owl:Class ;
rdfs:comment "Chunking is the process of segmenting source documents into smaller, semantically coherent passages before they are embedded and indexed for retrieval-augmented generation. Strategies range from fixed-size and overlapping windows to recursive, sentence-aware, and semantic chunking that respects document structure. It matters because chunk size and boundaries directly govern retrieval precision and the relevance of context supplied to a language model, making chunking a primary lever for RAG quality."@en ;
rdfs:label "Chunking"@en ;
rdfs:subClassOf ngm:information-retrieval ;
rdfs:subClassOf ngm:text-segmentation ;
rdfs:subClassOf _:r4270 ;
rdfs:subClassOf _:r4271 ;
vc:contrastsWith ngm:fine-tuning ;
vc:contrastsWith ngm:full-document-indexing ;
vc:contrastsWith ngm:parametric-knowledge ;
vc:dependsOn ngm:embedding-model ;
vc:dependsOn ngm:rag-pipeline ;
vc:dependsOn ngm:vector-database ;
vc:enables ngm:dense-retrieval ;
vc:enables ngm:hallucination-reduction ;
vc:enables ngm:hybrid-retrieval ;
vc:enables ngm:question-answering ;
vc:enables ngm:retrieval-augmented-generation ;
vc:enables ngm:semantic-search ;
vc:enables ngm:source-attribution ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:chunk-boundary ;
vc:hasPart ngm:chunk-metadata ;
vc:hasPart ngm:chunk-overlap ;
vc:hasPart ngm:document-parser ;
vc:hasPart ngm:splitting-strategy ;
vc:hasPart ngm:token-window ;
vc:implements ngm:document-indexing-pipeline ;
vc:implements ngm:rag-pipeline ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:chatbot ;
vc:relatedTo ngm:context-window ;
vc:relatedTo ngm:embedding-search ;
vc:relatedTo ngm:gpts-and-custom-assistants ;
vc:relatedTo ngm:information-extraction ;
vc:relatedTo ngm:knowledge-graph ;
vc:relatedTo ngm:nearest-neighbor-search ;
vc:relatedTo ngm:prompt-engineering ;
vc:relatedTo ngm:rag-pipeline ;
vc:relatedTo ngm:semantic-search ;
vc:requires ngm:document-parser ;
vc:requires ngm:embedding-model ;
vc:requires ngm:tokeniser ;
vc:slug "chunking" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:haystack ;
vc:standardizedBy ngm:lang-chain ;
vc:standardizedBy ngm:meta-llama-model-family-index ;
vc:supports ngm:document-intelligence ;
vc:supports ngm:enterprise-search ;
vc:supports ngm:knowledge-grounding ;
vc:supports ngm:question-answering ;
vc:supports ngm:source-attribution ;
vc:uses ngm:embedding-model ;
vc:uses ngm:large-language-models ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:sentence-transformers ;
vc:uses ngm:tokeniser ;
vc:uses ngm:vector-database .
ngm:chunking-mechanism a skos:Concept ;
rdfs:label "Chunking Mechanism"@en .
ngm:church-turing-thesis a skos:Concept ;
rdfs:label "Church Turing Thesis"@en .
ngm:ci-cd a owl:Class ;
rdfs:comment "CI/CD (continuous integration and continuous delivery/deployment) is the software engineering practice of automatically building, testing and releasing every code change through a versioned pipeline. Continuous integration merges work into a shared trunk many times a day behind automated test gates; continuous delivery keeps the mainline permanently releasable; continuous deployment pushes each passing change to production automatically. Together they shrink feedback loops, reduce integration risk and enable progressive release strategies such as canary and zero-downtime deployments."@en ;
rdfs:label "CI/CD"@en ;
rdfs:subClassOf ngm:devops ;
rdfs:subClassOf _:r3743 ;
rdfs:subClassOf _:r3744 ;
vc:enables ngm:canary-deployment ;
vc:enables ngm:zero-downtime-deployment ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:continuous-deployment ;
vc:hasPart ngm:continuous-integration ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:infrastructure-as-code ;
vc:relatedTo ngm:software-engineering ;
vc:slug "ci-cd" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:automated-testing ;
vc:uses ngm:container ;
vc:uses ngm:version-control .
ngm:ci-cd-automation a owl:Class ;
rdfs:comment "Continuous integration and continuous delivery (CI/CD) automation is the practice of automatically building, testing, and deploying software changes through a defined pipeline triggered by source-control events. Continuous integration merges and validates changes frequently to detect defects early; continuous delivery extends this to produce always-deployable artefacts, while continuous deployment automates release to production. CI/CD automation reduces integration risk, shortens feedback loops, and makes deployments repeatable and auditable. It is implemented through pipeline-as-code definitions executed by orchestrators such as GitHub Actions, GitLab CI, and Jenkins."@en ;
rdfs:label "CI-CD Automation"@en ;
rdfs:subClassOf ngm:automation ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.78"^^xsd:float ;
vc:relatedTo ngm:model-deployment ;
vc:relatedTo ngm:software-engineering ;
vc:slug "ci-cd-automation" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:data-pipeline .
ngm:ci-cd-pipeline a skos:Concept ;
rdfs:label "Ci Cd Pipeline"@en .
ngm:cia-301-canopen-standard a skos:Concept ;
rdfs:label "Cia 301 Canopen Standard"@en .
ngm:cid a owl:Class ;
rdfs:comment "A Content Identifier (CID) is a self-describing, cryptographic label used in the InterPlanetary File System (IPFS) and related protocols to uniquely and permanently address a piece of content based on its cryptographic hash rather than its location. CIDs encode the hash function used, the hash digest, and the codec describing the data format, enabling content-addressed storage where identical content always produces the same identifier regardless of where it is stored. CIDs are the primary addressing primitive of the IPLD (InterPlanetary Linked Data) ecosystem."@en ;
rdfs:label "CID"@en ;
rdfs:subClassOf ngm:content-identifier ;
vc:enables ngm:content-addressing ;
vc:enables ngm:decentralized-storage ;
vc:enables ngm:ipfs ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:distributed-hash-table ;
vc:relatedTo ngm:merkle-dag ;
vc:slug "cid" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:cryptographic-hash-function ;
vc:uses ngm:ipld ;
vc:uses ngm:multihash .
ngm:cidr-architecture a skos:Concept ;
rdfs:label "Cidr Architecture"@en .
ngm:cinematic-rendering a owl:Class ;
rdfs:comment "Cinematic Rendering is a rendering approach that prioritises photorealistic, film-quality visual output over real-time frame rates, applying techniques such as ray tracing, physically based materials, depth of field, and colour grading. It is used for pre-rendered animation, marketing visualisation, and offline previsualisation rather than interactive applications. It builds on general rendering techniques but trades real-time performance for image fidelity."@en ;
rdfs:label "Cinematic Rendering"@en ;
rdfs:subClassOf ngm:rendering-technique ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "cinematic-rendering" ;
vc:sourceDomain "spatial-computing" .
ngm:cinematics a skos:Concept ;
rdfs:label "Cinematics"@en .
ngm:ciou-loss a skos:Concept ;
rdfs:label "Ciou Loss"@en .
ngm:cipher a skos:Concept ;
rdfs:label "Cipher"@en .
ngm:ciphertrace a skos:Concept ;
rdfs:label "Ciphertrace"@en .
ngm:circle a owl:Class ;
rdfs:comment "Circle is a financial technology company that issues a US dollar stablecoin and provides payment and digital asset infrastructure."@en ;
rdfs:label "Circle"@en ;
rdfs:subClassOf ngm:stablecoin ;
rdfs:subClassOf _:r4272 ;
vc:bridgesTo ngm:financial-services ;
vc:enables ngm:cryptocurrency ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:stablecoin ;
vc:slug "circle" ;
vc:sourceDomain "blockchain" .
ngm:circle-grid a skos:Concept ;
rdfs:label "Circle Grid"@en .
ngm:circom a skos:Concept ;
rdfs:label "Circom"@en .
ngm:circuit-breaker a owl:Class ;
rdfs:comment "The circuit breaker is a fault-tolerance design pattern that monitors calls to a remote service or resource and, once failures exceed a threshold, trips open to fail fast and stop sending requests for a cooling-off period. After a timeout it allows a limited number of trial calls in a half-open state to test recovery before closing again. The pattern prevents cascading failures, protects struggling dependencies, and enables graceful degradation in distributed systems."@en ;
rdfs:label "Circuit Breaker"@en ;
rdfs:subClassOf ngm:fault-tolerance ;
rdfs:subClassOf _:r4273 ;
rdfs:subClassOf _:r4274 ;
vc:bridgesTo ngm:service-mesh ;
vc:dependsOn ngm:reliability-engineering ;
vc:enables ngm:resilience ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:observability ;
vc:implements ngm:fault-tolerance ;
vc:implements ngm:resilience ;
vc:isPartOf ngm:fault-tolerance ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:api-gateway ;
vc:relatedTo ngm:rate-limiting ;
vc:relatedTo ngm:service-mesh ;
vc:requires ngm:observability ;
vc:slug "circuit-breaker" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:microservices ;
vc:supports ngm:reliability-engineering ;
vc:uses ngm:observability .
ngm:circuit-breaker-pattern a skos:Concept ;
rdfs:label "Circuit Breaker Pattern"@en .
ngm:circuit-complexity a skos:Concept ;
rdfs:label "Circuit Complexity"@en .
ngm:circuit-switching a skos:Concept ;
rdfs:label "Circuit Switching"@en .
ngm:circuitbreaker a skos:Concept ;
rdfs:label "Circuitbreaker"@en .
ngm:circular-bitcoin-economy a skos:Concept ;
rdfs:label "Circular Bitcoin Economy"@en .
ngm:circular-economy a owl:Class ;
rdfs:comment "Systemic economic model that eliminates waste and keeps materials, components, and products in use at their highest value for as long as possible through restorative and regenerative design, distinguished from the linear \"take-make-dispose\" paradigm by organising economic activity around three fo..."@en ;
rdfs:label "Circular Economy"@en ;
rdfs:subClassOf ngm:economic-model ;
rdfs:subClassOf ngm:environmental-policy ;
rdfs:subClassOf ngm:industrial-ecology ;
rdfs:subClassOf ngm:infra-legal-and-regulatory ;
rdfs:subClassOf ngm:resource-management ;
rdfs:subClassOf ngm:sustainability ;
rdfs:subClassOf ngm:systems-thinking ;
rdfs:subClassOf _:r4275 ;
rdfs:subClassOf _:r4276 ;
rdfs:subClassOf _:r4277 ;
rdfs:subClassOf _:r4278 ;
rdfs:subClassOf _:r4279 ;
rdfs:subClassOf _:r4280 ;
rdfs:subClassOf _:r4281 ;
rdfs:subClassOf _:r4282 ;
rdfs:subClassOf _:r4283 ;
rdfs:subClassOf _:r4284 ;
rdfs:subClassOf _:r4285 ;
rdfs:subClassOf _:r4286 ;
rdfs:subClassOf _:r4287 ;
rdfs:subClassOf _:r4288 ;
rdfs:subClassOf _:r4289 ;
rdfs:subClassOf _:r4290 ;
rdfs:subClassOf _:r4291 ;
skos:broader ngm:infra-legal-and-regulatory ;
vc:bridgesTo ngm:economic-model ;
vc:bridgesTo ngm:governance ;
vc:contrastsWith ngm:fast-fashion ;
vc:contrastsWith ngm:landfill-disposal ;
vc:contrastsWith ngm:linear-economy ;
vc:contrastsWith ngm:planned-obsolescence ;
vc:contrastsWith ngm:single-use-products ;
vc:dependsOn ngm:artificial-intelligence ;
vc:dependsOn ngm:blockchain ;
vc:dependsOn ngm:digital-twin ;
vc:dependsOn ngm:gs1 ;
vc:dependsOn ngm:io-t ;
vc:dependsOn ngm:material-science ;
vc:dependsOn ngm:product-design ;
vc:dependsOn ngm:supply-chain ;
vc:enables ngm:carbon-credits ;
vc:enables ngm:esg-investing ;
vc:enables ngm:green-finance ;
vc:enables ngm:green-growth ;
vc:enables ngm:industrial-symbiosis ;
vc:enables ngm:neural-network-text-tokenisation ;
vc:enables ngm:resource-security ;
vc:enables ngm:sustainable-manufacturing ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:cradle-to-cradle-design ;
vc:hasPart ngm:deposit-return-scheme ;
vc:hasPart ngm:digital-product-passport ;
vc:hasPart ngm:extended-producer-responsibility ;
vc:hasPart ngm:industrial-symbiosis ;
vc:hasPart ngm:life-cycle-assessment ;
vc:hasPart ngm:material-flow-analysis ;
vc:hasPart ngm:product-as-a-service ;
vc:hasPart ngm:reverse-logistics ;
vc:hasPart ngm:waste-management ;
vc:implements ngm:cradle-to-cradle-design ;
vc:implements ngm:digital-product-passport ;
vc:implements ngm:ecodesign-for-sustainable-products-regulation ;
vc:implements ngm:ellen-macarthur-foundation ;
vc:implements ngm:eu-green-deal ;
vc:implements ngm:extended-producer-responsibility ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:carbon-credits ;
vc:relatedTo ngm:digital-product-passport ;
vc:relatedTo ngm:esg-investing ;
vc:relatedTo ngm:eu-green-deal ;
vc:relatedTo ngm:industrial-symbiosis ;
vc:relatedTo ngm:life-cycle-assessment ;
vc:relatedTo ngm:neural-network-text-tokenisation ;
vc:relatedTo ngm:product-design ;
vc:relatedTo ngm:supply-chain ;
vc:relatedTo ngm:waste-management ;
vc:requires ngm:life-cycle-assessment ;
vc:requires ngm:product-design ;
vc:requires ngm:regulatory-framework ;
vc:requires ngm:stakeholder-collaboration ;
vc:requires ngm:supply-chain ;
vc:requires ngm:traceability ;
vc:requires ngm:waste-management ;
vc:slug "circular-economy" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:ecodesign-for-sustainable-products-regulation ;
vc:standardizedBy ngm:eu-battery-regulation ;
vc:standardizedBy ngm:gs1-digital-link ;
vc:standardizedBy ngm:gs1-epcis ;
vc:standardizedBy ngm:iso-14040 ;
vc:standardizedBy ngm:iso-14044 ;
vc:standardizedBy ngm:iso-14072 ;
vc:standardizedBy ngm:iso-59004 ;
vc:supports ngm:carbon-credits ;
vc:supports ngm:climate-change-mitigation ;
vc:supports ngm:esg-investing ;
vc:supports ngm:green-finance ;
vc:supports ngm:neural-network-text-tokenisation ;
vc:supports ngm:sustainable-development ;
vc:supports ngm:sustainable-development-goals ;
vc:uses ngm:artificial-intelligence ;
vc:uses ngm:blockchain ;
vc:uses ngm:digital-twin ;
vc:uses ngm:gs1 ;
vc:uses ngm:hyperledger-fabric ;
vc:uses ngm:io-t ;
vc:uses ngm:life-cycle-assessment ;
vc:uses ngm:neural-network-text-tokenisation ;
vc:uses ngm:ve-chain .
ngm:circular-orbit a owl:Class ;
rdfs:label "Circular Orbit"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:orbital-dynamics ;
vc:slug "circular-orbit" ;
vc:sourceDomain "space-science-and-systems" .
ngm:circulating-supply a owl:Class ;
rdfs:comment "Circulating Supply is the quantity of a blockchain token that is publicly available and actively tradeable in the market at a given point in time—excluding tokens locked in smart contracts, held in treasury reserves, vested to team members, or burned. It serves as the operative supply figure for computing market capitalisation and price-to-earnings metrics, and changes continuously as new tokens are emitted via block rewards and locked tokens are released according to vesting schedules."@en ;
rdfs:label "Circulating Supply"@en ;
rdfs:subClassOf ngm:bc-defi-and-economics ;
rdfs:subClassOf ngm:blockchain-entity ;
rdfs:subClassOf ngm:economic-mechanism ;
rdfs:subClassOf _:r4292 ;
rdfs:subClassOf _:r4293 ;
skos:broader ngm:bc-defi-and-economics ;
vc:contrastsWith ngm:deflationary-token ;
vc:contrastsWith ngm:inflationary-token ;
vc:enables ngm:blockchain-economics ;
vc:enables ngm:burning-mechanism ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:fixed-supply-token ;
vc:relatedTo ngm:halving ;
vc:relatedTo ngm:market-capitalization ;
vc:relatedTo ngm:token-economics ;
vc:relatedTo ngm:tokenomics ;
vc:relatedTo ngm:total-supply ;
vc:requires ngm:blockchain-protocol ;
vc:requires ngm:emission-schedule ;
vc:slug "circulating-supply" ;
vc:sourceDomain "blockchain" .
ngm:cis-controls a skos:Concept ;
rdfs:label "Cis Controls"@en .
ngm:cis-mars-space-environment a owl:Class ;
rdfs:label "Cis-Mars Space Environment"@en ;
rdfs:subClassOf ngm:space-environment ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:space-life-sciences ;
vc:slug "cis-mars-space-environment" ;
vc:sourceDomain "space-science-and-systems" .
ngm:cis-mars-space-radiation-environment a owl:Class ;
rdfs:label "Cis-Mars Space Radiation Environment"@en ;
rdfs:subClassOf ngm:space-radiation-environment ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:space-life-sciences ;
vc:slug "cis-mars-space-radiation-environment" ;
vc:sourceDomain "space-science-and-systems" .
ngm:cislunar-space-environment a owl:Class ;
rdfs:label "Cislunar Space Environment"@en ;
rdfs:subClassOf ngm:space-environment ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:space-life-sciences ;
vc:slug "cislunar-space-environment" ;
vc:sourceDomain "space-science-and-systems" .
ngm:cislunar-space-radiation-environment a owl:Class ;
rdfs:label "Cislunar Space Radiation Environment"@en ;
rdfs:subClassOf ngm:space-radiation-environment ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:space-life-sciences ;
vc:slug "cislunar-space-radiation-environment" ;
vc:sourceDomain "space-science-and-systems" .
ngm:citation a skos:Concept ;
rdfs:label "Citation"@en .
ngm:citation-generation a skos:Concept ;
rdfs:label "Citation Generation"@en .
ngm:citation-grounded-answers a skos:Concept ;
rdfs:label "Citation Grounded Answers"@en .
ngm:citation-grounding-layer a skos:Concept ;
rdfs:label "Citation Grounding Layer"@en .
ngm:citation-network a skos:Concept ;
rdfs:label "Citation Network"@en .
ngm:citi-token-services a owl:Class ;
rdfs:comment "A service from Citi that issues tokenised representations of institutional client deposits on a permissioned blockchain to support faster cash management and trade transactions. It operates within the bank's regulated infrastructure rather than on a public network."@en ;
rdfs:label "Citi Token Services"@en ;
rdfs:subClassOf ngm:trade-finance ;
rdfs:subClassOf _:r4294 ;
rdfs:subClassOf _:r4295 ;
vc:bridgesTo ngm:distributed-ledger-technology ;
vc:bridgesTo ngm:smart-contract ;
vc:enables ngm:payment-channel ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:permissioned-blockchain ;
vc:requires ngm:tokenization ;
vc:slug "citi-token-services" ;
vc:sourceDomain "blockchain" .
ngm:citizen-engagement a skos:Concept ;
rdfs:label "Citizen Engagement"@en .
ngm:citizen-voting-rights a skos:Concept ;
rdfs:label "Citizen Voting Rights"@en .
ngm:citrea a skos:Concept ;
rdfs:label "Citrea"@en .
ngm:city-deal a skos:Concept ;
rdfs:label "City Deal"@en .
ngm:cityscapes-dataset a skos:Concept ;
rdfs:label "Cityscapes Dataset"@en .
ngm:civic-duties a skos:Concept ;
rdfs:label "Civic Duties"@en .
ngm:civic-engagement-platform a skos:Concept ;
rdfs:label "Civic Engagement Platform"@en .
ngm:civic-participation a owl:Class ;
rdfs:comment "The engagement of citizens in democratic processes and public decision-making through digital platforms, virtual environments, and emerging technologies including metaverse spaces, blockchain voting systems, and AI-enhanced deliberation tools that enable new forms of collective governance."@en ;
rdfs:label "Civic Participation"@en ;
rdfs:subClassOf ngm:democratic-engagement ;
rdfs:subClassOf ngm:sc-governance-and-safety ;
rdfs:subClassOf _:r4296 ;
rdfs:subClassOf _:r4297 ;
rdfs:subClassOf _:r4298 ;
skos:broader ngm:sc-governance-and-safety ;
vc:bridgesTo ngm:telecollaboration ;
vc:enables ngm:collective-governance ;
vc:enables ngm:digital-democracy ;
vc:enables ngm:public-deliberation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:accessibility ;
vc:requires ngm:digital-platform ;
vc:requires ngm:trust-infrastructure ;
vc:slug "civic-participation" ;
vc:sourceDomain "spatial-computing" .
ngm:civic-technology a skos:Concept ;
rdfs:label "Civic Technology"@en .
ngm:civil-liberties a skos:Concept ;
rdfs:label "Civil Liberties"@en .
ngm:civil-society a skos:Concept ;
rdfs:label "Civil Society"@en .
ngm:civil-society-oversight a skos:Concept ;
rdfs:label "Civil Society Oversight"@en .
ngm:civilian-cybersecurity a skos:Concept ;
rdfs:label "Civilian Cybersecurity"@en .
ngm:civitai a owl:Class ;
rdfs:comment "Civitai is a community-driven online platform for sharing, discovering, and downloading fine-tuned generative AI image models, primarily Stable Diffusion checkpoints, LoRA adaptors, embeddings, and VAEs, enabling practitioners and artists to distribute specialised model weights trained on specific styles, characters, or concepts without requiring the infrastructure overhead of operating their own model registry. It functions as both a social network for AI artists and a technical marketplace for model artefacts."@en ;
rdfs:label "Civitai"@en ;
rdfs:subClassOf ngm:generative-ai ;
rdfs:subClassOf ngm:model-registry ;
rdfs:subClassOf _:r4299 ;
rdfs:subClassOf _:r4300 ;
rdfs:subClassOf _:r4301 ;
rdfs:subClassOf _:r4302 ;
rdfs:subClassOf _:r4303 ;
rdfs:subClassOf _:r4304 ;
rdfs:subClassOf _:r4305 ;
vc:contrastsWith ngm:adobe-firefly ;
vc:contrastsWith ngm:dall-e-3 ;
vc:contrastsWith ngm:hugging-face-model-hub ;
vc:contrastsWith ngm:midjourney-text-to-image-service ;
vc:dependsOn ngm:diffusion-model ;
vc:dependsOn ngm:fine-tuning ;
vc:dependsOn ngm:generative-model ;
vc:enables ngm:creative-ai ;
vc:enables ngm:image-generation ;
vc:enables ngm:open-source-ai ;
vc:enables ngm:text-to-image ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:diffusion-model ;
vc:hasPart ngm:fine-tuning ;
vc:hasPart ngm:lo-ra-fine-tuning ;
vc:hasPart ngm:text-to-image ;
vc:implements ngm:creator-economy ;
vc:implements ngm:fine-tuning ;
vc:implements ngm:model-registry ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:ai-regulation ;
vc:relatedTo ngm:comfy-ui ;
vc:relatedTo ngm:content-moderation ;
vc:relatedTo ngm:control-net ;
vc:relatedTo ngm:copyright ;
vc:relatedTo ngm:deepfake-detection ;
vc:relatedTo ngm:flux ;
vc:relatedTo ngm:generative-model ;
vc:relatedTo ngm:open-source-ai ;
vc:relatedTo ngm:stable-diffusion-image-model ;
vc:relatedTo ngm:textual-inversion ;
vc:requires ngm:content-moderation ;
vc:requires ngm:diffusion-model ;
vc:requires ngm:gpu-compute ;
vc:slug "civitai" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:safetensors-format ;
vc:standardizedBy ngm:stable-diffusion-image-model ;
vc:supports ngm:creative-ai ;
vc:supports ngm:generative-ai ;
vc:supports ngm:image-generation ;
vc:supports ngm:open-source-ai ;
vc:uses ngm:deep-learning ;
vc:uses ngm:diffusion-model ;
vc:uses ngm:fine-tuning ;
vc:uses ngm:generative-model ;
vc:uses ngm:image-generation ;
vc:uses ngm:lo-ra-fine-tuning ;
vc:uses ngm:vae .
ngm:civitai-workflow-sharing a skos:Concept ;
rdfs:label "Civitai Workflow Sharing"@en .
ngm:ckks-scheme a skos:Concept ;
rdfs:label "Ckks Scheme"@en .
ngm:claap a skos:Concept ;
rdfs:label "Claap"@en .
ngm:claim a skos:Concept ;
rdfs:label "Claim"@en .
ngm:claim-issuer a skos:Concept ;
rdfs:label "Claim Issuer"@en .
ngm:claim-mapping a skos:Concept ;
rdfs:label "Claim Mapping"@en .
ngm:claim-topic-registry a skos:Concept ;
rdfs:label "Claim Topic Registry"@en .
ngm:clap a skos:Concept ;
rdfs:label "Clap"@en .
ngm:clap-audio-embeddings a skos:Concept ;
rdfs:label "Clap Audio Embeddings"@en .
ngm:clap-embeddings a skos:Concept ;
rdfs:label "Clap Embeddings"@en .
ngm:clarion a skos:Concept ;
rdfs:label "Clarion"@en .
ngm:clarity a owl:Class ;
rdfs:comment "Clarity is a decidable smart contract language designed so that contract behaviour can be analysed before execution, with no compilation step and explicit handling of conditions that could otherwise fail silently."@en ;
rdfs:label "Clarity"@en ;
rdfs:subClassOf ngm:smart-contracts ;
rdfs:subClassOf _:r4306 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:de-fi ;
vc:enables ngm:verifiable-computation ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:smart-contracts ;
vc:slug "clarity" ;
vc:sourceDomain "metaverse" .
ngm:clash-detection a skos:Concept ;
rdfs:label "Clash Detection"@en .
ngm:class-diagram a skos:Concept ;
rdfs:label "Class Diagram"@en .
ngm:class-imbalance a owl:Class ;
rdfs:comment "Class imbalance is the condition in a classification dataset where the number of examples in one class greatly exceeds that of another, causing learning algorithms to favour the majority class. It is common in problems such as fraud detection, medical diagnosis, and anomaly detection, where the events of interest are rare. Class imbalance undermines naive accuracy as an evaluation metric and motivates remedies such as resampling, cost-sensitive learning, and the use of precision-recall-oriented metrics."@en ;
rdfs:label "Class Imbalance"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:classification ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf ngm:supervised-learning ;
rdfs:subClassOf _:r4307 ;
rdfs:subClassOf _:r4308 ;
rdfs:subClassOf _:r4309 ;
rdfs:subClassOf _:r4310 ;
rdfs:subClassOf _:r4311 ;
rdfs:subClassOf _:r4312 ;
rdfs:subClassOf _:r4313 ;
skos:broader ngm:ai-technique ;
vc:contrastsWith ngm:accuracy-metric ;
vc:contrastsWith ngm:balanced-dataset ;
vc:contrastsWith ngm:overfitting ;
vc:dependsOn ngm:classification ;
vc:dependsOn ngm:data-preprocessing ;
vc:dependsOn ngm:feature-engineering ;
vc:dependsOn ngm:loss-function ;
vc:enables ngm:anomaly-detection ;
vc:enables ngm:fraud-detection ;
vc:enables ngm:intrusion-detection-system ;
vc:enables ngm:medical-diagnosis-ai ;
vc:enables ngm:predictive-maintenance ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:cost-sensitive-learning ;
vc:hasPart ngm:ensemble-methods ;
vc:hasPart ngm:focal-loss ;
vc:hasPart ngm:resampling ;
vc:hasPart ngm:smote ;
vc:implements ngm:cost-sensitive-learning ;
vc:implements ngm:focal-loss ;
vc:implements ngm:resampling ;
vc:implements ngm:smote ;
vc:isPartOf ngm:classification ;
vc:isPartOf ngm:machine-learning-discipline ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:active-learning ;
vc:relatedTo ngm:anomaly-detection ;
vc:relatedTo ngm:concept-drift ;
vc:relatedTo ngm:confusion-matrix ;
vc:relatedTo ngm:data-augmentation ;
vc:relatedTo ngm:f1-score ;
vc:relatedTo ngm:long-tail-distribution ;
vc:relatedTo ngm:precision-recall-curve ;
vc:relatedTo ngm:recall ;
vc:relatedTo ngm:roc-curve ;
vc:relatedTo ngm:transfer-learning ;
vc:requires ngm:confusion-matrix ;
vc:requires ngm:data-preprocessing ;
vc:requires ngm:evaluation-metric ;
vc:requires ngm:f1-score ;
vc:requires ngm:precision-recall-curve ;
vc:slug "class-imbalance" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:imbalanced-learn ;
vc:standardizedBy ngm:neurips-benchmarks ;
vc:standardizedBy ngm:scikit-learn ;
vc:supports ngm:model-performance ;
vc:supports ngm:precision-recall-curve ;
vc:supports ngm:recall ;
vc:supports ngm:roc-curve ;
vc:uses ngm:boosting ;
vc:uses ngm:deep-learning ;
vc:uses ngm:ensemble-methods ;
vc:uses ngm:feature-engineering ;
vc:uses ngm:loss-function ;
vc:uses ngm:random-forest ;
vc:uses ngm:resampling .
ngm:class-imbalance-mitigation a skos:Concept ;
rdfs:label "Class Imbalance Mitigation"@en .
ngm:class-incremental-learning a skos:Concept ;
rdfs:label "Class Incremental Learning"@en .
ngm:classic-search-crawler a skos:Concept ;
rdfs:label "Classic Search Crawler"@en .
ngm:classical-ai a skos:Concept ;
rdfs:label "Classical AI"@en .
ngm:classical-ai-planning a skos:Concept ;
rdfs:label "Classical AI Planning"@en .
ngm:classical-ai-without-learning a skos:Concept ;
rdfs:label "Classical AI Without Learning"@en .
ngm:classical-animation a skos:Concept ;
rdfs:label "Classical Animation"@en .
ngm:classical-bias-variance-tradeoff a skos:Concept ;
rdfs:label "Classical Bias Variance Tradeoff"@en .
ngm:classical-cloud-compute a skos:Concept ;
rdfs:label "Classical Cloud Compute"@en .
ngm:classical-cognitivism a skos:Concept ;
rdfs:label "Classical Cognitivism"@en .
ngm:classical-computing a skos:Concept ;
rdfs:label "Classical Computing"@en .
ngm:classical-control a skos:Concept ;
rdfs:label "Classical Control"@en .
ngm:classical-control-theory a skos:Concept ;
rdfs:label "Classical Control Theory"@en .
ngm:classical-genetics a skos:Concept ;
rdfs:label "Classical Genetics"@en .
ngm:classical-information-retrieval a skos:Concept ;
rdfs:label "Classical Information Retrieval"@en .
ngm:classical-mechanics a skos:Concept ;
rdfs:label "Classical Mechanics"@en .
ngm:classical-optimisation-without-feedback a skos:Concept ;
rdfs:label "Classical Optimisation Without Feedback"@en .
ngm:classical-planning a owl:Class ;
rdfs:comment "Classical planning is a branch of automated planning that computes a sequence of deterministic actions transforming a fully observable initial state into a state satisfying a goal condition. It assumes a single agent, discrete states, instantaneous actions with deterministic effects, and complete knowledge of the world. Problems are typically expressed in formalisms such as STRIPS or PDDL and solved by heuristic state-space search."@en ;
rdfs:label "Classical Planning"@en ;
rdfs:subClassOf ngm:automated-planning ;
rdfs:subClassOf ngm:planning-and-scheduling ;
rdfs:subClassOf _:r4314 ;
rdfs:subClassOf _:r4315 ;
rdfs:subClassOf _:r4316 ;
rdfs:subClassOf _:r4317 ;
rdfs:subClassOf _:r4318 ;
rdfs:subClassOf _:r4319 ;
rdfs:subClassOf _:r4320 ;
rdfs:subClassOf _:r4321 ;
rdfs:subClassOf _:r4322 ;
vc:contrastsWith ngm:markov-decision-process ;
vc:contrastsWith ngm:reactive-planning ;
vc:contrastsWith ngm:reinforcement-learning ;
vc:dependsOn ngm:formal-logic ;
vc:dependsOn ngm:knowledge-representation ;
vc:dependsOn ngm:search-algorithm ;
vc:enables ngm:agent ;
vc:enables ngm:autonomous-system ;
vc:enables ngm:multi-agent-coordination ;
vc:enables ngm:robotics ;
vc:enables ngm:task-automation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:heuristic-search ;
vc:hasPart ngm:hierarchical-task-network ;
vc:hasPart ngm:pddl ;
vc:hasPart ngm:state-space-search ;
vc:hasPart ngm:strips ;
vc:implements ngm:a-star-algorithm ;
vc:implements ngm:pddl ;
vc:implements ngm:strips ;
vc:isPartOf ngm:artificial-intelligence ;
vc:isPartOf ngm:automated-planning ;
vc:qualityScore "0.92"^^xsd:float ;
vc:relatedTo ngm:a-star-algorithm ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:hierarchical-task-network ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:optimisation ;
vc:relatedTo ngm:pathfinding ;
vc:relatedTo ngm:temporal-planning ;
vc:requires ngm:constraint-satisfaction ;
vc:requires ngm:formal-logic ;
vc:requires ngm:knowledge-representation ;
vc:requires ngm:search-algorithm ;
vc:slug "classical-planning" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:pddl ;
vc:supports ngm:game-playing ;
vc:supports ngm:logistics-optimisation ;
vc:supports ngm:motion-planning ;
vc:supports ngm:pathfinding ;
vc:uses ngm:formal-logic ;
vc:uses ngm:graph-search ;
vc:uses ngm:knowledge-representation ;
vc:uses ngm:sat-solving .
ngm:classical-rendering a skos:Concept ;
rdfs:label "Classical Rendering"@en .
ngm:classical-surveillance-systems a skos:Concept ;
rdfs:label "Classical Surveillance Systems"@en .
ngm:classification a owl:Class ;
rdfs:comment "Classification is a supervised machine learning task in which a model learns a mapping from input features to a discrete set of predefined category labels, using labelled training examples to optimise decision boundaries or probabilistic scoring rules. At inference time the model assigns each unseen input to one or more categories by applying a learned discriminant function or probabilistic scoring rule. The task encompasses binary, multi-class, and multi-label variants, and underpins applications ranging from image recognition and natural language understanding to medical diagnosis and fraud detection. Performance is evaluated with metrics such as accuracy, precision, recall, F1-score, and the area under the receiver-operating-characteristic curve, selected according to class imbalance and the relative cost of false positives versus false negatives."@en ;
rdfs:label "Classification"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf ngm:pattern-recognition ;
rdfs:subClassOf ngm:supervised-learning ;
rdfs:subClassOf _:r4339 ;
rdfs:subClassOf _:r4340 ;
rdfs:subClassOf _:r4341 ;
rdfs:subClassOf _:r4342 ;
rdfs:subClassOf _:r4343 ;
rdfs:subClassOf _:r4344 ;
rdfs:subClassOf _:r4345 ;
rdfs:subClassOf _:r4346 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:bioinformatics ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:knowledge-graph ;
vc:bridgesTo ngm:natural-language-processing ;
vc:bridgesTo ngm:robotics-perception ;
vc:contrastsWith ngm:anomaly-detection ;
vc:contrastsWith ngm:clustering ;
vc:contrastsWith ngm:generative-model ;
vc:contrastsWith ngm:regression ;
vc:contrastsWith ngm:reinforcement-learning ;
vc:dependsOn ngm:classification-threshold ;
vc:dependsOn ngm:cross-validation ;
vc:dependsOn ngm:hyperparameter-tuning ;
vc:dependsOn ngm:probability-calibration ;
vc:dependsOn ngm:training-data ;
vc:enables ngm:fraud-detection ;
vc:enables ngm:image-recognition ;
vc:enables ngm:intent-recognition ;
vc:enables ngm:medical-diagnosis-ai ;
vc:enables ngm:named-entity-recognition ;
vc:enables ngm:object-detection ;
vc:enables ngm:robotics-perception ;
vc:enables ngm:sentiment-analysis ;
vc:enables ngm:spam-filtering ;
vc:enables ngm:text-classification ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:classification ;
vc:hasPart ngm:classification-threshold ;
vc:hasPart ngm:hierarchical-classification ;
vc:hasPart ngm:multi-class-classification ;
vc:hasPart ngm:multi-label-classification ;
vc:hasPart ngm:ordinal-classification ;
vc:implements ngm:empirical-risk-minimisation ;
vc:implements ngm:pac-learning ;
vc:implements ngm:statistical-decision-theory ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:active-learning ;
vc:relatedTo ngm:auto-ml ;
vc:relatedTo ngm:class-imbalance ;
vc:relatedTo ngm:conformal-prediction ;
vc:relatedTo ngm:confusion-matrix ;
vc:relatedTo ngm:continual-learning ;
vc:relatedTo ngm:ensemble-methods ;
vc:relatedTo ngm:few-shot-learning ;
vc:relatedTo ngm:meta-learning ;
vc:relatedTo ngm:probabilistic-inference ;
vc:relatedTo ngm:representation-learning ;
vc:relatedTo ngm:roc-curve ;
vc:relatedTo ngm:semi-supervised-learning ;
vc:relatedTo ngm:statistical-learning-theory ;
vc:relatedTo ngm:transfer-learning ;
vc:relatedTo ngm:zero-shot-learning ;
vc:requires ngm:feature-engineering ;
vc:requires ngm:labelled-dataset ;
vc:requires ngm:loss-function ;
vc:requires ngm:model-evaluation ;
vc:requires ngm:supervised-learning ;
vc:requires ngm:training-data ;
vc:slug "classification" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:iso-iec-22989-2022 ;
vc:standardizedBy ngm:iso-iec-23053 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:ai-fairness ;
vc:supports ngm:ai-governance ;
vc:supports ngm:autonomous-system ;
vc:supports ngm:explainable-ai ;
vc:supports ngm:knowledge-graph ;
vc:uses ngm:convolutional-neural-network ;
vc:uses ngm:decision-tree ;
vc:uses ngm:gradient-boosted-trees ;
vc:uses ngm:k-nearest-neighbours ;
vc:uses ngm:logistic-regression ;
vc:uses ngm:naive-bayes ;
vc:uses ngm:neural-network ;
vc:uses ngm:random-forest ;
vc:uses ngm:support-vector-machine ;
vc:uses ngm:transformer-architecture .
ngm:classification-evaluation a owl:Class ;
rdfs:comment "Classification evaluation is the set of methods used to quantify how well a classifier's predicted labels match ground-truth labels, typically summarised through metrics derived from a confusion matrix such as precision, recall, and F1 score. It distinguishes between overall accuracy, which can be misleading under class imbalance, and per-class metrics that expose asymmetric error costs. Classification evaluation guides model selection, threshold tuning, and reporting of deployed classifier performance."@en ;
rdfs:label "Classification Evaluation"@en ;
rdfs:subClassOf ngm:evaluation-metric ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:evaluation-metric ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "classification-evaluation" ;
vc:sourceDomain "machine-learning" .
ngm:classification-framework a skos:Concept ;
rdfs:label "Classification Framework"@en .
ngm:classification-metric a skos:Concept ;
rdfs:label "Classification Metric"@en .
ngm:classification-rules a owl:Class ;
rdfs:comment "Classification Rules are explicit logical statements, typically in an if-then form, that assign instances or entities to predefined categories based on the values of their attributes or the satisfaction of specified conditions. Derived from rule-learning algorithms, expert elicitation, or ontology reasoning, classification rules provide interpretable, auditable decision logic for categorising data points in machine learning, knowledge engineering, and regulatory compliance contexts. They contrast with black-box classifiers by exposing their decision rationale directly as symbolic propositions."@en ;
rdfs:label "Classification Rules"@en ;
rdfs:subClassOf ngm:formal-logic ;
rdfs:subClassOf ngm:inference-engine ;
rdfs:subClassOf ngm:knowledge-representation ;
rdfs:subClassOf _:r4323 ;
rdfs:subClassOf _:r4324 ;
rdfs:subClassOf _:r4325 ;
rdfs:subClassOf _:r4326 ;
rdfs:subClassOf _:r4327 ;
rdfs:subClassOf _:r4328 ;
rdfs:subClassOf _:r4329 ;
vc:contrastsWith ngm:decision-tree ;
vc:contrastsWith ngm:ensemble-methods ;
vc:contrastsWith ngm:large-language-models ;
vc:contrastsWith ngm:neural-network ;
vc:dependsOn ngm:knowledge-base ;
vc:dependsOn ngm:knowledge-representation ;
vc:dependsOn ngm:ontology ;
vc:dependsOn ngm:supervised-learning ;
vc:enables ngm:business-rules-engine ;
vc:enables ngm:clinical-decision-support ;
vc:enables ngm:expert-systems ;
vc:enables ngm:explainability ;
vc:enables ngm:interpretability ;
vc:enables ngm:machine-learning-discipline ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:backward-chaining ;
vc:hasPart ngm:forward-chaining ;
vc:hasPart ngm:inference-engine ;
vc:hasPart ngm:production-rules ;
vc:implements ngm:backward-chaining ;
vc:implements ngm:forward-chaining ;
vc:implements ngm:logic-programming ;
vc:qualityScore "0.92"^^xsd:float ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:decision-tree ;
vc:relatedTo ngm:knowledge-base ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:owl ;
vc:relatedTo ngm:rdf ;
vc:requires ngm:formal-logic ;
vc:requires ngm:inference-engine ;
vc:requires ngm:knowledge-base ;
vc:slug "classification-rules" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:owl ;
vc:standardizedBy ngm:rdf ;
vc:supports ngm:business-rules-engine ;
vc:supports ngm:knowledge-graph ;
vc:supports ngm:natural-language-processing ;
vc:supports ngm:neuro-symbolic-ai ;
vc:uses ngm:description-logic ;
vc:uses ngm:formal-logic ;
vc:uses ngm:knowledge-graph ;
vc:uses ngm:logic-programming ;
vc:uses ngm:ontology ;
vc:uses ngm:owl ;
vc:uses ngm:rdf .
ngm:classification-scheme-database a skos:Concept ;
rdfs:label "Classification Scheme Database"@en .
ngm:classification-system a skos:Concept ;
rdfs:label "Classification System"@en .
ngm:classification-threshold a owl:Class ;
rdfs:comment "A Classification Threshold is a decision boundary applied to the probabilistic output of a classifier to assign discrete class labels. By default set at 0.5 for binary classification, the threshold can be adjusted to trade off precision against recall, or sensitivity against specificity, depending on application requirements. Threshold selection is a critical model calibration step that directly affects downstream decision quality and fairness properties."@en ;
rdfs:label "Classification Threshold"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf ngm:decision-system ;
rdfs:subClassOf ngm:model-evaluation ;
rdfs:subClassOf ngm:statistical-decision-theory ;
rdfs:subClassOf _:r4330 ;
rdfs:subClassOf _:r4331 ;
rdfs:subClassOf _:r4332 ;
rdfs:subClassOf _:r4333 ;
rdfs:subClassOf _:r4334 ;
rdfs:subClassOf _:r4335 ;
rdfs:subClassOf _:r4336 ;
rdfs:subClassOf _:r4337 ;
rdfs:subClassOf _:r4338 ;
skos:broader ngm:ai-technique ;
skos:broader ngm:artificial-intelligence ;
vc:bridgesTo ngm:active-learning ;
vc:bridgesTo ngm:bayesian-optimisation ;
vc:bridgesTo ngm:conformal-prediction ;
vc:bridgesTo ngm:mlops ;
vc:contrastsWith ngm:conformal-prediction ;
vc:contrastsWith ngm:hard-label ;
vc:contrastsWith ngm:ranking ;
vc:contrastsWith ngm:regression ;
vc:contrastsWith ngm:soft-classifier ;
vc:contrastsWith ngm:soft-label ;
vc:dependsOn ngm:class-imbalance ;
vc:dependsOn ngm:classification ;
vc:dependsOn ngm:classifier ;
vc:dependsOn ngm:confusion-matrix ;
vc:dependsOn ngm:loss-function ;
vc:dependsOn ngm:model-evaluation ;
vc:dependsOn ngm:precision ;
vc:dependsOn ngm:probability-calibration ;
vc:dependsOn ngm:recall ;
vc:dependsOn ngm:specificity ;
vc:enables ngm:ai-fairness-audit ;
vc:enables ngm:anomaly-detection ;
vc:enables ngm:clinical-decision-support ;
vc:enables ngm:cost-sensitive-learning ;
vc:enables ngm:credit-scoring ;
vc:enables ngm:decision-system ;
vc:enables ngm:fraud-detection ;
vc:enables ngm:malware-classification ;
vc:enables ngm:risk-management ;
vc:enables ngm:spam-filtering ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:confusion-matrix-slice ;
vc:hasPart ngm:cost-matrix ;
vc:hasPart ngm:f1-score ;
vc:hasPart ngm:operating-point ;
vc:hasPart ngm:precision-recall-curve ;
vc:hasPart ngm:roc-curve ;
vc:hasPart ngm:youden-j-statistic ;
vc:implements ngm:cost-sensitive-learning ;
vc:implements ngm:empirical-risk-minimisation ;
vc:implements ngm:operating-point-selection ;
vc:implements ngm:threshold-optimisation ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:adversarial-robustness ;
vc:relatedTo ngm:binary-classification ;
vc:relatedTo ngm:calibration ;
vc:relatedTo ngm:class-imbalance ;
vc:relatedTo ngm:concept-drift ;
vc:relatedTo ngm:confusion-matrix ;
vc:relatedTo ngm:covariate-shift ;
vc:relatedTo ngm:demographic-parity ;
vc:relatedTo ngm:equal-opportunity-fairness ;
vc:relatedTo ngm:f1-score ;
vc:relatedTo ngm:multi-label-classification ;
vc:relatedTo ngm:platt-scaling ;
vc:relatedTo ngm:temperature-scaling ;
vc:relatedTo ngm:youden-j-statistic ;
vc:requires ngm:classification ;
vc:requires ngm:classifier ;
vc:requires ngm:labelled-dataset ;
vc:requires ngm:machine-learning-discipline ;
vc:requires ngm:probability-calibration ;
vc:requires ngm:supervised-learning ;
vc:slug "classification-threshold" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:iso-iec-22989-2022 ;
vc:standardizedBy ngm:iso-iec-23053 ;
vc:standardizedBy ngm:mhra-samd-guidance ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:ai-audit ;
vc:supports ngm:ai-fairness ;
vc:supports ngm:ai-governance ;
vc:supports ngm:ai-model-card ;
vc:supports ngm:explainable-ai ;
vc:supports ngm:mlops ;
vc:supports ngm:regulatory-compliance ;
vc:uses ngm:auc-roc ;
vc:uses ngm:average-precision ;
vc:uses ngm:f1-score ;
vc:uses ngm:false-positive-rate ;
vc:uses ngm:matthews-correlation-coefficient ;
vc:uses ngm:precision ;
vc:uses ngm:recall ;
vc:uses ngm:sensitivity ;
vc:uses ngm:specificity ;
vc:uses ngm:true-positive-rate .
ngm:classification-token a skos:Concept ;
rdfs:label "Classification Token"@en .
ngm:classifier a owl:Class ;
rdfs:comment "A model or algorithm that assigns input instances to one of a finite set of discrete categories, typically by learning a decision function from labelled training data. Classifiers range from linear models (logistic regression, linear SVMs) through tree ensembles to deep neural networks, and most output class probabilities or scores that a decision threshold converts into hard labels. Their performance is characterised through confusion-matrix quantities such as true and false positives, precision, recall, and ROC analysis."@en ;
rdfs:label "Classifier"@en ;
rdfs:subClassOf ngm:ai-model ;
vc:contrastsWith ngm:deep-generative-model ;
vc:dependsOn ngm:supervised-learning ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:classification ;
vc:qualityScore "0.8"^^xsd:float ;
vc:slug "classifier" ;
vc:sourceDomain "machine-learning" ;
vc:uses ngm:classification-threshold .
ngm:classifier-evaluation a owl:Class ;
rdfs:comment "Classifier evaluation is the set of methods and metrics used to assess how well a trained classification model performs, covering measures such as accuracy, precision, recall, specificity and area under the ROC curve, computed against held-out labelled data. Different metrics emphasise different error costs, so evaluation practice typically reports several complementary measures rather than a single figure, particularly under class imbalance. It is a specific application of the broader discipline of model evaluation to classification tasks."@en ;
rdfs:label "Classifier Evaluation"@en ;
rdfs:subClassOf ngm:model-evaluation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:slug "classifier-evaluation" ;
vc:sourceDomain "machine-learning" .
ngm:classifier-free-guidance a owl:Class ;
rdfs:comment "Classifier-Free Guidance (CFG) is a conditional generation technique for diffusion models that steers the denoising trajectory towards a specified condition by computing a weighted extrapolation between a conditional score estimate and an unconditional score estimate produced by the same single model. Unlike classifier guidance, which requires a separately trained differentiable classifier, CFG trains one network jointly on conditional and unconditional objectives by randomly replacing conditioning inputs with a null embedding during training. At inference, the guided score is: score_guided = score_unconditional + w * (score_conditional - score_unconditional), where w is the guidance scale hyperparameter controlling the trade-off between sample diversity and condition alignment. CFG has become the dominant conditioning mechanism across text-to-image, text-to-video, and audio generation systems."@en ;
rdfs:label "Classifier-Free Guidance"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:conditional-generation ;
rdfs:subClassOf ngm:generative-ai ;
rdfs:subClassOf ngm:score-based-generative-model ;
rdfs:subClassOf _:r4347 ;
rdfs:subClassOf _:r4348 ;
rdfs:subClassOf _:r4349 ;
rdfs:subClassOf _:r4350 ;
rdfs:subClassOf _:r4351 ;
rdfs:subClassOf _:r4352 ;
rdfs:subClassOf _:r4353 ;
rdfs:subClassOf _:r4354 ;
rdfs:subClassOf _:r4355 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:reinforcement-learning-from-human-feedback ;
vc:bridgesTo ngm:reward-model ;
vc:contrastsWith ngm:autoregressive-model ;
vc:contrastsWith ngm:classifier-guidance ;
vc:contrastsWith ngm:energy-based-model ;
vc:contrastsWith ngm:flow-matching ;
vc:contrastsWith ngm:generative-adversarial-network ;
vc:contrastsWith ngm:unconditional-generation ;
vc:dependsOn ngm:attention-mechanism ;
vc:dependsOn ngm:bayesian-inference ;
vc:dependsOn ngm:dropout ;
vc:dependsOn ngm:latent-diffusion ;
vc:dependsOn ngm:markov-chain ;
vc:dependsOn ngm:score-based-generative-model ;
vc:dependsOn ngm:stochastic-differential-equation ;
vc:dependsOn ngm:vae ;
vc:dependsOn ngm:variational-inference ;
vc:enables ngm:audio-generation ;
vc:enables ngm:image-editing ;
vc:enables ngm:image-generation ;
vc:enables ngm:negative-prompting ;
vc:enables ngm:neural-radiance-field ;
vc:enables ngm:prompt-engineering ;
vc:enables ngm:score-distillation-sampling ;
vc:enables ngm:text-to-image ;
vc:enables ngm:text-to-video-generation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:conditioning-signal ;
vc:hasPart ngm:guidance-scale ;
vc:hasPart ngm:negative-prompting ;
vc:hasPart ngm:noise-schedule ;
vc:hasPart ngm:null-conditioning ;
vc:hasPart ngm:score-function ;
vc:implements ngm:bayesian-inference ;
vc:implements ngm:conditional-generation ;
vc:implements ngm:score-based-generative-model ;
vc:isPartOf ngm:generative-ai ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:bayesian-inference ;
vc:relatedTo ngm:clip ;
vc:relatedTo ngm:conditioning-signal ;
vc:relatedTo ngm:content-authentication ;
vc:relatedTo ngm:control-net ;
vc:relatedTo ngm:dall-e-3 ;
vc:relatedTo ngm:diffusion-transformer ;
vc:relatedTo ngm:energy-based-model ;
vc:relatedTo ngm:flow-matching ;
vc:relatedTo ngm:generative-ai ;
vc:relatedTo ngm:generative-model ;
vc:relatedTo ngm:image-editing ;
vc:relatedTo ngm:markov-chain ;
vc:relatedTo ngm:multimodal-ai-architecture-learning ;
vc:relatedTo ngm:neural-radiance-field ;
vc:relatedTo ngm:prompt-engineering ;
vc:relatedTo ngm:reinforcement-learning-from-human-feedback ;
vc:relatedTo ngm:reward-model ;
vc:relatedTo ngm:sampling ;
vc:relatedTo ngm:score-distillation-sampling ;
vc:relatedTo ngm:stable-diffusion-image-model ;
vc:relatedTo ngm:stochastic-differential-equation ;
vc:requires ngm:conditioning-signal ;
vc:requires ngm:noise-schedule ;
vc:requires ngm:probabilistic-model ;
vc:requires ngm:score-based-generative-model ;
vc:requires ngm:u-net ;
vc:slug "classifier-free-guidance" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:generative-ai ;
vc:supports ngm:ai-governance ;
vc:supports ngm:content-authentication ;
vc:supports ngm:generative-ai ;
vc:supports ngm:multimodal-ai-architecture-learning ;
vc:supports ngm:reward-model ;
vc:supports ngm:spatial-computing ;
vc:uses ngm:attention-mechanism ;
vc:uses ngm:clip ;
vc:uses ngm:diffusion-model ;
vc:uses ngm:diffusion-transformer ;
vc:uses ngm:knowledge-distillation ;
vc:uses ngm:latent-diffusion ;
vc:uses ngm:null-conditioning ;
vc:uses ngm:sampling ;
vc:uses ngm:score-function ;
vc:uses ngm:vae .
ngm:classifier-guidance a skos:Concept ;
rdfs:label "Classifier Guidance"@en .
ngm:classifier-model a skos:Concept ;
rdfs:label "Classifier Model"@en .
ngm:classifier-models a skos:Concept ;
rdfs:label "Classifier Models"@en .
ngm:claude a owl:Class ;
rdfs:comment "Claude is a family of large language model AI assistants developed by Anthropic, trained using Constitutional AI and reinforcement learning from human feedback to be helpful, harmless, and honest. The Claude model family encompasses tiered variants (Haiku, Sonnet, and Opus) spanning cost-performance trade-offs, with support for extended context windows, multimodal inputs, tool use, and agentic workflows via the Model Context Protocol. Claude embodies Anthropic's research programme on aligning advanced AI systems with human values, serving as both a commercial API product and a living demonstration that safety and capability are complementary rather than opposed. The model family has evolved through multiple generations, with each iteration advancing state-of-the-art performance on reasoning, coding, and instruction-following benchmarks whilst maintaining rigorous safety evaluation."@en ;
rdfs:label "Claude"@en ;
rdfs:subClassOf ngm:agentic-ai ;
rdfs:subClassOf ngm:foundation-model ;
rdfs:subClassOf ngm:large-language-model ;
rdfs:subClassOf ngm:large-language-models ;
rdfs:subClassOf ngm:proprietary-large-language-models ;
rdfs:subClassOf _:r4356 ;
rdfs:subClassOf _:r4357 ;
rdfs:subClassOf _:r4358 ;
rdfs:subClassOf _:r4359 ;
rdfs:subClassOf _:r4360 ;
rdfs:subClassOf _:r4361 ;
rdfs:subClassOf _:r4362 ;
rdfs:subClassOf _:r4363 ;
rdfs:subClassOf _:r4364 ;
rdfs:subClassOf _:r4365 ;
rdfs:subClassOf _:r4366 ;
rdfs:subClassOf _:r4367 ;
rdfs:subClassOf _:r4368 ;
rdfs:subClassOf _:r4369 ;
vc:bridgesTo ngm:ai-governance ;
vc:bridgesTo ngm:ai-safety-institute ;
vc:bridgesTo ngm:enterprise-ai-adoption ;
vc:bridgesTo ngm:enterprise-software-integration ;
vc:bridgesTo ngm:frontier-ai ;
vc:bridgesTo ngm:workflow-automation ;
vc:contrastsWith ngm:gemini-multimodal-language-model ;
vc:contrastsWith ngm:gpt-4 ;
vc:contrastsWith ngm:meta-llama-model-family ;
vc:contrastsWith ngm:meta-llama-model-family-3 ;
vc:contrastsWith ngm:openai-research-organisation ;
vc:dependsOn ngm:direct-preference-optimisation ;
vc:dependsOn ngm:human-feedback ;
vc:dependsOn ngm:instruction-tuning ;
vc:dependsOn ngm:mechanistic-interpretability ;
vc:dependsOn ngm:pre-training ;
vc:dependsOn ngm:red-teaming ;
vc:dependsOn ngm:reinforcement-learning-from-human-feedback ;
vc:enables ngm:agentic-ai ;
vc:enables ngm:agentic-workflow ;
vc:enables ngm:code-generation ;
vc:enables ngm:conversational-ai ;
vc:enables ngm:function-calling ;
vc:enables ngm:multi-step-reasoning ;
vc:enables ngm:retrieval-augmented-generation ;
vc:enables ngm:tool-use ;
vc:enables ngm:workflow-automation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:constitutional-ai-training-methodology ;
vc:hasPart ngm:direct-preference-optimisation ;
vc:hasPart ngm:instruction-tuning ;
vc:hasPart ngm:model-context-protocol ;
vc:hasPart ngm:pre-training ;
vc:hasPart ngm:red-teaming ;
vc:hasPart ngm:rlhf ;
vc:implements ngm:ai-model-card ;
vc:implements ngm:ai-safety ;
vc:implements ngm:constitutional-ai-training-methodology ;
vc:implements ngm:model-context-protocol ;
vc:implements ngm:responsible-scaling-policy ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:ai-alignment ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:alignment-research ;
vc:relatedTo ngm:anthropic ;
vc:relatedTo ngm:enterprise-ai-adoption ;
vc:relatedTo ngm:foundation-model ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:mechanistic-interpretability ;
vc:relatedTo ngm:red-teaming ;
vc:relatedTo ngm:responsible-scaling-policy ;
vc:relatedTo ngm:scalable-oversight ;
vc:requires ngm:human-feedback ;
vc:requires ngm:instruction-tuning ;
vc:requires ngm:large-language-models ;
vc:requires ngm:pre-training ;
vc:requires ngm:reinforcement-learning-from-human-feedback ;
vc:requires ngm:scalable-oversight ;
vc:requires ngm:transformer-architecture ;
vc:slug "claude" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:model-context-protocol ;
vc:standardizedBy ngm:responsible-scaling-policy ;
vc:supports ngm:ai-alignment ;
vc:supports ngm:ai-safety ;
vc:supports ngm:ai-safety-research ;
vc:supports ngm:enterprise-ai-adoption ;
vc:supports ngm:mechanistic-interpretability ;
vc:supports ngm:scalable-oversight ;
vc:uses ngm:agentic-workflow ;
vc:uses ngm:constitutional-ai-training-methodology ;
vc:uses ngm:direct-preference-optimisation ;
vc:uses ngm:instruction-tuning ;
vc:uses ngm:mechanistic-interpretability ;
vc:uses ngm:red-teaming ;
vc:uses ngm:rlhf ;
vc:uses ngm:transformer-architecture .
ngm:claude-3-5 a skos:Concept ;
rdfs:label "Claude 3 5"@en .
ngm:claude-agent-sdk a skos:Concept ;
rdfs:label "Claude Agent SDK"@en .
ngm:claude-co-work a owl:Class ;
rdfs:comment "A feature of Anthropic's Claude AI that enables collaborative work environments with file access, multi-step task execution, and plugin integration across platforms."@en ;
rdfs:label "Claude Co-work"@en ;
rdfs:subClassOf ngm:model ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:mcp-connectors ;
vc:relatedTo ngm:model ;
vc:slug "claude-co-work" ;
vc:sourceDomain "artificial-intelligence" .
ngm:claude-code a owl:Class ;
rdfs:comment "A command-line interface and agentic coding tool developed by Anthropic that enables developers to execute complex software engineering tasks using the Claude model family."@en ;
rdfs:label "Claude Code"@en ;
rdfs:subClassOf ngm:claude ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:agentic-workflow ;
vc:relatedTo ngm:claude ;
vc:relatedTo ngm:tool-use ;
vc:slug "claude-code" ;
vc:sourceDomain "artificial-intelligence" .
ngm:claude-code-claude-md-convention a skos:Concept ;
rdfs:label "Claude Code Claude Md Convention"@en .
ngm:claude-design a owl:Class ;
rdfs:comment "A design tool within the Claude ecosystem that generates visual elements using code and SVGs, featuring customizable parameters and positioned for systems design."@en ;
rdfs:label "Claude Design"@en ;
rdfs:subClassOf ngm:claude ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:claude ;
vc:relatedTo ngm:image-generation ;
vc:slug "claude-design" ;
vc:sourceDomain "artificial-intelligence" .
ngm:claude-sonnet a skos:Concept ;
rdfs:label "Claude Sonnet"@en .
ngm:claudette a skos:Concept ;
rdfs:label "Claudette"@en .
ngm:clay-mathematics-institute a skos:Concept ;
rdfs:label "Clay Mathematics Institute"@en .
ngm:clean-architecture a skos:Concept ;
rdfs:label "Clean Architecture"@en .
ngm:clean-energy-transition a skos:Concept ;
rdfs:label "Clean Energy Transition"@en .
ngm:clean-fid a skos:Concept ;
rdfs:label "Clean Fid"@en .
ngm:clean-spark a owl:Class ;
rdfs:comment "A publicly traded company that operates Bitcoin mining facilities in the United States, focusing on the use of low-cost and lower-carbon energy sources."@en ;
rdfs:label "CleanSpark"@en ;
rdfs:subClassOf ngm:bitcoin-proof-of-work-protocol-mining ;
rdfs:subClassOf _:r4370 ;
rdfs:subClassOf _:r4371 ;
vc:bridgesTo ngm:mining ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:bitcoin-proof-of-work-protocol ;
vc:requires ngm:bitcoin-proof-of-work-protocol-mining ;
vc:slug "clean-spark" ;
vc:sourceDomain "blockchain" .
ngm:cleanroom a skos:Concept ;
rdfs:label "Cleanroom"@en .
ngm:clearing a owl:Class ;
rdfs:comment "Clearing is the post-trade process of confirming, matching and managing the obligations arising from a transaction in the interval between execution and settlement. A clearing house, often acting as a central counterparty, novates trades and nets exposures, calculating the net obligations of each party and managing counterparty credit risk through margin and default funds. Clearing reduces systemic risk and operational burden in securities, derivatives and payment markets."@en ;
rdfs:label "Clearing"@en ;
rdfs:subClassOf ngm:financial-market-infrastructure ;
rdfs:subClassOf _:r4378 ;
rdfs:subClassOf _:r4379 ;
rdfs:subClassOf _:r4380 ;
vc:bridgesTo ngm:financial-infrastructure ;
vc:contrastsWith ngm:settlement ;
vc:dependsOn ngm:clearing-house ;
vc:enables ngm:settlement ;
vc:enables ngm:trade-execution ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:trade-execution ;
vc:isPartOf ngm:financial-market-infrastructure ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:custody ;
vc:relatedTo ngm:payment-system ;
vc:requires ngm:clearing-house ;
vc:requires ngm:risk-management ;
vc:slug "clearing" ;
vc:sourceDomain "finance" ;
vc:supports ngm:capital-markets ;
vc:supports ngm:payment-processing ;
vc:uses ngm:clearing-house .
ngm:clearing-and-settlement a owl:Class ;
rdfs:comment "Clearing and settlement are the post-trade processes that finalise a financial transaction: clearing reconciles, nets and confirms the obligations between counterparties, while settlement effects the actual transfer of securities and funds to discharge those obligations. Central counterparties and securities depositories reduce counterparty risk by interposing themselves and managing margin. The integrity of these processes underpins the stability of payment and securities markets."@en ;
rdfs:label "Clearing And Settlement"@en ;
rdfs:subClassOf ngm:financial-infrastructure ;
rdfs:subClassOf _:r4372 ;
rdfs:subClassOf _:r4373 ;
rdfs:subClassOf _:r4374 ;
rdfs:subClassOf _:r4375 ;
rdfs:subClassOf _:r4376 ;
vc:dependsOn ngm:payment-system ;
vc:enables ngm:cross-border-settlement ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:payment-settlement ;
vc:hasPart ngm:securities-settlement ;
vc:hasPart ngm:settlement ;
vc:implements ngm:settlement ;
vc:isPartOf ngm:financial-infrastructure ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:kyc-aml-compliance ;
vc:relatedTo ngm:payment-processing ;
vc:requires ngm:financial-infrastructure ;
vc:requires ngm:payment-system ;
vc:slug "clearing-and-settlement" ;
vc:sourceDomain "finance" ;
vc:standardizedBy ngm:central-bank ;
vc:supports ngm:order-book ;
vc:uses ngm:atomic-settlement ;
vc:uses ngm:real-time-gross-settlement .
ngm:clearing-house a owl:Class ;
rdfs:comment "A clearing house is a financial market intermediary that stands between the buyers and sellers of a trade to guarantee its completion, most often acting as a central counterparty that legally interposes itself through novation. By collecting margin, mutualising risk across a default fund, and netting offsetting obligations, it reduces counterparty credit risk and systemic contagion in securities, derivatives, and payment markets. Clearing houses are critical financial market infrastructure, subject to stringent prudential supervision because their failure could propagate across the financial system."@en ;
rdfs:label "Clearing House"@en ;
rdfs:subClassOf ngm:financial-market-infrastructure ;
rdfs:subClassOf _:r4377 ;
vc:enables ngm:financial-stability ;
vc:enables ngm:settlement-finality ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:central-counterparty ;
vc:hasPart ngm:default-management ;
vc:hasPart ngm:margin ;
vc:hasPart ngm:netting ;
vc:implements ngm:clearing ;
vc:implements ngm:settlement ;
vc:isPartOf ngm:financial-market-infrastructure ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:central-bank ;
vc:relatedTo ngm:institutional-trust ;
vc:slug "clearing-house" ;
vc:sourceDomain "finance" ;
vc:supports ngm:derivatives ;
vc:uses ngm:collateral ;
vc:uses ngm:risk-management .
ngm:clearing-mechanism a skos:Concept ;
rdfs:label "Clearing Mechanism"@en .
ngm:clearview-ai a skos:Concept ;
rdfs:label "Clearview AI"@en .
ngm:cli-multi-agent-systems a owl:Class ;
rdfs:comment "CLI multi-agent systems are software architectures in which networks of autonomous AI agents operate natively within command-line and terminal environments, coordinating to decompose, plan, and execute complex long-horizon tasks through tool invocation, sandboxed code execution, inter-agent messa..."@en ;
rdfs:label "CLI Multi-Agent Systems"@en ;
rdfs:subClassOf ngm:agentic-workflow ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:autonomous-agent ;
rdfs:subClassOf ngm:llm-agents ;
rdfs:subClassOf ngm:multi-agent-systems ;
rdfs:subClassOf ngm:tool-use ;
rdfs:subClassOf _:r3745 ;
rdfs:subClassOf _:r3746 ;
rdfs:subClassOf _:r3747 ;
rdfs:subClassOf _:r3748 ;
rdfs:subClassOf _:r3749 ;
rdfs:subClassOf _:r3750 ;
rdfs:subClassOf _:r3751 ;
rdfs:subClassOf _:r3752 ;
rdfs:subClassOf _:r3753 ;
rdfs:subClassOf _:r3754 ;
skos:broader ngm:ai-application ;
vc:bridgesTo ngm:autonomous-agent ;
vc:contrastsWith ngm:chatbot ;
vc:contrastsWith ngm:robotic-process-automation ;
vc:contrastsWith ngm:single-agent-system ;
vc:contrastsWith ngm:static-analysis ;
vc:contrastsWith ngm:traditional-ci-cd ;
vc:dependsOn ngm:function-calling ;
vc:dependsOn ngm:large-language-model ;
vc:dependsOn ngm:orchestration ;
vc:dependsOn ngm:prompt-engineering ;
vc:dependsOn ngm:reinforcement-learning-from-human-feedback ;
vc:dependsOn ngm:vector-database ;
vc:enables ngm:agentic-workflow ;
vc:enables ngm:automated-code-review ;
vc:enables ngm:autonomous-debugging ;
vc:enables ngm:ci-cd-automation ;
vc:enables ngm:dev-sec-ops ;
vc:enables ngm:repository-scale-refactoring ;
vc:enables ngm:software-engineering-agents ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:agent-orchestrator ;
vc:hasPart ngm:inter-agent-communication ;
vc:hasPart ngm:planning-agent ;
vc:hasPart ngm:sandbox-environment ;
vc:hasPart ngm:state-management ;
vc:hasPart ngm:task-decomposition ;
vc:hasPart ngm:tool-catalogue ;
vc:hasPart ngm:worker-agent ;
vc:implements ngm:agent2-agent-protocol ;
vc:implements ngm:auto-gen ;
vc:implements ngm:codeact ;
vc:implements ngm:crew-ai ;
vc:implements ngm:lang-graph ;
vc:implements ngm:model-context-protocol ;
vc:implements ngm:re-act ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:auto-gen ;
vc:relatedTo ngm:autonomous-agent ;
vc:relatedTo ngm:code-execution ;
vc:relatedTo ngm:crew-ai ;
vc:relatedTo ngm:lang-graph ;
vc:relatedTo ngm:llm-agents ;
vc:relatedTo ngm:orchestration ;
vc:relatedTo ngm:tool-use ;
vc:requires ngm:function-calling ;
vc:requires ngm:large-language-model ;
vc:requires ngm:large-language-models ;
vc:requires ngm:orchestration-protocol ;
vc:requires ngm:sandboxed-code-execution ;
vc:requires ngm:shell-environment ;
vc:requires ngm:tool-schema ;
vc:slug "cli-multi-agent-systems" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:agent2-agent-protocol ;
vc:standardizedBy ngm:model-context-protocol ;
vc:standardizedBy ngm:openai-research-organisation-agents-sdk ;
vc:supports ngm:agentic-workflow ;
vc:supports ngm:automated-testing ;
vc:supports ngm:code-execution ;
vc:supports ngm:dev-sec-ops ;
vc:supports ngm:human-in-the-loop-learning ;
vc:supports ngm:software-engineering-agents ;
vc:supports ngm:task-decomposition ;
vc:uses ngm:bash ;
vc:uses ngm:docker-containerisation-platform ;
vc:uses ngm:firecracker ;
vc:uses ngm:git ;
vc:uses ngm:model-context-protocol ;
vc:uses ngm:open-telemetry ;
vc:uses ngm:python .
ngm:click-tracking a skos:Concept ;
rdfs:label "Click Tracking"@en .
ngm:clickstream a skos:Concept ;
rdfs:label "Clickstream"@en .
ngm:client-activity-tracking a skos:Concept ;
rdfs:label "Client Activity Tracking"@en .
ngm:client-application a skos:Concept ;
rdfs:label "Client Application"@en .
ngm:client-credentials-flow a skos:Concept ;
rdfs:label "Client Credentials Flow"@en .
ngm:client-implementation a skos:Concept ;
rdfs:label "Client Implementation"@en .
ngm:client-server-architecture a owl:Class ;
rdfs:comment "Client-server architecture is a distributed computing model in which client processes request services or resources and dedicated server processes provide them, typically over a network. The model centralises shared resources, data and logic on servers while distributing presentation and interaction to many clients. It is the foundational pattern for the web, networked applications and most online services, and it contrasts with peer-to-peer architectures where every node is both provider and consumer."@en ;
rdfs:label "Client-Server Architecture"@en ;
rdfs:subClassOf ngm:distributed-architecture ;
rdfs:subClassOf _:r4381 ;
rdfs:subClassOf _:r4382 ;
rdfs:subClassOf _:r4383 ;
vc:contrastsWith ngm:microservices ;
vc:enables ngm:scalability ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:api ;
vc:implements ngm:rest ;
vc:isPartOf ngm:distributed-architecture ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:distributed-systems ;
vc:relatedTo ngm:stateless-protocol ;
vc:requires ngm:http ;
vc:requires ngm:network-protocol ;
vc:slug "client-server-architecture" ;
vc:sourceDomain "distributed-systems" ;
vc:supports ngm:load-balancing ;
vc:uses ngm:api ;
vc:uses ngm:http .
ngm:client-side-scanning a skos:Concept ;
rdfs:label "Client Side Scanning"@en .
ngm:client-side-validation a owl:Class ;
rdfs:comment "Client-Side Validation is the process of verifying user-supplied data within the browser or client application before that data is transmitted to a server, providing immediate feedback to users and reducing unnecessary network requests. In the context of Bitcoin and RGB Protocol, it refers to a distinct validation paradigm where the full state of off-chain assets is verified locally by the recipient rather than by all network nodes, enabling scalable, private asset transfers. The two usages share the principle of local verification but differ fundamentally in their security models and scope."@en ;
rdfs:label "Client-Side Validation"@en ;
rdfs:subClassOf ngm:data-integrity ;
rdfs:subClassOf _:r4384 ;
rdfs:subClassOf _:r4385 ;
rdfs:subClassOf _:r4386 ;
vc:contrastsWith ngm:ethereum-smart-contract-platform-smart-contracts ;
vc:dependsOn ngm:bitcoin-proof-of-work-protocol-network ;
vc:dependsOn ngm:utxo-model ;
vc:enables ngm:block-trails ;
vc:enables ngm:rgb-protocol ;
vc:enables ngm:web-contracts ;
vc:enables ngm:zero-knowledge-proof ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:proof-of-publication ;
vc:hasPart ngm:single-use-seals ;
vc:hasPart ngm:state-transition-function ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:layer-2-solutions ;
vc:relatedTo ngm:taproot-assets ;
vc:relatedTo ngm:zero-knowledge ;
vc:slug "client-side-validation" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:privacy-preserving-computation ;
vc:uses ngm:cryptographic-commitment ;
vc:uses ngm:cryptographic-proof ;
vc:uses ngm:json-data-interchange-format-schema ;
vc:uses ngm:utxo .
ngm:client-side-validation-theory a owl:Class ;
rdfs:comment "Client-side validation theory is the conceptual framework in which the validity of state transitions is verified by the affected parties themselves rather than by every node of a global consensus layer, with the blockchain used only to commit to and order single-use seals. Data and proofs are kept off-chain and shared peer-to-peer, so the base chain provides ordering and double-spend prevention without learning transaction contents. It matters because it underpins scalable, private smart-contract systems such as RGB that inherit Bitcoin's security without bloating its chain."@en ;
rdfs:label "Client-Side Validation Theory"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:rgb-and-client-side-validation ;
vc:slug "client-side-validation-theory" ;
vc:sourceDomain "blockchain" .
ngm:cliff-period a skos:Concept ;
rdfs:label "Cliff Period"@en .
ngm:climate-action a owl:Class ;
rdfs:comment "Climate action refers to coordinated efforts to mitigate climate change by reducing greenhouse-gas emissions and to adapt human and natural systems to its impacts. It spans policy, finance, technology and behaviour, from decarbonising energy and transport to protecting ecosystems and building resilience against extreme weather. Frameworks such as the Paris Agreement set the shared goal of limiting global warming, and pathways toward net zero translate that goal into concrete reductions across economies and supply chains."@en ;
rdfs:label "Climate Action"@en ;
rdfs:subClassOf ngm:environmental-sustainability ;
rdfs:subClassOf _:r4400 ;
rdfs:subClassOf _:r4401 ;
rdfs:subClassOf _:r4402 ;
rdfs:subClassOf _:r4403 ;
vc:dependsOn ngm:renewable-energy ;
vc:enables ngm:carbon-neutrality ;
vc:enables ngm:net-zero ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:carbon-neutrality ;
vc:hasPart ngm:decarbonisation ;
vc:isPartOf ngm:sustainable-development ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:carbon-footprint ;
vc:relatedTo ngm:circular-economy ;
vc:relatedTo ngm:climate-change ;
vc:requires ngm:decarbonisation ;
vc:requires ngm:renewable-energy ;
vc:slug "climate-action" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:paris-agreement ;
vc:supports ngm:esg ;
vc:supports ngm:sustainability ;
vc:uses ngm:carbon-accounting ;
vc:uses ngm:lifecycle-assessment .
ngm:climate-action-dao a owl:Class ;
rdfs:comment "A decentralized autonomous organization (DAO) governed by blockchain-based smart contracts and token-weighted voting that coordinates collective action toward climate change mitigation, adaptation, and environmental sustainability through transparent, democratic mechanisms for funding climate pro..."@en ;
rdfs:label "Climate Action DAO"@en ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
rdfs:subClassOf ngm:climatefinance ;
rdfs:subClassOf ngm:collective-governance ;
rdfs:subClassOf ngm:decentralized-autonomous-organization ;
rdfs:subClassOf ngm:impactinvestment ;
rdfs:subClassOf _:r4387 ;
rdfs:subClassOf _:r4388 ;
rdfs:subClassOf _:r4389 ;
rdfs:subClassOf _:r4390 ;
rdfs:subClassOf _:r4391 ;
rdfs:subClassOf _:r4392 ;
rdfs:subClassOf _:r4393 ;
rdfs:subClassOf _:r4394 ;
rdfs:subClassOf _:r4395 ;
rdfs:subClassOf _:r4396 ;
rdfs:subClassOf _:r4397 ;
rdfs:subClassOf _:r4398 ;
rdfs:subClassOf _:r4399 ;
skos:broader ngm:bc-governance-and-regulation ;
vc:bridgesTo ngm:collective-governance ;
vc:bridgesTo ngm:governance ;
vc:enables ngm:carbon-credit-retirement ;
vc:enables ngm:carboncreditretirement ;
vc:enables ngm:climate-finance ;
vc:enables ngm:community-coordination ;
vc:enables ngm:transparent-governance ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:governance-token ;
vc:hasPart ngm:impact-metrics ;
vc:hasPart ngm:impactmetrics ;
vc:hasPart ngm:proposal-system ;
vc:hasPart ngm:treasury-management ;
vc:hasPart ngm:voting-mechanism ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:community-participation ;
vc:requires ngm:communityparticipation ;
vc:requires ngm:impactverification ;
vc:requires ngm:smart-contracts ;
vc:requires ngm:token-economics ;
vc:slug "climate-action-dao" ;
vc:sourceDomain "blockchain" .
ngm:climate-action-planning a skos:Concept ;
rdfs:label "Climate Action Planning"@en .
ngm:climate-adaptation a skos:Concept ;
rdfs:label "Climate Adaptation"@en .
ngm:climate-change a owl:Class ;
rdfs:comment "Climate change refers to long-term shifts in temperatures and weather patterns, driven predominantly since the industrial era by human emissions of greenhouse gases that trap heat in the atmosphere. Its impacts include rising sea levels, more frequent extreme weather, ecosystem disruption and threats to food, water and economic systems. Responses span mitigation (reducing emissions) and adaptation (managing unavoidable impacts), coordinated through policy frameworks such as the Paris Agreement."@en ;
rdfs:label "Climate Change"@en ;
rdfs:subClassOf ngm:sustainability ;
rdfs:subClassOf _:r4405 ;
rdfs:subClassOf _:r4406 ;
vc:bridgesTo ngm:carbon-offsetting ;
vc:bridgesTo ngm:net-zero ;
vc:dependsOn ngm:greenhouse-gas-emissions ;
vc:enables ngm:climate-risk ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:sustainability ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:climate-risk ;
vc:relatedTo ngm:environmental-sustainability ;
vc:relatedTo ngm:esg ;
vc:requires ngm:climate-action ;
vc:requires ngm:decarbonisation ;
vc:slug "climate-change" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:paris-agreement ;
vc:supports ngm:renewable-energy .
ngm:climate-change-mitigation a owl:Class ;
rdfs:comment "Efforts to reduce or prevent the emission of greenhouse gases and to enhance their removal from the atmosphere, with the aim of limiting the extent of climate change. It includes shifting to low-carbon energy and improving efficiency."@en ;
rdfs:label "Climate Change Mitigation"@en ;
rdfs:subClassOf ngm:sustainability ;
rdfs:subClassOf _:r4404 ;
vc:bridgesTo ngm:sustainability ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:renewable-energy ;
vc:slug "climate-change-mitigation" ;
vc:sourceDomain "governance" .
ngm:climate-commitments a owl:Class ;
rdfs:comment "Climate commitments are formal pledges by governments, companies, or coalitions to achieve specified greenhouse-gas reduction or removal outcomes by defined dates, such as net-zero or science-based emissions targets. They typically combine a headline goal with interim milestones, accounting boundaries, and reporting obligations to make progress verifiable. They matter as the governance mechanism that translates climate ambition into measurable, accountable action and that shapes corporate sustainability and offsetting strategies."@en ;
rdfs:label "Climate Commitments"@en ;
rdfs:subClassOf ngm:sustainability ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:carbon-neutral-blockchain ;
vc:relatedTo ngm:net-zero-targets ;
vc:slug "climate-commitments" ;
vc:sourceDomain "governance" .
ngm:climate-data-record a owl:Class ;
rdfs:label "Climate Data Record"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-data-quality ;
vc:relatedTo ngm:earth-observation-processing ;
vc:slug "climate-data-record" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:climate-disclosure a skos:Concept ;
rdfs:label "Climate Disclosure"@en .
ngm:climate-fever a skos:Concept ;
rdfs:label "Climate Fever"@en .
ngm:climate-finance a owl:Class ;
rdfs:comment "Climate finance encompasses the local, national, and transnational flow of funds — drawn from public, private, and blended sources — directed at activities that mitigate greenhouse gas emissions or support adaptation to the adverse effects of climate change. It operates through a range of instruments including grants, concessional loans, guarantees, equity investment, and market-based mechanisms such as carbon credits. Internationally, climate finance is governed by commitments under the UNFCCC and the Paris Agreement, which established obligations for developed nations to mobilise and transfer funds to developing countries. The field intersects investment policy, sovereign risk, environmental regulation, and multilateral development banking."@en ;
rdfs:label "Climate Finance"@en ;
rdfs:subClassOf ngm:green-finance ;
rdfs:subClassOf _:r4407 ;
rdfs:subClassOf _:r4408 ;
rdfs:subClassOf _:r4409 ;
rdfs:subClassOf _:r4410 ;
vc:bridgesTo ngm:de-fi ;
vc:bridgesTo ngm:supply-chain-sustainability ;
vc:bridgesTo ngm:tokenised-carbon-credits ;
vc:contrastsWith ngm:fossil-fuel-subsidies ;
vc:dependsOn ngm:climate-policy ;
vc:dependsOn ngm:multilateral-development-banks ;
vc:enables ngm:carbon-markets ;
vc:enables ngm:climate-adaptation ;
vc:enables ngm:renewable-energy ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:blended-finance ;
vc:hasPart ngm:carbon-credits ;
vc:hasPart ngm:climate-risk-insurance ;
vc:hasPart ngm:green-bonds ;
vc:isPartOf ngm:green-finance ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:climate-disclosure ;
vc:relatedTo ngm:impact-investing ;
vc:relatedTo ngm:sovereign-green-bonds ;
vc:requires ngm:climate-risk-assessment ;
vc:requires ngm:esg-reporting ;
vc:slug "climate-finance" ;
vc:sourceDomain "finance" ;
vc:standardizedBy ngm:eu-taxonomy ;
vc:standardizedBy ngm:paris-agreement ;
vc:standardizedBy ngm:unfccc ;
vc:supports ngm:net-zero-transition ;
vc:supports ngm:sustainability ;
vc:supports ngm:sustainable-development-goals .
ngm:climate-financial-risk a skos:Concept ;
rdfs:label "Climate Financial Risk"@en .
ngm:climate-governance a owl:Class ;
rdfs:comment "Climate governance is the system of institutions, policies, agreements and accountability mechanisms through which societies steer collective action on climate change. It spans international treaties, national legislation, sub-national and corporate commitments, and the monitoring, reporting and verification arrangements that hold actors to their pledges. By coordinating mitigation and adaptation across scales, climate governance translates scientific assessment into binding and voluntary obligations. It draws on instruments such as carbon pricing, emissions targets and disclosure regimes to align economic activity with environmental limits."@en ;
rdfs:label "Climate Governance"@en ;
rdfs:subClassOf ngm:governance ;
rdfs:subClassOf _:r4411 ;
rdfs:subClassOf _:r4412 ;
rdfs:subClassOf _:r4413 ;
rdfs:subClassOf _:r4414 ;
rdfs:subClassOf _:r4415 ;
rdfs:subClassOf _:r4416 ;
vc:bridgesTo ngm:decarbonisation ;
vc:enables ngm:net-zero ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:esg-reporting ;
vc:hasPart ngm:paris-agreement ;
vc:hasPart ngm:sustainability-reporting ;
vc:implements ngm:climate-policy ;
vc:implements ngm:net-zero ;
vc:isPartOf ngm:governance ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:circular-economy ;
vc:relatedTo ngm:climate-policy ;
vc:relatedTo ngm:renewable-energy ;
vc:requires ngm:scope-3-emissions ;
vc:slug "climate-governance" ;
vc:sourceDomain "governance" ;
vc:supports ngm:carbon-footprint ;
vc:supports ngm:decarbonisation ;
vc:uses ngm:greenhouse-gas-protocol ;
vc:uses ngm:life-cycle-assessment .
ngm:climate-governance-frameworks a skos:Concept ;
rdfs:label "Climate Governance Frameworks"@en .
ngm:climate-investment a skos:Concept ;
rdfs:label "Climate Investment"@en .
ngm:climate-justice a skos:Concept ;
rdfs:label "Climate Justice"@en .
ngm:climate-modelling a owl:Class ;
rdfs:comment "Climate Modelling is the scientific discipline of constructing mathematical and computational representations of Earth's climate system to simulate past, present, and future climate states. Models range from simple energy-balance equations to high-resolution coupled atmosphere-ocean-land-ice systems running on supercomputing infrastructure. They underpin global projections published by the Intergovernmental Panel on Climate Change and inform policy decisions on emissions reduction and adaptation. Machine learning is increasingly integrated to accelerate parameterisation and downscaling. Outputs feed directly into carbon accounting, sustainability planning, and digital twin applications."@en ;
rdfs:label "Climate Modelling"@en ;
rdfs:subClassOf ngm:digital-twin ;
rdfs:subClassOf _:r4417 ;
vc:bridgesTo ngm:digital-twin-of-society-dto-s ;
vc:bridgesTo ngm:smart-city-infrastructure ;
vc:bridgesTo ngm:supply-chain-resilience ;
vc:dependsOn ngm:parallel-computing ;
vc:enables ngm:carbon-footprint-measurement ;
vc:enables ngm:carbon-neutrality-planning ;
vc:enables ngm:climate-risk-assessment ;
vc:enables ngm:sustainability-reporting ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:environmental-sustainability ;
vc:relatedTo ngm:iso-14064 ;
vc:requires ngm:high-performance-computing ;
vc:slug "climate-modelling" ;
vc:sourceDomain "data" ;
vc:uses ngm:gpu-acceleration ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:neural-network ;
vc:uses ngm:time-series-forecasting .
ngm:climate-pledges a skos:Concept ;
rdfs:label "Climate Pledges"@en .
ngm:climate-policy a owl:Class ;
rdfs:comment "Climate policy is the set of government measures, regulations, and commitments intended to reduce greenhouse gas emissions and address the effects of climate change."@en ;
rdfs:label "Climate Policy"@en ;
rdfs:subClassOf ngm:sustainability ;
vc:bridgesTo ngm:energy-consumption ;
vc:bridgesTo ngm:greenwashing ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:slug "climate-policy" ;
vc:sourceDomain "governance" .
ngm:climate-regulation a skos:Concept ;
rdfs:label "Climate Regulation"@en .
ngm:climate-related-financial-risk a skos:Concept ;
rdfs:label "Climate Related Financial Risk"@en .
ngm:climate-risk a owl:Class ;
rdfs:comment "Climate risk is the set of financial, operational and strategic threats that arise from climate change and the transition to a low-carbon economy. It is conventionally divided into physical risk, stemming from acute and chronic climate impacts, and transition risk, arising from policy, technology, market and reputational shifts. Organisations assess and disclose climate risk to inform capital allocation, resilience planning and regulatory compliance."@en ;
rdfs:label "Climate Risk"@en ;
rdfs:subClassOf ngm:risk-management ;
rdfs:subClassOf _:r4418 ;
rdfs:subClassOf _:r4419 ;
vc:bridgesTo ngm:financial-regulation ;
vc:bridgesTo ngm:sustainability-reporting ;
vc:dependsOn ngm:ghg-protocol ;
vc:enables ngm:disclosure ;
vc:enables ngm:disclosure-requirements ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:physical-risk ;
vc:hasPart ngm:transition-risk ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:carbon-accounting ;
vc:relatedTo ngm:climate-change ;
vc:relatedTo ngm:esg ;
vc:relatedTo ngm:existential-risk ;
vc:requires ngm:climate-scenario-analysis ;
vc:requires ngm:materiality-assessment ;
vc:slug "climate-risk" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:issb ;
vc:standardizedBy ngm:tcfd ;
vc:supports ngm:corporate-governance ;
vc:supports ngm:sustainable-finance .
ngm:climate-risk-assessment a owl:Class ;
rdfs:comment "Climate risk assessment is the structured process of identifying, quantifying, and prioritising the physical and transition risks that climate change poses to an asset, portfolio, or institution. Physical risk assessment models exposure to acute events such as floods and storms alongside chronic shifts such as sea-level rise and heat stress, while transition risk assessment evaluates exposure to policy, technology, and market shifts away from carbon-intensive activity. It draws on climate modelling outputs to translate physical hazard projections into financial or operational impact estimates, and is increasingly required under disclosure frameworks such as TCFD. Results feed into climate finance decisions, capital allocation, and regulatory reporting."@en ;
rdfs:label "Climate Risk Assessment"@en ;
rdfs:subClassOf ngm:climate-risk ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.0"^^xsd:float ;
vc:slug "climate-risk-assessment" ;
vc:sourceDomain "governance" .
ngm:climate-risk-disclosure a skos:Concept ;
rdfs:label "Climate Risk Disclosure"@en .
ngm:climate-risk-insurance a skos:Concept ;
rdfs:label "Climate Risk Insurance"@en .
ngm:climate-risk-management a skos:Concept ;
rdfs:label "Climate Risk Management"@en .
ngm:climate-risk-pricing a skos:Concept ;
rdfs:label "Climate Risk Pricing"@en .
ngm:climate-scenario-analysis a owl:Class ;
rdfs:comment "Climate scenario analysis is a structured method for exploring how an organisation's assets, operations, or investments might perform under different plausible future climate and policy pathways, such as varying degrees of global warming or rates of decarbonisation. It typically models physical risks, including extreme weather and chronic climate shifts, and transition risks, including policy, technology, and market changes, against defined time horizons. Climate scenario analysis informs climate risk disclosure and materiality assessment frameworks used by regulators and investors to evaluate long-term financial resilience."@en ;
rdfs:label "Climate Scenario Analysis"@en ;
rdfs:subClassOf ngm:climate-risk ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:slug "climate-scenario-analysis" ;
vc:sourceDomain "governance" .
ngm:climate-scenario-database a skos:Concept ;
rdfs:label "Climate Scenario Database"@en .
ngm:climate-science a skos:Concept ;
rdfs:label "Climate Science"@en .
ngm:climate-stress-testing a skos:Concept ;
rdfs:label "Climate Stress Testing"@en .
ngm:climate-tech a owl:Class ;
rdfs:comment "Climate Tech encompasses the portfolio of technologies, platforms, and business models designed to mitigate greenhouse gas emissions, support climate adaptation, and accelerate the energy transition. It spans renewable energy generation, energy storage, carbon capture and removal, sustainable agriculture, climate risk analytics, and digital tools for emissions measurement and reporting. Climate Tech investment has grown into a distinct venture capital and corporate innovation category, underpinned by regulatory drivers, net-zero commitments, and the rapid cost-reduction curves of clean energy technologies."@en ;
rdfs:label "Climate Tech"@en ;
rdfs:subClassOf ngm:sustainability ;
vc:enables ngm:carbon-markets ;
vc:enables ngm:net-zero-targets ;
vc:enables ngm:renewable-energy ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:carbon-credits ;
vc:relatedTo ngm:esg-reporting ;
vc:relatedTo ngm:sustainable-finance ;
vc:slug "climate-tech" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:environmental-monitoring ;
vc:uses ngm:machine-learning-discipline .
ngm:climatetrade a skos:Concept ;
rdfs:label "Climatetrade"@en .
ngm:cline a skos:Concept ;
rdfs:label "Cline"@en .
ngm:clinical-ai a skos:Concept ;
rdfs:label "Clinical AI"@en .
ngm:clinical-ai-deployment a skos:Concept ;
rdfs:label "Clinical AI Deployment"@en .
ngm:clinical-assessment a skos:Concept ;
rdfs:label "Clinical Assessment"@en .
ngm:clinical-decision-support a owl:Class ;
rdfs:comment "Clinical Decision Support (CDS) refers to AI systems that provide healthcare professionals with patient-specific assessments, recommendations, and information to support clinical decision-making at the point of care. CDS systems integrate patient data, medical knowledge bases, clinical guidelines, and evidence-based protocols to assist in diagnosis, treatment selection, medication management, and care coordination whilst maintaining clinician autonomy and clinical judgement."@en ;
rdfs:label "Clinical Decision Support"@en ;
rdfs:subClassOf ngm:medical-ai ;
rdfs:subClassOf _:r4420 ;
rdfs:subClassOf _:r4421 ;
rdfs:subClassOf _:r4422 ;
rdfs:subClassOf _:r4423 ;
vc:bridgesTo ngm:healthcare-analytics ;
vc:bridgesTo ngm:telecollaboration ;
vc:contrastsWith ngm:autonomous-medical-ai ;
vc:enables ngm:medical-diagnosis-ai ;
vc:enables ngm:medication-safety ;
vc:enables ngm:treatment-planning-ai ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:isPartOf ngm:electronic-health-record ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:explainable-ai ;
vc:relatedTo ngm:health-data-privacy ;
vc:requires ngm:data-integration ;
vc:requires ngm:electronic-health-record ;
vc:requires ngm:interoperability ;
vc:requires ngm:knowledge-base ;
vc:slug "clinical-decision-support" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:hl7-fhir ;
vc:supports ngm:evidence-based-medicine ;
vc:supports ngm:patient-safety ;
vc:uses ngm:knowledge-representation ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:medical-ai ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:rule-based-systems .
ngm:clinical-documentation a skos:Concept ;
rdfs:label "Clinical Documentation"@en .
ngm:clinical-gait-analysis a skos:Concept ;
rdfs:label "Clinical Gait Analysis"@en .
ngm:clinical-genomics a skos:Concept ;
rdfs:label "Clinical Genomics"@en .
ngm:clinical-nlp a skos:Concept ;
rdfs:label "Clinical NLP"@en .
ngm:clinical-note-generation a skos:Concept ;
rdfs:label "Clinical Note Generation"@en .
ngm:clinical-terminology a skos:Concept ;
rdfs:label "Clinical Terminology"@en .
ngm:clinical-trials a owl:Class ;
rdfs:comment "Blockchain-based clinical trial management systems employ immutable audit trails, smart contracts for protocol compliance, and cryptographic verification to ensure data integrity, prevent fraud, and provide FDA 21 CFR Part 11 compliant tamper-proof records whilst reducing monitoring costs. These systems address pharmaceutical development challenges including data falsification, patient recruitment inefficiency, and multi-site coordination failures."@en ;
rdfs:label "Clinical Trials"@en ;
rdfs:subClassOf ngm:network-component ;
rdfs:subClassOf _:r4424 ;
rdfs:subClassOf _:r4425 ;
vc:dependsOn ngm:compliance-framework ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:requires ngm:blockchain-compliance ;
vc:requires ngm:data-integrity ;
vc:slug "clinical-trials" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:drug-discovery ;
vc:supports ngm:healthcare-records ;
vc:uses ngm:audit-trail ;
vc:uses ngm:hyperledger-fabric ;
vc:uses ngm:smart-contract .
ngm:clip a owl:Class ;
rdfs:comment "CLIP (Contrastive Language-Image Pre-training) is a dual-encoder neural network architecture developed by OpenAI in which a vision encoder (Vision Transformer or CNN) and a text encoder (Transformer) are jointly trained on large-scale internet-sourced image-text pairs using an InfoNCE contrastive objective. The training maximises cosine similarity between embeddings of matched image-text pairs and minimises it for unmatched pairs within a batch, yielding a shared multimodal embedding space where semantically related images and text are geometrically proximate. This shared space enables zero-shot image classification by comparing image embeddings to natural language class descriptions without task-specific fine-tuning, and has become a foundational component in text-to-image diffusion models, open-vocabulary object detection, and cross-modal retrieval systems."@en ;
rdfs:label "CLIP"@en ;
rdfs:subClassOf ngm:ai-model-architecture ;
rdfs:subClassOf ngm:foundation-model ;
rdfs:subClassOf ngm:multimodal-ai-architecture-ai ;
rdfs:subClassOf _:r3768 ;
rdfs:subClassOf _:r3769 ;
rdfs:subClassOf _:r3770 ;
rdfs:subClassOf _:r3771 ;
rdfs:subClassOf _:r3772 ;
rdfs:subClassOf _:r3773 ;
rdfs:subClassOf _:r3774 ;
rdfs:subClassOf _:r3775 ;
rdfs:subClassOf _:r3776 ;
skos:broader ngm:ai-model-architecture ;
vc:bridgesTo ngm:augmented-reality ;
vc:bridgesTo ngm:spatial-anchor ;
vc:contrastsWith ngm:align ;
vc:contrastsWith ngm:coca ;
vc:contrastsWith ngm:florence ;
vc:contrastsWith ngm:metaclip ;
vc:contrastsWith ngm:siglip ;
vc:dependsOn ngm:embedding-model ;
vc:dependsOn ngm:transfer-learning ;
vc:dependsOn ngm:vision-transformer ;
vc:enables ngm:cross-modal-retrieval ;
vc:enables ngm:image-classification ;
vc:enables ngm:image-text-retrieval ;
vc:enables ngm:multimodal-search ;
vc:enables ngm:open-vocabulary-detection ;
vc:enables ngm:text-to-image-generation ;
vc:enables ngm:zero-shot-learning ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:cosine-similarity ;
vc:hasPart ngm:embedding-space ;
vc:hasPart ngm:infonce-loss ;
vc:hasPart ngm:transformer-architecture ;
vc:hasPart ngm:vision-transformer ;
vc:implements ngm:contrastive-learning ;
vc:implements ngm:dual-encoder-architecture ;
vc:isPartOf ngm:foundation-model ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:augmented-reality ;
vc:relatedTo ngm:foundation-model ;
vc:relatedTo ngm:multimodal-ai-architecture-ai ;
vc:relatedTo ngm:openclip ;
vc:relatedTo ngm:prompt-engineering ;
vc:relatedTo ngm:spatial-anchor ;
vc:relatedTo ngm:vision-language-model ;
vc:relatedTo ngm:zero-shot-learning ;
vc:requires ngm:contrastive-learning ;
vc:requires ngm:embedding-space ;
vc:requires ngm:large-scale-datasets ;
vc:requires ngm:self-supervised-learning ;
vc:slug "clip" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:laion ;
vc:standardizedBy ngm:openai-research-organisation ;
vc:standardizedBy ngm:openclip ;
vc:supports ngm:multimodal-search ;
vc:supports ngm:stable-diffusion-image-model ;
vc:supports ngm:text-to-image ;
vc:supports ngm:text-to-image-generation ;
vc:supports ngm:vision-language-model ;
vc:uses ngm:contrastive-learning ;
vc:uses ngm:cosine-similarity ;
vc:uses ngm:infonce-loss ;
vc:uses ngm:prompt-engineering ;
vc:uses ngm:self-supervised-learning ;
vc:uses ngm:transformer-architecture ;
vc:uses ngm:vision-transformer .
ngm:clip-encoder a owl:Class ;
rdfs:comment "A CLIP Encoder is either of the two paired neural network encoders — an image encoder and a text encoder — within the Contrastive Language-Image Pre-training (CLIP) framework developed by OpenAI. Each encoder maps its respective modality into a shared high-dimensional embedding space where semantically related image-text pairs are placed in proximity, enabling zero-shot image classification, cross-modal retrieval, and semantic image search without task-specific fine-tuning. CLIP Encoders serve as foundational components in multimodal AI pipelines, diffusion model conditioning, and vision-language models."@en ;
rdfs:label "CLIP Encoder"@en ;
rdfs:subClassOf ngm:deep-learning ;
rdfs:subClassOf ngm:embedding-model ;
rdfs:subClassOf ngm:encoder ;
rdfs:subClassOf ngm:foundation-model-component ;
rdfs:subClassOf ngm:neural-network ;
rdfs:subClassOf _:r3755 ;
rdfs:subClassOf _:r3756 ;
rdfs:subClassOf _:r3757 ;
rdfs:subClassOf _:r3758 ;
rdfs:subClassOf _:r3759 ;
rdfs:subClassOf _:r3760 ;
rdfs:subClassOf _:r3761 ;
rdfs:subClassOf _:r3762 ;
rdfs:subClassOf _:r3763 ;
rdfs:subClassOf _:r3764 ;
rdfs:subClassOf _:r3765 ;
rdfs:subClassOf _:r3766 ;
rdfs:subClassOf _:r3767 ;
vc:contrastsWith ngm:autoencoder ;
vc:contrastsWith ngm:bert ;
vc:contrastsWith ngm:generative-adversarial-network ;
vc:contrastsWith ngm:masked-autoencoder ;
vc:contrastsWith ngm:self-supervised-learning ;
vc:contrastsWith ngm:supervised-image-classifier ;
vc:contrastsWith ngm:vae ;
vc:dependsOn ngm:backpropagation ;
vc:dependsOn ngm:batch-normalisation ;
vc:dependsOn ngm:layer-normalisation ;
vc:dependsOn ngm:mixed-precision-training ;
vc:dependsOn ngm:stochastic-gradient-descent ;
vc:enables ngm:content-moderation ;
vc:enables ngm:cross-modal-retrieval ;
vc:enables ngm:diffusion-model ;
vc:enables ngm:image-captioning ;
vc:enables ngm:image-classification ;
vc:enables ngm:multimodal-ai-architecture-learning ;
vc:enables ngm:open-vocabulary-object-detection ;
vc:enables ngm:retrieval-augmented-generation ;
vc:enables ngm:semantic-search ;
vc:enables ngm:stable-diffusion-image-model ;
vc:enables ngm:text-to-image-generation ;
vc:enables ngm:vision-language-model ;
vc:enables ngm:zero-shot-learning ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:attention-mechanism ;
vc:hasPart ngm:byte-pair-encoding ;
vc:hasPart ngm:cls-token ;
vc:hasPart ngm:feed-forward-network ;
vc:hasPart ngm:layer-normalisation ;
vc:hasPart ngm:linear-projection-head ;
vc:hasPart ngm:multi-head-attention ;
vc:hasPart ngm:patch-embedding ;
vc:hasPart ngm:temperature-parameter ;
vc:hasPart ngm:transformer ;
vc:hasPart ngm:vision-transformer ;
vc:implements ngm:clip ;
vc:implements ngm:contrastive-language-image-pre-training ;
vc:implements ngm:dual-encoder-architecture ;
vc:implements ngm:infonce-loss ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:align ;
vc:relatedTo ngm:clip ;
vc:relatedTo ngm:computer-vision ;
vc:relatedTo ngm:dall-e-3 ;
vc:relatedTo ngm:embedding ;
vc:relatedTo ngm:embedding-space ;
vc:relatedTo ngm:eva-clip ;
vc:relatedTo ngm:flamingo ;
vc:relatedTo ngm:imagenet ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:llava ;
vc:relatedTo ngm:metaclip ;
vc:relatedTo ngm:multimodal-ai-architecture-ai ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:openclip ;
vc:relatedTo ngm:siglip ;
vc:relatedTo ngm:stable-diffusion-image-model ;
vc:requires ngm:batch-sampling ;
vc:requires ngm:contrastive-learning ;
vc:requires ngm:cosine-similarity ;
vc:requires ngm:gradient-descent ;
vc:requires ngm:infonce-loss ;
vc:requires ngm:large-scale-datasets ;
vc:requires ngm:training-data ;
vc:slug "clip-encoder" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:baai ;
vc:standardizedBy ngm:laion ;
vc:standardizedBy ngm:openai-research-organisation ;
vc:supports ngm:dataset-curation ;
vc:supports ngm:deepfake-detection ;
vc:supports ngm:image-text-retrieval ;
vc:supports ngm:multimodal-embedding ;
vc:supports ngm:safety-classifier ;
vc:supports ngm:semantic-segmentation ;
vc:supports ngm:text-to-image-generation ;
vc:uses ngm:attention-mechanism ;
vc:uses ngm:byte-pair-encoding ;
vc:uses ngm:contrastive-learning ;
vc:uses ngm:cosine-similarity ;
vc:uses ngm:infonce-loss ;
vc:uses ngm:patch-embedding ;
vc:uses ngm:resnet ;
vc:uses ngm:transformer ;
vc:uses ngm:vision-transformer .
ngm:clip-text-conditioning a skos:Concept ;
rdfs:label "Clip Text Conditioning"@en .
ngm:clipboard-synchronisation a skos:Concept ;
rdfs:label "Clipboard Synchronisation"@en .
ngm:cliptextencode a skos:Concept ;
rdfs:label "Cliptextencode"@en .
ngm:clique-consensus a skos:Concept ;
rdfs:label "Clique Consensus"@en .
ngm:clique-percolation-method a skos:Concept ;
rdfs:label "Clique Percolation Method"@en .
ngm:clock-drift a skos:Concept ;
rdfs:label "Clock Drift"@en .
ngm:clock-recovery a owl:Class ;
rdfs:comment "Clock recovery (clock and data recovery, CDR) is the physical-layer process by which a receiver extracts a synchronised timing reference from an incoming data stream that carries no separate clock signal. It uses phase-locked loops or oversampling to align sampling instants with the centre of each symbol, compensating for jitter and frequency offset between transmitter and receiver. It matters because correct sampling timing is essential for reliable symbol detection in serial communication links."@en ;
rdfs:label "Clock Recovery"@en ;
rdfs:subClassOf ngm:infra-network-and-comms ;
skos:broader ngm:infra-network-and-comms ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:physical-layer ;
vc:slug "clock-recovery" ;
vc:sourceDomain "infrastructure" .
ngm:clock-skew a skos:Concept ;
rdfs:label "Clock Skew"@en .
ngm:clock-speed a skos:Concept ;
rdfs:label "Clock Speed"@en .
ngm:clock-synchronization a owl:Class ;
rdfs:comment "Clock Synchronization is the process of coordinating the time references of distributed computing nodes or electronic systems so that they share a consistent and accurate notion of time, enabling correct ordering of events, coordinated actions, and time-stamped record-keeping. Protocols such as NTP (Network Time Protocol) and PTP (Precision Time Protocol, IEEE 1588) achieve synchronization by exchanging timestamped messages and compensating for network propagation delays. Accurate clock synchronization is critical for distributed databases, consensus algorithms, telecommunications, industrial control systems, and financial transaction ordering."@en ;
rdfs:label "Clock Synchronization"@en ;
rdfs:subClassOf ngm:network-synchronization ;
vc:enables ngm:consensus-mechanism ;
vc:enables ngm:distributed-systems ;
vc:enables ngm:time-sensitive-networking ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:internet-of-things ;
vc:relatedTo ngm:latency ;
vc:relatedTo ngm:timestamp-service ;
vc:slug "clock-synchronization" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:synchronization-protocol ;
vc:uses ngm:timestamp .
ngm:clone-stamp-tool a skos:Concept ;
rdfs:label "Clone Stamp Tool"@en .
ngm:closed-book-generation a skos:Concept ;
rdfs:label "Closed Book Generation"@en .
ngm:closed-end-investment-fund a skos:Concept ;
rdfs:label "Closed End Investment Fund"@en .
ngm:closed-form-ik a skos:Concept ;
rdfs:label "Closed Form Ik"@en .
ngm:closed-loop-control a owl:Class ;
rdfs:comment "A control system that uses feedback from sensors to compare the actual output with the desired output and adjusts the control action to minimize error. The system continuously monitors and corrects its behavior."@en ;
rdfs:label "Closed-Loop Control"@en ;
rdfs:subClassOf ngm:control-system ;
rdfs:subClassOf ngm:robo-actuation-and-control ;
rdfs:subClassOf _:r4432 ;
rdfs:subClassOf _:r4433 ;
rdfs:subClassOf _:r4434 ;
rdfs:subClassOf _:r4435 ;
rdfs:subClassOf _:r4436 ;
rdfs:subClassOf _:r4437 ;
rdfs:subClassOf _:r4438 ;
rdfs:subClassOf _:r4439 ;
skos:broader ngm:robo-actuation-and-control ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:reinforcement-learning ;
vc:contrastsWith ngm:open-loop-control ;
vc:contrastsWith ngm:rb-1001-open-loop-control ;
vc:dependsOn ngm:kalman-filter ;
vc:dependsOn ngm:state-estimation ;
vc:enables ngm:accuracy ;
vc:enables ngm:disturbance-rejection ;
vc:enables ngm:rb-1007-trajectory-generation ;
vc:enables ngm:rb-1013-localization ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:error-signal ;
vc:hasPart ngm:feedback-mechanism ;
vc:hasPart ngm:setpoint ;
vc:implements ngm:adaptive-control ;
vc:implements ngm:optimal-control ;
vc:implements ngm:pid-control ;
vc:implements ngm:robust-control ;
vc:isPartOf ngm:control-system ;
vc:isPartOf ngm:control-theory ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:system-identification ;
vc:requires ngm:actuator ;
vc:requires ngm:controller ;
vc:requires ngm:feedback-mechanism ;
vc:requires ngm:sensor-system ;
vc:requires ngm:stability ;
vc:slug "closed-loop-control" ;
vc:sourceDomain "robotics" ;
vc:standardizedBy ngm:iso-8373-2021 ;
vc:supports ngm:autonomous-vehicle ;
vc:supports ngm:industrial-automation ;
vc:supports ngm:robotics ;
vc:uses ngm:actuator ;
vc:uses ngm:controller ;
vc:uses ngm:sensor-system ;
vc:uses ngm:state-space-representation .
ngm:closed-loop-cooling a owl:Class ;
rdfs:comment "A thermal management system that recirculates coolant within a sealed circuit to dissipate heat without consuming external water resources."@en ;
rdfs:label "Closed-Loop Cooling"@en ;
rdfs:subClassOf ngm:data-center-sustainability ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:data-center-sustainability ;
vc:relatedTo ngm:infrastructure ;
vc:slug "closed-loop-cooling" ;
vc:sourceDomain "infrastructure" .
ngm:closed-loop-neuromodulation a skos:Concept ;
rdfs:label "Closed Loop Neuromodulation"@en .
ngm:closed-peer-review a skos:Concept ;
rdfs:label "Closed Peer Review"@en .
ngm:closed-platform a skos:Concept ;
rdfs:label "Closed Platform"@en .
ngm:closed-source a skos:Concept ;
rdfs:label "Closed Source"@en .
ngm:closed-source-analytics a skos:Concept ;
rdfs:label "Closed Source Analytics"@en .
ngm:closed-source-model a skos:Concept ;
rdfs:label "Closed Source Model"@en .
ngm:closed-source-software a skos:Concept ;
rdfs:label "Closed Source Software"@en .
ngm:closed-specification a skos:Concept ;
rdfs:label "Closed Specification"@en .
ngm:closed-weight-models a skos:Concept ;
rdfs:label "Closed Weight Models"@en .
ngm:closed-world-assumption a owl:Class ;
rdfs:comment "The Closed World Assumption (CWA) is the presumption that any statement not known to be true is false, treating the knowledge base as a complete description of the world. It is foundational to database query semantics, logic programming, and negation as failure, where the absence of a fact licenses inferring its negation. CWA simplifies reasoning over finite, curated domains but breaks down where information is incomplete."@en ;
rdfs:label "Closed World Assumption"@en ;
rdfs:subClassOf ngm:formal-logic ;
rdfs:subClassOf ngm:knowledge-representation ;
rdfs:subClassOf ngm:non-monotonic-reasoning ;
rdfs:subClassOf _:r4426 ;
rdfs:subClassOf _:r4427 ;
rdfs:subClassOf _:r4428 ;
rdfs:subClassOf _:r4429 ;
rdfs:subClassOf _:r4430 ;
rdfs:subClassOf _:r4431 ;
vc:bridgesTo ngm:enterprise-knowledge-graph ;
vc:bridgesTo ngm:large-language-models ;
vc:bridgesTo ngm:logic-programming ;
vc:bridgesTo ngm:retrieval-augmented-generation ;
vc:bridgesTo ngm:semantic-web-linked-data-standard ;
vc:bridgesTo ngm:shacl ;
vc:contrastsWith ngm:bayesian-inference ;
vc:contrastsWith ngm:non-monotonic-logic ;
vc:contrastsWith ngm:open-world-assumption ;
vc:contrastsWith ngm:owl-class-hierarchy ;
vc:contrastsWith ngm:semantic-web-linked-data-standard ;
vc:dependsOn ngm:database-theory ;
vc:dependsOn ngm:first-order-logic ;
vc:dependsOn ngm:formal-logic ;
vc:dependsOn ngm:knowledge-representation ;
vc:enables ngm:answer-set-programming ;
vc:enables ngm:automated-reasoning ;
vc:enables ngm:data-integrity-constraint ;
vc:enables ngm:definite-query-answering ;
vc:enables ngm:expert-systems ;
vc:enables ngm:query-answering ;
vc:enables ngm:reasoning ;
vc:enables ngm:relational-database-semantics ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:answer-set-programming ;
vc:hasPart ngm:database-completeness-assumption ;
vc:hasPart ngm:negation-as-failure ;
vc:implements ngm:datalog ;
vc:implements ngm:deductive-database-semantics ;
vc:implements ngm:negation-as-failure ;
vc:implements ngm:prolog ;
vc:implements ngm:reasoning ;
vc:implements ngm:shacl ;
vc:isPartOf ngm:artificial-intelligence ;
vc:isPartOf ngm:database-theory ;
vc:qualityScore "0.92"^^xsd:float ;
vc:relatedTo ngm:answer-set-programming ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:automated-reasoning ;
vc:relatedTo ngm:database-theory ;
vc:relatedTo ngm:description-logic ;
vc:relatedTo ngm:expert-systems ;
vc:relatedTo ngm:inference-engine ;
vc:relatedTo ngm:knowledge-graph ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:ontology ;
vc:relatedTo ngm:reasoning ;
vc:relatedTo ngm:retrieval-augmented-generation ;
vc:relatedTo ngm:shacl ;
vc:relatedTo ngm:sparql ;
vc:requires ngm:first-order-logic ;
vc:requires ngm:formal-language ;
vc:requires ngm:formal-logic ;
vc:requires ngm:inference-engine ;
vc:requires ngm:knowledge-representation ;
vc:requires ngm:logic-programming ;
vc:slug "closed-world-assumption" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:iso-iec ;
vc:standardizedBy ngm:w3-c ;
vc:supports ngm:deductive-database ;
vc:supports ngm:knowledge-representation ;
vc:supports ngm:logic-programming ;
vc:supports ngm:relational-database ;
vc:supports ngm:shacl ;
vc:supports ngm:sparql ;
vc:supports ngm:sql ;
vc:uses ngm:datalog ;
vc:uses ngm:description-logic ;
vc:uses ngm:inference-engine ;
vc:uses ngm:negation-as-failure ;
vc:uses ngm:prolog ;
vc:uses ngm:rdf ;
vc:uses ngm:sparql ;
vc:uses ngm:sql .
ngm:closed-world-negation-as-failure a skos:Concept ;
rdfs:label "Closed World Negation As Failure"@en .
ngm:cloth-simulation a owl:Class ;
rdfs:comment "Cloth Simulation is the computational modelling of textile deformation and dynamics, representing fabric as a mesh of particles connected by spring constraints (stretch, shear, and bend) or by a continuum-mechanics model, and integrating the equations of motion to produce plausible cloth behaviour under gravity, wind, collision, and user interaction. The particle-spring model, popularised by Provot (1995), remains prevalent in real-time applications; more accurate results for offline rendering use finite-element or position-based dynamics (PBD) methods. Collision detection and response against rigid bodies and self-collision are the principal computational bottlenecks, requiring spatial acceleration structures such as bounding volume hierarchies. Cloth simulation is a sub-discipline of physically based animation used in character clothing, flag animation, curtains, and virtual fashion design within game engines, VFX pipelines, and metaverse avatar systems."@en ;
rdfs:label "Cloth Simulation"@en ;
rdfs:subClassOf ngm:physics-simulation ;
vc:enables ngm:dynamic-character-animation ;
vc:enables ngm:real-time-rendering ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:particle-system ;
vc:relatedTo ngm:rigid-body ;
vc:relatedTo ngm:soft-body-dynamics ;
vc:slug "cloth-simulation" ;
vc:sourceDomain "metaverse" ;
vc:supports ngm:game-development ;
vc:supports ngm:simulation-software ;
vc:uses ngm:animation-technique ;
vc:uses ngm:physics-engine .
ngm:cloud-ai a skos:Concept ;
rdfs:label "Cloud AI"@en .
ngm:cloud-ai-platform a skos:Concept ;
rdfs:label "Cloud AI Platform"@en .
ngm:cloud-analytics-service a skos:Concept ;
rdfs:label "Cloud Analytics Service"@en .
ngm:cloud-anchor-infrastructure a skos:Concept ;
rdfs:label "Cloud Anchor Infrastructure"@en .
ngm:cloud-computing a owl:Class ;
rdfs:comment "Cloud computing is the on-demand delivery of computing resources — servers, storage, databases, networking, software, analytics, and AI accelerators — over the internet via provider-managed data centres, abstracting physical infrastructure into programmable APIs with pay-per-use economics. Service models (IaaS, PaaS, SaaS) and deployment models (public, private, hybrid, multi-cloud) define the boundary of managed responsibility between provider and consumer. Hyperscale providers such as AWS, Microsoft Azure, and Google Cloud Platform underpin modern AI training, inference serving, and distributed application deployment at global scale. The paradigm enables elastic provisioning — scaling from zero to thousands of compute nodes in seconds — transforming both software engineering and machine learning operations."@en ;
rdfs:label "Cloud Computing"@en ;
rdfs:subClassOf ngm:distributed-systems ;
rdfs:subClassOf _:r4440 ;
rdfs:subClassOf _:r4441 ;
rdfs:subClassOf _:r4442 ;
rdfs:subClassOf _:r4443 ;
rdfs:subClassOf _:r4444 ;
rdfs:subClassOf _:r4445 ;
rdfs:subClassOf _:r4446 ;
rdfs:subClassOf _:r4447 ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:federated-learning ;
vc:bridgesTo ngm:spatial-computing ;
vc:contrastsWith ngm:mainframe-computing ;
vc:contrastsWith ngm:on-premises-computing ;
vc:dependsOn ngm:distributed-computing ;
vc:dependsOn ngm:high-availability ;
vc:enables ngm:ai-infrastructure ;
vc:enables ngm:big-data ;
vc:enables ngm:devops ;
vc:enables ngm:distributed-training ;
vc:enables ngm:inference ;
vc:enables ngm:mlops ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:infrastructure-as-a-service ;
vc:hasPart ngm:platform-as-a-service ;
vc:hasPart ngm:serverless-architecture ;
vc:hasPart ngm:software-as-a-service ;
vc:isPartOf ngm:internet-infrastructure ;
vc:qualityScore "0.76"^^xsd:float ;
vc:relatedTo ngm:cloud-security ;
vc:relatedTo ngm:cost-optimisation ;
vc:relatedTo ngm:multi-cloud ;
vc:requires ngm:data-centre ;
vc:requires ngm:network-infrastructure ;
vc:requires ngm:virtualisation ;
vc:slug "cloud-computing" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:iso-iec-17788 ;
vc:standardizedBy ngm:nist-cloud-computing ;
vc:standardizedBy ngm:nist-cloud-computing-definition ;
vc:supports ngm:cloud-platform ;
vc:supports ngm:edge-computing ;
vc:supports ngm:hybrid-cloud ;
vc:uses ngm:cdn ;
vc:uses ngm:containerisation ;
vc:uses ngm:kubernetes ;
vc:uses ngm:object-storage .
ngm:cloud-computing-revenue a owl:Class ;
rdfs:comment "The financial income generated by cloud service providers from the sale of infrastructure, platform, and software services to customers."@en ;
rdfs:label "Cloud Computing Revenue"@en ;
rdfs:subClassOf ngm:hyperscale-cloud ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:aws-financial-performance ;
vc:relatedTo ngm:hyperscale-cloud ;
vc:slug "cloud-computing-revenue" ;
vc:sourceDomain "economics" .
ngm:cloud-cover-fraction a owl:Class ;
rdfs:label "Cloud Cover Fraction"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-data-quality ;
vc:slug "cloud-cover-fraction" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:cloud-database a skos:Concept ;
rdfs:label "Cloud Database"@en .
ngm:cloud-development-environment a skos:Concept ;
rdfs:label "Cloud Development Environment"@en .
ngm:cloud-forensics a skos:Concept ;
rdfs:label "Cloud Forensics"@en .
ngm:cloud-gaming a owl:Class ;
rdfs:comment "Cloud gaming is a model in which games are rendered on remote server GPUs and streamed as video to a client device, while player input is sent back to the server over the network. It shifts compute off the end device, allowing demanding titles to run on thin clients, but is highly sensitive to network latency, bandwidth, and jitter. It matters as a delivery paradigm that depends on adaptive bitrate streaming and low-latency encoding to maintain interactivity."@en ;
rdfs:label "Cloud Gaming"@en ;
rdfs:subClassOf ngm:infra-computing-and-cloud ;
skos:broader ngm:infra-computing-and-cloud ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:bandwidth-adaptation ;
vc:slug "cloud-gaming" ;
vc:sourceDomain "metaverse" .
ngm:cloud-hosting a skos:Concept ;
rdfs:label "Cloud Hosting"@en .
ngm:cloud-identity a skos:Concept ;
rdfs:label "Cloud Identity"@en .
ngm:cloud-inference a skos:Concept ;
rdfs:label "Cloud Inference"@en .
ngm:cloud-infrastructure a owl:Class ;
rdfs:comment "Cloud infrastructure is a computing model that provides on-demand access to virtualized computing resources including servers, storage, networking, and platform services delivered over the internet, enabling organizations to provision and scale IT resources dynamically through IaaS, PaaS, and SaaS service models without managing physical hardware."@en ;
rdfs:label "Cloud Infrastructure"@en ;
rdfs:subClassOf ngm:infra-computing-and-cloud ;
rdfs:subClassOf _:r4448 ;
rdfs:subClassOf _:r4449 ;
rdfs:subClassOf _:r4450 ;
rdfs:subClassOf _:r4451 ;
rdfs:subClassOf _:r4452 ;
skos:broader ngm:infra-computing-and-cloud ;
vc:bridgesTo ngm:spatial-computing ;
vc:contrastsWith ngm:edge-computing ;
vc:contrastsWith ngm:on-premises-infrastructure ;
vc:enables ngm:elasticity ;
vc:enables ngm:infrastructure-as-a-service ;
vc:enables ngm:platform-as-a-service ;
vc:enables ngm:scalability ;
vc:enables ngm:self-service-provisioning ;
vc:enables ngm:software-as-a-service ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:object-storage ;
vc:hasPart ngm:virtual-machine ;
vc:implements ngm:multi-tenancy ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:cloud-native-applications ;
vc:relatedTo ngm:devops ;
vc:requires ngm:identity-and-access-management ;
vc:requires ngm:network-connectivity ;
vc:requires ngm:virtualisation ;
vc:slug "cloud-infrastructure" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:iso-iec-17788 ;
vc:supports ngm:containerisation ;
vc:supports ngm:hybrid-cloud ;
vc:supports ngm:multi-cloud ;
vc:supports ngm:serverless-architecture .
ngm:cloud-mask a owl:Class ;
rdfs:label "Cloud Mask"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-processing ;
vc:slug "cloud-mask" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:cloud-migration a skos:Concept ;
rdfs:label "Cloud Migration"@en .
ngm:cloud-native a owl:Class ;
rdfs:comment "Cloud Native is an approach to building and running applications that fully exploits the advantages of cloud computing infrastructure — elastic scaling, managed services, pay-per-use economics, and high availability — by designing for containerisation, dynamic orchestration, microservices decomposition, and declarative APIs. The Cloud Native Computing Foundation (CNCF) defines it as the use of containers, service meshes, microservices, immutable infrastructure, and declarative APIs to build resilient, manageable, and observable systems. Cloud Native architectures enable rapid, reproducible delivery of software at scale across public, private, and hybrid cloud environments."@en ;
rdfs:label "Cloud Native"@en ;
rdfs:subClassOf ngm:cloud-computing ;
vc:enables ngm:continuous-integration ;
vc:enables ngm:high-availability ;
vc:enables ngm:scalability ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:edge-computing ;
vc:relatedTo ngm:fault-tolerance ;
vc:relatedTo ngm:microservices-architecture ;
vc:slug "cloud-native" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:kubernetes ;
vc:uses ngm:microservices ;
vc:uses ngm:service-mesh .
ngm:cloud-native-applications a owl:Class ;
rdfs:comment "Cloud-native applications are software systems specifically designed and architected to exploit the capabilities of cloud computing environments, built from loosely coupled microservices deployed via containers and orchestrated across private, public, or hybrid cloud infrastructure. They prioritise scalability, resilience, observability, and automated lifecycle management over the characteristics of traditional monolithic systems. The paradigm is distinguished not by where an application runs but by how it is constructed, operated, and evolved."@en ;
rdfs:label "Cloud-Native Applications"@en ;
rdfs:subClassOf ngm:infra-computing-and-cloud ;
rdfs:subClassOf _:r4475 ;
rdfs:subClassOf _:r4476 ;
rdfs:subClassOf _:r4477 ;
rdfs:subClassOf _:r4478 ;
rdfs:subClassOf _:r4479 ;
rdfs:subClassOf _:r4480 ;
rdfs:subClassOf _:r4481 ;
rdfs:subClassOf _:r4482 ;
skos:broader ngm:infra-computing-and-cloud ;
vc:bridgesTo ngm:artificial-intelligence-operations ;
vc:bridgesTo ngm:edge-computing ;
vc:bridgesTo ngm:sensor-input ;
vc:contrastsWith ngm:monolithic-architecture ;
vc:dependsOn ngm:service-discovery ;
vc:dependsOn ngm:twelve-factor-app ;
vc:enables ngm:autoscaling ;
vc:enables ngm:industry-cloud-platforms ;
vc:enables ngm:platform-service ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:api-gateway ;
vc:hasPart ngm:containerisation ;
vc:hasPart ngm:microservices-architecture ;
vc:hasPart ngm:serverless-architecture ;
vc:hasPart ngm:service-mesh ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:distributed-systems ;
vc:relatedTo ngm:site-reliability-engineering ;
vc:relatedTo ngm:technology-infrastructure-domain-architecture ;
vc:requires ngm:container-orchestration ;
vc:requires ngm:immutable-infrastructure ;
vc:requires ngm:kubernetes ;
vc:slug "cloud-native-applications" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:cncf ;
vc:standardizedBy ngm:open-container-initiative ;
vc:uses ngm:cloud-infrastructure ;
vc:uses ngm:devops ;
vc:uses ngm:edge-cloud-collaboration ;
vc:uses ngm:platform-engineering .
ngm:cloud-native-architecture a owl:Class ;
rdfs:comment "Cloud-native architecture is an approach to designing and operating applications that fully exploit elastic, on-demand cloud infrastructure. It favours loosely coupled, independently deployable services packaged in containers, orchestrated dynamically, and managed through automation, declarative configuration and continuous delivery. The goal is resilient, scalable systems that can be evolved rapidly and recover automatically from failure."@en ;
rdfs:label "Cloud-Native Architecture"@en ;
rdfs:subClassOf ngm:cloud-infrastructure ;
rdfs:subClassOf _:r4483 ;
rdfs:subClassOf _:r4484 ;
rdfs:subClassOf _:r4485 ;
rdfs:subClassOf _:r4486 ;
vc:bridgesTo ngm:service-mesh ;
vc:bridgesTo ngm:twelve-factor-app ;
vc:contrastsWith ngm:service-oriented-architecture ;
vc:dependsOn ngm:infrastructure-as-code ;
vc:dependsOn ngm:observability ;
vc:enables ngm:continuous-deployment ;
vc:enables ngm:high-availability ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:containerisation ;
vc:hasPart ngm:microservices-architecture ;
vc:isPartOf ngm:cloud-infrastructure ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:devops ;
vc:relatedTo ngm:observability ;
vc:requires ngm:containerisation ;
vc:requires ngm:kubernetes ;
vc:slug "cloud-native-architecture" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:immutable-infrastructure ;
vc:supports ngm:microservices ;
vc:uses ngm:devops ;
vc:uses ngm:kubernetes .
ngm:cloud-native-computing-foundation a owl:Class ;
rdfs:comment "The Cloud Native Computing Foundation (CNCF) is a vendor-neutral, open-source foundation hosted by the Linux Foundation that stewards critical cloud-native projects such as Kubernetes, Prometheus and Envoy. It defines and promotes the cloud-native computing model based on containers, microservices and declarative orchestration. The CNCF maintains a graduated project lifecycle (sandbox, incubating, graduated) and coordinates the wider ecosystem through events, certification programmes and a technical oversight committee."@en ;
rdfs:label "Cloud Native Computing Foundation"@en ;
rdfs:subClassOf ngm:linux-foundation ;
rdfs:subClassOf _:r4453 ;
rdfs:subClassOf _:r4454 ;
vc:bridgesTo ngm:standards-organization ;
vc:contrastsWith ngm:standards-body ;
vc:enables ngm:cloud-computing ;
vc:enables ngm:devops ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:kubernetes ;
vc:hasPart ngm:observability ;
vc:isPartOf ngm:linux-foundation ;
vc:isPartOf ngm:open-source ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:cloud-platform ;
vc:relatedTo ngm:observability ;
vc:slug "cloud-native-computing-foundation" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:standards-organization ;
vc:supports ngm:cloud-native-applications ;
vc:supports ngm:microservices ;
vc:supports ngm:service-mesh ;
vc:uses ngm:kubernetes .
ngm:cloud-native-network-function a skos:Concept ;
rdfs:label "Cloud Native Network Function"@en .
ngm:cloud-platform a owl:Class ;
rdfs:comment "A cloud platform is an integrated suite of managed infrastructure, runtime services, and developer tooling delivered over the internet that enables organisations to build, deploy, scale, and operate applications without owning physical hardware. Cloud platforms abstract away operational complexity through pay-as-you-go pricing, elastic scaling, and managed service lifecycles, spanning IaaS, PaaS, and SaaS delivery models. The dominant hyperscale providers — Amazon Web Services, Microsoft Azure, and Google Cloud Platform — offer hundreds of services covering compute, storage, networking, databases, AI/ML, security, and observability, forming the primary substrate for modern enterprise and AI workloads."@en ;
rdfs:label "Cloud Platform"@en ;
rdfs:subClassOf ngm:cloud-infrastructure ;
rdfs:subClassOf _:r4455 ;
rdfs:subClassOf _:r4456 ;
rdfs:subClassOf _:r4457 ;
rdfs:subClassOf _:r4458 ;
rdfs:subClassOf _:r4459 ;
rdfs:subClassOf _:r4460 ;
rdfs:subClassOf _:r4461 ;
rdfs:subClassOf _:r4462 ;
rdfs:subClassOf _:r4463 ;
vc:bridgesTo ngm:ai-inference-infrastructure ;
vc:bridgesTo ngm:foundation-model ;
vc:bridgesTo ngm:inference-infrastructure ;
vc:contrastsWith ngm:edge-computing ;
vc:contrastsWith ngm:on-premise-infrastructure ;
vc:dependsOn ngm:data-centre ;
vc:dependsOn ngm:internet-protocol ;
vc:enables ngm:cloud-native-applications ;
vc:enables ngm:continuous-integration ;
vc:enables ngm:devops ;
vc:enables ngm:machine-learning-discipline-infrastructure ;
vc:enables ngm:machine-learning-discipline-platform ;
vc:enables ngm:platform-engineering ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:container-orchestration ;
vc:hasPart ngm:microservices-architecture ;
vc:hasPart ngm:platform-layer ;
vc:hasPart ngm:platform-service ;
vc:hasPart ngm:serverless-architecture ;
vc:hasPart ngm:technology-infrastructure-domain-component ;
vc:isPartOf ngm:cloud-infrastructure ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:distributed-computing ;
vc:relatedTo ngm:multi-cloud-strategy ;
vc:relatedTo ngm:platform-governance ;
vc:relatedTo ngm:service-oriented-architecture ;
vc:relatedTo ngm:technology-infrastructure-domain-architecture ;
vc:requires ngm:identity-and-access-management ;
vc:requires ngm:network-infrastructure ;
vc:requires ngm:virtualisation ;
vc:slug "cloud-platform" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:cncf ;
vc:standardizedBy ngm:nist-cloud-computing ;
vc:supports ngm:data-governance ;
vc:supports ngm:finops ;
vc:supports ngm:mlops ;
vc:uses ngm:api-gateway ;
vc:uses ngm:data-pipeline ;
vc:uses ngm:kubernetes ;
vc:uses ngm:version-control .
ngm:cloud-portability a skos:Concept ;
rdfs:label "Cloud Portability"@en .
ngm:cloud-rendering a owl:Class ;
rdfs:comment "Cloud rendering is the practice of generating images or interactive 3D frames on remote, GPU-equipped servers and streaming the results to a client device, rather than rendering locally. It decouples visual fidelity from the client's hardware, enabling thin clients to display high-quality graphics by offloading computation to data centers. It powers cloud gaming, remote visualisation, and immersive metaverse experiences, but depends on low-latency networking and efficient video streaming to remain responsive."@en ;
rdfs:label "Cloud Rendering"@en ;
rdfs:subClassOf ngm:remote-rendering ;
rdfs:subClassOf _:r4464 ;
rdfs:subClassOf _:r4465 ;
vc:bridgesTo ngm:cloud-computing ;
vc:dependsOn ngm:gpu ;
vc:dependsOn ngm:latency ;
vc:enables ngm:cloud-gaming ;
vc:enables ngm:volumetric-rendering ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:thin-client ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:real-time-rendering ;
vc:relatedTo ngm:spatial-computing ;
vc:requires ngm:data-centre ;
vc:requires ngm:edge-computing ;
vc:slug "cloud-rendering" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:interactive-rendering ;
vc:supports ngm:metaverse ;
vc:uses ngm:gpu-rendering ;
vc:uses ngm:web-rtc .
ngm:cloud-run a skos:Concept ;
rdfs:label "Cloud Run"@en .
ngm:cloud-security a owl:Class ;
rdfs:comment "Cloud security is the discipline of protecting data, applications, identities and infrastructure hosted in cloud computing environments against unauthorised access, misconfiguration, data loss and service disruption. It applies controls across the shared-responsibility boundary between cloud providers and customers, spanning identity and access management, encryption, network segmentation, configuration governance and continuous monitoring. Cloud security extends established information-security principles to elastic, multi-tenant and API-driven platforms where infrastructure is provisioned programmatically."@en ;
rdfs:label "Cloud Security"@en ;
rdfs:subClassOf ngm:security ;
rdfs:subClassOf _:r4466 ;
rdfs:subClassOf _:r4467 ;
vc:bridgesTo ngm:confidential-computing ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:authentication ;
vc:isPartOf ngm:cloud-computing ;
vc:isPartOf ngm:security ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-governance ;
vc:relatedTo ngm:security-architecture ;
vc:requires ngm:encryption ;
vc:requires ngm:identity-and-access-management ;
vc:slug "cloud-security" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:iso-27001 ;
vc:supports ngm:compliance ;
vc:supports ngm:data-privacy ;
vc:uses ngm:access-control ;
vc:uses ngm:data-loss-prevention ;
vc:uses ngm:threat-detection ;
vc:uses ngm:zero-trust-architecture .
ngm:cloud-security-alliance a skos:Concept ;
rdfs:label "Cloud Security Alliance"@en .
ngm:cloud-shadow-mask a owl:Class ;
rdfs:label "Cloud Shadow Mask"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-processing ;
vc:slug "cloud-shadow-mask" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:cloud-storage a owl:Class ;
rdfs:comment "Cloud storage is a model of data persistence in which digital data is held on remote servers operated by a cloud service provider, accessed over a network (typically the internet) via well-defined APIs rather than on locally attached hardware. Providers maintain geographically distributed, redundant infrastructure implementing erasure coding or multi-region replication to guarantee high durability and availability, typically billing clients on capacity consumed and egress data transfer. The paradigm encompasses object storage, cloud file systems, and block storage volumes, and underpins virtually every modern cloud-native application architecture by decoupling storage from compute. Major implementations include Amazon S3, Google Cloud Storage, Azure Blob Storage, and S3-compatible open-source systems such as MinIO."@en ;
rdfs:label "Cloud Storage"@en ;
rdfs:subClassOf ngm:data-storage ;
rdfs:subClassOf _:r4468 ;
rdfs:subClassOf _:r4469 ;
rdfs:subClassOf _:r4470 ;
rdfs:subClassOf _:r4471 ;
rdfs:subClassOf _:r4472 ;
rdfs:subClassOf _:r4473 ;
rdfs:subClassOf _:r4474 ;
vc:bridgesTo ngm:decentralized-storage ;
vc:bridgesTo ngm:hybrid-cloud ;
vc:contrastsWith ngm:content-addressed-storage ;
vc:contrastsWith ngm:distributed-storage ;
vc:contrastsWith ngm:on-premises-storage ;
vc:enables ngm:backup-and-recovery ;
vc:enables ngm:cloud-native-applications ;
vc:enables ngm:data-lake ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:block-storage ;
vc:hasPart ngm:file-system ;
vc:hasPart ngm:object-storage ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:cloud-infrastructure ;
vc:relatedTo ngm:cloud-platform ;
vc:relatedTo ngm:data-sovereignty ;
vc:requires ngm:cloud-computing ;
vc:requires ngm:identity-and-access-management ;
vc:requires ngm:network-infrastructure ;
vc:slug "cloud-storage" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:rest-api ;
vc:standardizedBy ngm:s3-api ;
vc:supports ngm:data-management ;
vc:supports ngm:machine-learning-discipline ;
vc:supports ngm:vector-database ;
vc:uses ngm:cdn ;
vc:uses ngm:encryption ;
vc:uses ngm:erasure-coding .
ngm:cloud-storage-infrastructure a owl:Class ;
rdfs:comment "Cloud storage infrastructure is the distributed system of servers, object and block stores, replication, and access APIs that lets applications persist and retrieve data on demand over a network. It provides durability through redundancy, elastic capacity, and tiered performance classes ranging from hot object storage to cold archives. It matters because it is the foundation for storing large media assets, such as meeting recordings, at scale with high availability and pay-as-you-go economics."@en ;
rdfs:label "Cloud Storage Infrastructure"@en ;
rdfs:subClassOf ngm:infra-computing-and-cloud ;
skos:broader ngm:infra-computing-and-cloud ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:meeting-recording ;
vc:slug "cloud-storage-infrastructure" ;
vc:sourceDomain "infrastructure" .
ngm:cloudlet-architecture a skos:Concept ;
rdfs:label "Cloudlet Architecture"@en .
ngm:clr-fund-protocol a skos:Concept ;
rdfs:label "Clr Fund Protocol"@en .
ngm:clrs-introduction-to-algorithms a skos:Concept ;
rdfs:label "Clrs Introduction To Algorithms"@en .
ngm:cls-token a skos:Concept ;
rdfs:label "Cls Token"@en .
ngm:cluster-computing a skos:Concept ;
rdfs:label "Cluster Computing"@en .
ngm:clustered-data-state a owl:Class ;
rdfs:label "Clustered Data State"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-processing ;
vc:slug "clustered-data-state" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:clustered-shading a skos:Concept ;
rdfs:label "Clustered Shading"@en .
ngm:clustering a owl:Class ;
rdfs:comment "Clustering is an unsupervised machine learning task that partitions a set of objects into groups, or clusters, such that objects within a group are more similar to one another than to those in other groups, according to a chosen distance or similarity metric. Unlike classification it operates without predefined labels, discovering latent structure directly from the data. Algorithms differ in their cluster model, ranging from centroid-based and density-based to hierarchical and probabilistic approaches. Clustering is widely used for exploratory analysis, segmentation, anomaly detection, and as a preprocessing step for downstream learning."@en ;
rdfs:label "Clustering"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:data-mining ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf ngm:statistical-learning-theory ;
rdfs:subClassOf ngm:unsupervised-learning ;
rdfs:subClassOf _:r4487 ;
rdfs:subClassOf _:r4488 ;
rdfs:subClassOf _:r4489 ;
rdfs:subClassOf _:r4490 ;
rdfs:subClassOf _:r4491 ;
rdfs:subClassOf _:r4492 ;
rdfs:subClassOf _:r4493 ;
rdfs:subClassOf _:r4494 ;
skos:broader ngm:ai-technique ;
vc:contrastsWith ngm:classification ;
vc:contrastsWith ngm:regression ;
vc:contrastsWith ngm:semi-supervised-learning ;
vc:dependsOn ngm:density-estimation ;
vc:dependsOn ngm:dimensionality-reduction ;
vc:dependsOn ngm:feature-engineering ;
vc:dependsOn ngm:linear-algebra ;
vc:dependsOn ngm:probability-theory ;
vc:enables ngm:anomaly-detection ;
vc:enables ngm:cell-type-identification ;
vc:enables ngm:community-detection ;
vc:enables ngm:customer-segmentation ;
vc:enables ngm:document-organisation ;
vc:enables ngm:exploratory-data-analysis ;
vc:enables ngm:image-retrieval ;
vc:enables ngm:topic-modelling ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:dbscan ;
vc:hasPart ngm:distance-metric ;
vc:hasPart ngm:expectation-maximisation ;
vc:hasPart ngm:gaussian-mixture-model ;
vc:hasPart ngm:hdbscan ;
vc:hasPart ngm:hierarchical-clustering ;
vc:hasPart ngm:k-means ;
vc:hasPart ngm:silhouette-score ;
vc:hasPart ngm:spectral-clustering ;
vc:implements ngm:expectation-maximisation ;
vc:implements ngm:graph-laplacian ;
vc:implements ngm:k-means ;
vc:implements ngm:manifold-hypothesis ;
vc:isPartOf ngm:unsupervised-learning ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:bayesian-nonparametrics ;
vc:relatedTo ngm:bioinformatics ;
vc:relatedTo ngm:combinatorial-optimisation ;
vc:relatedTo ngm:contrastive-learning ;
vc:relatedTo ngm:data-mining ;
vc:relatedTo ngm:density-estimation ;
vc:relatedTo ngm:graph-analytics ;
vc:relatedTo ngm:information-theory ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:representation-learning ;
vc:relatedTo ngm:self-supervised-learning ;
vc:relatedTo ngm:transfer-learning ;
vc:requires ngm:distance-metric ;
vc:requires ngm:embedding ;
vc:requires ngm:embedding-space ;
vc:requires ngm:feature-engineering ;
vc:requires ngm:similarity-function ;
vc:slug "clustering" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:ieee-tpami ;
vc:standardizedBy ngm:scikit-learn ;
vc:supports ngm:bioinformatics ;
vc:supports ngm:data-preprocessing ;
vc:supports ngm:dimensionality-reduction ;
vc:supports ngm:graph-analytics ;
vc:supports ngm:predictive-analytics ;
vc:supports ngm:representation-learning ;
vc:supports ngm:transfer-learning ;
vc:uses ngm:autoencoder ;
vc:uses ngm:contrastive-learning ;
vc:uses ngm:dimensionality-reduction ;
vc:uses ngm:embedding ;
vc:uses ngm:embedding-space ;
vc:uses ngm:expectation-maximisation ;
vc:uses ngm:gaussian-mixture-model ;
vc:uses ngm:graph-neural-network ;
vc:uses ngm:hdbscan ;
vc:uses ngm:large-language-model ;
vc:uses ngm:neural-network ;
vc:uses ngm:principal-component-analysis ;
vc:uses ngm:self-supervised-learning ;
vc:uses ngm:t-sne ;
vc:uses ngm:umap ;
vc:uses ngm:vector-database .
ngm:cma a skos:Concept ;
rdfs:label "Cma"@en .
ngm:cma-strategic-market-status a skos:Concept ;
rdfs:label "Cma Strategic Market Status"@en .
ngm:cmaf a skos:Concept ;
rdfs:label "Cmaf"@en .
ngm:cmake-build-system a skos:Concept ;
rdfs:label "Cmake Build System"@en .
ngm:cme-bitcoin-reference-rate a skos:Concept ;
rdfs:label "Cme Bitcoin Reference Rate"@en .
ngm:cme-brr a skos:Concept ;
rdfs:label "Cme Brr"@en .
ngm:cmmd a skos:Concept ;
rdfs:label "Cmmd"@en .
ngm:cmmi-institute a skos:Concept ;
rdfs:label "Cmmi Institute"@en .
ngm:cmms-integration a skos:Concept ;
rdfs:label "Cmms Integration"@en .
ngm:cmos-process a skos:Concept ;
rdfs:label "Cmos Process"@en .
ngm:cnc a skos:Concept ;
rdfs:label "Cnc"@en .
ngm:cnc-machine-tools a skos:Concept ;
rdfs:label "Cnc Machine Tools"@en .
ngm:cnc-machining a owl:Class ;
rdfs:comment "CNC (computer numerical control) machining is a subtractive manufacturing process in which programmed instructions drive automated cutting tools to remove material from a workpiece and produce precise parts. Toolpaths derived from a digital model control multi-axis motion of mills, lathes and routers to achieve tight tolerances and repeatable results. It is a cornerstone of precision manufacturing across metals, plastics and composites."@en ;
rdfs:label "CNC Machining"@en ;
rdfs:subClassOf ngm:precision-manufacturing ;
rdfs:subClassOf _:r3777 ;
vc:contrastsWith ngm:additive-manufacturing ;
vc:dependsOn ngm:automation ;
vc:enables ngm:digital-fabrication ;
vc:enables ngm:manufacturing-automation ;
vc:enables ngm:prototyping ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:motion-control ;
vc:isPartOf ngm:precision-manufacturing ;
vc:qualityScore "0.62"^^xsd:float ;
vc:slug "cnc-machining" ;
vc:sourceDomain "robotics" ;
vc:supports ngm:industrial-robotics ;
vc:supports ngm:robotics ;
vc:uses ngm:actuator ;
vc:uses ngm:cad-software ;
vc:uses ngm:computer-aided-design .
ngm:cncf a owl:Class ;
rdfs:comment "The Cloud Native Computing Foundation (CNCF) is a vendor-neutral, open-source foundation established in 2015 under the Linux Foundation to steward cloud-native software projects including Kubernetes, Prometheus, Envoy, and over 150 additional hosted projects. CNCF defines cloud-native computing as building and running scalable applications in modern, dynamic environments such as public, private, and hybrid clouds using techniques including containers, microservices, and declarative APIs. The Foundation operates a Technical Oversight Committee (TOC) that governs project acceptance through sandbox, incubating, and graduated maturity stages."@en ;
rdfs:label "CNCF"@en ;
rdfs:subClassOf ngm:linux-foundation ;
rdfs:subClassOf _:r3778 ;
rdfs:subClassOf _:r3779 ;
rdfs:subClassOf _:r3780 ;
rdfs:subClassOf _:r3781 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:enables ngm:cloud-native-applications ;
vc:enables ngm:container-orchestration ;
vc:enables ngm:microservices-architecture ;
vc:enables ngm:open-source-software ;
vc:enables ngm:platform-engineering ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:envoy-proxy ;
vc:hasPart ngm:kubernetes ;
vc:hasPart ngm:open-telemetry ;
vc:hasPart ngm:prometheus ;
vc:isPartOf ngm:linux-foundation ;
vc:isPartOf ngm:open-source ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:cloud-infrastructure ;
vc:relatedTo ngm:microservices ;
vc:relatedTo ngm:observability ;
vc:relatedTo ngm:open-container-initiative ;
vc:relatedTo ngm:service-mesh ;
vc:slug "cncf" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:standards-body ;
vc:standardizedBy ngm:technical-standards ;
vc:supports ngm:gitops ;
vc:supports ngm:supply-chain-security ;
vc:supports ngm:web-assembly .
ngm:cnn-dailymail-dataset a skos:Concept ;
rdfs:label "Cnn Dailymail Dataset"@en .
ngm:cns-drug-discovery a skos:Concept ;
rdfs:label "Cns Drug Discovery"@en .
ngm:co-ap a owl:Class ;
rdfs:comment "The Constrained Application Protocol (CoAP) is a specialised web transfer protocol defined in RFC 7252 (IETF, 2014) designed for use with constrained nodes and networks in the Internet of Things ecosystem. Modelled on HTTP's request-response semantics and RESTful resource model but optimised for low-power, lossy networks, CoAP uses UDP as its transport layer, features a compact binary header, supports observe (pub/sub) extensions, and includes built-in mechanisms for reliability, multicast, and asynchronous communication. CoAP is a cornerstone protocol for IoT device management and machine-to-machine communication."@en ;
rdfs:label "CoAP"@en ;
rdfs:subClassOf ngm:network-protocol ;
vc:contrastsWith ngm:http-protocol ;
vc:contrastsWith ngm:mqtt ;
vc:enables ngm:building-automation ;
vc:enables ngm:edge-computing ;
vc:enables ngm:internet-of-things ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:slug "co-ap" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:embedded-systems ;
vc:uses ngm:rest-api .
ngm:co-creation a owl:Class ;
rdfs:comment "Co-creation is a collaborative process in which two or more parties, including end users, jointly generate a product, design or piece of content rather than one party producing it for passive consumption by the others. It emphasises shared authorship and iterative feedback across the creative process, and is a common pattern in participatory design, open-source development and collaborative virtual environments. Co-creation is enabled by tools that support simultaneous, shared editing and by design methodologies that structure participant input."@en ;
rdfs:label "Co-creation"@en ;
rdfs:subClassOf ngm:collaboration ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:collaboration ;
vc:qualityScore "0.65"^^xsd:float ;
vc:slug "co-creation" ;
vc:sourceDomain "distributed-collaboration" .
ngm:co-design a skos:Concept ;
rdfs:label "Co Design"@en .
ngm:co-design-workshop a skos:Concept ;
rdfs:label "Co Design Workshop"@en .
ngm:co-evolution a skos:Concept ;
rdfs:label "Co Evolution"@en .
ngm:co-intelligence a skos:Concept ;
rdfs:label "Co Intelligence"@en .
ngm:co-intelligence-framework a skos:Concept ;
rdfs:label "Co Intelligence Framework"@en .
ngm:co-located-collaboration a skos:Concept ;
rdfs:label "Co Located Collaboration"@en .
ngm:co-location a skos:Concept ;
rdfs:label "Co Location"@en .
ngm:co-operative-governance a skos:Concept ;
rdfs:label "Co Operative Governance"@en .
ngm:co-operative-member-rights a skos:Concept ;
rdfs:label "Co Operative Member Rights"@en .
ngm:co-packaged-optics a skos:Concept ;
rdfs:label "Co Packaged Optics"@en .
ngm:co-presence a owl:Class ;
rdfs:comment "Co-presence is the sense that other people are sharing the same virtual or physical-digital space with a user at the same time, and can perceive and be perceived in return. It extends the individual sense of presence to a shared, social context, and is a key quality metric for telecollaboration and metaverse platforms, where avatars, spatial audio and non-verbal cues are used to reinforce the impression of being together. Strong co-presence is associated with more natural social interaction in virtual environments."@en ;
rdfs:label "Co-Presence"@en ;
rdfs:subClassOf ngm:presence ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:presence ;
vc:qualityScore "0.65"^^xsd:float ;
vc:slug "co-presence" ;
vc:sourceDomain "spatial-computing" .
ngm:co-regulation a owl:Class ;
rdfs:comment "Co-regulation is a governance model in which statutory authorities and industry actors jointly develop and enforce rules, blending the legitimacy and backstop powers of the state with the technical expertise and agility of the regulated sector. It sits between command-and-control regulation and pure self-regulation: codes of practice drafted by industry are approved and overseen by a public regulator that retains enforcement powers. The approach is common in online safety, broadcasting and data protection."@en ;
rdfs:label "Co Regulation"@en ;
rdfs:subClassOf ngm:regulatory-framework ;
rdfs:subClassOf _:r4495 ;
rdfs:subClassOf _:r4496 ;
vc:contrastsWith ngm:centralised-finance ;
vc:contrastsWith ngm:self-regulation ;
vc:enables ngm:data-governance ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:policy-framework ;
vc:implements ngm:regulation ;
vc:isPartOf ngm:regulatory-framework ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:content-moderation ;
vc:relatedTo ngm:ofcom ;
vc:relatedTo ngm:uk-online-safety-act ;
vc:requires ngm:accountability ;
vc:requires ngm:compliance ;
vc:slug "co-regulation" ;
vc:sourceDomain "governance" ;
vc:supports ngm:governance ;
vc:supports ngm:platform-governance ;
vc:uses ngm:audit ;
vc:uses ngm:transparency-reporting .
ngm:co-training a owl:Class ;
rdfs:comment "Co-training is a semi-supervised machine learning technique where two or more models trained on complementary feature views iteratively label unlabelled data for each other. Each model labels examples confidently classified under its own view, and these pseudo-labels are added to the other model's training set, bootstrapping performance without requiring large labelled corpora."@en ;
rdfs:label "Co Training"@en ;
rdfs:subClassOf ngm:ai-technique ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:autonomous-robot ;
vc:enables ngm:generative-ai ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:isPartOf ngm:semi-supervised-learning ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:active-learning ;
vc:relatedTo ngm:self-training ;
vc:slug "co-training" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:machine-learning-model .
ngm:coala a skos:Concept ;
rdfs:label "Coala"@en .
ngm:coala-model-dao-law a skos:Concept ;
rdfs:label "Coala Model DAO Law"@en .
ngm:coastal-monitoring a owl:Class ;
rdfs:label "Coastal Monitoring"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-applications ;
vc:slug "coastal-monitoring" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:coating a skos:Concept ;
rdfs:label "Coating"@en .
ngm:cobit a skos:Concept ;
rdfs:label "Cobit"@en .
ngm:cobit-framework a skos:Concept ;
rdfs:label "Cobit Framework"@en .
ngm:cobot-deployment a owl:Class ;
rdfs:comment "Cobot deployment is the process of installing and configuring a collaborative robot into a shared workspace with human operators, encompassing risk assessment, speed and separation monitoring, power and force limiting, and compliance with safety standards governing human-robot proximity. It translates abstract safety standards such as ISO/TS 15066 into a concrete, validated physical installation. Successful deployment requires certifying that the cobot's safety-rated monitored stop and force limits meet the standard's thresholds before it operates alongside people."@en ;
rdfs:label "Cobot Deployment"@en ;
rdfs:subClassOf ngm:collaborative-systems-modality-robot ;
rdfs:subClassOf _:r4497 ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.55"^^xsd:float ;
vc:requires ngm:collaborative-systems-modality-robot ;
vc:slug "cobot-deployment" ;
vc:sourceDomain "robotics" ;
vc:uses ngm:cobot-safety-levels .
ngm:cobot-safety-levels a owl:Class ;
rdfs:comment "Standardized safety classifications and requirements for collaborative robots (cobots) operating in shared workspaces with humans, defining protection measures, risk assessments, and operational modes to ensure safe human-robot interaction according to ISO/TS 15066."@en ;
rdfs:label "Cobot Safety Levels"@en ;
rdfs:subClassOf ngm:robo-safety-and-standards ;
rdfs:subClassOf ngm:safety-standard ;
rdfs:subClassOf _:r4498 ;
rdfs:subClassOf _:r4499 ;
skos:broader ngm:robo-safety-and-standards ;
vc:bridgesTo ngm:safety-standard ;
vc:bridgesTo ngm:telecollaboration ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:rb-0094-power-and-force-limiting ;
vc:implements ngm:rb-0105-speed-and-separation-monitoring ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:risk-assessment ;
vc:requires ngm:safety-certification ;
vc:slug "cobot-safety-levels" ;
vc:sourceDomain "robotics" .
ngm:cobotic-system a skos:Concept ;
rdfs:label "Cobotic System"@en .
ngm:coca a skos:Concept ;
rdfs:label "Coca"@en .
ngm:cockroachdb a skos:Concept ;
rdfs:label "Cockroachdb"@en .
ngm:coco-dataset a owl:Class ;
rdfs:comment "The COCO Dataset (Common Objects in Context) is a large-scale benchmark dataset for computer vision research comprising over 330,000 images with dense per-instance annotations covering object detection, instance segmentation, panoptic segmentation, keypoint estimation, and image captioning across 80 object categories in natural everyday scenes. Released in 2014 by Microsoft Research, it became the de-facto standard evaluation corpus for detection and segmentation models because its annotations capture objects in realistic, cluttered contexts rather than artificially isolated settings. COCO metrics—specifically Average Precision (AP) averaged across IoU thresholds—are the primary performance currency for reporting state-of-the-art results in visual perception research."@en ;
rdfs:label "COCO Dataset"@en ;
rdfs:subClassOf ngm:benchmarks ;
vc:enables ngm:instance-segmentation ;
vc:enables ngm:object-detection ;
vc:enables ngm:panoptic-segmentation ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:image-segmentation ;
vc:relatedTo ngm:machine-learning-model ;
vc:relatedTo ngm:object-recognition ;
vc:slug "coco-dataset" ;
vc:sourceDomain "ai" ;
vc:uses ngm:computer-vision ;
vc:uses ngm:data-annotation .
ngm:coco-wholebody a owl:Class ;
rdfs:comment "COCO WholeBody is an extension of the COCO dataset that adds dense whole-body keypoint annotations, covering the body, hands, feet, and face with 133 keypoints per person rather than the 17 body-only keypoints of the original COCO annotations. It is used to train and benchmark whole-body pose estimation models, including hand and facial landmark detectors used by tools such as DWPose. The extended annotation set enables downstream applications such as gesture recognition, sign-language interpretation, and fine-grained human motion capture from images."@en ;
rdfs:label "COCO WholeBody"@en ;
rdfs:subClassOf ngm:coco-dataset ;
vc:enables ngm:pose-estimation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:slug "coco-wholebody" ;
vc:sourceDomain "artificial-intelligence" .
ngm:code-based-cryptography a skos:Concept ;
rdfs:label "Code Based Cryptography"@en .
ngm:code-based-design a owl:Class ;
rdfs:comment "A design methodology where visual elements are generated and manipulated through code structures like SVGs rather than raster-based image synthesis."@en ;
rdfs:label "Code-based Design"@en ;
rdfs:subClassOf ngm:image-generation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:image-generation ;
vc:relatedTo ngm:svg-generation ;
vc:slug "code-based-design" ;
vc:sourceDomain "artificial-intelligence" .
ngm:code-corpus a skos:Concept ;
rdfs:label "Code Corpus"@en .
ngm:code-coverage a skos:Concept ;
rdfs:label "Code Coverage"@en .
ngm:code-embedding a skos:Concept ;
rdfs:label "Code Embedding"@en .
ngm:code-embedding-model a skos:Concept ;
rdfs:label "Code Embedding Model"@en .
ngm:code-execution a owl:Class ;
rdfs:comment "Code execution, in the context of AI agents, is the capability whereby a model generates source code and runs it in a sandboxed interpreter or runtime, then incorporates the results into its reasoning. It transforms a language model from a text generator into a tool-using agent that can compute, manipulate data, call APIs, and verify outputs programmatically. It matters because executable tool use grounds agent behaviour in deterministic computation and extends capabilities beyond what next-token prediction alone can achieve."@en ;
rdfs:label "Code Execution"@en ;
rdfs:subClassOf ngm:agentic-workflow ;
rdfs:subClassOf ngm:ai-agent-system ;
rdfs:subClassOf ngm:ai-agent-systems ;
rdfs:subClassOf ngm:cli-multi-agent-systems ;
rdfs:subClassOf ngm:llm-agents ;
rdfs:subClassOf ngm:tool-use ;
rdfs:subClassOf _:r4500 ;
rdfs:subClassOf _:r4501 ;
rdfs:subClassOf _:r4502 ;
rdfs:subClassOf _:r4503 ;
rdfs:subClassOf _:r4504 ;
rdfs:subClassOf _:r4505 ;
rdfs:subClassOf _:r4506 ;
rdfs:subClassOf _:r4507 ;
rdfs:subClassOf _:r4508 ;
rdfs:subClassOf _:r4509 ;
rdfs:subClassOf _:r4510 ;
rdfs:subClassOf _:r4511 ;
rdfs:subClassOf _:r4512 ;
vc:contrastsWith ngm:code-generation ;
vc:contrastsWith ngm:formal-verification ;
vc:contrastsWith ngm:low-code-platform ;
vc:contrastsWith ngm:robotic-process-automation ;
vc:contrastsWith ngm:static-analysis ;
vc:contrastsWith ngm:symbolic-execution ;
vc:dependsOn ngm:code-generation ;
vc:dependsOn ngm:function-calling ;
vc:dependsOn ngm:large-language-models ;
vc:dependsOn ngm:orchestration ;
vc:dependsOn ngm:prompt-engineering ;
vc:dependsOn ngm:reinforcement-learning ;
vc:dependsOn ngm:state-management ;
vc:dependsOn ngm:tool-use ;
vc:enables ngm:agentic-workflow ;
vc:enables ngm:api-integration ;
vc:enables ngm:automated-code-review ;
vc:enables ngm:automated-testing ;
vc:enables ngm:autonomous-debugging ;
vc:enables ngm:ci-cd-automation ;
vc:enables ngm:data-analysis ;
vc:enables ngm:dev-sec-ops ;
vc:enables ngm:repository-scale-refactoring ;
vc:enables ngm:self-correcting-agent ;
vc:enables ngm:software-engineering-agents ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:bash ;
vc:hasPart ngm:docker-containerisation-platform ;
vc:hasPart ngm:execution-timeout ;
vc:hasPart ngm:firecracker ;
vc:hasPart ngm:gvisor ;
vc:hasPart ngm:output-parser ;
vc:hasPart ngm:python ;
vc:hasPart ngm:resource-governance ;
vc:hasPart ngm:sandbox-environment ;
vc:hasPart ngm:sandboxed-code-execution ;
vc:hasPart ngm:shell-environment ;
vc:hasPart ngm:state-management ;
vc:implements ngm:auto-gen ;
vc:implements ngm:cli-multi-agent-systems ;
vc:implements ngm:codeact ;
vc:implements ngm:lang-graph ;
vc:implements ngm:openhands ;
vc:implements ngm:re-act ;
vc:implements ngm:swe-agent ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:agent-orchestrator ;
vc:relatedTo ngm:automated-testing ;
vc:relatedTo ngm:cli-multi-agent-systems ;
vc:relatedTo ngm:code-generation ;
vc:relatedTo ngm:function-calling ;
vc:relatedTo ngm:infrastructure-as-code ;
vc:relatedTo ngm:inter-agent-communication ;
vc:relatedTo ngm:llm-agents ;
vc:relatedTo ngm:orchestration ;
vc:relatedTo ngm:planning-agent ;
vc:relatedTo ngm:reinforcement-learning ;
vc:relatedTo ngm:software-engineering-agents ;
vc:relatedTo ngm:tool-use ;
vc:requires ngm:code-generation ;
vc:requires ngm:docker-containerisation-platform ;
vc:requires ngm:firecracker ;
vc:requires ngm:function-calling ;
vc:requires ngm:large-language-models ;
vc:requires ngm:model-context-protocol ;
vc:requires ngm:prompt-engineering ;
vc:requires ngm:sandbox-environment ;
vc:requires ngm:tool-schema ;
vc:slug "code-execution" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:agent2-agent-protocol ;
vc:standardizedBy ngm:model-context-protocol ;
vc:standardizedBy ngm:openai-research-organisation-agents-sdk ;
vc:supports ngm:agentic-workflow ;
vc:supports ngm:automated-testing ;
vc:supports ngm:ci-cd-automation ;
vc:supports ngm:cli-multi-agent-systems ;
vc:supports ngm:dev-sec-ops ;
vc:supports ngm:human-in-the-loop-learning ;
vc:supports ngm:planning-agent ;
vc:supports ngm:software-engineering-agents ;
vc:supports ngm:task-decomposition ;
vc:uses ngm:bash ;
vc:uses ngm:docker-containerisation-platform ;
vc:uses ngm:e2b ;
vc:uses ngm:firecracker ;
vc:uses ngm:git ;
vc:uses ngm:gvisor ;
vc:uses ngm:model-context-protocol ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:open-telemetry ;
vc:uses ngm:python .
ngm:code-executor a skos:Concept ;
rdfs:label "Code Executor"@en .
ngm:code-first-education a skos:Concept ;
rdfs:label "Code First Education"@en .
ngm:code-former a owl:Class ;
rdfs:comment "CodeFormer is a Transformer-based blind face restoration model that combines a discrete codebook prior — learned via a vector-quantised autoencoder — with a controllable fidelity-quality trade-off mechanism, allowing it to recover high-quality facial details from severely degraded inputs such as low-resolution, compressed, or heavily noisy images. Unlike earlier GAN-based restoration approaches, CodeFormer's codebook provides rich, semantically plausible facial priors that guide reconstruction without requiring clean reference images, and its fidelity weight parameter lets users tune the balance between realism and fidelity to the original degraded input. The model generalises to face enhancement tasks in AI-generated images, old photo restoration, and video face restoration."@en ;
rdfs:label "CodeFormer"@en ;
rdfs:subClassOf ngm:blind-image-restoration ;
rdfs:subClassOf ngm:computer-vision ;
rdfs:subClassOf ngm:deep-learning ;
rdfs:subClassOf ngm:face-recognition ;
rdfs:subClassOf ngm:generative-ai ;
rdfs:subClassOf ngm:image-restoration ;
rdfs:subClassOf _:r4531 ;
rdfs:subClassOf _:r4532 ;
rdfs:subClassOf _:r4533 ;
rdfs:subClassOf _:r4534 ;
rdfs:subClassOf _:r4535 ;
rdfs:subClassOf _:r4536 ;
rdfs:subClassOf _:r4537 ;
vc:bridgesTo ngm:cultural-heritage-digitisation ;
vc:bridgesTo ngm:forensic-imaging ;
vc:bridgesTo ngm:medical-imaging ;
vc:bridgesTo ngm:on-device-learning ;
vc:contrastsWith ngm:diffbir ;
vc:contrastsWith ngm:diffusion-model ;
vc:contrastsWith ngm:generative-adversarial-network ;
vc:contrastsWith ngm:gfpgan ;
vc:contrastsWith ngm:real-esrgan ;
vc:contrastsWith ngm:stylegan ;
vc:contrastsWith ngm:vqfr ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:gpu-compute ;
vc:dependsOn ngm:image-processing ;
vc:dependsOn ngm:loss-function ;
vc:dependsOn ngm:neural-network ;
vc:dependsOn ngm:training-data ;
vc:enables ngm:ai-image-enhancement ;
vc:enables ngm:computer-vision ;
vc:enables ngm:deepfake-detection ;
vc:enables ngm:generative-ai ;
vc:enables ngm:old-photo-restoration ;
vc:enables ngm:portrait-enhancement ;
vc:enables ngm:video-restoration ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:codebook-prior ;
vc:hasPart ngm:convolutional-neural-network ;
vc:hasPart ngm:face-detection-module ;
vc:hasPart ngm:fidelity-weight-controller ;
vc:hasPart ngm:multi-head-attention ;
vc:hasPart ngm:perceptual-loss-function ;
vc:hasPart ngm:self-attention ;
vc:hasPart ngm:transformer ;
vc:hasPart ngm:vector-quantization ;
vc:implements ngm:blind-image-restoration ;
vc:implements ngm:codebook-lookup ;
vc:implements ngm:discrete-latent-representation ;
vc:implements ngm:image-to-image-translation ;
vc:implements ngm:transformer-attention ;
vc:implements ngm:vector-quantized-autoencoder ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:ai-upscaling-and-super-resolution ;
vc:relatedTo ngm:comfy-ui ;
vc:relatedTo ngm:diffbir ;
vc:relatedTo ngm:esrgan ;
vc:relatedTo ngm:generative-adversarial-network ;
vc:relatedTo ngm:image-classification ;
vc:relatedTo ngm:inpainting ;
vc:relatedTo ngm:object-detection ;
vc:relatedTo ngm:stable-diffusion-image-model ;
vc:relatedTo ngm:super-resolution ;
vc:relatedTo ngm:supir ;
vc:relatedTo ngm:vqfr ;
vc:relatedTo ngm:vqgan ;
vc:requires ngm:backpropagation ;
vc:requires ngm:face-alignment ;
vc:requires ngm:face-detection ;
vc:requires ngm:ffhq-dataset ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:training-data ;
vc:slug "code-former" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:neurips-2022 ;
vc:standardizedBy ngm:ntire-2025 ;
vc:standardizedBy ngm:s-lab-license ;
vc:supports ngm:archival-photo-restoration ;
vc:supports ngm:cultural-heritage-digitisation ;
vc:supports ngm:film-vfx ;
vc:supports ngm:forensic-imaging ;
vc:supports ngm:media-production ;
vc:supports ngm:medical-imaging ;
vc:supports ngm:social-media-image-enhancement ;
vc:uses ngm:arc-face ;
vc:uses ngm:convolutional-neural-network ;
vc:uses ngm:diffusion-transformer ;
vc:uses ngm:image-processing ;
vc:uses ngm:loss-function ;
vc:uses ngm:perceptual-loss-function ;
vc:uses ngm:self-attention ;
vc:uses ngm:transformer ;
vc:uses ngm:vector-quantization ;
vc:uses ngm:vgg .
ngm:code-generation a owl:Class ;
rdfs:comment "The automated production of source code by AI systems from natural language specifications, partial code, or structured prompts. Code generation systems leverage large language models trained on code corpora to synthesise functions, classes, and complete programs, accelerating software development workflows."@en ;
rdfs:label "Code Generation"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf ngm:generative-ai ;
rdfs:subClassOf ngm:large-language-models ;
rdfs:subClassOf ngm:program-synthesis ;
rdfs:subClassOf _:r4513 ;
rdfs:subClassOf _:r4514 ;
rdfs:subClassOf _:r4515 ;
rdfs:subClassOf _:r4516 ;
rdfs:subClassOf _:r4517 ;
rdfs:subClassOf _:r4518 ;
rdfs:subClassOf _:r4519 ;
rdfs:subClassOf _:r4520 ;
rdfs:subClassOf _:r4521 ;
rdfs:subClassOf _:r4522 ;
rdfs:subClassOf _:r4523 ;
rdfs:subClassOf _:r4524 ;
rdfs:subClassOf _:r4525 ;
rdfs:subClassOf _:r4526 ;
skos:broader ngm:artificial-intelligence ;
vc:bridgesTo ngm:infrastructure-as-code ;
vc:bridgesTo ngm:smart-contract ;
vc:contrastsWith ngm:compiler-technology ;
vc:contrastsWith ngm:formal-verification ;
vc:contrastsWith ngm:low-code-platform ;
vc:contrastsWith ngm:manual-programming ;
vc:contrastsWith ngm:robotic-process-automation ;
vc:contrastsWith ngm:static-analysis ;
vc:contrastsWith ngm:symbolic-ai ;
vc:contrastsWith ngm:transpilation ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:distributed-training ;
vc:dependsOn ngm:large-language-models ;
vc:dependsOn ngm:neural-network ;
vc:dependsOn ngm:self-supervised-learning ;
vc:enables ngm:ai-augmented-software-engineering ;
vc:enables ngm:automated-code-review ;
vc:enables ngm:cli-multi-agent-systems ;
vc:enables ngm:continuous-integration ;
vc:enables ngm:documentation-generation ;
vc:enables ngm:infrastructure-as-code ;
vc:enables ngm:repository-scale-refactoring ;
vc:enables ngm:smart-contract ;
vc:enables ngm:software-development-process ;
vc:enables ngm:test-driven-development ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:attention-mechanism ;
vc:hasPart ngm:chain-of-thought ;
vc:hasPart ngm:embedding ;
vc:hasPart ngm:fine-tuning ;
vc:hasPart ngm:prompt-engineering ;
vc:hasPart ngm:tokenization ;
vc:hasPart ngm:training-data ;
vc:hasPart ngm:transformer-architecture ;
vc:implements ngm:program-synthesis ;
vc:implements ngm:re-act ;
vc:implements ngm:reinforcement-learning-from-human-feedback ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:automated-testing ;
vc:relatedTo ngm:cli-multi-agent-systems ;
vc:relatedTo ngm:code-execution ;
vc:relatedTo ngm:deep-learning ;
vc:relatedTo ngm:devops ;
vc:relatedTo ngm:infrastructure-as-code ;
vc:relatedTo ngm:llm-agents ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:smart-contract ;
vc:relatedTo ngm:software-architecture ;
vc:relatedTo ngm:software-testing ;
vc:relatedTo ngm:static-analysis ;
vc:relatedTo ngm:zero-shot-learning ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:large-language-models ;
vc:requires ngm:neural-network ;
vc:requires ngm:reinforcement-learning-from-human-feedback ;
vc:requires ngm:self-supervised-learning ;
vc:requires ngm:training-data ;
vc:slug "code-generation" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:bigcode-project ;
vc:standardizedBy ngm:humaneval-benchmark ;
vc:standardizedBy ngm:nist-ai-standards ;
vc:standardizedBy ngm:swe-bench ;
vc:supports ngm:agentic-ai ;
vc:supports ngm:agile-software-development ;
vc:supports ngm:automated-testing ;
vc:supports ngm:dev-sec-ops ;
vc:supports ngm:devops ;
vc:supports ngm:software-architecture ;
vc:uses ngm:attention-mechanism ;
vc:uses ngm:chain-of-thought ;
vc:uses ngm:distributed-training ;
vc:uses ngm:embedding ;
vc:uses ngm:few-shot-learning ;
vc:uses ngm:fine-tuning ;
vc:uses ngm:foundation-model ;
vc:uses ngm:gpu-compute ;
vc:uses ngm:large-language-models ;
vc:uses ngm:model-optimization ;
vc:uses ngm:prompt-engineering ;
vc:uses ngm:reinforcement-learning-from-human-feedback ;
vc:uses ngm:self-supervised-learning ;
vc:uses ngm:tokenization ;
vc:uses ngm:training-data ;
vc:uses ngm:transformer-architecture ;
vc:uses ngm:zero-shot-learning .
ngm:code-interpretation-service a skos:Concept ;
rdfs:label "Code Interpretation Service"@en .
ngm:code-maintainability a skos:Concept ;
rdfs:label "Code Maintainability"@en .
ngm:code-navigation a skos:Concept ;
rdfs:label "Code Navigation"@en .
ngm:code-of-conduct a skos:Concept ;
rdfs:label "Code Of Conduct"@en .
ngm:code-profiling a skos:Concept ;
rdfs:label "Code Profiling"@en .
ngm:code-quality-assurance a skos:Concept ;
rdfs:label "Code Quality Assurance"@en .
ngm:code-review a owl:Class ;
rdfs:comment "Code review is the systematic, human-led examination of proposed source code changes by one or more reviewers other than the original author, intended to detect defects, enforce coding standards, and disseminate architectural knowledge across a development team. It is most commonly performed asynchronously via pull requests or merge requests in version-controlled repositories, augmented by automated static analysis, linting, and continuous integration checks. Effective code review functions as both a quality gate and a collaborative learning mechanism, reducing the cost of defects by catching them before integration into the main codebase. It is a foundational practice in professional software engineering, distributed-collaboration workflows, and secure development lifecycles."@en ;
rdfs:label "Code Review"@en ;
rdfs:subClassOf ngm:software-engineering ;
rdfs:subClassOf _:r4527 ;
rdfs:subClassOf _:r4528 ;
vc:bridgesTo ngm:automated-code-review ;
vc:bridgesTo ngm:large-language-model ;
vc:contrastsWith ngm:formal-inspection ;
vc:contrastsWith ngm:pair-programming ;
vc:dependsOn ngm:collaborative-workflow ;
vc:dependsOn ngm:source-code-management ;
vc:enables ngm:continuous-integration ;
vc:enables ngm:knowledge-sharing ;
vc:enables ngm:quality-assurance ;
vc:enables ngm:secure-development-lifecycle ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:devops ;
vc:isPartOf ngm:software-development ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:agile-software-development ;
vc:relatedTo ngm:open-source-development ;
vc:relatedTo ngm:refactoring ;
vc:requires ngm:coding-standards ;
vc:requires ngm:pull-request ;
vc:requires ngm:version-control ;
vc:slug "code-review" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:code-maintainability ;
vc:supports ngm:software-testing ;
vc:supports ngm:technical-debt-management ;
vc:uses ngm:diff-algorithm ;
vc:uses ngm:inline-commenting ;
vc:uses ngm:static-analysis .
ngm:code-search a skos:Concept ;
rdfs:label "Code Search"@en .
ngm:code-signing a owl:Class ;
rdfs:comment "Code Signing is a cryptographic practice in which software publishers digitally sign executables, scripts, container images, and other software artefacts using a private key, enabling recipients to verify the artefact's authenticity and integrity through the corresponding public key certificate. Implemented via asymmetric cryptography and X.509 certificate chains anchored to trusted Certificate Authorities or transparency logs, code signing is a fundamental control in software supply chain security, preventing the distribution of tampered or malicious software. Modern approaches include keyless signing via short-lived certificates and cryptographic transparency logs."@en ;
rdfs:label "Code Signing"@en ;
rdfs:subClassOf ngm:cryptographic-signing ;
rdfs:subClassOf _:r4529 ;
rdfs:subClassOf _:r4530 ;
vc:bridgesTo ngm:infrastructure ;
vc:bridgesTo ngm:supply-chain ;
vc:enables ngm:provenance-tracking ;
vc:enables ngm:secure-boot ;
vc:enables ngm:supply-chain-traceability ;
vc:enables ngm:tee ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:non-repudiation ;
vc:implements ngm:supply-chain-security ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:notary-service ;
vc:relatedTo ngm:sigstore ;
vc:relatedTo ngm:supply-chain ;
vc:requires ngm:certificate-revocation ;
vc:requires ngm:key-management ;
vc:slug "code-signing" ;
vc:sourceDomain "security" ;
vc:supports ngm:slsa-framework ;
vc:supports ngm:software-bill-of-materials ;
vc:uses ngm:asymmetric-cryptography ;
vc:uses ngm:certificate-authority ;
vc:uses ngm:cryptographic-hash-function ;
vc:uses ngm:cryptographic-infrastructure ;
vc:uses ngm:digital-signature ;
vc:uses ngm:x-509-certificate .
ngm:code-summarisation a skos:Concept ;
rdfs:label "Code Summarisation"@en .
ngm:code-switching a skos:Concept ;
rdfs:label "Code Switching"@en .
ngm:code-synthesis a skos:Concept ;
rdfs:label "Code Synthesis"@en .
ngm:code-to-diagram-reverse-engineering a skos:Concept ;
rdfs:label "Code To Diagram Reverse Engineering"@en .
ngm:code-understanding a skos:Concept ;
rdfs:label "Code Understanding"@en .
ngm:code-verification a skos:Concept ;
rdfs:label "Code Verification"@en .
ngm:code-walkthrough a skos:Concept ;
rdfs:label "Code Walkthrough"@en .
ngm:codeact a skos:Concept ;
rdfs:label "Codeact"@en .
ngm:codebert a skos:Concept ;
rdfs:label "Codebert"@en .
ngm:codebook-lookup a skos:Concept ;
rdfs:label "Codebook Lookup"@en .
ngm:codebook-prior a skos:Concept ;
rdfs:label "Codebook Prior"@en .
ngm:codec a owl:Class ;
rdfs:comment "A codec is a piece of software or hardware that encodes data into a compressed or transmittable format and decodes it back for use, applied to audio, video or general data streams. Codecs trade off compression ratio, computational cost and fidelity, and a specific data format's specification typically names the codec, or set of permitted codecs, it requires. Screen recording software depends on a codec to encode captured frames into a storable video file in real time."@en ;
rdfs:label "Codec"@en ;
rdfs:subClassOf ngm:data-format ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:slug "codec" ;
vc:sourceDomain "infrastructure" .
ngm:codec-ecosystem a skos:Concept ;
rdfs:label "Codec Ecosystem"@en .
ngm:codec-licensing a skos:Concept ;
rdfs:label "Codec Licensing"@en .
ngm:codec-parameter-controller a skos:Concept ;
rdfs:label "Codec Parameter Controller"@en .
ngm:codes-of-practice a skos:Concept ;
rdfs:label "Codes Of Practice"@en .
ngm:codet5 a skos:Concept ;
rdfs:label "Codet5"@en .
ngm:codex-alimentarius a skos:Concept ;
rdfs:label "Codex Alimentarius"@en .
ngm:coding-agents a skos:Concept ;
rdfs:label "Coding Agents"@en .
ngm:coding-assistant a skos:Concept ;
rdfs:label "Coding Assistant"@en .
ngm:coding-copilots a skos:Concept ;
rdfs:label "Coding Copilots"@en .
ngm:coding-standards a skos:Concept ;
rdfs:label "Coding Standards"@en .
ngm:coding-theory a owl:Class ;
rdfs:comment "The mathematical study of codes — structured mappings from messages to symbol sequences — and of their properties for reliable, efficient representation and transmission of information. Spanning error-correcting codes that add redundancy to detect and repair corruption, source codes that compress data towards its entropy, and cryptographic and network codes, coding theory turns Shannon's existence theorems into constructive schemes such as Hamming, Reed-Solomon, LDPC, turbo, and polar codes that underpin storage, networking, and broadcasting."@en ;
rdfs:label "Coding Theory"@en ;
rdfs:subClassOf ngm:information-theory ;
rdfs:subClassOf _:r4538 ;
rdfs:subClassOf _:r4539 ;
vc:enables ngm:data-compression ;
vc:enables ngm:erasure-coding ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:error-correction ;
vc:hasPart ngm:reed-solomon-codes ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:computational-complexity-theory ;
vc:slug "coding-theory" ;
vc:sourceDomain "data" .
ngm:coercive-statecraft a skos:Concept ;
rdfs:label "Coercive Statecraft"@en .
ngm:cognitive-accessibility a skos:Concept ;
rdfs:label "Cognitive Accessibility"@en .
ngm:cognitive-ai a owl:Class ;
rdfs:comment "Cognitive AI is the family of artificial-intelligence systems built around cognitively-plausible architectures that explicitly model the components and information-flow of human cognition — working memory, declarative and procedural long-term memory, perception-action loops, attention, production..."@en ;
rdfs:label "Cognitive AI"@en ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf ngm:cognitive-architecture ;
rdfs:subClassOf ngm:cognitive-science ;
rdfs:subClassOf ngm:hybrid-ai ;
rdfs:subClassOf ngm:neuro-symbolic-ai ;
rdfs:subClassOf _:r4540 ;
rdfs:subClassOf _:r4541 ;
rdfs:subClassOf _:r4542 ;
rdfs:subClassOf _:r4543 ;
rdfs:subClassOf _:r4544 ;
rdfs:subClassOf _:r4545 ;
rdfs:subClassOf _:r4546 ;
rdfs:subClassOf _:r4547 ;
skos:broader ngm:ai-research-area ;
skos:broader ngm:artificial-intelligence ;
vc:contrastsWith ngm:black-box-machine-learning ;
vc:contrastsWith ngm:deep-learning ;
vc:contrastsWith ngm:end-to-end-neural-network ;
vc:contrastsWith ngm:pure-symbolic-ai ;
vc:contrastsWith ngm:statistical-nlp ;
vc:dependsOn ngm:cognitive-psychology ;
vc:dependsOn ngm:computational-neuroscience ;
vc:dependsOn ngm:logic-programming ;
vc:dependsOn ngm:probabilistic-inference ;
vc:dependsOn ngm:reinforcement-learning ;
vc:enables ngm:cognitive-modelling ;
vc:enables ngm:continual-learning ;
vc:enables ngm:decision-support ;
vc:enables ngm:explainable-reasoning ;
vc:enables ngm:human-machine-teaming ;
vc:enables ngm:intelligent-tutoring-system ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:chunking-mechanism ;
vc:hasPart ngm:declarative-memory ;
vc:hasPart ngm:goal-stack ;
vc:hasPart ngm:metacognitive-controller ;
vc:hasPart ngm:motor-module ;
vc:hasPart ngm:perception-module ;
vc:hasPart ngm:procedural-memory ;
vc:hasPart ngm:production-rules ;
vc:hasPart ngm:working-memory ;
vc:implements ngm:act-r ;
vc:implements ngm:clarion ;
vc:implements ngm:coala ;
vc:implements ngm:companion-cognitive-architecture ;
vc:implements ngm:lida ;
vc:implements ngm:nars ;
vc:implements ngm:sigma-architecture ;
vc:implements ngm:soar ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:artificial-general-intelligence ;
vc:relatedTo ngm:common-sense-reasoning ;
vc:relatedTo ngm:embodied-ai ;
vc:relatedTo ngm:global-workspace-theory ;
vc:relatedTo ngm:neuromorphic-computing ;
vc:relatedTo ngm:predictive-processing ;
vc:requires ngm:conflict-resolution ;
vc:requires ngm:inference-engine ;
vc:requires ngm:knowledge-representation ;
vc:requires ngm:memory-indexing ;
vc:requires ngm:symbol-grounding ;
vc:slug "cognitive-ai" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:aaai-cognitive-systems ;
vc:standardizedBy ngm:advances-in-cognitive-systems-journal ;
vc:standardizedBy ngm:cognitive-science-society ;
vc:standardizedBy ngm:iccm-conference ;
vc:standardizedBy ngm:soar ;
vc:supports ngm:cognitive-engineering ;
vc:supports ngm:defence-decision-support ;
vc:supports ngm:education-technology ;
vc:supports ngm:human-computer-interaction ;
vc:supports ngm:pilot-training ;
vc:uses ngm:bayesian-inference ;
vc:uses ngm:large-language-model ;
vc:uses ngm:large-language-models ;
vc:uses ngm:production-system ;
vc:uses ngm:semantic-network ;
vc:uses ngm:spreading-activation ;
vc:uses ngm:vector-embedding .
ngm:cognitive-architecture a owl:Class ;
rdfs:comment "A cognitive architecture is a formal specification of the fixed computational structures, memory systems, and control mechanisms that together constitute a general-purpose intelligent agent, independent of any particular task or domain. It prescribes how perception, attention, memory retrieval, reasoning, learning, and action selection are integrated into a unified processing cycle, providing a theoretical and engineering framework for building systems that exhibit adaptive, goal-directed behaviour. Classical examples include ACT-R (Adaptive Control of Thought–Rational), SOAR, and LIDA; contemporary variants extend these principles to neural-symbolic hybrids, transformer-based agent frameworks, and large language model scaffolding systems. Cognitive architectures serve simultaneously as psychological theories of the human mind and as blueprints for artificial intelligence systems."@en ;
rdfs:label "Cognitive Architecture"@en ;
rdfs:subClassOf ngm:agent ;
rdfs:subClassOf ngm:agent-based-modelling ;
rdfs:subClassOf ngm:ai-model-architecture ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf _:r4548 ;
rdfs:subClassOf _:r4549 ;
rdfs:subClassOf _:r4550 ;
rdfs:subClassOf _:r4551 ;
rdfs:subClassOf _:r4552 ;
rdfs:subClassOf _:r4553 ;
rdfs:subClassOf _:r4554 ;
rdfs:subClassOf _:r4555 ;
rdfs:subClassOf _:r4556 ;
rdfs:subClassOf _:r4557 ;
skos:broader ngm:ai-model-architecture ;
skos:broader ngm:artificial-intelligence ;
vc:bridgesTo ngm:brain-computer-interfaces ;
vc:bridgesTo ngm:multi-agent-systems ;
vc:bridgesTo ngm:robotics ;
vc:contrastsWith ngm:deep-learning ;
vc:contrastsWith ngm:narrow-ai ;
vc:contrastsWith ngm:task-specific-model ;
vc:dependsOn ngm:cognitive-psychology ;
vc:dependsOn ngm:cognitive-science ;
vc:dependsOn ngm:computational-neuroscience ;
vc:dependsOn ngm:decision-making ;
vc:enables ngm:agentic-ai ;
vc:enables ngm:autonomous-agent ;
vc:enables ngm:cognitive-modelling ;
vc:enables ngm:expert-systems ;
vc:enables ngm:explainable-ai ;
vc:enables ngm:human-computer-interaction ;
vc:enables ngm:intelligent-tutoring-system ;
vc:enables ngm:symbolic-reasoning ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:action-selection ;
vc:hasPart ngm:declarative-memory ;
vc:hasPart ngm:goal-directed-behaviour ;
vc:hasPart ngm:long-term-memory ;
vc:hasPart ngm:meta-cognition ;
vc:hasPart ngm:perception ;
vc:hasPart ngm:planning-and-scheduling ;
vc:hasPart ngm:procedural-memory ;
vc:hasPart ngm:production-rules ;
vc:hasPart ngm:reasoning ;
vc:hasPart ngm:working-memory ;
vc:implements ngm:agent-loop ;
vc:implements ngm:chain-of-thought ;
vc:implements ngm:global-workspace-theory ;
vc:implements ngm:re-act-pattern ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:cognitive-psychology ;
vc:relatedTo ngm:cognitive-science ;
vc:relatedTo ngm:computational-neuroscience ;
vc:relatedTo ngm:decision-making ;
vc:relatedTo ngm:foundation-model ;
vc:relatedTo ngm:general-intelligence ;
vc:relatedTo ngm:global-workspace-theory ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:multi-agent-systems ;
vc:relatedTo ngm:neuro-symbolic-ai ;
vc:relatedTo ngm:transformer-architecture ;
vc:requires ngm:knowledge-representation ;
vc:requires ngm:machine-learning-discipline ;
vc:requires ngm:ontology ;
vc:requires ngm:production-rules ;
vc:slug "cognitive-architecture" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:darpa-xai-programme ;
vc:standardizedBy ngm:ieee-p7001 ;
vc:supports ngm:ai-alignment ;
vc:supports ngm:ai-safety ;
vc:supports ngm:natural-language-processing ;
vc:uses ngm:agent-memory ;
vc:uses ngm:attention-mechanism ;
vc:uses ngm:bayesian-inference ;
vc:uses ngm:knowledge-graph ;
vc:uses ngm:neural-network ;
vc:uses ngm:probabilistic-graphical-models ;
vc:uses ngm:reinforcement-learning ;
vc:uses ngm:retrieval-augmented-generation .
ngm:cognitive-augmentation a skos:Concept ;
rdfs:label "Cognitive Augmentation"@en .
ngm:cognitive-automation-revolution a owl:Class ;
rdfs:comment "The Cognitive Revolution describes the transformative societal shift driven by AI systems automating cognitive and knowledge work at scale, drawing analogy to the Industrial Revolution's mechanisation of physical labour. It encompasses the displacement of routine mental tasks—coding, content creation, data analysis—freeing human effort for higher-order creativity and judgement, whilst raising urgent questions about workforce adaptation and economic equity."@en ;
rdfs:label "Cognitive Automation Revolution"@en ;
rdfs:subClassOf ngm:ai-research-area ;
skos:broader ngm:ai-research-area ;
vc:contrastsWith ngm:ai-impact-assessment ;
vc:enables ngm:workflow-automation ;
vc:enables ngm:workforce-augmentation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:ai-adoption ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:generative-ai ;
vc:slug "cognitive-automation-revolution" ;
vc:sourceDomain "artificial-intelligence" .
ngm:cognitive-bias a skos:Concept ;
rdfs:label "Cognitive Bias"@en .
ngm:cognitive-constraints a skos:Concept ;
rdfs:label "Cognitive Constraints"@en .
ngm:cognitive-engineering a skos:Concept ;
rdfs:label "Cognitive Engineering"@en .
ngm:cognitive-enhancement a skos:Concept ;
rdfs:label "Cognitive Enhancement"@en .
ngm:cognitive-ergonomics a skos:Concept ;
rdfs:label "Cognitive Ergonomics"@en .
ngm:cognitive-feedback-interface a owl:Class ;
rdfs:comment "Adaptive interface system that dynamically adjusts information flow and interaction modalities based on real-time assessment of user cognitive state, attention levels, and mental workload."@en ;
rdfs:label "Cognitive Feedback Interface"@en ;
rdfs:subClassOf ngm:sc-interaction ;
rdfs:subClassOf _:r4558 ;
rdfs:subClassOf _:r4559 ;
rdfs:subClassOf _:r4560 ;
rdfs:subClassOf _:r4561 ;
skos:broader ngm:sc-interaction ;
vc:bridgesTo ngm:sensor-input ;
vc:dependsOn ngm:biometric-sensors ;
vc:dependsOn ngm:neurofeedback-system ;
vc:dependsOn ngm:real-time-analytics ;
vc:enables ngm:adaptive-interfaces ;
vc:enables ngm:attention-aware-interaction ;
vc:enables ngm:cognitive-load-management ;
vc:enables ngm:personalized-experiences ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:adaptive-ui-controller ;
vc:hasPart ngm:attention-tracker ;
vc:hasPart ngm:cognitive-state-monitor ;
vc:hasPart ngm:workload-analyzer ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:brain-computer-interfaces ;
vc:requires ngm:cognitive-model ;
vc:requires ngm:eye-tracking ;
vc:requires ngm:machine-learning-discipline ;
vc:slug "cognitive-feedback-interface" ;
vc:sourceDomain "spatial-computing" .
ngm:cognitive-immersion a skos:Concept ;
rdfs:label "Cognitive Immersion"@en .
ngm:cognitive-load a owl:Class ;
rdfs:comment "Cognitive load is the total amount of working-memory resource demanded by a task, interface, or learning activity at a given moment. It is commonly decomposed into intrinsic load (inherent task difficulty), extraneous load (imposed by poor presentation), and germane load (effort devoted to building durable mental schemas). Managing cognitive load is a central goal of user-experience and interaction design, since exceeding a user's capacity degrades comprehension, accuracy, and satisfaction."@en ;
rdfs:label "Cognitive Load"@en ;
rdfs:subClassOf ngm:user-experience ;
rdfs:subClassOf _:r4562 ;
vc:bridgesTo ngm:ergonomics ;
vc:contrastsWith ngm:affordance ;
vc:dependsOn ngm:attention ;
vc:dependsOn ngm:working-memory ;
vc:enables ngm:user-research ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:user-experience ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:human-computer-interaction ;
vc:relatedTo ngm:mental-model ;
vc:relatedTo ngm:usability ;
vc:requires ngm:attention ;
vc:slug "cognitive-load" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:usability ;
vc:uses ngm:mental-model .
ngm:cognitive-load-management a skos:Concept ;
rdfs:label "Cognitive Load Management"@en .
ngm:cognitive-load-metric a owl:Class ;
rdfs:comment "Quantitative measure of mental effort required during virtual interaction tasks, typically assessed using standardized scales like NASA-TLX."@en ;
rdfs:label "Cognitive Load Metric"@en ;
rdfs:subClassOf ngm:sc-interaction ;
skos:broader ngm:sc-interaction ;
vc:bridgesTo ngm:telecollaboration ;
vc:dependsOn ngm:task-complexity-analysis ;
vc:dependsOn ngm:user-feedback ;
vc:enables ngm:interface-design-validation ;
vc:enables ngm:performance-optimization ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:usability-testing ;
vc:isPartOf ngm:user-experience ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:measurement-framework ;
vc:requires ngm:psychometric-scale ;
vc:slug "cognitive-load-metric" ;
vc:sourceDomain "spatial-computing" .
ngm:cognitive-load-theory a skos:Concept ;
rdfs:label "Cognitive Load Theory"@en .
ngm:cognitive-model a skos:Concept ;
rdfs:label "Cognitive Model"@en .
ngm:cognitive-modelling a owl:Class ;
rdfs:comment "Cognitive modelling is the construction of computational models that simulate human cognitive processes such as perception, memory, reasoning and decision-making, in order to test theories of mind or to inform artificial agents. Models range from symbolic production-rule systems to connectionist and hybrid architectures that reproduce empirical response-time and error patterns from human studies. Cognitive architectures and cognitive AI systems draw on cognitive modelling to structure how an artificial agent represents and reasons over knowledge."@en ;
rdfs:label "Cognitive Modelling"@en ;
rdfs:subClassOf ngm:cognitive-science ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:cognitive-science ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "cognitive-modelling" ;
vc:sourceDomain "artificial-intelligence" .
ngm:cognitive-neuroscience a skos:Concept ;
rdfs:label "Cognitive Neuroscience"@en .
ngm:cognitive-psychology a owl:Class ;
rdfs:comment "Cognitive psychology is the scientific discipline that investigates the internal mental processes underlying intelligent behaviour, including perception, attention, memory, language, problem-solving, reasoning, and decision-making, treating the mind as an information-processing system and using controlled experiments, computational models, and neuroimaging to reveal its representations and operations."@en ;
rdfs:label "Cognitive Psychology"@en ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf ngm:behavioural-science ;
rdfs:subClassOf ngm:cognitive-science ;
rdfs:subClassOf ngm:psychology ;
rdfs:subClassOf _:r4563 ;
rdfs:subClassOf _:r4564 ;
rdfs:subClassOf _:r4565 ;
rdfs:subClassOf _:r4566 ;
rdfs:subClassOf _:r4567 ;
rdfs:subClassOf _:r4568 ;
rdfs:subClassOf _:r4569 ;
skos:broader ngm:ai-research-area ;
vc:contrastsWith ngm:behaviourism ;
vc:contrastsWith ngm:connectionism ;
vc:contrastsWith ngm:psychoanalysis ;
vc:contrastsWith ngm:situated-cognition ;
vc:dependsOn ngm:computer-science ;
vc:dependsOn ngm:linguistics ;
vc:dependsOn ngm:neuroscience ;
vc:dependsOn ngm:philosophy-of-mind ;
vc:enables ngm:behavioural-economics ;
vc:enables ngm:clinical-assessment ;
vc:enables ngm:cognitive-rehabilitation ;
vc:enables ngm:explainable-ai ;
vc:enables ngm:human-computer-interaction ;
vc:enables ngm:intelligent-tutoring-system ;
vc:enables ngm:user-experience-design ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:attention-mechanism ;
vc:hasPart ngm:episodic-memory ;
vc:hasPart ngm:executive-function ;
vc:hasPart ngm:language-processing ;
vc:hasPart ngm:long-term-memory ;
vc:hasPart ngm:perception ;
vc:hasPart ngm:procedural-memory ;
vc:hasPart ngm:semantic-memory ;
vc:hasPart ngm:working-memory ;
vc:implements ngm:computational-modelling ;
vc:implements ngm:experimental-methods ;
vc:implements ngm:information-processing ;
vc:qualityScore "0.88"^^xsd:float ;
vc:relatedTo ngm:behavioural-economics ;
vc:relatedTo ngm:cognitive-ai ;
vc:relatedTo ngm:cognitive-architecture ;
vc:relatedTo ngm:computational-linguistics ;
vc:relatedTo ngm:decision-making ;
vc:relatedTo ngm:embodied-cognition ;
vc:relatedTo ngm:information-theory ;
vc:relatedTo ngm:knowledge-graphs ;
vc:relatedTo ngm:knowledge-representation ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:philosophy-of-mind ;
vc:requires ngm:computational-modelling ;
vc:requires ngm:experimental-methods ;
vc:requires ngm:neuroscience ;
vc:requires ngm:statistics ;
vc:slug "cognitive-psychology" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:american-psychological-association ;
vc:standardizedBy ngm:british-psychological-society ;
vc:supports ngm:affective-computing ;
vc:supports ngm:artificial-intelligence ;
vc:supports ngm:cognitive-architecture ;
vc:supports ngm:machine-learning-discipline ;
vc:supports ngm:natural-language-processing ;
vc:supports ngm:reinforcement-learning ;
vc:uses ngm:dual-task-paradigm ;
vc:uses ngm:eye-tracking ;
vc:uses ngm:neuroimaging ;
vc:uses ngm:psychophysics ;
vc:uses ngm:reaction-time ;
vc:uses ngm:reaction-time-methods ;
vc:uses ngm:signal-detection-theory .
ngm:cognitive-radio a skos:Concept ;
rdfs:label "Cognitive Radio"@en .
ngm:cognitive-rehabilitation a skos:Concept ;
rdfs:label "Cognitive Rehabilitation"@en .
ngm:cognitive-robotics a skos:Concept ;
rdfs:label "Cognitive Robotics"@en .
ngm:cognitive-science a owl:Class ;
rdfs:comment "Cognitive Science is an inherently interdisciplinary field that investigates the nature of mind, intelligence, and cognition by integrating methods and theories from psychology, neuroscience, linguistics, philosophy, computer science, and anthropology. It studies how information is represented, processed, and transformed in biological and artificial systems, encompassing perception, attention, memory, language, reasoning, problem-solving, and decision-making. Computational models derived from cognitive science provide foundational frameworks for artificial intelligence, informing architectures ranging from symbolic reasoning systems to neural network design. Its empirical findings on human cognition directly shape human-computer interaction, educational technology, and the development of intelligent user interfaces."@en ;
rdfs:label "Cognitive Science"@en ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf ngm:interdisciplinary-science ;
rdfs:subClassOf _:r4570 ;
rdfs:subClassOf _:r4571 ;
rdfs:subClassOf _:r4572 ;
rdfs:subClassOf _:r4573 ;
rdfs:subClassOf _:r4574 ;
rdfs:subClassOf _:r4575 ;
rdfs:subClassOf _:r4576 ;
rdfs:subClassOf _:r4577 ;
rdfs:subClassOf _:r4578 ;
rdfs:subClassOf _:r4579 ;
skos:broader ngm:ai-research-area ;
skos:broader ngm:artificial-intelligence ;
vc:bridgesTo ngm:affective-computing ;
vc:bridgesTo ngm:augmented-reality ;
vc:bridgesTo ngm:cognitive-load ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:information-processing ;
vc:bridgesTo ngm:knowledge-graphs ;
vc:bridgesTo ngm:large-language-models ;
vc:bridgesTo ngm:neuromorphic-computing ;
vc:bridgesTo ngm:retrieval-augmented-generation ;
vc:bridgesTo ngm:robotics ;
vc:bridgesTo ngm:statistical-learning-theory ;
vc:contrastsWith ngm:behaviourism ;
vc:contrastsWith ngm:connectionism ;
vc:dependsOn ngm:linguistics ;
vc:dependsOn ngm:neuroscience ;
vc:dependsOn ngm:philosophy-of-mind ;
vc:dependsOn ngm:psychology ;
vc:enables ngm:affective-computing ;
vc:enables ngm:cognitive-ai ;
vc:enables ngm:human-computer-interaction ;
vc:enables ngm:intelligent-tutoring-system ;
vc:enables ngm:natural-language-processing ;
vc:enables ngm:neuro-symbolic-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:cognitive-architecture ;
vc:hasPart ngm:cognitive-neuroscience ;
vc:hasPart ngm:cognitive-psychology ;
vc:hasPart ngm:computational-linguistics ;
vc:hasPart ngm:decision-making ;
vc:hasPart ngm:developmental-cognition ;
vc:hasPart ngm:language-processing ;
vc:hasPart ngm:pattern-recognition ;
vc:hasPart ngm:social-cognition ;
vc:hasPart ngm:working-memory ;
vc:implements ngm:attention-mechanism ;
vc:implements ngm:transfer-learning ;
vc:implements ngm:transformer-architecture ;
vc:qualityScore "0.91"^^xsd:float ;
vc:relatedTo ngm:behavioural-economics ;
vc:relatedTo ngm:cognitive-bias ;
vc:relatedTo ngm:consciousness ;
vc:relatedTo ngm:embodied-cognition ;
vc:relatedTo ngm:philosophy-of-mind ;
vc:relatedTo ngm:situated-cognition ;
vc:requires ngm:computational-modelling ;
vc:requires ngm:information-theory ;
vc:requires ngm:neuroscience ;
vc:requires ngm:psychology ;
vc:slug "cognitive-science" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:deep-learning ;
vc:supports ngm:explainable-ai ;
vc:supports ngm:machine-learning-discipline ;
vc:supports ngm:reinforcement-learning ;
vc:supports ngm:representation-learning ;
vc:supports ngm:user-experience-design ;
vc:uses ngm:brain-computer-interface ;
vc:uses ngm:computational-modelling ;
vc:uses ngm:experimental-methods ;
vc:uses ngm:knowledge-representation ;
vc:uses ngm:neuroimaging ;
vc:uses ngm:probabilistic-reasoning ;
vc:uses ngm:signal-detection-theory .
ngm:cognitive-science-society a skos:Concept ;
rdfs:label "Cognitive Science Society"@en .
ngm:cognitive-state-monitor a skos:Concept ;
rdfs:label "Cognitive State Monitor"@en .
ngm:cognitive-trait-indicators a skos:Concept ;
rdfs:label "Cognitive Trait Indicators"@en .
ngm:cognitive-walkthrough a owl:Class ;
rdfs:comment "A cognitive walkthrough is a usability inspection method in which evaluators step through a task sequence as a first-time user would, at each step asking whether the user would know what to do, would notice the correct action is available, and would correctly interpret the feedback received. Unlike heuristic evaluation, which checks a design against general usability principles, a cognitive walkthrough focuses specifically on learnability for new users performing a defined task. It is typically conducted early in design, using prototypes rather than finished products."@en ;
rdfs:label "Cognitive Walkthrough"@en ;
rdfs:subClassOf ngm:usability ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:isPartOf ngm:usability ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "cognitive-walkthrough" ;
vc:sourceDomain "spatial-computing" .
ngm:cognitively-diverse-users a skos:Concept ;
rdfs:label "Cognitively Diverse Users"@en .
ngm:cohere a owl:Class ;
rdfs:comment "Cohere is a Canadian-American enterprise AI company founded in 2019 by Aidan Gomez, Nick Frosst, and Ivan Zhang — all former Google Brain researchers — that develops and deploys large language models, text embedding models, and reranking models through a cloud API, private cloud, and on-premises deployment model, with a strategic focus on enterprise data security, sovereign AI, and retrieval-augmented generation pipelines. Its model families include the Command series for generative tasks, the Embed series for dense vector representations, the Rerank series for cross-encoder document scoring, and the Aya multilingual research models covering 101 languages. Cohere is distinguished by its early and consistent commitment to private and on-premises deployment options that ensure enterprise data never transits external infrastructure, and by its April 2026 merger with Germany's Aleph Alpha to form a transatlantic sovereign AI entity valued at approximately $20 billion."@en ;
rdfs:label "Cohere"@en ;
rdfs:subClassOf ngm:enterprise-ai ;
rdfs:subClassOf ngm:large-language-models ;
rdfs:subClassOf ngm:natural-language-processing ;
rdfs:subClassOf _:r4580 ;
rdfs:subClassOf _:r4581 ;
rdfs:subClassOf _:r4582 ;
rdfs:subClassOf _:r4583 ;
rdfs:subClassOf _:r4584 ;
rdfs:subClassOf _:r4585 ;
rdfs:subClassOf _:r4586 ;
rdfs:subClassOf _:r4587 ;
rdfs:subClassOf _:r4588 ;
rdfs:subClassOf _:r4589 ;
rdfs:subClassOf _:r4590 ;
rdfs:subClassOf _:r4591 ;
rdfs:subClassOf _:r4592 ;
rdfs:subClassOf _:r4593 ;
rdfs:subClassOf _:r4594 ;
vc:contrastsWith ngm:aleph-alpha ;
vc:contrastsWith ngm:anthropic ;
vc:contrastsWith ngm:google-ai ;
vc:contrastsWith ngm:openai-research ;
vc:dependsOn ngm:api ;
vc:dependsOn ngm:embeddings ;
vc:dependsOn ngm:gpu-compute ;
vc:dependsOn ngm:large-language-models ;
vc:dependsOn ngm:self-supervised-learning ;
vc:dependsOn ngm:vector-database ;
vc:enables ngm:agentic-ai ;
vc:enables ngm:document-understanding ;
vc:enables ngm:information-retrieval ;
vc:enables ngm:knowledge-graph ;
vc:enables ngm:multilingual-nlp ;
vc:enables ngm:question-answering ;
vc:enables ngm:retrieval-augmented-generation ;
vc:enables ngm:semantic-search ;
vc:enables ngm:text-classification ;
vc:enables ngm:text-generation ;
vc:enables ngm:text-summarisation ;
vc:enables ngm:tool-use ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:agentic-ai ;
vc:hasPart ngm:aya-expanse ;
vc:hasPart ngm:command-r ;
vc:hasPart ngm:embed-v4 ;
vc:hasPart ngm:embeddings ;
vc:hasPart ngm:language-model ;
vc:hasPart ngm:model-vault ;
vc:hasPart ngm:multilingual-nlp ;
vc:hasPart ngm:north-platform ;
vc:hasPart ngm:rerank-4 ;
vc:hasPart ngm:reranking ;
vc:hasPart ngm:retrieval-augmented-generation ;
vc:hasPart ngm:semantic-search ;
vc:hasPart ngm:text-generation ;
vc:implements ngm:information-retrieval ;
vc:implements ngm:mixture-of-experts ;
vc:implements ngm:model-compression ;
vc:implements ngm:multimodal-ai-architecture-ai ;
vc:implements ngm:transformer-architecture ;
vc:implements ngm:vector-search ;
vc:qualityScore "0.91"^^xsd:float ;
vc:relatedTo ngm:aleph-alpha ;
vc:relatedTo ngm:data-privacy ;
vc:relatedTo ngm:instruction-tuning ;
vc:relatedTo ngm:model-compression ;
vc:relatedTo ngm:regulatory-compliance ;
vc:relatedTo ngm:rlhf ;
vc:relatedTo ngm:self-supervised-learning ;
vc:relatedTo ngm:sovereign-ai ;
vc:requires ngm:embeddings ;
vc:requires ngm:fine-tuning ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:instruction-tuning ;
vc:requires ngm:rlhf ;
vc:requires ngm:self-supervised-learning ;
vc:requires ngm:transformer ;
vc:requires ngm:transformer-architecture ;
vc:slug "cohere" ;
vc:sourceDomain "ai" ;
vc:supports ngm:data-privacy ;
vc:supports ngm:fine-tuning ;
vc:supports ngm:on-premises-deployment ;
vc:supports ngm:regulatory-compliance ;
vc:supports ngm:reranking ;
vc:supports ngm:sovereign-ai ;
vc:supports ngm:text-summarisation ;
vc:uses ngm:amazon-web-services ;
vc:uses ngm:api ;
vc:uses ngm:azure ;
vc:uses ngm:cloud-ai-platform ;
vc:uses ngm:knowledge-graph ;
vc:uses ngm:language-model ;
vc:uses ngm:oracle-cloud ;
vc:uses ngm:reranking ;
vc:uses ngm:vector-database .
ngm:coherent-light-source a skos:Concept ;
rdfs:label "Coherent Light Source"@en .
ngm:coin a owl:Class ;
rdfs:comment "A Coin is a native cryptographic asset issued and governed by a blockchain protocol itself, distinct from tokens created by smart contracts on top of an existing chain. Coins function as the primary medium of exchange for transaction fees, validator rewards, and network participation incentives within their respective distributed ledger ecosystems, and may also serve as stores of value, monetary reserves, or collateral in decentralised finance applications."@en ;
rdfs:label "Coin"@en ;
rdfs:subClassOf ngm:bc-token-and-asset ;
rdfs:subClassOf ngm:blockchain-entity ;
rdfs:subClassOf ngm:economic-mechanism ;
rdfs:subClassOf _:r4595 ;
rdfs:subClassOf _:r4596 ;
rdfs:subClassOf _:r4597 ;
rdfs:subClassOf _:r4598 ;
skos:broader ngm:bc-token-and-asset ;
vc:contrastsWith ngm:cryptocurrency-token ;
vc:enables ngm:digital-asset-market ;
vc:enables ngm:mining-reward ;
vc:enables ngm:stablecoin-token ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:monetary-system ;
vc:hasPart ngm:payment-system ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:central-bank-digital-currency-cbdc ;
vc:relatedTo ngm:cryptocurrency ;
vc:relatedTo ngm:digital-currency ;
vc:relatedTo ngm:economic-layer ;
vc:relatedTo ngm:monetary-sovereignty ;
vc:requires ngm:blockchain ;
vc:requires ngm:consensus-mechanism ;
vc:slug "coin" ;
vc:sourceDomain "blockchain" .
ngm:coin-flipping-protocol a skos:Concept ;
rdfs:label "Coin Flipping Protocol"@en .
ngm:coin-selection a skos:Concept ;
rdfs:label "Coin Selection"@en .
ngm:coinbase a owl:Class ;
rdfs:comment "Coinbase is a publicly traded United States cryptocurrency exchange, custody, and financial services company founded in 2012 by Brian Armstrong and Fred Ehrsam. It provides retail and institutional trading, custodial and self-custody wallet services, staking, lending, and payment infrastructure, operating as one of the most regulated crypto platforms in the United States. The company completed a direct listing on Nasdaq in April 2021, becoming the first major cryptocurrency exchange to go public in the US. Beyond exchange operations, Coinbase develops the Base layer-2 network (built on the OP Stack), offers a developer platform for on-chain applications, and provides institutional prime brokerage services."@en ;
rdfs:label "Coinbase"@en ;
rdfs:subClassOf ngm:digital-asset ;
rdfs:subClassOf _:r4603 ;
rdfs:subClassOf _:r4604 ;
rdfs:subClassOf _:r4605 ;
rdfs:subClassOf _:r4606 ;
rdfs:subClassOf _:r4607 ;
vc:bridgesTo ngm:securities-regulation ;
vc:bridgesTo ngm:traditional-finance ;
vc:contrastsWith ngm:binance ;
vc:contrastsWith ngm:decentralised-exchange ;
vc:contrastsWith ngm:kraken ;
vc:dependsOn ngm:blockchain ;
vc:dependsOn ngm:cryptographic-infrastructure ;
vc:enables ngm:crypto-trading ;
vc:enables ngm:de-fi ;
vc:enables ngm:digital-asset-custody ;
vc:enables ngm:staking ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:base ;
vc:hasPart ngm:coinbase-custody ;
vc:hasPart ngm:coinbase-prime ;
vc:hasPart ngm:coinbase-wallet ;
vc:implements ngm:kyc ;
vc:implements ngm:proof-of-stake ;
vc:qualityScore "0.73"^^xsd:float ;
vc:relatedTo ngm:centralised-exchange ;
vc:relatedTo ngm:layer-2-scaling ;
vc:relatedTo ngm:optimism ;
vc:requires ngm:blockchain-wallet ;
vc:requires ngm:cryptographic-key-management ;
vc:requires ngm:regulatory-compliance ;
vc:slug "coinbase" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:ethereum ;
vc:uses ngm:op-stack ;
vc:uses ngm:smart-contract .
ngm:coinbase-custody a skos:Concept ;
rdfs:label "Coinbase Custody"@en .
ngm:coinbase-prime a skos:Concept ;
rdfs:label "Coinbase Prime"@en .
ngm:coinbase-reward-distribution a skos:Concept ;
rdfs:label "Coinbase Reward Distribution"@en .
ngm:coinbase-transaction a owl:Class ;
rdfs:comment "The first transaction in every blockchain block, created by the miner or block producer, that contains no inputs and issues the block reward plus accumulated transaction fees to the miner's address. Unlike regular transactions, the coinbase transaction has no sender; it creates new coins from protocol-defined issuance rules and serves as the primary mechanism by which new cryptocurrency enters circulation."@en ;
rdfs:label "Coinbase Transaction"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf ngm:blockchain-entity ;
rdfs:subClassOf ngm:consensus-protocol ;
rdfs:subClassOf _:r4599 ;
rdfs:subClassOf _:r4600 ;
rdfs:subClassOf _:r4601 ;
rdfs:subClassOf _:r4602 ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:enables ngm:cryptocurrency ;
vc:enables ngm:mining-reward ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:block-reward ;
vc:hasPart ngm:transaction-fee ;
vc:isPartOf ngm:blockchain-network ;
vc:isPartOf ngm:blockchain-transaction ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:blockchain-protocol ;
vc:relatedTo ngm:proof-of-work ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:mining ;
vc:slug "coinbase-transaction" ;
vc:sourceDomain "blockchain" .
ngm:coinbase-wallet a skos:Concept ;
rdfs:label "Coinbase Wallet"@en .
ngm:coincidence-of-wants a skos:Concept ;
rdfs:label "Coincidence Of Wants"@en .
ngm:coinjoin a skos:Concept ;
rdfs:label "Coinjoin"@en .
ngm:coinshift a skos:Concept ;
rdfs:label "Coinshift"@en .
ngm:colbert a owl:Class ;
rdfs:comment "A late-interaction neural retrieval model that encodes queries and documents into per-token embedding matrices with BERT and scores relevance by summing each query token's maximum similarity over document tokens, retaining much of the accuracy of full cross-encoder attention whilst permitting document embeddings to be precomputed and indexed for scalable, fast retrieval."@en ;
rdfs:label "ColBERT"@en ;
rdfs:subClassOf ngm:dense-retrieval ;
vc:contrastsWith ngm:cross-encoder-reranking ;
vc:contrastsWith ngm:dense-passage-retrieval ;
vc:enables ngm:semantic-search ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:beir-benchmark ;
vc:relatedTo ngm:hybrid-search ;
vc:slug "colbert" ;
vc:sourceDomain "machine-learning" ;
vc:uses ngm:bert .
ngm:colbert-late-interaction a skos:Concept ;
rdfs:label "Colbert Late Interaction"@en .
ngm:colbertv2 a skos:Concept ;
rdfs:label "Colbertv2"@en .
ngm:colcon-build-system a skos:Concept ;
rdfs:label "Colcon Build System"@en .
ngm:cold-ai-interaction a skos:Concept ;
rdfs:label "Cold AI Interaction"@en .
ngm:cold-chain-monitoring a owl:Class ;
rdfs:comment "Cold chain monitoring is an integrated infrastructure discipline encompassing sensor networks, communication protocols, data management platforms, and provenance-recording systems that collectively maintain, verify, and audit temperature-controlled conditions for perishable goods across the entir..."@en ;
rdfs:label "Cold Chain Monitoring"@en ;
rdfs:subClassOf ngm:compliance-infrastructure ;
rdfs:subClassOf ngm:infra-legal-and-regulatory ;
rdfs:subClassOf ngm:logistics-management ;
rdfs:subClassOf ngm:monitoring-systems ;
rdfs:subClassOf ngm:sensor-networks ;
rdfs:subClassOf ngm:supply-chain ;
rdfs:subClassOf ngm:traceability ;
rdfs:subClassOf _:r4608 ;
rdfs:subClassOf _:r4609 ;
rdfs:subClassOf _:r4610 ;
rdfs:subClassOf _:r4611 ;
rdfs:subClassOf _:r4612 ;
rdfs:subClassOf _:r4613 ;
rdfs:subClassOf _:r4614 ;
rdfs:subClassOf _:r4615 ;
rdfs:subClassOf _:r4616 ;
rdfs:subClassOf _:r4617 ;
rdfs:subClassOf _:r4618 ;
rdfs:subClassOf _:r4619 ;
rdfs:subClassOf _:r4620 ;
rdfs:subClassOf _:r4621 ;
rdfs:subClassOf _:r4622 ;
skos:broader ngm:infra-legal-and-regulatory ;
vc:bridgesTo ngm:logistics-management ;
vc:contrastsWith ngm:centralised-data-silos ;
vc:contrastsWith ngm:manual-temperature-logging ;
vc:contrastsWith ngm:paper-based-documentation ;
vc:contrastsWith ngm:periodic-checkpoint-monitoring ;
vc:contrastsWith ngm:point-in-time-monitoring ;
vc:dependsOn ngm:cloud-infrastructure ;
vc:dependsOn ngm:cryptography ;
vc:dependsOn ngm:data-analytics ;
vc:dependsOn ngm:edge-computing ;
vc:dependsOn ngm:logistics ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:refrigeration-technology ;
vc:enables ngm:automated-lot-release ;
vc:enables ngm:compliance-evidence ;
vc:enables ngm:excursion-detection ;
vc:enables ngm:food-safety ;
vc:enables ngm:pharmaceutical-supply-chain ;
vc:enables ngm:predictive-maintenance ;
vc:enables ngm:regulatory-reporting ;
vc:enables ngm:sustainability-reporting ;
vc:enables ngm:traceability ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:alert-system ;
vc:hasPart ngm:asset-registry ;
vc:hasPart ngm:blockchain-records ;
vc:hasPart ngm:certificate-of-compliance ;
vc:hasPart ngm:compliance-dashboard ;
vc:hasPart ngm:data-analytics-platform ;
vc:hasPart ngm:digital-twin ;
vc:hasPart ngm:edge-gateway ;
vc:hasPart ngm:io-t-sensors ;
vc:hasPart ngm:rfid ;
vc:hasPart ngm:smart-contracts ;
vc:hasPart ngm:temperature-logger ;
vc:implements ngm:dscsa-compliance ;
vc:implements ngm:fsma-204 ;
vc:implements ngm:gdp-chapter-9 ;
vc:implements ngm:good-distribution-practice ;
vc:implements ngm:gs1-epcis ;
vc:implements ngm:iata-temperature-control-regulations ;
vc:implements ngm:iso-22000 ;
vc:implements ngm:who-evm ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:asset-registry ;
vc:relatedTo ngm:blockchain ;
vc:relatedTo ngm:digital-twin ;
vc:relatedTo ngm:food-safety ;
vc:relatedTo ngm:internet-of-things ;
vc:relatedTo ngm:logistics ;
vc:relatedTo ngm:pharmaceutical-supply-chain ;
vc:relatedTo ngm:rfid ;
vc:relatedTo ngm:sensor-networks ;
vc:relatedTo ngm:smart-contracts ;
vc:relatedTo ngm:supply-chain ;
vc:relatedTo ngm:traceability ;
vc:requires ngm:blockchain ;
vc:requires ngm:calibration-standards ;
vc:requires ngm:cloud-computing ;
vc:requires ngm:gs-1-standards ;
vc:requires ngm:internet-of-things ;
vc:requires ngm:network-connectivity ;
vc:requires ngm:refrigeration-technology ;
vc:requires ngm:sensor-networks ;
vc:slug "cold-chain-monitoring" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:codex-alimentarius ;
vc:standardizedBy ngm:dscsa-compliance ;
vc:standardizedBy ngm:eu-gdp-guidelines ;
vc:standardizedBy ngm:gs1 ;
vc:standardizedBy ngm:iata-temperature-control-regulations ;
vc:standardizedBy ngm:iso-22000 ;
vc:standardizedBy ngm:mhra-gdp-chapter-9 ;
vc:standardizedBy ngm:uk-food-standards-agency ;
vc:standardizedBy ngm:who-evm ;
vc:supports ngm:biologics-logistics ;
vc:supports ngm:chemical-logistics ;
vc:supports ngm:food-safety ;
vc:supports ngm:insurance-claims-processing ;
vc:supports ngm:pharmaceutical-supply-chain ;
vc:supports ngm:sustainability-reporting ;
vc:supports ngm:vaccine-distribution ;
vc:uses ngm:blockchain ;
vc:uses ngm:digital-twin ;
vc:uses ngm:gs1-epcis ;
vc:uses ngm:lo-ra-wan ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:nb-io-t ;
vc:uses ngm:rfid ;
vc:uses ngm:satellite-connectivity ;
vc:uses ngm:smart-contracts ;
vc:uses ngm:zero-knowledge-proof .
ngm:cold-gas-propulsion a owl:Class ;
rdfs:label "Cold Gas Propulsion"@en ;
rdfs:subClassOf ngm:spacecraft-propulsion ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:spacecraft-propulsion ;
vc:slug "cold-gas-propulsion" ;
vc:sourceDomain "space-science-and-systems" .
ngm:cold-start-problem a skos:Concept ;
rdfs:label "Cold Start Problem"@en .
ngm:cold-storage a owl:Class ;
rdfs:comment "Cold Storage in the context of digital assets and cryptocurrency refers to the practice of holding private keys in an offline environment — physically disconnected from any network — to eliminate the attack surface presented by internet-connected systems. Hardware wallets, air-gapped computers, and paper wallets are common cold storage implementations. By contrast with hot wallets (internet-connected), cold storage sacrifices transaction convenience for maximum security, and is the industry standard for custodying large quantities of cryptocurrency at exchanges, institutional custodians, and high-net-worth individual holders."@en ;
rdfs:label "Cold Storage"@en ;
rdfs:subClassOf ngm:custody-infrastructure ;
rdfs:subClassOf _:r4623 ;
rdfs:subClassOf _:r4624 ;
vc:bridgesTo ngm:infrastructure ;
vc:bridgesTo ngm:security ;
vc:contrastsWith ngm:hot-wallet ;
vc:contrastsWith ngm:warm-storage ;
vc:enables ngm:digital-asset-custody ;
vc:enables ngm:institutional-custody ;
vc:enables ngm:key-ceremony ;
vc:enables ngm:self-custody ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol-network ;
vc:relatedTo ngm:decentralized-finance-de-fi ;
vc:relatedTo ngm:digital-asset-exchange ;
vc:requires ngm:physical-security ;
vc:requires ngm:private-key ;
vc:slug "cold-storage" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:multisignature-wallets ;
vc:supports ngm:partially-signed-bitcoin-transaction ;
vc:supports ngm:threshold-signature-scheme ;
vc:uses ngm:air-gapped-computer ;
vc:uses ngm:cryptographic-key-management ;
vc:uses ngm:hardware-security-module ;
vc:uses ngm:hardware-wallet ;
vc:uses ngm:multisignature .
ngm:collaboration a owl:Class ;
rdfs:comment "Collaboration is the coordinated joint activity of two or more agents — human or artificial — working toward shared goals through negotiated division of labour, mutual adjustment, and shared artefact production. In digital and distributed settings it encompasses synchronous and asynchronous communication, collective sense-making, and structured workflows mediated by software systems that maintain shared state and contextual awareness across geographic and organisational boundaries. Effective collaboration depends on social and technical mechanisms for conflict resolution, attribution, version management, and trust; its theoretical foundations draw from Computer-Supported Cooperative Work (CSCW), distributed cognition, and organisational theory. Contemporary collaboration increasingly involves AI agents, immersive shared environments, and decentralised coordination protocols."@en ;
rdfs:label "Collaboration"@en ;
rdfs:subClassOf ngm:dc-workspace-tools ;
rdfs:subClassOf ngm:distributed-collaboration ;
rdfs:subClassOf _:r4641 ;
rdfs:subClassOf _:r4642 ;
rdfs:subClassOf _:r4643 ;
rdfs:subClassOf _:r4644 ;
rdfs:subClassOf _:r4645 ;
rdfs:subClassOf _:r4646 ;
skos:broader ngm:dc-workspace-tools ;
skos:broader ngm:distributed-collaboration ;
vc:bridgesTo ngm:decentralised-autonomous-organisation ;
vc:bridgesTo ngm:multi-agent-system ;
vc:bridgesTo ngm:social-vr ;
vc:contrastsWith ngm:cooperation ;
vc:contrastsWith ngm:coordination ;
vc:enables ngm:co-creation ;
vc:enables ngm:collective-intelligence ;
vc:enables ngm:knowledge-sharing ;
vc:enables ngm:telecollaboration ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:asynchronous-coordination ;
vc:hasPart ngm:shared-workspace ;
vc:hasPart ngm:synchronous-communication ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:computer-supported-cooperative-work ;
vc:relatedTo ngm:social-network ;
vc:relatedTo ngm:workflow-management ;
vc:requires ngm:access-control ;
vc:requires ngm:trust ;
vc:requires ngm:version-control ;
vc:slug "collaboration" ;
vc:sourceDomain "distributed-collaboration" ;
vc:standardizedBy ngm:ieee ;
vc:standardizedBy ngm:w3-c ;
vc:supports ngm:organisational-learning ;
vc:supports ngm:team-formation ;
vc:uses ngm:collaboration-platform ;
vc:uses ngm:conflict-free-replicated-data-type ;
vc:uses ngm:groupware ;
vc:uses ngm:operational-transformation .
ngm:collaboration-platform a owl:Class ;
rdfs:comment "A Collaboration Platform is an integrated software environment that unifies communication channels, shared workspaces, workflow automation, and content management tooling to enable coordinated work among distributed teams. Such platforms expose API-first architectures built atop real-time messaging protocols, WebRTC-based media pipelines, and cloud storage with conflict resolution, providing a composable substrate for synchronous and asynchronous teamwork. Enterprise-grade deployments layer in identity federation, data residency controls, compliance archiving, and extensible integration ecosystems, while modern platforms increasingly embed AI-driven capabilities such as meeting transcription, action-item extraction, and intelligent search. The category spans lightweight messaging tools through full unified-communications suites and extends into spatial and immersive collaboration modalities."@en ;
rdfs:label "Collaboration Platform"@en ;
rdfs:subClassOf ngm:distributed-systems ;
rdfs:subClassOf _:r4625 ;
rdfs:subClassOf _:r4626 ;
rdfs:subClassOf _:r4627 ;
rdfs:subClassOf _:r4628 ;
rdfs:subClassOf _:r4629 ;
rdfs:subClassOf _:r4630 ;
rdfs:subClassOf _:r4631 ;
rdfs:subClassOf _:r4632 ;
vc:bridgesTo ngm:ai-assistant ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:metaverse-and-telecollaboration ;
vc:contrastsWith ngm:email-system ;
vc:contrastsWith ngm:point-to-point-communication ;
vc:enables ngm:augmented-reality-collaboration ;
vc:enables ngm:digital-twin-collaboration ;
vc:enables ngm:remote-work ;
vc:enables ngm:tc-0080-team-coordination ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:real-time-messaging ;
vc:hasPart ngm:tc-0002-collaborative-document-editing ;
vc:hasPart ngm:video-conferencing ;
vc:hasPart ngm:workflow-automation ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:enterprise-resource-planning ;
vc:relatedTo ngm:social-network ;
vc:relatedTo ngm:xr-meeting-space ;
vc:requires ngm:cloud-storage ;
vc:requires ngm:identity-and-access-management ;
vc:requires ngm:web-rtc ;
vc:slug "collaboration-platform" ;
vc:sourceDomain "distributed-collaboration" ;
vc:supports ngm:compliance-and-governance ;
vc:supports ngm:enterprise-security ;
vc:supports ngm:knowledge-management ;
vc:uses ngm:api-gateway ;
vc:uses ngm:edge-computing ;
vc:uses ngm:end-to-end-encryption ;
vc:uses ngm:microservices-architecture .
ngm:collaboration-technology a owl:Class ;
rdfs:comment "Software and hardware systems that enable multiple participants to coordinate, communicate, and jointly produce work across physical or virtual spaces. In spatial computing contexts, collaboration technology encompasses shared XR environments, co-presence avatars, spatial audio, and synchronised digital workspace tools that support telecollaboration at a distance."@en ;
rdfs:label "Collaboration Technology"@en ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf _:r4633 ;
rdfs:subClassOf _:r4634 ;
skos:broader ngm:sc-platform-and-environment ;
vc:bridgesTo ngm:telecollaboration ;
vc:enables ngm:collaboration ;
vc:enables ngm:telecollaboration ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:collaboration-platform ;
vc:relatedTo ngm:telecollaboration-and-telepresence ;
vc:requires ngm:network-infrastructure ;
vc:requires ngm:quality-of-service ;
vc:slug "collaboration-technology" ;
vc:sourceDomain "spatial-computing" .
ngm:collaboration-tool a skos:Concept ;
rdfs:label "Collaboration Tool"@en .
ngm:collaboration-tool-categorization a skos:Concept ;
rdfs:label "Collaboration Tool Categorization"@en .
ngm:collaboration-tools a owl:Class ;
rdfs:comment "Software that supports people working together on shared tasks or documents, including communication, coordination and concurrent editing features."@en ;
rdfs:label "Collaboration Tools"@en ;
rdfs:subClassOf ngm:software-development ;
rdfs:subClassOf _:r4635 ;
rdfs:subClassOf _:r4636 ;
rdfs:subClassOf _:r4637 ;
rdfs:subClassOf _:r4638 ;
rdfs:subClassOf _:r4639 ;
rdfs:subClassOf _:r4640 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:crdt ;
vc:bridgesTo ngm:spatial-computing ;
vc:bridgesTo ngm:version-control ;
vc:contrastsWith ngm:email ;
vc:dependsOn ngm:access-control ;
vc:dependsOn ngm:cloud-infrastructure ;
vc:enables ngm:distributed-teams ;
vc:enables ngm:knowledge-sharing ;
vc:enables ngm:operational-transformation ;
vc:enables ngm:remote-work ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:tc-0002-collaborative-document-editing ;
vc:hasPart ngm:version-control ;
vc:hasPart ngm:video-conferencing ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:notification-system ;
vc:relatedTo ngm:project-management ;
vc:relatedTo ngm:workflow-automation ;
vc:requires ngm:authentication ;
vc:requires ngm:network-architecture ;
vc:requires ngm:real-time-communication ;
vc:slug "collaboration-tools" ;
vc:sourceDomain "distributed-collaboration" ;
vc:supports ngm:agile-software-development ;
vc:supports ngm:open-source-development ;
vc:uses ngm:crdt ;
vc:uses ngm:end-to-end-encryption ;
vc:uses ngm:web-socket .
ngm:collaborative-3d-editing a skos:Concept ;
rdfs:label "Collaborative 3d Editing"@en .
ngm:collaborative-analytics a skos:Concept ;
rdfs:label "Collaborative Analytics"@en .
ngm:collaborative-ar-experiences a skos:Concept ;
rdfs:label "Collaborative AR Experiences"@en .
ngm:collaborative-automation a skos:Concept ;
rdfs:label "Collaborative Automation"@en .
ngm:collaborative-decision-making a skos:Concept ;
rdfs:label "Collaborative Decision Making"@en .
ngm:collaborative-development a skos:Concept ;
rdfs:label "Collaborative Development"@en .
ngm:collaborative-editing a owl:Class ;
rdfs:comment "Collaborative editing is the capability for multiple people to view and modify a shared document simultaneously, with their changes merged consistently and surfaced to all participants in near real time. It relies on concurrency-control techniques such as operational transformation or conflict-free replicated data types to reconcile concurrent edits without conflicts. Combined with presence and cursor awareness, it makes co-authoring across distributed users feel immediate and coherent."@en ;
rdfs:label "Collaborative Editing"@en ;
rdfs:subClassOf ngm:real-time-collaboration ;
rdfs:subClassOf ngm:version-history ;
rdfs:subClassOf _:r4649 ;
rdfs:subClassOf _:r4650 ;
vc:enables ngm:collaboration ;
vc:enables ngm:real-time-collaboration ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:conflict-free-replicated-data-type ;
vc:isPartOf ngm:distributed-collaboration ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:crdt ;
vc:relatedTo ngm:operational-transformation ;
vc:relatedTo ngm:presence-awareness ;
vc:requires ngm:conflict-resolution ;
vc:requires ngm:presence-awareness ;
vc:slug "collaborative-editing" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:distributed-collaboration ;
vc:uses ngm:crdt ;
vc:uses ngm:operational-transformation ;
vc:uses ngm:web-socket .
ngm:collaborative-model-ownership a skos:Concept ;
rdfs:label "Collaborative Model Ownership"@en .
ngm:collaborative-presence a skos:Concept ;
rdfs:label "Collaborative Presence"@en .
ngm:collaborative-reasoning a skos:Concept ;
rdfs:label "Collaborative Reasoning"@en .
ngm:collaborative-research a skos:Concept ;
rdfs:label "Collaborative Research"@en .
ngm:collaborative-software-development a skos:Concept ;
rdfs:label "Collaborative Software Development"@en .
ngm:collaborative-systems-modality a owl:Class ;
rdfs:comment "Collaborative describes systems, processes, or modalities in which multiple agents—human or robotic—work together toward shared goals, actively coordinating actions, sharing information, and adapting to one another's contributions. In robotics, 'collaborative' is most precisely applied to human–robot collaboration (HRC) per ISO/TS 15066, where robot and human share a workspace without fixed barriers. In knowledge work and software, it describes tools and practices enabling co-creation, distributed editing, and collective decision-making across asynchronous or real-time channels."@en ;
rdfs:label "Collaborative Systems Modality"@en ;
rdfs:subClassOf ngm:infra-computing-and-cloud ;
rdfs:subClassOf _:r4688 ;
rdfs:subClassOf _:r4689 ;
rdfs:subClassOf _:r4690 ;
skos:broader ngm:infra-computing-and-cloud ;
vc:bridgesTo ngm:collaboration ;
vc:enables ngm:collective-intelligence-system ;
vc:enables ngm:realtime-collaboration ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:asynchronous-collaboration ;
vc:hasPart ngm:collaborative-systems-modality-learning ;
vc:hasPart ngm:collaborative-systems-modality-operation ;
vc:qualityScore "0.7"^^xsd:float ;
vc:relatedTo ngm:collaborative-systems-modality-robot ;
vc:relatedTo ngm:distributed-collaboration ;
vc:relatedTo ngm:human-robot-interaction ;
vc:relatedTo ngm:multi-agent-systems ;
vc:slug "collaborative-systems-modality" ;
vc:sourceDomain "infrastructure" .
ngm:collaborative-systems-modality-design a owl:Class ;
rdfs:comment "Collaborative Design is a design methodology in which multiple stakeholders—including designers, engineers, end users, and domain experts—jointly participate in defining, iterating, and validating artefacts or systems. It draws on participatory design traditions to ensure that lived experience and diverse expertise shape outcomes rather than being consulted retrospectively. Digital collaborative design platforms support real-time co-authoring, version management, and synchronous review across distributed teams. The approach is applied in product development, spatial design, software architecture, and policy co-creation."@en ;
rdfs:label "Collaborative Design"@en ;
rdfs:subClassOf ngm:design-thinking ;
rdfs:subClassOf _:r4647 ;
rdfs:subClassOf _:r4648 ;
vc:bridgesTo ngm:human-ai-interaction ;
vc:bridgesTo ngm:spatial-computing ;
vc:enables ngm:co-creation ;
vc:enables ngm:generative-design-tool ;
vc:enables ngm:product-design ;
vc:enables ngm:rapid-prototyping ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:human-centred-design ;
vc:implements ngm:participatory-design ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:collaborative-systems-modality-learning ;
vc:relatedTo ngm:human-computer-interaction ;
vc:relatedTo ngm:participatory-policy-making ;
vc:relatedTo ngm:usability-testing ;
vc:relatedTo ngm:user-research ;
vc:requires ngm:shared-workspace ;
vc:requires ngm:stakeholder-engagement ;
vc:slug "collaborative-design" ;
vc:sourceDomain "distributed-collaboration" ;
vc:supports ngm:agile-software-development ;
vc:supports ngm:design-sprint ;
vc:uses ngm:collaborative-systems-modality-whiteboard ;
vc:uses ngm:design-software ;
vc:uses ngm:real-time-collaboration ;
vc:uses ngm:version-control .
ngm:collaborative-systems-modality-filtering a owl:Class ;
rdfs:comment "Collaborative filtering is a machine learning technique for building recommendation systems that generates predictions about user preferences by aggregating the behaviour or ratings of many users, without requiring explicit knowledge of item content. Memory-based approaches compute similarity between users (user-based) or items (item-based) using rating vectors; model-based approaches such as matrix factorisation decompose the user-item interaction matrix into latent factor spaces. The method operates on the assumption that users who agreed in the past will agree in the future, and is the foundational algorithm behind recommendation engines at Netflix, Spotify, and Amazon."@en ;
rdfs:label "Collaborative Filtering"@en ;
rdfs:subClassOf ngm:information-retrieval ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf ngm:machine-learning-discipline-technique ;
rdfs:subClassOf _:r4651 ;
rdfs:subClassOf _:r4652 ;
rdfs:subClassOf _:r4653 ;
rdfs:subClassOf _:r4654 ;
rdfs:subClassOf _:r4655 ;
rdfs:subClassOf _:r4656 ;
rdfs:subClassOf _:r4657 ;
rdfs:subClassOf _:r4658 ;
rdfs:subClassOf _:r4659 ;
rdfs:subClassOf _:r4660 ;
rdfs:subClassOf _:r4661 ;
rdfs:subClassOf _:r4662 ;
rdfs:subClassOf _:r4663 ;
vc:contrastsWith ngm:content-based-filtering ;
vc:contrastsWith ngm:search-engine ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:graph-neural-network ;
vc:dependsOn ngm:large-language-model ;
vc:dependsOn ngm:neural-network ;
vc:dependsOn ngm:transformer-architecture ;
vc:dependsOn ngm:vector-database ;
vc:enables ngm:drug-discovery ;
vc:enables ngm:e-commerce ;
vc:enables ngm:hyper-personalisation ;
vc:enables ngm:information-retrieval ;
vc:enables ngm:natural-language-processing ;
vc:enables ngm:recommendation-engine ;
vc:enables ngm:recommendation-system ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:attention-mechanism ;
vc:hasPart ngm:embeddings ;
vc:hasPart ngm:latent-factor-model ;
vc:hasPart ngm:matrix-factorisation ;
vc:hasPart ngm:nearest-neighbor-search ;
vc:hasPart ngm:neighbourhood-method ;
vc:hasPart ngm:stochastic-gradient-descent ;
vc:hasPart ngm:user-behaviour-data ;
vc:hasPart ngm:user-item-interaction-matrix ;
vc:hasPart ngm:vae ;
vc:implements ngm:alternating-least-squares ;
vc:implements ngm:attention-mechanism ;
vc:implements ngm:gradient-descent ;
vc:implements ngm:machine-learning-model ;
vc:implements ngm:matrix-factorisation ;
vc:implements ngm:stochastic-gradient-descent ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:cold-start-problem ;
vc:relatedTo ngm:data-pipeline ;
vc:relatedTo ngm:data-privacy ;
vc:relatedTo ngm:drug-discovery ;
vc:relatedTo ngm:filter-bubble ;
vc:relatedTo ngm:gdpr ;
vc:relatedTo ngm:knowledge-graph ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:privacy-preserving-data-mining ;
vc:relatedTo ngm:recommendation-systems ;
vc:relatedTo ngm:social-media-platform-infrastructure ;
vc:requires ngm:embeddings ;
vc:requires ngm:gradient-descent ;
vc:requires ngm:loss-function ;
vc:requires ngm:machine-learning-model ;
vc:requires ngm:regularisation ;
vc:requires ngm:sparse-data ;
vc:requires ngm:user-behaviour-data ;
vc:slug "collaborative-filtering" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:recommendation-systems ;
vc:supports ngm:a-b-testing ;
vc:supports ngm:data-privacy ;
vc:supports ngm:differential-privacy ;
vc:supports ngm:federated-learning ;
vc:supports ngm:gdpr ;
vc:supports ngm:privacy-preserving-data-mining ;
vc:uses ngm:approximate-nearest-neighbour-search ;
vc:uses ngm:attention-mechanism ;
vc:uses ngm:data-pipeline ;
vc:uses ngm:embeddings ;
vc:uses ngm:gradient-descent ;
vc:uses ngm:knowledge-graph ;
vc:uses ngm:large-language-model ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:reinforcement-learning ;
vc:uses ngm:vae ;
vc:uses ngm:vector-database .
ngm:collaborative-systems-modality-learning a owl:Class ;
rdfs:comment "An educational approach where learners work together in virtual environments, metaverse platforms, or VR spaces to achieve shared learning goals through social interaction, knowledge co-construction, and collective problem-solving enabled by immersive and embodied digital experiences."@en ;
rdfs:label "Collaborative Learning"@en ;
rdfs:subClassOf ngm:educational-methodology ;
rdfs:subClassOf _:r4664 ;
rdfs:subClassOf _:r4665 ;
rdfs:subClassOf _:r4666 ;
rdfs:subClassOf _:r4667 ;
vc:bridgesTo ngm:federated-learning ;
vc:bridgesTo ngm:telecollaboration ;
vc:dependsOn ngm:avatar ;
vc:dependsOn ngm:network-infrastructure ;
vc:enables ngm:collective-intelligence ;
vc:enables ngm:knowledge-co-construction ;
vc:enables ngm:remote-collaboration ;
vc:enables ngm:social-learning ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:educational-methodology ;
vc:qualityScore "0.68"^^xsd:float ;
vc:relatedTo ngm:metaverse ;
vc:requires ngm:communication-tools ;
vc:requires ngm:shared-workspace ;
vc:requires ngm:social-presence ;
vc:requires ngm:virtual-environment ;
vc:slug "collaborative-learning" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:experiential-learning ;
vc:supports ngm:formative-assessment ;
vc:uses ngm:collaboration-platform ;
vc:uses ngm:immersive-technology ;
vc:uses ngm:spatial-audio .
ngm:collaborative-systems-modality-operation a owl:Class ;
rdfs:comment "Collaborative Operation - Coordinated execution of tasks between Human Operators and Robotic Systems within the same workspace, governed by safety protocols, task allocation mechanisms, and real-time communication to achieve shared objectives."@en ;
rdfs:label "Collaborative Operation"@en ;
rdfs:subClassOf ngm:human-robot-interaction ;
rdfs:subClassOf ngm:robotics ;
rdfs:subClassOf _:r4668 ;
rdfs:subClassOf _:r4669 ;
rdfs:subClassOf _:r4670 ;
skos:broader ngm:robotics ;
vc:enables ngm:production-flexibility ;
vc:enables ngm:workspace-efficiency ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:human-robot-interaction ;
vc:isPartOf ngm:manufacturing-process ;
vc:qualityScore "0.56"^^xsd:float ;
vc:requires ngm:force-feedback ;
vc:requires ngm:safety-monitoring ;
vc:requires ngm:task-planning ;
vc:slug "collaborative-operation" ;
vc:sourceDomain "robotics" .
ngm:collaborative-systems-modality-presence a skos:Concept ;
rdfs:label "Collaborative Systems Modality Presence"@en .
ngm:collaborative-systems-modality-robot a owl:Class ;
rdfs:comment "Collaborative Robot (cobot) - A lightweight robotic arm engineered to operate safely alongside human workers, combining force/torque sensing, reduced kinetic energy, and speed limitations to enable Human-Robot Collaboration in shared manufacturing and assembly environments. Cobots are distinguished from traditional industrial robots by their intrinsic safety mechanisms, ease of programming, and ability to share workspace with humans without physical guarding barriers."@en ;
rdfs:label "Collaborative Robot"@en ;
rdfs:subClassOf ngm:industrial-robot ;
rdfs:subClassOf ngm:robotics ;
rdfs:subClassOf _:r4671 ;
rdfs:subClassOf _:r4672 ;
rdfs:subClassOf _:r4673 ;
rdfs:subClassOf _:r4674 ;
rdfs:subClassOf _:r4675 ;
rdfs:subClassOf _:r4676 ;
rdfs:subClassOf _:r4677 ;
rdfs:subClassOf _:r4678 ;
skos:broader ngm:robotics ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:telecollaboration ;
vc:contrastsWith ngm:autonomous-mobile-robots ;
vc:enables ngm:flexible-assembly ;
vc:enables ngm:human-robot-collaboration ;
vc:enables ngm:rapid-deployment ;
vc:enables ngm:reduced-labour-costs ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:collision-detection-system ;
vc:hasPart ngm:end-effector ;
vc:hasPart ngm:force-torque-sensor ;
vc:implements ngm:iso-10218 ;
vc:implements ngm:rb-0104-hand-guiding ;
vc:isPartOf ngm:collaborative-systems-modality ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:teleoperation ;
vc:requires ngm:force-torque-sensor ;
vc:requires ngm:iso-ts-15066 ;
vc:requires ngm:rb-0094-power-and-force-limiting ;
vc:requires ngm:rb-0105-speed-and-separation-monitoring ;
vc:requires ngm:safety-controller ;
vc:slug "collaborative-robot" ;
vc:sourceDomain "robotics" ;
vc:standardizedBy ngm:ieee ;
vc:standardizedBy ngm:iso ;
vc:uses ngm:machine-vision ;
vc:uses ngm:ros ;
vc:uses ngm:sensor-fusion .
ngm:collaborative-systems-modality-robotics a owl:Class ;
rdfs:comment "Collaborative Robotics is the engineering discipline concerned with designing, deploying, and operating robotic systems — particularly collaborative robots (cobots) — that share workspace and tasks with human workers without requiring physical barriers, relying instead on force-torque sensing, speed-and-separation monitoring, and power-and-force limiting to maintain safety under ISO 10218 and ISO/TS 15066. Unlike traditional industrial robots that operate in guarded cages, cobots are designed with compliant joints, rounded profiles, and real-time collision-detection to enable direct physical cooperation with humans on assembly, inspection, and logistics tasks. The discipline integrates mechanical design, control theory, human-robot interaction research, and regulatory compliance to enable safe human-robot co-presence in shared workspaces."@en ;
rdfs:label "Collaborative Robotics"@en ;
rdfs:subClassOf ngm:collaborative-systems-modality-robot ;
rdfs:subClassOf _:r4679 ;
rdfs:subClassOf _:r4680 ;
rdfs:subClassOf _:r4681 ;
rdfs:subClassOf _:r4682 ;
rdfs:subClassOf _:r4683 ;
rdfs:subClassOf _:r4684 ;
rdfs:subClassOf _:r4685 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:digital-twin ;
vc:contrastsWith ngm:autonomous-mobile-robots ;
vc:contrastsWith ngm:industrial-robot ;
vc:enables ngm:assistive-robotics ;
vc:enables ngm:flexible-manufacturing ;
vc:enables ngm:human-robot-collaboration ;
vc:enables ngm:manufacturing-automation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:cobot-safety-levels ;
vc:hasPart ngm:end-effector ;
vc:hasPart ngm:force-torque-sensor ;
vc:hasPart ngm:impedance-control ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:human-robot-interaction ;
vc:relatedTo ngm:imitation-learning ;
vc:relatedTo ngm:robot-programming ;
vc:requires ngm:real-time-control ;
vc:requires ngm:risk-assessment ;
vc:requires ngm:robot-safety ;
vc:slug "collaborative-robotics" ;
vc:sourceDomain "robotics" ;
vc:standardizedBy ngm:iso-10218 ;
vc:standardizedBy ngm:iso-ts-15066 ;
vc:uses ngm:computer-vision ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:motion-planning ;
vc:uses ngm:tactile-sensing .
ngm:collaborative-systems-modality-robots a owl:Class ;
rdfs:comment "Collaborative robots, or cobots, are robots designed to work safely alongside humans within a shared workspace."@en ;
rdfs:label "Collaborative Robots"@en ;
rdfs:subClassOf ngm:industrial-robot ;
rdfs:subClassOf ngm:industrial-robotics ;
rdfs:subClassOf _:r4686 ;
rdfs:subClassOf _:r4687 ;
vc:bridgesTo ngm:control-theory ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:actuators ;
vc:requires ngm:sensors ;
vc:slug "collaborative-robots" ;
vc:sourceDomain "robotics" .
ngm:collaborative-systems-modality-simulation a owl:Class ;
rdfs:comment "A computational environment in which multiple participants — human or agent — share, manipulate, and observe a common simulation state in real time. It combines networked synchronisation with physics or behavioural modelling to support joint exploration, training, or design activities across distributed locations."@en ;
rdfs:label "Collaborative Simulation"@en ;
rdfs:subClassOf ngm:collaborative-systems-modality-technology ;
vc:enables ngm:collaborative-systems-modality-design ;
vc:enables ngm:digital-twin-collaboration ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:collaborative-systems-modality-learning ;
vc:relatedTo ngm:extended-reality-xr ;
vc:slug "collaborative-simulation" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:digital-twin ;
vc:uses ngm:game-engine .
ngm:collaborative-systems-modality-technology a owl:Class ;
rdfs:comment "Collaborative Technology encompasses the hardware, software, protocols, and infrastructure components that enable distributed teams to work together effectively across time and space. This includes real-time media processing, synchronisation protocols, edge computing for latency reduction, and zero-trust security models forming the technological substrate of telecollaboration."@en ;
rdfs:label "Collaborative Technology"@en ;
rdfs:subClassOf ngm:infra-computing-and-cloud ;
skos:broader ngm:infra-computing-and-cloud ;
vc:dependsOn ngm:networking-infrastructure ;
vc:enables ngm:telecollaboration ;
vc:enables ngm:video-conferencing ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.35"^^xsd:float ;
vc:slug "collaborative-technology" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:distributed-collaboration ;
vc:uses ngm:communication-protocol ;
vc:uses ngm:network-protocol .
ngm:collaborative-systems-modality-whiteboard a owl:Class ;
rdfs:comment "A Collaborative Whiteboard is a shared infinite-canvas digital workspace enabling real-time multi-user drawing, diagramming, sticky-note placement, voting, and structured ideation, delivered through web or native applications with CRDT-based (Conflict-free Replicated Data Type) or Operational..."@en ;
rdfs:label "Collaborative Whiteboard"@en ;
rdfs:subClassOf ngm:asynchronous-communication ;
rdfs:subClassOf ngm:dc-communication ;
rdfs:subClassOf ngm:dc-workspace-tools ;
rdfs:subClassOf ngm:digital-workspace ;
rdfs:subClassOf ngm:distributed-collaboration ;
rdfs:subClassOf ngm:remote-work-technology ;
rdfs:subClassOf ngm:visual-collaboration-tools ;
rdfs:subClassOf _:r4691 ;
rdfs:subClassOf _:r4692 ;
rdfs:subClassOf _:r4693 ;
rdfs:subClassOf _:r4694 ;
rdfs:subClassOf _:r4695 ;
rdfs:subClassOf _:r4696 ;
rdfs:subClassOf _:r4697 ;
rdfs:subClassOf _:r4698 ;
rdfs:subClassOf _:r4699 ;
rdfs:subClassOf _:r4700 ;
rdfs:subClassOf _:r4701 ;
rdfs:subClassOf _:r4702 ;
rdfs:subClassOf _:r4703 ;
rdfs:subClassOf _:r4704 ;
skos:broader ngm:dc-communication ;
skos:broader ngm:dc-workspace-tools ;
skos:broader ngm:distributed-collaboration ;
vc:contrastsWith ngm:physical-whiteboard ;
vc:contrastsWith ngm:presentation-software ;
vc:contrastsWith ngm:screen-sharing ;
vc:contrastsWith ngm:static-diagramming-tool ;
vc:contrastsWith ngm:videoconference-whiteboard ;
vc:dependsOn ngm:cdn ;
vc:dependsOn ngm:cloud-infrastructure ;
vc:dependsOn ngm:hybrid-logical-clock ;
vc:dependsOn ngm:identity-management ;
vc:dependsOn ngm:real-time-synchronisation ;
vc:dependsOn ngm:web-socket ;
vc:enables ngm:affinity-diagramming ;
vc:enables ngm:asynchronous-ideation ;
vc:enables ngm:collaborative-systems-modality-design ;
vc:enables ngm:design-sprint ;
vc:enables ngm:design-thinking ;
vc:enables ngm:distributed-brainstorming ;
vc:enables ngm:retrospective ;
vc:enables ngm:sprint-planning ;
vc:enables ngm:user-journey-mapping ;
vc:enables ngm:visual-process-mapping ;
vc:enables ngm:wardley-mapping ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:breakout-board ;
vc:hasPart ngm:connector ;
vc:hasPart ngm:crdt ;
vc:hasPart ngm:embed-widget ;
vc:hasPart ngm:follow-mode ;
vc:hasPart ngm:frame ;
vc:hasPart ngm:freehand-drawing ;
vc:hasPart ngm:infinite-canvas ;
vc:hasPart ngm:kanban-board ;
vc:hasPart ngm:mind-map ;
vc:hasPart ngm:real-time-cursors ;
vc:hasPart ngm:shape-library ;
vc:hasPart ngm:sticky-notes ;
vc:hasPart ngm:template-library ;
vc:hasPart ngm:timer ;
vc:hasPart ngm:voting-system ;
vc:hasPart ngm:voting-systems ;
vc:implements ngm:conflict-resolution ;
vc:implements ngm:crdt ;
vc:implements ngm:lww-register ;
vc:implements ngm:operational-transformation ;
vc:implements ngm:or-set ;
vc:implements ngm:vector-graphics ;
vc:implements ngm:web-rtc ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:breakout-room ;
vc:relatedTo ngm:collaboration-platform ;
vc:relatedTo ngm:confluence ;
vc:relatedTo ngm:design-tools ;
vc:relatedTo ngm:excalidraw ;
vc:relatedTo ngm:fig-jam ;
vc:relatedTo ngm:figma ;
vc:relatedTo ngm:jira ;
vc:relatedTo ngm:miro ;
vc:relatedTo ngm:mural ;
vc:relatedTo ngm:project-management ;
vc:relatedTo ngm:screen-sharing ;
vc:relatedTo ngm:slack ;
vc:relatedTo ngm:video-conferencing ;
vc:requires ngm:authentication ;
vc:requires ngm:browser-graphics-rendering ;
vc:requires ngm:cdn ;
vc:requires ngm:cloud-storage ;
vc:requires ngm:crdt ;
vc:requires ngm:operational-transformation ;
vc:requires ngm:web-gl ;
vc:requires ngm:web-socket ;
vc:slug "collaborative-whiteboard" ;
vc:sourceDomain "distributed-collaboration" ;
vc:standardizedBy ngm:crdt-academic-literature ;
vc:standardizedBy ngm:iso-9241-usability ;
vc:standardizedBy ngm:w3c-pointer-events ;
vc:standardizedBy ngm:wcag-2-2 ;
vc:standardizedBy ngm:web-rtc ;
vc:supports ngm:agile-retrospective ;
vc:supports ngm:design-thinking ;
vc:supports ngm:inclusive-participation ;
vc:supports ngm:knowledge-management ;
vc:supports ngm:liberating-structures ;
vc:supports ngm:remote-facilitation ;
vc:supports ngm:sprint-planning ;
vc:uses ngm:canvas-api ;
vc:uses ngm:json-data-interchange-format ;
vc:uses ngm:large-language-models ;
vc:uses ngm:oauth-2-0 ;
vc:uses ngm:rest-api ;
vc:uses ngm:sentence-transformers ;
vc:uses ngm:svg ;
vc:uses ngm:web-gl ;
vc:uses ngm:web-socket .
ngm:collaborative-workflow a skos:Concept ;
rdfs:label "Collaborative Workflow"@en .
ngm:collaborative-workflows a skos:Concept ;
rdfs:label "Collaborative Workflows"@en .
ngm:collaborative-xr a skos:Concept ;
rdfs:label "Collaborative XR"@en .
ngm:collada a skos:Concept ;
rdfs:label "Collada"@en .
ngm:collada-format a skos:Concept ;
rdfs:label "Collada Format"@en .
ngm:collateral a owl:Class ;
rdfs:comment "Collateral is an asset pledged by a borrower to a lender as security for a loan or obligation, which the lender may seize or liquidate if the borrower defaults. In decentralised finance it typically takes the form of over-collateralised crypto assets locked in a smart contract, backing loans, synthetic assets, or stablecoin pegs. The collateral-to-debt ratio determines solvency and triggers liquidation when it falls below a protocol-defined threshold."@en ;
rdfs:label "Collateral"@en ;
rdfs:subClassOf ngm:finance ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "collateral" ;
vc:sourceDomain "finance" .
ngm:collateral-factor a skos:Concept ;
rdfs:label "Collateral Factor"@en .
ngm:collateral-management a owl:Class ;
rdfs:comment "Collateral management is the operational and risk management discipline concerned with the posting, valuation, optimisation, and return of financial assets pledged as security against credit exposure in derivatives, securities lending, repo, and cleared transactions, ensuring that counterparty credit risk is adequately mitigated throughout the life of a financial contract. It encompasses collateral eligibility determination, margin call issuance and settlement, collateral transformation, and regulatory compliance with frameworks including EMIR, Dodd-Frank, and Basel III initial margin requirements."@en ;
rdfs:label "Collateral Management"@en ;
rdfs:subClassOf ngm:risk-management ;
vc:enables ngm:de-fi ;
vc:enables ngm:financial-stability ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:blockchain-oracle ;
vc:relatedTo ngm:financial-transactions ;
vc:relatedTo ngm:stablecoin ;
vc:slug "collateral-management" ;
vc:sourceDomain "finance" ;
vc:uses ngm:financial-instruments ;
vc:uses ngm:risk-assessment ;
vc:uses ngm:smart-contract .
ngm:collateralised-borrowing a owl:Class ;
rdfs:comment "Collateralised borrowing is a lending mechanism in which a borrower locks digital assets as collateral in a smart contract in order to draw a loan, typically in a different asset, without a credit check or intermediary. The collateral is held against default risk and may be liquidated automatically if its value falls below a protocol-defined threshold relative to the loan. It is a core primitive of decentralised finance protocols such as Aave and Compound."@en ;
rdfs:label "Collateralised Borrowing"@en ;
rdfs:subClassOf ngm:de-fi ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:de-fi ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "collateralised-borrowing" ;
vc:sourceDomain "blockchain" .
ngm:collateralised-debt-position a skos:Concept ;
rdfs:label "Collateralised Debt Position"@en .
ngm:collection-management a skos:Concept ;
rdfs:label "Collection Management"@en .
ngm:collective-action a owl:Class ;
rdfs:comment "Coordinated behaviour by a group of individuals or organisations toward a shared goal that no single actor could achieve unilaterally. It is characterised by interdependence, the risk of free-riding, and the need for mechanisms — such as incentives, norms, or contracts — to align individual contributions with the group objective."@en ;
rdfs:label "Collective Action"@en ;
rdfs:subClassOf ngm:coordination-mechanisms ;
rdfs:subClassOf _:r4705 ;
rdfs:subClassOf _:r4706 ;
rdfs:subClassOf _:r4707 ;
vc:bridgesTo ngm:dao ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:bridgesTo ngm:multi-agent-system ;
vc:contrastsWith ngm:individual-rationality ;
vc:contrastsWith ngm:tragedy-of-the-commons ;
vc:enables ngm:collective-governance ;
vc:enables ngm:institutional-design ;
vc:enables ngm:public-goods ;
vc:enables ngm:public-goods-funding ;
vc:enables ngm:social-interaction ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:free-rider-problem ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:collective-intelligence ;
vc:relatedTo ngm:common-pool-resources ;
vc:relatedTo ngm:community-governance ;
vc:relatedTo ngm:game-theory ;
vc:relatedTo ngm:prisoners-dilemma ;
vc:relatedTo ngm:social-contract ;
vc:requires ngm:incentive-mechanism ;
vc:requires ngm:monitoring ;
vc:requires ngm:trust ;
vc:slug "collective-action" ;
vc:sourceDomain "governance" ;
vc:uses ngm:coordination-protocol ;
vc:uses ngm:smart-contract ;
vc:uses ngm:voting-mechanism .
ngm:collective-anomaly-detection a skos:Concept ;
rdfs:label "Collective Anomaly Detection"@en .
ngm:collective-bargaining a skos:Concept ;
rdfs:label "Collective Bargaining"@en .
ngm:collective-behaviour a skos:Concept ;
rdfs:label "Collective Behaviour"@en .
ngm:collective-code-ownership a skos:Concept ;
rdfs:label "Collective Code Ownership"@en .
ngm:collective-communication a owl:Class ;
rdfs:comment "Collective communication is the class of synchronised, multi-party data-exchange operations in which a group of processes jointly participate, such as broadcast, scatter, gather, all-gather, reduce, and all-reduce. It provides the communication primitives that coordinate state across the nodes of a parallel or distributed system, and it is the backbone of distributed machine-learning training, where gradients and parameters are aggregated and synchronised across many accelerators. Implementations are optimised over high-speed interconnects to minimise the communication overhead that otherwise bottlenecks scaling."@en ;
rdfs:label "Collective Communication"@en ;
rdfs:subClassOf ngm:distributed-training ;
rdfs:subClassOf _:r4708 ;
rdfs:subClassOf _:r4709 ;
vc:dependsOn ngm:message-passing ;
vc:dependsOn ngm:rdma ;
vc:enables ngm:data-parallelism ;
vc:enables ngm:model-parallelism ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:gradient-aggregation ;
vc:isPartOf ngm:distributed-training ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:gpu-cluster ;
vc:relatedTo ngm:gradient-aggregation ;
vc:relatedTo ngm:message-passing ;
vc:requires ngm:gpu-cluster ;
vc:requires ngm:interconnect ;
vc:slug "collective-communication" ;
vc:sourceDomain "machine-learning" ;
vc:supports ngm:parameter-server ;
vc:uses ngm:infiniband ;
vc:uses ngm:mpi .
ngm:collective-decision-making a owl:Class ;
rdfs:comment "Collective decision making is the social and technical process by which a group of agents — human, algorithmic, or hybrid — aggregate individual preferences, information, or votes to arrive at a binding or advisory choice on behalf of the group. It encompasses the design and analysis of voting systems, preference aggregation mechanisms, deliberation protocols, and incentive structures that determine how group choices are reached and enforced. In digital and distributed contexts, collective decision making is formalised through on-chain governance mechanisms, decentralised autonomous organisations, and algorithmic consensus protocols that encode group agency in smart contract logic. The field draws on social choice theory, mechanism design, game theory, and organisational science to evaluate fairness, efficiency, and manipulation-resistance of alternative procedures."@en ;
rdfs:label "Collective Decision Making"@en ;
rdfs:subClassOf ngm:social-choice-theory ;
rdfs:subClassOf _:r4710 ;
rdfs:subClassOf _:r4711 ;
vc:bridgesTo ngm:consensus-algorithm ;
vc:bridgesTo ngm:federated-learning ;
vc:bridgesTo ngm:multi-agent-system ;
vc:contrastsWith ngm:autocratic-governance ;
vc:contrastsWith ngm:centralised-authority ;
vc:dependsOn ngm:game-theory ;
vc:dependsOn ngm:mechanism-design ;
vc:enables ngm:community-governance ;
vc:enables ngm:dao-governance ;
vc:enables ngm:on-chain-governance ;
vc:enables ngm:participatory-democracy ;
vc:enables ngm:protocol-upgrade ;
vc:enables ngm:protocol-upgrades ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:proposal-process ;
vc:hasPart ngm:quorum-requirement ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:arrow-impossibility-theorem ;
vc:relatedTo ngm:collective-intelligence-system ;
vc:relatedTo ngm:consent-management ;
vc:relatedTo ngm:deliberative-democracy ;
vc:relatedTo ngm:governance-token ;
vc:requires ngm:deliberation-protocol ;
vc:requires ngm:identity-verification ;
vc:requires ngm:preference-aggregation ;
vc:slug "collective-decision-making" ;
vc:sourceDomain "governance" ;
vc:uses ngm:conviction-voting ;
vc:uses ngm:liquid-democracy ;
vc:uses ngm:quadratic-voting ;
vc:uses ngm:ranked-choice-voting ;
vc:uses ngm:token-weighted-voting ;
vc:uses ngm:voting-mechanism .
ngm:collective-governance a owl:Class ;
rdfs:comment "A system of rules, norms, and decision-making processes through which a group of stakeholders jointly determines how shared resources, organisations, or platforms are managed. It distributes authority among participants rather than concentrating it in a single administrator, seeking legitimacy through inclusive participation and transparent deliberation."@en ;
rdfs:label "Collective Governance"@en ;
rdfs:subClassOf ngm:community-governance ;
rdfs:subClassOf _:r4712 ;
rdfs:subClassOf _:r4713 ;
vc:enables ngm:dao-governance ;
vc:enables ngm:polycentric-governance ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:collective-decision-making ;
vc:relatedTo ngm:community-decision-making ;
vc:requires ngm:collective-action ;
vc:requires ngm:coordination-mechanisms ;
vc:slug "collective-governance" ;
vc:sourceDomain "governance" .
ngm:collective-intelligence a owl:Class ;
rdfs:comment "Collective intelligence is the shared or group intelligence that emerges from the collaboration, competition, and collective decision-making of many individuals or agents, producing cognitive capacities — prediction accuracy, problem-solving breadth, creative output — that exceed what any individual participant could achieve alone. It manifests in biological systems such as ant colonies and immune networks, human social institutions, and engineered multi-agent systems, and is characterised by distributed information processing, diversity of perspective, and aggregation mechanisms."@en ;
rdfs:label "Collective Intelligence"@en ;
rdfs:subClassOf ngm:collective-intelligence-system ;
rdfs:subClassOf _:r4727 ;
vc:bridgesTo ngm:ant-colony-optimisation ;
vc:bridgesTo ngm:decentralised-autonomous-organisation ;
vc:enables ngm:collective-decision-making ;
vc:enables ngm:decentralised-coordination ;
vc:enables ngm:emergence ;
vc:enables ngm:open-source-development ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:stigmergy ;
vc:hasPart ngm:wisdom-of-crowds ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:agent-based-models ;
vc:relatedTo ngm:ensemble-methods ;
vc:relatedTo ngm:governance ;
vc:relatedTo ngm:multi-agent-systems ;
vc:slug "collective-intelligence" ;
vc:sourceDomain "distributed-collaboration" ;
vc:uses ngm:knowledge-management ;
vc:uses ngm:multi-agent-system ;
vc:uses ngm:prediction-markets ;
vc:uses ngm:swarm-intelligence .
ngm:collective-intelligence-system a owl:Class ;
rdfs:comment "Mechanism enabling groups of humans and agents to solve problems collaboratively using shared data through swarm intelligence and emergent decision-making."@en ;
rdfs:label "Collective Intelligence System"@en ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf ngm:collaborative-systems-modality ;
rdfs:subClassOf ngm:distributed-artificial-intelligence ;
rdfs:subClassOf ngm:multi-agent-system ;
rdfs:subClassOf _:r4714 ;
rdfs:subClassOf _:r4715 ;
rdfs:subClassOf _:r4716 ;
rdfs:subClassOf _:r4717 ;
rdfs:subClassOf _:r4718 ;
rdfs:subClassOf _:r4719 ;
rdfs:subClassOf _:r4720 ;
rdfs:subClassOf _:r4721 ;
rdfs:subClassOf _:r4722 ;
rdfs:subClassOf _:r4723 ;
rdfs:subClassOf _:r4724 ;
rdfs:subClassOf _:r4725 ;
rdfs:subClassOf _:r4726 ;
skos:broader ngm:ai-research-area ;
vc:bridgesTo ngm:autonomous-robot ;
vc:bridgesTo ngm:decentralised-autonomous-organisation ;
vc:bridgesTo ngm:digital-democracy ;
vc:contrastsWith ngm:agent ;
vc:contrastsWith ngm:centralised-ai ;
vc:contrastsWith ngm:crowd-sourcing-platform ;
vc:contrastsWith ngm:expert-systems ;
vc:dependsOn ngm:complex-systems ;
vc:dependsOn ngm:distributed-computing ;
vc:dependsOn ngm:game-theory ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:network-infrastructure ;
vc:enables ngm:collaborative-decision-making ;
vc:enables ngm:collective-learning ;
vc:enables ngm:crowd-wisdom ;
vc:enables ngm:emergent-problem-solving ;
vc:enables ngm:federated-learning ;
vc:enables ngm:swarm-intelligence ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:consensus-mechanism ;
vc:hasPart ngm:data-synchronization ;
vc:hasPart ngm:distributed-decision-making ;
vc:hasPart ngm:emergent-pattern-detector ;
vc:hasPart ngm:human-computer-interface ;
vc:hasPart ngm:knowledge-aggregation-module ;
vc:hasPart ngm:shared-knowledge-base ;
vc:hasPart ngm:swarm-coordination-engine ;
vc:implements ngm:ant-colony-optimisation ;
vc:implements ngm:mixture-of-agents ;
vc:implements ngm:stigmergy ;
vc:isPartOf ngm:collaborative-systems-modality ;
vc:isPartOf ngm:distributed-computing ;
vc:isPartOf ngm:multi-agent-system ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:agent-based-modelling ;
vc:relatedTo ngm:distributed-artificial-intelligence ;
vc:relatedTo ngm:emergence ;
vc:relatedTo ngm:human-computer-interaction ;
vc:relatedTo ngm:wisdom-of-crowds ;
vc:requires ngm:agent-communication-language ;
vc:requires ngm:communication-protocol ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:data-synchronization ;
vc:requires ngm:network-infrastructure ;
vc:requires ngm:shared-knowledge-base ;
vc:slug "collective-intelligence-system" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:fipa ;
vc:standardizedBy ngm:ieee-std-2510 ;
vc:standardizedBy ngm:w3c-web-of-things ;
vc:supports ngm:autonomous-robot ;
vc:supports ngm:crisis-management ;
vc:supports ngm:healthcare-decision-support ;
vc:supports ngm:policy-design ;
vc:supports ngm:scientific-collaboration ;
vc:uses ngm:bayesian-inference ;
vc:uses ngm:large-language-model ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:reinforcement-learning .
ngm:collective-learning a owl:Class ;
rdfs:comment "A collaborative educational approach in virtual environments and metaverse platforms where groups of learners work toger to construct knowledge, share experiences, and solve problems through social interaction, benefiting from diverse perspectives, AI-powered personalization, and immersive VR/AR ..."@en ;
rdfs:label "Collective Learning"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:educational-methodology ;
rdfs:subClassOf _:r4728 ;
rdfs:subClassOf _:r4729 ;
rdfs:subClassOf _:r4730 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:educational-methodology ;
vc:bridgesTo ngm:telecollaboration ;
vc:enables ngm:collaboration ;
vc:enables ngm:knowledge-co-construction ;
vc:enables ngm:peer-learning ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:communication-tools ;
vc:requires ngm:learning-management-system ;
vc:requires ngm:virtual-environment ;
vc:slug "collective-learning" ;
vc:sourceDomain "artificial-intelligence" .
ngm:collective-memory-archive a owl:Class ;
rdfs:comment "A community-maintained repository that preserves shared cultural memories, historical events, and collective experiences for long-term access and cultural heritage preservation."@en ;
rdfs:label "Collective Memory Archive"@en ;
rdfs:subClassOf ngm:sc-content-and-assets ;
rdfs:subClassOf _:r4731 ;
rdfs:subClassOf _:r4732 ;
rdfs:subClassOf _:r4733 ;
rdfs:subClassOf _:r4734 ;
skos:broader ngm:sc-content-and-assets ;
vc:bridgesTo ngm:did-nostr-identity ;
vc:dependsOn ngm:preservation-policies ;
vc:dependsOn ngm:search-engine ;
vc:dependsOn ngm:storage-infrastructure ;
vc:enables ngm:community-storytelling ;
vc:enables ngm:cultural-preservation ;
vc:enables ngm:heritage-access ;
vc:enables ngm:historical-documentation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:access-control-system ;
vc:hasPart ngm:community-contributions ;
vc:hasPart ngm:memory-records ;
vc:hasPart ngm:preservation-metadata ;
vc:hasPart ngm:temporal-index ;
vc:isPartOf ngm:community-knowledge-systems ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:authentication-service ;
vc:requires ngm:digital-repository ;
vc:requires ngm:metadata-registry ;
vc:slug "collective-memory-archive" ;
vc:sourceDomain "spatial-computing" .
ngm:collective-ownership a skos:Concept ;
rdfs:label "Collective Ownership"@en .
ngm:collective-proceedings a skos:Concept ;
rdfs:label "Collective Proceedings"@en .
ngm:collective-redress a skos:Concept ;
rdfs:label "Collective Redress"@en .
ngm:collision-avoidance a owl:Class ;
rdfs:comment "Collision Avoidance - An active safety mechanism using Sensors (lidar, ultrasonic, vision) and path planning algorithms to detect obstacles and dynamically modify Robot Trajectories to prevent unintended contact with people, equipment, or structures."@en ;
rdfs:label "Collision Avoidance"@en ;
rdfs:subClassOf ngm:robo-navigation-and-planning ;
rdfs:subClassOf ngm:robotics ;
rdfs:subClassOf _:r4735 ;
rdfs:subClassOf _:r4736 ;
rdfs:subClassOf _:r4737 ;
rdfs:subClassOf _:r4738 ;
rdfs:subClassOf _:r4739 ;
rdfs:subClassOf _:r4740 ;
skos:broader ngm:robo-navigation-and-planning ;
skos:broader ngm:robotics ;
vc:bridgesTo ngm:computer-vision ;
vc:contrastsWith ngm:reactive-control ;
vc:dependsOn ngm:real-time-operating-system ;
vc:enables ngm:autonomous-navigation ;
vc:enables ngm:safe-human-robot-proximity ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:advanced-driver-assistance-system ;
vc:isPartOf ngm:motion-control ;
vc:isPartOf ngm:safety-system ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:functional-safety ;
vc:requires ngm:obstacle-detection ;
vc:requires ngm:perception-system ;
vc:requires ngm:rb-0090-emergency-stop ;
vc:requires ngm:real-time-processing ;
vc:requires ngm:sensor-fusion ;
vc:slug "collision-avoidance" ;
vc:sourceDomain "robotics" ;
vc:standardizedBy ngm:ieee-standards ;
vc:standardizedBy ngm:iso-26262 ;
vc:uses ngm:computer-vision ;
vc:uses ngm:lidar ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:path-planning .
ngm:collision-detection a owl:Class ;
rdfs:comment "Collision Detection is the computational discipline of determining when two or more geometric primitives, rigid bodies, deformable meshes, articulated kinematic chains, or volumetric fields occupy overlapping regions of a shared spatial domain, decomposed canonically into a broad phase that rapid..."@en ;
rdfs:label "Collision Detection"@en ;
rdfs:subClassOf ngm:computational-geometry ;
rdfs:subClassOf ngm:geometric-algorithm ;
rdfs:subClassOf ngm:physics-simulation ;
rdfs:subClassOf ngm:real-time-algorithm ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf ngm:spatial-computing-paradigm ;
rdfs:subClassOf _:r4741 ;
rdfs:subClassOf _:r4742 ;
rdfs:subClassOf _:r4743 ;
rdfs:subClassOf _:r4744 ;
skos:broader ngm:sc-platform-and-environment ;
vc:contrastsWith ngm:frustum-culling ;
vc:contrastsWith ngm:occlusion-culling ;
vc:contrastsWith ngm:path-planning ;
vc:contrastsWith ngm:ray-casting ;
vc:contrastsWith ngm:visibility-determination ;
vc:dependsOn ngm:control-theory ;
vc:dependsOn ngm:convex-optimization ;
vc:dependsOn ngm:linear-algebra ;
vc:dependsOn ngm:minkowski-sum ;
vc:dependsOn ngm:numerical-methods ;
vc:dependsOn ngm:quaternion-math ;
vc:dependsOn ngm:risk-assessment ;
vc:enables ngm:cloth-simulation ;
vc:enables ngm:collision-avoidance ;
vc:enables ngm:haptic-feedback ;
vc:enables ngm:motion-planning ;
vc:enables ngm:physics-simulation ;
vc:enables ngm:predictive-maintenance ;
vc:enables ngm:quality-assurance ;
vc:enables ngm:ragdoll-animation ;
vc:enables ngm:safety-certification ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:bounding-volume-hierarchy ;
vc:hasPart ngm:broad-phase-detection ;
vc:hasPart ngm:contact-manifold ;
vc:hasPart ngm:contact-resolution ;
vc:hasPart ngm:narrow-phase-detection ;
vc:hasPart ngm:penetration-depth ;
vc:hasPart ngm:separating-axis-theorem ;
vc:hasPart ngm:time-of-impact ;
vc:implements ngm:bsp-tree ;
vc:implements ngm:conservative-advancement ;
vc:implements ngm:continuous-collision-detection ;
vc:implements ngm:epa-algorithm ;
vc:implements ngm:gjk-algorithm ;
vc:implements ngm:signed-distance-function ;
vc:implements ngm:spatial-hashing ;
vc:implements ngm:sweep-and-prune ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:cloth-simulation ;
vc:relatedTo ngm:deep-sdf ;
vc:relatedTo ngm:deepsdf ;
vc:relatedTo ngm:fluid-simulation ;
vc:relatedTo ngm:gpu-computing ;
vc:relatedTo ngm:inverse-kinematics ;
vc:relatedTo ngm:motion-planning ;
vc:relatedTo ngm:neural-implicit-surface ;
vc:relatedTo ngm:rigid-body-dynamics ;
vc:relatedTo ngm:soft-body-dynamics ;
vc:relatedTo ngm:training-data ;
vc:requires ngm:coordinate-frame ;
vc:requires ngm:floating-point-arithmetic ;
vc:requires ngm:geometric-primitive ;
vc:requires ngm:numerical-robustness ;
vc:requires ngm:spatial-partitioning ;
vc:slug "collision-detection" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:iso-iec-18039 ;
vc:standardizedBy ngm:khronos-open-xr ;
vc:standardizedBy ngm:mjcf ;
vc:standardizedBy ngm:ros-rep ;
vc:standardizedBy ngm:urdf ;
vc:standardizedBy ngm:usd-physics-schema ;
vc:standardizedBy ngm:w-3-c-web-xr ;
vc:supports ngm:animation ;
vc:supports ngm:autonomous-vehicle ;
vc:supports ngm:cad-software ;
vc:supports ngm:crash-simulation ;
vc:supports ngm:digital-twin ;
vc:supports ngm:robotics ;
vc:supports ngm:surgical-simulation ;
vc:supports ngm:video-games ;
vc:supports ngm:vr-ar ;
vc:uses ngm:box2-d ;
vc:uses ngm:box2d ;
vc:uses ngm:brax ;
vc:uses ngm:bullet-physics ;
vc:uses ngm:drake ;
vc:uses ngm:fcl ;
vc:uses ngm:havok-physics ;
vc:uses ngm:jolt-physics ;
vc:uses ngm:mu-jo-co ;
vc:uses ngm:nvidia-corporation-flex ;
vc:uses ngm:nvidia-corporation-phys-x ;
vc:uses ngm:nvidia-corporation-warp ;
vc:uses ngm:nvidia-flex ;
vc:uses ngm:nvidia-physx ;
vc:uses ngm:nvidia-warp ;
vc:uses ngm:open-dynamics-engine ;
vc:uses ngm:rapier-physics .
ngm:collision-detection-system a owl:Class ;
rdfs:comment "A computational subsystem that continuously tests whether geometric objects in a simulation or physical environment intersect or are about to intersect, enabling physics engines, robotics planners, and interactive applications to respond to contact events. It combines spatial partitioning structures with narrow-phase geometry tests to balance accuracy against performance."@en ;
rdfs:label "Collision Detection System"@en ;
rdfs:subClassOf ngm:collision-detection ;
vc:enables ngm:collision-avoidance ;
vc:enables ngm:haptic-feedback ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:cloth-simulation ;
vc:relatedTo ngm:collaborative-systems-modality-simulation ;
vc:slug "collision-detection-system" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:bullet-physics ;
vc:uses ngm:game-engine .
ngm:collision-free-motion a skos:Concept ;
rdfs:label "Collision Free Motion"@en .
ngm:collision-mesh a skos:Concept ;
rdfs:label "Collision Mesh"@en .
ngm:collision-resistance a owl:Class ;
rdfs:comment "A security property of a cryptographic hash function asserting that it is computationally infeasible to find two distinct inputs that produce the same output digest. Collision resistance underpins the integrity guarantees of Merkle trees, digital signatures, and proof-of-work puzzles, and its absence would allow adversaries to forge blocks or certificates."@en ;
rdfs:label "Collision Resistance"@en ;
rdfs:subClassOf ngm:blockchain-entity ;
rdfs:subClassOf ngm:cryptographic-primitive ;
vc:enables ngm:digital-signature ;
vc:enables ngm:merkle-tree ;
vc:enables ngm:proof-of-work ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:cryptographic-primitive ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:cryptographic-hash-function ;
vc:relatedTo ngm:hash-function ;
vc:relatedTo ngm:keccak-256 ;
vc:relatedTo ngm:preimage-resistance ;
vc:relatedTo ngm:sha-256 ;
vc:slug "collision-resistance" ;
vc:sourceDomain "blockchain" .
ngm:collision-response a skos:Concept ;
rdfs:label "Collision Response"@en .
ngm:collocated-work a skos:Concept ;
rdfs:label "Collocated Work"@en .
ngm:colmap a owl:Class ;
rdfs:comment "COLMAP is an open-source general-purpose Structure-from-Motion and multi-view stereo pipeline used to reconstruct three-dimensional scenes from unordered collections of photographs. It performs feature extraction, image matching, incremental camera pose estimation, triangulation, and dense point-cloud generation. COLMAP is widely used as a preprocessing step for neural radiance fields and 3D Gaussian Splatting pipelines. Its modular architecture supports both GPU-accelerated and CPU-only execution, making it accessible across a range of hardware configurations."@en ;
rdfs:label "COLMAP"@en ;
rdfs:subClassOf ngm:structure-from-motion ;
vc:enables ngm:3-d-gaussian-splatting ;
vc:enables ngm:gaussian-splatting ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:depth-estimation ;
vc:relatedTo ngm:photogrammetry ;
vc:relatedTo ngm:point-cloud ;
vc:relatedTo ngm:spatial-mapping ;
vc:slug "colmap" ;
vc:sourceDomain "metaverse" ;
vc:uses ngm:computer-vision ;
vc:uses ngm:gpu-computing .
ngm:colocation-services a skos:Concept ;
rdfs:label "Colocation Services"@en .
ngm:colony-governance a skos:Concept ;
rdfs:label "Colony Governance"@en .
ngm:color-accuracy a skos:Concept ;
rdfs:label "Color Accuracy"@en .
ngm:color-grading a skos:Concept ;
rdfs:label "Color Grading"@en .
ngm:color-management-system a skos:Concept ;
rdfs:label "Color Management System"@en .
ngm:colored-coins a skos:Concept ;
rdfs:label "Colored Coins"@en .
ngm:colorimeter a skos:Concept ;
rdfs:label "Colorimeter"@en .
ngm:colour-contrast a skos:Concept ;
rdfs:label "Colour Contrast"@en .
ngm:colour-correction a skos:Concept ;
rdfs:label "Colour Correction"@en .
ngm:colour-grading a owl:Class ;
rdfs:comment "Colour grading is the post-production process of altering and enhancing the colour, contrast, and tonal qualities of a moving image or rendered frame to establish a consistent look and convey mood. It builds on basic colour correction — which neutralises exposure and white-balance errors — by applying creative adjustments such as curves, lift-gamma-gain controls, and secondary qualifiers that isolate specific hues or regions. In real-time rendering and virtual production the grade is frequently applied as a post-processing pass using look-up tables and tone-mapping operators so interactive scenes match the intended cinematic aesthetic."@en ;
rdfs:label "Colour Grading"@en ;
rdfs:subClassOf ngm:post-processing ;
rdfs:subClassOf _:r4745 ;
rdfs:subClassOf _:r4746 ;
rdfs:subClassOf _:r4747 ;
vc:enables ngm:photorealism ;
vc:enables ngm:visual-effects ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:colour-correction ;
vc:hasPart ngm:tone-mapping ;
vc:isPartOf ngm:film-production ;
vc:isPartOf ngm:post-processing ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:computer-graphics ;
vc:relatedTo ngm:physically-based-rendering ;
vc:requires ngm:gpu-rendering ;
vc:requires ngm:rendering ;
vc:slug "colour-grading" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:hdr ;
vc:uses ngm:shader ;
vc:uses ngm:texture-mapping .
ngm:colour-management a owl:Class ;
rdfs:comment "Colour management is the controlled conversion of colour representations between the characteristics of different devices and media so that colours appear consistent across capture, display and output. It relies on device profiles that describe how a given device reproduces colour and a profile connection space to translate between them. In spatial computing and real-time rendering, colour management ensures perceptually accurate imagery across cameras, displays and headsets."@en ;
rdfs:label "Colour Management"@en ;
rdfs:subClassOf ngm:display-technology ;
rdfs:subClassOf _:r4748 ;
rdfs:subClassOf _:r4749 ;
vc:bridgesTo ngm:augmented-reality ;
vc:contrastsWith ngm:rendering ;
vc:dependsOn ngm:display-technology ;
vc:enables ngm:physically-based-rendering ;
vc:enables ngm:rendering-pipeline ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:display-calibration ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:computer-graphics ;
vc:relatedTo ngm:design-software ;
vc:relatedTo ngm:texture-mapping ;
vc:requires ngm:display-calibration ;
vc:slug "colour-management" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:real-time-rendering ;
vc:supports ngm:virtual-production ;
vc:uses ngm:shader .
ngm:colour-palette a skos:Concept ;
rdfs:label "Colour Palette"@en .
ngm:colour-reference-chart a skos:Concept ;
rdfs:label "Colour Reference Chart"@en .
ngm:colour-science a skos:Concept ;
rdfs:label "Colour Science"@en .
ngm:colour-subsampling a skos:Concept ;
rdfs:label "Colour Subsampling"@en .
ngm:colour-theory a skos:Concept ;
rdfs:label "Colour Theory"@en .
ngm:coloured-coins a skos:Concept ;
rdfs:label "Coloured Coins"@en .
ngm:column-wise-normalisation a skos:Concept ;
rdfs:label "Column Wise Normalisation"@en .
ngm:columnar-database a skos:Concept ;
rdfs:label "Columnar Database"@en .
ngm:columnar-databases a skos:Concept ;
rdfs:label "Columnar Databases"@en .
ngm:columnar-index a skos:Concept ;
rdfs:label "Columnar Index"@en .
ngm:columnar-storage a owl:Class ;
rdfs:comment "Columnar storage is a data organisation scheme that stores values from the same column of a table contiguously on disk, rather than storing complete rows together as in row-oriented storage. This layout allows analytical queries to scan only the columns they need, and enables aggressive compression because adjacent values within a column tend to be similar. Formats such as Apache Parquet and engines built for online analytical processing rely on columnar storage to accelerate large-scale aggregation and filtering workloads."@en ;
rdfs:label "Columnar Storage"@en ;
rdfs:subClassOf ngm:data-storage ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:slug "columnar-storage" ;
vc:sourceDomain "data" .
ngm:combinatorial-auction a skos:Concept ;
rdfs:label "Combinatorial Auction"@en .
ngm:combinatorial-optimisation a owl:Class ;
rdfs:comment "Combinatorial optimisation is the study of finding an optimal object from a finite but typically enormous set of discrete candidate solutions. Problems are defined over discrete structures such as graphs, permutations and integer assignments, and many are NP-hard, meaning no known algorithm solves all instances efficiently. Practical approaches combine exact methods, approximation algorithms and metaheuristics to obtain good solutions within acceptable time bounds."@en ;
rdfs:label "Combinatorial Optimisation"@en ;
rdfs:subClassOf ngm:mathematical-optimisation ;
rdfs:subClassOf ngm:optimisation ;
rdfs:subClassOf _:r4750 ;
rdfs:subClassOf _:r4751 ;
rdfs:subClassOf _:r4752 ;
rdfs:subClassOf _:r4753 ;
rdfs:subClassOf _:r4754 ;
rdfs:subClassOf _:r4755 ;
rdfs:subClassOf _:r4756 ;
vc:contrastsWith ngm:bayesian-optimisation ;
vc:contrastsWith ngm:convex-optimisation ;
vc:dependsOn ngm:algorithm ;
vc:dependsOn ngm:computational-complexity ;
vc:dependsOn ngm:graph-theory ;
vc:dependsOn ngm:np-hardness ;
vc:enables ngm:constraint-satisfaction ;
vc:enables ngm:logistics ;
vc:enables ngm:network-design ;
vc:enables ngm:planning-and-scheduling ;
vc:enables ngm:supply-chain ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:approximation-algorithm ;
vc:hasPart ngm:branch-and-bound ;
vc:hasPart ngm:dynamic-programming ;
vc:hasPart ngm:local-search ;
vc:hasPart ngm:metaheuristic ;
vc:implements ngm:heuristic-search ;
vc:implements ngm:integer-programming ;
vc:isPartOf ngm:mathematical-optimisation ;
vc:isPartOf ngm:operations-research ;
vc:isPartOf ngm:optimisation ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:constraint-solver ;
vc:relatedTo ngm:mathematical-optimisation ;
vc:relatedTo ngm:multi-objective-optimisation ;
vc:relatedTo ngm:quantum-computation-paradigm ;
vc:relatedTo ngm:reinforcement-learning ;
vc:requires ngm:algorithm ;
vc:requires ngm:computational-complexity-theory ;
vc:requires ngm:graph-theory ;
vc:requires ngm:optimisation ;
vc:slug "combinatorial-optimisation" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:operations-research ;
vc:supports ngm:decision-making ;
vc:supports ngm:hyperparameter-optimisation ;
vc:supports ngm:neural-architecture-search ;
vc:uses ngm:dynamic-programming ;
vc:uses ngm:genetic-algorithm ;
vc:uses ngm:graph-neural-network ;
vc:uses ngm:integer-programming ;
vc:uses ngm:linear-programming ;
vc:uses ngm:simulated-annealing ;
vc:uses ngm:tabu-search .
ngm:combinatorial-problem-solving a skos:Concept ;
rdfs:label "Combinatorial Problem Solving"@en .
ngm:combinatorics a skos:Concept ;
rdfs:label "Combinatorics"@en .
ngm:comet a owl:Class ;
rdfs:label "Comet"@en ;
rdfs:subClassOf ngm:astronomical-body ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:astronomy ;
vc:slug "comet" ;
vc:sourceDomain "space-science-and-systems" .
ngm:comet-metric a owl:Class ;
rdfs:comment "A family of learned, reference-based and reference-free evaluation metrics for machine translation that use pre-trained multilingual language model representations to predict human-quality assessments of translation output. COMET models correlate more strongly with human judgements than n-gram-overlap metrics such as BLEU by capturing semantic and contextual similarity rather than surface string matching."@en ;
rdfs:label "COMET Metric"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:evaluation-metric ;
rdfs:subClassOf ngm:natural-language-processing ;
rdfs:subClassOf _:r3782 ;
rdfs:subClassOf _:r3783 ;
rdfs:subClassOf _:r3784 ;
rdfs:subClassOf _:r3785 ;
skos:broader ngm:ai-technique ;
vc:contrastsWith ngm:bleu-score ;
vc:contrastsWith ngm:bleurt ;
vc:contrastsWith ngm:chrf ;
vc:contrastsWith ngm:meteor ;
vc:contrastsWith ngm:ter ;
vc:contrastsWith ngm:translation ;
vc:dependsOn ngm:direct-assessment ;
vc:dependsOn ngm:multidimensional-quality-metrics ;
vc:dependsOn ngm:wmt-shared-task ;
vc:dependsOn ngm:xlm-roberta ;
vc:enables ngm:human-evaluation ;
vc:enables ngm:mt-benchmarking ;
vc:enables ngm:post-editing-workflow ;
vc:enables ngm:quality-estimation ;
vc:enables ngm:translation-quality-assurance ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:direct-assessment ;
vc:hasPart ngm:multidimensional-quality-metrics ;
vc:hasPart ngm:quality-estimation ;
vc:hasPart ngm:regression-model ;
vc:hasPart ngm:xlm-roberta ;
vc:implements ngm:fine-tuning ;
vc:implements ngm:ranking-model ;
vc:implements ngm:regression-model ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:attention-mechanism ;
vc:relatedTo ngm:bleu-score ;
vc:relatedTo ngm:flores-200 ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:llm-as-judge ;
vc:relatedTo ngm:mqm-annotation ;
vc:relatedTo ngm:natural-language-understanding ;
vc:relatedTo ngm:neural-machine-translation ;
vc:relatedTo ngm:post-editing ;
vc:relatedTo ngm:post-editing-workflow ;
vc:relatedTo ngm:sequence-to-sequence-model ;
vc:relatedTo ngm:transformer-architecture ;
vc:relatedTo ngm:translation-quality-assurance ;
vc:relatedTo ngm:wmt-shared-task ;
vc:relatedTo ngm:xcomet ;
vc:requires ngm:human-annotation ;
vc:requires ngm:multilingual-language-model ;
vc:requires ngm:parallel-corpus ;
vc:requires ngm:transfer-learning ;
vc:slug "comet-metric" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:instituto-superior-tecnico ;
vc:standardizedBy ngm:unbabel ;
vc:standardizedBy ngm:wmt-shared-task ;
vc:supports ngm:machine-translation ;
vc:supports ngm:neural-machine-translation ;
vc:supports ngm:post-editing-workflow ;
vc:supports ngm:translation-quality-assurance ;
vc:uses ngm:contrastive-learning ;
vc:uses ngm:machine-translation ;
vc:uses ngm:multilingual-language-model ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:transfer-learning ;
vc:uses ngm:xlm-roberta .
ngm:comet-ml a skos:Concept ;
rdfs:label "Comet ML"@en .
ngm:comex-contract-specifications a skos:Concept ;
rdfs:label "Comex Contract Specifications"@en .
ngm:comex-futures-contract-standard a skos:Concept ;
rdfs:label "Comex Futures Contract Standard"@en .
ngm:comex-gold-futures a skos:Concept ;
rdfs:label "Comex Gold Futures"@en .
ngm:comfy-cli a skos:Concept ;
rdfs:label "Comfy Cli"@en .
ngm:comfy-node-registry a skos:Concept ;
rdfs:label "Comfy Node Registry"@en .
ngm:comfy-org a skos:Concept ;
rdfs:label "Comfy Org"@en .
ngm:comfy-org-2024-workflow-json-spec a skos:Concept ;
rdfs:label "Comfy Org 2024 Workflow Json Spec"@en .
ngm:comfy-org-git-hub-organisation a skos:Concept ;
rdfs:label "Comfy Org Git Hub Organisation"@en .
ngm:comfy-org-github-organisation a skos:Concept ;
rdfs:label "Comfy Org Github Organisation"@en .
ngm:comfy-ui a owl:Class ;
rdfs:comment "ComfyUI is an open-source, node-graph based interface for building and executing generative-AI image and video pipelines, most commonly around diffusion models such as Stable Diffusion. Users assemble workflows by wiring together nodes for model loading, sampling, conditioning and post-processing, giving fine-grained control over the generation graph. Its modular design supports extensions, custom nodes and reproducible, shareable workflows."@en ;
rdfs:label "Comfy Ui"@en ;
rdfs:subClassOf ngm:generative-ai ;
rdfs:subClassOf ngm:node-based-visual-programming ;
rdfs:subClassOf ngm:open-source-software ;
rdfs:subClassOf ngm:workflow-automation ;
rdfs:subClassOf _:r4757 ;
rdfs:subClassOf _:r4758 ;
rdfs:subClassOf _:r4759 ;
rdfs:subClassOf _:r4760 ;
rdfs:subClassOf _:r4761 ;
rdfs:subClassOf _:r4762 ;
rdfs:subClassOf _:r4763 ;
rdfs:subClassOf _:r4764 ;
rdfs:subClassOf _:r4765 ;
rdfs:subClassOf _:r4766 ;
vc:contrastsWith ngm:automatic-1111-web-ui ;
vc:contrastsWith ngm:generative-adversarial-network ;
vc:contrastsWith ngm:invoke-ai ;
vc:dependsOn ngm:clip ;
vc:dependsOn ngm:diffusion-model ;
vc:dependsOn ngm:latent-diffusion ;
vc:dependsOn ngm:latent-diffusion-pipeline ;
vc:dependsOn ngm:noise-schedule ;
vc:dependsOn ngm:stable-diffusion-image-model ;
vc:dependsOn ngm:vae ;
vc:enables ngm:agentic-workflow ;
vc:enables ngm:batch-image-processing ;
vc:enables ngm:content-creation-pipeline ;
vc:enables ngm:digital-asset-workflow ;
vc:enables ngm:image-generation ;
vc:enables ngm:image-synthesis ;
vc:enables ngm:image-to-image ;
vc:enables ngm:inpainting ;
vc:enables ngm:outpainting ;
vc:enables ngm:text-to-image ;
vc:enables ngm:video-generation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:checkpoint-model ;
vc:hasPart ngm:ksampler ;
vc:hasPart ngm:node-based-diffusion-pipeline-interface-api-specification ;
vc:hasPart ngm:node-based-diffusion-pipeline-interface-manager ;
vc:hasPart ngm:node-based-diffusion-pipeline-interface-workflows ;
vc:hasPart ngm:node-graph ;
vc:hasPart ngm:python-runtime ;
vc:hasPart ngm:rest-api ;
vc:hasPart ngm:web-socket-protocol ;
vc:implements ngm:content-production-workflow ;
vc:implements ngm:directed-acyclic-graph-execution ;
vc:implements ngm:workflow-automation ;
vc:implements ngm:workflow-json-format ;
vc:implements ngm:workflow-serialisation ;
vc:isPartOf ngm:generative-ai ;
vc:isPartOf ngm:open-source-software ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:agentic-workflow ;
vc:relatedTo ngm:deep-generative-model ;
vc:relatedTo ngm:digital-asset-workflow ;
vc:relatedTo ngm:generative-model ;
vc:relatedTo ngm:hugging-face-hub ;
vc:relatedTo ngm:image-to-image ;
vc:relatedTo ngm:inference-orchestration-system ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:neural-network ;
vc:relatedTo ngm:score-based-generative-model ;
vc:requires ngm:aiohttp ;
vc:requires ngm:diffusion-model ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:py-torch ;
vc:requires ngm:python ;
vc:slug "comfy-ui" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:comfy-org-github-organisation ;
vc:standardizedBy ngm:node-based-diffusion-pipeline-interface-api-specification ;
vc:supports ngm:animatediff ;
vc:supports ngm:control-net ;
vc:supports ngm:control-net-conditioning ;
vc:supports ngm:flux-1 ;
vc:supports ngm:ip-adapter ;
vc:supports ngm:latent-tensor ;
vc:supports ngm:lo-ra-fine-tuning ;
vc:supports ngm:prompt-engineering ;
vc:supports ngm:sdxl ;
vc:supports ngm:upscaling ;
vc:uses ngm:clip ;
vc:uses ngm:json-data-interchange-format-serialisation ;
vc:uses ngm:latent-diffusion ;
vc:uses ngm:lo-ra-fine-tuning ;
vc:uses ngm:node-graph ;
vc:uses ngm:noise-schedule ;
vc:uses ngm:py-torch ;
vc:uses ngm:stable-diffusion-image-model ;
vc:uses ngm:vae ;
vc:uses ngm:web-socket-protocol .
ngm:comfyui-animatediff-evolved a skos:Concept ;
rdfs:label "Comfyui Animatediff Evolved"@en .
ngm:comfyui-desktop-app a skos:Concept ;
rdfs:label "Comfyui Desktop App"@en .
ngm:comfyui-ipadapter-plus a skos:Concept ;
rdfs:label "Comfyui Ipadapter Plus"@en .
ngm:comfyui-node-registry a skos:Concept ;
rdfs:label "Comfyui Node Registry"@en .
ngm:command-and-control-infrastructure a skos:Concept ;
rdfs:label "Command And Control Infrastructure"@en .
ngm:command-and-control-organisations a skos:Concept ;
rdfs:label "Command And Control Organisations"@en .
ngm:command-and-data-handling a owl:Class ;
rdfs:label "Command and Data Handling"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:space-systems-engineering ;
vc:slug "command-and-data-handling" ;
vc:sourceDomain "space-science-and-systems" .
ngm:command-buffer a skos:Concept ;
rdfs:label "Command Buffer"@en .
ngm:command-line-interface a skos:Concept ;
rdfs:label "Command Line Interface"@en .
ngm:command-query-responsibility-segregation a skos:Concept ;
rdfs:label "Command Query Responsibility Segregation"@en .
ngm:command-query-separation a skos:Concept ;
rdfs:label "Command Query Separation"@en .
ngm:command-r a skos:Concept ;
rdfs:label "Command R"@en .
ngm:command-submission-pattern a skos:Concept ;
rdfs:label "Command Submission Pattern"@en .
ngm:commemoration-event a skos:Concept ;
rdfs:label "Commemoration Event"@en .
ngm:comment-extraction a skos:Concept ;
rdfs:label "Comment Extraction"@en .
ngm:commerce a skos:Concept ;
rdfs:label "Commerce"@en .
ngm:commercial-bank a owl:Class ;
rdfs:comment "A commercial bank is a deposit-taking financial institution that accepts deposits from the public, extends loans and provides payment and related financial services. Through lending against a fraction of its deposits it participates in money creation and the transmission of monetary policy. Commercial banks are central to retail and corporate finance and operate under prudential regulation and capital requirements."@en ;
rdfs:label "Commercial Bank"@en ;
rdfs:subClassOf ngm:monetary-system ;
rdfs:subClassOf _:r4798 ;
rdfs:subClassOf _:r4799 ;
rdfs:subClassOf _:r4800 ;
rdfs:subClassOf _:r4801 ;
vc:contrastsWith ngm:central-bank ;
vc:contrastsWith ngm:shadow-banking ;
vc:dependsOn ngm:liquidity ;
vc:dependsOn ngm:monetary-system ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:lending-protocol ;
vc:hasPart ngm:payment-system ;
vc:implements ngm:monetary-policy-transmission ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:correspondent-banking ;
vc:relatedTo ngm:traditional-banking ;
vc:requires ngm:basel-iii ;
vc:requires ngm:liquidity-coverage-ratio ;
vc:slug "commercial-bank" ;
vc:sourceDomain "finance" ;
vc:supports ngm:liquidity-provision ;
vc:supports ngm:payment-settlement ;
vc:uses ngm:digital-payment-system .
ngm:commercial-bank-deposit a skos:Concept ;
rdfs:label "Commercial Bank Deposit"@en .
ngm:commercial-bank-deposits a skos:Concept ;
rdfs:label "Commercial Bank Deposits"@en .
ngm:commercial-bank-money a skos:Concept ;
rdfs:label "Commercial Bank Money"@en .
ngm:commercial-off-the-shelf-hardware a skos:Concept ;
rdfs:label "Commercial Off The Shelf Hardware"@en .
ngm:commercial-productisation a skos:Concept ;
rdfs:label "Commercial Productisation"@en .
ngm:commercial-profiling a skos:Concept ;
rdfs:label "Commercial Profiling"@en .
ngm:commercial-spyware a skos:Concept ;
rdfs:label "Commercial Spyware"@en .
ngm:commit a owl:Class ;
rdfs:comment "The atomic unit of change in a version control system: an immutable, uniquely identified snapshot of a project's tracked content together with metadata — author, timestamp, descriptive message, and references to one or more parent commits — so that the full set of commits forms a directed acyclic graph recording the project's history; in Git each commit is content-addressed by a cryptographic hash of its tree and parents, making history tamper-evident and enabling branching, merging, reverting, and precise attribution of every line of a codebase."@en ;
rdfs:label "Commit"@en ;
rdfs:subClassOf ngm:data-structure ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:git ;
vc:isPartOf ngm:version-control ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:merkle-tree ;
vc:slug "commit" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:cryptographic-hash ;
vc:uses ngm:directed-acyclic-graph .
ngm:commit-phase a skos:Concept ;
rdfs:label "Commit Phase"@en .
ngm:commit-reveal-scheme a owl:Class ;
rdfs:comment "A commit-reveal scheme is a two-phase cryptographic protocol in which a participant first publishes a binding, hiding commitment to a value (typically a hash of the value plus a nonce) and later reveals the value for verification. The commit phase prevents others from learning or altering the choice, while the reveal phase lets anyone check the value against the earlier commitment. It matters for on-chain voting and auctions because it stops front-running and last-mover advantage by concealing inputs until all parties are bound."@en ;
rdfs:label "Commit-Reveal Scheme"@en ;
rdfs:subClassOf ngm:cryptographic-protocol ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:quadratic-voting ;
vc:slug "commit-reveal-scheme" ;
vc:sourceDomain "blockchain" .
ngm:commitment-scheme a owl:Class ;
rdfs:comment "A commitment scheme is a two-phase cryptographic primitive that allows a party (the committer) to bind itself to a chosen value by producing a short commitment string — analogous to sealing a value in an envelope — that is later opened by revealing the original value and a randomness parameter, with the scheme satisfying two security properties: binding (the committer cannot change the value after committing) and hiding (the commitment reveals nothing about the value before opening). Commitment schemes are foundational building blocks for zero-knowledge proofs, secure multi-party computation, and blockchain protocols."@en ;
rdfs:label "Commitment Scheme"@en ;
rdfs:subClassOf ngm:cryptographic-primitive ;
vc:bridgesTo ngm:smart-contract ;
vc:contrastsWith ngm:digital-signature ;
vc:contrastsWith ngm:encryption-scheme ;
vc:enables ngm:blockchain-anchoring ;
vc:enables ngm:coin-flipping-protocol ;
vc:enables ngm:secure-multi-party-computation ;
vc:enables ngm:verifiable-random-function ;
vc:enables ngm:zero-knowledge-proof ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:kzg-polynomial-commitment ;
vc:implements ngm:pedersen-commitment ;
vc:implements ngm:vector-commitment ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:information-theoretic-security ;
vc:relatedTo ngm:merkle-proof ;
vc:relatedTo ngm:post-quantum-cryptography ;
vc:relatedTo ngm:zero-knowledge ;
vc:requires ngm:randomness ;
vc:slug "commitment-scheme" ;
vc:sourceDomain "security" ;
vc:supports ngm:threshold-signature-scheme ;
vc:supports ngm:zk-snark ;
vc:supports ngm:zk-starks ;
vc:uses ngm:cryptographic-hash-function ;
vc:uses ngm:elliptic-curve-cryptography ;
vc:uses ngm:hash-function ;
vc:uses ngm:merkle-tree .
ngm:commitment-strategy a skos:Concept ;
rdfs:label "Commitment Strategy"@en .
ngm:commitment-transaction a skos:Concept ;
rdfs:label "Commitment Transaction"@en .
ngm:committee-on-payments-and-market-infrastructures a skos:Concept ;
rdfs:label "Committee On Payments And Market Infrastructures"@en .
ngm:committee-rotation a skos:Concept ;
rdfs:label "Committee Rotation"@en .
ngm:commodity-money a owl:Class ;
rdfs:comment "Commodity money is a form of money whose value derives from the intrinsic worth of the physical commodity from which it is made, such as gold, silver, salt or grain. Because the medium of exchange is itself a useful or scarce good, its monetary value is anchored to its commodity value rather than to government decree. Commodity money predates and contrasts with fiat currency, where value rests on trust in an issuing authority."@en ;
rdfs:label "Commodity Money"@en ;
rdfs:subClassOf ngm:money ;
rdfs:subClassOf _:r4802 ;
vc:contrastsWith ngm:cryptocurrency ;
vc:contrastsWith ngm:fiat-currency ;
vc:enables ngm:store-of-value ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:hard-money ;
vc:isPartOf ngm:monetary-system ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:bitcoin ;
vc:relatedTo ngm:finance ;
vc:relatedTo ngm:inflation ;
vc:relatedTo ngm:monetary-policy ;
vc:relatedTo ngm:money ;
vc:requires ngm:value ;
vc:slug "commodity-money" ;
vc:sourceDomain "finance" ;
vc:supports ngm:gold-standard ;
vc:uses ngm:gold .
ngm:commodity-money-model a skos:Concept ;
rdfs:label "Commodity Money Model"@en .
ngm:commodity-regulation a skos:Concept ;
rdfs:label "Commodity Regulation"@en .
ngm:common-crawl a owl:Class ;
rdfs:comment "Common Crawl is a California 501(c)3 non-profit organisation founded in 2008 by Gil Elbaz that maintains a petabyte-scale, freely accessible archive of web crawl data stored on Amazon S3 under the AWS Open Data Sponsorship Programme. The dataset — distributed as WARC, WAT, and WET files — underpins virtually every major open pre-training corpus including C4, FineWeb, RedPajama, Dolma, and DCLM, and has been cited by the Mozilla Foundation (2024) as essential to the emergence of modern generative AI."@en ;
rdfs:label "Common Crawl"@en ;
rdfs:subClassOf ngm:open-data ;
rdfs:subClassOf ngm:training-data ;
rdfs:subClassOf ngm:web-archive ;
rdfs:subClassOf _:r4803 ;
rdfs:subClassOf _:r4804 ;
rdfs:subClassOf _:r4805 ;
rdfs:subClassOf _:r4806 ;
rdfs:subClassOf _:r4807 ;
rdfs:subClassOf _:r4808 ;
vc:contrastsWith ngm:curated-datasets ;
vc:contrastsWith ngm:proprietary-web-index ;
vc:contrastsWith ngm:synthetic-data ;
vc:dependsOn ngm:amazon-s3 ;
vc:dependsOn ngm:apache-nutch ;
vc:dependsOn ngm:cloud-computing ;
vc:dependsOn ngm:fasttext ;
vc:dependsOn ngm:trafilatura ;
vc:enables ngm:foundation-model ;
vc:enables ngm:information-retrieval ;
vc:enables ngm:large-language-models ;
vc:enables ngm:model-training ;
vc:enables ngm:multilingual-nlp ;
vc:enables ngm:natural-language-processing ;
vc:enables ngm:pre-training ;
vc:enables ngm:scaling-laws ;
vc:enables ngm:transfer-learning ;
vc:enables ngm:web-science ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:cdx-index ;
vc:hasPart ngm:columnar-index ;
vc:hasPart ngm:crawl-statistics ;
vc:hasPart ngm:monthly-snapshot ;
vc:hasPart ngm:url-index ;
vc:hasPart ngm:warc-files ;
vc:hasPart ngm:wat-files ;
vc:hasPart ngm:wet-files ;
vc:implements ngm:cdx-protocol ;
vc:implements ngm:language-filtering ;
vc:implements ngm:minhash-deduplication ;
vc:implements ngm:trafilatura-extraction ;
vc:implements ngm:warc-standard ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:bias-in-large-language-models ;
vc:relatedTo ngm:copyright ;
vc:relatedTo ngm:data-governance ;
vc:relatedTo ngm:eu-ai-act-regulatory-instrument ;
vc:relatedTo ngm:gpt ;
vc:relatedTo ngm:information-retrieval ;
vc:relatedTo ngm:language-model ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:multimodal-ai-architecture-ai ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:robotics ;
vc:relatedTo ngm:synthetic-data ;
vc:requires ngm:cloud-storage ;
vc:requires ngm:data-curation ;
vc:requires ngm:data-pipeline ;
vc:requires ngm:deduplication ;
vc:requires ngm:language-identification ;
vc:requires ngm:neural-network-text-tokenisation ;
vc:requires ngm:web-crawl-infrastructure ;
vc:requires ngm:web-scraping ;
vc:slug "common-crawl" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:aws-open-data-sponsorship-programme ;
vc:standardizedBy ngm:iso-28500 ;
vc:supports ngm:bert ;
vc:supports ngm:c4-dataset ;
vc:supports ngm:datacomp-lm ;
vc:supports ngm:deep-learning ;
vc:supports ngm:dolma ;
vc:supports ngm:fineweb ;
vc:supports ngm:gpt ;
vc:supports ngm:gpt-3 ;
vc:supports ngm:meta-llama-model-family ;
vc:supports ngm:olmo ;
vc:supports ngm:redpajama ;
vc:supports ngm:refinedweb ;
vc:supports ngm:scaling-laws ;
vc:supports ngm:transfer-learning ;
vc:uses ngm:amazon-s3 ;
vc:uses ngm:apache-nutch ;
vc:uses ngm:cdx-protocol ;
vc:uses ngm:fasttext ;
vc:uses ngm:trafilatura .
ngm:common-criteria a skos:Concept ;
rdfs:label "Common Criteria"@en .
ngm:common-encryption a skos:Concept ;
rdfs:label "Common Encryption"@en .
ngm:common-equity-tier-1 a skos:Concept ;
rdfs:label "Common Equity Tier 1"@en .
ngm:common-event-format a skos:Concept ;
rdfs:label "Common Event Format"@en .
ngm:common-law a skos:Concept ;
rdfs:label "Common Law"@en .
ngm:common-law-system a skos:Concept ;
rdfs:label "Common Law System"@en .
ngm:common-pool-resources a owl:Class ;
rdfs:comment "Natural or human-made resources that are non-excludable to a defined community but rival in consumption, meaning one actor's use diminishes availability for others. Classic examples include fisheries, groundwater, pastures, and shared spectrum; digital analogues include shared compute pools and open training datasets. Sustainable governance requires institutions that constrain extraction without full privatisation or state control."@en ;
rdfs:label "Common Pool Resources"@en ;
rdfs:subClassOf ngm:resource-management ;
rdfs:subClassOf _:r4809 ;
rdfs:subClassOf _:r4810 ;
vc:enables ngm:community-governance ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:collective-action ;
vc:relatedTo ngm:property-rights ;
vc:relatedTo ngm:public-goods-funding ;
vc:requires ngm:collective-governance ;
vc:requires ngm:polycentric-governance ;
vc:slug "common-pool-resources" ;
vc:sourceDomain "governance" .
ngm:common-reporting-standard a skos:Concept ;
rdfs:label "Common Reporting Standard"@en .
ngm:common-sense-reasoning a owl:Class ;
rdfs:comment "The capacity of an AI system to draw inferences that humans consider obvious from general background knowledge about the physical world, social norms, causality, and everyday object behaviour — without explicit instruction. It encompasses naive physics, naive psychology, temporal reasoning, spatial reasoning, and social cognition grounded in embodied human experience, and is tested against benchmarks including CommonsenseQA, HellaSwag, WinoGrande, and PIQA."@en ;
rdfs:label "Common Sense Reasoning"@en ;
rdfs:subClassOf ngm:automated-reasoning ;
rdfs:subClassOf ngm:natural-language-understanding ;
rdfs:subClassOf ngm:reasoning ;
rdfs:subClassOf _:r4811 ;
rdfs:subClassOf _:r4812 ;
rdfs:subClassOf _:r4813 ;
rdfs:subClassOf _:r4814 ;
rdfs:subClassOf _:r4815 ;
rdfs:subClassOf _:r4816 ;
vc:contrastsWith ngm:description-logic ;
vc:contrastsWith ngm:formal-reasoning ;
vc:contrastsWith ngm:logic-programming ;
vc:contrastsWith ngm:symbolic-ai ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:few-shot-learning ;
vc:dependsOn ngm:foundation-model ;
vc:dependsOn ngm:semantic-network ;
vc:enables ngm:ai-agents ;
vc:enables ngm:conversational-ai ;
vc:enables ngm:embodied-ai ;
vc:enables ngm:natural-language-understanding ;
vc:enables ngm:planning ;
vc:enables ngm:question-answering ;
vc:enables ngm:robotics ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:causal-reasoning ;
vc:hasPart ngm:default-logic ;
vc:hasPart ngm:frame-semantics ;
vc:hasPart ngm:naive-physics ;
vc:hasPart ngm:non-monotonic-reasoning ;
vc:hasPart ngm:spatial-reasoning ;
vc:hasPart ngm:temporal-reasoning ;
vc:hasPart ngm:theory-of-mind ;
vc:implements ngm:chain-of-thought ;
vc:implements ngm:constitutional-ai-training-methodology ;
vc:implements ngm:neural-symbolic-integration ;
vc:implements ngm:neuro-symbolic-ai ;
vc:implements ngm:rlhf ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:ai-alignment ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:cognitive-architecture ;
vc:relatedTo ngm:collective-intelligence ;
vc:relatedTo ngm:evaluation-benchmarks-and-leaderboards ;
vc:relatedTo ngm:expert-systems ;
vc:relatedTo ngm:generative-ai ;
vc:relatedTo ngm:hallucination ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:multi-modal-learning ;
vc:relatedTo ngm:visual-question-answering ;
vc:requires ngm:grounding ;
vc:requires ngm:inference ;
vc:requires ngm:knowledge-base ;
vc:requires ngm:knowledge-representation ;
vc:requires ngm:world-model ;
vc:slug "common-sense-reasoning" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:commonsenseqa ;
vc:standardizedBy ngm:hellaswag ;
vc:standardizedBy ngm:ontology ;
vc:standardizedBy ngm:winogrande ;
vc:supports ngm:ai-safety ;
vc:supports ngm:explainable-ai ;
vc:supports ngm:natural-language-processing ;
vc:uses ngm:chain-of-thought ;
vc:uses ngm:conceptnet ;
vc:uses ngm:fine-tuning ;
vc:uses ngm:knowledge-graph ;
vc:uses ngm:large-language-models ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:retrieval-augmented-generation ;
vc:uses ngm:transfer-learning ;
vc:uses ngm:transformer-architecture ;
vc:uses ngm:wordnet .
ngm:common-spatial-patterns a skos:Concept ;
rdfs:label "Common Spatial Patterns"@en .
ngm:commoncrawl a skos:Concept ;
rdfs:label "Commoncrawl"@en .
ngm:commons a skos:Concept ;
rdfs:label "Commons"@en .
ngm:commons-based-peer-production a owl:Class ;
rdfs:comment "Commons-based peer production is a model of decentralised, collaborative creation in which large numbers of individuals contribute effort to a shared resource without centralised managerial coordination or market-priced compensation, coined by legal scholar Yochai Benkler. Open-source software development is its archetypal example, with contributions coordinated through modular tasks, transparent version control, and reputation rather than employment contracts. The model has since been extended to open encyclopaedias, open data, and blockchain-funded public goods."@en ;
rdfs:label "Commons-Based Peer Production"@en ;
rdfs:subClassOf ngm:digital-commons ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:digital-commons ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "commons-based-peer-production" ;
vc:sourceDomain "distributed-collaboration" .
ngm:commons-governance a owl:Class ;
rdfs:comment "Commons governance is the set of institutions, rules and collective practices through which a community manages a shared resource so that it remains productive and is not depleted by individual self-interest. Drawing on Elinor Ostrom's design principles, it relies on clearly defined boundaries, participatory rule-making, monitoring and graduated sanctions rather than pure markets or central control. In blockchain contexts it is expressed through DAOs and public-goods funding that coordinate stewardship of shared digital infrastructure."@en ;
rdfs:label "Commons Governance"@en ;
rdfs:subClassOf ngm:governance ;
rdfs:subClassOf _:r4817 ;
vc:bridgesTo ngm:collective-action ;
vc:bridgesTo ngm:dao ;
vc:dependsOn ngm:governance-token ;
vc:enables ngm:collective-action ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:isPartOf ngm:governance ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:dao ;
vc:relatedTo ngm:quadratic-funding ;
vc:relatedTo ngm:retroactive-public-goods-funding ;
vc:requires ngm:collective-action ;
vc:slug "commons-governance" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:retroactive-public-goods-funding ;
vc:supports ngm:sustainability ;
vc:uses ngm:dao ;
vc:uses ngm:governance-token .
ngm:commons-stack a owl:Class ;
rdfs:comment "Commons Stack is an initiative providing tools and economic models for funding and governing public goods through token-based communities. It draws on mechanisms such as bonding curves and continuous funding."@en ;
rdfs:label "Commons Stack"@en ;
rdfs:subClassOf ngm:public-goods-funding ;
rdfs:subClassOf _:r4818 ;
vc:bridgesTo ngm:dao ;
vc:enables ngm:quadratic-funding ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:tokenomics ;
vc:slug "commons-stack" ;
vc:sourceDomain "blockchain" .
ngm:commons-stack-abc-spec a skos:Concept ;
rdfs:label "Commons Stack Abc Spec"@en .
ngm:commonsense-reasoning a owl:Class ;
rdfs:comment "Commonsense reasoning is the ability of an artificial system to make plausible inferences about everyday situations using broad background knowledge that humans take for granted. It covers naive physics, folk psychology, temporal causality, social norms, and typical cause-and-effect expectations that are rarely stated explicitly in text. It remains a long-standing challenge because such knowledge is vast, tacit, and context-dependent, requiring both large-scale knowledge resources and flexible defeasible inference mechanisms."@en ;
rdfs:label "Commonsense Reasoning"@en ;
rdfs:subClassOf ngm:automated-reasoning ;
rdfs:subClassOf ngm:reasoning ;
rdfs:subClassOf _:r4819 ;
rdfs:subClassOf _:r4820 ;
rdfs:subClassOf _:r4821 ;
rdfs:subClassOf _:r4822 ;
rdfs:subClassOf _:r4823 ;
rdfs:subClassOf _:r4824 ;
vc:bridgesTo ngm:embodied-ai ;
vc:bridgesTo ngm:world-model ;
vc:contrastsWith ngm:expert-systems ;
vc:contrastsWith ngm:formal-logic ;
vc:contrastsWith ngm:logic-programming ;
vc:contrastsWith ngm:symbolic-reasoning ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:foundation-model ;
vc:dependsOn ngm:knowledge-representation ;
vc:dependsOn ngm:ontology ;
vc:dependsOn ngm:semantic-network ;
vc:enables ngm:ai-agents ;
vc:enables ngm:conversational-ai ;
vc:enables ngm:dialogue-management ;
vc:enables ngm:embodied-ai ;
vc:enables ngm:natural-language-understanding ;
vc:enables ngm:planning ;
vc:enables ngm:question-answering ;
vc:enables ngm:robotics ;
vc:enables ngm:visual-question-answering ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:causal-reasoning ;
vc:hasPart ngm:default-logic ;
vc:hasPart ngm:frame-semantics ;
vc:hasPart ngm:naive-physics ;
vc:hasPart ngm:non-monotonic-reasoning ;
vc:hasPart ngm:spatial-reasoning ;
vc:hasPart ngm:temporal-reasoning ;
vc:hasPart ngm:theory-of-mind ;
vc:implements ngm:chain-of-thought ;
vc:implements ngm:grounding ;
vc:implements ngm:neural-symbolic-integration ;
vc:implements ngm:retrieval-augmented-generation ;
vc:isPartOf ngm:reasoning ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:ai-agent ;
vc:relatedTo ngm:ai-alignment ;
vc:relatedTo ngm:automated-reasoning ;
vc:relatedTo ngm:cognitive-architecture ;
vc:relatedTo ngm:cognitive-science ;
vc:relatedTo ngm:collective-intelligence ;
vc:relatedTo ngm:foundation-model ;
vc:relatedTo ngm:generative-ai ;
vc:relatedTo ngm:hallucination ;
vc:relatedTo ngm:inference-engine ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:multi-modal-learning ;
vc:relatedTo ngm:retrieval-augmented-generation ;
vc:relatedTo ngm:visual-question-answering ;
vc:relatedTo ngm:word-sense-disambiguation ;
vc:requires ngm:grounding ;
vc:requires ngm:inference ;
vc:requires ngm:knowledge-base ;
vc:requires ngm:knowledge-representation ;
vc:requires ngm:world-model ;
vc:slug "commonsense-reasoning" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:commonsenseqa ;
vc:standardizedBy ngm:conceptnet ;
vc:standardizedBy ngm:hellaswag ;
vc:standardizedBy ngm:ontology ;
vc:standardizedBy ngm:piqa ;
vc:standardizedBy ngm:social-iqa ;
vc:standardizedBy ngm:winogrande ;
vc:supports ngm:ai-alignment ;
vc:supports ngm:ai-safety ;
vc:supports ngm:explainable-ai ;
vc:supports ngm:multi-modal-learning ;
vc:supports ngm:natural-language-processing ;
vc:uses ngm:chain-of-thought ;
vc:uses ngm:cognitive-architecture ;
vc:uses ngm:conceptnet ;
vc:uses ngm:description-logic ;
vc:uses ngm:fine-tuning ;
vc:uses ngm:knowledge-graph ;
vc:uses ngm:large-language-model ;
vc:uses ngm:neural-symbolic-integration ;
vc:uses ngm:retrieval-augmented-generation ;
vc:uses ngm:transfer-learning ;
vc:uses ngm:transformer-architecture ;
vc:uses ngm:wordnet .
ngm:commonsenseqa a skos:Concept ;
rdfs:label "Commonsenseqa"@en .
ngm:communication-bus a skos:Concept ;
rdfs:label "Communication Bus"@en .
ngm:communication-capabilities a skos:Concept ;
rdfs:label "Communication Capabilities"@en .
ngm:communication-channel a owl:Class ;
rdfs:comment "A communication channel is the medium or pathway, physical or logical, through which information is transmitted from a sender to a receiver, characterised by properties such as bandwidth, latency, noise and capacity. The concept originates in information theory, where channel capacity bounds the rate at which information can be transmitted reliably. It is a prerequisite for any feedback loop or social interaction that depends on exchanging signals between agents."@en ;
rdfs:label "Communication Channel"@en ;
rdfs:subClassOf ngm:information-theory ;
rdfs:subClassOf _:r4825 ;
vc:enables ngm:feedback-loop ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.55"^^xsd:float ;
vc:relatedTo ngm:social-interaction ;
vc:requires ngm:information-theory ;
vc:slug "communication-channel" ;
vc:sourceDomain "infrastructure" .
ngm:communication-complexity a skos:Concept ;
rdfs:label "Communication Complexity"@en .
ngm:communication-for-locked-in-patients a skos:Concept ;
rdfs:label "Communication For Locked In Patients"@en .
ngm:communication-infrastructure a owl:Class ;
rdfs:comment "The physical and logical substrate — including fibre, wireless networks, data centres, protocols, and switching equipment — that enables the transmission of information between nodes in a networked system. It underpins digital services by providing reliable, low-latency, and high-bandwidth connectivity at scale, from local area networks to global internet backbones."@en ;
rdfs:label "Communication Infrastructure"@en ;
rdfs:subClassOf ngm:ai-infrastructure ;
vc:enables ngm:cloud-computing ;
vc:enables ngm:communication-tools ;
vc:enables ngm:immersive-communication ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:bandwidth-optimization ;
vc:relatedTo ngm:network-communication ;
vc:slug "communication-infrastructure" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:5-g-network ;
vc:uses ngm:communication-protocol .
ngm:communication-interface a owl:Class ;
rdfs:comment "A communication interface is a defined boundary — hardware, software, or logical — through which two or more distinct systems, components, or agents exchange data, commands, or signals according to agreed protocols and encodings. It abstracts the internal implementation details of each participant, exposing only the contract necessary for interoperability, and may operate synchronously or asynchronously across local buses, networks, or inter-process mechanisms. Communication interfaces are fundamental to modular system design, enabling independent development, testing, and replacement of components without disrupting the broader system."@en ;
rdfs:label "Communication Interface"@en ;
rdfs:subClassOf ngm:communication-protocol ;
vc:enables ngm:api-integration ;
vc:enables ngm:distributed-system ;
vc:enables ngm:microservices ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:data-access-interface ;
vc:relatedTo ngm:network-protocol ;
vc:relatedTo ngm:user-interface ;
vc:slug "communication-interface" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:middleware ;
vc:uses ngm:rest-api .
ngm:communication-layer a owl:Class ;
rdfs:comment "The Communication Layer is the stratum that governs the exchange of messages between components or participants. It sits above the Transport Layer that delivers bytes and below the coordination and application strata that rely on conversation. It contains messaging patterns, encoding, addressing, and delivery semantics."@en ;
rdfs:label "Communication Layer"@en ;
rdfs:subClassOf ngm:infra-network-and-comms ;
rdfs:subClassOf ngm:owl-thing ;
rdfs:subClassOf _:r4826 ;
skos:broader ngm:infra-network-and-comms ;
vc:bridgesTo ngm:message-passing ;
vc:bridgesTo ngm:publish-subscribe ;
vc:enables ngm:coordination-layer ;
vc:enables ngm:integration-layer ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:transport-layer ;
vc:slug "communication-layer" ;
vc:sourceDomain "infrastructure" .
ngm:communication-network a owl:Class ;
rdfs:comment "A communication network is an interconnected collection of nodes and links that transports information between endpoints according to shared protocols. Networks are characterised by their topology, switching method, transmission media, and the protocol stack that governs addressing, routing, and error control. They span scales from local wireless links to global packet-switched internetworks, and they provide the substrate on which distributed systems, decentralised ledgers, and immersive media depend. Performance is described by metrics including bandwidth, latency, jitter, and reliability."@en ;
rdfs:label "Communication Network"@en ;
rdfs:subClassOf ngm:communication-infrastructure ;
rdfs:subClassOf _:r4827 ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:transport-layer ;
vc:qualityScore "0.76"^^xsd:float ;
vc:relatedTo ngm:network-performance-metrics ;
vc:slug "communication-network" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:communication-protocol .
ngm:communication-protocol a owl:Class ;
rdfs:comment "Communication protocol defines message formats, transmission rules, addressing schemes, and error-handling procedures that enable robots and computational systems to reliably exchange information over wired or wireless channels."@en ;
rdfs:label "Communication Protocol"@en ;
rdfs:subClassOf ngm:communication-infrastructure ;
rdfs:subClassOf ngm:human-robot-interaction ;
rdfs:subClassOf ngm:information-architecture ;
rdfs:subClassOf _:r4828 ;
rdfs:subClassOf _:r4829 ;
rdfs:subClassOf _:r4830 ;
rdfs:subClassOf _:r4831 ;
rdfs:subClassOf _:r4832 ;
rdfs:subClassOf _:r4833 ;
rdfs:subClassOf _:r4834 ;
rdfs:subClassOf _:r4835 ;
rdfs:subClassOf _:r4836 ;
rdfs:subClassOf _:r4837 ;
rdfs:subClassOf _:r4838 ;
rdfs:subClassOf _:r4839 ;
rdfs:subClassOf _:r4840 ;
rdfs:subClassOf _:r4841 ;
rdfs:subClassOf _:r4842 ;
vc:bridgesTo ngm:ai-agent-system ;
vc:enables ngm:distributed-control ;
vc:enables ngm:sensor-fusion ;
vc:enables ngm:swarm-control ;
vc:enables ngm:teleoperation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:addressing-scheme ;
vc:hasPart ngm:congestion-control ;
vc:hasPart ngm:error-correction ;
vc:hasPart ngm:message-format ;
vc:implements ngm:communication-infrastructure ;
vc:implements ngm:information-architecture ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:bandwidth ;
vc:requires ngm:data-serialization ;
vc:requires ngm:fault-tolerance ;
vc:requires ngm:latency ;
vc:requires ngm:physical-layer ;
vc:requires ngm:synchronisation ;
vc:slug "communication-protocol" ;
vc:sourceDomain "robotics" .
ngm:communication-protocols a owl:Class ;
rdfs:comment "Communication protocols are formal sets of rules, conventions, and standards that specify how data is formatted, transmitted, received, and acknowledged between two or more communicating entities, including computers, devices, and software systems. They define the syntax and semantics of messages, error detection and correction mechanisms, flow control, session management, and the sequencing of exchanges required to achieve reliable information transfer. Protocols operate across layered architectural models such as the OSI Reference Model and the TCP/IP suite, where each layer provides well-defined services to the layer above it while abstracting the implementation details below. Together, these layered agreements enable heterogeneous systems from different vendors and organisations to interoperate reliably across diverse network topologies."@en ;
rdfs:label "Communication Protocols"@en ;
rdfs:subClassOf ngm:network-protocol ;
rdfs:subClassOf _:r4843 ;
rdfs:subClassOf _:r4844 ;
rdfs:subClassOf _:r4845 ;
rdfs:subClassOf _:r4846 ;
rdfs:subClassOf _:r4847 ;
vc:bridgesTo ngm:agent-communication-language ;
vc:bridgesTo ngm:consensus-mechanism ;
vc:bridgesTo ngm:spatial-computing ;
vc:contrastsWith ngm:proprietary-interface ;
vc:enables ngm:distributed-systems ;
vc:enables ngm:interoperability ;
vc:enables ngm:real-time-communication ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:application-layer ;
vc:hasPart ngm:data-link-layer ;
vc:hasPart ngm:session-management ;
vc:hasPart ngm:transport-layer ;
vc:implements ngm:osi-model ;
vc:implements ngm:tcp-ip ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:g-rpc ;
vc:relatedTo ngm:http ;
vc:relatedTo ngm:message-queue ;
vc:relatedTo ngm:mqtt ;
vc:relatedTo ngm:web-socket ;
vc:requires ngm:data-encoding ;
vc:requires ngm:network-infrastructure ;
vc:slug "communication-protocols" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:ieee ;
vc:standardizedBy ngm:ietf ;
vc:standardizedBy ngm:iso ;
vc:supports ngm:cloud-computing ;
vc:supports ngm:edge-computing ;
vc:supports ngm:internet-of-things ;
vc:uses ngm:cryptographic-handshake ;
vc:uses ngm:error-correction ;
vc:uses ngm:flow-control .
ngm:communication-software a owl:Class ;
rdfs:comment "Software applications and platforms that enable real-time interaction, collaboration, and social connection within virtual environments and metaverse spaces, including immersive video conferencing, spatial audio, avatar-based communication, and AI-enhanced translation and transcription services t..."@en ;
rdfs:label "Communication Software"@en ;
rdfs:subClassOf ngm:collaboration-technology ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf _:r4848 ;
rdfs:subClassOf _:r4849 ;
skos:broader ngm:sc-platform-and-environment ;
vc:bridgesTo ngm:telecollaboration ;
vc:enables ngm:real-time-collaboration ;
vc:enables ngm:realtime-collaboration ;
vc:enables ngm:remote-communication ;
vc:enables ngm:virtual-meeting ;
vc:enables ngm:virtual-meetings ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:audio-visual-systems ;
vc:requires ngm:network-infrastructure ;
vc:requires ngm:user-interface ;
vc:slug "communication-software" ;
vc:sourceDomain "spatial-computing" .
ngm:communication-synchronicity-theory a skos:Concept ;
rdfs:label "Communication Synchronicity Theory"@en .
ngm:communication-theory a owl:Class ;
rdfs:comment "Communication Theory provides the theoretical foundations for understanding how information, meaning, and social presence are transmitted and perceived in mediated communication contexts. Key frameworks include media richness theory, social presence theory, and theories of computer-mediated communication that directly inform the design of telecollaboration systems and collaborative technology."@en ;
rdfs:label "Communication Theory"@en ;
rdfs:subClassOf ngm:dc-communication ;
rdfs:subClassOf ngm:telecollaboration ;
rdfs:subClassOf _:r4850 ;
rdfs:subClassOf _:r4851 ;
skos:broader ngm:dc-communication ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:media-richness-theory ;
vc:hasPart ngm:social-presence-theory ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:social-presence ;
vc:relatedTo ngm:video-conferencing ;
vc:slug "communication-theory" ;
vc:sourceDomain "distributed-collaboration" ;
vc:supports ngm:collaborative-systems-modality-technology ;
vc:supports ngm:telecollaboration .
ngm:communication-tools a owl:Class ;
rdfs:comment "Software applications and platforms that enable individuals and teams to exchange information, coordinate activities, and maintain shared context across synchronous and asynchronous channels. They span messaging, video conferencing, email, collaborative documents, and emerging immersive communication modalities, forming the operational backbone of distributed work."@en ;
rdfs:label "Communication Tools"@en ;
rdfs:subClassOf ngm:collaborative-systems-modality-technology ;
vc:enables ngm:asynchronous-collaboration ;
vc:enables ngm:distributed-team-collaboration ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:immersive-communication ;
vc:relatedTo ngm:video-conferencing ;
vc:relatedTo ngm:virtual-workspace ;
vc:slug "communication-tools" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:asynchronous-communication ;
vc:uses ngm:communication-infrastructure .
ngm:communicationeffectiveness a skos:Concept ;
rdfs:label "Communicationeffectiveness"@en .
ngm:community a owl:Class ;
rdfs:comment "A community is a group of people who interact around a shared interest, project, or platform, contributing to its development, governance, or use."@en ;
rdfs:label "community"@en ;
rdfs:subClassOf ngm:dc-communication ;
rdfs:subClassOf ngm:owl-thing ;
skos:broader ngm:dc-communication ;
vc:bridgesTo ngm:governance ;
vc:enables ngm:open-source ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:slug "community" ;
vc:sourceDomain "distributed-collaboration" .
ngm:community-alignment a skos:Concept ;
rdfs:label "Community Alignment"@en .
ngm:community-bonding a skos:Concept ;
rdfs:label "Community Bonding"@en .
ngm:community-consultation a skos:Concept ;
rdfs:label "Community Consultation"@en .
ngm:community-contributions a skos:Concept ;
rdfs:label "Community Contributions"@en .
ngm:community-coordination a owl:Class ;
rdfs:comment "Community coordination is the process by which a distributed group of participants aligns on shared goals, decisions, and resource allocation without centralised command, typically using deliberation, voting, or reputation mechanisms. It underpins governance of open-source projects, decentralised autonomous organisations, and platform communities, where outcomes must reflect dispersed stakeholder input. Effective community coordination balances inclusivity of participation against the decision latency inherent in consensus-seeking."@en ;
rdfs:label "Community Coordination"@en ;
rdfs:subClassOf ngm:collective-action ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:collective-action ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "community-coordination" ;
vc:sourceDomain "governance" .
ngm:community-decision-making a owl:Class ;
rdfs:comment "The processes by which a defined community of stakeholders collectively identifies issues, deliberates alternatives, and reaches binding or advisory decisions about matters affecting shared resources, norms, or direction. It encompasses participatory design, public consultation, deliberative democracy mechanisms, and digital governance platforms that translate community preferences into actionable outcomes."@en ;
rdfs:label "Community Decision Making"@en ;
rdfs:subClassOf ngm:collective-decision-making ;
vc:enables ngm:collective-governance ;
vc:enables ngm:community-governance ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:collective-action ;
vc:relatedTo ngm:conviction-voting ;
vc:relatedTo ngm:dao-governance ;
vc:slug "community-decision-making" ;
vc:sourceDomain "governance" ;
vc:uses ngm:communication-tools ;
vc:uses ngm:coordination-mechanisms .
ngm:community-detection a owl:Class ;
rdfs:comment "Community detection is the computational task of identifying cohesive subgroups, or communities, within a network graph, where nodes within each group are more densely interconnected than they are with nodes in other groups. Algorithms such as the Louvain and Leiden methods optimise a modularity objective to partition the graph, whilst spectral clustering, label propagation, and stochastic block models offer alternative formulations. The problem is formally NP-hard in its general form, making approximation and heuristic approaches the practical norm. Applications span social-network analysis, bioinformatics, knowledge-graph organisation, recommendation systems, and cybersecurity anomaly detection."@en ;
rdfs:label "Community Detection"@en ;
rdfs:subClassOf ngm:clustering ;
rdfs:subClassOf ngm:graph-analysis ;
rdfs:subClassOf ngm:network-analysis ;
rdfs:subClassOf ngm:unsupervised-learning ;
rdfs:subClassOf _:r4852 ;
rdfs:subClassOf _:r4853 ;
rdfs:subClassOf _:r4854 ;
rdfs:subClassOf _:r4855 ;
rdfs:subClassOf _:r4856 ;
vc:bridgesTo ngm:bioinformatics ;
vc:bridgesTo ngm:blockchain-governance ;
vc:bridgesTo ngm:cybersecurity ;
vc:bridgesTo ngm:distributed-systems ;
vc:contrastsWith ngm:density-based-clustering ;
vc:contrastsWith ngm:graph-partitioning ;
vc:contrastsWith ngm:hierarchical-clustering ;
vc:contrastsWith ngm:k-means-clustering ;
vc:dependsOn ngm:graph-theory ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:network-topology ;
vc:enables ngm:anomaly-detection ;
vc:enables ngm:bioinformatics ;
vc:enables ngm:data-aggregation ;
vc:enables ngm:fraud-detection ;
vc:enables ngm:knowledge-graph-embedding ;
vc:enables ngm:protein-interaction-network-analysis ;
vc:enables ngm:recommendation-systems ;
vc:enables ngm:social-network-analysis ;
vc:enables ngm:urban-mobility-analysis ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:bigclam ;
vc:hasPart ngm:clique-percolation-method ;
vc:hasPart ngm:infomap ;
vc:hasPart ngm:label-propagation ;
vc:hasPart ngm:leiden-algorithm ;
vc:hasPart ngm:louvain-algorithm ;
vc:hasPart ngm:modularity-optimisation ;
vc:hasPart ngm:spectral-clustering ;
vc:hasPart ngm:stochastic-block-model ;
vc:hasPart ngm:walktrap-algorithm ;
vc:implements ngm:constant-potts-model ;
vc:implements ngm:minimum-description-length ;
vc:implements ngm:modularity-optimisation ;
vc:implements ngm:stochastic-block-model ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:clustering ;
vc:relatedTo ngm:community-governance-model ;
vc:relatedTo ngm:complex-networks ;
vc:relatedTo ngm:deep-learning ;
vc:relatedTo ngm:distributed-systems ;
vc:relatedTo ngm:graph-database ;
vc:relatedTo ngm:knowledge-graph ;
vc:relatedTo ngm:link-prediction ;
vc:relatedTo ngm:network-topology ;
vc:relatedTo ngm:ontology ;
vc:relatedTo ngm:scale-free-networks ;
vc:relatedTo ngm:self-supervised-learning ;
vc:relatedTo ngm:small-world-networks ;
vc:relatedTo ngm:social-network-analysis ;
vc:requires ngm:adjacency-matrix ;
vc:requires ngm:graph-theory ;
vc:requires ngm:linear-algebra ;
vc:requires ngm:probability-theory ;
vc:slug "community-detection" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:network-analysis ;
vc:supports ngm:blockchain-governance ;
vc:supports ngm:distributed-systems ;
vc:supports ngm:knowledge-graph ;
vc:supports ngm:knowledge-graph-embedding ;
vc:supports ngm:linked-data ;
vc:supports ngm:social-network-analysis ;
vc:uses ngm:contrastive-learning ;
vc:uses ngm:deep-learning ;
vc:uses ngm:graph-attention-network ;
vc:uses ngm:graph-convolutional-network ;
vc:uses ngm:graph-database ;
vc:uses ngm:graph-neural-networks ;
vc:uses ngm:information-theory ;
vc:uses ngm:matrix-factorisation ;
vc:uses ngm:node-embedding ;
vc:uses ngm:random-walk ;
vc:uses ngm:self-supervised-learning ;
vc:uses ngm:temporal-graph-networks ;
vc:uses ngm:vae .
ngm:community-driven-innovation a skos:Concept ;
rdfs:label "Community Driven Innovation"@en .
ngm:community-engagement a skos:Concept ;
rdfs:label "Community Engagement"@en .
ngm:community-extension-ecosystem a skos:Concept ;
rdfs:label "Community Extension Ecosystem"@en .
ngm:community-fine-tuning a skos:Concept ;
rdfs:label "Community Fine Tuning"@en .
ngm:community-governance a owl:Class ;
rdfs:comment "Community Governance refers to the structures, processes, and norms through which a community of stakeholders collectively makes decisions, allocates resources, resolves disputes, and sets rules for shared systems or commons. It encompasses formal mechanisms such as voting protocols, proposal systems, and constitutional rules, as well as informal norms of participation, legitimacy, and accountability. Community governance may be implemented on-chain through smart contracts and token-weighted voting in decentralised autonomous organisations, or off-chain through forum deliberation, elected councils, and working groups in open-source projects, platform cooperatives, and public institutions. The field draws on political science, institutional economics, commons theory, and distributed systems to design governance models that are simultaneously legitimate, efficient, and resistant to capture."@en ;
rdfs:label "Community Governance"@en ;
rdfs:subClassOf ngm:decentralised-governance ;
rdfs:subClassOf _:r4875 ;
rdfs:subClassOf _:r4876 ;
rdfs:subClassOf _:r4877 ;
rdfs:subClassOf _:r4878 ;
rdfs:subClassOf _:r4879 ;
rdfs:subClassOf _:r4880 ;
rdfs:subClassOf _:r4881 ;
rdfs:subClassOf _:r4882 ;
vc:bridgesTo ngm:ai-alignment ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:digital-commons ;
vc:contrastsWith ngm:centralised-control ;
vc:contrastsWith ngm:corporate-governance ;
vc:dependsOn ngm:legitimacy ;
vc:dependsOn ngm:social-contract ;
vc:enables ngm:collective-decision-making ;
vc:enables ngm:commons-stack ;
vc:enables ngm:protocol-upgrade ;
vc:enables ngm:protocol-upgrades ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:dispute-resolution ;
vc:hasPart ngm:proposal-system ;
vc:hasPart ngm:treasury-management ;
vc:hasPart ngm:voting-mechanism ;
vc:isPartOf ngm:decentralised-governance ;
vc:isPartOf ngm:institutional-design ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:metagovernance ;
vc:relatedTo ngm:ostrom-principles ;
vc:relatedTo ngm:rough-consensus ;
vc:requires ngm:accountability-mechanism ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:stakeholder-participation ;
vc:slug "community-governance" ;
vc:sourceDomain "governance" ;
vc:supports ngm:decentralised-autonomous-organisation ;
vc:supports ngm:open-source ;
vc:supports ngm:platform-cooperative ;
vc:uses ngm:multisig-wallet ;
vc:uses ngm:quadratic-voting ;
vc:uses ngm:smart-contract ;
vc:uses ngm:token-weighted-voting .
ngm:community-governance-model a owl:Class ;
rdfs:comment "A participatory decision-making framework that defines rules, voting mechanisms, proposal systems, and dispute resolution processes for virtual communities, enabling democratic and transparent collective governance."@en ;
rdfs:label "Community Governance Model"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:ai-governance-framework ;
rdfs:subClassOf ngm:collective-governance ;
rdfs:subClassOf ngm:commons-governance ;
rdfs:subClassOf ngm:institutional-framework ;
rdfs:subClassOf ngm:participatory-democracy ;
rdfs:subClassOf _:r4857 ;
rdfs:subClassOf _:r4858 ;
rdfs:subClassOf _:r4859 ;
rdfs:subClassOf _:r4860 ;
rdfs:subClassOf _:r4861 ;
rdfs:subClassOf _:r4862 ;
rdfs:subClassOf _:r4863 ;
rdfs:subClassOf _:r4864 ;
rdfs:subClassOf _:r4865 ;
rdfs:subClassOf _:r4866 ;
rdfs:subClassOf _:r4867 ;
rdfs:subClassOf _:r4868 ;
rdfs:subClassOf _:r4869 ;
rdfs:subClassOf _:r4870 ;
rdfs:subClassOf _:r4871 ;
rdfs:subClassOf _:r4872 ;
rdfs:subClassOf _:r4873 ;
rdfs:subClassOf _:r4874 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:ai-governance-framework ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:civic-technology ;
vc:bridgesTo ngm:participatory-democracy ;
vc:contrastsWith ngm:centralised-governance ;
vc:contrastsWith ngm:corporate-governance ;
vc:contrastsWith ngm:representative-democracy ;
vc:contrastsWith ngm:technocracy ;
vc:dependsOn ngm:blockchain ;
vc:dependsOn ngm:coordination-mechanisms ;
vc:dependsOn ngm:reputation-system ;
vc:dependsOn ngm:smart-contract ;
vc:dependsOn ngm:token-economics ;
vc:enables ngm:collective-action ;
vc:enables ngm:collective-decision-making ;
vc:enables ngm:collective-intelligence ;
vc:enables ngm:community-decision-making ;
vc:enables ngm:democratic-participation ;
vc:enables ngm:participatory-budgeting ;
vc:enables ngm:token-economics ;
vc:enables ngm:transparent-governance ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:decision-rules ;
vc:hasPart ngm:delegation-system ;
vc:hasPart ngm:dispute-resolution ;
vc:hasPart ngm:governance-token ;
vc:hasPart ngm:membership-criteria ;
vc:hasPart ngm:proposal-mechanism ;
vc:hasPart ngm:quorum-mechanism ;
vc:hasPart ngm:reputation-system ;
vc:hasPart ngm:timelock-contract ;
vc:hasPart ngm:treasury-management ;
vc:hasPart ngm:voting-system ;
vc:hasPart ngm:voting-systems ;
vc:implements ngm:autonomous-governance ;
vc:implements ngm:conviction-voting ;
vc:implements ngm:dao-governance-standards ;
vc:implements ngm:distributed-governance ;
vc:implements ngm:futarchy ;
vc:implements ngm:polycentric-governance ;
vc:isPartOf ngm:dao ;
vc:isPartOf ngm:digital-public-infrastructure ;
vc:isPartOf ngm:platform-cooperative ;
vc:isPartOf ngm:virtual-community-platform ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:algorithmic-governance ;
vc:relatedTo ngm:commons-governance ;
vc:relatedTo ngm:cross-chain-governance ;
vc:relatedTo ngm:mechanism-design ;
vc:relatedTo ngm:platform-cooperative ;
vc:relatedTo ngm:public-choice-theory ;
vc:relatedTo ngm:social-choice-theory ;
vc:relatedTo ngm:stakeholder-theory ;
vc:requires ngm:access-control ;
vc:requires ngm:blockchain-infrastructure ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:identity-management ;
vc:requires ngm:multisignature-wallets ;
vc:requires ngm:on-chain-voting ;
vc:requires ngm:smart-contract ;
vc:requires ngm:sybil-resistance ;
vc:slug "community-governance-model" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:dao-governance-standards ;
vc:standardizedBy ngm:iso-37001-anti-bribery-management ;
vc:standardizedBy ngm:w3c-decentralized-governance ;
vc:supports ngm:ai-governance-framework ;
vc:supports ngm:algorithmic-governance ;
vc:supports ngm:community-detection ;
vc:supports ngm:digital-public-infrastructure ;
vc:uses ngm:ai-agent-system ;
vc:uses ngm:algorithmic-governance ;
vc:uses ngm:formal-verification ;
vc:uses ngm:liquid-democracy ;
vc:uses ngm:on-chain-voting ;
vc:uses ngm:prediction-markets ;
vc:uses ngm:quadratic-voting ;
vc:uses ngm:soulbound-tokens .
ngm:community-grant-funding a skos:Concept ;
rdfs:label "Community Grant Funding"@en .
ngm:community-growth a skos:Concept ;
rdfs:label "Community Growth"@en .
ngm:community-guidelines-enforcement a skos:Concept ;
rdfs:label "Community Guidelines Enforcement"@en .
ngm:community-knowledge-systems a skos:Concept ;
rdfs:label "Community Knowledge Systems"@en .
ngm:community-led-allocation a skos:Concept ;
rdfs:label "Community Led Allocation"@en .
ngm:community-licensing a skos:Concept ;
rdfs:label "Community Licensing"@en .
ngm:community-management a skos:Concept ;
rdfs:label "Community Management"@en .
ngm:community-membership a skos:Concept ;
rdfs:label "Community Membership"@en .
ngm:community-of-practice a skos:Concept ;
rdfs:label "Community Of Practice"@en .
ngm:community-ownership a skos:Concept ;
rdfs:label "Community Ownership"@en .
ngm:community-participation a skos:Concept ;
rdfs:label "Community Participation"@en .
ngm:community-platform a skos:Concept ;
rdfs:label "Community Platform"@en .
ngm:community-protection a skos:Concept ;
rdfs:label "Community Protection"@en .
ngm:community-standards a owl:Class ;
rdfs:comment "The rules, guidelines, and behavioral norms established for virtual environments and metaverse platforms that govern user conduct, content creation, and social interactions, often enforced through technical standards, governance frameworks, and moderation systems to ensure safety, inclusivity, an..."@en ;
rdfs:label "Community Standards"@en ;
rdfs:subClassOf ngm:platform-governance ;
rdfs:subClassOf ngm:sc-governance-and-safety ;
rdfs:subClassOf _:r4883 ;
rdfs:subClassOf _:r4884 ;
rdfs:subClassOf _:r4885 ;
skos:broader ngm:sc-governance-and-safety ;
vc:bridgesTo ngm:telecollaboration ;
vc:enables ngm:content-moderation ;
vc:enables ngm:trust-building ;
vc:enables ngm:user-safety ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:platform-governance ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:governance-framework ;
vc:requires ngm:moderation-tools ;
vc:requires ngm:reporting-mechanisms ;
vc:slug "community-standards" ;
vc:sourceDomain "spatial-computing" .
ngm:community-storytelling a skos:Concept ;
rdfs:label "Community Storytelling"@en .
ngm:community-structure a skos:Concept ;
rdfs:label "Community Structure"@en .
ngm:community-treasury a skos:Concept ;
rdfs:label "Community Treasury"@en .
ngm:community-trust a skos:Concept ;
rdfs:label "Community Trust"@en .
ngm:community-understanding a skos:Concept ;
rdfs:label "Community Understanding"@en .
ngm:community-voting a skos:Concept ;
rdfs:label "Community Voting"@en .
ngm:communityparticipation a skos:Concept ;
rdfs:label "Communityparticipation"@en .
ngm:commutativity a skos:Concept ;
rdfs:label "Commutativity"@en .
ngm:comp-token a skos:Concept ;
rdfs:label "Comp Token"@en .
ngm:compact-block-relay a skos:Concept ;
rdfs:label "Compact Block Relay"@en .
ngm:companies-act a skos:Concept ;
rdfs:label "Companies Act"@en .
ngm:companies-house a skos:Concept ;
rdfs:label "Companies House"@en .
ngm:companies-house-psc-register a skos:Concept ;
rdfs:label "Companies House Psc Register"@en .
ngm:companion-ai a skos:Concept ;
rdfs:label "Companion AI"@en .
ngm:companion-cognitive-architecture a skos:Concept ;
rdfs:label "Companion Cognitive Architecture"@en .
ngm:companion-robotics a skos:Concept ;
rdfs:label "Companion Robotics"@en .
ngm:comparative-planetology a owl:Class ;
rdfs:label "Comparative Planetology"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:planetary-science ;
vc:slug "comparative-planetology" ;
vc:sourceDomain "space-science-and-systems" .
ngm:comparator a skos:Concept ;
rdfs:label "Comparator"@en .
ngm:comparison-outcome-matrix a skos:Concept ;
rdfs:label "Comparison Outcome Matrix"@en .
ngm:compartmental-model a skos:Concept ;
rdfs:label "Compartmental Model"@en .
ngm:compatibility-process a owl:Class ;
rdfs:comment "Systematic procedure for ensuring that digital assets, applications, and systems conform to common standards, protocols, and specifications to enable seamless exchange, integration, and interoperability across metaverse platforms."@en ;
rdfs:label "Compatibility Process"@en ;
rdfs:subClassOf ngm:compatibility-standards ;
rdfs:subClassOf ngm:sc-standards-and-interop ;
rdfs:subClassOf _:r4886 ;
rdfs:subClassOf _:r4887 ;
rdfs:subClassOf _:r4888 ;
rdfs:subClassOf _:r4889 ;
rdfs:subClassOf _:r4890 ;
rdfs:subClassOf _:r4891 ;
rdfs:subClassOf _:r4892 ;
rdfs:subClassOf _:r4893 ;
skos:broader ngm:sc-standards-and-interop ;
vc:bridgesTo ngm:sensor-input ;
vc:dependsOn ngm:api-specifications ;
vc:dependsOn ngm:data-format-schemas ;
vc:dependsOn ngm:interoperability-framework ;
vc:dependsOn ngm:protocol-definitions ;
vc:dependsOn ngm:technical-standards ;
vc:enables ngm:asset-portability ;
vc:enables ngm:cross-platform-interoperability ;
vc:enables ngm:ecosystem-connectivity ;
vc:enables ngm:standards-compliance ;
vc:enables ngm:system-integration ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:cross-platform-testing ;
vc:hasPart ngm:format-validation ;
vc:hasPart ngm:integration-testing ;
vc:hasPart ngm:interoperability ;
vc:hasPart ngm:protocol-compatibility-checks ;
vc:hasPart ngm:standards-conformance-testing ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:compatibility-standards ;
vc:requires ngm:reference-implementations ;
vc:requires ngm:standards-conformance ;
vc:requires ngm:test-specifications ;
vc:requires ngm:validation-tools ;
vc:slug "compatibility-process" ;
vc:sourceDomain "spatial-computing" .
ngm:compatibility-standards a owl:Class ;
rdfs:comment "Technical specifications and protocols that enable interoperability between different metaverse platforms, virtual environments, and digital systems, including asset formats, communication protocols, and interface standards that allow seamless user experiences across multiple platforms without ve..."@en ;
rdfs:label "Compatibility Standards"@en ;
rdfs:subClassOf ngm:sc-standards-and-interop ;
rdfs:subClassOf ngm:technical-standards ;
rdfs:subClassOf _:r4894 ;
rdfs:subClassOf _:r4895 ;
rdfs:subClassOf _:r4896 ;
rdfs:subClassOf _:r4897 ;
skos:broader ngm:sc-standards-and-interop ;
vc:bridgesTo ngm:sensor-input ;
vc:enables ngm:asset-portability ;
vc:enables ngm:cross-platform-experience ;
vc:enables ngm:interoperability ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:collaboration ;
vc:requires ngm:protocol-development ;
vc:requires ngm:standards-bodies ;
vc:requires ngm:standards-body ;
vc:slug "compatibility-standards" ;
vc:sourceDomain "spatial-computing" .
ngm:compensable-harm a skos:Concept ;
rdfs:label "Compensable Harm"@en .
ngm:compensating-control a skos:Concept ;
rdfs:label "Compensating Control"@en .
ngm:compensation-escalation a skos:Concept ;
rdfs:label "Compensation Escalation"@en .
ngm:compensation-for-victims a skos:Concept ;
rdfs:label "Compensation For Victims"@en .
ngm:compensation-system a skos:Concept ;
rdfs:label "Compensation System"@en .
ngm:competence-development a skos:Concept ;
rdfs:label "Competence Development"@en .
ngm:competency-based-education a owl:Class ;
rdfs:comment "Competency-Based Education is an instructional model that grants progression and credentials based on demonstrated mastery of defined competencies rather than time spent in instruction. Learners advance when they can prove they have met explicit, measurable outcomes, often supported by personalised pacing and frequent assessment. The approach relies on learning analytics and educational technology to track and verify competency attainment."@en ;
rdfs:label "Competency Based Education"@en ;
rdfs:subClassOf ngm:education-technology ;
rdfs:subClassOf ngm:mastery-learning ;
rdfs:subClassOf ngm:personalised-learning ;
rdfs:subClassOf ngm:self-paced-learning ;
rdfs:subClassOf _:r4898 ;
rdfs:subClassOf _:r4899 ;
rdfs:subClassOf _:r4900 ;
rdfs:subClassOf _:r4901 ;
rdfs:subClassOf _:r4902 ;
rdfs:subClassOf _:r4903 ;
rdfs:subClassOf _:r4904 ;
rdfs:subClassOf _:r4905 ;
rdfs:subClassOf _:r4906 ;
rdfs:subClassOf _:r4907 ;
vc:contrastsWith ngm:apprenticeship ;
vc:contrastsWith ngm:time-based-education ;
vc:dependsOn ngm:feedback-loop ;
vc:dependsOn ngm:item-response-theory ;
vc:dependsOn ngm:knowledge-component-model ;
vc:dependsOn ngm:learner-model ;
vc:dependsOn ngm:learning-analytics ;
vc:dependsOn ngm:learning-management-system ;
vc:enables ngm:adaptive-learning ;
vc:enables ngm:digital-badge ;
vc:enables ngm:lifelong-learning ;
vc:enables ngm:micro-credential ;
vc:enables ngm:open-badges ;
vc:enables ngm:personalised-learning ;
vc:enables ngm:self-paced-learning ;
vc:enables ngm:skills-gap-analysis ;
vc:enables ngm:workforce-development ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:competency-framework ;
vc:hasPart ngm:curriculum-design ;
vc:hasPart ngm:feedback-loop ;
vc:hasPart ngm:formative-assessment ;
vc:hasPart ngm:knowledge-component-model ;
vc:hasPart ngm:learner-model ;
vc:hasPart ngm:prior-learning-assessment ;
vc:hasPart ngm:rubric-based-assessment ;
vc:hasPart ngm:summative-assessment ;
vc:implements ngm:bloom-s-taxonomy ;
vc:implements ngm:bloom-taxonomy ;
vc:implements ngm:cognitive-load-theory ;
vc:implements ngm:differentiated-instruction ;
vc:implements ngm:mastery-learning ;
vc:implements ngm:scaffolding ;
vc:implements ngm:zone-of-proximal-development ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:cognitive-load-theory ;
vc:relatedTo ngm:curriculum-learning ;
vc:relatedTo ngm:data-privacy ;
vc:relatedTo ngm:explainable-ai ;
vc:relatedTo ngm:federated-learning ;
vc:relatedTo ngm:gamification ;
vc:relatedTo ngm:higher-education ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:open-educational-resources ;
vc:relatedTo ngm:prior-learning-assessment ;
vc:relatedTo ngm:professional-development ;
vc:relatedTo ngm:zone-of-proximal-development ;
vc:requires ngm:bayesian-knowledge-tracing ;
vc:requires ngm:competency-framework ;
vc:requires ngm:feedback-loop ;
vc:requires ngm:item-response-theory ;
vc:requires ngm:knowledge-component-model ;
vc:requires ngm:learning-analytics ;
vc:requires ngm:learning-management-system ;
vc:slug "competency-based-education" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:bloom-s-taxonomy ;
vc:standardizedBy ngm:credential-framework ;
vc:standardizedBy ngm:open-badges ;
vc:supports ngm:digital-badge ;
vc:supports ngm:higher-education ;
vc:supports ngm:learning-analytics ;
vc:supports ngm:metacognition ;
vc:supports ngm:micro-credential ;
vc:supports ngm:open-badges ;
vc:supports ngm:open-learner-model ;
vc:supports ngm:professional-development ;
vc:uses ngm:bayesian-knowledge-tracing ;
vc:uses ngm:deep-knowledge-tracing ;
vc:uses ngm:gamification ;
vc:uses ngm:intelligent-tutoring-system ;
vc:uses ngm:item-response-theory ;
vc:uses ngm:knowledge-graph ;
vc:uses ngm:large-language-model ;
vc:uses ngm:learning-management-system ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:openedx ;
vc:uses ngm:reinforcement-learning .
ngm:competency-framework a skos:Concept ;
rdfs:label "Competency Framework"@en .
ngm:competing-consumers-pattern a skos:Concept ;
rdfs:label "Competing Consumers Pattern"@en .
ngm:competition-and-markets-authority a skos:Concept ;
rdfs:label "Competition And Markets Authority"@en .
ngm:competition-in-ai a owl:Class ;
rdfs:comment "Competition in AI is the multi-dimensional race dynamics — geopolitical, corporate, research, and regulatory — through which nation-states, hyperscaler enterprises, independent laboratories, open-source collectives, and frontier-model providers compete for technological leadership in artificial i..."@en ;
rdfs:label "Competition in AI"@en ;
rdfs:subClassOf ngm:ai-governance ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:geopolitics ;
rdfs:subClassOf ngm:industrial-competition ;
rdfs:subClassOf ngm:innovation-economics ;
rdfs:subClassOf ngm:technology-race ;
rdfs:subClassOf _:r4908 ;
rdfs:subClassOf _:r4909 ;
rdfs:subClassOf _:r4910 ;
rdfs:subClassOf _:r4911 ;
rdfs:subClassOf _:r4912 ;
rdfs:subClassOf _:r4913 ;
rdfs:subClassOf _:r4914 ;
rdfs:subClassOf _:r4915 ;
rdfs:subClassOf _:r4916 ;
rdfs:subClassOf _:r4917 ;
rdfs:subClassOf _:r4918 ;
rdfs:subClassOf _:r4919 ;
rdfs:subClassOf _:r4920 ;
rdfs:subClassOf _:r4921 ;
rdfs:subClassOf _:r4922 ;
rdfs:subClassOf _:r4923 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:geopolitics ;
vc:contrastsWith ngm:ai-alignment ;
vc:contrastsWith ngm:ai-cooperation ;
vc:contrastsWith ngm:ai-regulation ;
vc:contrastsWith ngm:ai-safety ;
vc:contrastsWith ngm:open-source-ai ;
vc:dependsOn ngm:ai-regulation ;
vc:dependsOn ngm:ai-safety ;
vc:dependsOn ngm:cloud-infrastructure ;
vc:dependsOn ngm:geopolitics ;
vc:dependsOn ngm:large-scale-pretrained-foundation-model ;
vc:dependsOn ngm:semiconductor-industry ;
vc:enables ngm:ai-policy ;
vc:enables ngm:ai-sovereignty ;
vc:enables ngm:economic-competitiveness ;
vc:enables ngm:national-security-advantage ;
vc:enables ngm:technological-leadership ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ai-chips ;
vc:hasPart ngm:ai-investment ;
vc:hasPart ngm:ai-regulation ;
vc:hasPart ngm:ai-safety ;
vc:hasPart ngm:benchmark-evaluation ;
vc:hasPart ngm:compute-access ;
vc:hasPart ngm:export-controls ;
vc:hasPart ngm:frontier-models ;
vc:hasPart ngm:open-source-ai ;
vc:hasPart ngm:talent-concentration ;
vc:implements ngm:antitrust-oversight ;
vc:implements ngm:benchmark-evaluation ;
vc:implements ngm:compute-governance ;
vc:implements ngm:export-controls ;
vc:implements ngm:open-model-licensing ;
vc:implements ngm:responsible-scaling-policy ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:ai-chips ;
vc:relatedTo ngm:ai-investment ;
vc:relatedTo ngm:ai-regulation ;
vc:relatedTo ngm:anthropic ;
vc:relatedTo ngm:frontier-models ;
vc:relatedTo ngm:geopolitics ;
vc:relatedTo ngm:google-ai-technology-corporation-deep-mind ;
vc:relatedTo ngm:meta-ai ;
vc:relatedTo ngm:mistral-ai-open-weight-model-family ;
vc:relatedTo ngm:openai-research-organisation ;
vc:requires ngm:ai-research-talent ;
vc:requires ngm:capital-markets ;
vc:requires ngm:cloud-infrastructure ;
vc:requires ngm:gpu-supply-chain ;
vc:requires ngm:regulatory-framework ;
vc:requires ngm:regulatory-frameworks ;
vc:requires ngm:training-data ;
vc:slug "competition-in-ai" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:ieee-standards-association ;
vc:standardizedBy ngm:iso-iec-jtc1-sc42 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:ai-adoption ;
vc:supports ngm:ai-policy ;
vc:supports ngm:ai-sovereignty ;
vc:supports ngm:innovation-ecosystems ;
vc:supports ngm:national-ai-strategies ;
vc:uses ngm:agentic-ai-systems ;
vc:uses ngm:inference-optimisation ;
vc:uses ngm:large-scale-pretrained-foundation-model ;
vc:uses ngm:mixture-of-experts-architecture ;
vc:uses ngm:reinforcement-learning-from-human-feedback .
ngm:competition-law a skos:Concept ;
rdfs:label "Competition Law"@en .
ngm:competition-policy a skos:Concept ;
rdfs:label "Competition Policy"@en .
ngm:competitive-advantage a skos:Concept ;
rdfs:label "Competitive Advantage"@en .
ngm:competitive-analysis a skos:Concept ;
rdfs:label "Competitive Analysis"@en .
ngm:competitive-intelligence a skos:Concept ;
rdfs:label "Competitive Intelligence"@en .
ngm:competitive-strategy a skos:Concept ;
rdfs:label "Competitive Strategy"@en .
ngm:compile-time-environment a skos:Concept ;
rdfs:label "Compile Time Environment"@en .
ngm:compiler a owl:Class ;
rdfs:comment "A software system that translates source code written in a high-level programming language into a lower-level representation — typically machine code, bytecode, or an intermediate representation — performing lexical analysis, syntactic parsing, semantic checking, optimisation, and code emission in a structured pipeline. Compilers are foundational to software development, enabling human-readable programs to run efficiently on hardware."@en ;
rdfs:label "Compiler"@en ;
rdfs:subClassOf ngm:software-development ;
vc:enables ngm:code-generation ;
vc:enables ngm:runtime-environment ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:onnx-runtime ;
vc:relatedTo ngm:opcodes ;
vc:slug "compiler" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:ai-augmented-software-engineering ;
vc:uses ngm:programming-language .
ngm:compiler-optimisation a skos:Concept ;
rdfs:label "Compiler Optimisation"@en .
ngm:compiler-optimization a owl:Class ;
rdfs:comment "Compiler optimisation is the set of program transformations a compiler applies to make generated code faster, smaller or more energy-efficient while preserving its observable behaviour. It operates over intermediate representations using analyses such as data-flow and dependence analysis to enable transformations like inlining, loop optimisation and dead-code elimination. Optimisation is central to extracting performance from modern hardware without burdening the programmer."@en ;
rdfs:label "Compiler Optimization"@en ;
rdfs:subClassOf ngm:compiler ;
rdfs:subClassOf _:r4924 ;
rdfs:subClassOf _:r4925 ;
vc:dependsOn ngm:bytecode ;
vc:dependsOn ngm:static-analysis ;
vc:enables ngm:optimisation-algorithm ;
vc:enables ngm:performance-optimization ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:profiling ;
vc:hasPart ngm:static-analysis ;
vc:isPartOf ngm:compiler ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:just-in-time-compilation ;
vc:relatedTo ngm:performance-optimization ;
vc:relatedTo ngm:programming-language ;
vc:slug "compiler-optimization" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:programming-language ;
vc:uses ngm:just-in-time-compilation ;
vc:uses ngm:profiling .
ngm:compiler-technology a skos:Concept ;
rdfs:label "Compiler Technology"@en .
ngm:compiler-theory a skos:Concept ;
rdfs:label "Compiler Theory"@en .
ngm:complaint-analytics a skos:Concept ;
rdfs:label "Complaint Analytics"@en .
ngm:complaint-infrastructure a owl:Class ;
rdfs:comment "Complaint infrastructure is the organisational and technical system through which consumers can submit, track, escalate, and resolve grievances against providers, and through which regulators monitor systemic harms. It comprises intake channels, case-management workflows, redress mechanisms, and reporting that feed enforcement and policy. It matters because accessible, auditable complaint handling is a structural requirement of consumer-protection regimes, turning individual grievances into actionable signals and remedies."@en ;
rdfs:label "Complaint Infrastructure"@en ;
rdfs:subClassOf ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:consumer-protection ;
vc:slug "complaint-infrastructure" ;
vc:sourceDomain "governance" .
ngm:complementary-filter a owl:Class ;
rdfs:comment "A complementary filter is a lightweight sensor fusion technique that combines two signals with complementary error characteristics, typically a low-noise but slow-drifting measurement such as an accelerometer and a fast but drift-prone measurement such as a gyroscope, into a single accurate estimate. It applies a low-pass filter to one signal and a high-pass filter to the other before summing them, avoiding the computational cost of a full Kalman filter. Complementary filters are widely used in inertial measurement units for real-time orientation estimation in robotics and spatial-computing applications."@en ;
rdfs:label "Complementary Filter"@en ;
rdfs:subClassOf ngm:sensor-fusion ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:slug "complementary-filter" ;
vc:sourceDomain "robotics" .
ngm:complete-data-log-likelihood a skos:Concept ;
rdfs:label "Complete Data Log Likelihood"@en .
ngm:complete-hri-terms-reference a owl:Class ;
rdfs:comment "A structured terminology reference documenting standardised vocabulary for Human-Robot Interaction (HRI), encompassing communication protocols, behavioural patterns, and engagement modalities. It enables consistent annotation and semantic understanding of interaction contexts across robotic and autonomous systems, aligned with IEEE and ISO standards."@en ;
rdfs:label "COMPLETE_HRI_TERMS_REFERENCE"@en ;
rdfs:subClassOf ngm:human-robot-interaction ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.4"^^xsd:float ;
vc:relatedTo ngm:robotics ;
vc:relatedTo ngm:robotics-domain ;
vc:relatedTo ngm:social-robotics ;
vc:slug "complete-hri-terms-reference" ;
vc:sourceDomain "robotics" ;
vc:supports ngm:human-robot-interaction ;
vc:supports ngm:robotics ;
vc:uses ngm:communication-protocol ;
vc:uses ngm:knowledge-representation .
ngm:complete-ontology-index a owl:Class ;
rdfs:comment "A comprehensive reference catalogue documenting and interconnecting all ontology terms, semantic classifications, and knowledge relationships across multiple domains and knowledge graphs. This index enables discovery, navigation, and semantic reasoning across the entire knowledge base, serving as the master pointer for all class hierarchies and inter-domain relations."@en ;
rdfs:label "COMPLETE ONTOLOGY INDEX"@en ;
rdfs:subClassOf ngm:metaverse-ontology ;
rdfs:subClassOf ngm:sc-standards-and-interop ;
rdfs:subClassOf _:r3786 ;
rdfs:subClassOf _:r3787 ;
skos:broader ngm:sc-standards-and-interop ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:ontology-structure ;
vc:hasPart ngm:owl-class-hierarchy ;
vc:qualityScore "0.4"^^xsd:float ;
vc:slug "complete-ontology-index" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:knowledge-graph ;
vc:supports ngm:ontology ;
vc:uses ngm:knowledge-representation ;
vc:uses ngm:rdf .
ngm:complete-search a skos:Concept ;
rdfs:label "Complete Search"@en .
ngm:completeness a skos:Concept ;
rdfs:label "Completeness"@en .
ngm:completion-report a owl:Class ;
rdfs:comment "A Completion Report is a formal documentation artefact summarising the outcomes, achievements, and validation status of a completed project or work package. It captures deliverables, quality metrics, sign-off records, and governance evidence required for stakeholder communication and project closure in regulated or standards-aligned environments."@en ;
rdfs:label "COMPLETION_REPORT"@en ;
rdfs:subClassOf ngm:sc-content-and-assets ;
skos:broader ngm:sc-content-and-assets ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.4"^^xsd:float ;
vc:relatedTo ngm:governance-framework ;
vc:relatedTo ngm:metaverse ;
vc:relatedTo ngm:metaverse-domain ;
vc:slug "completion-report" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:governance ;
vc:supports ngm:quality-assurance ;
vc:uses ngm:documentation-standards .
ngm:complex a skos:Concept ;
rdfs:label "Complex"@en .
ngm:complex-adaptive-systems a owl:Class ;
rdfs:comment "Complex adaptive systems are systems composed of many interacting agents whose collective behaviour emerges from local interactions and adaptation rather than central control. The agents adjust their behaviour in response to one another and to their environment, producing non-linear dynamics, self-organisation and emergent order. Studied across biology, economics and artificial intelligence, they provide a lens for understanding resilience, learning and unpredictability in distributed populations."@en ;
rdfs:label "Complex Adaptive Systems"@en ;
rdfs:subClassOf ngm:complexity-science ;
rdfs:subClassOf ngm:dynamical-systems-theory ;
rdfs:subClassOf ngm:systems-theory ;
rdfs:subClassOf _:r4926 ;
rdfs:subClassOf _:r4927 ;
rdfs:subClassOf _:r4928 ;
rdfs:subClassOf _:r4929 ;
rdfs:subClassOf _:r4930 ;
rdfs:subClassOf _:r4931 ;
rdfs:subClassOf _:r4932 ;
rdfs:subClassOf _:r4933 ;
vc:bridgesTo ngm:control-theory ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:large-language-models ;
vc:bridgesTo ngm:multi-agent-systems ;
vc:contrastsWith ngm:control-theory ;
vc:contrastsWith ngm:linear-systems ;
vc:dependsOn ngm:dynamical-systems-theory ;
vc:dependsOn ngm:feedback-loop ;
vc:dependsOn ngm:network-science ;
vc:dependsOn ngm:statistical-mechanics ;
vc:enables ngm:collective-behaviour ;
vc:enables ngm:collective-intelligence ;
vc:enables ngm:emergence ;
vc:enables ngm:phase-transition ;
vc:enables ngm:resilience ;
vc:enables ngm:self-organised-criticality ;
vc:enables ngm:stigmergy ;
vc:enables ngm:swarm-intelligence ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:adaptation ;
vc:hasPart ngm:autonomous-agent ;
vc:hasPart ngm:co-evolution ;
vc:hasPart ngm:emergence ;
vc:hasPart ngm:feedback-loop ;
vc:hasPart ngm:non-linear-dynamics ;
vc:hasPart ngm:resilience ;
vc:hasPart ngm:self-organisation ;
vc:implements ngm:agent-based-modelling ;
vc:implements ngm:artificial-life ;
vc:implements ngm:evolutionary-computation ;
vc:implements ngm:swarm-intelligence ;
vc:isPartOf ngm:complexity-science ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:chaos-theory ;
vc:relatedTo ngm:collective-intelligence ;
vc:relatedTo ngm:cybernetics ;
vc:relatedTo ngm:dynamical-systems-theory ;
vc:relatedTo ngm:game-theory ;
vc:relatedTo ngm:network-science ;
vc:relatedTo ngm:network-theory ;
vc:relatedTo ngm:path-dependence ;
vc:relatedTo ngm:phase-transition ;
vc:relatedTo ngm:power-law-distributions ;
vc:relatedTo ngm:scale-free-network ;
vc:relatedTo ngm:self-organised-criticality ;
vc:relatedTo ngm:statistical-mechanics ;
vc:relatedTo ngm:systems-theory ;
vc:requires ngm:feedback-loop ;
vc:requires ngm:information-theory ;
vc:requires ngm:non-linear-dynamics ;
vc:requires ngm:systems-theory ;
vc:slug "complex-adaptive-systems" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:santa-fe-institute ;
vc:supports ngm:agent-based-modelling ;
vc:supports ngm:digital-twin ;
vc:supports ngm:epidemiology ;
vc:supports ngm:multi-agent-reinforcement-learning ;
vc:supports ngm:multi-agent-systems ;
vc:supports ngm:policy-simulation ;
vc:supports ngm:urban-computing ;
vc:uses ngm:cellular-automata ;
vc:uses ngm:evolutionary-computation ;
vc:uses ngm:feedback-loop ;
vc:uses ngm:game-theory ;
vc:uses ngm:genetic-algorithm ;
vc:uses ngm:reinforcement-learning .
ngm:complex-decision-documentation a skos:Concept ;
rdfs:label "Complex Decision Documentation"@en .
ngm:complex-event-processing a owl:Class ;
rdfs:comment "Complex event processing is a paradigm that continuously analyses streams of discrete events to detect meaningful patterns, correlations and derived higher-level events in near real time. Rather than querying stored data after the fact, it evaluates standing pattern queries over moving event streams, recognising temporal sequences, aggregates over windows and absence-of-event conditions. It enables systems to react to situations as they emerge rather than discovering them in later batch analysis."@en ;
rdfs:label "Complex Event Processing"@en ;
rdfs:subClassOf ngm:stream-processing ;
rdfs:subClassOf _:r4934 ;
rdfs:subClassOf _:r4935 ;
vc:bridgesTo ngm:message-queue ;
vc:dependsOn ngm:stream-processing ;
vc:enables ngm:event-driven-architecture ;
vc:enables ngm:real-time-analytics ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:stream-processing ;
vc:isPartOf ngm:event-driven-architecture ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:event-driven-architecture ;
vc:relatedTo ngm:real-time-analytics ;
vc:requires ngm:message-queue ;
vc:slug "complex-event-processing" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:real-time-analytics ;
vc:uses ngm:message-queue ;
vc:uses ngm:stream-processing .
ngm:complex-networks a skos:Concept ;
rdfs:label "Complex Networks"@en .
ngm:complex-pattern-recognition a skos:Concept ;
rdfs:label "Complex Pattern Recognition"@en .
ngm:complex-systems a owl:Class ;
rdfs:comment "Systems composed of many interacting components whose collective behaviour cannot be simply inferred from the behaviour of the individual parts; characterised by nonlinearity, emergence, self-organisation, and feedback dynamics across scales."@en ;
rdfs:label "Complex Systems"@en ;
rdfs:subClassOf ngm:owl-thing ;
rdfs:subClassOf ngm:systems-theory ;
rdfs:subClassOf _:r4936 ;
rdfs:subClassOf _:r4937 ;
rdfs:subClassOf _:r4938 ;
rdfs:subClassOf _:r4939 ;
rdfs:subClassOf _:r4940 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:distributed-systems ;
vc:bridgesTo ngm:ecology ;
vc:bridgesTo ngm:economics ;
vc:bridgesTo ngm:feedback-loop ;
vc:dependsOn ngm:information-theory ;
vc:dependsOn ngm:statistical-mechanics ;
vc:enables ngm:emergence ;
vc:enables ngm:resilience-engineering ;
vc:enables ngm:self-organisation ;
vc:enables ngm:simulation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:agent-based-models ;
vc:hasPart ngm:feedback-loop ;
vc:hasPart ngm:phase-transition ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:chaos-theory ;
vc:relatedTo ngm:cybernetics ;
vc:requires ngm:dynamical-systems-theory ;
vc:requires ngm:network-theory ;
vc:slug "complex-systems" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:adaptive-systems ;
vc:supports ngm:swarm-intelligence .
ngm:complex-systems-science a skos:Concept ;
rdfs:label "Complex Systems Science"@en .
ngm:complex-systems-society a skos:Concept ;
rdfs:label "Complex Systems Society"@en .
ngm:complexity-modelling a skos:Concept ;
rdfs:label "Complexity Modelling"@en .
ngm:complexity-penalisation a skos:Concept ;
rdfs:label "Complexity Penalisation"@en .
ngm:complexity-science a owl:Class ;
rdfs:comment "Complexity science is the interdisciplinary study of complex adaptive systems composed of many interacting components whose collective behaviour cannot be reduced to that of the individual parts. It investigates emergence, self-organisation, networks, nonlinear dynamics, and adaptation across physical, biological, social, and economic systems. It matters because it provides a unifying lens and a set of computational and analytical tools for understanding phenomena such as markets, ecosystems, and epidemics that defy reductionist explanation."@en ;
rdfs:label "Complexity Science"@en ;
rdfs:subClassOf ngm:ai-research-area ;
skos:broader ngm:ai-research-area ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:economics ;
vc:relatedTo ngm:emergence ;
vc:slug "complexity-science" ;
vc:sourceDomain "data" .
ngm:compliance a owl:Class ;
rdfs:comment "Compliance is the organisational practice of adhering to laws, regulations, standards, and internal policies that govern the conduct of systems, processes, and personnel. It encompasses the identification of applicable obligations, the implementation of controls to satisfy them, continuous monitoring to verify ongoing conformance, and documented evidence to demonstrate that conformance to internal and external stakeholders. Modern compliance programmes span regulatory domains including data protection, financial services, cybersecurity, environmental obligations, and increasingly AI-specific requirements."@en ;
rdfs:label "Compliance"@en ;
rdfs:subClassOf ngm:governance ;
rdfs:subClassOf _:r4993 ;
rdfs:subClassOf _:r4994 ;
rdfs:subClassOf _:r4995 ;
rdfs:subClassOf _:r4996 ;
rdfs:subClassOf _:r4997 ;
rdfs:subClassOf _:r4998 ;
vc:bridgesTo ngm:ai-governance ;
vc:bridgesTo ngm:smart-contract ;
vc:contrastsWith ngm:non-conformance ;
vc:dependsOn ngm:data-protection ;
vc:dependsOn ngm:governance-framework ;
vc:enables ngm:accountability ;
vc:enables ngm:regulatory-approval ;
vc:enables ngm:trust ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:compliance-framework ;
vc:hasPart ngm:compliance-monitoring ;
vc:hasPart ngm:control ;
vc:implements ngm:regulation ;
vc:implements ngm:standard ;
vc:isPartOf ngm:governance ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:certification ;
vc:relatedTo ngm:ethics ;
vc:relatedTo ngm:reporting ;
vc:requires ngm:audit ;
vc:requires ngm:audit-trail ;
vc:requires ngm:policy ;
vc:requires ngm:risk-assessment ;
vc:slug "compliance" ;
vc:sourceDomain "governance" ;
vc:supports ngm:data-governance ;
vc:supports ngm:risk-management ;
vc:uses ngm:grc-platform ;
vc:uses ngm:identity-and-access-management .
ngm:compliance-and-governance a skos:Concept ;
rdfs:label "Compliance And Governance"@en .
ngm:compliance-architecture a skos:Concept ;
rdfs:label "Compliance Architecture"@en .
ngm:compliance-assurance a skos:Concept ;
rdfs:label "Compliance Assurance"@en .
ngm:compliance-audit a skos:Concept ;
rdfs:label "Compliance Audit"@en .
ngm:compliance-audit-trail a owl:Class ;
rdfs:comment "Immutable record system demonstrating adherence to policies and regulations through cryptographically sealed logs of compliance verification activities and evidence."@en ;
rdfs:label "Compliance Audit Trail"@en ;
rdfs:subClassOf ngm:accountability ;
rdfs:subClassOf ngm:ai-governance ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:data-governance ;
rdfs:subClassOf _:r4941 ;
rdfs:subClassOf _:r4942 ;
rdfs:subClassOf _:r4943 ;
rdfs:subClassOf _:r4944 ;
rdfs:subClassOf _:r4945 ;
rdfs:subClassOf _:r4946 ;
rdfs:subClassOf _:r4947 ;
rdfs:subClassOf _:r4948 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:smart-contract ;
vc:bridgesTo ngm:zero-knowledge-proof ;
vc:dependsOn ngm:audit-automation ;
vc:dependsOn ngm:data-governance ;
vc:dependsOn ngm:data-provenance ;
vc:dependsOn ngm:regulatory-framework ;
vc:dependsOn ngm:risk-management ;
vc:enables ngm:accountability ;
vc:enables ngm:algorithmic-auditing ;
vc:enables ngm:compliance-verification ;
vc:enables ngm:explainability ;
vc:enables ngm:human-oversight ;
vc:enables ngm:regulatory-reporting ;
vc:enables ngm:risk-assessment ;
vc:enables ngm:transparency ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:compliance-event-log ;
vc:hasPart ngm:digital-signature ;
vc:hasPart ngm:policy-document ;
vc:hasPart ngm:regulatory-evidence ;
vc:hasPart ngm:timestamp ;
vc:hasPart ngm:verification-record ;
vc:implements ngm:eu-ai-act-regulatory-instrument ;
vc:implements ngm:iso-37301 ;
vc:implements ngm:iso-iec-42001 ;
vc:implements ngm:nist-ai-rmf ;
vc:isPartOf ngm:ai-governance ;
vc:isPartOf ngm:compliance-management ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:ai-model-card ;
vc:relatedTo ngm:eu-ai-act-regulatory-instrument ;
vc:relatedTo ngm:explainability ;
vc:relatedTo ngm:gdpr ;
vc:relatedTo ngm:mifid-ii ;
vc:relatedTo ngm:mlops ;
vc:relatedTo ngm:model-cards ;
vc:relatedTo ngm:operational-resilience ;
vc:relatedTo ngm:responsible-ai ;
vc:requires ngm:access-control ;
vc:requires ngm:cryptographic-hash ;
vc:requires ngm:data-provenance ;
vc:requires ngm:immutable-storage ;
vc:requires ngm:policy-engine ;
vc:requires ngm:timestamp ;
vc:slug "compliance-audit-trail" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:iso-37301 ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:supports ngm:ai-governance ;
vc:supports ngm:change-management ;
vc:supports ngm:compliance-verification ;
vc:supports ngm:incident-management ;
vc:supports ngm:regulatory-reporting ;
vc:supports ngm:responsible-ai .
ngm:compliance-auditing a skos:Concept ;
rdfs:label "Compliance Auditing"@en .
ngm:compliance-automation a owl:Class ;
rdfs:comment "Compliance automation is the use of software systems to continuously monitor, enforce, and evidence adherence to regulatory and policy requirements, replacing manual audit-driven checks with machine-executable controls. It typically encodes rules as code, evaluates them against live system state or transaction streams, and generates auditable records without human intervention. It reduces the cost and latency of regulatory adherence while improving consistency across large organisations."@en ;
rdfs:label "Compliance Automation"@en ;
rdfs:subClassOf ngm:regulatory-compliance ;
rdfs:subClassOf _:r4949 ;
vc:enables ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.55"^^xsd:float ;
vc:requires ngm:governance ;
vc:slug "compliance-automation" ;
vc:sourceDomain "governance" .
ngm:compliance-cap-and-trade-registry a skos:Concept ;
rdfs:label "Compliance Cap And Trade Registry"@en .
ngm:compliance-carbon-market a owl:Class ;
rdfs:comment "A compliance carbon market is a regulated market in which emitters covered by a mandatory cap must surrender allowances or credits equal to their emissions, created under law to enforce climate targets. Prices are set by the supply of capped allowances and demand from regulated entities, creating a financial incentive to abate. It stands in contrast to voluntary carbon markets, where participation and credit purchase are discretionary."@en ;
rdfs:label "Compliance Carbon Market"@en ;
rdfs:subClassOf ngm:regulatory-framework ;
rdfs:subClassOf _:r4950 ;
rdfs:subClassOf _:r4951 ;
rdfs:subClassOf _:r4952 ;
rdfs:subClassOf _:r4953 ;
vc:contrastsWith ngm:voluntary-carbon-market ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:carbon-credits ;
vc:hasPart ngm:carbon-registry ;
vc:implements ngm:carbon-tax ;
vc:implements ngm:climate-policy ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:climate-finance ;
vc:relatedTo ngm:green-finance ;
vc:requires ngm:carbon-accounting ;
vc:requires ngm:regulatory-compliance ;
vc:slug "compliance-carbon-market" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:kyoto-protocol ;
vc:standardizedBy ngm:paris-agreement ;
vc:supports ngm:carbon-offset ;
vc:uses ngm:verification .
ngm:compliance-control a owl:Class ;
rdfs:comment "Compliance Control is an enterprise governance mechanism comprising the policies, procedures, automated tests, and continuous monitoring activities that an organisation deploys to demonstrate, document, and enforce adherence to regulatory obligations, internal standards, and contractual requireme..."@en ;
rdfs:label "Compliance Control"@en ;
rdfs:subClassOf ngm:corporate-governance ;
rdfs:subClassOf ngm:enterprise-risk-management ;
rdfs:subClassOf ngm:information-security-management ;
rdfs:subClassOf ngm:infra-legal-and-regulatory ;
rdfs:subClassOf ngm:infra-security-and-identity ;
rdfs:subClassOf ngm:internal-control ;
rdfs:subClassOf ngm:regulatory-compliance ;
rdfs:subClassOf ngm:risk-management ;
rdfs:subClassOf _:r4954 ;
rdfs:subClassOf _:r4955 ;
rdfs:subClassOf _:r4956 ;
rdfs:subClassOf _:r4957 ;
rdfs:subClassOf _:r4958 ;
rdfs:subClassOf _:r4959 ;
rdfs:subClassOf _:r4960 ;
skos:broader ngm:infra-legal-and-regulatory ;
skos:broader ngm:infra-security-and-identity ;
vc:bridgesTo ngm:enterprise-risk-management ;
vc:contrastsWith ngm:automated-control ;
vc:contrastsWith ngm:compensating-control ;
vc:contrastsWith ngm:corrective-control ;
vc:contrastsWith ngm:detective-control ;
vc:contrastsWith ngm:manual-control ;
vc:contrastsWith ngm:preventive-control ;
vc:dependsOn ngm:business-process-management ;
vc:dependsOn ngm:data-governance ;
vc:dependsOn ngm:enterprise-risk-management ;
vc:dependsOn ngm:identity-and-access-management ;
vc:dependsOn ngm:it-general-controls ;
vc:dependsOn ngm:operational-risk-framework ;
vc:dependsOn ngm:policy-management ;
vc:enables ngm:basel-iii ;
vc:enables ngm:dora-compliance ;
vc:enables ngm:fca-consumer-duty ;
vc:enables ngm:gdpr ;
vc:enables ngm:iso-27001 ;
vc:enables ngm:regulatory-assurance ;
vc:enables ngm:smcr-compliance ;
vc:enables ngm:soc-2-type-ii-attestation ;
vc:enables ngm:sox-compliance ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:control-activity ;
vc:hasPart ngm:control-evidence ;
vc:hasPart ngm:control-library ;
vc:hasPart ngm:control-maturity-assessment ;
vc:hasPart ngm:control-objective ;
vc:hasPart ngm:control-owner ;
vc:hasPart ngm:control-testing ;
vc:hasPart ngm:exception-management ;
vc:hasPart ngm:remediation-plan ;
vc:hasPart ngm:segregation-of-duties ;
vc:implements ngm:continuous-controls-monitoring ;
vc:implements ngm:control-framework ;
vc:implements ngm:grc-platform ;
vc:implements ngm:iso-27001 ;
vc:implements ngm:iso-27701 ;
vc:implements ngm:nist-cybersecurity-framework ;
vc:implements ngm:regtech-automation ;
vc:implements ngm:three-lines-of-defence ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:access-control-system ;
vc:relatedTo ngm:ai-risks ;
vc:relatedTo ngm:algorithmic-bias-and-variance ;
vc:relatedTo ngm:aml-kyc-compliance ;
vc:relatedTo ngm:audit ;
vc:relatedTo ngm:continuous-controls-monitoring ;
vc:relatedTo ngm:corporate-governance ;
vc:relatedTo ngm:coso ;
vc:relatedTo ngm:cyber-risk-management ;
vc:relatedTo ngm:data-governance ;
vc:relatedTo ngm:data-loss-prevention ;
vc:relatedTo ngm:enterprise-risk-management ;
vc:relatedTo ngm:esg-reporting ;
vc:relatedTo ngm:fca-consumer-duty ;
vc:relatedTo ngm:grc-platform ;
vc:relatedTo ngm:identity-and-access-management ;
vc:relatedTo ngm:iso-27001 ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:nist-cybersecurity-framework ;
vc:relatedTo ngm:onetrust ;
vc:relatedTo ngm:operational-risk ;
vc:relatedTo ngm:regtech-automation ;
vc:relatedTo ngm:regulatory-technology ;
vc:relatedTo ngm:service-now ;
vc:relatedTo ngm:siem ;
vc:relatedTo ngm:sox-compliance ;
vc:relatedTo ngm:third-party-risk-management ;
vc:relatedTo ngm:three-lines-of-defence ;
vc:requires ngm:audit-trail ;
vc:requires ngm:business-process-management ;
vc:requires ngm:control-documentation ;
vc:requires ngm:it-general-controls ;
vc:requires ngm:management-oversight ;
vc:requires ngm:policy-framework ;
vc:requires ngm:regulatory-mapping ;
vc:requires ngm:risk-assessment ;
vc:requires ngm:segregation-of-duties ;
vc:slug "compliance-control" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:basel-committee-on-banking-supervision ;
vc:standardizedBy ngm:coso ;
vc:standardizedBy ngm:european-parliament ;
vc:standardizedBy ngm:fca ;
vc:standardizedBy ngm:iia ;
vc:standardizedBy ngm:isaca ;
vc:standardizedBy ngm:iso-iec ;
vc:standardizedBy ngm:nist ;
vc:standardizedBy ngm:pcaob ;
vc:standardizedBy ngm:pra ;
vc:standardizedBy ngm:sec ;
vc:supports ngm:aml-kyc-compliance ;
vc:supports ngm:cyber-risk-management ;
vc:supports ngm:data-protection ;
vc:supports ngm:esg-reporting ;
vc:supports ngm:financial-reporting-integrity ;
vc:supports ngm:operational-resilience ;
vc:supports ngm:risk-management ;
vc:supports ngm:third-party-risk-management ;
vc:uses ngm:audit ;
vc:uses ngm:data-loss-prevention ;
vc:uses ngm:grc-software ;
vc:uses ngm:large-language-models ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:policy-management-platform ;
vc:uses ngm:siem ;
vc:uses ngm:workflow-automation .
ngm:compliance-criteria a skos:Concept ;
rdfs:label "Compliance Criteria"@en .
ngm:compliance-dashboard a owl:Class ;
rdfs:comment "A visual interface and monitoring system that provides real-time visibility into regulatory compliance status, risk metrics, and audit trails across blockchain networks and digital platforms, enabling organizations to track adherence to legal requirements, detect anomalies, and demonstrate compliance to regulators through transparent reporting."@en ;
rdfs:label "Compliance Dashboard"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:regulatory-technology ;
rdfs:subClassOf _:r4961 ;
rdfs:subClassOf _:r4962 ;
rdfs:subClassOf _:r4963 ;
rdfs:subClassOf _:r4964 ;
rdfs:subClassOf _:r4965 ;
rdfs:subClassOf _:r4966 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:security ;
vc:contrastsWith ngm:audit ;
vc:dependsOn ngm:data-governance ;
vc:dependsOn ngm:identity-management ;
vc:dependsOn ngm:smart-contract ;
vc:enables ngm:aml-kyc-compliance ;
vc:enables ngm:kyc ;
vc:enables ngm:real-time-monitoring ;
vc:enables ngm:regulatory-reporting ;
vc:enables ngm:risk-visualization ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:audit-trail ;
vc:hasPart ngm:notification-system ;
vc:implements ngm:regulatory-framework ;
vc:implements ngm:risk-management ;
vc:isPartOf ngm:regulatory-technology ;
vc:qualityScore "0.68"^^xsd:float ;
vc:relatedTo ngm:transaction-monitoring ;
vc:requires ngm:analytics-engine ;
vc:requires ngm:blockchain-network ;
vc:requires ngm:data-integration ;
vc:requires ngm:data-pipeline ;
vc:slug "compliance-dashboard" ;
vc:sourceDomain "governance" ;
vc:supports ngm:financial-compliance ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:zero-knowledge-proof .
ngm:compliance-documentation a skos:Concept ;
rdfs:label "Compliance Documentation"@en .
ngm:compliance-enforcement a skos:Concept ;
rdfs:label "Compliance Enforcement"@en .
ngm:compliance-event-log a skos:Concept ;
rdfs:label "Compliance Event Log"@en .
ngm:compliance-evidence a owl:Class ;
rdfs:comment "Compliance evidence is the documented, verifiable record that an organisation or process meets a regulatory, contractual, or standards-based requirement. It includes artefacts such as audit logs, sensor readings, certificates, attestations, and chain-of-custody records, ideally tamper-evident and timestamped. It matters because it converts asserted compliance into auditable proof, supporting attestations to regulators and customers and enabling automated verification in areas such as cold-chain integrity and supply-chain assurance."@en ;
rdfs:label "Compliance Evidence"@en ;
rdfs:subClassOf ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:cold-chain-monitoring ;
vc:relatedTo ngm:evidence-collection ;
vc:slug "compliance-evidence" ;
vc:sourceDomain "governance" .
ngm:compliance-framework a owl:Class ;
rdfs:comment "A Compliance Framework is a structured set of policies, controls, procedures, and audit mechanisms that organisations implement to satisfy regulatory obligations and industry standards governing the design, development, and deployment of systems — especially AI and data-intensive systems. It systematically maps external legal requirements (such as the EU AI Act, GDPR, ISO 42001, and NIST AI RMF) onto internal risk registers, technical documentation, accountability chains, and monitoring pipelines. A compliance framework defines the scope of applicability, assigns ownership of controls, establishes evidence-collection workflows, and mandates review cycles so that organisations can continuously demonstrate conformance to auditors, regulators, and stakeholders. It bridges governance intent with operational practice by providing a traceable path from regulatory obligation through implemented control to verified outcome."@en ;
rdfs:label "Compliance Framework"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf _:r4967 ;
rdfs:subClassOf _:r4968 ;
rdfs:subClassOf _:r4969 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:explainable-ai ;
vc:bridgesTo ngm:smart-contract ;
vc:contrastsWith ngm:voluntary-guidelines ;
vc:enables ngm:accountability ;
vc:enables ngm:organisational-trust ;
vc:enables ngm:regulatory-compliance ;
vc:enables ngm:transparency ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:eu-ai-act-regulatory-instrument ;
vc:implements ngm:gdpr ;
vc:implements ngm:nist-ai-rmf ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:ai-model-card ;
vc:relatedTo ngm:algorithmic-impact-assessment ;
vc:relatedTo ngm:corporate-governance ;
vc:requires ngm:audit-trail ;
vc:requires ngm:data-governance ;
vc:requires ngm:policy-management ;
vc:requires ngm:risk-management ;
vc:slug "compliance-framework" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:iso-27001 ;
vc:standardizedBy ngm:iso-42001 ;
vc:standardizedBy ngm:nist-cybersecurity-framework ;
vc:supports ngm:ai-ethics ;
vc:supports ngm:information-security ;
vc:supports ngm:privacy-engineering ;
vc:supports ngm:responsible-ai .
ngm:compliance-layer a owl:Class ;
rdfs:comment "The Compliance Layer is the cross-cutting stratum that checks system behaviour against external obligations such as law, regulation, and contractual terms. It sits above the Policy Layer, consuming its enforcement records, and reports to the Regulatory and Governance Layers. It contains controls, evidence collection, audit trails, and conformance assessments rather than the operations being assessed."@en ;
rdfs:label "Compliance Layer"@en ;
rdfs:subClassOf ngm:infra-legal-and-regulatory ;
rdfs:subClassOf ngm:owl-thing ;
rdfs:subClassOf _:r4970 ;
rdfs:subClassOf _:r4971 ;
skos:broader ngm:infra-legal-and-regulatory ;
vc:bridgesTo ngm:audit ;
vc:bridgesTo ngm:risk-management ;
vc:enables ngm:institutional-layer ;
vc:enables ngm:regulatory-layer ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:governance-layer ;
vc:requires ngm:policy-layer ;
vc:slug "compliance-layer" ;
vc:sourceDomain "governance" .
ngm:compliance-management a owl:Class ;
rdfs:comment "Compliance Management is the systematic process by which organisations identify, assess, implement, and monitor adherence to applicable laws, regulations, standards, and internal policies. It encompasses the full lifecycle of obligation tracking, control design, evidence collection, and reporting to demonstrate that operational activities conform to required norms."@en ;
rdfs:label "Compliance Management"@en ;
rdfs:subClassOf ngm:governance-framework ;
rdfs:subClassOf _:r4972 ;
vc:dependsOn ngm:risk-management ;
vc:enables ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:data-governance ;
vc:requires ngm:audit-trail ;
vc:slug "compliance-management" ;
vc:sourceDomain "governance" ;
vc:uses ngm:policy-enforcement .
ngm:compliance-metric a skos:Concept ;
rdfs:label "Compliance Metric"@en .
ngm:compliance-monitoring a owl:Class ;
rdfs:comment "Compliance Monitoring is the continuous, automated oversight of systems, processes, people, and data flows to verify ongoing adherence to applicable regulatory requirements, internal policies, contractual obligations, and technical standards across the full operational surface area of an organisa..."@en ;
rdfs:label "Compliance Monitoring"@en ;
rdfs:subClassOf ngm:automated-compliance ;
rdfs:subClassOf ngm:continuous-control-monitoring ;
rdfs:subClassOf ngm:governance-risk-compliance ;
rdfs:subClassOf ngm:infra-legal-and-regulatory ;
rdfs:subClassOf ngm:regulatory-technology ;
rdfs:subClassOf ngm:risk-management ;
rdfs:subClassOf _:r4973 ;
rdfs:subClassOf _:r4974 ;
rdfs:subClassOf _:r4975 ;
rdfs:subClassOf _:r4976 ;
rdfs:subClassOf _:r4977 ;
rdfs:subClassOf _:r4978 ;
rdfs:subClassOf _:r4979 ;
rdfs:subClassOf _:r4980 ;
rdfs:subClassOf _:r4981 ;
rdfs:subClassOf _:r4982 ;
rdfs:subClassOf _:r4983 ;
rdfs:subClassOf _:r4984 ;
skos:broader ngm:infra-legal-and-regulatory ;
vc:bridgesTo ngm:automated-compliance ;
vc:contrastsWith ngm:checkbox-compliance ;
vc:contrastsWith ngm:manual-review ;
vc:contrastsWith ngm:periodic-auditing ;
vc:contrastsWith ngm:reactive-incident-response ;
vc:dependsOn ngm:cloud-infrastructure ;
vc:dependsOn ngm:cryptographic-hash-function ;
vc:dependsOn ngm:graph-databases ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:natural-language-processing ;
vc:dependsOn ngm:stream-processing ;
vc:enables ngm:aml ;
vc:enables ngm:financial-regulation ;
vc:enables ngm:fraud-detection ;
vc:enables ngm:gdpr ;
vc:enables ngm:iso-27001 ;
vc:enables ngm:sanctions-screening ;
vc:enables ngm:soc-2-compliance ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:alert-management ;
vc:hasPart ngm:audit-trail ;
vc:hasPart ngm:case-management-system ;
vc:hasPart ngm:evidence-repository ;
vc:hasPart ngm:policy-engine ;
vc:hasPart ngm:regulatory-reporting-module ;
vc:hasPart ngm:risk-scoring-engine ;
vc:hasPart ngm:transaction-monitoring ;
vc:implements ngm:anomaly-detection ;
vc:implements ngm:continuous-assurance ;
vc:implements ngm:explainable-ai ;
vc:implements ngm:federated-learning ;
vc:implements ngm:graph-analytics ;
vc:implements ngm:policy-as-code ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:aml ;
vc:relatedTo ngm:digital-operational-resilience ;
vc:relatedTo ngm:fraud-detection ;
vc:relatedTo ngm:governance-risk-compliance ;
vc:relatedTo ngm:kyc ;
vc:relatedTo ngm:regulatory-reporting ;
vc:relatedTo ngm:security-operations ;
vc:requires ngm:data-governance ;
vc:requires ngm:identity-and-access-management ;
vc:requires ngm:kyc ;
vc:requires ngm:policy-enforcement ;
vc:requires ngm:regulatory-framework ;
vc:requires ngm:security-information-and-event-management ;
vc:slug "compliance-monitoring" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:basel-committee-on-banking-supervision ;
vc:standardizedBy ngm:eba ;
vc:standardizedBy ngm:fatf ;
vc:standardizedBy ngm:fca ;
vc:standardizedBy ngm:fin-cen ;
vc:standardizedBy ngm:iosco ;
vc:standardizedBy ngm:iso-iec-27001 ;
vc:standardizedBy ngm:nist-cybersecurity-framework ;
vc:supports ngm:data-protection ;
vc:supports ngm:financial-regulation ;
vc:supports ngm:market-abuse-detection ;
vc:supports ngm:operational-resilience ;
vc:supports ngm:security-operations ;
vc:supports ngm:supply-chain-compliance ;
vc:uses ngm:bayesian-risk-models ;
vc:uses ngm:blockchain-analytics ;
vc:uses ngm:digital-identity ;
vc:uses ngm:homomorphic-encryption ;
vc:uses ngm:knowledge-graph ;
vc:uses ngm:knowledge-graphs ;
vc:uses ngm:large-language-models .
ngm:compliance-officer a skos:Concept ;
rdfs:label "Compliance Officer"@en .
ngm:compliance-policy a skos:Concept ;
rdfs:label "Compliance Policy"@en .
ngm:compliance-proofs a skos:Concept ;
rdfs:label "Compliance Proofs"@en .
ngm:compliance-reporting a skos:Concept ;
rdfs:label "Compliance Reporting"@en .
ngm:compliance-standards a owl:Class ;
rdfs:comment "The regulatory requirements, technical specifications, and legal frameworks that govern operations within virtual environments and metaverse platforms, encompassing data privacy, intellectual property, consumer protection, and conduct standards that organizations must adhere to when operating in or developing for immersive digital spaces."@en ;
rdfs:label "Compliance Standards"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:regulatory-framework ;
rdfs:subClassOf _:r4985 ;
rdfs:subClassOf _:r4986 ;
rdfs:subClassOf _:r4987 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:smart-contract ;
vc:contrastsWith ngm:self-regulation ;
vc:dependsOn ngm:identity-and-access-management ;
vc:dependsOn ngm:legal-framework ;
vc:enables ngm:consumer-protection ;
vc:enables ngm:data-protection ;
vc:enables ngm:interoperability ;
vc:enables ngm:legal-compliance ;
vc:enables ngm:trust-and-safety ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:eu-ai-act-regulatory-instrument ;
vc:implements ngm:gdpr ;
vc:implements ngm:regulatory-framework ;
vc:qualityScore "0.68"^^xsd:float ;
vc:relatedTo ngm:cybersecurity ;
vc:relatedTo ngm:platform-governance ;
vc:requires ngm:audit-and-accountability ;
vc:requires ngm:legal-expertise ;
vc:requires ngm:monitoring-system ;
vc:requires ngm:monitoring-systems ;
vc:requires ngm:regulatory-guidance ;
vc:requires ngm:risk-assessment ;
vc:slug "compliance-standards" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:iso-standards ;
vc:standardizedBy ngm:w3-c ;
vc:supports ngm:digital-markets-act ;
vc:supports ngm:digital-services-act ;
vc:supports ngm:intellectual-property-law ;
vc:uses ngm:data-governance ;
vc:uses ngm:privacy-by-design .
ngm:compliance-systems a owl:Class ;
rdfs:comment "Compliance systems are the integrated software and process frameworks organisations use to enforce, monitor, and report adherence to laws, regulations, and internal policies. They encompass policy management, control automation, monitoring and alerting, audit-trail capture, and regulatory reporting workflows. They matter because they operationalise obligations such as content-moderation duties under the Digital Services Act or custody and reporting rules for digital assets, turning legal requirements into continuously enforced controls."@en ;
rdfs:label "Compliance Systems"@en ;
rdfs:subClassOf ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:digital-asset-management ;
vc:relatedTo ngm:digital-services-act ;
vc:slug "compliance-systems" ;
vc:sourceDomain "governance" .
ngm:compliance-testing a owl:Class ;
rdfs:comment "Compliance testing is the systematic verification that a product, system, or process conforms to a defined standard, specification, or regulatory requirement. It produces objective, repeatable measurements that are compared against documented acceptance criteria to determine pass or fail status. It is a core component of validation and certification workflows, providing the evidentiary basis for conformity claims."@en ;
rdfs:label "Compliance Testing"@en ;
rdfs:subClassOf ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:display-metrology ;
vc:relatedTo ngm:validation-process ;
vc:slug "compliance-testing" ;
vc:sourceDomain "governance" .
ngm:compliance-validation-engine a skos:Concept ;
rdfs:label "Compliance Validation Engine"@en .
ngm:compliance-verification a owl:Class ;
rdfs:comment "Compliance verification in blockchain contexts encompasses the automated and manual processes for ensuring that cryptoasset transactions, service providers, and participants adhere to regulatory requirements including Know Your Customer (KYC), Anti-Money Laundering (AML), sanctions screening, and transaction monitoring obligations. Blockchain-based compliance systems leverage immutable ledgers, smart contracts, and AI-driven analytics to maintain tamper-proof records and detect suspicious activities in real-time."@en ;
rdfs:label "Compliance Verification"@en ;
rdfs:subClassOf ngm:compliance-monitoring ;
rdfs:subClassOf _:r4988 ;
rdfs:subClassOf _:r4989 ;
rdfs:subClassOf _:r4990 ;
rdfs:subClassOf _:r4991 ;
rdfs:subClassOf _:r4992 ;
vc:bridgesTo ngm:on-chain-governance ;
vc:bridgesTo ngm:self-sovereign-identity ;
vc:contrastsWith ngm:privacy-preserving-computation ;
vc:dependsOn ngm:blockchain ;
vc:dependsOn ngm:verifiable-credentials ;
vc:enables ngm:audit-trail ;
vc:enables ngm:kyc-aml ;
vc:enables ngm:regulatory-reporting ;
vc:enables ngm:sanctions-screening ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:aml ;
vc:hasPart ngm:sanctions-screening ;
vc:implements ngm:fatf-recommendations ;
vc:implements ngm:travel-rule ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:financial-crime-prevention ;
vc:requires ngm:identity-verification ;
vc:requires ngm:risk-assessment ;
vc:requires ngm:transaction-monitoring ;
vc:slug "compliance-verification" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:financial-action-task-force ;
vc:standardizedBy ngm:transfer-of-funds-regulation ;
vc:supports ngm:compliance ;
vc:supports ngm:regtech ;
vc:uses ngm:decentralised-identity ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:smart-contracts ;
vc:uses ngm:zero-knowledge-proof .
ngm:compliance-with-ccpa a skos:Concept ;
rdfs:label "Compliance With Ccpa"@en .
ngm:compliant-actuation a skos:Concept ;
rdfs:label "Compliant Actuation"@en .
ngm:compliant-manipulation a owl:Class ;
rdfs:comment "Compliant Manipulation is a branch of robotic manipulation in which the robot's end-effector or structural members intentionally yield to contact forces, using passive mechanical compliance or active force control to safely interact with uncertain, fragile, or human-occupied environments. Unlike rigid position-controlled manipulation, compliant manipulation regulates interaction forces as a first-class control objective."@en ;
rdfs:label "Compliant Manipulation"@en ;
rdfs:subClassOf ngm:robot-manipulation ;
rdfs:subClassOf _:r4999 ;
vc:enables ngm:robotic-grasping ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:haptic-feedback ;
vc:relatedTo ngm:soft-robotics ;
vc:requires ngm:actuator ;
vc:slug "compliant-manipulation" ;
vc:sourceDomain "robotics" ;
vc:uses ngm:force-control .
ngm:compliant-mechanism a skos:Concept ;
rdfs:label "Compliant Mechanism"@en .
ngm:compliant-motion a owl:Class ;
rdfs:comment "Compliant motion is robot motion that yields to external contact forces rather than rigidly tracking a predefined trajectory, allowing a manipulator to accommodate unexpected contact, surface irregularities or misalignment. It is achieved through admittance or impedance control, which regulate the relationship between measured force and commanded motion. It is essential for tasks involving physical contact with uncertain environments, such as assembly, polishing and human-robot interaction."@en ;
rdfs:label "Compliant Motion"@en ;
rdfs:subClassOf ngm:force-control ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "compliant-motion" ;
vc:sourceDomain "robotics" .
ngm:compliant-motion-control a skos:Concept ;
rdfs:label "Compliant Motion Control"@en .
ngm:compliant-robot a skos:Concept ;
rdfs:label "Compliant Robot"@en .
ngm:compliant-spring-element a skos:Concept ;
rdfs:label "Compliant Spring Element"@en .
ngm:compliant-transfer a skos:Concept ;
rdfs:label "Compliant Transfer"@en .
ngm:complyadvantage a skos:Concept ;
rdfs:label "Complyadvantage"@en .
ngm:component a owl:Class ;
rdfs:comment "A discrete, modular unit within an AI system or infrastructure that provides a specific capability, can be developed and tested independently, and interacts with other components through defined interfaces. Components include hardware accelerators, software modules, model artefacts, data pipelines, and monitoring subsystems."@en ;
rdfs:label "Component"@en ;
rdfs:subClassOf ngm:ai-infrastructure ;
rdfs:subClassOf ngm:digital-infrastructure ;
rdfs:subClassOf ngm:software-architecture ;
rdfs:subClassOf _:r5000 ;
rdfs:subClassOf _:r5001 ;
rdfs:subClassOf _:r5002 ;
rdfs:subClassOf _:r5003 ;
rdfs:subClassOf _:r5004 ;
rdfs:subClassOf _:r5005 ;
rdfs:subClassOf _:r5006 ;
rdfs:subClassOf _:r5007 ;
rdfs:subClassOf _:r5008 ;
rdfs:subClassOf _:r5009 ;
rdfs:subClassOf _:r5010 ;
rdfs:subClassOf _:r5011 ;
rdfs:subClassOf _:r5012 ;
rdfs:subClassOf _:r5013 ;
rdfs:subClassOf _:r5014 ;
rdfs:subClassOf _:r5015 ;
rdfs:subClassOf _:r5016 ;
rdfs:subClassOf _:r5017 ;
vc:contrastsWith ngm:monolithic-architecture ;
vc:dependsOn ngm:ai-framework ;
vc:dependsOn ngm:containerisation ;
vc:dependsOn ngm:edge-computing ;
vc:dependsOn ngm:feature-engineering ;
vc:dependsOn ngm:gpu-compute ;
vc:dependsOn ngm:kubernetes ;
vc:dependsOn ngm:service-mesh ;
vc:enables ngm:ai-system-eu-definition ;
vc:enables ngm:deep-learning ;
vc:enables ngm:distributed-training ;
vc:enables ngm:fault-tolerance ;
vc:enables ngm:machine-learning-discipline-pipeline ;
vc:enables ngm:mlops ;
vc:enables ngm:model-deployment ;
vc:enables ngm:model-serving ;
vc:enables ngm:reusability ;
vc:enables ngm:testability ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ai-system-component ;
vc:hasPart ngm:attention-mechanism ;
vc:hasPart ngm:data-pipeline ;
vc:hasPart ngm:embedding ;
vc:hasPart ngm:feature-engineering ;
vc:hasPart ngm:hardware-component ;
vc:hasPart ngm:inference-engine ;
vc:hasPart ngm:model-registry ;
vc:hasPart ngm:model-serving ;
vc:hasPart ngm:monitoring ;
vc:hasPart ngm:neural-network ;
vc:hasPart ngm:neural-network-component ;
vc:hasPart ngm:neural-network-layer ;
vc:hasPart ngm:software-module ;
vc:hasPart ngm:transformer-architecture ;
vc:implements ngm:dependency-injection ;
vc:implements ngm:design-pattern ;
vc:implements ngm:event-driven-architecture ;
vc:implements ngm:microservices ;
vc:implements ngm:separation-of-concerns ;
vc:isPartOf ngm:ai-system-eu-definition ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:ai-framework ;
vc:relatedTo ngm:ai-infrastructure ;
vc:relatedTo ngm:attention-mechanism ;
vc:relatedTo ngm:benchmarks ;
vc:relatedTo ngm:data-pipeline ;
vc:relatedTo ngm:embedded-systems ;
vc:relatedTo ngm:event-driven-architecture ;
vc:relatedTo ngm:explainability ;
vc:relatedTo ngm:feature-engineering ;
vc:relatedTo ngm:inference-engine ;
vc:relatedTo ngm:iso-iec-23053 ;
vc:relatedTo ngm:iso-iec-25010 ;
vc:relatedTo ngm:knowledge-distillation ;
vc:relatedTo ngm:large-language-model ;
vc:relatedTo ngm:machine-learning-discipline-framework ;
vc:relatedTo ngm:machine-learning-discipline-pipeline ;
vc:relatedTo ngm:microservices ;
vc:relatedTo ngm:model-registry ;
vc:relatedTo ngm:monitoring ;
vc:relatedTo ngm:neural-network ;
vc:relatedTo ngm:neural-network-layer ;
vc:relatedTo ngm:quantisation ;
vc:relatedTo ngm:responsible-ai ;
vc:relatedTo ngm:retrieval-augmented-generation ;
vc:relatedTo ngm:safety ;
vc:relatedTo ngm:software-architecture ;
vc:relatedTo ngm:transformer-architecture ;
vc:requires ngm:api ;
vc:requires ngm:containerisation ;
vc:requires ngm:interface ;
vc:requires ngm:modularity ;
vc:requires ngm:reusability ;
vc:requires ngm:separation-of-concerns ;
vc:requires ngm:testability ;
vc:slug "component" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:iso-iec-23053 ;
vc:standardizedBy ngm:iso-iec-25010 ;
vc:supports ngm:artificial-intelligence ;
vc:supports ngm:data-governance ;
vc:supports ngm:deep-learning ;
vc:supports ngm:distributed-training ;
vc:supports ngm:embedded-systems ;
vc:supports ngm:machine-learning-discipline-pipeline ;
vc:supports ngm:mlops ;
vc:supports ngm:model-serving ;
vc:uses ngm:api ;
vc:uses ngm:edge-computing ;
vc:uses ngm:gpu-compute ;
vc:uses ngm:kubernetes ;
vc:uses ngm:mlops ;
vc:uses ngm:model-registry ;
vc:uses ngm:monitoring ;
vc:uses ngm:service-mesh ;
vc:uses ngm:vector-database .
ngm:component-assembly a skos:Concept ;
rdfs:label "Component Assembly"@en .
ngm:component-definitions a skos:Concept ;
rdfs:label "Component Definitions"@en .
ngm:component-integration a skos:Concept ;
rdfs:label "Component Integration"@en .
ngm:component-reusability a skos:Concept ;
rdfs:label "Component Reusability"@en .
ngm:composability a owl:Class ;
rdfs:comment "Composability is the property by which independent components can be combined into larger systems whose behaviour is predictable from the behaviour of the parts. In blockchain and decentralised finance it describes how permissionless smart contracts can call and build upon one another so that protocols interlock like building blocks, often called money legos. Composability accelerates innovation but couples systems together, propagating both functionality and risk across the stack."@en ;
rdfs:label "Composability"@en ;
rdfs:subClassOf ngm:smart-contract ;
rdfs:subClassOf _:r5018 ;
vc:bridgesTo ngm:de-fi ;
vc:contrastsWith ngm:interoperability ;
vc:dependsOn ngm:smart-contract ;
vc:enables ngm:de-fi ;
vc:enables ngm:interoperability ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:blockchain ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:de-fi-protocol ;
vc:relatedTo ngm:decentralized-exchange ;
vc:relatedTo ngm:interoperability ;
vc:requires ngm:interoperability ;
vc:slug "composability" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:de-fi ;
vc:supports ngm:de-fi-protocol ;
vc:uses ngm:smart-contract .
ngm:composable-architecture a owl:Class ;
rdfs:comment "Composable architecture is a software design approach in which independent, interchangeable components or services are assembled and reassembled to build applications, rather than being built as a single monolith. Components expose well-defined interfaces so they can be combined, replaced or extended without redesigning the whole system. It underpins API-integration strategies and modern system-integration practice, where new capabilities are added by composing existing building blocks."@en ;
rdfs:label "Composable Architecture"@en ;
rdfs:subClassOf ngm:software-architecture ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "composable-architecture" ;
vc:sourceDomain "infrastructure" .
ngm:composable-finance a skos:Concept ;
rdfs:label "Composable Finance"@en .
ngm:composio a skos:Concept ;
rdfs:label "Composio"@en .
ngm:composite-ai a owl:Class ;
rdfs:comment "Composite AI is an architectural paradigm that integrates multiple distinct AI techniques — such as machine learning, symbolic reasoning, natural language processing, computer vision, and knowledge graphs — into a unified hierarchical system to solve complex real-world problems that no single technique alone can address adequately. By orchestrating complementary AI capabilities, composite AI achieves higher contextual understanding, adaptability, and decision-making precision than monolithic approaches. It is increasingly the default pattern in enterprise intelligent automation, autonomous systems, and multimodal applications."@en ;
rdfs:label "Composite AI"@en ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf _:r5019 ;
rdfs:subClassOf _:r5020 ;
rdfs:subClassOf _:r5021 ;
rdfs:subClassOf _:r5022 ;
rdfs:subClassOf _:r5023 ;
skos:broader ngm:ai-research-area ;
vc:bridgesTo ngm:computer-vision ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:computer-vision ;
vc:hasPart ngm:knowledge-graph ;
vc:hasPart ngm:machine-learning-discipline ;
vc:hasPart ngm:natural-language-processing ;
vc:hasPart ngm:symbolic-reasoning ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:deep-learning ;
vc:relatedTo ngm:ensemble-methods ;
vc:relatedTo ngm:explainable-ai ;
vc:relatedTo ngm:generative-ai ;
vc:relatedTo ngm:multimodal-ai-architecture ;
vc:relatedTo ngm:reinforcement-learning ;
vc:slug "composite-ai" ;
vc:sourceDomain "artificial-intelligence" .
ngm:composite-material a skos:Concept ;
rdfs:label "Composite Material"@en .
ngm:compositing a skos:Concept ;
rdfs:label "Compositing"@en .
ngm:compositing-pipeline a skos:Concept ;
rdfs:label "Compositing Pipeline"@en .
ngm:composition-arcs a skos:Concept ;
rdfs:label "Composition Arcs"@en .
ngm:composition-theorems a skos:Concept ;
rdfs:label "Composition Theorems"@en .
ngm:compositional-reasoning a skos:Concept ;
rdfs:label "Compositional Reasoning"@en .
ngm:compound a owl:Class ;
rdfs:comment "Compound is an algorithmic, autonomous interest-rate protocol built on Ethereum that enables users to supply crypto assets to liquidity pools and earn continuously accruing interest, or borrow assets against over-collateralised positions at algorithmically determined rates. Interest rates adjust dynamically based on the utilisation ratio of each asset pool, eliminating the need for bilateral loan negotiation or centralised intermediaries. Supplied assets are represented as cTokens — ERC-20 tokens whose exchange rate appreciates with every block as interest accrues — which can themselves be used as collateral or freely traded. Governance of protocol parameters is conducted on-chain through the COMP token and the Compound Governor Bravo smart-contract system, making it one of the earliest fully decentralised autonomous lending protocols in the DeFi ecosystem."@en ;
rdfs:label "Compound"@en ;
rdfs:subClassOf ngm:bc-defi-and-economics ;
rdfs:subClassOf _:r5028 ;
rdfs:subClassOf _:r5029 ;
rdfs:subClassOf _:r5030 ;
rdfs:subClassOf _:r5031 ;
skos:broader ngm:bc-defi-and-economics ;
vc:bridgesTo ngm:algorithmic-market-design ;
vc:bridgesTo ngm:mechanism-design ;
vc:contrastsWith ngm:aave ;
vc:contrastsWith ngm:maker-dao ;
vc:contrastsWith ngm:uniswap ;
vc:dependsOn ngm:ethereum-smart-contract-platform-virtual-machine ;
vc:dependsOn ngm:price-oracle ;
vc:enables ngm:collateralised-borrowing ;
vc:enables ngm:digital-asset-lending ;
vc:enables ngm:liquidity-mining ;
vc:enables ngm:yield-farming ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:compound-governor-bravo ;
vc:hasPart ngm:ctoken ;
vc:hasPart ngm:interest-rate-model ;
vc:isPartOf ngm:de-fi ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:autonomous-market-operations ;
vc:relatedTo ngm:collateral-factor ;
vc:relatedTo ngm:de-fi ;
vc:relatedTo ngm:liquidation ;
vc:relatedTo ngm:total-value-locked ;
vc:requires ngm:liquidity-pool ;
vc:requires ngm:oracle ;
vc:requires ngm:over-collateralisation ;
vc:slug "compound" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:erc-20-token-standard ;
vc:uses ngm:ethereum ;
vc:uses ngm:governance-token ;
vc:uses ngm:smart-contracts .
ngm:compound-ai-system a skos:Concept ;
rdfs:label "Compound AI System"@en .
ngm:compound-coordinate-reference-system a owl:Class ;
rdfs:label "Compound Coordinate Reference System"@en ;
rdfs:subClassOf ngm:coordinate-reference-system ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:projected-coordinate-reference-system ;
vc:relatedTo ngm:vertical-coordinate-reference-system ;
vc:slug "compound-coordinate-reference-system" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:compound-governor-alpha a skos:Concept ;
rdfs:label "Compound Governor Alpha"@en .
ngm:compound-governor-bravo a owl:Class ;
rdfs:comment "Compound Governor Bravo is the second-generation on-chain governance smart contract deployed by the Compound protocol, superseding Governor Alpha with configurable parameters and a clean separation between governance voting logic and the Timelock executor contract. It enables COMP token holders to create, vote on, and enqueue governance proposals that modify protocol parameters — including interest rate models, collateral factors, reserve factors, and supported asset listings — without requiring contract redeployment to adjust governance thresholds. Governor Bravo introduced an abstraction layer allowing the proposal threshold, voting delay, voting period, and quorum to be updated through the same governance process they govern, substantially reducing upgrade friction. The contract has become a widely forked reference implementation across decentralised finance, with derivatives adopted by Uniswap, Indexed Finance, and many other protocols seeking battle-tested on-chain governance infrastructure."@en ;
rdfs:label "Compound Governor Bravo"@en ;
rdfs:subClassOf ngm:on-chain-governance ;
rdfs:subClassOf _:r5024 ;
rdfs:subClassOf _:r5025 ;
rdfs:subClassOf _:r5026 ;
rdfs:subClassOf _:r5027 ;
vc:bridgesTo ngm:decentralised-autonomous-organisation ;
vc:bridgesTo ngm:smart-contract-security ;
vc:contrastsWith ngm:compound-governor-alpha ;
vc:contrastsWith ngm:open-zeppelin-governor ;
vc:contrastsWith ngm:snapshot-governance ;
vc:dependsOn ngm:ethereum ;
vc:dependsOn ngm:governance-token ;
vc:enables ngm:dao ;
vc:enables ngm:de-fi ;
vc:enables ngm:protocol-parameter-management ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:proposal-lifecycle ;
vc:implements ngm:quorum-mechanism ;
vc:implements ngm:token-weighted-voting ;
vc:isPartOf ngm:compound ;
vc:isPartOf ngm:governance-framework ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:dao-analytics ;
vc:relatedTo ngm:de-fi-protocol ;
vc:relatedTo ngm:governance-attack ;
vc:requires ngm:comp-token ;
vc:requires ngm:ethereum-smart-contract-platform-smart-contracts ;
vc:requires ngm:timelock ;
vc:requires ngm:vote-delegation ;
vc:slug "compound-governor-bravo" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:blockchain-governance ;
vc:supports ngm:dao-governance ;
vc:uses ngm:calldata-execution ;
vc:uses ngm:proposal-system ;
vc:uses ngm:voting-mechanism .
ngm:compressed-air a skos:Concept ;
rdfs:label "Compressed Air"@en .
ngm:compressed-air-supply a skos:Concept ;
rdfs:label "Compressed Air Supply"@en .
ngm:compressed-sensing a owl:Class ;
rdfs:comment "Compressed sensing is a signal processing technique that reconstructs a signal from far fewer samples than classical sampling theory requires, exploiting the fact that many real-world signals are sparse in some basis. Reconstruction is typically posed as a convex optimisation problem that recovers the sparsest signal consistent with the observed measurements. It has applications in medical imaging, wireless communications and any domain where sampling is costly or constrained."@en ;
rdfs:label "Compressed Sensing"@en ;
rdfs:subClassOf ngm:sparse-representation ;
rdfs:subClassOf _:r5032 ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:convex-optimisation ;
vc:slug "compressed-sensing" ;
vc:sourceDomain "machine-learning" .
ngm:compression-function a owl:Class ;
rdfs:comment "A compression function is a fixed-input-length cryptographic primitive that maps two inputs (a chaining value and a message block) to a single shorter output. It is the core building block of iterated hash functions, where it is applied repeatedly under constructions such as Merkle-Damgard to process arbitrary-length messages. Its collision and preimage resistance directly determine the security of the hash function built on top of it."@en ;
rdfs:label "Compression Function"@en ;
rdfs:subClassOf ngm:cryptographic-primitive ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:hash-function ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:hash-function ;
vc:slug "compression-function" ;
vc:sourceDomain "security" .
ngm:computability-theory a owl:Class ;
rdfs:comment "Computability theory, also known as recursion theory, is the branch of mathematical logic and theoretical computer science that studies which problems can be solved algorithmically in principle, independent of resource constraints. It defines models of computation such as the Turing machine, establishes the existence of undecidable problems like the halting problem, and characterises the limits of effective procedures via the Church-Turing thesis. It contrasts with complexity theory, which asks how efficiently solvable problems can be solved."@en ;
rdfs:label "Computability Theory"@en ;
rdfs:subClassOf ngm:computational-complexity-theory ;
rdfs:subClassOf ngm:computer-science ;
rdfs:subClassOf ngm:mathematical-logic ;
rdfs:subClassOf ngm:proof-theory ;
rdfs:subClassOf _:r5033 ;
rdfs:subClassOf _:r5034 ;
rdfs:subClassOf _:r5035 ;
rdfs:subClassOf _:r5036 ;
rdfs:subClassOf _:r5037 ;
rdfs:subClassOf _:r5038 ;
rdfs:subClassOf _:r5039 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:contrastsWith ngm:computational-complexity-theory ;
vc:contrastsWith ngm:hypercomputation ;
vc:contrastsWith ngm:probabilistic-computing ;
vc:dependsOn ngm:g-del-incompleteness-theorems ;
vc:dependsOn ngm:mathematical-logic ;
vc:dependsOn ngm:peano-arithmetic ;
vc:dependsOn ngm:set-theory ;
vc:enables ngm:ai-safety ;
vc:enables ngm:automata-theory ;
vc:enables ngm:automated-theorem-proving ;
vc:enables ngm:compiler-theory ;
vc:enables ngm:descriptive-complexity ;
vc:enables ngm:formal-methods ;
vc:enables ngm:model-checking ;
vc:enables ngm:programme-verification ;
vc:enables ngm:programming-language-theory ;
vc:enables ngm:static-analysis ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:automata-theory ;
vc:hasPart ngm:church-turing-thesis ;
vc:hasPart ngm:decidability ;
vc:hasPart ngm:formal-language ;
vc:hasPart ngm:halting-problem ;
vc:hasPart ngm:kolmogorov-complexity ;
vc:hasPart ngm:lambda-calculus ;
vc:hasPart ngm:oracle-computation ;
vc:hasPart ngm:post-correspondence-problem ;
vc:hasPart ngm:recursive-function ;
vc:hasPart ngm:rice-s-theorem ;
vc:hasPart ngm:semi-decidability ;
vc:hasPart ngm:turing-degree ;
vc:hasPart ngm:turing-machine ;
vc:implements ngm:church-turing-thesis ;
vc:implements ngm:enumeration ;
vc:implements ngm:formal-ontology ;
vc:implements ngm:reduction ;
vc:implements ngm:semi-decidability ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:algorithm ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:cellular-automata ;
vc:relatedTo ngm:cryptography ;
vc:relatedTo ngm:deep-learning ;
vc:relatedTo ngm:descriptive-complexity ;
vc:relatedTo ngm:formal-language ;
vc:relatedTo ngm:godel-incompleteness ;
vc:relatedTo ngm:information-theory ;
vc:relatedTo ngm:kolmogorov-complexity ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:neural-network ;
vc:relatedTo ngm:oracle-computation ;
vc:relatedTo ngm:post-correspondence-problem ;
vc:relatedTo ngm:programming-language-theory ;
vc:relatedTo ngm:quantum-computation-paradigm ;
vc:relatedTo ngm:reverse-mathematics ;
vc:relatedTo ngm:set-theory ;
vc:relatedTo ngm:type-theory ;
vc:requires ngm:mathematical-logic ;
vc:requires ngm:number-theory ;
vc:requires ngm:proof-theory ;
vc:requires ngm:set-theory ;
vc:slug "computability-theory" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:association-for-computing-machinery ;
vc:standardizedBy ngm:mathematical-logic ;
vc:supports ngm:ai-alignment ;
vc:supports ngm:ai-safety ;
vc:supports ngm:automated-reasoning ;
vc:supports ngm:cryptography ;
vc:supports ngm:knowledge-graph ;
vc:supports ngm:knowledge-representation ;
vc:supports ngm:reverse-mathematics ;
vc:supports ngm:software-engineering ;
vc:supports ngm:type-theory ;
vc:uses ngm:category-theory ;
vc:uses ngm:diagonalisation ;
vc:uses ngm:enumeration ;
vc:uses ngm:fixed-point-theorem ;
vc:uses ngm:g-del-incompleteness-theorems ;
vc:uses ngm:kolmogorov-complexity ;
vc:uses ngm:oracle-computation ;
vc:uses ngm:reduction .
ngm:computation-graph a owl:Class ;
rdfs:comment "A Computation Graph is a directed graph in which nodes represent operations or variables and edges represent the flow of data (typically tensors) between them. It is the central abstraction in modern machine learning frameworks, where a model's forward pass is expressed as a graph and gradients are computed by traversing it in reverse via automatic differentiation. Graphs may be built statically ahead of execution or dynamically as code runs, and they enable optimisation, scheduling and hardware acceleration."@en ;
rdfs:label "Computation Graph"@en ;
rdfs:subClassOf ngm:directed-acyclic-graph ;
rdfs:subClassOf _:r5040 ;
rdfs:subClassOf _:r5041 ;
vc:bridgesTo ngm:py-torch ;
vc:bridgesTo ngm:tensor-flow ;
vc:dependsOn ngm:machine-learning-discipline-framework ;
vc:enables ngm:backpropagation ;
vc:enables ngm:gpu-acceleration ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:tensor ;
vc:implements ngm:neural-network ;
vc:isPartOf ngm:deep-learning-framework ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:deep-learning ;
vc:requires ngm:automatic-differentiation ;
vc:slug "computation-graph" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:onnx ;
vc:supports ngm:gradient-descent ;
vc:supports ngm:model-training ;
vc:uses ngm:directed-acyclic-graph .
ngm:computation-hardware a skos:Concept ;
rdfs:label "Computation Hardware"@en .
ngm:computational-biology a owl:Class ;
rdfs:comment "Computational biology is the application of computational methods, mathematical modelling, statistical inference, and data analysis to understand biological systems and processes at every scale of organisation, from individual molecules and cells through tissues, organisms, populations, and ecosystems. It develops algorithms and models to interpret molecular, cellular, and organismal data, spanning sequence analysis, structural prediction, systems modelling, and simulation. The discipline increasingly relies on machine learning and deep learning to extract patterns from large and complex biological datasets, and is the parent domain of bioinformatics."@en ;
rdfs:label "Computational Biology"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf ngm:bioinformatics ;
rdfs:subClassOf ngm:biology ;
rdfs:subClassOf ngm:data-science ;
rdfs:subClassOf ngm:scientific-computing ;
rdfs:subClassOf _:r5042 ;
rdfs:subClassOf _:r5043 ;
rdfs:subClassOf _:r5044 ;
rdfs:subClassOf _:r5045 ;
rdfs:subClassOf _:r5046 ;
rdfs:subClassOf _:r5047 ;
rdfs:subClassOf _:r5048 ;
rdfs:subClassOf _:r5049 ;
rdfs:subClassOf _:r5050 ;
skos:broader ngm:artificial-intelligence ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:bridgesTo ngm:scientific-computing ;
vc:contrastsWith ngm:classical-genetics ;
vc:contrastsWith ngm:experimental-biochemistry ;
vc:contrastsWith ngm:wet-laboratory-biology ;
vc:dependsOn ngm:biology ;
vc:dependsOn ngm:data-science ;
vc:dependsOn ngm:linear-algebra ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:optimisation ;
vc:dependsOn ngm:probability-theory ;
vc:dependsOn ngm:scientific-computing ;
vc:dependsOn ngm:statistics ;
vc:enables ngm:agricultural-genomics ;
vc:enables ngm:cancer-genomics ;
vc:enables ngm:drug-discovery ;
vc:enables ngm:healthcare ;
vc:enables ngm:pandemic-preparedness ;
vc:enables ngm:precision-medicine ;
vc:enables ngm:protein-structure-prediction ;
vc:enables ngm:synthetic-biology ;
vc:enables ngm:vaccine-design ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:bioinformatics ;
vc:hasPart ngm:cancer-genomics ;
vc:hasPart ngm:epigenomics ;
vc:hasPart ngm:evolutionary-biology ;
vc:hasPart ngm:immunoinformatics ;
vc:hasPart ngm:metagenomics ;
vc:hasPart ngm:molecular-dynamics ;
vc:hasPart ngm:phylogenetics ;
vc:hasPart ngm:population-genetics ;
vc:hasPart ngm:proteomics ;
vc:hasPart ngm:structural-biology ;
vc:hasPart ngm:systems-biology ;
vc:hasPart ngm:transcriptomics ;
vc:implements ngm:bayesian-inference ;
vc:implements ngm:expectation-maximisation ;
vc:implements ngm:markov-chain-monte-carlo ;
vc:implements ngm:molecular-dynamics ;
vc:implements ngm:probabilistic-modelling ;
vc:implements ngm:sequence-alignment ;
vc:implements ngm:variational-inference ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:alphafold ;
vc:relatedTo ngm:bioinformatics ;
vc:relatedTo ngm:data-science ;
vc:relatedTo ngm:drug-discovery ;
vc:relatedTo ngm:embl-ebi ;
vc:relatedTo ngm:francis-crick-institute ;
vc:relatedTo ngm:genomics ;
vc:relatedTo ngm:human-cell-atlas ;
vc:relatedTo ngm:knowledge-graph ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:scientific-machine-learning ;
vc:relatedTo ngm:synthetic-biology ;
vc:relatedTo ngm:uk-biobank ;
vc:relatedTo ngm:wellcome-sanger-institute ;
vc:relatedTo ngm:wellcome-trust ;
vc:requires ngm:algorithm ;
vc:requires ngm:big-data ;
vc:requires ngm:biology ;
vc:requires ngm:cloud-computing ;
vc:requires ngm:gpu ;
vc:requires ngm:high-performance-computing ;
vc:requires ngm:parallel-computing ;
vc:requires ngm:scientific-computing ;
vc:slug "computational-biology" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:embl-ebi ;
vc:standardizedBy ngm:global-alliance-for-genomics-and-health ;
vc:standardizedBy ngm:ncbi ;
vc:standardizedBy ngm:wellcome-sanger-institute ;
vc:supports ngm:cancer-genomics ;
vc:supports ngm:clinical-genomics ;
vc:supports ngm:drug-discovery ;
vc:supports ngm:genomics ;
vc:supports ngm:healthcare ;
vc:supports ngm:precision-medicine ;
vc:supports ngm:protein-structure-prediction ;
vc:supports ngm:public-health ;
vc:supports ngm:synthetic-biology ;
vc:supports ngm:systems-biology ;
vc:uses ngm:alphafold ;
vc:uses ngm:bayesian-inference ;
vc:uses ngm:deep-learning ;
vc:uses ngm:differential-equations ;
vc:uses ngm:dynamic-programming ;
vc:uses ngm:graph-neural-network ;
vc:uses ngm:hidden-markov-model ;
vc:uses ngm:large-language-models ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:neural-network ;
vc:uses ngm:probabilistic-modelling ;
vc:uses ngm:reinforcement-learning ;
vc:uses ngm:sequence-alignment ;
vc:uses ngm:statistics ;
vc:uses ngm:transformer-architecture ;
vc:uses ngm:vae .
ngm:computational-budget a skos:Concept ;
rdfs:label "Computational Budget"@en .
ngm:computational-chemistry a skos:Concept ;
rdfs:label "Computational Chemistry"@en .
ngm:computational-complexity a skos:Concept ;
rdfs:label "Computational Complexity"@en .
ngm:computational-complexity-theory a owl:Class ;
rdfs:comment "The mathematical study of the resources — principally time and memory (space) — required to solve computational problems, and the classification of problems according to their inherent difficulty into complexity classes such as P, NP, PSPACE, BPP, and EXPTIME. It establishes which problems are tractable (solvable efficiently in polynomial time) and which are intractable, and investigates the relationships between complexity classes, most famously the unresolved P vs NP question."@en ;
rdfs:label "Computational Complexity Theory"@en ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf ngm:computer-science ;
rdfs:subClassOf ngm:mathematical-logic ;
rdfs:subClassOf ngm:owl-thing ;
rdfs:subClassOf _:r5051 ;
rdfs:subClassOf _:r5052 ;
rdfs:subClassOf _:r5053 ;
rdfs:subClassOf _:r5054 ;
rdfs:subClassOf _:r5055 ;
rdfs:subClassOf _:r5056 ;
rdfs:subClassOf _:r5057 ;
skos:broader ngm:ai-research-area ;
vc:bridgesTo ngm:cryptography ;
vc:bridgesTo ngm:data-science ;
vc:bridgesTo ngm:deep-learning ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:bridgesTo ngm:neural-network ;
vc:bridgesTo ngm:quantum-information ;
vc:contrastsWith ngm:algorithm-design ;
vc:contrastsWith ngm:computability-theory ;
vc:contrastsWith ngm:heuristic-search ;
vc:dependsOn ngm:computability-theory ;
vc:dependsOn ngm:graph-theory ;
vc:dependsOn ngm:information-theory ;
vc:dependsOn ngm:mathematical-logic ;
vc:dependsOn ngm:set-theory ;
vc:enables ngm:approximation-algorithms ;
vc:enables ngm:computational-learning-theory ;
vc:enables ngm:cryptographic-hardness-assumption ;
vc:enables ngm:formal-verification ;
vc:enables ngm:post-quantum-cryptography ;
vc:enables ngm:quantum-computation-paradigm ;
vc:enables ngm:sat-solving ;
vc:enables ngm:zero-knowledge-proof ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:approximation-algorithms ;
vc:hasPart ngm:automata-theory ;
vc:hasPart ngm:average-case-complexity ;
vc:hasPart ngm:circuit-complexity ;
vc:hasPart ngm:communication-complexity ;
vc:hasPart ngm:counting-complexity ;
vc:hasPart ngm:derandomisation ;
vc:hasPart ngm:fine-grained-complexity ;
vc:hasPart ngm:interactive-proofs ;
vc:hasPart ngm:parameterised-complexity ;
vc:hasPart ngm:proof-complexity ;
vc:implements ngm:boolean-satisfiability ;
vc:implements ngm:constraint-satisfaction ;
vc:implements ngm:graph-algorithm ;
vc:implements ngm:graph-isomorphism ;
vc:implements ngm:integer-programming ;
vc:implements ngm:randomised-algorithms ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:algebraic-geometry ;
vc:relatedTo ngm:coding-theory ;
vc:relatedTo ngm:computer-science ;
vc:relatedTo ngm:constraint-satisfaction ;
vc:relatedTo ngm:information-theory ;
vc:relatedTo ngm:knowledge-graph ;
vc:relatedTo ngm:kolmogorov-complexity ;
vc:relatedTo ngm:ontology ;
vc:requires ngm:algorithm ;
vc:requires ngm:automata-theory ;
vc:requires ngm:boolean-algebra ;
vc:requires ngm:formal-language ;
vc:requires ngm:mathematical-logic ;
vc:requires ngm:set-theory ;
vc:requires ngm:turing-machine ;
vc:slug "computational-complexity-theory" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:clay-mathematics-institute ;
vc:supports ngm:automated-reasoning ;
vc:supports ngm:constraint-satisfaction-problem ;
vc:supports ngm:cryptography ;
vc:supports ngm:description-logic ;
vc:supports ngm:formal-verification ;
vc:supports ngm:knowledge-representation ;
vc:supports ngm:machine-learning-discipline ;
vc:supports ngm:ontology ;
vc:supports ngm:planning-and-scheduling ;
vc:uses ngm:cryptographic-proof-system ;
vc:uses ngm:oracle ;
vc:uses ngm:probability-theory ;
vc:uses ngm:reduction .
ngm:computational-component a owl:Class ;
rdfs:comment "A Computational Component is a modular, well-defined unit of an AI or software system that encapsulates specific processing logic — such as a neural network layer, a feature extraction module, or an inference engine — and interacts with other components through defined interfaces. Computational components abstract implementation details from consumers, enabling composition into larger pipelines and substitution of equivalent implementations without modifying the surrounding system. They are the primary unit of reuse, testing, and deployment in AI infrastructure, ranging from low-level hardware accelerator kernels to high-level model serving endpoints."@en ;
rdfs:label "Computational Component"@en ;
rdfs:subClassOf ngm:ai-infrastructure ;
rdfs:subClassOf ngm:component ;
rdfs:subClassOf _:r5058 ;
rdfs:subClassOf _:r5059 ;
rdfs:subClassOf _:r5060 ;
rdfs:subClassOf _:r5061 ;
rdfs:subClassOf _:r5062 ;
vc:enables ngm:inference ;
vc:enables ngm:model-training ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:algorithm ;
vc:hasPart ngm:module ;
vc:hasPart ngm:neural-network-layer ;
vc:isPartOf ngm:ai-system-component ;
vc:isPartOf ngm:machine-learning-discipline-pipeline ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:middleware ;
vc:relatedTo ngm:model-architecture ;
vc:relatedTo ngm:neural-network-component ;
vc:relatedTo ngm:software-architecture ;
vc:requires ngm:computational-resources ;
vc:requires ngm:interface ;
vc:slug "computational-component" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:compute-infrastructure ;
vc:uses ngm:gpu-compute ;
vc:uses ngm:hardware-acceleration .
ngm:computational-creativity a owl:Class ;
rdfs:comment "Computational creativity is the subfield of artificial intelligence concerned with building systems that exhibit behaviours regarded as creative, such as generating novel and valuable artefacts in art, music, design, or narrative. It studies both the algorithmic generation of original output and the evaluation of novelty, surprise, and value. The field informs generative models, procedural content systems, and AI-assisted creative tooling."@en ;
rdfs:label "Computational Creativity"@en ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf ngm:cognitive-science ;
rdfs:subClassOf _:r5063 ;
rdfs:subClassOf _:r5064 ;
rdfs:subClassOf _:r5065 ;
rdfs:subClassOf _:r5066 ;
rdfs:subClassOf _:r5067 ;
rdfs:subClassOf _:r5068 ;
rdfs:subClassOf _:r5069 ;
rdfs:subClassOf _:r5070 ;
rdfs:subClassOf _:r5071 ;
rdfs:subClassOf _:r5072 ;
rdfs:subClassOf _:r5073 ;
skos:broader ngm:ai-research-area ;
skos:broader ngm:artificial-intelligence ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:human-computer-interaction ;
vc:bridgesTo ngm:multimodal-ai-architecture-ai ;
vc:bridgesTo ngm:natural-language-processing ;
vc:contrastsWith ngm:classical-ai-planning ;
vc:contrastsWith ngm:discriminative-ai ;
vc:contrastsWith ngm:rule-based-systems ;
vc:dependsOn ngm:cognitive-science ;
vc:dependsOn ngm:diffusion-model ;
vc:dependsOn ngm:foundation-model ;
vc:dependsOn ngm:generative-adversarial-network ;
vc:dependsOn ngm:generative-ai ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:representation-learning ;
vc:dependsOn ngm:vae ;
vc:enables ngm:autonomous-artistic-system ;
vc:enables ngm:creative-ai ;
vc:enables ngm:creative-expression ;
vc:enables ngm:creative-industries ;
vc:enables ngm:game-development ;
vc:enables ngm:human-ai-collaboration ;
vc:enables ngm:scientific-discovery ;
vc:enables ngm:synthetic-data ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:aesthetic-knowledge-base ;
vc:hasPart ngm:conceptual-space-model ;
vc:hasPart ngm:content-generation ;
vc:hasPart ngm:creative-evaluation-framework ;
vc:hasPart ngm:image-generation ;
vc:hasPart ngm:music-generation ;
vc:hasPart ngm:novelty-estimation ;
vc:hasPart ngm:procedural-content-generation ;
vc:implements ngm:conceptual-blending ;
vc:implements ngm:deep-learning ;
vc:implements ngm:diffusion-model ;
vc:implements ngm:evolutionary-algorithm ;
vc:implements ngm:generative-adversarial-network ;
vc:implements ngm:large-language-models ;
vc:implements ngm:reinforcement-learning ;
vc:implements ngm:transformer ;
vc:implements ngm:vae ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:affective-computing ;
vc:relatedTo ngm:ai-in-games ;
vc:relatedTo ngm:cognitive-architecture ;
vc:relatedTo ngm:cognitive-science ;
vc:relatedTo ngm:computational-intelligence ;
vc:relatedTo ngm:eu-ai-act-regulatory-instrument ;
vc:relatedTo ngm:intellectual-property-rights-framework ;
vc:relatedTo ngm:representation-learning ;
vc:relatedTo ngm:synthetic-data ;
vc:requires ngm:constraint-satisfaction ;
vc:requires ngm:deep-generative-model ;
vc:requires ngm:knowledge-representation ;
vc:requires ngm:reinforcement-learning-from-human-feedback ;
vc:requires ngm:representation-learning ;
vc:requires ngm:search-algorithm ;
vc:requires ngm:training-data ;
vc:slug "computational-creativity" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:c2pa-provenance-standard ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:supports ngm:augmented-reality ;
vc:supports ngm:creative-expression ;
vc:supports ngm:creative-software ;
vc:supports ngm:education-and-ai ;
vc:supports ngm:game-development ;
vc:supports ngm:human-ai-collaboration ;
vc:supports ngm:metaverse ;
vc:supports ngm:scientific-discovery ;
vc:uses ngm:cognitive-ai ;
vc:uses ngm:cognitive-science ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:optimisation ;
vc:uses ngm:reinforcement-learning .
ngm:computational-fluid-dynamics a skos:Concept ;
rdfs:label "Computational Fluid Dynamics"@en .
ngm:computational-geometry a owl:Class ;
rdfs:comment "Computational geometry is the study of algorithms for solving geometric problems, such as finding convex hulls, intersections, and nearest points. It provides foundational techniques for computer graphics, robotics motion planning, geographic information systems, and computer-aided design."@en ;
rdfs:label "Computational Geometry"@en ;
rdfs:subClassOf ngm:algorithm ;
rdfs:subClassOf _:r5074 ;
rdfs:subClassOf _:r5075 ;
rdfs:subClassOf _:r5076 ;
rdfs:subClassOf _:r5077 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:computational-geometry ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:dependsOn ngm:algorithm ;
vc:dependsOn ngm:graph-theory ;
vc:enables ngm:3-d-engine ;
vc:enables ngm:collision-detection ;
vc:enables ngm:computer-aided-design ;
vc:enables ngm:geographic-information-system ;
vc:enables ngm:pathfinding ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:voronoi-diagram ;
vc:isPartOf ngm:spatial-computing ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:point-cloud-processing ;
vc:requires ngm:data-structure ;
vc:requires ngm:linear-algebra ;
vc:requires ngm:numerical-methods ;
vc:slug "computational-geometry" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:computer-vision ;
vc:supports ngm:robotics ;
vc:uses ngm:bounding-volume-hierarchy ;
vc:uses ngm:spatial-index .
ngm:computational-graph a owl:Class ;
rdfs:comment "A computational graph is a directed acyclic graph in which nodes represent mathematical operations or variables and edges represent the flow of data (tensors) between them. It provides the structural backbone for evaluating composite functions and for computing gradients through automatic differentiation. Deep learning frameworks construct such graphs either statically ahead of execution or dynamically during the forward pass, then traverse them in reverse to propagate derivatives."@en ;
rdfs:label "Computational Graph"@en ;
rdfs:subClassOf ngm:automatic-differentiation ;
rdfs:subClassOf _:r5078 ;
rdfs:subClassOf _:r5079 ;
vc:bridgesTo ngm:deep-learning ;
vc:contrastsWith ngm:optimisation-algorithm ;
vc:dependsOn ngm:automatic-differentiation ;
vc:enables ngm:automatic-differentiation ;
vc:enables ngm:backpropagation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:loss-function ;
vc:implements ngm:deep-learning-framework ;
vc:isPartOf ngm:deep-learning-framework ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:gradient ;
vc:relatedTo ngm:neural-network ;
vc:requires ngm:tensor ;
vc:slug "computational-graph" ;
vc:sourceDomain "machine-learning" ;
vc:supports ngm:gradient-descent ;
vc:supports ngm:stochastic-gradient-descent ;
vc:uses ngm:tensor .
ngm:computational-graphs a skos:Concept ;
rdfs:label "Computational Graphs"@en .
ngm:computational-hardness-assumption a owl:Class ;
rdfs:comment "A computational hardness assumption is a conjecture that a particular mathematical problem cannot be solved efficiently by any probabilistic polynomial-time algorithm. Such assumptions, including integer factorisation, the discrete logarithm, and learning-with-errors, are the foundations on which provable security of cryptographic schemes is reduced. If an assumption is broken, every construction whose security reduces to it is compromised."@en ;
rdfs:label "Computational Hardness Assumption"@en ;
rdfs:subClassOf ngm:cryptographic-primitive ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:cryptography ;
vc:relatedTo ngm:digital-signature ;
vc:slug "computational-hardness-assumption" ;
vc:sourceDomain "security" .
ngm:computational-image-relighting-technique a owl:Class ;
rdfs:comment "Relighting is a computer graphics and generative AI technique that computationally alters the illumination of an existing image or video, repositioning or replacing light sources to produce a different lighting environment without re-capturing the scene. Modern approaches use neural rendering models trained on diverse lighting conditions, enabling portrait relighting, object relighting, and scene relighting from a single input image. Open-source workflows in tools such as ComfyUI implement IC-Light and similar diffusion-based pipelines that rival or exceed proprietary solutions."@en ;
rdfs:label "Computational Image Relighting Technique"@en ;
rdfs:subClassOf ngm:infra-computing-and-cloud ;
rdfs:subClassOf _:r5080 ;
skos:broader ngm:infra-computing-and-cloud ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.7"^^xsd:float ;
vc:relatedTo ngm:ai-video ;
vc:relatedTo ngm:control-net ;
vc:relatedTo ngm:differentiable-rendering ;
vc:relatedTo ngm:inpainting ;
vc:requires ngm:node-based-diffusion-pipeline-interface-workflows ;
vc:slug "computational-image-relighting-technique" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:diffusion-model ;
vc:uses ngm:neural-rendering ;
vc:uses ngm:physically-based-rendering .
ngm:computational-imaging a owl:Class ;
rdfs:comment "Computational imaging is the field that jointly designs image-capture hardware and reconstruction algorithms, using computation to recover visual information such as depth, motion, or scenes beyond conventional optics that a camera sensor alone cannot directly capture."@en ;
rdfs:label "Computational Imaging"@en ;
rdfs:subClassOf ngm:image-processing ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:slug "computational-imaging" ;
vc:sourceDomain "ai" .
ngm:computational-infrastructure a owl:Class ;
rdfs:comment "Computational infrastructure refers to the ensemble of physical and virtualised hardware resources, networking fabric, storage systems, and supporting services that provide the computational substrate upon which software workloads execute. It encompasses data centres, server clusters, GPUs, networking interconnects, and the orchestration layers that manage resource allocation, scheduling, and fault tolerance. In the context of AI and large-scale distributed systems, computational infrastructure determines the ceiling on model scale, training throughput, and inference latency, making it a strategic bottleneck as much as a technical one."@en ;
rdfs:label "Computational Infrastructure"@en ;
rdfs:subClassOf ngm:digital-infrastructure ;
rdfs:subClassOf _:r5081 ;
rdfs:subClassOf _:r5082 ;
rdfs:subClassOf _:r5083 ;
rdfs:subClassOf _:r5084 ;
rdfs:subClassOf _:r5085 ;
rdfs:subClassOf _:r5086 ;
rdfs:subClassOf _:r5087 ;
rdfs:subClassOf _:r5088 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:bridgesTo ngm:spatial-computing ;
vc:dependsOn ngm:cloud-computing ;
vc:dependsOn ngm:hyperscale-computing ;
vc:enables ngm:distributed-computing ;
vc:enables ngm:high-performance-computing ;
vc:enables ngm:model-training ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:cloud-infrastructure ;
vc:hasPart ngm:compute-resources ;
vc:hasPart ngm:data-centre ;
vc:hasPart ngm:gpu-computing ;
vc:hasPart ngm:networking-infrastructure ;
vc:hasPart ngm:storage-infrastructure ;
vc:qualityScore "0.7"^^xsd:float ;
vc:relatedTo ngm:compute-layer ;
vc:relatedTo ngm:computing-infrastructure ;
vc:relatedTo ngm:resource-scheduling ;
vc:requires ngm:cooling-system ;
vc:requires ngm:semiconductor-manufacturing ;
vc:slug "computational-infrastructure" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:ai-infrastructure ;
vc:supports ngm:blockchain-infrastructure ;
vc:supports ngm:edge-computing ;
vc:uses ngm:container-orchestration ;
vc:uses ngm:virtualisation .
ngm:computational-intelligence a owl:Class ;
rdfs:comment "Computational Intelligence (CI) is an umbrella field encompassing bio-inspired and nature-analogous algorithmic paradigms—principally neural networks, fuzzy logic, and evolutionary computation—that equip machines with adaptive, learning, and reasoning capabilities. Unlike classical symbolic AI, CI techniques tolerate imprecision, uncertainty, and partial truth, deriving solutions through iterative adaptation rather than explicit programming."@en ;
rdfs:label "Computational Intelligence"@en ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf ngm:applied-machine-learning ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf _:r5089 ;
rdfs:subClassOf _:r5090 ;
rdfs:subClassOf _:r5091 ;
rdfs:subClassOf _:r5092 ;
rdfs:subClassOf _:r5093 ;
rdfs:subClassOf _:r5094 ;
rdfs:subClassOf _:r5095 ;
rdfs:subClassOf _:r5096 ;
rdfs:subClassOf _:r5097 ;
rdfs:subClassOf _:r5098 ;
skos:broader ngm:ai-research-area ;
skos:broader ngm:artificial-intelligence ;
vc:contrastsWith ngm:classical-ai ;
vc:contrastsWith ngm:rule-based-systems ;
vc:contrastsWith ngm:symbolic-ai ;
vc:dependsOn ngm:backpropagation ;
vc:dependsOn ngm:optimisation-algorithm ;
vc:dependsOn ngm:reasoning ;
vc:dependsOn ngm:stochastic-gradient-descent ;
vc:dependsOn ngm:training-data ;
vc:enables ngm:autonomous-system ;
vc:enables ngm:control-system ;
vc:enables ngm:decision-support ;
vc:enables ngm:drug-discovery ;
vc:enables ngm:intelligent-automation ;
vc:enables ngm:machine-learning-discipline ;
vc:enables ngm:materials-discovery ;
vc:enables ngm:pattern-recognition ;
vc:enables ngm:predictive-analytics ;
vc:enables ngm:robotics ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:deep-reinforcement-learning ;
vc:hasPart ngm:evolutionary-algorithm ;
vc:hasPart ngm:fuzzy-logic ;
vc:hasPart ngm:genetic-algorithm ;
vc:hasPart ngm:neural-network ;
vc:hasPart ngm:neuro-fuzzy-system ;
vc:hasPart ngm:particle-swarm-optimisation ;
vc:hasPart ngm:swarm-intelligence ;
vc:implements ngm:convolutional-neural-network ;
vc:implements ngm:deep-learning ;
vc:implements ngm:deep-neural-network ;
vc:implements ngm:foundation-model ;
vc:implements ngm:large-language-models ;
vc:implements ngm:reinforcement-learning ;
vc:implements ngm:stochastic-gradient-descent ;
vc:implements ngm:transformer ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:adversarial-machine-learning ;
vc:relatedTo ngm:bayesian-deep-learning ;
vc:relatedTo ngm:cognitive-ai ;
vc:relatedTo ngm:cognitive-architecture ;
vc:relatedTo ngm:cognitive-science ;
vc:relatedTo ngm:computational-creativity ;
vc:relatedTo ngm:explainable-ai ;
vc:relatedTo ngm:fairness-in-machine-learning ;
vc:relatedTo ngm:knowledge-representation ;
vc:relatedTo ngm:reasoning ;
vc:relatedTo ngm:representation-learning ;
vc:requires ngm:backpropagation ;
vc:requires ngm:fitness-function ;
vc:requires ngm:membership-function ;
vc:requires ngm:optimisation-algorithm ;
vc:requires ngm:stochastic-gradient-descent ;
vc:requires ngm:training-data ;
vc:slug "computational-intelligence" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:iso-iec-22989-2022 ;
vc:supports ngm:applied-machine-learning ;
vc:supports ngm:computational-creativity ;
vc:supports ngm:computer-vision ;
vc:supports ngm:control-system ;
vc:supports ngm:drug-discovery ;
vc:supports ngm:explainable-ai ;
vc:supports ngm:natural-language-processing ;
vc:supports ngm:robotics ;
vc:uses ngm:attention-mechanism ;
vc:uses ngm:convolutional-neural-network ;
vc:uses ngm:deep-neural-network ;
vc:uses ngm:generative-ai ;
vc:uses ngm:large-language-models ;
vc:uses ngm:transformer .
ngm:computational-learning-theory a skos:Concept ;
rdfs:label "Computational Learning Theory"@en .
ngm:computational-linguistics a owl:Class ;
rdfs:comment "Computational Linguistics is the interdisciplinary study of language from a computational perspective, developing formal models and algorithms that enable computers to analyse, generate and understand human language. It draws on theoretical linguistics, computer science and statistics to model phenomena such as syntax, semantics and discourse. The field underpins practical natural language processing systems and provides the scientific grounding for language technologies."@en ;
rdfs:label "Computational Linguistics"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf ngm:natural-language-processing ;
rdfs:subClassOf _:r5099 ;
rdfs:subClassOf _:r5100 ;
rdfs:subClassOf _:r5101 ;
rdfs:subClassOf _:r5102 ;
rdfs:subClassOf _:r5103 ;
rdfs:subClassOf _:r5104 ;
rdfs:subClassOf _:r5105 ;
rdfs:subClassOf _:r5106 ;
rdfs:subClassOf _:r5107 ;
rdfs:subClassOf _:r5108 ;
skos:broader ngm:artificial-intelligence ;
vc:bridgesTo ngm:information-retrieval ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:contrastsWith ngm:psycholinguistics ;
vc:contrastsWith ngm:symbolic-ai ;
vc:dependsOn ngm:attention-mechanism ;
vc:dependsOn ngm:corpus-linguistics ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:language-model ;
vc:dependsOn ngm:pre-trained-language-model ;
vc:dependsOn ngm:transformer ;
vc:dependsOn ngm:word-embedding ;
vc:enables ngm:dialogue-systems ;
vc:enables ngm:knowledge-graph ;
vc:enables ngm:machine-translation ;
vc:enables ngm:natural-language-generation ;
vc:enables ngm:natural-language-understanding ;
vc:enables ngm:neural-machine-translation ;
vc:enables ngm:question-answering ;
vc:enables ngm:sentiment-analysis ;
vc:enables ngm:text-classification ;
vc:enables ngm:text-summarisation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:coreference-resolution ;
vc:hasPart ngm:dependency-parsing ;
vc:hasPart ngm:discourse-analysis ;
vc:hasPart ngm:named-entity-recognition ;
vc:hasPart ngm:part-of-speech-tagging ;
vc:hasPart ngm:relation-extraction ;
vc:hasPart ngm:semantic-parsing ;
vc:hasPart ngm:semantic-role-labelling ;
vc:hasPart ngm:text-classification ;
vc:hasPart ngm:tokenization ;
vc:hasPart ngm:word-sense-disambiguation ;
vc:implements ngm:cross-lingual-transfer ;
vc:implements ngm:discourse-analysis ;
vc:implements ngm:morphology ;
vc:implements ngm:phonology ;
vc:implements ngm:pragmatics ;
vc:implements ngm:semantics ;
vc:implements ngm:syntax ;
vc:isPartOf ngm:natural-language-processing ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:cognitive-science ;
vc:relatedTo ngm:corpus-linguistics ;
vc:relatedTo ngm:deep-learning ;
vc:relatedTo ngm:information-retrieval ;
vc:relatedTo ngm:knowledge-graph ;
vc:relatedTo ngm:large-language-model ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:psycholinguistics ;
vc:relatedTo ngm:representation-learning ;
vc:requires ngm:attention-mechanism ;
vc:requires ngm:corpus-linguistics ;
vc:requires ngm:grammar ;
vc:requires ngm:language-model ;
vc:requires ngm:linguistics ;
vc:requires ngm:word-embedding ;
vc:slug "computational-linguistics" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:association-for-computational-linguistics ;
vc:standardizedBy ngm:universal-dependencies ;
vc:supports ngm:automatic-speech-recognition ;
vc:supports ngm:information-retrieval ;
vc:supports ngm:knowledge-graph ;
vc:supports ngm:sequence-to-sequence-model ;
vc:supports ngm:speech-recognition ;
vc:supports ngm:text-mining ;
vc:supports ngm:uncertainty-quantification ;
vc:uses ngm:attention-mechanism ;
vc:uses ngm:fine-tuning ;
vc:uses ngm:language-model ;
vc:uses ngm:large-language-model ;
vc:uses ngm:pre-trained-language-model ;
vc:uses ngm:statistical-language-model ;
vc:uses ngm:transfer-learning ;
vc:uses ngm:transformer ;
vc:uses ngm:word-embedding .
ngm:computational-model a owl:Class ;
rdfs:comment "A computational model is a mathematical and algorithmic representation of a system that uses computing resources to simulate, predict, or analyse the system's behaviour under varying conditions. It encodes the entities, state variables, and governing rules of a phenomenon into executable form so that experiments can be run in silico rather than physically. Computational models underpin scientific simulation, engineering design, and the predictive components of spatial and physical computing."@en ;
rdfs:label "Computational Model"@en ;
rdfs:subClassOf ngm:simulation ;
rdfs:subClassOf _:r5109 ;
rdfs:subClassOf _:r5110 ;
rdfs:subClassOf _:r5111 ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:enables ngm:digital-twin ;
vc:enables ngm:physics-engine ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:computational-geometry ;
vc:implements ngm:algorithm ;
vc:isPartOf ngm:simulation ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:perception-system ;
vc:relatedTo ngm:simulation ;
vc:relatedTo ngm:spatial-computing ;
vc:requires ngm:algorithm ;
vc:requires ngm:computational-geometry ;
vc:slug "computational-model" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:autonomous-vehicle-testing ;
vc:uses ngm:algorithm .
ngm:computational-modelling a owl:Class ;
rdfs:comment "Computational Modelling is the use of mathematical formalisms implemented as computer programs to simulate the behaviour of real-world systems across domains such as physics, biology, economics, and climate science. A computational model translates theoretical assumptions into executable code so that hypotheses can be tested, predictions generated, and sensitivity analyses performed at scale. It forms the methodological backbone of simulation-based science and underpins modern AI training pipelines."@en ;
rdfs:label "Computational Modelling"@en ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf ngm:scientific-machine-learning ;
rdfs:subClassOf ngm:simulation ;
rdfs:subClassOf _:r5112 ;
rdfs:subClassOf _:r5113 ;
rdfs:subClassOf _:r5114 ;
rdfs:subClassOf _:r5115 ;
rdfs:subClassOf _:r5116 ;
rdfs:subClassOf _:r5117 ;
rdfs:subClassOf _:r5118 ;
rdfs:subClassOf _:r5119 ;
rdfs:subClassOf _:r5120 ;
rdfs:subClassOf _:r5121 ;
rdfs:subClassOf _:r5122 ;
rdfs:subClassOf _:r5123 ;
rdfs:subClassOf _:r5124 ;
rdfs:subClassOf _:r5125 ;
rdfs:subClassOf _:r5126 ;
skos:broader ngm:ai-research-area ;
skos:broader ngm:artificial-intelligence ;
vc:contrastsWith ngm:agent-based-modelling ;
vc:contrastsWith ngm:simulation ;
vc:dependsOn ngm:gpu-acceleration ;
vc:dependsOn ngm:graph-neural-network ;
vc:dependsOn ngm:operator-learning ;
vc:dependsOn ngm:physics-informed-neural-network ;
vc:dependsOn ngm:surrogate-model ;
vc:dependsOn ngm:transfer-learning ;
vc:enables ngm:climate-modelling ;
vc:enables ngm:collaborative-systems-modality-simulation ;
vc:enables ngm:computational-biology ;
vc:enables ngm:data-assimilation ;
vc:enables ngm:digital-twin ;
vc:enables ngm:epidemiological-modelling ;
vc:enables ngm:fluid-simulation ;
vc:enables ngm:protein-structure-prediction ;
vc:enables ngm:systems-biology ;
vc:enables ngm:time-series-forecasting ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:agent-based-modelling ;
vc:hasPart ngm:cellular-automata ;
vc:hasPart ngm:computational-fluid-dynamics ;
vc:hasPart ngm:data-assimilation ;
vc:hasPart ngm:finite-element-analysis ;
vc:hasPart ngm:molecular-dynamics ;
vc:hasPart ngm:monte-carlo-simulation ;
vc:hasPart ngm:numerical-methods ;
vc:hasPart ngm:sensitivity-analysis ;
vc:hasPart ngm:system-dynamics ;
vc:hasPart ngm:uncertainty-quantification ;
vc:implements ngm:bayesian-inference ;
vc:implements ngm:mathematical-optimisation ;
vc:implements ngm:physics-informed-neural-network ;
vc:implements ngm:probabilistic-modelling ;
vc:implements ngm:surrogate-model ;
vc:implements ngm:uncertainty-quantification ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:cellular-automata ;
vc:relatedTo ngm:collaborative-systems-modality-simulation ;
vc:relatedTo ngm:computational-biology ;
vc:relatedTo ngm:digital-twin ;
vc:relatedTo ngm:mathematical-optimisation ;
vc:relatedTo ngm:molecular-dynamics ;
vc:relatedTo ngm:probabilistic-modelling ;
vc:relatedTo ngm:scientific-machine-learning ;
vc:relatedTo ngm:stochastic-process ;
vc:requires ngm:differential-equations ;
vc:requires ngm:discretisation ;
vc:requires ngm:high-performance-computing ;
vc:requires ngm:linear-algebra ;
vc:requires ngm:mathematical-optimisation ;
vc:requires ngm:statistics ;
vc:requires ngm:stochastic-process ;
vc:slug "computational-modelling" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:siam ;
vc:supports ngm:complex-systems ;
vc:supports ngm:computational-biology ;
vc:supports ngm:deep-learning ;
vc:supports ngm:optimisation ;
vc:supports ngm:reinforcement-learning ;
vc:supports ngm:systems-biology ;
vc:uses ngm:bayesian-inference ;
vc:uses ngm:deep-learning ;
vc:uses ngm:gpu-acceleration ;
vc:uses ngm:graph-neural-network ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:neural-network ;
vc:uses ngm:operator-learning ;
vc:uses ngm:physics-informed-neural-network ;
vc:uses ngm:reinforcement-learning ;
vc:uses ngm:scientific-machine-learning ;
vc:uses ngm:surrogate-model ;
vc:uses ngm:transfer-learning .
ngm:computational-neuroscience a owl:Class ;
rdfs:comment "Computational neuroscience is the study of the nervous system through mathematical models, simulations, and information-processing theories that describe how neurons and neural circuits represent, compute, and learn. It spans biophysical models of single neurons, network models of population dynamics, and theories of coding, plasticity, and behaviour. The field both explains experimental data and inspires artificial neural and neuromorphic systems by clarifying the principles of biological computation."@en ;
rdfs:label "Computational Neuroscience"@en ;
rdfs:subClassOf ngm:cognitive-ai ;
rdfs:subClassOf ngm:cognitive-science ;
vc:bridgesTo ngm:deep-learning ;
vc:contrastsWith ngm:deep-learning ;
vc:dependsOn ngm:neural-network ;
vc:enables ngm:neuromorphic-computing ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:cognitive-science ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:cognitive-science ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:neural-network ;
vc:slug "computational-neuroscience" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:cognitive-architecture ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:reinforcement-learning .
ngm:computational-photography a owl:Class ;
rdfs:comment "A discipline that extends or supplants the optical and electromechanical capabilities of a camera system through digital computation, combining multiple sensor readings, learned priors, and algorithmic inference to produce images that no single physical exposure could yield. The field integrates optics, signal processing, machine learning, and human visual perception to reconstruct scene radiance, estimate scene geometry, and synthesise perceptually superior final images."@en ;
rdfs:label "Computational Photography"@en ;
rdfs:subClassOf ngm:computational-imaging ;
rdfs:subClassOf ngm:computer-vision ;
rdfs:subClassOf ngm:image-processing ;
rdfs:subClassOf _:r5127 ;
rdfs:subClassOf _:r5128 ;
rdfs:subClassOf _:r5129 ;
rdfs:subClassOf _:r5130 ;
rdfs:subClassOf _:r5131 ;
rdfs:subClassOf _:r5132 ;
rdfs:subClassOf _:r5133 ;
rdfs:subClassOf _:r5134 ;
rdfs:subClassOf _:r5135 ;
vc:contrastsWith ngm:image-processing ;
vc:contrastsWith ngm:optics ;
vc:contrastsWith ngm:traditional-film-photography ;
vc:dependsOn ngm:convolutional-neural-network ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:gpu-compute ;
vc:dependsOn ngm:image-sensor ;
vc:dependsOn ngm:optics ;
vc:enables ngm:3-d-reconstruction ;
vc:enables ngm:augmented-reality ;
vc:enables ngm:computer-vision ;
vc:enables ngm:depth-estimation ;
vc:enables ngm:face-detection ;
vc:enables ngm:medical-imaging ;
vc:enables ngm:satellite-imagery ;
vc:enables ngm:scene-understanding ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:bokeh-simulation ;
vc:hasPart ngm:demosaicing ;
vc:hasPart ngm:depth-estimation ;
vc:hasPart ngm:exposure-fusion ;
vc:hasPart ngm:hdr-imaging ;
vc:hasPart ngm:image-noise-reduction ;
vc:hasPart ngm:multi-frame-fusion ;
vc:hasPart ngm:neural-image-signal-processor ;
vc:hasPart ngm:night-mode-photography ;
vc:hasPart ngm:panorama-stitching ;
vc:hasPart ngm:semantic-segmentation ;
vc:hasPart ngm:super-resolution ;
vc:hasPart ngm:tone-mapping ;
vc:hasPart ngm:video-stabilisation ;
vc:implements ngm:colour-science ;
vc:implements ngm:convolutional-neural-network ;
vc:implements ngm:deep-learning ;
vc:implements ngm:generative-adversarial-network ;
vc:implements ngm:optical-flow ;
vc:implements ngm:signal-processing ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:3-d-reconstruction ;
vc:relatedTo ngm:computational-imaging ;
vc:relatedTo ngm:diffusion-model ;
vc:relatedTo ngm:face-detection ;
vc:relatedTo ngm:image-noise-reduction ;
vc:relatedTo ngm:image-segmentation ;
vc:relatedTo ngm:light-field-camera ;
vc:relatedTo ngm:ne-rf ;
vc:relatedTo ngm:plenoptic-camera ;
vc:relatedTo ngm:scene-understanding ;
vc:relatedTo ngm:video-stabilisation ;
vc:requires ngm:camera ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:image-formation-model ;
vc:requires ngm:image-sensor ;
vc:requires ngm:neural-network ;
vc:requires ngm:optics ;
vc:requires ngm:raw-image-pipeline ;
vc:requires ngm:signal-processing ;
vc:slug "computational-photography" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:c2-pa ;
vc:supports ngm:augmented-reality ;
vc:supports ngm:medical-imaging ;
vc:supports ngm:real-time-rendering ;
vc:supports ngm:smartphone ;
vc:uses ngm:diffusion-model ;
vc:uses ngm:generative-adversarial-network ;
vc:uses ngm:light-field-camera ;
vc:uses ngm:neural-network ;
vc:uses ngm:optical-flow ;
vc:uses ngm:plenoptic-camera ;
vc:uses ngm:super-resolution ;
vc:uses ngm:transformer-architecture .
ngm:computational-processing a skos:Concept ;
rdfs:label "Computational Processing"@en .
ngm:computational-puzzle a skos:Concept ;
rdfs:label "Computational Puzzle"@en .
ngm:computational-resources a owl:Class ;
rdfs:comment "Computational Resources denotes the aggregate hardware and software infrastructure — encompassing processors (CPUs, GPUs, NPUs, TPUs), memory hierarchies, storage systems, network fabrics, and associated middleware — that a computing system makes available to execute workloads. The capacity, performance characteristics, and allocation policies of these resources determine achievable throughput, latency, and quality of service across application domains from real-time simulation and AI inference to distributed data processing. Resource management disciplines — including scheduling, load balancing, virtualisation, and power efficiency — govern how competing workloads share finite physical capacity, making computational resources a foundational abstraction in systems design and infrastructure planning."@en ;
rdfs:label "Computational Resources"@en ;
rdfs:subClassOf ngm:computing-infrastructure ;
rdfs:subClassOf ngm:infrastructure ;
rdfs:subClassOf _:r5136 ;
rdfs:subClassOf _:r5137 ;
rdfs:subClassOf _:r5138 ;
rdfs:subClassOf _:r5139 ;
rdfs:subClassOf _:r5140 ;
rdfs:subClassOf _:r5141 ;
rdfs:subClassOf _:r5142 ;
rdfs:subClassOf _:r5143 ;
skos:broader ngm:infrastructure ;
vc:bridgesTo ngm:federated-learning ;
vc:bridgesTo ngm:neural-processing-unit ;
vc:contrastsWith ngm:bandwidth ;
vc:contrastsWith ngm:latency ;
vc:dependsOn ngm:operating-system ;
vc:dependsOn ngm:virtualisation ;
vc:enables ngm:artificial-intelligence ;
vc:enables ngm:cloud-computing ;
vc:enables ngm:digital-twin ;
vc:enables ngm:edge-computing ;
vc:enables ngm:extended-reality ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:central-processing-unit ;
vc:hasPart ngm:graphics-processing-unit ;
vc:hasPart ngm:memory-subsystem ;
vc:hasPart ngm:network-fabric ;
vc:hasPart ngm:neural-processing-unit ;
vc:hasPart ngm:storage-systems ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:load-balancing ;
vc:relatedTo ngm:optimisation ;
vc:relatedTo ngm:resource-scheduling ;
vc:relatedTo ngm:scalability ;
vc:requires ngm:hardware ;
vc:requires ngm:power-management ;
vc:slug "computational-resources" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:distributed-computing ;
vc:supports ngm:machine-learning-discipline ;
vc:supports ngm:rendering-engine ;
vc:supports ngm:simulation .
ngm:computational-security a skos:Concept ;
rdfs:label "Computational Security"@en .
ngm:computational-social-science a skos:Concept ;
rdfs:label "Computational Social Science"@en .
ngm:computational-statistics a skos:Concept ;
rdfs:label "Computational Statistics"@en .
ngm:computational-substrate a skos:Concept ;
rdfs:label "Computational Substrate"@en .
ngm:computational-sustainability a skos:Concept ;
rdfs:label "Computational Sustainability"@en .
ngm:computational-theory-of-mind a skos:Concept ;
rdfs:label "Computational Theory Of Mind"@en .
ngm:computational-universality a skos:Concept ;
rdfs:label "Computational Universality"@en .
ngm:computationalmethods a skos:Concept ;
rdfs:label "Computationalmethods"@en .
ngm:computationalpower a skos:Concept ;
rdfs:label "Computationalpower"@en .
ngm:computationalthroughput a skos:Concept ;
rdfs:label "Computationalthroughput"@en .
ngm:computationandintelligencedomain a skos:Concept ;
rdfs:label "Computationandintelligencedomain"@en .
ngm:compute-access a skos:Concept ;
rdfs:label "Compute Access"@en .
ngm:compute-budget a skos:Concept ;
rdfs:label "Compute Budget"@en .
ngm:compute-cluster a owl:Class ;
rdfs:comment "A compute cluster is a collection of interconnected computers that work together as a single system to execute large or parallel workloads. Nodes are coordinated by a scheduler that allocates jobs across processors, accelerators, and memory, sharing high-speed networking and often a common storage fabric. Clusters underpin large-scale model training, simulation, and data processing where a single machine cannot supply enough compute."@en ;
rdfs:label "Compute Cluster"@en ;
rdfs:subClassOf ngm:high-performance-computing ;
rdfs:subClassOf _:r5144 ;
rdfs:subClassOf _:r5145 ;
rdfs:subClassOf _:r5146 ;
vc:dependsOn ngm:cloud-computing ;
vc:dependsOn ngm:data-centre ;
vc:enables ngm:distributed-training ;
vc:enables ngm:model-training ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:high-performance-computing ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-centre ;
vc:relatedTo ngm:deep-learning ;
vc:relatedTo ngm:distributed-computing ;
vc:requires ngm:gpu ;
vc:requires ngm:resource-management ;
vc:requires ngm:scheduler ;
vc:slug "compute-cluster" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:batch-processing ;
vc:supports ngm:mlops ;
vc:uses ngm:kubernetes ;
vc:uses ngm:parallel-computing .
ngm:compute-democratisation a skos:Concept ;
rdfs:label "Compute Democratisation"@en .
ngm:compute-divide a skos:Concept ;
rdfs:label "Compute Divide"@en .
ngm:compute-exchange a skos:Concept ;
rdfs:label "Compute Exchange"@en .
ngm:compute-governance a owl:Class ;
rdfs:comment "Compute governance is the set of policies, controls, and oversight mechanisms applied to the large-scale computing hardware used to train and deploy advanced AI systems. Because frontier AI capability is tightly coupled to access to specialised accelerators, governing compute offers a measurable, supply-chain-anchored lever for AI policy. Mechanisms include export controls, usage reporting thresholds, and on-chip verification of training runs."@en ;
rdfs:label "Compute Governance"@en ;
rdfs:subClassOf ngm:ai-governance ;
rdfs:subClassOf _:r5147 ;
rdfs:subClassOf _:r5148 ;
rdfs:subClassOf _:r5149 ;
rdfs:subClassOf _:r5150 ;
vc:bridgesTo ngm:infrastructure ;
vc:bridgesTo ngm:security ;
vc:bridgesTo ngm:supply-chain ;
vc:contrastsWith ngm:algorithmic-governance ;
vc:contrastsWith ngm:data-governance ;
vc:dependsOn ngm:cloud-computing ;
vc:dependsOn ngm:gpu-cluster ;
vc:dependsOn ngm:hardware-security-module ;
vc:enables ngm:ai-safety ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:export-controls ;
vc:implements ngm:ai-policy ;
vc:implements ngm:export-controls ;
vc:qualityScore "0.73"^^xsd:float ;
vc:relatedTo ngm:ai-risks ;
vc:relatedTo ngm:competition-in-ai ;
vc:relatedTo ngm:large-language-model ;
vc:requires ngm:international-cooperation ;
vc:requires ngm:kyc ;
vc:requires ngm:semiconductor-supply-chain ;
vc:slug "compute-governance" ;
vc:sourceDomain "governance" ;
vc:supports ngm:ai-risk-management ;
vc:supports ngm:responsible-ai ;
vc:uses ngm:cryptographic-verification ;
vc:uses ngm:tee .
ngm:compute-infrastructure a owl:Class ;
rdfs:comment "Compute Infrastructure in the artificial intelligence era denotes the integrated stack of accelerated silicon, high-bandwidth interconnect fabrics, multi-megawatt power and cooling plant, and orchestration software that hosts the training and inference of frontier neural-network models at ind..."@en ;
rdfs:label "Compute Infrastructure"@en ;
rdfs:subClassOf ngm:computing-infrastructure ;
rdfs:subClassOf ngm:critical-national-infrastructure ;
rdfs:subClassOf ngm:data-centre ;
rdfs:subClassOf ngm:infra-computing-and-cloud ;
rdfs:subClassOf ngm:infrastructure ;
rdfs:subClassOf _:r5151 ;
rdfs:subClassOf _:r5152 ;
rdfs:subClassOf _:r5153 ;
rdfs:subClassOf _:r5154 ;
rdfs:subClassOf _:r5155 ;
rdfs:subClassOf _:r5156 ;
rdfs:subClassOf _:r5157 ;
rdfs:subClassOf _:r5158 ;
rdfs:subClassOf _:r5159 ;
rdfs:subClassOf _:r5160 ;
rdfs:subClassOf _:r5161 ;
rdfs:subClassOf _:r5162 ;
rdfs:subClassOf _:r5163 ;
skos:broader ngm:infra-computing-and-cloud ;
skos:broader ngm:infrastructure ;
vc:contrastsWith ngm:classical-cloud-compute ;
vc:contrastsWith ngm:cpu-centric-datacentre ;
vc:contrastsWith ngm:edge-inference ;
vc:contrastsWith ngm:fp64-optimised-hpc ;
vc:contrastsWith ngm:traditional-hpc ;
vc:dependsOn ngm:cuda ;
vc:dependsOn ngm:electrical-grid ;
vc:dependsOn ngm:hbm-supply ;
vc:dependsOn ngm:optical-networking ;
vc:dependsOn ngm:rocm ;
vc:dependsOn ngm:semiconductor-manufacturing ;
vc:dependsOn ngm:tsmc ;
vc:enables ngm:ai-factory ;
vc:enables ngm:distributed-system ;
vc:enables ngm:foundation-model-inference ;
vc:enables ngm:generative-ai ;
vc:enables ngm:large-language-model-training ;
vc:enables ngm:scientific-simulation ;
vc:enables ngm:sovereign-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:asic ;
vc:hasPart ngm:datacentre-network ;
vc:hasPart ngm:gpu-accelerator ;
vc:hasPart ngm:high-bandwidth-memory ;
vc:hasPart ngm:infiniband ;
vc:hasPart ngm:liquid-cooling ;
vc:hasPart ngm:nvlink ;
vc:hasPart ngm:orchestration-layer ;
vc:hasPart ngm:power-distribution ;
vc:hasPart ngm:spectrum-x ;
vc:hasPart ngm:storage-systems ;
vc:implements ngm:collective-communication ;
vc:implements ngm:expert-parallelism ;
vc:implements ngm:mixed-precision-arithmetic ;
vc:implements ngm:model-parallelism ;
vc:implements ngm:pipeline-parallelism ;
vc:implements ngm:tensor-computation ;
vc:implements ngm:tensor-parallelism ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:ai-companies ;
vc:relatedTo ngm:ai-supply-chain ;
vc:relatedTo ngm:cloud-computing ;
vc:relatedTo ngm:hyperscaler ;
vc:relatedTo ngm:nuclear-energy ;
vc:relatedTo ngm:power-grid ;
vc:relatedTo ngm:sovereign-ai ;
vc:requires ngm:cooling-capacity ;
vc:requires ngm:cowos-packaging ;
vc:requires ngm:electrical-power ;
vc:requires ngm:high-bandwidth-memory ;
vc:requires ngm:network-fabric ;
vc:requires ngm:semiconductor-supply-chain ;
vc:requires ngm:skilled-operators ;
vc:slug "compute-infrastructure" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:infiniband-trade-association ;
vc:standardizedBy ngm:mlcommons ;
vc:standardizedBy ngm:open-compute-project ;
vc:standardizedBy ngm:ualink-consortium ;
vc:standardizedBy ngm:ultra-ethernet-consortium ;
vc:supports ngm:autonomous-system ;
vc:supports ngm:climate-modelling ;
vc:supports ngm:drug-discovery ;
vc:supports ngm:frontier-model-training ;
vc:supports ngm:inference-serving ;
vc:supports ngm:scientific-computing ;
vc:supports ngm:sovereign-research ;
vc:uses ngm:direct-current-distribution ;
vc:uses ngm:floating-point-arithmetic ;
vc:uses ngm:fp8-arithmetic ;
vc:uses ngm:gpudirect ;
vc:uses ngm:hbm3e ;
vc:uses ngm:liquid-cooling ;
vc:uses ngm:rdma .
ngm:compute-layer a owl:Class ;
rdfs:comment "Software layer managing computational resources and orchestration for rendering, simulation, physics, AI processing, and real-time processing within metaverse systems."@en ;
rdfs:label "Compute Layer"@en ;
rdfs:subClassOf ngm:infra-computing-and-cloud ;
rdfs:subClassOf _:r5164 ;
rdfs:subClassOf _:r5165 ;
rdfs:subClassOf _:r5166 ;
rdfs:subClassOf _:r5167 ;
rdfs:subClassOf _:r5168 ;
rdfs:subClassOf _:r5169 ;
rdfs:subClassOf _:r5170 ;
rdfs:subClassOf _:r5171 ;
rdfs:subClassOf _:r5172 ;
rdfs:subClassOf _:r5173 ;
skos:broader ngm:infra-computing-and-cloud ;
vc:bridgesTo ngm:computer-vision ;
vc:dependsOn ngm:container-orchestration ;
vc:dependsOn ngm:load-balancer ;
vc:dependsOn ngm:resource-scheduler ;
vc:enables ngm:ai-inference ;
vc:enables ngm:distributed-computing ;
vc:enables ngm:edge-computing ;
vc:enables ngm:physics-simulation ;
vc:enables ngm:real-time-rendering ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ai-processing-service ;
vc:hasPart ngm:compute-infrastructure ;
vc:hasPart ngm:experience-layer ;
vc:hasPart ngm:physics-engine ;
vc:hasPart ngm:rendering-engine ;
vc:hasPart ngm:simulation-engine ;
vc:isPartOf ngm:metaverse-architecture-stack ;
vc:isPartOf ngm:metaverse-stack ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:data-storage-layer ;
vc:requires ngm:gpu-resources ;
vc:requires ngm:network-infrastructure ;
vc:requires ngm:processing-hardware ;
vc:slug "compute-layer" ;
vc:sourceDomain "infrastructure" .
ngm:compute-optimal-training a skos:Concept ;
rdfs:label "Compute Optimal Training"@en .
ngm:compute-power a skos:Concept ;
rdfs:label "Compute Power"@en .
ngm:compute-resources a owl:Class ;
rdfs:comment "Compute resources are the aggregate processing capacity available to execute computational workloads, encompassing CPUs, GPUs, specialised accelerators (TPUs, NPUs), memory, network bandwidth, and associated storage I/O. They are quantified by metrics such as FLOPS, memory bandwidth, core count, and clock speed, and are provisioned via physical hardware, virtualised cloud instances, or serverless functions. Effective allocation and scheduling of compute resources is the foundational concern of cloud computing, high-performance computing, and AI infrastructure."@en ;
rdfs:label "Compute Resources"@en ;
rdfs:subClassOf ngm:computational-resources ;
rdfs:subClassOf ngm:infra-computing-and-cloud ;
rdfs:subClassOf _:r5174 ;
rdfs:subClassOf _:r5175 ;
rdfs:subClassOf _:r5176 ;
rdfs:subClassOf _:r5177 ;
rdfs:subClassOf _:r5178 ;
rdfs:subClassOf _:r5179 ;
rdfs:subClassOf _:r5180 ;
skos:broader ngm:infra-computing-and-cloud ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:contrastsWith ngm:edge-computing ;
vc:dependsOn ngm:virtualisation ;
vc:enables ngm:distributed-training ;
vc:enables ngm:gpu-computing ;
vc:enables ngm:high-performance-computing ;
vc:enables ngm:inference ;
vc:enables ngm:model-training ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:compute-layer ;
vc:hasPart ngm:cpu ;
vc:hasPart ngm:gpu-resources ;
vc:hasPart ngm:memory-bandwidth ;
vc:hasPart ngm:network-bandwidth ;
vc:isPartOf ngm:cloud-computing ;
vc:isPartOf ngm:data-centre ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:ai-infrastructure ;
vc:relatedTo ngm:resource-allocation ;
vc:requires ngm:cooling-system ;
vc:requires ngm:power-infrastructure ;
vc:slug "compute-resources" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:containerisation ;
vc:supports ngm:workload-scheduling .
ngm:compute-scaling a skos:Concept ;
rdfs:label "Compute Scaling"@en .
ngm:compute-shader a owl:Class ;
rdfs:comment "A Compute Shader is a programmable GPU kernel that executes arbitrary parallel computations outside the traditional graphics rendering pipeline, enabling general-purpose GPU (GPGPU) workloads such as physics simulation, procedural generation, image post-processing, and data-parallel algorithms within real-time 3D and metaverse applications."@en ;
rdfs:label "Compute Shader"@en ;
rdfs:subClassOf ngm:metaverse ;
rdfs:subClassOf ngm:sc-display-and-rendering ;
rdfs:subClassOf _:r5181 ;
rdfs:subClassOf _:r5182 ;
rdfs:subClassOf _:r5183 ;
rdfs:subClassOf _:r5184 ;
skos:broader ngm:sc-display-and-rendering ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:inference ;
vc:contrastsWith ngm:cpu-computing ;
vc:dependsOn ngm:parallel-computing ;
vc:enables ngm:gpu-driven-rendering ;
vc:enables ngm:physics-simulation ;
vc:enables ngm:post-processing ;
vc:enables ngm:procedural-generation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:pixel-shader ;
vc:hasPart ngm:vertex-shader ;
vc:qualityScore "0.68"^^xsd:float ;
vc:relatedTo ngm:cuda ;
vc:relatedTo ngm:opencl ;
vc:requires ngm:graphics-processing-unit ;
vc:requires ngm:shader-compiler ;
vc:slug "compute-shader" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:vulkan ;
vc:standardizedBy ngm:webgpu ;
vc:uses ngm:hlsl ;
vc:uses ngm:parallel-processing ;
vc:uses ngm:real-time-rendering .
ngm:compute-soc a skos:Concept ;
rdfs:label "Compute Soc"@en .
ngm:compute-threshold a skos:Concept ;
rdfs:label "Compute Threshold"@en .
ngm:compute-trends a skos:Concept ;
rdfs:label "Compute Trends"@en .
ngm:computed-torque-control a owl:Class ;
rdfs:comment "Computed torque control is a model-based robot control method that uses the inverse dynamics of the manipulator to cancel nonlinear coupling and gravity terms, linearising the closed-loop behaviour. The controller computes the joint torques required to achieve a desired acceleration, then adds a linear feedback term to correct tracking error. It enables high-accuracy trajectory following at the cost of requiring an accurate dynamic model."@en ;
rdfs:label "Computed Torque Control"@en ;
rdfs:subClassOf ngm:robo-actuation-and-control ;
skos:broader ngm:robo-actuation-and-control ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:force-control ;
vc:relatedTo ngm:motion-control ;
vc:slug "computed-torque-control" ;
vc:sourceDomain "robotics" .
ngm:computer-aided-design a owl:Class ;
rdfs:comment "Computer Aided Design is the use of software to create, modify, analyse and document precise two- and three-dimensional geometric models of physical products and structures. CAD systems support parametric and direct modelling, assemblies, drafting and engineering analysis, forming the digital foundation for manufacturing and robotics. They produce the geometry and tolerances that downstream simulation, fabrication and inspection processes consume."@en ;
rdfs:label "Computer Aided Design"@en ;
rdfs:subClassOf ngm:robotics ;
rdfs:subClassOf ngm:software-engineering ;
skos:broader ngm:robotics ;
vc:bridgesTo ngm:advanced-manufacturing ;
vc:dependsOn ngm:3d-modelling ;
vc:enables ngm:digital-twin ;
vc:enables ngm:rapid-prototyping ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:specification ;
vc:isPartOf ngm:advanced-manufacturing ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:collision-detection ;
vc:relatedTo ngm:simulation ;
vc:slug "computer-aided-design" ;
vc:sourceDomain "robotics" ;
vc:supports ngm:digital-twin ;
vc:supports ngm:rapid-prototyping ;
vc:uses ngm:3d-modelling .
ngm:computer-aided-diagnosis a skos:Concept ;
rdfs:label "Computer Aided Diagnosis"@en .
ngm:computer-aided-drug-design a skos:Concept ;
rdfs:label "Computer Aided Drug Design"@en .
ngm:computer-animation a skos:Concept ;
rdfs:label "Computer Animation"@en .
ngm:computer-architecture a skos:Concept ;
rdfs:label "Computer Architecture"@en .
ngm:computer-generated-holography a skos:Concept ;
rdfs:label "Computer Generated Holography"@en .
ngm:computer-graphics a owl:Class ;
rdfs:comment "Computer Graphics is the computational discipline concerned with synthesising, manipulating, and displaying visual imagery using mathematical models and algorithms running on specialised hardware. It encompasses the full pipeline from scene representation—geometry, materials, lighting—through rasterisation or ray-tracing renderers, shading languages, and GPU-accelerated display systems. As the enabling layer for all visual digital experiences, it underpins spatial computing, interactive media, simulation, scientific visualisation, and metaverse infrastructure. The field spans real-time and offline rendering paradigms, blending applied mathematics, physics-based light transport, and hardware architecture."@en ;
rdfs:label "Computer Graphics"@en ;
rdfs:subClassOf ngm:sc-display-and-rendering ;
rdfs:subClassOf _:r5185 ;
rdfs:subClassOf _:r5186 ;
rdfs:subClassOf _:r5187 ;
rdfs:subClassOf _:r5188 ;
rdfs:subClassOf _:r5189 ;
rdfs:subClassOf _:r5190 ;
rdfs:subClassOf _:r5191 ;
rdfs:subClassOf _:r5192 ;
rdfs:subClassOf _:r5193 ;
skos:broader ngm:sc-display-and-rendering ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:neural-rendering ;
vc:contrastsWith ngm:image-processing ;
vc:enables ngm:3-d-animation ;
vc:enables ngm:augmented-reality ;
vc:enables ngm:digital-twin ;
vc:enables ngm:level-of-detail ;
vc:enables ngm:scientific-visualisation ;
vc:enables ngm:virtual-reality ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:global-illumination ;
vc:hasPart ngm:rasterization ;
vc:hasPart ngm:ray-tracing ;
vc:hasPart ngm:rendering-pipeline ;
vc:hasPart ngm:shader ;
vc:hasPart ngm:texture-mapping ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:physically-based-rendering ;
vc:relatedTo ngm:spatial-computing ;
vc:requires ngm:3-d-geometry ;
vc:requires ngm:gpu ;
vc:requires ngm:linear-algebra ;
vc:slug "computer-graphics" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:khronos-group ;
vc:standardizedBy ngm:siggraph ;
vc:uses ngm:game-engine ;
vc:uses ngm:open-gl ;
vc:uses ngm:vulkan ;
vc:uses ngm:webgpu .
ngm:computer-hardware a owl:Class ;
rdfs:comment "Physical computing components optimised for artificial intelligence and spatial computing workloads, encompassing GPUs, TPUs, FPGAs, ASICs, and neuromorphic chips. Modern AI hardware emphasises parallel matrix processing, high-bandwidth memory, mixed-precision arithmetic, and energy-efficient inference at scale, enabling both large-model training and real-time rendering in immersive applications."@en ;
rdfs:label "Computer Hardware"@en ;
rdfs:subClassOf ngm:ai-infrastructure ;
vc:enables ngm:deep-learning ;
vc:enables ngm:gpu-compute ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:distributed-computing ;
vc:relatedTo ngm:training ;
vc:slug "computer-hardware" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:autonomous-robot ;
vc:supports ngm:digital-twin ;
vc:uses ngm:hardware-acceleration .
ngm:computer-laboratory a skos:Concept ;
rdfs:label "Computer Laboratory"@en .
ngm:computer-network-exploitation a skos:Concept ;
rdfs:label "Computer Network Exploitation"@en .
ngm:computer-network-operations-doctrine a skos:Concept ;
rdfs:label "Computer Network Operations Doctrine"@en .
ngm:computer-networks a skos:Concept ;
rdfs:label "Computer Networks"@en .
ngm:computer-numerical-control a skos:Concept ;
rdfs:label "Computer Numerical Control"@en .
ngm:computer-science a owl:Class ;
rdfs:comment "Computer science is the systematic study of computation, algorithms, data structures, programming languages, and the principles underlying the design and analysis of computing systems. It encompasses both theoretical foundations — including computability theory, computational complexity, formal languages, and logic — and applied disciplines such as software engineering, artificial intelligence, databases, and computer networks. As a rigorous scientific and engineering discipline, it provides the intellectual and practical frameworks for building reliable, efficient, and scalable digital systems. Computer science intersects with mathematics, electrical engineering, cognitive science, and the natural sciences, and it underpins virtually every domain of modern technological infrastructure."@en ;
rdfs:label "Computer Science"@en ;
rdfs:subClassOf ngm:software-engineering ;
rdfs:subClassOf _:r5194 ;
rdfs:subClassOf _:r5195 ;
rdfs:subClassOf _:r5196 ;
rdfs:subClassOf _:r5197 ;
rdfs:subClassOf _:r5198 ;
rdfs:subClassOf _:r5199 ;
rdfs:subClassOf _:r5200 ;
rdfs:subClassOf _:r5201 ;
rdfs:subClassOf _:r5202 ;
rdfs:subClassOf _:r5203 ;
rdfs:subClassOf _:r5204 ;
rdfs:subClassOf _:r5205 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:robotics ;
vc:bridgesTo ngm:spatial-computing ;
vc:enables ngm:artificial-intelligence ;
vc:enables ngm:cybersecurity ;
vc:enables ngm:distributed-systems ;
vc:enables ngm:software-engineering ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:algorithms ;
vc:hasPart ngm:computability-theory ;
vc:hasPart ngm:computational-complexity-theory ;
vc:hasPart ngm:computer-networks ;
vc:hasPart ngm:data-structure ;
vc:hasPart ngm:database-systems ;
vc:hasPart ngm:operating-system ;
vc:hasPart ngm:programming-language ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:human-computer-interaction ;
vc:relatedTo ngm:information-theory ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:requires ngm:discrete-mathematics ;
vc:requires ngm:logic ;
vc:slug "computer-science" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:acm ;
vc:standardizedBy ngm:ieee ;
vc:uses ngm:formal-methods ;
vc:uses ngm:type-theory .
ngm:computer-science-curriculum a skos:Concept ;
rdfs:label "Computer Science Curriculum"@en .
ngm:computer-supported-cooperative-work a owl:Class ;
rdfs:comment "Computer-Supported Cooperative Work (CSCW) is the interdisciplinary research field that studies how people work together using computer systems and how to design technology that supports their collaboration. It examines coordination, communication, awareness and the social organisation of group work across time and space, informing the design of groupware and collaborative tools. CSCW bridges human-computer interaction, the social sciences and distributed-systems engineering."@en ;
rdfs:label "Computer-Supported Cooperative Work"@en ;
rdfs:subClassOf ngm:dc-workspace-tools ;
rdfs:subClassOf ngm:distributed-collaboration ;
rdfs:subClassOf _:r5246 ;
rdfs:subClassOf _:r5247 ;
skos:broader ngm:dc-workspace-tools ;
skos:broader ngm:distributed-collaboration ;
vc:bridgesTo ngm:human-computer-interaction ;
vc:enables ngm:remote-collaboration ;
vc:enables ngm:shared-workspace ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:awareness ;
vc:hasPart ngm:presence ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:crdt ;
vc:relatedTo ngm:distributed-collaboration ;
vc:slug "computer-supported-cooperative-work" ;
vc:sourceDomain "distributed-collaboration" ;
vc:supports ngm:collaboration ;
vc:supports ngm:remote-work ;
vc:uses ngm:synchronisation .
ngm:computer-use a owl:Class ;
rdfs:comment "Computer Use is an AI capability that enables multimodal models to perceive, navigate, and interact with graphical user interfaces, desktop applications, and operating system environments to autonomously complete multi-step tasks. The model receives screenshot observations of the screen and emits mouse-click, keyboard, and scroll actions, effectively operating software as a human operator would. It extends conventional tool-use paradigms by treating the entire GUI surface as an action space rather than a structured API."@en ;
rdfs:label "Computer Use"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf _:r5224 ;
rdfs:subClassOf _:r5225 ;
skos:broader ngm:ai-application ;
vc:enables ngm:autonomous-agent ;
vc:enables ngm:workflow-automation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:interface ;
vc:requires ngm:multimodal-ai-architecture ;
vc:requires ngm:tool-use ;
vc:slug "computer-use" ;
vc:sourceDomain "artificial-intelligence" .
ngm:computer-use-and-browser-agents a owl:Class ;
rdfs:comment "Computer Use and Browser Agents are a class of agentic AI systems that operate graphical user interfaces, web browsers, and operating systems by perceiving the screen through vision-language models (VLMs), planning actions in natural language, and emitting low-level input events (mouse coordinate..."@en ;
rdfs:label "Computer Use and Browser Agents"@en ;
rdfs:subClassOf ngm:agents ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:autonomous-system ;
rdfs:subClassOf ngm:cognitive-architecture ;
rdfs:subClassOf ngm:intelligent-system ;
rdfs:subClassOf ngm:multimodal-ai-architecture-ai ;
rdfs:subClassOf _:r5206 ;
rdfs:subClassOf _:r5207 ;
rdfs:subClassOf _:r5208 ;
rdfs:subClassOf _:r5209 ;
rdfs:subClassOf _:r5210 ;
rdfs:subClassOf _:r5211 ;
rdfs:subClassOf _:r5212 ;
rdfs:subClassOf _:r5213 ;
rdfs:subClassOf _:r5214 ;
rdfs:subClassOf _:r5215 ;
rdfs:subClassOf _:r5216 ;
rdfs:subClassOf _:r5217 ;
rdfs:subClassOf _:r5218 ;
rdfs:subClassOf _:r5219 ;
rdfs:subClassOf _:r5220 ;
rdfs:subClassOf _:r5221 ;
rdfs:subClassOf _:r5222 ;
rdfs:subClassOf _:r5223 ;
skos:broader ngm:ai-application ;
vc:bridgesTo ngm:cognitive-architecture ;
vc:bridgesTo ngm:intelligent-systems ;
vc:contrastsWith ngm:api-only-agent ;
vc:contrastsWith ngm:browser-plugin ;
vc:contrastsWith ngm:chatbot ;
vc:contrastsWith ngm:digital-assistant-siri-alexa ;
vc:contrastsWith ngm:robotic-process-automation ;
vc:contrastsWith ngm:static-inference-pipeline ;
vc:contrastsWith ngm:workflow-automation ;
vc:dependsOn ngm:chrome-devtools-protocol ;
vc:dependsOn ngm:constitutional-ai-training-methodology ;
vc:dependsOn ngm:multimodal-foundation-model ;
vc:dependsOn ngm:playwright ;
vc:dependsOn ngm:reinforcement-learning-from-human-feedback ;
vc:dependsOn ngm:selenium ;
vc:dependsOn ngm:transformer-architecture ;
vc:dependsOn ngm:webdriver-bidi ;
vc:enables ngm:agentic-internet ;
vc:enables ngm:agentic-workflow ;
vc:enables ngm:automation ;
vc:enables ngm:autonomous-task-execution ;
vc:enables ngm:browser-automation ;
vc:enables ngm:computer-use ;
vc:enables ngm:end-to-end-ui-testing ;
vc:enables ngm:visual-web-research ;
vc:enables ngm:web-navigation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:accessibility-tree ;
vc:hasPart ngm:action-executor ;
vc:hasPart ngm:planning-module ;
vc:hasPart ngm:reasoning-trace ;
vc:hasPart ngm:reflection-loop ;
vc:hasPart ngm:screen-capture ;
vc:hasPart ngm:set-of-mark-prompting ;
vc:hasPart ngm:tool-schema ;
vc:hasPart ngm:virtual-machine-sandbox ;
vc:hasPart ngm:vision-language-model ;
vc:implements ngm:chain-of-thought ;
vc:implements ngm:plan-and-execute ;
vc:implements ngm:re-act ;
vc:implements ngm:reflexion ;
vc:implements ngm:screen2tree-parsing ;
vc:implements ngm:set-of-mark-prompting ;
vc:implements ngm:visual-grounding ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:agents ;
vc:relatedTo ngm:ai-alignment ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:embodied-ai ;
vc:relatedTo ngm:multi-agent-system ;
vc:relatedTo ngm:prompt-injection ;
vc:relatedTo ngm:tool-augmented-llm ;
vc:relatedTo ngm:web-scraping ;
vc:requires ngm:browser-engine ;
vc:requires ngm:display-server ;
vc:requires ngm:foundation-model ;
vc:requires ngm:function-calling ;
vc:requires ngm:human-oversight ;
vc:requires ngm:inference-compute ;
vc:requires ngm:large-scale-pretrained-foundation-model ;
vc:requires ngm:operating-system ;
vc:requires ngm:tool-definition ;
vc:requires ngm:vision-language-model ;
vc:slug "computer-use-and-browser-agents" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:agent2-agent-protocol-google-2025 ;
vc:standardizedBy ngm:chrome-dev-tools-protocol ;
vc:standardizedBy ngm:chrome-devtools-protocol ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument-article-50 ;
vc:standardizedBy ngm:model-context-protocol-anthropic-2024 ;
vc:standardizedBy ngm:owasp-llm-top-10-2025 ;
vc:standardizedBy ngm:webdriver-bidi-w3c-2024 ;
vc:supports ngm:accessibility ;
vc:supports ngm:customer-service-automation ;
vc:supports ngm:deep-research ;
vc:supports ngm:enterprise-workflow ;
vc:supports ngm:personal-assistance ;
vc:supports ngm:quality-assurance ;
vc:supports ngm:software-development-automation ;
vc:supports ngm:web-scraping ;
vc:uses ngm:accessibility-tree ;
vc:uses ngm:agent2-agent-protocol ;
vc:uses ngm:function-schemas ;
vc:uses ngm:model-context-protocol ;
vc:uses ngm:ocr ;
vc:uses ngm:open-cv ;
vc:uses ngm:screenshot ;
vc:uses ngm:vision-language-model .
ngm:computer-vision a owl:Class ;
rdfs:comment "Computer Vision is the field of artificial intelligence concerned with enabling machines to interpret, understand, and process visual information from the world, emulating human visual perception capabilities."@en ;
rdfs:label "Computer Vision"@en ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf _:r5238 ;
rdfs:subClassOf _:r5239 ;
rdfs:subClassOf _:r5240 ;
rdfs:subClassOf _:r5241 ;
rdfs:subClassOf _:r5242 ;
rdfs:subClassOf _:r5243 ;
rdfs:subClassOf _:r5244 ;
rdfs:subClassOf _:r5245 ;
skos:broader ngm:ai-research-area ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:io-t-sensors ;
vc:bridgesTo ngm:robotics ;
vc:dependsOn ngm:convolutional-neural-network ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:neural-network ;
vc:enables ngm:autonomous-navigation ;
vc:enables ngm:medical-imaging-ai ;
vc:enables ngm:quality-control ;
vc:enables ngm:robotics-perception ;
vc:enables ngm:surveillance-systems ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:3-d-reconstruction ;
vc:hasPart ngm:image-classification ;
vc:hasPart ngm:motion-tracking ;
vc:hasPart ngm:object-detection ;
vc:hasPart ngm:semantic-segmentation ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:feature-extraction ;
vc:requires ngm:image-processing ;
vc:requires ngm:pattern-recognition ;
vc:slug "computer-vision" ;
vc:sourceDomain "artificial-intelligence" .
ngm:computer-vision-algorithms a skos:Concept ;
rdfs:label "Computer Vision Algorithms"@en .
ngm:computer-vision-benchmarks a skos:Concept ;
rdfs:label "Computer Vision Benchmarks"@en .
ngm:computer-vision-domain a skos:Concept ;
rdfs:label "Computer Vision Domain"@en .
ngm:computer-vision-foundation a skos:Concept ;
rdfs:label "Computer Vision Foundation"@en .
ngm:computer-vision-pipeline a skos:Concept ;
rdfs:label "Computer Vision Pipeline"@en .
ngm:computer-vision-system a owl:Class ;
rdfs:comment "An integrated assembly of hardware and software components—cameras, depth sensors, inference pipelines, and output interfaces—that acquires, processes, and interprets visual information from the physical world. Computer vision systems underpin spatial computing applications such as AR tracking, spatial mapping, and object detection, translating raw image data into actionable semantic understanding for downstream tasks."@en ;
rdfs:label "Computer Vision System"@en ;
rdfs:subClassOf ngm:sc-interaction ;
rdfs:subClassOf _:r5226 ;
rdfs:subClassOf _:r5227 ;
rdfs:subClassOf _:r5228 ;
rdfs:subClassOf _:r5229 ;
rdfs:subClassOf _:r5230 ;
skos:broader ngm:sc-interaction ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:robotics-perception ;
vc:contrastsWith ngm:lidar ;
vc:enables ngm:augmented-reality ;
vc:enables ngm:object-detection ;
vc:enables ngm:pose-estimation ;
vc:enables ngm:simultaneous-localisation-and-mapping ;
vc:enables ngm:spatial-mapping ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:camera-calibration ;
vc:hasPart ngm:depth-sensor ;
vc:hasPart ngm:image-sensor ;
vc:implements ngm:image-classification ;
vc:implements ngm:semantic-segmentation ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:pattern-recognition ;
vc:relatedTo ngm:real-time-processing ;
vc:requires ngm:gpu-accelerator ;
vc:requires ngm:image-preprocessing ;
vc:requires ngm:training-dataset ;
vc:slug "computer-vision-system" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:autonomous-vehicle ;
vc:supports ngm:industrial-robot ;
vc:uses ngm:convolutional-neural-network ;
vc:uses ngm:deep-learning ;
vc:uses ngm:feature-extraction ;
vc:uses ngm:optical-flow .
ngm:computer-vision-task a owl:Class ;
rdfs:comment "A Computer Vision Task is a specific computational problem solved using visual input data, encompassing image classification, object detection, semantic segmentation, instance segmentation, and pose estimation. These tasks form the building blocks of downstream vision applications such as scene understanding, autonomous navigation, and visual question answering, typically implemented via convolutional or transformer-based neural architectures."@en ;
rdfs:label "Computer Vision Task"@en ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf ngm:computer-vision ;
rdfs:subClassOf _:r5231 ;
rdfs:subClassOf _:r5232 ;
rdfs:subClassOf _:r5233 ;
rdfs:subClassOf _:r5234 ;
rdfs:subClassOf _:r5235 ;
skos:broader ngm:ai-research-area ;
vc:enables ngm:autonomous-navigation ;
vc:enables ngm:scene-understanding ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:image-classification ;
vc:hasPart ngm:instance-segmentation ;
vc:hasPart ngm:object-detection ;
vc:hasPart ngm:pose-estimation ;
vc:hasPart ngm:semantic-segmentation ;
vc:isPartOf ngm:computer-vision ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:multimodal-ai-architecture-ai ;
vc:slug "computer-vision-task" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:convolutional-neural-network ;
vc:uses ngm:deep-learning ;
vc:uses ngm:feature-extraction .
ngm:computer-vision-training a skos:Concept ;
rdfs:label "Computer Vision Training"@en .
ngm:computer-vision-video-analysis a owl:Class ;
rdfs:comment "The computational analysis, understanding, and manipulation of video data using machine learning and computer vision techniques. Core tasks include object detection and tracking, semantic segmentation, action recognition, temporal modelling, and scene understanding. Modern approaches employ 3D convolutional networks, vision transformers, and self-supervised learning on large-scale video datasets."@en ;
rdfs:label "Computer Vision Video Analysis"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf _:r5236 ;
rdfs:subClassOf _:r5237 ;
skos:broader ngm:ai-application ;
vc:enables ngm:instance-segmentation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:object-detection ;
vc:hasPart ngm:semantic-segmentation ;
vc:qualityScore "0.0"^^xsd:float ;
vc:slug "computer-vision-video-analysis" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:computer-vision ;
vc:uses ngm:convolutional-neural-network ;
vc:uses ngm:transformer .
ngm:computerised-adaptive-testing a owl:Class ;
rdfs:comment "Computerised adaptive testing (CAT) is an assessment method that selects each subsequent question based on a test-taker's performance on previous items, converging on an estimate of ability with fewer questions than a fixed-form test. It relies on item response theory to model the probability of a correct answer as a function of item difficulty and estimated learner ability, updating the estimate after every response. CAT is widely used in standardised testing and adaptive learning platforms because it shortens test duration while improving measurement precision at the extremes of the ability range. It is closely related to Bayesian knowledge tracing, which similarly updates a learner model from sequential evidence."@en ;
rdfs:label "Computerised Adaptive Testing"@en ;
rdfs:subClassOf ngm:adaptive-learning ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.0"^^xsd:float ;
vc:slug "computerised-adaptive-testing" ;
vc:sourceDomain "machine-learning" .
ngm:computing-education a skos:Concept ;
rdfs:label "Computing Education"@en .
ngm:computing-hardware a owl:Class ;
rdfs:comment "Computing Hardware encompasses the physical processing, memory, and peripheral devices that underpin spatial computing experiences, including GPUs, neural accelerators, XR headsets, and edge devices. It forms the substrate on which spatial applications, rendering engines, and sensor fusion pipelines execute."@en ;
rdfs:label "Computing Hardware"@en ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf _:r5248 ;
rdfs:subClassOf _:r5249 ;
skos:broader ngm:sc-platform-and-environment ;
vc:bridgesTo ngm:sensor-input ;
vc:enables ngm:spatial-computing ;
vc:enables ngm:spatial-computing-paradigm ;
vc:enables ngm:xr-hardware ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:gpu-compute ;
vc:hasPart ngm:hardware-acceleration ;
vc:qualityScore "0.35"^^xsd:float ;
vc:slug "computing-hardware" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:hardware-and-edge ;
vc:supports ngm:mixed-reality .
ngm:computing-infrastructure a owl:Class ;
rdfs:comment "Computing infrastructure encompasses the physical and virtual resources required for building, running, and delivering applications and services, including servers, storage systems, networking equipment, power systems, and cooling facilities housed in data centres. It provides the foundational capacity that IT systems require to process, store, and transmit digital data. Modern computing infrastructure increasingly extends from on-premises hardware into cloud-hosted and edge environments, and is a prerequisite for AI workloads, distributed applications, and spatial computing platforms."@en ;
rdfs:label "Computing Infrastructure"@en ;
rdfs:subClassOf ngm:infra-computing-and-cloud ;
rdfs:subClassOf _:r5250 ;
rdfs:subClassOf _:r5251 ;
rdfs:subClassOf _:r5252 ;
rdfs:subClassOf _:r5253 ;
skos:broader ngm:infra-computing-and-cloud ;
vc:enables ngm:ai-infrastructure ;
vc:enables ngm:orchestration ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:gpu-compute ;
vc:hasPart ngm:network-infrastructure ;
vc:hasPart ngm:networking-infrastructure ;
vc:hasPart ngm:storage-infrastructure ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:cloud-infrastructure ;
vc:relatedTo ngm:digital-infrastructure ;
vc:relatedTo ngm:distributed-computing ;
vc:relatedTo ngm:edge-computing ;
vc:slug "computing-infrastructure" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:power-management ;
vc:supports ngm:sustainability .
ngm:computing-platform a owl:Class ;
rdfs:comment "A computing platform is a hardware and software environment that provides the foundational execution context for applications, services, and AI workloads. It encompasses the combination of processor architecture, operating system, runtime libraries, and supporting infrastructure—such as cloud, edge, or on-premises nodes—that determines what software can run and how it performs."@en ;
rdfs:label "Computing Platform"@en ;
rdfs:subClassOf ngm:infra-computing-and-cloud ;
rdfs:subClassOf _:r5254 ;
rdfs:subClassOf _:r5255 ;
rdfs:subClassOf _:r5256 ;
rdfs:subClassOf _:r5257 ;
skos:broader ngm:infra-computing-and-cloud ;
vc:bridgesTo ngm:computer-vision ;
vc:enables ngm:ai-infrastructure ;
vc:enables ngm:distributed-computing ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:gpu-compute ;
vc:hasPart ngm:middleware ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:edge-computing ;
vc:requires ngm:hardware ;
vc:requires ngm:operating-system ;
vc:slug "computing-platform" ;
vc:sourceDomain "infrastructure" .
ngm:computing-research-community a skos:Concept ;
rdfs:label "Computing Research Community"@en .
ngm:comsol-multiphysics a skos:Concept ;
rdfs:label "Comsol Multiphysics"@en .
ngm:concatenative-synthesis a skos:Concept ;
rdfs:label "Concatenative Synthesis"@en .
ngm:concentrated-liquidity a owl:Class ;
rdfs:comment "Concentrated liquidity is a capital efficiency mechanism for automated market makers (AMMs) in which liquidity providers deposit assets within user-specified price ranges rather than uniformly across the full price curve from zero to infinity. Within an active price range, the capital deployed behaves equivalently to a much larger position in a constant-product AMM, dramatically increasing fee revenue per unit of capital while simultaneously reducing the price impact of trades of a given size. This design was pioneered by Uniswap v3 and has since been widely adopted across decentralised exchanges."@en ;
rdfs:label "Concentrated Liquidity"@en ;
rdfs:subClassOf ngm:liquidity-provision ;
rdfs:subClassOf _:r5258 ;
rdfs:subClassOf _:r5259 ;
vc:bridgesTo ngm:financial-derivatives ;
vc:bridgesTo ngm:market-microstructure ;
vc:contrastsWith ngm:constant-product-amm ;
vc:contrastsWith ngm:order-book-exchange ;
vc:dependsOn ngm:blockchain ;
vc:dependsOn ngm:impermanent-loss ;
vc:enables ngm:capital-efficiency ;
vc:enables ngm:decentralized-exchange ;
vc:enables ngm:liquidity ;
vc:enables ngm:token-economics ;
vc:enables ngm:yield-farming ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:liquidity-position ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:de-fi ;
vc:relatedTo ngm:perpetual-futures ;
vc:relatedTo ngm:protocol-owned-liquidity ;
vc:relatedTo ngm:uniswap ;
vc:requires ngm:fee-tier ;
vc:requires ngm:price-oracle ;
vc:slug "concentrated-liquidity" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:automated-market-maker ;
vc:uses ngm:liquidity-pool ;
vc:uses ngm:non-fungible-token ;
vc:uses ngm:smart-contract .
ngm:concentration-inequalities a owl:Class ;
rdfs:comment "Concentration inequalities are probabilistic bounds — such as Markov's, Chebyshev's, Hoeffding's and Chernoff's inequalities — that quantify how tightly a random variable, typically a sum or average, concentrates around its expected value. In machine learning they provide the mathematical basis for generalisation bounds, showing how closely empirical risk on a finite sample tracks true risk as sample size grows. They are a core analytical tool within statistical learning theory and underpin bias-variance and PAC-learning arguments."@en ;
rdfs:label "Concentration Inequalities"@en ;
rdfs:subClassOf ngm:statistical-learning-theory ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:isPartOf ngm:statistical-learning-theory ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "concentration-inequalities" ;
vc:sourceDomain "machine-learning" .
ngm:concept-art a owl:Class ;
rdfs:comment "Concept art is a discipline of visual development practice in which illustrators, designers, and increasingly AI-assisted workflows produce preliminary visual representations of characters, environments, vehicles, creatures, and props to establish the aesthetic, mood, and functional parameters of an intended creative production before commitment to the labour-intensive downstream stages of 3D modelling, animation, and rendering. It functions as the design language and communication medium between creative direction and production teams across games, film, animation, and extended reality."@en ;
rdfs:label "Concept Art"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:creative-expression ;
rdfs:subClassOf ngm:creative-industries ;
rdfs:subClassOf ngm:visual-development ;
rdfs:subClassOf _:r5260 ;
rdfs:subClassOf _:r5261 ;
rdfs:subClassOf _:r5262 ;
rdfs:subClassOf _:r5263 ;
rdfs:subClassOf _:r5264 ;
skos:broader ngm:ai-application ;
vc:contrastsWith ngm:3-d-content-generation ;
vc:contrastsWith ngm:film-vfx ;
vc:contrastsWith ngm:final-art-production ;
vc:contrastsWith ngm:final-production-art ;
vc:contrastsWith ngm:technical-illustration ;
vc:dependsOn ngm:art-direction ;
vc:dependsOn ngm:copyright ;
vc:dependsOn ngm:creative-commons ;
vc:dependsOn ngm:intellectual-property-rights-framework ;
vc:dependsOn ngm:pre-production ;
vc:dependsOn ngm:prompt-engineering ;
vc:enables ngm:3-d-content-creation ;
vc:enables ngm:3d-modelling ;
vc:enables ngm:animation ;
vc:enables ngm:animation-rig ;
vc:enables ngm:asset-pipeline ;
vc:enables ngm:character-rigging ;
vc:enables ngm:film-production ;
vc:enables ngm:film-vfx ;
vc:enables ngm:game-asset-generation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:asset-pipeline ;
vc:hasPart ngm:character-animation ;
vc:hasPart ngm:character-design ;
vc:hasPart ngm:colour-palette ;
vc:hasPart ngm:environment-design ;
vc:hasPart ngm:moodboard ;
vc:hasPart ngm:prop-design ;
vc:hasPart ngm:silhouette-design ;
vc:hasPart ngm:storyboard ;
vc:implements ngm:diffusion-model ;
vc:implements ngm:fine-tuning ;
vc:implements ngm:generative-adversarial-network ;
vc:implements ngm:generative-ai ;
vc:implements ngm:generative-design ;
vc:implements ngm:procedural-content-generation ;
vc:implements ngm:style-transfer ;
vc:implements ngm:text-to-image-generation ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:3-d-asset ;
vc:relatedTo ngm:adobe-firefly ;
vc:relatedTo ngm:ai-art ;
vc:relatedTo ngm:colour-grading ;
vc:relatedTo ngm:colour-management ;
vc:relatedTo ngm:control-net ;
vc:relatedTo ngm:copyright ;
vc:relatedTo ngm:creative-expression ;
vc:relatedTo ngm:creative-software ;
vc:relatedTo ngm:creative-tools ;
vc:relatedTo ngm:game-engine ;
vc:relatedTo ngm:generative-design ;
vc:relatedTo ngm:image-generation ;
vc:relatedTo ngm:lo-ra ;
vc:relatedTo ngm:midjourney-text-to-image-service ;
vc:relatedTo ngm:procedural-content-generation ;
vc:relatedTo ngm:prompt-engineering ;
vc:relatedTo ngm:stable-diffusion-image-model ;
vc:relatedTo ngm:storytelling ;
vc:relatedTo ngm:synthetic-media ;
vc:relatedTo ngm:virtual-production-workflow ;
vc:requires ngm:art-direction ;
vc:requires ngm:creative-ai ;
vc:requires ngm:image-generation ;
vc:requires ngm:pre-production ;
vc:requires ngm:visual-narrative ;
vc:slug "concept-art" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:creative-industries ;
vc:supports ngm:animation-software ;
vc:supports ngm:content-production-workflow ;
vc:supports ngm:creative-ai ;
vc:supports ngm:game-engine ;
vc:supports ngm:intellectual-property-rights-framework ;
vc:supports ngm:virtual-production-workflow ;
vc:uses ngm:adobe-creative-cloud ;
vc:uses ngm:adobe-firefly ;
vc:uses ngm:control-net ;
vc:uses ngm:control-net-conditioning ;
vc:uses ngm:diffusion-models ;
vc:uses ngm:generative-adversarial-network ;
vc:uses ngm:lo-ra ;
vc:uses ngm:midjourney-text-to-image-service ;
vc:uses ngm:prompt-engineering ;
vc:uses ngm:proprietary-image-generation ;
vc:uses ngm:stable-diffusion-image-model .
ngm:concept-constructor a skos:Concept ;
rdfs:label "Concept Constructor"@en .
ngm:concept-drift a owl:Class ;
rdfs:comment "Concept Drift is the phenomenon in which the statistical properties of the target variable that a machine learning model was trained to predict change over time, causing model performance to degrade. Drift can be abrupt, gradual, or recurring, and may stem from evolving user behaviour, environmental shifts, or data collection changes. Detecting and adapting to concept drift is essential for maintaining the reliability of deployed ML systems."@en ;
rdfs:label "Concept Drift"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:distribution-shift ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf ngm:machine-learning-discipline-technique ;
rdfs:subClassOf _:r5265 ;
rdfs:subClassOf _:r5266 ;
rdfs:subClassOf _:r5267 ;
rdfs:subClassOf _:r5268 ;
rdfs:subClassOf _:r5269 ;
rdfs:subClassOf _:r5270 ;
rdfs:subClassOf _:r5271 ;
rdfs:subClassOf _:r5272 ;
rdfs:subClassOf _:r5273 ;
skos:broader ngm:ai-technique ;
vc:contrastsWith ngm:catastrophic-forgetting ;
vc:contrastsWith ngm:catastrophic-risk-assessment ;
vc:contrastsWith ngm:covariate-shift ;
vc:contrastsWith ngm:data-drift ;
vc:dependsOn ngm:data-annotation ;
vc:dependsOn ngm:data-quality ;
vc:dependsOn ngm:feature-store ;
vc:dependsOn ngm:machine-learning-discipline-pipeline ;
vc:dependsOn ngm:model-registry ;
vc:dependsOn ngm:observability ;
vc:dependsOn ngm:probability-distribution ;
vc:dependsOn ngm:streaming-data ;
vc:enables ngm:active-learning ;
vc:enables ngm:ai-governance ;
vc:enables ngm:continual-learning ;
vc:enables ngm:domain-adaptation ;
vc:enables ngm:feedback-loop ;
vc:enables ngm:mlops ;
vc:enables ngm:model-training ;
vc:enables ngm:online-learning ;
vc:enables ngm:retraining ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:adwin ;
vc:hasPart ngm:drift-detection-method ;
vc:hasPart ngm:kolmogorov-smirnov-test ;
vc:hasPart ngm:model-monitoring ;
vc:hasPart ngm:page-hinkley-test ;
vc:hasPart ngm:population-stability-index ;
vc:hasPart ngm:statistical-process-control ;
vc:implements ngm:anomaly-detection ;
vc:implements ngm:bayesian-inference ;
vc:implements ngm:ensemble-methods ;
vc:implements ngm:information-theory ;
vc:implements ngm:knowledge-distillation ;
vc:implements ngm:statistical-hypothesis-testing ;
vc:implements ngm:transfer-learning ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:active-learning ;
vc:relatedTo ngm:anomaly-detection ;
vc:relatedTo ngm:bayesian-optimisation ;
vc:relatedTo ngm:data-pipeline ;
vc:relatedTo ngm:deep-learning ;
vc:relatedTo ngm:distribution-shift ;
vc:relatedTo ngm:feature-engineering ;
vc:relatedTo ngm:feature-store ;
vc:relatedTo ngm:federated-edge-learning ;
vc:relatedTo ngm:federated-learning ;
vc:relatedTo ngm:feedback-loop ;
vc:relatedTo ngm:inference ;
vc:relatedTo ngm:knowledge-distillation ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:machine-learning-accelerator ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:mlops ;
vc:relatedTo ngm:model-degradation ;
vc:relatedTo ngm:model-registry ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:neural-network ;
vc:relatedTo ngm:online-learning ;
vc:relatedTo ngm:reinforcement-learning ;
vc:relatedTo ngm:time-series ;
vc:relatedTo ngm:transfer-learning ;
vc:requires ngm:data-pipeline ;
vc:requires ngm:data-quality ;
vc:requires ngm:feature-engineering ;
vc:requires ngm:model-monitoring ;
vc:requires ngm:observability ;
vc:requires ngm:probability-distribution ;
vc:requires ngm:statistics ;
vc:requires ngm:streaming-data ;
vc:slug "concept-drift" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:machine-learning-discipline-techniques-survey ;
vc:standardizedBy ngm:machine-learning-md ;
vc:supports ngm:ai-governance ;
vc:supports ngm:ai-lifecycle ;
vc:supports ngm:machine-learning-discipline-infrastructure ;
vc:supports ngm:machine-learning-operations ;
vc:supports ngm:mlops ;
vc:supports ngm:model-training-pipeline ;
vc:supports ngm:observability ;
vc:uses ngm:anomaly-detection ;
vc:uses ngm:bayesian-deep-learning ;
vc:uses ngm:bayesian-inference ;
vc:uses ngm:ensemble-methods ;
vc:uses ngm:feature-store ;
vc:uses ngm:information-theory ;
vc:uses ngm:machine-learning-discipline-framework ;
vc:uses ngm:model-registry .
ngm:concept-language a skos:Concept ;
rdfs:label "Concept Language"@en .
ngm:concept-of-operations a skos:Concept ;
rdfs:label "Concept Of Operations"@en .
ngm:conceptnet a skos:Concept ;
rdfs:label "Conceptnet"@en .
ngm:conceptual-blending a skos:Concept ;
rdfs:label "Conceptual Blending"@en .
ngm:conceptual-hierarchy a owl:Class ;
rdfs:comment "A Conceptual Hierarchy is a structured taxonomic organisation of domain concepts into subsumption (is-a) and composition (part-of) relationships, enabling systematic knowledge representation, inheritance of properties, and semantic interoperability across robotic and autonomous systems. It supports automated reasoning, modular system design, and classification of new entities within standardised ontological frameworks."@en ;
rdfs:label "Conceptual Hierarchy"@en ;
rdfs:subClassOf ngm:software-engineering ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:owl-class-hierarchy ;
vc:relatedTo ngm:rdf ;
vc:slug "conceptual-hierarchy" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:knowledge-graph ;
vc:supports ngm:robotics ;
vc:uses ngm:knowledge-representation ;
vc:uses ngm:ontology .
ngm:conceptual-layer a owl:Class ;
rdfs:comment "The Conceptual Layer represents the highest abstraction level in an ontological classification system, encompassing pure concepts, theoretical models, design principles, and logical frameworks that are independent of specific technical implementations. Concepts at this layer can be realised through multiple concrete approaches while retaining their essential semantic properties."@en ;
rdfs:label "Conceptual Layer"@en ;
rdfs:subClassOf ngm:software-engineering ;
rdfs:subClassOf _:r5274 ;
vc:contrastsWith ngm:protocol-layer ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:ontology-structure ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:software-architecture ;
vc:relatedTo ngm:system-architecture ;
vc:slug "conceptual-layer" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:knowledge-representation ;
vc:supports ngm:ontology .
ngm:conceptual-space-model a skos:Concept ;
rdfs:label "Conceptual Space Model"@en .
ngm:conceptualisation a skos:Concept ;
rdfs:label "Conceptualisation"@en .
ngm:concrete-domain a skos:Concept ;
rdfs:label "Concrete Domain"@en .
ngm:concurrency a owl:Class ;
rdfs:comment "Concurrency is the composition of independently executing computations that make progress within overlapping time periods, whether or not they run simultaneously on separate processors. It is a way of structuring a program so that multiple tasks can be in flight at once, coordinating access to shared state through synchronisation primitives. Concurrency is distinct from parallelism: it concerns the dealing with many things at once, while parallelism concerns the doing of many things at once."@en ;
rdfs:label "Concurrency"@en ;
rdfs:subClassOf ngm:infrastructure ;
rdfs:subClassOf ngm:software-engineering ;
rdfs:subClassOf _:r5277 ;
skos:broader ngm:infrastructure ;
vc:contrastsWith ngm:parallel-computing ;
vc:dependsOn ngm:multithreading ;
vc:enables ngm:real-time-analytics ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:actor-model ;
vc:relatedTo ngm:flow-control ;
vc:relatedTo ngm:parallel-processing ;
vc:requires ngm:operating-system ;
vc:slug "concurrency" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:high-throughput-computing ;
vc:supports ngm:parallel-computing ;
vc:uses ngm:asynchronous-programming ;
vc:uses ngm:event-loop ;
vc:uses ngm:message-passing ;
vc:uses ngm:multithreading .
ngm:concurrency-control a owl:Class ;
rdfs:comment "Concurrency control is the set of techniques that coordinate simultaneous operations on shared data so that correctness is preserved despite interleaving. It ensures that concurrent transactions or processes produce results equivalent to some valid serial execution, preventing anomalies such as lost updates and inconsistent reads. It is foundational to databases, distributed systems, and collaborative applications."@en ;
rdfs:label "Concurrency Control"@en ;
rdfs:subClassOf ngm:distributed-systems ;
rdfs:subClassOf _:r5275 ;
rdfs:subClassOf _:r5276 ;
vc:bridgesTo ngm:database-system ;
vc:contrastsWith ngm:conflict-resolution ;
vc:dependsOn ngm:concurrency ;
vc:enables ngm:data-consistency ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:data-consistency ;
vc:isPartOf ngm:distributed-systems ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:conflict-resolution ;
vc:relatedTo ngm:state-synchronisation ;
vc:requires ngm:data-consistency ;
vc:requires ngm:transaction ;
vc:slug "concurrency-control" ;
vc:sourceDomain "distributed-systems" ;
vc:supports ngm:database-system ;
vc:uses ngm:transaction .
ngm:concurrency-model a skos:Concept ;
rdfs:label "Concurrency Model"@en .
ngm:concurrent-engineering a skos:Concept ;
rdfs:label "Concurrent Engineering"@en .
ngm:concurrent-programming a skos:Concept ;
rdfs:label "Concurrent Programming"@en .
ngm:concurrent-task-execution a skos:Concept ;
rdfs:label "Concurrent Task Execution"@en .
ngm:condensed-matter-physics a skos:Concept ;
rdfs:label "Condensed Matter Physics"@en .
ngm:condition-monitoring a owl:Class ;
rdfs:comment "Condition monitoring is the continuous or periodic measurement of physical parameters — vibration, temperature, pressure, or acoustic signature — from operating machinery to detect degradation before it causes failure. It is a core Industrial IoT application, relying on networked sensors to stream measurements to analytics systems that flag anomalies for predictive maintenance. It reduces unplanned downtime compared with fixed-interval preventive maintenance schedules."@en ;
rdfs:label "Condition Monitoring"@en ;
rdfs:subClassOf ngm:industrial-io-t ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:industrial-io-t ;
vc:qualityScore "0.6"^^xsd:float ;
vc:slug "condition-monitoring" ;
vc:sourceDomain "infrastructure" .
ngm:condition-node a skos:Concept ;
rdfs:label "Condition Node"@en .
ngm:condition-report a skos:Concept ;
rdfs:label "Condition Report"@en .
ngm:conditional-computation a skos:Concept ;
rdfs:label "Conditional Computation"@en .
ngm:conditional-entropy a skos:Concept ;
rdfs:label "Conditional Entropy"@en .
ngm:conditional-flow-matching a skos:Concept ;
rdfs:label "Conditional Flow Matching"@en .
ngm:conditional-generation a skos:Concept ;
rdfs:label "Conditional Generation"@en .
ngm:conditional-image-generation a skos:Concept ;
rdfs:label "Conditional Image Generation"@en .
ngm:conditional-payment a owl:Class ;
rdfs:comment "A conditional payment is a transfer of value that is released only when one or more predefined conditions are met, rather than executing unconditionally on submission. On blockchains these conditions are enforced by smart contracts or scripts such as hash and time locks, removing the need for a trusted intermediary to adjudicate. Conditional payments are the foundation of escrow, payment channels and atomic cross-chain swaps."@en ;
rdfs:label "Conditional Payment"@en ;
rdfs:subClassOf ngm:smart-contract ;
rdfs:subClassOf _:r5278 ;
rdfs:subClassOf _:r5279 ;
vc:contrastsWith ngm:micropayment ;
vc:enables ngm:atomic-swap ;
vc:enables ngm:micropayment ;
vc:enables ngm:payment-channel ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:hash-time-locked-contract ;
vc:implements ngm:trustless-execution ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:bitcoin ;
vc:relatedTo ngm:trustless-execution ;
vc:requires ngm:oracle ;
vc:requires ngm:timelock ;
vc:slug "conditional-payment" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:lightning-network ;
vc:uses ngm:smart-contract ;
vc:uses ngm:state-channel .
ngm:conditional-probability a skos:Concept ;
rdfs:label "Conditional Probability"@en .
ngm:conditional-random-field a owl:Class ;
rdfs:comment "A Conditional Random Field (CRF) is a discriminative probabilistic graphical model used for structured prediction tasks such as sequence labelling, where the model directly estimates the conditional probability P(y|x) of an output label sequence y given an observed input sequence x. CRFs overcome the label bias problem of maximum-entropy Markov models by considering the entire output sequence jointly, making them effective for named entity recognition, part-of-speech tagging, and image segmentation."@en ;
rdfs:label "Conditional Random Field"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf _:r5280 ;
rdfs:subClassOf _:r5281 ;
rdfs:subClassOf _:r5282 ;
skos:broader ngm:ai-technique ;
vc:contrastsWith ngm:convolutional-neural-network ;
vc:contrastsWith ngm:recurrent-neural-network ;
vc:contrastsWith ngm:transformer ;
vc:enables ngm:named-entity-recognition ;
vc:enables ngm:natural-language-processing ;
vc:enables ngm:speech-recognition ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:machine-learning-discipline-technique ;
vc:relatedTo ngm:named-entity ;
vc:relatedTo ngm:natural-language-understanding ;
vc:requires ngm:feature-extraction ;
vc:requires ngm:machine-learning-discipline ;
vc:requires ngm:probabilistic-model ;
vc:slug "conditional-random-field" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:deep-learning ;
vc:uses ngm:machine-learning-model .
ngm:conditional-random-fields a skos:Concept ;
rdfs:label "Conditional Random Fields"@en .
ngm:conditionality a skos:Concept ;
rdfs:label "Conditionality"@en .
ngm:conditioning-encoder a skos:Concept ;
rdfs:label "Conditioning Encoder"@en .
ngm:conditioning-preprocessor a skos:Concept ;
rdfs:label "Conditioning Preprocessor"@en .
ngm:conditioning-signal a owl:Class ;
rdfs:comment "A conditioning signal is auxiliary input - such as a text prompt, class label, pose map, or edge map - supplied to a generative model to steer its output toward desired attributes without retraining the base model. Techniques such as classifier-free guidance and ControlNet-style spatial conditioning inject these signals at specific points in the generation process to control content, structure, or style. The strength and fidelity of a conditioning signal determine how closely generated output adheres to the intended constraint."@en ;
rdfs:label "Conditioning Signal"@en ;
rdfs:subClassOf ngm:control-signal ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.0"^^xsd:float ;
vc:slug "conditioning-signal" ;
vc:sourceDomain "artificial-intelligence" .
ngm:conduct-of-business-rules a skos:Concept ;
rdfs:label "Conduct Of Business Rules"@en .
ngm:conduct-regulation a skos:Concept ;
rdfs:label "Conduct Regulation"@en .
ngm:conduit a skos:Concept ;
rdfs:label "Conduit"@en .
ngm:cone-of-depression a owl:Class ;
rdfs:label "Cone Of Depression"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-system-phenomena ;
vc:slug "cone-of-depression" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:cone-of-impression a owl:Class ;
rdfs:label "Cone Of Impression"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-system-phenomena ;
vc:slug "cone-of-impression" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:conference-facilitation a skos:Concept ;
rdfs:label "Conference Facilitation"@en .
ngm:conference-interpreting a skos:Concept ;
rdfs:label "Conference Interpreting"@en .
ngm:conference-of-parties a skos:Concept ;
rdfs:label "Conference Of Parties"@en .
ngm:confidence-estimator a skos:Concept ;
rdfs:label "Confidence Estimator"@en .
ngm:confidence-interval a skos:Concept ;
rdfs:label "Confidence Interval"@en .
ngm:confidence-scoring a skos:Concept ;
rdfs:label "Confidence Scoring"@en .
ngm:confidential-ai a skos:Concept ;
rdfs:label "Confidential AI"@en .
ngm:confidential-asset a skos:Concept ;
rdfs:label "Confidential Asset"@en .
ngm:confidential-collaboration a skos:Concept ;
rdfs:label "Confidential Collaboration"@en .
ngm:confidential-computing a owl:Class ;
rdfs:comment "A hardware-based security paradigm that protects data in use by isolating computation within trusted execution environments (TEEs) backed by processor security extensions (Intel SGX, AMD SEV, ARM TrustZone). It extends encryption from data at rest and in transit to data actively being processed, preventing access even by privileged software, hypervisors, or cloud providers. Key AI applications include secure model training, private inference, and TEE-protected federated learning aggregation."@en ;
rdfs:label "Confidential Computing"@en ;
rdfs:subClassOf ngm:hardware-security ;
rdfs:subClassOf _:r5283 ;
rdfs:subClassOf _:r5284 ;
rdfs:subClassOf _:r5285 ;
rdfs:subClassOf _:r5286 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:digital-twin ;
vc:contrastsWith ngm:tls ;
vc:dependsOn ngm:amd-sev ;
vc:dependsOn ngm:arm-trust-zone ;
vc:dependsOn ngm:intel-sgx ;
vc:enables ngm:federated-learning ;
vc:enables ngm:privacy-preserving-machine-learning ;
vc:enables ngm:private-inference ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:remote-attestation ;
vc:hasPart ngm:secure-enclave ;
vc:hasPart ngm:tee ;
vc:implements ngm:zero-trust-architecture ;
vc:isPartOf ngm:cloud-security ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:ai-security ;
vc:relatedTo ngm:cybersecurity ;
vc:relatedTo ngm:data-security ;
vc:requires ngm:memory-encryption ;
vc:slug "confidential-computing" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:confidential-computing-consortium ;
vc:supports ngm:gdpr-compliance ;
vc:supports ngm:hardware-security-module ;
vc:uses ngm:differential-privacy ;
vc:uses ngm:homomorphic-encryption ;
vc:uses ngm:secure-multi-party-computation .
ngm:confidential-computing-consortium a owl:Class ;
rdfs:comment "The Confidential Computing Consortium is a Linux Foundation project that brings together hardware vendors, cloud providers and software firms to advance the adoption and standardisation of confidential computing. It defines confidential computing as protecting data in use by performing computation within a hardware-based trusted execution environment. The consortium stewards open-source projects, terminology and best practices that promote interoperable enclave technologies."@en ;
rdfs:label "Confidential Computing Consortium"@en ;
rdfs:subClassOf ngm:standards-documentation ;
vc:bridgesTo ngm:confidential-computing ;
vc:contrastsWith ngm:homomorphic-encryption ;
vc:enables ngm:secure-enclave ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:standards-documentation ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:homomorphic-encryption ;
vc:relatedTo ngm:tee ;
vc:slug "confidential-computing-consortium" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:standards-documentation ;
vc:supports ngm:confidential-computing ;
vc:supports ngm:tee ;
vc:uses ngm:attestation .
ngm:confidential-proceedings a skos:Concept ;
rdfs:label "Confidential Proceedings"@en .
ngm:confidential-smart-contract a skos:Concept ;
rdfs:label "Confidential Smart Contract"@en .
ngm:confidential-smart-contracts a skos:Concept ;
rdfs:label "Confidential Smart Contracts"@en .
ngm:confidential-transactions a owl:Class ;
rdfs:comment "Confidential Transactions (CT) is a cryptographic protocol for distributed ledgers, designed by Gregory Maxwell in 2015, that conceals the amounts transferred in financial transactions whilst preserving the ability for validators to verify that no value is created or destroyed. It employs Pedersen commitments—homomorphic elliptic-curve constructs—to encode transaction values in a form that is computationally hiding yet perfectly binding, combined with range proofs (typically Bulletproofs) to ensure committed values are non-negative and thus prevent inflation attacks. CT has been deployed in the Liquid Network sidechain, Monero's RingCT, and the MimbleWimble protocol family, and underpins much of the contemporary research into privacy-preserving decentralised finance."@en ;
rdfs:label "Confidential Transactions"@en ;
rdfs:subClassOf ngm:blockchain-transaction ;
rdfs:subClassOf ngm:cryptographic-primitive ;
rdfs:subClassOf _:r5287 ;
rdfs:subClassOf _:r5288 ;
rdfs:subClassOf _:r5289 ;
vc:bridgesTo ngm:financial-privacy ;
vc:bridgesTo ngm:regulatory-compliance ;
vc:bridgesTo ngm:secure-multi-party-computation ;
vc:contrastsWith ngm:blockchain ;
vc:contrastsWith ngm:zk-snark ;
vc:dependsOn ngm:cryptographic-algorithm ;
vc:dependsOn ngm:utxo-model ;
vc:enables ngm:confidential-asset ;
vc:enables ngm:privacy-preserving-blockchain ;
vc:enables ngm:private-defi ;
vc:enables ngm:selective-disclosure ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:amount-hiding ;
vc:implements ngm:homomorphic-commitment ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:confidential-computing ;
vc:relatedTo ngm:confidential-transactions ;
vc:relatedTo ngm:liquid-network ;
vc:relatedTo ngm:mimblewimble ;
vc:relatedTo ngm:monero ;
vc:requires ngm:cryptographic-hash-function ;
vc:requires ngm:discrete-logarithm-problem ;
vc:requires ngm:range-proof ;
vc:slug "confidential-transactions" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:bitcoin-proof-of-work-protocol-improvement-proposals ;
vc:standardizedBy ngm:elements-project ;
vc:uses ngm:bulletproofs ;
vc:uses ngm:elliptic-curve-cryptography ;
vc:uses ngm:homomorphic-encryption ;
vc:uses ngm:pedersen-commitment ;
vc:uses ngm:zero-knowledge-proof .
ngm:confidential-virtual-machine a skos:Concept ;
rdfs:label "Confidential Virtual Machine"@en .
ngm:configuration a owl:Class ;
rdfs:comment "Configuration is the set of parameters, settings, and environment variables that determine the runtime behaviour of a spatial computing platform, application, or pipeline component. Proper configuration governs interoperability between subsystems, controls feature flags, and defines integration points between platform services, hardware abstraction layers, and content pipelines."@en ;
rdfs:label "Configuration"@en ;
rdfs:subClassOf ngm:sc-content-and-assets ;
rdfs:subClassOf _:r5300 ;
skos:broader ngm:sc-content-and-assets ;
vc:bridgesTo ngm:computer-vision ;
vc:enables ngm:platform-service ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:configuration-setting ;
vc:relatedTo ngm:platform-engineering ;
vc:requires ngm:hardware-abstraction ;
vc:slug "configuration" ;
vc:sourceDomain "spatial-computing" .
ngm:configuration-item a skos:Concept ;
rdfs:label "Configuration Item"@en .
ngm:configuration-management a owl:Class ;
rdfs:comment "Configuration management is the engineering discipline of systematically establishing, recording, and maintaining the desired state of a system's components, settings, and dependencies throughout its lifecycle. It ensures that environments are reproducible and consistent by treating configuration as versioned, auditable artefacts rather than ad hoc manual changes. In modern practice it underpins infrastructure-as-code and continuous delivery, using declarative tools to converge machines and services to a defined state and to track every change for traceability and rollback."@en ;
rdfs:label "Configuration Management"@en ;
rdfs:subClassOf ngm:automation ;
rdfs:subClassOf ngm:software-engineering ;
rdfs:subClassOf _:r5290 ;
rdfs:subClassOf _:r5291 ;
rdfs:subClassOf _:r5292 ;
rdfs:subClassOf _:r5293 ;
rdfs:subClassOf _:r5294 ;
rdfs:subClassOf _:r5295 ;
rdfs:subClassOf _:r5296 ;
rdfs:subClassOf _:r5297 ;
vc:bridgesTo ngm:devops ;
vc:bridgesTo ngm:infrastructure-as-code ;
vc:contrastsWith ngm:manual-administration ;
vc:dependsOn ngm:agile-software-development ;
vc:dependsOn ngm:automation ;
vc:dependsOn ngm:software-engineering ;
vc:enables ngm:continuous-delivery ;
vc:enables ngm:continuous-deployment ;
vc:enables ngm:continuous-integration ;
vc:enables ngm:devops ;
vc:enables ngm:disaster-recovery ;
vc:enables ngm:gitops ;
vc:enables ngm:infrastructure-as-code ;
vc:enables ngm:reproducibility ;
vc:enables ngm:supply-chain-security ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:audit ;
vc:hasPart ngm:baseline ;
vc:hasPart ngm:change-management ;
vc:hasPart ngm:configuration-item ;
vc:hasPart ngm:configuration-management-database ;
vc:hasPart ngm:idempotency ;
vc:hasPart ngm:policy-as-code ;
vc:hasPart ngm:sbom ;
vc:hasPart ngm:version-control ;
vc:implements ngm:change-management ;
vc:implements ngm:immutable-infrastructure ;
vc:implements ngm:policy-as-code ;
vc:implements ngm:sbom ;
vc:implements ngm:slsa ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:audit ;
vc:relatedTo ngm:automated-testing ;
vc:relatedTo ngm:cloud-computing ;
vc:relatedTo ngm:cloud-native ;
vc:relatedTo ngm:containerisation ;
vc:relatedTo ngm:continuous-integration ;
vc:relatedTo ngm:data-versioning ;
vc:relatedTo ngm:dev-sec-ops ;
vc:relatedTo ngm:incident-response ;
vc:relatedTo ngm:microservices ;
vc:relatedTo ngm:platform-engineering ;
vc:relatedTo ngm:sbom ;
vc:relatedTo ngm:site-reliability-engineering ;
vc:relatedTo ngm:software-delivery-lifecycle ;
vc:relatedTo ngm:supply-chain-security ;
vc:relatedTo ngm:testing ;
vc:requires ngm:audit ;
vc:requires ngm:build-automation ;
vc:requires ngm:idempotency ;
vc:requires ngm:version-control ;
vc:slug "configuration-management" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:compliance ;
vc:supports ngm:dev-sec-ops ;
vc:supports ngm:devops ;
vc:supports ngm:mlops ;
vc:supports ngm:observability ;
vc:supports ngm:quality-assurance ;
vc:supports ngm:security-scanning ;
vc:supports ngm:site-reliability-engineering ;
vc:supports ngm:testing ;
vc:uses ngm:ansible ;
vc:uses ngm:argo-cd ;
vc:uses ngm:chef ;
vc:uses ngm:docker-containerisation-platform ;
vc:uses ngm:flux-cd ;
vc:uses ngm:gitops ;
vc:uses ngm:hashicorp-vault ;
vc:uses ngm:jenkins ;
vc:uses ngm:kubernetes ;
vc:uses ngm:open-policy-agent ;
vc:uses ngm:opentofu ;
vc:uses ngm:pulumi ;
vc:uses ngm:puppet ;
vc:uses ngm:sigstore ;
vc:uses ngm:terraform ;
vc:uses ngm:version-control .
ngm:configuration-management-database a skos:Concept ;
rdfs:label "Configuration Management Database"@en .
ngm:configuration-sample a skos:Concept ;
rdfs:label "Configuration Sample"@en .
ngm:configuration-setting a owl:Class ;
rdfs:comment "A Configuration Setting is a named parameter or preference value that governs the runtime behaviour of a spatial computing application, platform, or XR experience. Configuration settings control rendering quality, user accessibility options, privacy preferences, and network parameters, and are typically persisted across sessions to maintain consistent user experiences within metaverse and immersive environments."@en ;
rdfs:label "Configuration Setting"@en ;
rdfs:subClassOf ngm:sc-content-and-assets ;
skos:broader ngm:sc-content-and-assets ;
vc:bridgesTo ngm:computer-vision ;
vc:enables ngm:real-time-rendering ;
vc:enables ngm:simulation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:isPartOf ngm:spatial-computing ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:computer-vision ;
vc:relatedTo ngm:privacy ;
vc:slug "configuration-setting" ;
vc:sourceDomain "spatial-computing" .
ngm:configuration-space a owl:Class ;
rdfs:comment "Configuration space, often written C-space, is the set of all possible configurations of a robot, where each point fully specifies the position of every part of the mechanism. Its dimensionality equals the robot's degrees of freedom, and obstacles in the physical workspace map to forbidden regions, partitioning C-space into free and blocked subsets. Motion planning is then recast as finding a continuous path through the free portion of configuration space."@en ;
rdfs:label "Configuration Space"@en ;
rdfs:subClassOf ngm:motion-planning ;
rdfs:subClassOf _:r5298 ;
rdfs:subClassOf _:r5299 ;
vc:bridgesTo ngm:workspace ;
vc:enables ngm:obstacle-avoidance ;
vc:enables ngm:path-planning ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:degrees-of-freedom ;
vc:hasPart ngm:joint-space ;
vc:isPartOf ngm:robotics ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:inverse-kinematics ;
vc:relatedTo ngm:kinematics ;
vc:relatedTo ngm:probabilistic-roadmap ;
vc:relatedTo ngm:rapidly-exploring-random-tree ;
vc:requires ngm:collision-detection ;
vc:requires ngm:forward-kinematics ;
vc:slug "configuration-space" ;
vc:sourceDomain "robotics" ;
vc:supports ngm:robot-manipulation ;
vc:uses ngm:sampling-based-planning .
ngm:configuration-store a skos:Concept ;
rdfs:label "Configuration Store"@en .
ngm:confined-aquifer a owl:Class ;
rdfs:label "Confined Aquifer"@en ;
rdfs:subClassOf ngm:aquifer ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-system-phenomena ;
vc:slug "confined-aquifer" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:confined-bed a owl:Class ;
rdfs:label "Confined Bed"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-system-phenomena ;
vc:slug "confined-bed" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:confined-unit a owl:Class ;
rdfs:label "Confined Unit"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-system-phenomena ;
vc:slug "confined-unit" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:confined-zone a owl:Class ;
rdfs:label "Confined Zone"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-system-phenomena ;
vc:slug "confined-zone" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:confirmation-bias a skos:Concept ;
rdfs:label "Confirmation Bias"@en .
ngm:conflict-free-replicated-data-type a owl:Class ;
rdfs:comment "A conflict-free replicated data type (CRDT) is a data structure that can be replicated across many nodes and updated independently, with mathematical guarantees that all replicas converge to the same state once they have exchanged updates. By designing operations to be commutative or merges to be monotonic, CRDTs avoid the need for coordination or central conflict resolution. They are a foundational technique for offline-first and real-time collaborative distributed systems."@en ;
rdfs:label "Conflict Free Replicated Data Type"@en ;
rdfs:subClassOf ngm:eventual-consistency ;
rdfs:subClassOf _:r5301 ;
vc:bridgesTo ngm:distributed-system ;
vc:contrastsWith ngm:operational-transformation ;
vc:dependsOn ngm:concurrency ;
vc:dependsOn ngm:replication ;
vc:enables ngm:conflict-resolution ;
vc:enables ngm:operational-transformation ;
vc:enables ngm:state-synchronisation ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:eventual-consistency ;
vc:isPartOf ngm:distributed-collaboration ;
vc:isPartOf ngm:distributed-system ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:concurrency ;
vc:relatedTo ngm:conflict-resolution ;
vc:relatedTo ngm:vector-clock ;
vc:requires ngm:eventual-consistency ;
vc:slug "conflict-free-replicated-data-type" ;
vc:sourceDomain "distributed-collaboration" ;
vc:supports ngm:distributed-collaboration ;
vc:supports ngm:state-synchronisation ;
vc:uses ngm:replication ;
vc:uses ngm:vector-clock .
ngm:conflict-free-replicated-data-types a skos:Concept ;
rdfs:label "Conflict Free Replicated Data Types"@en .
ngm:conflict-mineral-tracking a owl:Class ;
rdfs:comment "Conflict Mineral Tracking denotes the use of blockchain technology to record and verify the provenance of 3TG minerals (tin, tantalum, tungsten, gold) through complex supply chains, ensuring they do not finance armed conflict or human rights abuses in the Democratic Republic of Congo and adjoining regions. Implementations combine immutable custody chains, cryptographic material fingerprinting, and smart-contract-enforced compliance checks to satisfy regulatory obligations including Dodd-Frank Section 1502 and the EU Conflict Minerals Regulation while enabling premium pricing for verified responsible sourcing."@en ;
rdfs:label "Conflict Mineral Tracking"@en ;
rdfs:subClassOf ngm:network-component ;
rdfs:subClassOf _:r5302 ;
rdfs:subClassOf _:r5303 ;
vc:enables ngm:audit-trail ;
vc:enables ngm:provenance-tracking ;
vc:enables ngm:supply-chain-traceability ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:blockchain-compliance ;
vc:relatedTo ngm:consortium-blockchain ;
vc:relatedTo ngm:esg-reporting ;
vc:relatedTo ngm:supply-chain-blockchain ;
vc:requires ngm:compliance-verification ;
vc:requires ngm:supply-chain-management ;
vc:slug "conflict-mineral-tracking" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:hyperledger-fabric ;
vc:uses ngm:internet-of-things ;
vc:uses ngm:permissioned-blockchain ;
vc:uses ngm:smart-contracts .
ngm:conflict-resolution a owl:Class ;
rdfs:comment "Conflict Resolution encompasses the structured methods, protocols, and mechanisms used to identify, address, and settle disputes between parties — whether human individuals, organisations, autonomous agents, or distributed systems. In technical contexts it includes algorithmic approaches for reconciling inconsistencies in distributed data systems, consensus protocols that converge divergent states, and governance frameworks for mediating disagreements in decentralised organisations. In social and legal contexts it spans negotiation, mediation, arbitration, and adjudication, with increasing automation and AI-assisted facilitation. Across all domains, effective conflict resolution preserves relationships, maintains system integrity, and enables continued collaboration."@en ;
rdfs:label "Conflict Resolution"@en ;
rdfs:subClassOf ngm:dispute-resolution-mechanism ;
rdfs:subClassOf _:r5304 ;
rdfs:subClassOf _:r5305 ;
vc:bridgesTo ngm:byzantine-fault-tolerance ;
vc:bridgesTo ngm:value-alignment ;
vc:contrastsWith ngm:adversarial-coordination ;
vc:contrastsWith ngm:deadlock ;
vc:enables ngm:community-governance-model ;
vc:enables ngm:decentralized-governance ;
vc:enables ngm:trustless-coordination ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:dispute-resolution-mechanism ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:arbitration-decision-engine ;
vc:relatedTo ngm:arbitration-process ;
vc:relatedTo ngm:consensus-mechanism ;
vc:relatedTo ngm:mediation ;
vc:relatedTo ngm:negotiation-protocol ;
vc:requires ngm:governance-framework ;
vc:requires ngm:trust-model ;
vc:slug "conflict-resolution" ;
vc:sourceDomain "governance" ;
vc:supports ngm:distributed-ledger-technology ;
vc:supports ngm:multi-agent-systems ;
vc:supports ngm:organisational-resilience ;
vc:uses ngm:dao-governance ;
vc:uses ngm:game-theory ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:smart-contract-coordination .
ngm:conflict-resolution-mechanism a skos:Concept ;
rdfs:label "Conflict Resolution Mechanism"@en .
ngm:confluence a owl:Class ;
rdfs:comment "Confluence is a team workspace and wiki product developed by Atlassian for collaborative documentation, knowledge management, and project information sharing. It organises content into spaces and pages with rich editing, versioning, and tight integration with issue-tracking tools such as Jira. It is widely deployed as a digital-workplace platform for enterprise knowledge capture."@en ;
rdfs:label "Confluence"@en ;
rdfs:subClassOf ngm:dc-workspace-tools ;
rdfs:subClassOf _:r5306 ;
rdfs:subClassOf _:r5307 ;
skos:broader ngm:dc-workspace-tools ;
vc:bridgesTo ngm:infrastructure ;
vc:bridgesTo ngm:jira ;
vc:contrastsWith ngm:notion ;
vc:dependsOn ngm:distributed-collaboration ;
vc:enables ngm:knowledge-management ;
vc:enables ngm:runbook ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:enterprise-content-management ;
vc:isPartOf ngm:digital-workplace-platform ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:collaborative-systems-modality-whiteboard ;
vc:relatedTo ngm:issue-tracking ;
vc:requires ngm:access-control ;
vc:requires ngm:user-authentication ;
vc:slug "confluence" ;
vc:sourceDomain "distributed-collaboration" ;
vc:supports ngm:asynchronous-communication ;
vc:supports ngm:remote-work ;
vc:uses ngm:rest-api ;
vc:uses ngm:webhook .
ngm:conformal-prediction a owl:Class ;
rdfs:comment "Conformal prediction is a distribution-free, model-agnostic framework for producing statistically valid prediction sets or intervals that are guaranteed to contain the true outcome with a user-specified probability, using only the mild assumption of exchangeability over the data. A held-out calibration set and a nonconformity score function are sufficient to construct finite-sample marginal coverage guarantees for any base predictor — ranging from linear models and neural networks to Gaussian processes and large language models. The framework unifies classification (prediction sets), regression (prediction intervals), and sequence generation (conformal risk control), and has become a cornerstone method for trustworthy AI deployment in safety-critical and regulated domains."@en ;
rdfs:label "Conformal Prediction"@en ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf ngm:machine-learning-discipline-technique ;
rdfs:subClassOf ngm:statistical-learning-theory ;
rdfs:subClassOf ngm:uncertainty-quantification ;
rdfs:subClassOf _:r5308 ;
rdfs:subClassOf _:r5309 ;
rdfs:subClassOf _:r5310 ;
rdfs:subClassOf _:r5311 ;
vc:contrastsWith ngm:bayesian-deep-learning ;
vc:contrastsWith ngm:bayesian-inference ;
vc:contrastsWith ngm:gaussian-process ;
vc:contrastsWith ngm:model-calibration ;
vc:contrastsWith ngm:semantic-entropy ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:loss-function ;
vc:dependsOn ngm:model-evaluation ;
vc:dependsOn ngm:statistical-learning-theory ;
vc:enables ngm:ai-safety ;
vc:enables ngm:anomaly-detection ;
vc:enables ngm:federated-learning ;
vc:enables ngm:risk-assessment ;
vc:enables ngm:selective-prediction ;
vc:enables ngm:trustworthy-ai ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:calibration ;
vc:hasPart ngm:calibration-set ;
vc:hasPart ngm:coverage-guarantee ;
vc:hasPart ngm:exchangeability ;
vc:hasPart ngm:nonconformity-score ;
vc:hasPart ngm:prediction-interval ;
vc:hasPart ngm:prediction-set ;
vc:implements ngm:frequentist-statistics ;
vc:implements ngm:hypothesis-testing ;
vc:implements ngm:online-learning ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:active-learning ;
vc:relatedTo ngm:bayesian-deep-learning ;
vc:relatedTo ngm:bayesian-inference ;
vc:relatedTo ngm:bayesian-optimisation ;
vc:relatedTo ngm:cross-validation ;
vc:relatedTo ngm:distribution-shift ;
vc:relatedTo ngm:ensemble-methods ;
vc:relatedTo ngm:fairness-in-machine-learning ;
vc:relatedTo ngm:image-segmentation ;
vc:relatedTo ngm:interpretability ;
vc:relatedTo ngm:logistic-regression ;
vc:relatedTo ngm:model-calibration ;
vc:relatedTo ngm:natural-language-inference ;
vc:relatedTo ngm:probabilistic-model ;
vc:relatedTo ngm:reinforcement-learning ;
vc:relatedTo ngm:retrieval-augmented-generation ;
vc:relatedTo ngm:transfer-learning ;
vc:requires ngm:calibration ;
vc:requires ngm:cross-validation ;
vc:requires ngm:exchangeability ;
vc:requires ngm:probability-theory ;
vc:slug "conformal-prediction" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:supports ngm:autonomous-system ;
vc:supports ngm:computer-vision ;
vc:supports ngm:drug-discovery ;
vc:supports ngm:medical-imaging ;
vc:supports ngm:multi-label-classification ;
vc:supports ngm:natural-language-processing ;
vc:supports ngm:object-detection ;
vc:supports ngm:reinforcement-learning ;
vc:supports ngm:time-series-forecasting ;
vc:uses ngm:deep-learning ;
vc:uses ngm:ensemble-methods ;
vc:uses ngm:foundation-model ;
vc:uses ngm:gaussian-process ;
vc:uses ngm:mc-dropout ;
vc:uses ngm:monte-carlo-methods ;
vc:uses ngm:neural-network ;
vc:uses ngm:variational-inference .
ngm:conformance a skos:Concept ;
rdfs:label "Conformance"@en .
ngm:conformer-architecture a skos:Concept ;
rdfs:label "Conformer Architecture"@en .
ngm:conformity-assessment a owl:Class ;
rdfs:comment "Conformity Assessment is a structured set of procedures used to determine whether a product, system, service, or process meets specified requirements defined in regulations, standards, or contractual obligations. In the context of AI and digital systems, it encompasses technical documentation review, testing, auditing, risk analysis, and post-market surveillance carried out either by the developer as a self-assessment or by an accredited third-party notified body. Under frameworks such as the EU AI Act, ISO/IEC 17000-series standards, and NIST guidelines, the conformity declaration produced is a legal and operational precondition for market entry and continued deployment. It inherits procedural principles from product safety certification while adapting them to the probabilistic, data-dependent, and emergent behaviour of machine learning systems."@en ;
rdfs:label "Conformity Assessment"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf _:r5312 ;
rdfs:subClassOf _:r5313 ;
rdfs:subClassOf _:r5314 ;
rdfs:subClassOf _:r5315 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:federated-learning ;
vc:bridgesTo ngm:model-cards ;
vc:contrastsWith ngm:self-certification ;
vc:contrastsWith ngm:voluntary-disclosure ;
vc:dependsOn ngm:data-governance ;
vc:dependsOn ngm:market-surveillance ;
vc:enables ngm:market-access ;
vc:enables ngm:regulatory-compliance ;
vc:enables ngm:trustworthy-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:eu-ai-act-regulatory-instrument ;
vc:implements ngm:iso-iec-17000 ;
vc:implements ngm:nist-ai-rmf ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:accreditation ;
vc:relatedTo ngm:certification ;
vc:requires ngm:auditability ;
vc:requires ngm:risk-assessment ;
vc:requires ngm:technical-documentation ;
vc:requires ngm:transparency ;
vc:slug "conformity-assessment" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:etsi ;
vc:standardizedBy ngm:iso-iec-jtc1-sc42 ;
vc:standardizedBy ngm:nist ;
vc:supports ngm:ai-regulation ;
vc:supports ngm:ai-safety ;
vc:supports ngm:consumer-protection ;
vc:uses ngm:bias-testing ;
vc:uses ngm:explainability ;
vc:uses ngm:model-evaluation ;
vc:uses ngm:robustness-testing .
ngm:conformity-assessment-body a owl:Class ;
rdfs:comment "A conformity assessment body is an accredited organisation authorised to evaluate whether products, processes, or services meet specified standards or regulatory requirements. It performs testing, inspection, and certification activities and issues the formal attestations that allow goods to be placed on a market. Such bodies are themselves accredited by national accreditation authorities to ensure impartiality and competence."@en ;
rdfs:label "Conformity Assessment Body"@en ;
rdfs:subClassOf ngm:standards-body ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:robot-standard ;
vc:relatedTo ngm:trust-framework ;
vc:slug "conformity-assessment-body" ;
vc:sourceDomain "governance" .
ngm:confounding-variable a skos:Concept ;
rdfs:label "Confounding Variable"@en .
ngm:confusion-matrix a owl:Class ;
rdfs:comment "A tabular visualisation and analytical tool summarising the performance of a classification model by displaying the counts or proportions of predictions cross-tabulated against actual class labels, typically organised with predicted classes as columns and actual classes as rows (or vice versa), enabling systematic analysis of where a model succeeds and fails, calculation of various performance metrics, and identification of specific confusion patterns between classes."@en ;
rdfs:label "Confusion Matrix"@en ;
rdfs:subClassOf ngm:model-evaluation ;
rdfs:subClassOf _:r5316 ;
rdfs:subClassOf _:r5317 ;
rdfs:subClassOf _:r5318 ;
rdfs:subClassOf _:r5319 ;
rdfs:subClassOf _:r5320 ;
rdfs:subClassOf _:r5321 ;
vc:bridgesTo ngm:ai-audit ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:evaluation-metric ;
vc:contrastsWith ngm:roc-curve ;
vc:enables ngm:error-analysis ;
vc:enables ngm:fairness-assessment ;
vc:enables ngm:model-debugging ;
vc:enables ngm:threshold-optimisation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:false-negative ;
vc:hasPart ngm:false-positive ;
vc:hasPart ngm:true-negative ;
vc:hasPart ngm:true-positive ;
vc:isPartOf ngm:model-performance ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:ai-model-card ;
vc:relatedTo ngm:class-imbalance ;
vc:requires ngm:classification ;
vc:requires ngm:ground-truth-labels ;
vc:slug "confusion-matrix" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:iso-iec-25059 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:accuracy ;
vc:supports ngm:f1-score ;
vc:supports ngm:precision ;
vc:supports ngm:recall ;
vc:supports ngm:sensitivity ;
vc:supports ngm:specificity ;
vc:uses ngm:cross-validation ;
vc:uses ngm:supervised-learning .
ngm:confusion-matrix-slice a skos:Concept ;
rdfs:label "Confusion Matrix Slice"@en .
ngm:congelation-ice a owl:Class ;
rdfs:label "Congelation Ice"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-system-phenomena ;
vc:slug "congelation-ice" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:congestion-control a owl:Class ;
rdfs:comment "Congestion Control is the set of mechanisms and algorithms that regulate the rate of data transmission across a network to prevent any sender, link, or node from being overwhelmed by more traffic than it can handle, thereby maintaining overall network stability and fairness. Operating primarily at the transport layer, congestion control algorithms infer network capacity from signals such as packet loss, explicit congestion notification, and round-trip time variations, adjusting sender rates accordingly. Classical implementations include TCP Tahoe, Reno, CUBIC, and BBR; modern variants extend to QUIC, WebRTC, and multipath scenarios where joint path management adds additional complexity."@en ;
rdfs:label "Congestion Control"@en ;
rdfs:subClassOf ngm:network-protocol ;
rdfs:subClassOf _:r5322 ;
vc:bridgesTo ngm:cdn ;
vc:bridgesTo ngm:reinforcement-learning ;
vc:contrastsWith ngm:flow-control ;
vc:contrastsWith ngm:traffic-shaping ;
vc:dependsOn ngm:internet-protocol ;
vc:dependsOn ngm:transport-layer ;
vc:enables ngm:fairness ;
vc:enables ngm:latency-management-protocol ;
vc:enables ngm:peer-to-peer-network ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:active-queue-management ;
vc:implements ngm:bbr-algorithm ;
vc:implements ngm:quic ;
vc:implements ngm:tcp-cubic ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:bandwidth-adaptation ;
vc:relatedTo ngm:network-latency ;
vc:relatedTo ngm:quality-of-service ;
vc:requires ngm:packet-loss-recovery ;
vc:requires ngm:round-trip-time-measurement ;
vc:slug "congestion-control" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:ietf ;
vc:supports ngm:distributed-computing ;
vc:supports ngm:networking-infrastructure ;
vc:supports ngm:real-time-communication ;
vc:uses ngm:sliding-window-protocol .
ngm:congestion-signal a skos:Concept ;
rdfs:label "Congestion Signal"@en .
ngm:conjugate-function a skos:Concept ;
rdfs:label "Conjugate Function"@en .
ngm:conjugate-prior a skos:Concept ;
rdfs:label "Conjugate Prior"@en .
ngm:conjunctive-query-answering a skos:Concept ;
rdfs:label "Conjunctive Query Answering"@en .
ngm:conll-2010-shared-task a skos:Concept ;
rdfs:label "Conll 2010 Shared Task"@en .
ngm:conll-2012-shared-task a skos:Concept ;
rdfs:label "Conll 2012 Shared Task"@en .
ngm:connected-comparison-graph a skos:Concept ;
rdfs:label "Connected Comparison Graph"@en .
ngm:connected-components a skos:Concept ;
rdfs:label "Connected Components"@en .
ngm:connected-society a skos:Concept ;
rdfs:label "Connected Society"@en .
ngm:connection-management a skos:Concept ;
rdfs:label "Connection Management"@en .
ngm:connection-migration a skos:Concept ;
rdfs:label "Connection Migration"@en .
ngm:connection-pool a skos:Concept ;
rdfs:label "Connection Pool"@en .
ngm:connection-protocol a skos:Concept ;
rdfs:label "Connection Protocol"@en .
ngm:connectionism a owl:Class ;
rdfs:comment "Connectionism is an approach in cognitive science and artificial intelligence that models mental and computational phenomena as emergent from networks of simple, densely interconnected units whose collective activity, governed by weighted connections, gives rise to behaviour. It treats knowledge as distributed across connection strengths rather than stored as explicit symbols, and learning as the adjustment of those weights through experience. The paradigm provides the theoretical foundation for artificial neural networks and deep learning."@en ;
rdfs:label "Connectionism"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:cognitive-science ;
rdfs:subClassOf _:r5323 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:cognitive-science ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:contrastsWith ngm:symbolic-ai ;
vc:contrastsWith ngm:symbolic-reasoning ;
vc:enables ngm:deep-learning ;
vc:enables ngm:machine-learning-discipline ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:neural-network ;
vc:implements ngm:neural-network ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:artificial-general-intelligence ;
vc:relatedTo ngm:deep-learning ;
vc:relatedTo ngm:neural-network ;
vc:slug "connectionism" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:artificial-intelligence ;
vc:uses ngm:backpropagation ;
vc:uses ngm:gradient-descent .
ngm:connectionist-temporal-classification a owl:Class ;
rdfs:comment "Connectionist Temporal Classification (CTC) is a sequence-modelling loss function and decoding scheme that trains neural networks to map unsegmented input sequences to output label sequences without requiring pre-aligned data. It introduces a blank symbol and marginalises over all valid alignments, allowing a network to learn the alignment implicitly during training. CTC is widely used in speech recognition and handwriting recognition where input and output lengths differ and frame-level labels are unavailable."@en ;
rdfs:label "Connectionist Temporal Classification"@en ;
rdfs:subClassOf ngm:speech-recognition ;
rdfs:subClassOf _:r5324 ;
rdfs:subClassOf _:r5325 ;
rdfs:subClassOf _:r5326 ;
rdfs:subClassOf _:r5327 ;
vc:contrastsWith ngm:attention-mechanism ;
vc:contrastsWith ngm:transformer ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:enables ngm:automatic-speech-recognition ;
vc:enables ngm:real-time-translation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:alignment ;
vc:hasPart ngm:loss-function ;
vc:implements ngm:sequence-to-sequence ;
vc:implements ngm:speech-to-text ;
vc:isPartOf ngm:speech-recognition ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:acoustic-model ;
vc:relatedTo ngm:language-model ;
vc:requires ngm:neural-network ;
vc:requires ngm:recurrent-neural-network ;
vc:slug "connectionist-temporal-classification" ;
vc:sourceDomain "distributed-collaboration" ;
vc:uses ngm:beam-search ;
vc:uses ngm:loss-function ;
vc:uses ngm:lstm .
ngm:connectivism a skos:Concept ;
rdfs:label "Connectivism"@en .
ngm:connectivity-fabric a skos:Concept ;
rdfs:label "Connectivity Fabric"@en .
ngm:connectivity-standards-alliance a skos:Concept ;
rdfs:label "Connectivity Standards Alliance"@en .
ngm:connector a skos:Concept ;
rdfs:label "Connector"@en .
ngm:connector-standards a owl:Class ;
rdfs:comment "Connector standards are specifications that define the mechanical form factor, pin assignment, and electrical signalling of the physical interfaces used to join cables and devices. They guarantee interoperability across vendors at the physical layer, covering examples such as USB-C, RJ45, and HDMI. Standardised connectors reduce fragmentation and enable plug-and-play interconnection."@en ;
rdfs:label "Connector Standards"@en ;
rdfs:subClassOf ngm:technical-standard ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:physical-layer ;
vc:slug "connector-standards" ;
vc:sourceDomain "infrastructure" .
ngm:connext a owl:Class ;
rdfs:comment "A cross-chain interoperability protocol that enables fast transfers and contract calls between Ethereum-compatible blockchains and Layer 2 networks without relying on a single trusted custodian, coordinating liquidity routers and a verification layer to achieve trust-minimised cross-chain composability."@en ;
rdfs:label "Connext"@en ;
rdfs:subClassOf ngm:cross-chain-bridge ;
rdfs:subClassOf _:r5328 ;
rdfs:subClassOf _:r5329 ;
rdfs:subClassOf _:r5330 ;
rdfs:subClassOf _:r5331 ;
vc:bridgesTo ngm:cross-chain-bridge ;
vc:bridgesTo ngm:distributed-systems ;
vc:bridgesTo ngm:infrastructure ;
vc:contrastsWith ngm:trusted-bridge ;
vc:contrastsWith ngm:wrapped-token ;
vc:dependsOn ngm:ethereum ;
vc:dependsOn ngm:evm-compatibility ;
vc:enables ngm:atomic-swap ;
vc:enables ngm:cross-chain-composability ;
vc:enables ngm:cross-chain-messaging ;
vc:enables ngm:interoperability ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:cross-chain-bridge ;
vc:relatedTo ngm:intent-based-bridging ;
vc:requires ngm:ethereum-smart-contract-platform ;
vc:requires ngm:liquidity-pool ;
vc:requires ngm:smart-contract ;
vc:requires ngm:squid-router ;
vc:slug "connext" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:de-fi ;
vc:supports ngm:layer-2-scaling ;
vc:supports ngm:rollup ;
vc:uses ngm:automated-market-maker ;
vc:uses ngm:hashed-timelock-contract ;
vc:uses ngm:optimistic-verification .
ngm:consciousness a skos:Concept ;
rdfs:label "Consciousness"@en .
ngm:consciousness-studies a skos:Concept ;
rdfs:label "Consciousness Studies"@en .
ngm:consecutive-interpretation a skos:Concept ;
rdfs:label "Consecutive Interpretation"@en .
ngm:consen-sys a owl:Class ;
rdfs:comment "ConsenSys is a Brooklyn-founded blockchain software company, established in 2014 by Ethereum co-founder Joseph Lubin, that builds developer tooling, infrastructure, and end-user products for the Ethereum ecosystem. Its product portfolio spans the MetaMask browser wallet, the Infura node-as-a-service API network, the Truffle and Hardhat-adjacent development suite, and the Linea zkEVM Layer 2 network. ConsenSys acts as a principal driver of Ethereum protocol adoption by providing the production-grade infrastructure on which the majority of decentralised application front-ends depend. The company also engages in enterprise blockchain consulting and contributes to Ethereum standards through active participation in the Ethereum Foundation and EIP processes."@en ;
rdfs:label "ConsenSys"@en ;
rdfs:subClassOf ngm:network-component ;
rdfs:subClassOf _:r5332 ;
rdfs:subClassOf _:r5333 ;
rdfs:subClassOf _:r5334 ;
vc:bridgesTo ngm:digital-asset-custody ;
vc:bridgesTo ngm:enterprise-blockchain ;
vc:contrastsWith ngm:alchemy ;
vc:contrastsWith ngm:coinbase ;
vc:enables ngm:de-fi ;
vc:enables ngm:decentralised-application ;
vc:enables ngm:web3 ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:infura ;
vc:hasPart ngm:linea ;
vc:hasPart ngm:meta-mask ;
vc:hasPart ngm:truffle-suite ;
vc:implements ngm:eip ;
vc:implements ngm:zk-rollup ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:ethereum-smart-contract-platform-foundation ;
vc:relatedTo ngm:layer-2-scaling ;
vc:relatedTo ngm:token-standard ;
vc:requires ngm:ethereum ;
vc:requires ngm:proof-of-stake ;
vc:slug "consen-sys" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:decentralised-identity ;
vc:supports ngm:ethereum-smart-contract-platform-virtual-machine ;
vc:supports ngm:non-fungible-token ;
vc:uses ngm:json-data-interchange-format-rpc ;
vc:uses ngm:smart-contract ;
vc:uses ngm:solidity .
ngm:consensual-avatar a skos:Concept ;
rdfs:label "Consensual Avatar"@en .
ngm:consensus a owl:Class ;
rdfs:comment "The general problem of getting distributed processes to agree on a common value or decision despite failures, communication delays or adversarial behaviour."@en ;
rdfs:label "Consensus"@en ;
rdfs:subClassOf ngm:distributed-systems ;
rdfs:subClassOf _:r5382 ;
rdfs:subClassOf _:r5383 ;
rdfs:subClassOf _:r5384 ;
rdfs:subClassOf _:r5385 ;
rdfs:subClassOf _:r5386 ;
rdfs:subClassOf _:r5387 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:bridgesTo ngm:tendermint ;
vc:contrastsWith ngm:cap-theorem ;
vc:contrastsWith ngm:eventual-consistency ;
vc:enables ngm:atomic-broadcast ;
vc:enables ngm:consensus-mechanisms ;
vc:enables ngm:distributed-databases ;
vc:enables ngm:distributed-ledger ;
vc:enables ngm:state-machine-replication ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:leader-election ;
vc:hasPart ngm:voting-round ;
vc:implements ngm:byzantine-fault-tolerance ;
vc:implements ngm:paxos ;
vc:implements ngm:raft ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:byzantine-generals-problem ;
vc:relatedTo ngm:partial-synchrony ;
vc:relatedTo ngm:tendermint ;
vc:requires ngm:distributed-systems ;
vc:requires ngm:fault-tolerance ;
vc:requires ngm:message-passing ;
vc:requires ngm:quorum ;
vc:slug "consensus" ;
vc:sourceDomain "distributed-systems" ;
vc:supports ngm:blockchain ;
vc:supports ngm:smart-contract ;
vc:uses ngm:cryptographic-hash ;
vc:uses ngm:digital-signature .
ngm:consensus-algorithm a owl:Class ;
rdfs:comment "Distributed computational protocol ensuring all participants in a Blockchain Network agree on the canonical transaction history and current state without centralised authority, tolerating a bounded fraction of faulty or malicious nodes."@en ;
rdfs:label "Consensus Algorithm"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf _:r5335 ;
rdfs:subClassOf _:r5336 ;
rdfs:subClassOf _:r5337 ;
rdfs:subClassOf _:r5338 ;
rdfs:subClassOf _:r5339 ;
rdfs:subClassOf _:r5340 ;
rdfs:subClassOf _:r5341 ;
rdfs:subClassOf _:r5342 ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:multi-agent-system ;
vc:contrastsWith ngm:centralised-database ;
vc:contrastsWith ngm:two-phase-commit ;
vc:dependsOn ngm:cryptographic-hash-function ;
vc:dependsOn ngm:digital-signature ;
vc:dependsOn ngm:fault-tolerance ;
vc:enables ngm:blockchain-transaction ;
vc:enables ngm:distributed-ledger ;
vc:enables ngm:transaction-finality ;
vc:enables ngm:trustless-coordination ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:delegated-proof-of-stake ;
vc:hasPart ngm:practical-byzantine-fault-tolerance ;
vc:hasPart ngm:proof-of-stake ;
vc:hasPart ngm:proof-of-work ;
vc:implements ngm:distributed-consensus ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:data-integrity ;
vc:relatedTo ngm:network-security ;
vc:relatedTo ngm:sharding ;
vc:requires ngm:blockchain-network ;
vc:requires ngm:byzantine-fault-tolerance ;
vc:requires ngm:peer-to-peer-network ;
vc:requires ngm:validator-node ;
vc:slug "consensus-algorithm" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:dao ;
vc:supports ngm:decentralised-governance ;
vc:supports ngm:smart-contract .
ngm:consensus-layer a owl:Class ;
rdfs:comment "The Consensus Layer is the stratum responsible for agreement on a single canonical ordering of events across distributed participants. In the canonical stack it sits directly above the Protocol Layer and below the Data Layer, converting peer-to-peer message exchange into a shared, append-only history. It contains the agreement algorithms, fork-choice rules, and finality conditions that all participants follow."@en ;
rdfs:label "Consensus Layer"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf ngm:owl-thing ;
rdfs:subClassOf _:r5343 ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:bridgesTo ngm:byzantine-fault-tolerance ;
vc:bridgesTo ngm:proof-of-stake ;
vc:enables ngm:data-layer ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:protocol-layer ;
vc:slug "consensus-layer" ;
vc:sourceDomain "blockchain" .
ngm:consensus-mechanism a owl:Class ;
rdfs:comment "A Consensus Mechanism is a Distributed Algorithm enabling a population of independent, potentially adversarial nodes communicating over an unreliable network to agree on a single, totally-ordered sequence of state transitions (a replicated log) such that all honest participants eventually..."@en ;
rdfs:label "Consensus Mechanism"@en ;
rdfs:subClassOf ngm:atomic-broadcast ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf ngm:byzantine-fault-tolerance ;
rdfs:subClassOf ngm:coordination-protocol ;
rdfs:subClassOf ngm:distributed-algorithm ;
rdfs:subClassOf ngm:state-machine-replication ;
rdfs:subClassOf _:r5344 ;
rdfs:subClassOf _:r5345 ;
rdfs:subClassOf _:r5346 ;
rdfs:subClassOf _:r5347 ;
rdfs:subClassOf _:r5348 ;
rdfs:subClassOf _:r5349 ;
rdfs:subClassOf _:r5350 ;
rdfs:subClassOf _:r5351 ;
rdfs:subClassOf _:r5352 ;
rdfs:subClassOf _:r5353 ;
rdfs:subClassOf _:r5354 ;
rdfs:subClassOf _:r5355 ;
rdfs:subClassOf _:r5356 ;
rdfs:subClassOf _:r5357 ;
rdfs:subClassOf _:r5358 ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:bridgesTo ngm:coordination-protocol ;
vc:contrastsWith ngm:byzantine-quorum-without-total-order ;
vc:contrastsWith ngm:centralised-consensus ;
vc:contrastsWith ngm:coordinator-based-tangle ;
vc:contrastsWith ngm:crdt ;
vc:contrastsWith ngm:eventually-consistent-system ;
vc:contrastsWith ngm:single-source-of-truth-database ;
vc:dependsOn ngm:cap-theorem ;
vc:dependsOn ngm:cryptographic-hash-function ;
vc:dependsOn ngm:flp-impossibility ;
vc:dependsOn ngm:game-theory ;
vc:dependsOn ngm:network-synchrony-model ;
vc:dependsOn ngm:threshold-signature-scheme ;
vc:dependsOn ngm:verifiable-random-function ;
vc:enables ngm:blockchain-security ;
vc:enables ngm:censorship-resistance ;
vc:enables ngm:double-spend-prevention ;
vc:enables ngm:permissionless-participation ;
vc:enables ngm:state-synchronisation ;
vc:enables ngm:sybil-resistance ;
vc:enables ngm:trustless-settlement ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:block-proposal ;
vc:hasPart ngm:cryptographic-signature ;
vc:hasPart ngm:finality-gadget ;
vc:hasPart ngm:fork-choice-rule ;
vc:hasPart ngm:leader-election ;
vc:hasPart ngm:quorum-certificate ;
vc:hasPart ngm:slashing-condition ;
vc:hasPart ngm:validator-set ;
vc:hasPart ngm:view-change ;
vc:hasPart ngm:voting-round ;
vc:implements ngm:avalanche ;
vc:implements ngm:hedera-hashgraph ;
vc:implements ngm:hot-stuff ;
vc:implements ngm:nakamoto-consensus ;
vc:implements ngm:paxos ;
vc:implements ngm:practical-byzantine-fault-tolerance ;
vc:implements ngm:proof-of-authority ;
vc:implements ngm:proof-of-history ;
vc:implements ngm:proof-of-stake ;
vc:implements ngm:proof-of-work ;
vc:implements ngm:raft ;
vc:implements ngm:tendermint ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:blockchain-protocol ;
vc:relatedTo ngm:decentralisation ;
vc:relatedTo ngm:distributed-ledger ;
vc:relatedTo ngm:finality ;
vc:relatedTo ngm:mev ;
vc:relatedTo ngm:scalability ;
vc:relatedTo ngm:validator-economics ;
vc:requires ngm:blockchain-network ;
vc:requires ngm:clock-synchronization ;
vc:requires ngm:cryptographic-hash ;
vc:requires ngm:digital-signature ;
vc:requires ngm:economic-incentive ;
vc:requires ngm:incentive-mechanism ;
vc:requires ngm:peer-to-peer-network ;
vc:requires ngm:validator-registry ;
vc:slug "consensus-mechanism" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:bitcoin-proof-of-work-protocol ;
vc:standardizedBy ngm:cosmos ;
vc:standardizedBy ngm:ethereum-smart-contract-platform ;
vc:standardizedBy ngm:ietf ;
vc:standardizedBy ngm:iso-tc-307-blockchain-standards ;
vc:standardizedBy ngm:nist-post-quantum-cryptography ;
vc:supports ngm:cross-chain-bridge ;
vc:supports ngm:cross-chain-bridges ;
vc:supports ngm:data-availability ;
vc:supports ngm:de-fi ;
vc:supports ngm:distributed-ledger-technology ;
vc:supports ngm:layer-2-solutions ;
vc:supports ngm:smart-contract-execution ;
vc:uses ngm:bls-signature ;
vc:uses ngm:erasure-coding ;
vc:uses ngm:gossip-protocol ;
vc:uses ngm:merkle-tree ;
vc:uses ngm:quorum-intersection ;
vc:uses ngm:threshold-cryptography ;
vc:uses ngm:verifiable-random-function .
ngm:consensus-mechanisms a owl:Class ;
rdfs:comment "The family of protocols by which distributed participants agree on a single shared state or ordering of events without relying on a central authority, spanning classical fault-tolerant algorithms, probabilistic approaches, and cryptoeconomic incentive designs."@en ;
rdfs:label "Consensus Mechanisms"@en ;
rdfs:subClassOf ngm:distributed-systems ;
rdfs:subClassOf _:r5359 ;
rdfs:subClassOf _:r5360 ;
rdfs:subClassOf _:r5361 ;
rdfs:subClassOf _:r5362 ;
rdfs:subClassOf _:r5363 ;
rdfs:subClassOf _:r5364 ;
rdfs:subClassOf _:r5365 ;
rdfs:subClassOf _:r5366 ;
rdfs:subClassOf _:r5367 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:governance ;
vc:bridgesTo ngm:proof-of-stake ;
vc:bridgesTo ngm:security ;
vc:bridgesTo ngm:tendermint ;
vc:contrastsWith ngm:leader-election ;
vc:dependsOn ngm:cryptography ;
vc:dependsOn ngm:digital-signatures ;
vc:dependsOn ngm:hash-functions ;
vc:enables ngm:blockchain ;
vc:enables ngm:de-fi ;
vc:enables ngm:distributed-ledger ;
vc:enables ngm:smart-contracts ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:byzantine-fault-tolerance ;
vc:hasPart ngm:delegated-proof-of-stake ;
vc:hasPart ngm:practical-byzantine-fault-tolerance ;
vc:hasPart ngm:proof-of-stake ;
vc:hasPart ngm:proof-of-work ;
vc:hasPart ngm:tendermint ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:finality ;
vc:relatedTo ngm:validator-node ;
vc:requires ngm:consensus ;
vc:requires ngm:fault-tolerance ;
vc:requires ngm:peer-to-peer-network ;
vc:slug "consensus-mechanisms" ;
vc:sourceDomain "distributed-systems" ;
vc:supports ngm:decentralization ;
vc:supports ngm:immutability ;
vc:supports ngm:sybil-resistance .
ngm:consensus-process a owl:Class ;
rdfs:comment "A consensus process is the structured, participatory procedure by which a standards body or governance group develops, refines, and adopts decisions through deliberation aimed at broad agreement rather than narrow majority voting. It gathers stakeholder input, circulates drafts for review and public comment, resolves objections substantively, and seeks a state of general acceptance — often characterised as rough consensus — where remaining dissent has been heard and addressed. The process underpins the legitimacy and durability of open standards by ensuring decisions reflect the considered views of affected parties rather than the preferences of a dominant actor."@en ;
rdfs:label "Consensus Process"@en ;
rdfs:subClassOf ngm:standards ;
rdfs:subClassOf _:r5368 ;
rdfs:subClassOf _:r5369 ;
rdfs:subClassOf _:r5370 ;
vc:contrastsWith ngm:voting ;
vc:contrastsWith ngm:voting-mechanism ;
vc:dependsOn ngm:consensus ;
vc:dependsOn ngm:stakeholder-engagement ;
vc:enables ngm:open-standards ;
vc:enables ngm:technical-standard ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:public-comment ;
vc:hasPart ngm:working-group ;
vc:implements ngm:standards-body ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:ietf ;
vc:relatedTo ngm:iso ;
vc:requires ngm:decision-making ;
vc:requires ngm:deliberation ;
vc:requires ngm:stakeholder-engagement ;
vc:slug "consensus-process" ;
vc:sourceDomain "standards" ;
vc:supports ngm:interoperability ;
vc:uses ngm:rough-consensus ;
vc:uses ngm:voting ;
vc:uses ngm:voting-mechanism .
ngm:consensus-protocol a owl:Class ;
rdfs:comment "A consensus protocol is a set of rules and algorithms by which distributed network participants reach agreement on a single shared state or value without requiring centralised authority, ensuring liveness, safety, and Byzantine fault tolerance up to a specified threshold of adversarial nodes. Classical families include compute-bound Proof-of-Work, stake-weighted Proof-of-Stake, and message-passing BFT protocols such as PBFT, Tendermint, and HotStuff. Each protocol specifies leader election, block proposal, voting rounds, and finality conditions that together determine throughput, latency, decentralisation, and security trade-offs. Consensus protocols underpin blockchains, distributed databases, and any replicated state machine requiring deterministic agreement across potentially unreliable or malicious peers."@en ;
rdfs:label "Consensus Protocol"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf _:r5371 ;
rdfs:subClassOf _:r5372 ;
rdfs:subClassOf _:r5373 ;
rdfs:subClassOf _:r5374 ;
rdfs:subClassOf _:r5375 ;
rdfs:subClassOf _:r5376 ;
rdfs:subClassOf _:r5377 ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:bridgesTo ngm:federated-learning ;
vc:bridgesTo ngm:multi-agent-coordination ;
vc:contrastsWith ngm:centralised-database ;
vc:contrastsWith ngm:raft-consensus ;
vc:dependsOn ngm:network-topology ;
vc:dependsOn ngm:sybil-resistance ;
vc:enables ngm:blockchain ;
vc:enables ngm:de-fi ;
vc:enables ngm:distributed-ledger ;
vc:enables ngm:smart-contract ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:byzantine-fault-tolerance ;
vc:hasPart ngm:finality-gadget ;
vc:hasPart ngm:proof-of-stake ;
vc:hasPart ngm:proof-of-work ;
vc:implements ngm:distributed-agreement ;
vc:implements ngm:state-machine-replication ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:block-production ;
vc:relatedTo ngm:fork-choice-rule ;
vc:relatedTo ngm:leader-election ;
vc:relatedTo ngm:paxos ;
vc:relatedTo ngm:validator-node ;
vc:requires ngm:cryptographic-hash-function ;
vc:requires ngm:digital-signature ;
vc:requires ngm:peer-to-peer-network ;
vc:slug "consensus-protocol" ;
vc:sourceDomain "blockchain" .
ngm:consensus-protocols a skos:Concept ;
rdfs:label "Consensus Protocols"@en .
ngm:consensus-research a skos:Concept ;
rdfs:label "Consensus Research"@en .
ngm:consensus-rule a owl:Class ;
rdfs:comment "A Consensus Rule is a protocol-level validation requirement that every fully-validating node in a blockchain network must enforce uniformly to reach and maintain agreement on the canonical chain state. Consensus rules define which blocks and transactions are valid, covering aspects such as block structure, cryptographic proofs, transaction format, gas limits, and state-transition logic. Deviation from consensus rules — whether accidental or deliberate — results in a fork, splitting the network into incompatible chains."@en ;
rdfs:label "Consensus Rule"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf ngm:blockchain-entity ;
rdfs:subClassOf ngm:consensus-protocol ;
rdfs:subClassOf _:r5378 ;
rdfs:subClassOf _:r5379 ;
rdfs:subClassOf _:r5380 ;
rdfs:subClassOf _:r5381 ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:contrastsWith ngm:governance-model ;
vc:enables ngm:blockchain-governance ;
vc:enables ngm:finality ;
vc:enables ngm:smart-contract ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:fork-choice-rule ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:51-attack ;
vc:relatedTo ngm:blockchain ;
vc:relatedTo ngm:byzantine-fault-tolerance ;
vc:relatedTo ngm:proof-of-stake ;
vc:relatedTo ngm:proof-of-work ;
vc:relatedTo ngm:validator-set ;
vc:requires ngm:blockchain-network ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:distributed-ledger ;
vc:slug "consensus-rule" ;
vc:sourceDomain "blockchain" .
ngm:consensus-rules a skos:Concept ;
rdfs:label "Consensus Rules"@en .
ngm:consensus-security a skos:Concept ;
rdfs:label "Consensus Security"@en .
ngm:consensus-service a skos:Concept ;
rdfs:label "Consensus Service"@en .
ngm:consensus-standardisation a skos:Concept ;
rdfs:label "Consensus Standardisation"@en .
ngm:consent-audit-trail a skos:Concept ;
rdfs:label "Consent Audit Trail"@en .
ngm:consent-management a owl:Class ;
rdfs:comment "System for recording and enforcing user permissions for data collection, processing, and sharing across metaverse platforms, ensuring compliance with privacy regulations and user autonomy."@en ;
rdfs:label "Consent Management"@en ;
rdfs:subClassOf ngm:infra-legal-and-regulatory ;
rdfs:subClassOf _:r5388 ;
rdfs:subClassOf _:r5389 ;
rdfs:subClassOf _:r5390 ;
rdfs:subClassOf _:r5391 ;
rdfs:subClassOf _:r5392 ;
rdfs:subClassOf _:r5393 ;
rdfs:subClassOf _:r5394 ;
rdfs:subClassOf _:r5395 ;
rdfs:subClassOf _:r5396 ;
skos:broader ngm:infra-legal-and-regulatory ;
vc:bridgesTo ngm:telecollaboration ;
vc:enables ngm:data-privacy ;
vc:enables ngm:gdpr-compliance ;
vc:enables ngm:right-to-be-forgotten ;
vc:enables ngm:transparency ;
vc:enables ngm:user-control ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:audit-logging ;
vc:hasPart ngm:consent-registry ;
vc:hasPart ngm:permission-controller ;
vc:hasPart ngm:policy-engine ;
vc:hasPart ngm:user-interface ;
vc:isPartOf ngm:etsi-domain-data-management-ethics ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:data-governance-framework ;
vc:requires ngm:identity-provider ;
vc:requires ngm:privacy-policy ;
vc:requires ngm:user-authentication ;
vc:slug "consent-management" ;
vc:sourceDomain "infrastructure" .
ngm:consent-management-platform a skos:Concept ;
rdfs:label "Consent Management Platform"@en .
ngm:consent-payload a skos:Concept ;
rdfs:label "Consent Payload"@en .
ngm:consent-registry a owl:Class ;
rdfs:comment "A consent registry is a system of record that stores, versions, and serves the consent decisions data subjects have granted or withdrawn for processing their personal data. It provides an auditable, queryable source of truth that data controllers and processors consult before performing a processing activity. It is a central component of privacy-compliance and consent-management architectures."@en ;
rdfs:label "Consent Registry"@en ;
rdfs:subClassOf ngm:identity-management ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:consent-management ;
vc:relatedTo ngm:user-consent-token ;
vc:slug "consent-registry" ;
vc:sourceDomain "security" .
ngm:consent-revocation a skos:Concept ;
rdfs:label "Consent Revocation"@en .
ngm:consent-verification a skos:Concept ;
rdfs:label "Consent Verification"@en .
ngm:consequence-based-algorithm a skos:Concept ;
rdfs:label "Consequence Based Algorithm"@en .
ngm:conservation-database a skos:Concept ;
rdfs:label "Conservation Database"@en .
ngm:conservative-advancement a skos:Concept ;
rdfs:label "Conservative Advancement"@en .
ngm:consignment a skos:Concept ;
rdfs:label "Consignment"@en .
ngm:consignment-protocol a skos:Concept ;
rdfs:label "Consignment Protocol"@en .
ngm:consistency a skos:Concept ;
rdfs:label "Consistency"@en .
ngm:consistency-checking a owl:Class ;
rdfs:comment "Consistency checking is the process of verifying that a set of statements, data items or constraints contains no contradictions and that all derivable conclusions remain mutually compatible. In knowledge representation it confirms that an ontology or knowledge base admits at least one model, while in data systems it confirms that records satisfy declared integrity rules. The technique underpins trust in automated reasoning by rejecting configurations that would license arbitrary or unsound inferences."@en ;
rdfs:label "Consistency Checking"@en ;
rdfs:subClassOf ngm:verification ;
rdfs:subClassOf _:r5397 ;
rdfs:subClassOf _:r5398 ;
vc:enables ngm:data-integrity ;
vc:enables ngm:inference ;
vc:enables ngm:reasoning ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:schema-validation ;
vc:relatedTo ngm:semantic-web-linked-data-standard ;
vc:requires ngm:formal-verification ;
vc:requires ngm:knowledge-representation ;
vc:slug "consistency-checking" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:data-validation ;
vc:supports ngm:quality-assurance ;
vc:uses ngm:constraint-satisfaction ;
vc:uses ngm:inference-engine ;
vc:uses ngm:theorem-proving .
ngm:consistency-distillation a skos:Concept ;
rdfs:label "Consistency Distillation"@en .
ngm:consistency-guarantees a skos:Concept ;
rdfs:label "Consistency Guarantees"@en .
ngm:consistency-model a owl:Class ;
rdfs:comment "A consistency model is a contract between a distributed data store and its clients that specifies the guarantees about the visibility and ordering of reads and writes across replicas. It defines which outcomes of concurrent operations are permissible, ranging from strong models like linearizability that behave as a single up-to-date copy, to weak models like eventual consistency that allow temporary divergence. The chosen model shapes application correctness, performance, and the achievable balance among consistency, availability, and partition tolerance."@en ;
rdfs:label "Consistency Model"@en ;
rdfs:subClassOf ngm:distributed-data-structure ;
rdfs:subClassOf _:r5399 ;
rdfs:subClassOf _:r5400 ;
rdfs:subClassOf _:r5401 ;
rdfs:subClassOf _:r5402 ;
vc:bridgesTo ngm:distributed-systems ;
vc:contrastsWith ngm:partition-tolerance ;
vc:dependsOn ngm:consensus-mechanism ;
vc:dependsOn ngm:replication-protocol ;
vc:enables ngm:fault-tolerance ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:eventual-consistency ;
vc:hasPart ngm:linearizability ;
vc:hasPart ngm:strong-consistency ;
vc:isPartOf ngm:distributed-data-structure ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:cap-theorem ;
vc:relatedTo ngm:partition-tolerance ;
vc:relatedTo ngm:vector-clock ;
vc:requires ngm:replication-protocol ;
vc:slug "consistency-model" ;
vc:sourceDomain "distributed-systems" ;
vc:supports ngm:state-machine-replication ;
vc:uses ngm:quorum ;
vc:uses ngm:vector-clock .
ngm:consistency-protocols a skos:Concept ;
rdfs:label "Consistency Protocols"@en .
ngm:consistent-hashing a owl:Class ;
rdfs:comment "Consistent hashing is a distribution technique that maps both data keys and storage nodes onto the same circular hash space, so that each key is assigned to the next node encountered clockwise on the ring. When a node joins or leaves, only the keys in its immediate neighbourhood are remapped rather than the entire key space, minimising data movement. Virtual nodes are commonly used to smooth load distribution across heterogeneous servers."@en ;
rdfs:label "Consistent Hashing"@en ;
rdfs:subClassOf ngm:distributed-hash-table ;
rdfs:subClassOf _:r5403 ;
vc:enables ngm:fault-tolerance ;
vc:enables ngm:scalability ;
vc:enables ngm:sharding ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:data-partitioning ;
vc:implements ngm:load-balancing ;
vc:isPartOf ngm:distributed-hash-table ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:distributed-systems ;
vc:relatedTo ngm:node ;
vc:relatedTo ngm:peer-to-peer-network ;
vc:requires ngm:hash-function ;
vc:slug "consistent-hashing" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:caching ;
vc:supports ngm:load-balancing ;
vc:uses ngm:data-partitioning ;
vc:uses ngm:hash-function .
ngm:consolidation a skos:Concept ;
rdfs:label "Consolidation"@en .
ngm:consolidation-pipeline a skos:Concept ;
rdfs:label "Consolidation Pipeline"@en .
ngm:consortium-blockchain a owl:Class ;
rdfs:comment "Consortium Blockchain is a permissioned distributed ledger architecture in which a pre-approved set of legally distinct organisations jointly operates the validator infrastructure, governs the protocol rules, and controls the read/write access matrix — occupying a deliberate middle position in th..."@en ;
rdfs:label "Consortium Blockchain"@en ;
rdfs:subClassOf ngm:distributed-ledger-technology ;
rdfs:subClassOf ngm:enterprise-blockchain ;
rdfs:subClassOf ngm:federated-system ;
rdfs:subClassOf ngm:multi-organisation-database ;
rdfs:subClassOf ngm:network-component ;
rdfs:subClassOf ngm:permissioned-network ;
rdfs:subClassOf _:r5404 ;
rdfs:subClassOf _:r5405 ;
rdfs:subClassOf _:r5406 ;
rdfs:subClassOf _:r5407 ;
rdfs:subClassOf _:r5408 ;
rdfs:subClassOf _:r5409 ;
rdfs:subClassOf _:r5410 ;
rdfs:subClassOf _:r5411 ;
rdfs:subClassOf _:r5412 ;
vc:bridgesTo ngm:federated-system ;
vc:contrastsWith ngm:bitcoin-proof-of-work-protocol ;
vc:contrastsWith ngm:ethereum-smart-contract-platform ;
vc:contrastsWith ngm:permissionless-blockchain ;
vc:contrastsWith ngm:private-blockchain ;
vc:contrastsWith ngm:public-blockchain ;
vc:contrastsWith ngm:swift-messaging ;
vc:contrastsWith ngm:traditional-edi ;
vc:dependsOn ngm:consortium-governance-framework ;
vc:dependsOn ngm:cryptographic-infrastructure ;
vc:dependsOn ngm:digital-signature ;
vc:dependsOn ngm:legal-agreement ;
vc:dependsOn ngm:merkle-tree ;
vc:dependsOn ngm:threshold-cryptography ;
vc:dependsOn ngm:x-509-certificate ;
vc:enables ngm:atomic-delivery-versus-payment ;
vc:enables ngm:regulatory-reporting-automation ;
vc:enables ngm:selective-disclosure ;
vc:enables ngm:supply-chain-provenance ;
vc:enables ngm:tokenised-deposit ;
vc:enables ngm:tokenised-real-world-assets ;
vc:enables ngm:trade-finance-digitisation ;
vc:enables ngm:wholesale-cbdc ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:certificate-authority ;
vc:hasPart ngm:chaincode-container ;
vc:hasPart ngm:channels-and-private-data-collections ;
vc:hasPart ngm:endorsement-policy ;
vc:hasPart ngm:membership-service-provider ;
vc:hasPart ngm:notary-service ;
vc:hasPart ngm:off-chain-data-store ;
vc:hasPart ngm:ordering-service ;
vc:hasPart ngm:validator-node ;
vc:implements ngm:crash-fault-tolerant-ordering ;
vc:implements ngm:ibft ;
vc:implements ngm:pbft ;
vc:implements ngm:proof-of-authority ;
vc:implements ngm:qbft ;
vc:implements ngm:raft-consensus ;
vc:implements ngm:smart-bft ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:blockchain-interoperability ;
vc:relatedTo ngm:cbdcs ;
vc:relatedTo ngm:distributed-ledger-technology ;
vc:relatedTo ngm:neural-network-text-tokenisation ;
vc:relatedTo ngm:self-sovereign-identity ;
vc:relatedTo ngm:smart-contract ;
vc:relatedTo ngm:supply-chain-management ;
vc:relatedTo ngm:trade-finance ;
vc:relatedTo ngm:verifiable-credentials ;
vc:requires ngm:byzantine-fault-tolerance ;
vc:requires ngm:cryptographic-infrastructure ;
vc:requires ngm:identity-management-system ;
vc:requires ngm:multi-party-governance ;
vc:requires ngm:network-membership-agreement ;
vc:requires ngm:smart-contract-platform ;
vc:slug "consortium-blockchain" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:enterprise-ethereum-alliance ;
vc:standardizedBy ngm:ethtrust-security-levels ;
vc:standardizedBy ngm:hyperledger-foundation ;
vc:standardizedBy ngm:interwork-alliance-token-taxonomy ;
vc:standardizedBy ngm:iso-22739 ;
vc:standardizedBy ngm:iso-23257 ;
vc:standardizedBy ngm:iso-24165 ;
vc:standardizedBy ngm:iso-tr-23455 ;
vc:standardizedBy ngm:lf-decentralized-trust ;
vc:supports ngm:citi-token-services ;
vc:supports ngm:ebsi ;
vc:supports ngm:hsbc-orion ;
vc:supports ngm:ibm-food-trust ;
vc:supports ngm:jpmorgan-onyx ;
vc:supports ngm:kinexys ;
vc:supports ngm:medi-ledger ;
vc:supports ngm:project-agora ;
vc:supports ngm:project-m-bridge ;
vc:supports ngm:project-rosalind ;
vc:uses ngm:azure-confidential-consortium-framework ;
vc:uses ngm:go-quorum ;
vc:uses ngm:hardware-security-module ;
vc:uses ngm:hyperledger-besu ;
vc:uses ngm:hyperledger-fabric ;
vc:uses ngm:hyperledger-iroha ;
vc:uses ngm:quorum ;
vc:uses ngm:r3-corda .
ngm:consortium-governance a owl:Class ;
rdfs:comment "Consortium governance is the model by which a defined group of organisations jointly operates and controls a permissioned blockchain or shared infrastructure. Membership, validator rights, and decision-making authority are restricted to vetted participants who agree to a governing charter. It balances the decentralisation benefits of distributed ledgers with the accountability and access control enterprises require."@en ;
rdfs:label "Consortium Governance"@en ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
skos:broader ngm:bc-governance-and-regulation ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:blockchain-as-a-service ;
vc:relatedTo ngm:enterprise-smart-contracts ;
vc:slug "consortium-governance" ;
vc:sourceDomain "blockchain" .
ngm:consortium-governance-framework a skos:Concept ;
rdfs:label "Consortium Governance Framework"@en .
ngm:conspiratorial-thinking-in-technology-communities a owl:Class ;
rdfs:comment "Conspiracies, in the context of technology communities, refers to the recurring pattern of conspiratorial thinking that attaches to emerging technologies such as cryptocurrency and AI. Often rooted in legitimate governance concerns, such thinking can escalate into disinformation ecosystems, creating tensions within technology policy, AI safety debates, and open-source governance."@en ;
rdfs:label "Conspiratorial Thinking in Technology Communities"@en ;
rdfs:subClassOf ngm:software-engineering ;
vc:bridgesTo ngm:california-ai-bill ;
vc:bridgesTo ngm:open-source-ai ;
vc:contrastsWith ngm:ai-governance ;
vc:contrastsWith ngm:safety-and-alignment ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:ai-governance-law-and-privacy ;
vc:relatedTo ngm:blockchain ;
vc:slug "conspiratorial-thinking-in-technology-communities" ;
vc:sourceDomain "infrastructure" .
ngm:constant-bandwidth-server a skos:Concept ;
rdfs:label "Constant Bandwidth Server"@en .
ngm:constant-bitrate-encoding a skos:Concept ;
rdfs:label "Constant Bitrate Encoding"@en .
ngm:constant-potts-model a skos:Concept ;
rdfs:label "Constant Potts Model"@en .
ngm:constant-product-amm a skos:Concept ;
rdfs:label "Constant Product Amm"@en .
ngm:constant-product-formula a owl:Class ;
rdfs:comment "The constant product formula is the pricing rule used by many automated market makers in which the product of the two pooled token reserves is held constant during trades."@en ;
rdfs:label "Constant Product Formula"@en ;
rdfs:subClassOf ngm:automated-market-maker ;
rdfs:subClassOf _:r5413 ;
vc:bridgesTo ngm:uniswap ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:liquidity-pool ;
vc:slug "constant-product-formula" ;
vc:sourceDomain "blockchain" .
ngm:constant-time-algorithm a skos:Concept ;
rdfs:label "Constant Time Algorithm"@en .
ngm:constant-time-programming a skos:Concept ;
rdfs:label "Constant Time Programming"@en .
ngm:constantthroughput a skos:Concept ;
rdfs:label "Constantthroughput"@en .
ngm:constitutional-ai a owl:Class ;
rdfs:comment "An alignment training method, introduced by Anthropic in 2022, in which a language model is steered by an explicit written set of principles (a constitution) rather than solely by human preference labels: the model critiques and revises its own outputs against the principles during supervised learning, then a preference model trained on AI-generated comparisons (RLAIF) provides the reinforcement signal, yielding harmlessness that is transparent, auditable, and scalable with far less human labelling."@en ;
rdfs:label "Constitutional AI"@en ;
rdfs:subClassOf ngm:ai-alignment ;
vc:contrastsWith ngm:rlhf ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:isPartOf ngm:ai-safety-research ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:corrigibility ;
vc:relatedTo ngm:instruction-following ;
vc:relatedTo ngm:red-teaming ;
vc:slug "constitutional-ai" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:large-language-model ;
vc:uses ngm:reinforcement-learning-from-human-feedback .
ngm:constitutional-ai-training-methodology a owl:Class ;
rdfs:comment "A method for training AI assistants to be harmless through self-improvement, using a set of principles or \"constitution\" to guide behaviour without human labels for harmful outputs. Constitutional AI combines supervised learning for self-critiques and revisions with Reinforcement Learning from AI Feedback (RLAIF), producing models that are helpful, harmless, and honest at scale."@en ;
rdfs:label "Constitutional AI Training Methodology"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf _:r5414 ;
rdfs:subClassOf _:r5415 ;
rdfs:subClassOf _:r5416 ;
rdfs:subClassOf _:r5417 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:ai-regulation ;
vc:bridgesTo ngm:computer-vision ;
vc:contrastsWith ngm:reinforcement-learning-from-human-feedback ;
vc:dependsOn ngm:instruction-following ;
vc:dependsOn ngm:proximal-policy-optimisation ;
vc:enables ngm:ai-alignment ;
vc:enables ngm:ai-safety ;
vc:enables ngm:harmlessness ;
vc:enables ngm:scalable-oversight ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:supervised-fine-tuning ;
vc:implements ngm:value-alignment ;
vc:isPartOf ngm:ai-alignment ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:safety-evaluation ;
vc:requires ngm:chain-of-thought-reasoning ;
vc:requires ngm:large-language-models ;
vc:requires ngm:reinforcement-learning ;
vc:slug "constitutional-ai-training-methodology" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:ai-ethics ;
vc:supports ngm:ai-governance ;
vc:supports ngm:responsible-ai ;
vc:uses ngm:ai-feedback ;
vc:uses ngm:large-language-models ;
vc:uses ngm:red-teaming .
ngm:constitutional-ai-training-methodology-language-model-family a owl:Class ;
rdfs:comment "Anthropic Claude is a family of large language models developed by Anthropic PBC, designed around Constitutional AI principles that prioritise safety, helpfulness, and honesty. The model series spans Claude Instant, Claude 2, Claude 3 (Haiku, Sonnet, Opus), and Claude 3.5, with each generation advancing reasoning, coding, and multilingual capabilities. Claude is distinguished by its long context windows (up to 200k tokens in Claude 3) and its training methodology that emphasises harmlessness through RLHF and Constitutional AI feedback loops."@en ;
rdfs:label "Constitutional AI Language Model Family"@en ;
rdfs:subClassOf ngm:proprietary-large-language-models ;
vc:contrastsWith ngm:gemini-multimodal-language-model ;
vc:contrastsWith ngm:instruction-following-conversational-ai-system ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:model-training ;
vc:enables ngm:ai-alignment ;
vc:enables ngm:conversational-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:constitutional-ai-training-methodology ;
vc:implements ngm:instruction-tuning ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:anthropic ;
vc:relatedTo ngm:constitutional-ai-training-methodology ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:rlhf ;
vc:slug "constitutional-ai-language-model-family" ;
vc:sourceDomain "ai" ;
vc:supports ngm:ai-safety ;
vc:supports ngm:responsible-ai .
ngm:constitutional-classifiers a skos:Concept ;
rdfs:label "Constitutional Classifiers"@en .
ngm:constitutional-law a skos:Concept ;
rdfs:label "Constitutional Law"@en .
ngm:constitutional-principle a owl:Class ;
rdfs:comment "A Constitutional Principle in AI alignment is a natural-language rule or norm—derived from human rights frameworks, professional codes, or organisational policies—that is embedded into an AI system's training or inference process to constrain its behaviour across diverse contexts. Constitutional AI, introduced by Anthropic, uses a curated list of such principles as a self-critique scaffold during reinforcement learning from AI feedback (RLAIF), enabling large language models to evaluate and revise their own outputs against explicit normative standards without requiring a human rater for every example. Constitutional Principles serve as the value-bearing component of this approach, operationalising abstract ethical commitments into verifiable behavioural constraints."@en ;
rdfs:label "Constitutional Principle"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf _:r5418 ;
rdfs:subClassOf _:r5419 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:enables ngm:ai-alignment ;
vc:enables ngm:ai-safety ;
vc:enables ngm:human-agency-and-oversight ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:constitutional-ai-training-methodology ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:accountability ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:ai-governance-principle ;
vc:relatedTo ngm:ai-regulation ;
vc:relatedTo ngm:fairness ;
vc:requires ngm:reinforcement-learning ;
vc:requires ngm:value-alignment ;
vc:slug "constitutional-principle" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:ai-governance-framework .
ngm:constitutional-rights a skos:Concept ;
rdfs:label "Constitutional Rights"@en .
ngm:constitutionalai a skos:Concept ;
rdfs:label "Constitutionalai"@en .
ngm:constrained-decoding a owl:Class ;
rdfs:comment "A family of inference-time techniques that restrict the token choices of a language model during generation so that output is guaranteed to satisfy formal constraints — a JSON schema, a context-free grammar, a regular expression, or required lexical content. At each decoding step the sampler masks tokens that would violate the constraint, typically by intersecting the model's next-token distribution with the valid transitions of a compiled automaton, yielding syntactically valid structured output without retraining the model."@en ;
rdfs:label "Constrained Decoding"@en ;
rdfs:subClassOf ngm:text-generation ;
vc:enables ngm:structured-output ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:beam-search ;
vc:relatedTo ngm:large-language-model ;
vc:slug "constrained-decoding" ;
vc:sourceDomain "machine-learning" ;
vc:uses ngm:finite-state-machine ;
vc:uses ngm:sampling .
ngm:constrained-optimisation a skos:Concept ;
rdfs:label "Constrained Optimisation"@en .
ngm:constraineddecoding a skos:Concept ;
rdfs:label "Constraineddecoding"@en .
ngm:constraint a owl:Class ;
rdfs:comment "A Constraint is a condition, restriction, or rule that limits the set of permissible states, actions, or solutions within a computational, logical, or physical system. Constraints formalise requirements such as resource bounds, logical invariants, safety properties, and optimality criteria, and are manipulated by constraint-satisfaction and optimisation algorithms to find feasible or optimal solutions. They appear across AI planning, machine learning regularisation, smart-contract execution, and formal verification."@en ;
rdfs:label "Constraint"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:formal-method ;
rdfs:subClassOf ngm:knowledge-representation ;
rdfs:subClassOf _:r5448 ;
rdfs:subClassOf _:r5449 ;
rdfs:subClassOf _:r5450 ;
rdfs:subClassOf _:r5451 ;
rdfs:subClassOf _:r5452 ;
rdfs:subClassOf _:r5453 ;
rdfs:subClassOf _:r5454 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:smart-contract ;
vc:contrastsWith ngm:gradient-descent ;
vc:contrastsWith ngm:heuristic-methods ;
vc:dependsOn ngm:inference ;
vc:dependsOn ngm:satisfiability ;
vc:dependsOn ngm:search-algorithm ;
vc:dependsOn ngm:smt-solver ;
vc:enables ngm:explainability ;
vc:enables ngm:fairness ;
vc:enables ngm:formal-verification ;
vc:enables ngm:optimisation ;
vc:enables ngm:planning ;
vc:enables ngm:planning-and-scheduling ;
vc:enables ngm:reasoning ;
vc:enables ngm:safety ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:arc-consistency ;
vc:hasPart ngm:backtracking-search ;
vc:hasPart ngm:constraint-programming ;
vc:hasPart ngm:constraint-satisfaction-problem ;
vc:hasPart ngm:regularisation ;
vc:implements ngm:answer-set-programming ;
vc:implements ngm:combinatorial-optimisation ;
vc:implements ngm:description-logic ;
vc:implements ngm:integer-programming ;
vc:implements ngm:linear-programming ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:arc-consistency ;
vc:relatedTo ngm:loss-function ;
vc:relatedTo ngm:markov-decision-process ;
vc:relatedTo ngm:model-checking ;
vc:relatedTo ngm:neural-network ;
vc:relatedTo ngm:parameter ;
vc:relatedTo ngm:property ;
vc:relatedTo ngm:reinforcement-learning ;
vc:relatedTo ngm:satisfiability ;
vc:relatedTo ngm:system ;
vc:relatedTo ngm:theorem-proving ;
vc:requires ngm:algorithm ;
vc:requires ngm:model ;
vc:requires ngm:objective ;
vc:requires ngm:system ;
vc:slug "constraint" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:deep-learning ;
vc:supports ngm:explainability ;
vc:supports ngm:fairness ;
vc:supports ngm:knowledge-representation ;
vc:supports ngm:machine-learning-discipline ;
vc:supports ngm:ontology ;
vc:uses ngm:algorithm ;
vc:uses ngm:backtracking-search ;
vc:uses ngm:gradient-descent ;
vc:uses ngm:inference ;
vc:uses ngm:search-algorithm ;
vc:uses ngm:smt-solver .
ngm:constraint-based-design a owl:Class ;
rdfs:comment "Constraint based design is an engineering and AI methodology in which the valid solution space is explicitly defined by a set of constraints — physical laws, geometric relationships, functional requirements, regulatory bounds, manufacturing limits, or performance thresholds — that any acceptable design must simultaneously satisfy. Constraint solvers, optimisation algorithms, and AI planners traverse or prune this feasible region to discover configurations meeting all constraints, optionally optimising an objective within the feasible space. The method is foundational to parametric CAD, generative design tools, topology optimisation, robotics motion planning, and cyber-physical system validation, and is increasingly integrated with machine learning to learn constraint representations from data and guide search with neural heuristics."@en ;
rdfs:label "Constraint Based Design"@en ;
rdfs:subClassOf ngm:ai-system-component ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:constraint-satisfaction ;
rdfs:subClassOf ngm:symbolic-ai ;
rdfs:subClassOf _:r5420 ;
rdfs:subClassOf _:r5421 ;
rdfs:subClassOf _:r5422 ;
rdfs:subClassOf _:r5423 ;
rdfs:subClassOf _:r5424 ;
rdfs:subClassOf _:r5425 ;
rdfs:subClassOf _:r5426 ;
rdfs:subClassOf _:r5427 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:ai-system-component ;
vc:bridgesTo ngm:constraint-satisfaction ;
vc:bridgesTo ngm:robotics ;
vc:bridgesTo ngm:simulation-engine ;
vc:contrastsWith ngm:generative-ai ;
vc:contrastsWith ngm:generative-design-tool ;
vc:contrastsWith ngm:reinforcement-learning ;
vc:contrastsWith ngm:rule-based-systems ;
vc:dependsOn ngm:computer-aided-design ;
vc:dependsOn ngm:constraint-satisfaction ;
vc:dependsOn ngm:parametric-design-methodology-modeling ;
vc:dependsOn ngm:structural-analysis ;
vc:enables ngm:additive-manufacturing ;
vc:enables ngm:co-design ;
vc:enables ngm:deep-learning ;
vc:enables ngm:formal-verification ;
vc:enables ngm:generative-design-tool ;
vc:enables ngm:graph-neural-network ;
vc:enables ngm:motion-planning ;
vc:enables ngm:multi-objective-optimization ;
vc:enables ngm:participatory-design ;
vc:enables ngm:product-design ;
vc:enables ngm:topology-optimization ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:constraint-propagation ;
vc:hasPart ngm:constraint-solver ;
vc:hasPart ngm:design-space-exploration ;
vc:hasPart ngm:feasibility ;
vc:hasPart ngm:functional-requirements ;
vc:hasPart ngm:geometric-constraint ;
vc:hasPart ngm:optimisation-algorithm ;
vc:implements ngm:model-based-systems-engineering ;
vc:implements ngm:neuro-symbolic-ai ;
vc:implements ngm:symbolic-ai ;
vc:implements ngm:systems-engineering ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:answer-set-programming ;
vc:relatedTo ngm:automated-planning ;
vc:relatedTo ngm:autonomous-robot ;
vc:relatedTo ngm:backtracking-search ;
vc:relatedTo ngm:co-design ;
vc:relatedTo ngm:combinatorial-optimisation ;
vc:relatedTo ngm:concurrent-engineering ;
vc:relatedTo ngm:constraint-logic-programming ;
vc:relatedTo ngm:cyber-physical-systems ;
vc:relatedTo ngm:digital-twin ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:neuro-symbolic-ai ;
vc:relatedTo ngm:operations-research ;
vc:relatedTo ngm:topology-optimisation ;
vc:relatedTo ngm:variable-ordering-heuristic ;
vc:requires ngm:constraint-satisfaction ;
vc:requires ngm:finite-element-analysis ;
vc:requires ngm:knowledge-representation ;
vc:requires ngm:optimisation-algorithm ;
vc:requires ngm:simulation ;
vc:slug "constraint-based-design" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:minizinc ;
vc:standardizedBy ngm:sysml-v2 ;
vc:supports ngm:additive-manufacturing ;
vc:supports ngm:configuration-management ;
vc:supports ngm:cyber-physical-systems ;
vc:supports ngm:digital-twin ;
vc:supports ngm:requirements-engineering ;
vc:supports ngm:safety-engineering ;
vc:uses ngm:evolutionary-algorithm ;
vc:uses ngm:finite-element-analysis ;
vc:uses ngm:gradient-descent ;
vc:uses ngm:graph-neural-network ;
vc:uses ngm:integer-programming ;
vc:uses ngm:linear-programming ;
vc:uses ngm:neural-network ;
vc:uses ngm:parametric-design-methodology-modeling ;
vc:uses ngm:reinforcement-learning ;
vc:uses ngm:sat-solver .
ngm:constraint-logic-programming a skos:Concept ;
rdfs:label "Constraint Logic Programming"@en .
ngm:constraint-programming a skos:Concept ;
rdfs:label "Constraint Programming"@en .
ngm:constraint-propagation a owl:Class ;
rdfs:comment "An inference technique in constraint satisfaction that repeatedly applies local consistency rules to shrink the domains of variables, eliminating values that cannot participate in any solution before or during search. By propagating the logical consequences of each constraint through the constraint network, it prunes the search space dramatically, often exposes infeasibility early without any backtracking, and turns otherwise intractable combinatorial problems into practically solvable ones."@en ;
rdfs:label "Constraint Propagation"@en ;
rdfs:subClassOf ngm:constraint-satisfaction ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:constraint-solver ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:backtracking-search ;
vc:relatedTo ngm:constraint ;
vc:slug "constraint-propagation" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:arc-consistency .
ngm:constraint-satisfaction a owl:Class ;
rdfs:comment "Constraint Satisfaction is a paradigm in artificial intelligence and combinatorial mathematics in which a problem is represented as a set of variables, each with a domain of possible values, and a set of constraints that restrict the allowable combinations of those values. The goal is to find an assignment of values to all variables such that every constraint is simultaneously satisfied, or to determine that no such assignment exists. Solution methods combine systematic backtracking search with constraint propagation techniques — notably arc consistency and path consistency — that prune infeasible values early, dramatically reducing the search space. Constraint satisfaction underpins scheduling, configuration, planning, and combinatorial optimisation across virtually every engineering domain."@en ;
rdfs:label "Constraint Satisfaction"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:combinatorial-optimisation ;
rdfs:subClassOf ngm:symbolic-ai ;
rdfs:subClassOf _:r5428 ;
rdfs:subClassOf _:r5429 ;
rdfs:subClassOf _:r5430 ;
rdfs:subClassOf _:r5431 ;
rdfs:subClassOf _:r5432 ;
rdfs:subClassOf _:r5433 ;
rdfs:subClassOf _:r5434 ;
rdfs:subClassOf _:r5435 ;
rdfs:subClassOf _:r5436 ;
rdfs:subClassOf _:r5437 ;
rdfs:subClassOf _:r5438 ;
rdfs:subClassOf _:r5439 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:automated-planning ;
vc:bridgesTo ngm:constraint-based-design ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:motion-planning ;
vc:bridgesTo ngm:network-configuration ;
vc:bridgesTo ngm:neuro-symbolic-ai ;
vc:bridgesTo ngm:robotic-task-planning ;
vc:bridgesTo ngm:supply-chain-optimisation ;
vc:contrastsWith ngm:linear-programming ;
vc:contrastsWith ngm:probabilistic-inference ;
vc:contrastsWith ngm:rule-based-systems ;
vc:contrastsWith ngm:satisfiability ;
vc:dependsOn ngm:combinatorial-optimisation ;
vc:dependsOn ngm:graph-theory ;
vc:dependsOn ngm:propositional-logic ;
vc:dependsOn ngm:satisfiability ;
vc:enables ngm:automated-planning ;
vc:enables ngm:configuration-management ;
vc:enables ngm:constraint-based-design ;
vc:enables ngm:formal-verification ;
vc:enables ngm:motion-planning ;
vc:enables ngm:network-configuration ;
vc:enables ngm:neuro-symbolic-ai ;
vc:enables ngm:planning-and-scheduling ;
vc:enables ngm:resource-allocation ;
vc:enables ngm:supply-chain-optimisation ;
vc:enables ngm:systems-engineering ;
vc:enables ngm:task-planning ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:arc-consistency ;
vc:hasPart ngm:backtracking-search ;
vc:hasPart ngm:branch-and-bound ;
vc:hasPart ngm:constraint-propagation ;
vc:hasPart ngm:constraint-solver ;
vc:hasPart ngm:graph-colouring ;
vc:hasPart ngm:inference-engine ;
vc:hasPart ngm:integer-programming ;
vc:hasPart ngm:local-search ;
vc:hasPart ngm:satisfiability ;
vc:hasPart ngm:variable-ordering-heuristic ;
vc:implements ngm:knowledge-representation ;
vc:implements ngm:logic-programming ;
vc:implements ngm:symbolic-ai ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:answer-set-programming ;
vc:relatedTo ngm:constraint-logic-programming ;
vc:relatedTo ngm:dynamic-programming ;
vc:relatedTo ngm:formal-verification ;
vc:relatedTo ngm:genetic-algorithm ;
vc:relatedTo ngm:graph-colouring ;
vc:relatedTo ngm:integer-programming ;
vc:relatedTo ngm:logic-programming ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:multi-objective-optimisation ;
vc:relatedTo ngm:operations-research ;
vc:relatedTo ngm:optimisation-algorithm ;
vc:relatedTo ngm:quantum-computation-paradigm ;
vc:relatedTo ngm:simulation ;
vc:relatedTo ngm:treewidth ;
vc:requires ngm:domain-representation ;
vc:requires ngm:inference-engine ;
vc:requires ngm:knowledge-representation ;
vc:requires ngm:search-algorithm ;
vc:slug "constraint-satisfaction" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:minizinc ;
vc:standardizedBy ngm:xcsp3 ;
vc:supports ngm:cyber-physical-systems ;
vc:supports ngm:decision-making ;
vc:supports ngm:digital-twin ;
vc:supports ngm:knowledge-representation ;
vc:supports ngm:model-based-systems-engineering ;
vc:supports ngm:neuro-symbolic-ai ;
vc:uses ngm:branch-and-bound ;
vc:uses ngm:evolutionary-algorithm ;
vc:uses ngm:genetic-algorithm ;
vc:uses ngm:heuristic-methods ;
vc:uses ngm:inference-engine ;
vc:uses ngm:local-search ;
vc:uses ngm:logic-programming ;
vc:uses ngm:reinforcement-learning .
ngm:constraint-satisfaction-problem a skos:Concept ;
rdfs:label "Constraint Satisfaction Problem"@en .
ngm:constraint-set a skos:Concept ;
rdfs:label "Constraint Set"@en .
ngm:constraint-solver a owl:Class ;
rdfs:comment "A constraint solver is a computational engine that finds assignments of values to variables such that all specified constraints — mathematical relationships, logical predicates, or physical laws — are simultaneously satisfied, drawing on techniques from constraint programming, SAT/SMT solving, linear programming, and numerical methods. Solvers operate by propagating constraint implications to prune the search space, applying backtracking or branch-and-bound search, and invoking domain-specific inference procedures that make the infeasibility of partial assignments detectable early. They are applied across planning and scheduling, combinatorial optimisation, formal verification, physics simulation, computer-aided design, and robotic motion planning."@en ;
rdfs:label "Constraint Solver"@en ;
rdfs:subClassOf ngm:combinatorial-optimisation ;
rdfs:subClassOf ngm:inference-engine ;
rdfs:subClassOf ngm:optimisation-algorithm ;
rdfs:subClassOf ngm:symbolic-ai ;
rdfs:subClassOf _:r5440 ;
rdfs:subClassOf _:r5441 ;
rdfs:subClassOf _:r5442 ;
rdfs:subClassOf _:r5443 ;
rdfs:subClassOf _:r5444 ;
rdfs:subClassOf _:r5445 ;
rdfs:subClassOf _:r5446 ;
rdfs:subClassOf _:r5447 ;
vc:bridgesTo ngm:operations-research ;
vc:bridgesTo ngm:robotics ;
vc:bridgesTo ngm:spatial-computing ;
vc:contrastsWith ngm:heuristic-search ;
vc:contrastsWith ngm:local-search ;
vc:contrastsWith ngm:neural-network ;
vc:dependsOn ngm:arc-consistency ;
vc:dependsOn ngm:constraint-propagation ;
vc:dependsOn ngm:graph-theory ;
vc:dependsOn ngm:propositional-logic ;
vc:enables ngm:automated-planning ;
vc:enables ngm:combinatorial-optimisation ;
vc:enables ngm:formal-verification ;
vc:enables ngm:motion-planning ;
vc:enables ngm:physics-simulation ;
vc:enables ngm:planning-and-scheduling ;
vc:enables ngm:supply-chain-optimisation ;
vc:enables ngm:trajectory-planning ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:arc-consistency ;
vc:hasPart ngm:backtracking-search ;
vc:hasPart ngm:branch-and-bound ;
vc:hasPart ngm:constraint-propagation ;
vc:hasPart ngm:local-search ;
vc:hasPart ngm:variable-ordering-heuristic ;
vc:implements ngm:constraint-satisfaction ;
vc:implements ngm:symbolic-ai ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:constraint-based-design ;
vc:relatedTo ngm:gpu-computing ;
vc:relatedTo ngm:graph-neural-network ;
vc:relatedTo ngm:mixed-integer-programming ;
vc:relatedTo ngm:neuro-symbolic-ai ;
vc:relatedTo ngm:operations-research ;
vc:relatedTo ngm:quantum-computation-paradigm ;
vc:relatedTo ngm:reinforcement-learning ;
vc:relatedTo ngm:trajectory-planning ;
vc:requires ngm:constraint-satisfaction ;
vc:requires ngm:propositional-logic ;
vc:requires ngm:search-algorithm ;
vc:slug "constraint-solver" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:minizinc ;
vc:standardizedBy ngm:xcsp3 ;
vc:supports ngm:computer-aided-design ;
vc:supports ngm:constraint-based-design ;
vc:supports ngm:decision-making ;
vc:supports ngm:knowledge-representation ;
vc:supports ngm:physics-simulation ;
vc:supports ngm:robotics ;
vc:uses ngm:heuristic-search ;
vc:uses ngm:interval-arithmetic ;
vc:uses ngm:linear-programming ;
vc:uses ngm:local-search ;
vc:uses ngm:logic-programming ;
vc:uses ngm:satisfiability ;
vc:uses ngm:smt-solving .
ngm:constraint-specification a owl:Class ;
rdfs:comment "A constraint specification is a formal statement of the limits and conditions a control system or plan must satisfy, such as joint limits, actuator bounds, obstacle avoidance, and safety envelopes. It is supplied to control and optimisation algorithms so that generated commands remain feasible and safe. Precise constraint specification is essential for model-based and optimisation-based control design."@en ;
rdfs:label "Constraint Specification"@en ;
rdfs:subClassOf ngm:control-theory ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:control-algorithm ;
vc:relatedTo ngm:model-based-control ;
vc:slug "constraint-specification" ;
vc:sourceDomain "robotics" .
ngm:constraint-system a skos:Concept ;
rdfs:label "Constraint System"@en .
ngm:construct-validity a skos:Concept ;
rdfs:label "Construct Validity"@en .
ngm:construction-coordination a skos:Concept ;
rdfs:label "Construction Coordination"@en .
ngm:construction-data a skos:Concept ;
rdfs:label "Construction Data"@en .
ngm:construction-digital-twin a owl:Class ;
rdfs:comment "An integrated 3D model of built assets synchronized with real-time construction, operational, and maintenance data, enabling lifecycle management from design through decommissioning."@en ;
rdfs:label "Construction Digital Twin"@en ;
rdfs:subClassOf ngm:digital-twin ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf _:r5455 ;
rdfs:subClassOf _:r5456 ;
rdfs:subClassOf _:r5457 ;
rdfs:subClassOf _:r5458 ;
rdfs:subClassOf _:r5459 ;
rdfs:subClassOf _:r5460 ;
rdfs:subClassOf _:r5461 ;
rdfs:subClassOf _:r5462 ;
rdfs:subClassOf _:r5463 ;
rdfs:subClassOf _:r5464 ;
skos:broader ngm:sc-platform-and-environment ;
vc:bridgesTo ngm:autonomous-robot ;
vc:dependsOn ngm:building-information-modelling ;
vc:dependsOn ngm:construction-data ;
vc:dependsOn ngm:facility-management-system ;
vc:enables ngm:ai-energy-optimisation ;
vc:enables ngm:energy-optimization ;
vc:enables ngm:lifecycle-management ;
vc:enables ngm:predictive-maintenance ;
vc:enables ngm:space-planning ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:asset-database ;
vc:hasPart ngm:bim-virtual-model ;
vc:hasPart ngm:energy-management ;
vc:hasPart ngm:io-t-sensor-network ;
vc:hasPart ngm:maintenance-schedule ;
vc:isPartOf ngm:digital-twin ;
vc:isPartOf ngm:smart-building-ecosystem ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:bim-software ;
vc:requires ngm:cloud-platform ;
vc:requires ngm:io-t-infrastructure ;
vc:requires ngm:real-time-synchronisation ;
vc:slug "construction-digital-twin" ;
vc:sourceDomain "spatial-computing" .
ngm:construction-optimization a skos:Concept ;
rdfs:label "Construction Optimization"@en .
ngm:construction-robotics a skos:Concept ;
rdfs:label "Construction Robotics"@en .
ngm:constructivism a skos:Concept ;
rdfs:label "Constructivism"@en .
ngm:constructor a skos:Concept ;
rdfs:label "Constructor"@en .
ngm:consul a skos:Concept ;
rdfs:label "Consul"@en .
ngm:consumer-ai a skos:Concept ;
rdfs:label "Consumer AI"@en .
ngm:consumer-ai-adoption a owl:Class ;
rdfs:comment "The process and metrics by which individual users integrate artificial intelligence tools into their daily workflows, driving demand for consumer-facing AI products and services."@en ;
rdfs:label "Consumer AI Adoption"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-market-dynamics ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:generative-ai ;
vc:slug "consumer-ai-adoption" ;
vc:sourceDomain "economics" .
ngm:consumer-ai-market a owl:Class ;
rdfs:comment "The commercial sector focused on delivering artificial intelligence products and services directly to individual end-users rather than enterprise clients."@en ;
rdfs:label "Consumer AI Market"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
skos:broader ngm:artificial-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:generative-ai ;
vc:relatedTo ngm:software-development ;
vc:slug "consumer-ai-market" ;
vc:sourceDomain "economics" .
ngm:consumer-group a skos:Concept ;
rdfs:label "Consumer Group"@en .
ngm:consumer-iot a skos:Concept ;
rdfs:label "Consumer IoT"@en .
ngm:consumer-messaging-apps a skos:Concept ;
rdfs:label "Consumer Messaging Apps"@en .
ngm:consumer-price-index a owl:Class ;
rdfs:comment "The Consumer Price Index (CPI) is a statistical measure that tracks the average change over time in the prices paid by households for a representative basket of consumer goods and services. It is the principal indicator used to quantify inflation, adjust wages and benefits, and inform monetary policy. The index is computed by weighting price observations according to typical household expenditure patterns and rebasing them against a reference period."@en ;
rdfs:label "Consumer Price Index"@en ;
rdfs:subClassOf ngm:macroeconomics ;
rdfs:subClassOf _:r5465 ;
vc:bridgesTo ngm:inflation-targeting ;
vc:bridgesTo ngm:price-stability ;
vc:contrastsWith ngm:economic-growth ;
vc:enables ngm:central-bank ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:inflation-targeting ;
vc:isPartOf ngm:macroeconomics ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:central-bank ;
vc:relatedTo ngm:economic-growth ;
vc:relatedTo ngm:economics ;
vc:relatedTo ngm:inflation ;
vc:requires ngm:statistics ;
vc:slug "consumer-price-index" ;
vc:sourceDomain "finance" ;
vc:supports ngm:fiscal-policy ;
vc:supports ngm:monetary-policy ;
vc:uses ngm:price-stability ;
vc:uses ngm:statistics .
ngm:consumer-privacy-in-ai a skos:Concept ;
rdfs:label "Consumer Privacy In AI"@en .
ngm:consumer-protection a owl:Class ;
rdfs:comment "Body of law, regulation, and enforcement mechanisms protecting individuals from unfair, deceptive, or abusive commercial practices — spanning statutory rights, enforcement agencies, complaint and redress processes, and product liability standards — now substantially reshaped by digital markets, A..."@en ;
rdfs:label "Consumer Protection"@en ;
rdfs:subClassOf ngm:ai-governance ;
rdfs:subClassOf ngm:competition-law ;
rdfs:subClassOf ngm:digital-regulation ;
rdfs:subClassOf ngm:infra-legal-and-regulatory ;
rdfs:subClassOf ngm:market-regulation ;
rdfs:subClassOf ngm:platform-governance ;
rdfs:subClassOf ngm:product-liability ;
rdfs:subClassOf ngm:regulation ;
rdfs:subClassOf _:r5466 ;
rdfs:subClassOf _:r5467 ;
rdfs:subClassOf _:r5468 ;
rdfs:subClassOf _:r5469 ;
rdfs:subClassOf _:r5470 ;
rdfs:subClassOf _:r5471 ;
rdfs:subClassOf _:r5472 ;
rdfs:subClassOf _:r5473 ;
rdfs:subClassOf _:r5474 ;
rdfs:subClassOf _:r5475 ;
rdfs:subClassOf _:r5476 ;
rdfs:subClassOf _:r5477 ;
rdfs:subClassOf _:r5478 ;
skos:broader ngm:infra-legal-and-regulatory ;
vc:contrastsWith ngm:co-regulation ;
vc:contrastsWith ngm:industry-self-regulation ;
vc:contrastsWith ngm:platform-terms-of-service ;
vc:contrastsWith ngm:sandbox-approaches ;
vc:contrastsWith ngm:voluntary-codes-of-conduct ;
vc:dependsOn ngm:ai-governance ;
vc:dependsOn ngm:behavioural-economics ;
vc:dependsOn ngm:competition-law ;
vc:dependsOn ngm:contract-law ;
vc:dependsOn ngm:data-protection ;
vc:dependsOn ngm:economics ;
vc:dependsOn ngm:product-liability-law ;
vc:enables ngm:ai-product-safety ;
vc:enables ngm:fair-algorithmic-pricing ;
vc:enables ngm:informed-purchasing-decisions ;
vc:enables ngm:market-fairness ;
vc:enables ngm:redress-procedure ;
vc:enables ngm:synthetic-content-accountability ;
vc:enables ngm:trust-in-digital-platforms ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:adr-schemes ;
vc:hasPart ngm:algorithmic-accountability ;
vc:hasPart ngm:collective-redress ;
vc:hasPart ngm:complaint-infrastructure ;
vc:hasPart ngm:dark-pattern-prohibition ;
vc:hasPart ngm:disclosure-requirements ;
vc:hasPart ngm:enforcement-mechanism ;
vc:hasPart ngm:redress-procedure ;
vc:hasPart ngm:safety-standard ;
vc:hasPart ngm:statutory-rights ;
vc:implements ngm:ai-act-product-safety ;
vc:implements ngm:cma-strategic-market-status ;
vc:implements ngm:digital-markets-competition-and-consumers-act-2024 ;
vc:implements ngm:digital-services-act ;
vc:implements ngm:eu-consumer-rights-directive ;
vc:implements ngm:fca-consumer-duty ;
vc:implements ngm:ftc-unfair-and-deceptive-practices ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:ai-adoption ;
vc:relatedTo ngm:ai-liability ;
vc:relatedTo ngm:ai-risks ;
vc:relatedTo ngm:algorithmic-bias-and-variance ;
vc:relatedTo ngm:aml-kyc-compliance ;
vc:relatedTo ngm:california-ai-bill ;
vc:relatedTo ngm:competition-in-ai ;
vc:relatedTo ngm:data-protection ;
vc:relatedTo ngm:deepfakes-and-fraudulent-content ;
vc:relatedTo ngm:eu-ai-act-regulatory-instrument ;
vc:requires ngm:algorithmic-transparency ;
vc:requires ngm:complaint-infrastructure ;
vc:requires ngm:cross-border-cooperation ;
vc:requires ngm:evidence-standards ;
vc:requires ngm:judicial-oversight ;
vc:requires ngm:regulatory-authority ;
vc:requires ngm:technical-audit-capability ;
vc:slug "consumer-protection" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:asa ;
vc:standardizedBy ngm:cma ;
vc:standardizedBy ngm:eu-consumer-protection-cooperation-network ;
vc:standardizedBy ngm:financial-conduct-authority ;
vc:standardizedBy ngm:ftc ;
vc:standardizedBy ngm:ico ;
vc:standardizedBy ngm:ofcom ;
vc:standardizedBy ngm:opss ;
vc:standardizedBy ngm:trading-standards ;
vc:supports ngm:algorithmic-transparency ;
vc:supports ngm:consumer-trust ;
vc:supports ngm:digital-inclusion ;
vc:supports ngm:fair-trading ;
vc:supports ngm:informed-consent ;
vc:supports ngm:market-efficiency ;
vc:supports ngm:vulnerable-consumer-protection ;
vc:uses ngm:algorithmic-auditing ;
vc:uses ngm:collective-proceedings ;
vc:uses ngm:complaint-analytics ;
vc:uses ngm:dark-pattern-detection ;
vc:uses ngm:enforcement-action ;
vc:uses ngm:market-investigations ;
vc:uses ngm:synthetic-content-detection .
ngm:consumer-protection-act-1987 a skos:Concept ;
rdfs:label "Consumer Protection Act 1987"@en .
ngm:consumer-trust a owl:Class ;
rdfs:comment "Consumer trust is the confidence buyers place in a brand, product, or supply chain to behave reliably, safely, and ethically. It is built through verifiable provenance, transparent practices, consistent quality, and accountable handling of grievances. In supply-chain contexts it is increasingly underpinned by traceability data and ethical-sourcing attestations."@en ;
rdfs:label "Consumer Trust"@en ;
rdfs:subClassOf ngm:governance ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:consumer-protection ;
vc:relatedTo ngm:ethical-sourcing ;
vc:slug "consumer-trust" ;
vc:sourceDomain "supply-chain" .
ngm:contact-based-assembly a skos:Concept ;
rdfs:label "Contact Based Assembly"@en .
ngm:contact-centre-ai a skos:Concept ;
rdfs:label "Contact Centre AI"@en .
ngm:contact-centre-as-a-service a owl:Class ;
rdfs:comment "Contact Centre as a Service (CCaaS) is a cloud-delivered model that provides the software for managing inbound and outbound customer interactions across voice, chat, email, and messaging channels. It removes the need for on-premises telephony infrastructure by offering routing, queuing, agent tooling, and analytics on a subscription basis. Modern CCaaS platforms increasingly embed AI for self-service, transcription, and agent assistance."@en ;
rdfs:label "Contact Centre as a Service"@en ;
rdfs:subClassOf ngm:infra-computing-and-cloud ;
skos:broader ngm:infra-computing-and-cloud ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:call-centres ;
vc:slug "contact-centre-as-a-service" ;
vc:sourceDomain "infrastructure" .
ngm:contact-detection a skos:Concept ;
rdfs:label "Contact Detection"@en .
ngm:contact-dynamics a skos:Concept ;
rdfs:label "Contact Dynamics"@en .
ngm:contact-dynamics-model a skos:Concept ;
rdfs:label "Contact Dynamics Model"@en .
ngm:contact-manifold a skos:Concept ;
rdfs:label "Contact Manifold"@en .
ngm:contact-mechanics a owl:Class ;
rdfs:comment "Contact mechanics is the study of the forces, deformations, and motions that arise when solid bodies touch and interact at their surfaces. It models phenomena such as normal contact forces, friction, adhesion, and local deformation, and provides the constitutive laws that govern how bodies push against, stick to, and slide over one another. In robotics it is essential for grasping, manipulation, locomotion, and physical simulation."@en ;
rdfs:label "Contact Mechanics"@en ;
rdfs:subClassOf ngm:physics-simulation ;
rdfs:subClassOf _:r5479 ;
rdfs:subClassOf _:r5480 ;
vc:contrastsWith ngm:rigid-body-dynamics ;
vc:dependsOn ngm:collision-detection ;
vc:dependsOn ngm:physics-simulation ;
vc:enables ngm:dexterous-manipulation ;
vc:enables ngm:grasping ;
vc:enables ngm:robotic-grasping ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:physics-simulation ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:friction ;
vc:relatedTo ngm:rigid-body-dynamics ;
vc:relatedTo ngm:tactile-sensing ;
vc:requires ngm:friction ;
vc:requires ngm:rigid-body-dynamics ;
vc:slug "contact-mechanics" ;
vc:sourceDomain "robotics" ;
vc:supports ngm:dexterous-manipulation ;
vc:supports ngm:soft-robotics ;
vc:uses ngm:collision-detection ;
vc:uses ngm:physics-engine .
ngm:contact-model a skos:Concept ;
rdfs:label "Contact Model"@en .
ngm:contact-network a skos:Concept ;
rdfs:label "Contact Network"@en .
ngm:contact-resolution a skos:Concept ;
rdfs:label "Contact Resolution"@en .
ngm:contact-tracing a skos:Concept ;
rdfs:label "Contact Tracing"@en .
ngm:contactless-payment a skos:Concept ;
rdfs:label "Contactless Payment"@en .
ngm:container a owl:Class ;
rdfs:comment "A container is a lightweight, isolated runtime package that bundles an application together with its dependencies, libraries and configuration so it runs consistently across environments. Containers share the host operating system kernel while using namespaces and control groups for isolation, making them far more efficient than full virtual machines. They are the standard unit of deployment for machine-learning services and microservices."@en ;
rdfs:label "Container"@en ;
rdfs:subClassOf ngm:ai-infrastructure ;
rdfs:subClassOf ngm:cloud-native ;
rdfs:subClassOf ngm:deployment-artifact ;
rdfs:subClassOf ngm:infrastructure ;
rdfs:subClassOf _:r5491 ;
rdfs:subClassOf _:r5492 ;
rdfs:subClassOf _:r5493 ;
rdfs:subClassOf _:r5494 ;
rdfs:subClassOf _:r5495 ;
rdfs:subClassOf _:r5496 ;
rdfs:subClassOf _:r5497 ;
rdfs:subClassOf _:r5498 ;
skos:broader ngm:infrastructure ;
vc:contrastsWith ngm:serverless ;
vc:contrastsWith ngm:virtualisation ;
vc:contrastsWith ngm:web-assembly ;
vc:dependsOn ngm:cloud-infrastructure ;
vc:dependsOn ngm:containerd ;
vc:dependsOn ngm:cri-o ;
vc:dependsOn ngm:kubernetes ;
vc:dependsOn ngm:orchestration ;
vc:enables ngm:edge-computing ;
vc:enables ngm:fault-tolerance ;
vc:enables ngm:high-availability ;
vc:enables ngm:immutable-infrastructure ;
vc:enables ngm:microservices ;
vc:enables ngm:model-deployment ;
vc:enables ngm:platform-engineering ;
vc:enables ngm:reproducibility ;
vc:enables ngm:scalability ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:container-image ;
vc:hasPart ngm:container-registry ;
vc:hasPart ngm:container-runtime ;
vc:hasPart ngm:control-groups ;
vc:hasPart ngm:deployment-artifact ;
vc:hasPart ngm:namespace ;
vc:implements ngm:gitops ;
vc:implements ngm:immutable-infrastructure ;
vc:implements ngm:resource-isolation ;
vc:implements ngm:software-supply-chain ;
vc:isPartOf ngm:cloud-infrastructure ;
vc:isPartOf ngm:cloud-native ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:cncf ;
vc:relatedTo ngm:container-security ;
vc:relatedTo ngm:devops ;
vc:relatedTo ngm:digital-twin ;
vc:relatedTo ngm:distributed-system ;
vc:relatedTo ngm:fault-tolerance ;
vc:relatedTo ngm:fintech ;
vc:relatedTo ngm:gpu-computing ;
vc:relatedTo ngm:high-availability ;
vc:relatedTo ngm:infrastructure-as-code ;
vc:relatedTo ngm:kubeflow ;
vc:relatedTo ngm:serverless ;
vc:relatedTo ngm:service-mesh ;
vc:relatedTo ngm:v-llm ;
vc:requires ngm:containerisation ;
vc:requires ngm:linux-kernel ;
vc:requires ngm:open-container-initiative ;
vc:requires ngm:resource-isolation ;
vc:slug "container" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:cncf ;
vc:standardizedBy ngm:open-container-initiative ;
vc:supports ngm:ci-cd ;
vc:supports ngm:devops ;
vc:supports ngm:distributed-system ;
vc:supports ngm:gitops ;
vc:supports ngm:microservices-architecture ;
vc:supports ngm:mlops ;
vc:supports ngm:platform-engineering ;
vc:uses ngm:cgroups ;
vc:uses ngm:control-groups ;
vc:uses ngm:docker-containerisation-platform ;
vc:uses ngm:ebpf ;
vc:uses ngm:linux-kernel ;
vc:uses ngm:namespace ;
vc:uses ngm:open-container-initiative .
ngm:container-image a owl:Class ;
rdfs:comment "An immutable, layered filesystem bundle packaging an application together with its runtime, libraries, and configuration metadata, from which container instances are created. Defined by the OCI Image Specification as content-addressed layers plus a manifest and configuration, images are built once, distributed through registries, and executed identically on any compliant runtime, providing the reproducible unit of software delivery that underpins containerised infrastructure from cloud clusters to edge devices."@en ;
rdfs:label "Container Image"@en ;
rdfs:subClassOf ngm:containerisation ;
vc:enables ngm:container ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:docker-containerisation-platform ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:container-registry ;
vc:relatedTo ngm:edge-computing ;
vc:slug "container-image" ;
vc:sourceDomain "infrastructure" .
ngm:container-networking a skos:Concept ;
rdfs:label "Container Networking"@en .
ngm:container-orchestration a owl:Class ;
rdfs:comment "Container orchestration is the automated management of the deployment, scaling, networking, and lifecycle of containerised workloads across a cluster of machines. An orchestrator continuously reconciles the observed state of the cluster with a declarative desired state, handling scheduling, health checking, self-healing, and rolling updates. It abstracts the underlying hosts into a single pool of compute, enabling resilient, horizontally scalable services without manual intervention."@en ;
rdfs:label "Container Orchestration"@en ;
rdfs:subClassOf ngm:orchestration ;
rdfs:subClassOf _:r5481 ;
rdfs:subClassOf _:r5482 ;
rdfs:subClassOf _:r5483 ;
rdfs:subClassOf _:r5484 ;
rdfs:subClassOf _:r5485 ;
vc:dependsOn ngm:distributed-computing ;
vc:enables ngm:fault-tolerance ;
vc:enables ngm:high-availability ;
vc:enables ngm:microservices ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:auto-scaling ;
vc:hasPart ngm:load-balancing ;
vc:hasPart ngm:service-discovery ;
vc:isPartOf ngm:cloud-native ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:gitops ;
vc:relatedTo ngm:kubernetes ;
vc:requires ngm:container-runtime ;
vc:requires ngm:containerisation ;
vc:slug "container-orchestration" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:devops ;
vc:supports ngm:resilience ;
vc:uses ngm:cloud-computing ;
vc:uses ngm:service-mesh .
ngm:container-registry a owl:Class ;
rdfs:comment "A content-addressed storage and distribution service for container images that implements the OCI Distribution Specification's push, pull, and discovery API. Registries hold image layers and manifests under named, tagged repositories, enforce authentication and access control, and increasingly store signatures, SBOMs, and other supply-chain artefacts alongside images, making them the central hand-off point between build pipelines and every runtime that deploys containerised software."@en ;
rdfs:label "Container Registry"@en ;
rdfs:subClassOf ngm:containerisation ;
rdfs:subClassOf _:r5486 ;
vc:contrastsWith ngm:model-registry ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:container-image ;
vc:isPartOf ngm:docker-containerisation-platform ;
vc:qualityScore "0.8"^^xsd:float ;
vc:slug "container-registry" ;
vc:sourceDomain "infrastructure" .
ngm:container-runtime a owl:Class ;
rdfs:comment "A container runtime is the software responsible for running containers on a host: pulling and unpacking images, configuring isolation and resource limits, and starting, stopping and supervising container processes. Runtimes operate at low and high levels, from minimal process launchers to daemons that manage image lifecycles, and present standard interfaces consumed by orchestrators such as Kubernetes. Container runtimes provide the execution foundation for portable, lightweight, cloud-native workloads."@en ;
rdfs:label "Container Runtime"@en ;
rdfs:subClassOf ngm:cloud-native ;
rdfs:subClassOf _:r5487 ;
rdfs:subClassOf _:r5488 ;
rdfs:subClassOf _:r5489 ;
rdfs:subClassOf _:r5490 ;
vc:contrastsWith ngm:virtual-machine ;
vc:dependsOn ngm:network-protocol ;
vc:enables ngm:continuous-deployment ;
vc:enables ngm:kubernetes ;
vc:enables ngm:microservices ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:orchestration ;
vc:hasPart ngm:resource-management ;
vc:implements ngm:service-discovery ;
vc:isPartOf ngm:cloud-native ;
vc:isPartOf ngm:infrastructure ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:kubernetes ;
vc:relatedTo ngm:microservices ;
vc:requires ngm:infrastructure ;
vc:requires ngm:resource-management ;
vc:slug "container-runtime" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:devops ;
vc:supports ngm:fault-tolerance ;
vc:supports ngm:scalability ;
vc:uses ngm:orchestration .
ngm:container-security a skos:Concept ;
rdfs:label "Container Security"@en .
ngm:containerd a skos:Concept ;
rdfs:label "Containerd"@en .
ngm:containerisation a owl:Class ;
rdfs:comment "Containerisation is an operating-system-level virtualisation technique that packages an application together with its dependencies, libraries, and configuration into a single portable, isolated unit called a container. Containers share the host kernel yet maintain isolated user spaces, making them far lighter than full virtual machines while remaining reproducible across environments. The approach underpins cloud-native software delivery, providing consistent runtime behaviour from a developer's laptop to production clusters."@en ;
rdfs:label "Containerisation"@en ;
rdfs:subClassOf ngm:container-runtime ;
rdfs:subClassOf ngm:virtualisation ;
rdfs:subClassOf _:r5499 ;
rdfs:subClassOf _:r5500 ;
vc:contrastsWith ngm:virtual-machine ;
vc:dependsOn ngm:virtual-machine ;
vc:enables ngm:cloud-native ;
vc:enables ngm:container-orchestration ;
vc:enables ngm:microservices ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:container-runtime ;
vc:implements ngm:immutable-infrastructure ;
vc:isPartOf ngm:cloud-native ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:gitops ;
vc:relatedTo ngm:kubernetes ;
vc:requires ngm:container-runtime ;
vc:slug "containerisation" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:continuous-deployment ;
vc:supports ngm:devops ;
vc:uses ngm:cloud-computing .
ngm:contamination-detection a skos:Concept ;
rdfs:label "Contamination Detection"@en .
ngm:content-access a skos:Concept ;
rdfs:label "Content Access"@en .
ngm:content-addressed-storage a owl:Class ;
rdfs:comment "Content-addressed storage (CAS) is a data storage paradigm in which each piece of data is identified and retrieved by a cryptographic hash of its content rather than by its location or a human-assigned name. Because the identifier is derived deterministically from the data itself, identical content always maps to the same address, enabling automatic deduplication and verifiable integrity without requiring trust in the storage provider. Content-addressed storage forms the basis of distributed systems such as IPFS, Git, and Arweave, and underlies the content-integrity mechanisms of blockchain data layers. It is fundamentally different from location-addressed storage, where the same content can exist at multiple addresses or the same address can point to different content over time."@en ;
rdfs:label "Content-Addressed Storage"@en ;
rdfs:subClassOf ngm:data-storage ;
rdfs:subClassOf _:r5598 ;
rdfs:subClassOf _:r5599 ;
vc:bridgesTo ngm:data-layer ;
vc:bridgesTo ngm:data-versioning ;
vc:bridgesTo ngm:model-registry ;
vc:contrastsWith ngm:location-addressed-storage ;
vc:contrastsWith ngm:object-storage ;
vc:enables ngm:cryptographic-verification ;
vc:enables ngm:data-availability ;
vc:enables ngm:data-deduplication ;
vc:enables ngm:provenance ;
vc:enables ngm:reproducible-builds ;
vc:enables ngm:tamper-evidence ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:arweave ;
vc:implements ngm:filecoin ;
vc:implements ngm:git ;
vc:implements ngm:ipfs ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:data-integrity ;
vc:relatedTo ngm:zero-knowledge-proof ;
vc:requires ngm:content-identifier ;
vc:requires ngm:hash-function ;
vc:slug "content-addressed-storage" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:decentralized-storage ;
vc:supports ngm:distributed-storage ;
vc:supports ngm:peer-to-peer-network ;
vc:supports ngm:version-control ;
vc:uses ngm:content-addressing ;
vc:uses ngm:cryptographic-hash ;
vc:uses ngm:distributed-hash-table ;
vc:uses ngm:kzg-commitment ;
vc:uses ngm:merkle-tree .
ngm:content-addressing a owl:Class ;
rdfs:comment "The fundamental principle (R1 in ADR-013) that derives a resource's URI deterministically from its Content Hash|cryptographic content hash (SHA-256), ensuring immutability, tamper-detection, and deduplication, enabling VisionClaw Agentic Container|VisionClaw artefacts (credentials, receip..."@en ;
rdfs:label "Content Addressing"@en ;
rdfs:subClassOf ngm:network-component ;
rdfs:subClassOf _:r5501 ;
rdfs:subClassOf _:r5502 ;
rdfs:subClassOf _:r5503 ;
rdfs:subClassOf _:r5504 ;
rdfs:subClassOf _:r5505 ;
rdfs:subClassOf _:r5506 ;
vc:bridgesTo ngm:blockchain-hash-functions ;
vc:bridgesTo ngm:data-layer ;
vc:bridgesTo ngm:distributed-hash-table ;
vc:bridgesTo ngm:merkle-tree ;
vc:enables ngm:decentralised-storage ;
vc:enables ngm:decentralized-storage ;
vc:enables ngm:deduplication ;
vc:enables ngm:immutability ;
vc:enables ngm:permanent-referenceability ;
vc:enables ngm:tamper-detection ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:content-identifier ;
vc:hasPart ngm:deterministic-serialisation ;
vc:hasPart ngm:hash-minting ;
vc:hasPart ngm:sha-256-hashing ;
vc:implements ngm:content-addressed-storage ;
vc:implements ngm:git-object-addressing ;
vc:implements ngm:ipfs-content-addressing ;
vc:qualityScore "0.92"^^xsd:float ;
vc:requires ngm:canonical-json ;
vc:requires ngm:cryptographic-hash-function ;
vc:requires ngm:deterministic-encoding ;
vc:slug "content-addressing" ;
vc:sourceDomain "blockchain" .
ngm:content-analysis-tools a skos:Concept ;
rdfs:label "Content Analysis Tools"@en .
ngm:content-authentication a owl:Class ;
rdfs:comment "Content Authentication is the process of verifying the origin, integrity, and provenance of digital content through cryptographic techniques such as digital signatures, watermarking, and blockchain-anchored certificates. It enables consumers and platforms to distinguish authentic content from synthetically generated or tampered media, particularly critical as generative AI proliferates."@en ;
rdfs:label "Content Authentication"@en ;
rdfs:subClassOf ngm:infra-security-and-identity ;
rdfs:subClassOf _:r5507 ;
rdfs:subClassOf _:r5508 ;
rdfs:subClassOf _:r5509 ;
rdfs:subClassOf _:r5510 ;
skos:broader ngm:infra-security-and-identity ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:contrastsWith ngm:deepfakes ;
vc:contrastsWith ngm:synthetic-media ;
vc:enables ngm:deepfake-detection ;
vc:enables ngm:trust-establishment ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:c2-pa-content-credentials ;
vc:implements ngm:c2-pa-standard ;
vc:qualityScore "0.7"^^xsd:float ;
vc:relatedTo ngm:digital-rights-management ;
vc:relatedTo ngm:non-fungible-token ;
vc:relatedTo ngm:zero-knowledge-proof ;
vc:requires ngm:certificate-authority ;
vc:requires ngm:cryptographic-infrastructure ;
vc:requires ngm:cryptographic-verification ;
vc:requires ngm:digital-signature ;
vc:slug "content-authentication" ;
vc:sourceDomain "security" ;
vc:supports ngm:digital-rights-management ;
vc:supports ngm:information-integrity ;
vc:uses ngm:blockchain ;
vc:uses ngm:cryptographic-hash-function ;
vc:uses ngm:digital-content-provenance-marking ;
vc:uses ngm:merkle-tree ;
vc:uses ngm:watermarking-service .
ngm:content-authenticity a owl:Class ;
rdfs:comment "Content authenticity is the property of a digital asset whereby its origin, creation history, and any subsequent modifications can be cryptographically verified and traced back to an identifiable source. It encompasses technical mechanisms — including cryptographic signatures, tamper-evident manifests, and provenance metadata — that allow consumers of media to assess whether content has been created or manipulated by humans or AI systems and whether it has been altered since its stated point of capture or creation. Content authenticity is increasingly codified through standards such as C2PA (Coalition for Content Provenance and Authenticity)."@en ;
rdfs:label "Content Authenticity"@en ;
rdfs:subClassOf ngm:content-authentication ;
vc:contrastsWith ngm:deepfakes-and-fraudulent-content ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:data-provenance ;
vc:relatedTo ngm:deepfakes ;
vc:relatedTo ngm:digital-signature ;
vc:relatedTo ngm:metadata-standard ;
vc:slug "content-authenticity" ;
vc:sourceDomain "security" ;
vc:uses ngm:c2-pa ;
vc:uses ngm:cryptographic-signature ;
vc:uses ngm:provenance-tracking .
ngm:content-authoring-system a skos:Concept ;
rdfs:label "Content Authoring System"@en .
ngm:content-based-filtering a owl:Class ;
rdfs:comment "A recommendation technique that suggests items by matching the attributes of items a user has previously engaged with — such as text features, genres, tags, or learned embeddings — against the attributes of candidate items, building a per-user preference profile in feature space; it requires no data about other users, handles new items gracefully, and offers explainable suggestions, but tends to over-specialise, recommending only items similar to what the user already knows."@en ;
rdfs:label "Content-Based Filtering"@en ;
rdfs:subClassOf ngm:recommendation-systems ;
vc:contrastsWith ngm:collaborative-systems-modality-filtering ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:content-discovery ;
vc:isPartOf ngm:hyper-personalisation ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:filter-bubble ;
vc:slug "content-based-filtering" ;
vc:sourceDomain "machine-learning" .
ngm:content-based-routing a skos:Concept ;
rdfs:label "Content Based Routing"@en .
ngm:content-catalog a skos:Concept ;
rdfs:label "Content Catalog"@en .
ngm:content-classification a skos:Concept ;
rdfs:label "Content Classification"@en .
ngm:content-classification-system a skos:Concept ;
rdfs:label "Content Classification System"@en .
ngm:content-composition a skos:Concept ;
rdfs:label "Content Composition"@en .
ngm:content-connector a skos:Concept ;
rdfs:label "Content Connector"@en .
ngm:content-creation a owl:Class ;
rdfs:comment "Content Creation is the structured process of conceiving, producing, and distributing communicative artefacts—including text, imagery, audio, video, and interactive media—designed to inform, entertain, educate, or persuade defined audiences. It spans the complete production lifecycle from ideation, research, and scripting through asset generation, editing, quality assurance, and multichannel distribution. In AI-augmented workflows, generative models assist at every stage, lowering production costs and accelerating iteration cycles while demanding rigorous editorial oversight for accuracy and brand consistency. Effective content creation integrates creative vision, platform-specific optimisation, audience psychology, and provenance management to maximise reach, trust, and impact."@en ;
rdfs:label "Content Creation"@en ;
rdfs:subClassOf ngm:digital-content ;
rdfs:subClassOf ngm:digital-content-creation ;
rdfs:subClassOf ngm:media-production ;
rdfs:subClassOf _:r5517 ;
rdfs:subClassOf _:r5518 ;
rdfs:subClassOf _:r5519 ;
rdfs:subClassOf _:r5520 ;
rdfs:subClassOf _:r5521 ;
rdfs:subClassOf _:r5522 ;
rdfs:subClassOf _:r5523 ;
vc:bridgesTo ngm:nft ;
vc:bridgesTo ngm:spatial-content ;
vc:contrastsWith ngm:content-curation ;
vc:contrastsWith ngm:user-generated-content ;
vc:dependsOn ngm:cdn ;
vc:dependsOn ngm:cloud-computing ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:natural-language-processing ;
vc:dependsOn ngm:recommendation-systems ;
vc:dependsOn ngm:transformer-architecture ;
vc:enables ngm:audience-engagement ;
vc:enables ngm:creator-economy ;
vc:enables ngm:data-storytelling ;
vc:enables ngm:digital-marketing ;
vc:enables ngm:knowledge-management ;
vc:enables ngm:social-media-platform-infrastructure ;
vc:enables ngm:synthetic-media ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:audio-generation ;
vc:hasPart ngm:content-strategy ;
vc:hasPart ngm:digital-asset-management ;
vc:hasPart ngm:editorial-workflow ;
vc:hasPart ngm:multimodal-ai-architecture-ai ;
vc:hasPart ngm:natural-language-generation ;
vc:hasPart ngm:text-to-image-model ;
vc:implements ngm:content-strategy ;
vc:implements ngm:editorial-workflow ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:algorithmic-accountability ;
vc:relatedTo ngm:content-discovery ;
vc:relatedTo ngm:content-strategy ;
vc:relatedTo ngm:creative-ai ;
vc:relatedTo ngm:digital-content-creation ;
vc:relatedTo ngm:etsi-domain-creative-media ;
vc:relatedTo ngm:generative-content ;
vc:relatedTo ngm:media-production ;
vc:relatedTo ngm:recommendation-systems ;
vc:requires ngm:content-moderation ;
vc:requires ngm:digital-asset-management ;
vc:requires ngm:editorial-workflow ;
vc:requires ngm:natural-language-processing ;
vc:slug "content-creation" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:etsi-domain-creative-media ;
vc:supports ngm:algorithmic-accountability ;
vc:supports ngm:brand-identity ;
vc:supports ngm:content-discovery ;
vc:supports ngm:data-storytelling ;
vc:supports ngm:knowledge-management ;
vc:supports ngm:search-engine-optimisation ;
vc:uses ngm:agentic-ai ;
vc:uses ngm:creative-ai ;
vc:uses ngm:creative-tools ;
vc:uses ngm:deep-learning ;
vc:uses ngm:diffusion-model ;
vc:uses ngm:generative-ai ;
vc:uses ngm:large-language-model ;
vc:uses ngm:multimodal-ai-architecture-ai ;
vc:uses ngm:natural-language-generation ;
vc:uses ngm:text-to-image-model ;
vc:uses ngm:transformer-architecture .
ngm:content-creation-pipeline a owl:Class ;
rdfs:comment "A Content Creation Pipeline is a structured, orchestrated workflow that sequences and parallelises the stages of producing digital content—spanning ideation, scripting, asset generation, editorial review, quality assurance, and multi-platform distribution—into a reproducible and scalable production system. Modern pipelines integrate AI generation models, digital asset management systems, localisation engines, and publishing endpoints to deliver high-throughput content production with traceable asset provenance. They are the operational backbone of film VFX studios, game development, streaming platforms, and enterprise marketing operations, governing how raw creative intent is transformed into finished, distributed artefacts. Pipeline architecture choices directly determine release velocity, brand consistency, and the cost structure of large-scale content organisations."@en ;
rdfs:label "Content Creation Pipeline"@en ;
rdfs:subClassOf ngm:content-creation ;
rdfs:subClassOf _:r5511 ;
rdfs:subClassOf _:r5512 ;
rdfs:subClassOf _:r5513 ;
rdfs:subClassOf _:r5514 ;
rdfs:subClassOf _:r5515 ;
rdfs:subClassOf _:r5516 ;
vc:bridgesTo ngm:data-pipeline ;
vc:bridgesTo ngm:machine-learning-discipline-pipeline ;
vc:contrastsWith ngm:manual-production-workflow ;
vc:dependsOn ngm:cdn ;
vc:dependsOn ngm:cloud-computing ;
vc:enables ngm:automated-publishing ;
vc:enables ngm:localisation ;
vc:enables ngm:media-production ;
vc:enables ngm:metaverse-content-creation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:asset-management ;
vc:hasPart ngm:distribution-platform ;
vc:hasPart ngm:quality-assurance ;
vc:hasPart ngm:workflow-orchestration ;
vc:implements ngm:directed-acyclic-graph ;
vc:implements ngm:provenance-tracking ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:c2-pa ;
vc:relatedTo ngm:creative-automation ;
vc:relatedTo ngm:digital-content-creation ;
vc:relatedTo ngm:video-production-pipeline ;
vc:requires ngm:content-management-system ;
vc:requires ngm:digital-asset-management ;
vc:requires ngm:version-control ;
vc:slug "content-creation-pipeline" ;
vc:sourceDomain "distributed-collaboration" ;
vc:uses ngm:content-creation-tool ;
vc:uses ngm:generative-ai ;
vc:uses ngm:render-farm ;
vc:uses ngm:workflow-engine .
ngm:content-creation-tool a owl:Class ;
rdfs:comment "A content creation tool is software that enables users to author, edit, and produce digital media such as text, images, audio, 3D assets, or video. It provides the interfaces and primitives needed to turn creative intent into finished, exportable artefacts. Generative AI has expanded this category to include tools that synthesise content from prompts and steer it within a production pipeline."@en ;
rdfs:label "Content Creation Tool"@en ;
rdfs:subClassOf ngm:sc-content-and-assets ;
skos:broader ngm:sc-content-and-assets ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:content-creation-pipeline ;
vc:relatedTo ngm:generative-design-tool ;
vc:slug "content-creation-tool" ;
vc:sourceDomain "metaverse" .
ngm:content-creation-tools a skos:Concept ;
rdfs:label "Content Creation Tools"@en .
ngm:content-creator-liability a skos:Concept ;
rdfs:label "Content Creator Liability"@en .
ngm:content-curation a owl:Class ;
rdfs:comment "The practice of discovering, selecting, contextualising, and organising existing content for a particular audience, in contrast to producing new material. Content curation adds value through judgement—filtering signal from an overwhelming volume of published media, sequencing items into coherent collections, and annotating them with commentary or provenance—whether performed by human editors, algorithmic recommendation systems, or hybrid pipelines that combine both."@en ;
rdfs:label "Content Curation"@en ;
rdfs:subClassOf ngm:information-management ;
vc:contrastsWith ngm:content-creation ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:attention-economy ;
vc:relatedTo ngm:content-moderation ;
vc:relatedTo ngm:data-curation ;
vc:slug "content-curation" ;
vc:sourceDomain "data" ;
vc:uses ngm:recommendation-system .
ngm:content-delivery a owl:Class ;
rdfs:comment "Content delivery is the distribution of digital media such as web pages, video and software to end users, typically optimised for speed and reliability. It is commonly accelerated by content delivery networks."@en ;
rdfs:label "Content Delivery"@en ;
rdfs:subClassOf ngm:infra-network-and-comms ;
rdfs:subClassOf ngm:owl-thing ;
rdfs:subClassOf _:r5541 ;
skos:broader ngm:infra-network-and-comms ;
vc:bridgesTo ngm:cdn ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:video-compression ;
vc:slug "content-delivery" ;
vc:sourceDomain "infrastructure" .
ngm:content-delivery-network a owl:Class ;
rdfs:comment "A Content Delivery Network (CDN) is a geographically distributed system of edge servers and Points of Presence (PoPs) that cache, replicate, and serve web assets — static files, media streams, and increasingly dynamic API responses — from locations physically near end users, substantially reducing round-trip latency and offloading origin-server load. CDNs use anycast routing, DNS-based request steering, and intelligent load balancing to direct each client request to the nearest healthy PoP, with cache coherence governed by HTTP cache-control semantics (RFC 9111) and conditional request mechanisms. Modern CDNs have evolved into full edge-compute platforms, offering TLS termination, DDoS mitigation, Web Application Firewall (WAF) services, and serverless edge runtimes (e.g. Cloudflare Workers, Fastly Compute) that execute application logic at PoPs without origin round-trips, blurring the boundary between network infrastructure and distributed application hosting."@en ;
rdfs:label "Content Delivery Network"@en ;
rdfs:subClassOf ngm:network-infrastructure ;
rdfs:subClassOf _:r5535 ;
rdfs:subClassOf _:r5536 ;
rdfs:subClassOf _:r5537 ;
rdfs:subClassOf _:r5538 ;
rdfs:subClassOf _:r5539 ;
rdfs:subClassOf _:r5540 ;
vc:bridgesTo ngm:edge-inference ;
vc:bridgesTo ngm:spatial-computing ;
vc:contrastsWith ngm:origin-server ;
vc:contrastsWith ngm:peer-to-peer-network ;
vc:enables ngm:ddos-mitigation ;
vc:enables ngm:edge-computing ;
vc:enables ngm:low-latency ;
vc:enables ngm:origin-offload ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:edge-server ;
vc:hasPart ngm:load-balancer ;
vc:hasPart ngm:point-of-presence ;
vc:hasPart ngm:web-application-firewall ;
vc:isPartOf ngm:internet-infrastructure ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:caching ;
vc:relatedTo ngm:network-latency ;
vc:relatedTo ngm:reverse-proxy ;
vc:relatedTo ngm:web-performance ;
vc:requires ngm:anycast-routing ;
vc:requires ngm:dns ;
vc:requires ngm:tls ;
vc:slug "content-delivery-network" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:cloud-infrastructure ;
vc:supports ngm:microservices-architecture ;
vc:supports ngm:scalability-pattern ;
vc:supports ngm:streaming-media ;
vc:uses ngm:anycast-routing ;
vc:uses ngm:encryption ;
vc:uses ngm:http-caching ;
vc:uses ngm:quic .
ngm:content-delivery-network-cdn a owl:Class ;
rdfs:comment "A geographically distributed network of proxy servers and data centers designed to provide high availability, high performance, and low latency content delivery by caching content closer to end-users."@en ;
rdfs:label "Content Delivery Network (CDN)"@en ;
rdfs:subClassOf ngm:infra-network-and-comms ;
rdfs:subClassOf ngm:network-infrastructure ;
rdfs:subClassOf _:r5524 ;
rdfs:subClassOf _:r5525 ;
rdfs:subClassOf _:r5526 ;
rdfs:subClassOf _:r5527 ;
rdfs:subClassOf _:r5528 ;
rdfs:subClassOf _:r5529 ;
rdfs:subClassOf _:r5530 ;
rdfs:subClassOf _:r5531 ;
rdfs:subClassOf _:r5532 ;
rdfs:subClassOf _:r5533 ;
rdfs:subClassOf _:r5534 ;
skos:broader ngm:infra-network-and-comms ;
vc:bridgesTo ngm:computer-vision ;
vc:dependsOn ngm:data-centre ;
vc:dependsOn ngm:internet-service-provider ;
vc:dependsOn ngm:network-protocol ;
vc:enables ngm:ddos-protection ;
vc:enables ngm:geographic-redundancy ;
vc:enables ngm:low-latency-content-delivery ;
vc:enables ngm:scalable-distribution ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:cache-layer ;
vc:hasPart ngm:edge-server ;
vc:hasPart ngm:load-balancer ;
vc:hasPart ngm:origin-server ;
vc:hasPart ngm:routing-protocol ;
vc:isPartOf ngm:network-infrastructure ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:dns ;
vc:requires ngm:network-infrastructure ;
vc:requires ngm:storage-systems ;
vc:slug "content-delivery-network-cdn" ;
vc:sourceDomain "infrastructure" .
ngm:content-delivery-networks a skos:Concept ;
rdfs:label "Content Delivery Networks"@en .
ngm:content-discovery a owl:Class ;
rdfs:comment "Content Discovery encompasses the mechanisms, algorithms, and systems by which users or automated agents locate, surface, and retrieve relevant digital content from large-scale repositories or networks. It spans search-engine indexing, recommendation algorithms, semantic retrieval, and social curation, and is increasingly driven by machine learning models that personalise results to individual preference signals. Effective content discovery is foundational to user experience across the web, streaming platforms, knowledge graphs, and decentralised content networks. It sits at the intersection of information retrieval theory, personalisation engineering, and data governance."@en ;
rdfs:label "Content Discovery"@en ;
rdfs:subClassOf ngm:information-retrieval ;
rdfs:subClassOf ngm:knowledge-management ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf _:r5542 ;
rdfs:subClassOf _:r5543 ;
rdfs:subClassOf _:r5544 ;
rdfs:subClassOf _:r5545 ;
rdfs:subClassOf _:r5546 ;
rdfs:subClassOf _:r5547 ;
rdfs:subClassOf _:r5548 ;
rdfs:subClassOf _:r5549 ;
rdfs:subClassOf _:r5550 ;
rdfs:subClassOf _:r5551 ;
rdfs:subClassOf _:r5552 ;
rdfs:subClassOf _:r5553 ;
vc:contrastsWith ngm:broadcast-media ;
vc:contrastsWith ngm:content-creation ;
vc:contrastsWith ngm:manual-curation ;
vc:contrastsWith ngm:search-engine-optimisation ;
vc:dependsOn ngm:gpu-compute ;
vc:dependsOn ngm:knowledge-graph ;
vc:dependsOn ngm:search-engine ;
vc:dependsOn ngm:social-media-platform-infrastructure ;
vc:dependsOn ngm:transformer-architecture ;
vc:dependsOn ngm:user-generated-content ;
vc:dependsOn ngm:vector-database ;
vc:enables ngm:audience-engagement ;
vc:enables ngm:content-moderation ;
vc:enables ngm:creator-economy ;
vc:enables ngm:digital-curation-platform ;
vc:enables ngm:discovery-layer ;
vc:enables ngm:knowledge-management ;
vc:enables ngm:personalisation ;
vc:enables ngm:retrieval-augmented-generation ;
vc:enables ngm:serendipitous-discovery ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:candidate-generation ;
vc:hasPart ngm:collaborative-systems-modality-filtering ;
vc:hasPart ngm:content-based-filtering ;
vc:hasPart ngm:dense-retrieval ;
vc:hasPart ngm:discovery-layer ;
vc:hasPart ngm:recommendation-systems ;
vc:hasPart ngm:search-engine ;
vc:hasPart ngm:semantic-search ;
vc:implements ngm:bm25 ;
vc:implements ngm:dense-retrieval ;
vc:implements ngm:hybrid-retrieval ;
vc:implements ngm:late-interaction ;
vc:implements ngm:two-tower-network ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:algorithmic-accountability ;
vc:relatedTo ngm:algorithmic-bias ;
vc:relatedTo ngm:algorithmic-transparency ;
vc:relatedTo ngm:cold-start-problem ;
vc:relatedTo ngm:content-creation ;
vc:relatedTo ngm:content-ranking ;
vc:relatedTo ngm:decentralised-content-network ;
vc:relatedTo ngm:digital-services-act ;
vc:relatedTo ngm:diversity-objective ;
vc:relatedTo ngm:engagement-maximisation ;
vc:relatedTo ngm:federated-social-web ;
vc:relatedTo ngm:filter-bubble ;
vc:relatedTo ngm:knowledge-graph ;
vc:relatedTo ngm:nostr-protocol ;
vc:relatedTo ngm:online-safety-act-2023 ;
vc:relatedTo ngm:responsible-ai ;
vc:relatedTo ngm:search-engine ;
vc:requires ngm:algorithmic-accountability ;
vc:requires ngm:content-moderation ;
vc:requires ngm:data-governance ;
vc:requires ngm:implicit-feedback ;
vc:requires ngm:indexing ;
vc:requires ngm:user-profiling ;
vc:slug "content-discovery" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:digital-services-act ;
vc:standardizedBy ngm:online-safety-act-2023 ;
vc:supports ngm:agentic-ai ;
vc:supports ngm:audience-engagement ;
vc:supports ngm:content-generation ;
vc:supports ngm:creator-economy ;
vc:supports ngm:digital-marketing ;
vc:supports ngm:natural-language-generation ;
vc:uses ngm:deep-learning ;
vc:uses ngm:embeddings ;
vc:uses ngm:feature-engineering ;
vc:uses ngm:graph-neural-network ;
vc:uses ngm:inverted-index ;
vc:uses ngm:large-language-model ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:nearest-neighbor-search ;
vc:uses ngm:recommendation-systems ;
vc:uses ngm:transformer-architecture ;
vc:uses ngm:vector-database .
ngm:content-distribution a owl:Class ;
rdfs:comment "Content Distribution encompasses the technical and logistical systems that deliver digital media—web pages, video, software, and other assets—from origin servers to end users at scale, minimising latency and maximising availability by replicating and caching content geographically close to consumers. It is realised primarily through Content Delivery Networks (CDNs) that operate distributed edge node infrastructure, but also includes peer-to-peer protocols, adaptive bitrate streaming, and decentralised storage networks as alternative or complementary mechanisms. Effective content distribution is the foundational infrastructure of the commercial internet, underpinning e-commerce, streaming media, and cloud-native application delivery."@en ;
rdfs:label "Content Distribution"@en ;
rdfs:subClassOf ngm:digital-infrastructure ;
rdfs:subClassOf _:r5554 ;
rdfs:subClassOf _:r5555 ;
vc:enables ngm:cloud-native-applications ;
vc:enables ngm:video-streaming ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:content-delivery-network-cdn ;
vc:hasPart ngm:edge-computing ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:cloud-infrastructure ;
vc:relatedTo ngm:decentralized-storage ;
vc:relatedTo ngm:peer-to-peer-network ;
vc:slug "content-distribution" ;
vc:sourceDomain "infrastructure" .
ngm:content-distribution-network a skos:Concept ;
rdfs:label "Content Distribution Network"@en .
ngm:content-encryption-engine a skos:Concept ;
rdfs:label "Content Encryption Engine"@en .
ngm:content-extraction-pipeline a skos:Concept ;
rdfs:label "Content Extraction Pipeline"@en .
ngm:content-generation a owl:Class ;
rdfs:comment "Content Generation is the application domain within [[Generative AI]] and [[AI Machine Learning]] concerned with automatically synthesising novel media artefacts — including text, images, code, audio, video, and mixed-modality outputs — from structured or natural-language inputs, using probabilistic generative models that have learned the distribution of training corpora. It encompasses [[Large Language Model]]-based text and code generation, [[Diffusion Model]]-based image and video synthesis, multimodal fusion pipelines, and the wider infrastructure for deployment, evaluation, and governance of such systems at scale."@en ;
rdfs:label "Content Generation"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:creative-ai ;
rdfs:subClassOf ngm:generative-ai ;
rdfs:subClassOf _:r5556 ;
rdfs:subClassOf _:r5557 ;
rdfs:subClassOf _:r5558 ;
rdfs:subClassOf _:r5559 ;
rdfs:subClassOf _:r5560 ;
rdfs:subClassOf _:r5561 ;
rdfs:subClassOf _:r5562 ;
rdfs:subClassOf _:r5563 ;
rdfs:subClassOf _:r5564 ;
rdfs:subClassOf _:r5565 ;
rdfs:subClassOf _:r5566 ;
rdfs:subClassOf _:r5567 ;
rdfs:subClassOf _:r5568 ;
rdfs:subClassOf _:r5569 ;
rdfs:subClassOf _:r5570 ;
skos:broader ngm:ai-application ;
vc:contrastsWith ngm:content-moderation ;
vc:contrastsWith ngm:discriminative-model ;
vc:contrastsWith ngm:human-authored-content ;
vc:contrastsWith ngm:rule-based-generation ;
vc:contrastsWith ngm:template-based-nlg ;
vc:dependsOn ngm:attention-mechanism ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:fine-tuning ;
vc:dependsOn ngm:large-language-model ;
vc:dependsOn ngm:neural-network ;
vc:dependsOn ngm:reinforcement-learning-from-human-feedback ;
vc:dependsOn ngm:rlhf ;
vc:dependsOn ngm:scaling-laws ;
vc:enables ngm:adaptive-learning ;
vc:enables ngm:agentic-ai ;
vc:enables ngm:automated-design ;
vc:enables ngm:content-discovery ;
vc:enables ngm:creative-ai ;
vc:enables ngm:personalisation ;
vc:enables ngm:scientific-hypothesis-generation ;
vc:enables ngm:synthetic-media ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:audio-generation ;
vc:hasPart ngm:code-synthesis ;
vc:hasPart ngm:multimodal-ai-architecture-ai ;
vc:hasPart ngm:natural-language-generation ;
vc:hasPart ngm:prompt-engineering ;
vc:hasPart ngm:retrieval-augmented-generation ;
vc:hasPart ngm:text-to-image ;
vc:hasPart ngm:text-to-video-generation ;
vc:implements ngm:autoregressive-model ;
vc:implements ngm:diffusion-model ;
vc:implements ngm:diffusion-transformer ;
vc:implements ngm:generative-adversarial-network ;
vc:implements ngm:latent-diffusion ;
vc:implements ngm:transformer-architecture ;
vc:implements ngm:vae ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:bias-in-ai ;
vc:relatedTo ngm:c2-pa ;
vc:relatedTo ngm:constitutional-ai-training-methodology ;
vc:relatedTo ngm:copyright ;
vc:relatedTo ngm:eu-ai-act-regulatory-instrument ;
vc:relatedTo ngm:hallucination ;
vc:relatedTo ngm:intellectual-property-rights-framework ;
vc:relatedTo ngm:model-collapse ;
vc:relatedTo ngm:responsible-ai ;
vc:relatedTo ngm:retrieval-augmented-generation ;
vc:relatedTo ngm:synthetic-media ;
vc:requires ngm:alignment ;
vc:requires ngm:embeddings ;
vc:requires ngm:fine-tuning ;
vc:requires ngm:foundation-model ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:prompt-engineering ;
vc:requires ngm:reinforcement-learning-from-human-feedback ;
vc:requires ngm:training-data ;
vc:slug "content-generation" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:c2-pa ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:content-discovery ;
vc:supports ngm:digital-marketing ;
vc:supports ngm:education-technology ;
vc:supports ngm:knowledge-graph ;
vc:supports ngm:model-evaluation ;
vc:supports ngm:retrieval-augmented-generation ;
vc:uses ngm:alignment ;
vc:uses ngm:direct-preference-optimisation ;
vc:uses ngm:embeddings ;
vc:uses ngm:gpu-compute ;
vc:uses ngm:grounding ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:nearest-neighbor-search ;
vc:uses ngm:watermarking-service .
ngm:content-identifier a owl:Class ;
rdfs:comment "A Content Identifier (CID) is a self-describing, cryptographically derived label used in the InterPlanetary File System and IPLD ecosystem to uniquely identify and verify content through its hash, encoding the hash function used, the hash digest, and a multicodec descriptor for the serialised data format into a compact, version-aware multihash structure."@en ;
rdfs:label "Content Identifier"@en ;
rdfs:subClassOf ngm:content-addressing ;
rdfs:subClassOf _:r5571 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:bridgesTo ngm:verifiable-credentials ;
vc:enables ngm:deduplication ;
vc:enables ngm:tamper-detection ;
vc:enables ngm:verifiable-data-registry ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:content-addressing ;
vc:isPartOf ngm:ipfs ;
vc:isPartOf ngm:ipld ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:filecoin ;
vc:relatedTo ngm:ipfs-content-addressing ;
vc:relatedTo ngm:nft-metadata ;
vc:requires ngm:cryptographic-hash-function ;
vc:slug "content-identifier" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:data-integrity ;
vc:supports ngm:distributed-storage ;
vc:supports ngm:peer-to-peer-network ;
vc:uses ngm:ipld ;
vc:uses ngm:merkle-dag ;
vc:uses ngm:multibase ;
vc:uses ngm:multicodec ;
vc:uses ngm:multihash .
ngm:content-indexer a skos:Concept ;
rdfs:label "Content Indexer"@en .
ngm:content-integrity a skos:Concept ;
rdfs:label "Content Integrity"@en .
ngm:content-interoperability a owl:Class ;
rdfs:comment "Content interoperability is the ability of digital assets to be created, exchanged, and rendered consistently across different platforms, engines, and tools without loss of fidelity. It depends on shared open formats, agreed schemas, and conformant import/export behaviour. In the metaverse it is the precondition for portable 3D assets, avatars, and scenes that work across virtual worlds."@en ;
rdfs:label "Content Interoperability"@en ;
rdfs:subClassOf ngm:sc-standards-and-interop ;
skos:broader ngm:sc-standards-and-interop ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:gl-tf-3-d-file-format ;
vc:relatedTo ngm:metaverse-content-pipeline ;
vc:slug "content-interoperability" ;
vc:sourceDomain "metaverse" .
ngm:content-labeling-metadata a skos:Concept ;
rdfs:label "Content Labeling Metadata"@en .
ngm:content-labelling a skos:Concept ;
rdfs:label "Content Labelling"@en .
ngm:content-language a skos:Concept ;
rdfs:label "Content Language"@en .
ngm:content-layer a owl:Class ;
rdfs:comment "The Content Layer is the stratum that holds the substantive information and media that a system manages and presents. It sits above the Data Layer that stores it and below the Presentation Layer that renders it. It contains documents, media assets, metadata, and the structures that organise meaning."@en ;
rdfs:label "Content Layer"@en ;
rdfs:subClassOf ngm:owl-thing ;
rdfs:subClassOf ngm:sc-content-and-assets ;
rdfs:subClassOf _:r5572 ;
skos:broader ngm:sc-content-and-assets ;
vc:bridgesTo ngm:content-management ;
vc:bridgesTo ngm:metadata ;
vc:enables ngm:application-layer ;
vc:enables ngm:presentation-layer ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:data-layer ;
vc:slug "content-layer" ;
vc:sourceDomain "metaverse" .
ngm:content-licensing a owl:Class ;
rdfs:comment "Content Licensing is the legal and commercial framework through which rights holders grant third parties permission to use, reproduce, distribute, or monetise creative or informational works under defined conditions, terms, and compensation structures. It governs the relationship between creators, intermediary platforms, and end consumers across media, software, data, and digital asset categories."@en ;
rdfs:label "Content Licensing"@en ;
rdfs:subClassOf ngm:digital-rights-management ;
rdfs:subClassOf _:r5573 ;
vc:enables ngm:royalty-distribution ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:content-creation ;
vc:relatedTo ngm:intellectual-property-rights-framework ;
vc:requires ngm:asset-management ;
vc:slug "content-licensing" ;
vc:sourceDomain "governance" ;
vc:uses ngm:digital-rights .
ngm:content-management a skos:Concept ;
rdfs:label "Content Management"@en .
ngm:content-management-system a owl:Class ;
rdfs:comment "A Content Management System (CMS) is software that lets users create, store, organise, edit and publish digital content without requiring direct manipulation of underlying code. It separates content from presentation, providing authoring interfaces, versioning, access control and workflow so that non-technical contributors can manage websites and applications. Modern variants include headless systems that expose content through APIs for delivery across many front ends, including spatial and immersive interfaces."@en ;
rdfs:label "Content Management System"@en ;
rdfs:subClassOf ngm:enterprise-software-platform ;
rdfs:subClassOf _:r5574 ;
rdfs:subClassOf _:r5575 ;
vc:bridgesTo ngm:cdn ;
vc:contrastsWith ngm:digital-asset-management ;
vc:dependsOn ngm:database ;
vc:enables ngm:cdn ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:digital-asset-management ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:digital-asset-management ;
vc:relatedTo ngm:metadata ;
vc:relatedTo ngm:search-engine ;
vc:requires ngm:database ;
vc:requires ngm:user-interface ;
vc:slug "content-management-system" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:metadata ;
vc:supports ngm:version-control ;
vc:uses ngm:api ;
vc:uses ngm:rest-api .
ngm:content-marketing a skos:Concept ;
rdfs:label "Content Marketing"@en .
ngm:content-moderation a owl:Class ;
rdfs:comment "Content Moderation is a systematic sociotechnical process for reviewing, classifying, filtering, and actioning user-generated and AI-generated media to enforce community standards, legal requirements, and platform policies, combining [[Machine Learning Models]], [[Natural Language Processing]], computer vision classifiers, and [[Human Moderators]] in hybrid pipelines that balance [[Harmful Content Prevention]] with [[Regulatory Compliance]] and freedom of expression, operating at scale under obligations imposed by frameworks including the [[EU AI Act]], the EU Digital Services Act, and the UK Online Safety Act."@en ;
rdfs:label "Content Moderation"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:ai-safety ;
rdfs:subClassOf ngm:platform-governance-system ;
rdfs:subClassOf ngm:responsible-ai ;
rdfs:subClassOf _:r5577 ;
rdfs:subClassOf _:r5578 ;
rdfs:subClassOf _:r5579 ;
rdfs:subClassOf _:r5580 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:ai-governance ;
vc:bridgesTo ngm:telecollaboration ;
vc:contrastsWith ngm:content-generation ;
vc:contrastsWith ngm:freedom-of-expression ;
vc:dependsOn ngm:bias-in-ai ;
vc:dependsOn ngm:decision-framework ;
vc:dependsOn ngm:human-moderators ;
vc:dependsOn ngm:machine-learning-discipline-models ;
vc:dependsOn ngm:reinforcement-learning-from-human-feedback ;
vc:dependsOn ngm:reporting-system ;
vc:enables ngm:ai-governance ;
vc:enables ngm:community-guidelines-enforcement ;
vc:enables ngm:harmful-content-prevention ;
vc:enables ngm:platform-governance-system ;
vc:enables ngm:regulatory-compliance ;
vc:enables ngm:safe-user-experience ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:appeal-process ;
vc:hasPart ngm:automated-filtering ;
vc:hasPart ngm:content-classification-system ;
vc:hasPart ngm:dsa-transparency-database ;
vc:hasPart ngm:human-review-workflow ;
vc:hasPart ngm:policy-enforcement-engine ;
vc:hasPart ngm:reporting-system ;
vc:hasPart ngm:reviewer-training-program ;
vc:implements ngm:deep-learning ;
vc:implements ngm:explainable-ai ;
vc:implements ngm:large-language-model ;
vc:implements ngm:natural-language-processing ;
vc:implements ngm:reinforcement-learning-from-human-feedback ;
vc:implements ngm:transformer-architecture ;
vc:isPartOf ngm:platform-governance-system ;
vc:isPartOf ngm:trust-and-safety-infrastructure ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:bias-in-ai ;
vc:relatedTo ngm:computer-vision ;
vc:relatedTo ngm:eu-ai-act-regulatory-instrument ;
vc:relatedTo ngm:explainable-ai ;
vc:relatedTo ngm:federated-learning ;
vc:relatedTo ngm:online-safety-act-2023 ;
vc:relatedTo ngm:reinforcement-learning-from-human-feedback ;
vc:relatedTo ngm:synthetic-media ;
vc:relatedTo ngm:telecollaboration ;
vc:requires ngm:community-standards ;
vc:requires ngm:content-analysis-tools ;
vc:requires ngm:decision-framework ;
vc:requires ngm:machine-learning-discipline-models ;
vc:requires ngm:moderation-policy ;
vc:requires ngm:natural-language-processing ;
vc:requires ngm:reviewer-training-program ;
vc:requires ngm:transformer-architecture ;
vc:slug "content-moderation" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:etsi-gr-arf-010 ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:online-safety-act-2023 ;
vc:supports ngm:ai-ethics ;
vc:supports ngm:ai-governance ;
vc:supports ngm:eu-ai-act-regulatory-instrument ;
vc:supports ngm:explainable-ai ;
vc:supports ngm:online-safety-act-2023 ;
vc:supports ngm:responsible-ai ;
vc:uses ngm:bias-in-ai ;
vc:uses ngm:content-analysis-tools ;
vc:uses ngm:dsa-transparency-database ;
vc:uses ngm:large-language-model ;
vc:uses ngm:synthetic-media ;
vc:uses ngm:watermarking-service .
ngm:content-moderation-standards a owl:Class ;
rdfs:comment "The policies, technologies, and practices used to monitor, review, and regulate user-generated content and behavior within virtual environments and metaverse platforms, addressing challenges unique to immersive spaces including harassment, hate speech, and harmful conduct that require both tradit..."@en ;
rdfs:label "Content Moderation Standards"@en ;
rdfs:subClassOf ngm:platform-governance ;
rdfs:subClassOf ngm:sc-governance-and-safety ;
rdfs:subClassOf _:r5576 ;
skos:broader ngm:sc-governance-and-safety ;
vc:bridgesTo ngm:telecollaboration ;
vc:enables ngm:community-trust ;
vc:enables ngm:harassment-prevention ;
vc:enables ngm:user-safety ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:platform-governance ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:ai-detection-systems ;
vc:requires ngm:human-moderators ;
vc:requires ngm:moderation-tools ;
vc:slug "content-moderation-standards" ;
vc:sourceDomain "spatial-computing" .
ngm:content-moderation-system a skos:Concept ;
rdfs:label "Content Moderation System"@en .
ngm:content-monetisation a owl:Class ;
rdfs:comment "Content monetisation is the set of mechanisms by which creators and rights-holders earn revenue from digital media, including advertising, subscriptions, micropayments, licensing and royalty distribution. Governance of these mechanisms covers rights attribution, usage tracking and the fair allocation of proceeds among contributors. Emerging models use programmable payments and on-chain royalties to automate compensation."@en ;
rdfs:label "Content Monetisation"@en ;
rdfs:subClassOf ngm:governance ;
rdfs:subClassOf _:r5581 ;
rdfs:subClassOf _:r5582 ;
vc:bridgesTo ngm:micropayment ;
vc:dependsOn ngm:digital-rights-management ;
vc:enables ngm:creator-economy ;
vc:enables ngm:creator-monetization ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:royalty-distribution ;
vc:isPartOf ngm:creator-economy ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:nft-marketplace ;
vc:relatedTo ngm:x402-and-l402-payment-protocols ;
vc:requires ngm:content-authentication ;
vc:requires ngm:intellectual-property-rights-framework ;
vc:slug "content-monetisation" ;
vc:sourceDomain "governance" ;
vc:supports ngm:creator-royalties ;
vc:supports ngm:royalty-distribution ;
vc:uses ngm:digital-rights-management ;
vc:uses ngm:micropayment .
ngm:content-negotiation a skos:Concept ;
rdfs:label "Content Negotiation"@en .
ngm:content-organisation a skos:Concept ;
rdfs:label "Content Organisation"@en .
ngm:content-personalisation a skos:Concept ;
rdfs:label "Content Personalisation"@en .
ngm:content-pipeline a owl:Class ;
rdfs:comment "A Content Pipeline is the end-to-end automated or semi-automated workflow that transforms raw creative assets—geometry, textures, audio, video, or data—from authoring tools into the optimised, platform-specific formats required by a runtime engine, distribution system, or media player. It encompasses ingestion, validation, processing, compression, and delivery stages with dependency tracking and incremental rebuild capabilities."@en ;
rdfs:label "Content Pipeline"@en ;
rdfs:subClassOf ngm:production-pipeline ;
rdfs:subClassOf _:r5583 ;
rdfs:subClassOf _:r5584 ;
rdfs:subClassOf _:r5585 ;
rdfs:subClassOf _:r5586 ;
rdfs:subClassOf _:r5587 ;
vc:bridgesTo ngm:cloud-computing ;
vc:bridgesTo ngm:generative-ai ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:enables ngm:game-engine ;
vc:enables ngm:real-time-rendering ;
vc:enables ngm:rendering-pipeline ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:asset-pipeline ;
vc:hasPart ngm:asset-validation ;
vc:hasPart ngm:data-ingestion ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:shader-compilation ;
vc:relatedTo ngm:usd ;
vc:relatedTo ngm:workflow-automation ;
vc:requires ngm:asset-management ;
vc:requires ngm:distributed-computing ;
vc:requires ngm:version-control ;
vc:slug "content-pipeline" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:content-creation ;
vc:supports ngm:digital-content-creation ;
vc:supports ngm:extended-reality ;
vc:uses ngm:asset-pipeline ;
vc:uses ngm:dependency-graph ;
vc:uses ngm:level-of-detail ;
vc:uses ngm:texture-compression .
ngm:content-portability a owl:Class ;
rdfs:comment "Content portability is the property that allows users to move their digital content and the associated rights between services, platforms, or virtual environments. It depends on standardised data formats and export mechanisms so that assets retain structure and meaning after transfer. It supports user ownership, reduces vendor lock-in, and is a stated goal of open data and open metaverse initiatives."@en ;
rdfs:label "Content Portability"@en ;
rdfs:subClassOf ngm:sc-standards-and-interop ;
skos:broader ngm:sc-standards-and-interop ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:asset-format-standards ;
vc:relatedTo ngm:data-format-standard ;
vc:slug "content-portability" ;
vc:sourceDomain "metaverse" .
ngm:content-preservation a skos:Concept ;
rdfs:label "Content Preservation"@en .
ngm:content-production-workflow a owl:Class ;
rdfs:comment "A structured sequence of stages and toolchain integrations through which raw creative inputs are transformed into publishable digital assets, covering pre-production, asset authoring, review, rendering, and distribution. In spatial computing contexts, such workflows incorporate 3D asset pipelines, real-time rendering checks, and version-controlled delivery to metaverse platforms."@en ;
rdfs:label "Content Production Workflow"@en ;
rdfs:subClassOf ngm:sc-content-and-assets ;
rdfs:subClassOf _:r5588 ;
rdfs:subClassOf _:r5589 ;
rdfs:subClassOf _:r5590 ;
rdfs:subClassOf _:r5591 ;
rdfs:subClassOf _:r5592 ;
rdfs:subClassOf _:r5593 ;
skos:broader ngm:sc-content-and-assets ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:dependsOn ngm:cdn ;
vc:dependsOn ngm:cloud-infrastructure ;
vc:enables ngm:content-distribution ;
vc:enables ngm:digital-content ;
vc:enables ngm:real-time-rendering ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:asset-management ;
vc:hasPart ngm:digital-content-creation ;
vc:hasPart ngm:rendering-pipeline ;
vc:hasPart ngm:version-control ;
vc:isPartOf ngm:media-production ;
vc:qualityScore "0.68"^^xsd:float ;
vc:relatedTo ngm:3-d-content-pipeline ;
vc:relatedTo ngm:metaverse-content-pipeline ;
vc:requires ngm:asset-pipeline ;
vc:requires ngm:digital-asset-management ;
vc:slug "content-production-workflow" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:extended-reality ;
vc:supports ngm:spatial-computing ;
vc:uses ngm:computer-vision ;
vc:uses ngm:generative-ai .
ngm:content-protection a owl:Class ;
rdfs:comment "Content Protection comprises technical and legal mechanisms that prevent unauthorised reproduction, distribution, or alteration of digital creative works. It includes digital rights management (DRM), encryption, access control, and blockchain-based provenance systems applied to media, software, and metaverse assets."@en ;
rdfs:label "Content Protection"@en ;
rdfs:subClassOf ngm:sc-governance-and-safety ;
rdfs:subClassOf _:r5594 ;
skos:broader ngm:sc-governance-and-safety ;
vc:bridgesTo ngm:blockchain ;
vc:enables ngm:digital-ownership ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:intellectual-property-rights-framework ;
vc:requires ngm:digital-rights ;
vc:slug "content-protection" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:access-control ;
vc:uses ngm:digital-rights-management ;
vc:uses ngm:encryption .
ngm:content-provenance a owl:Class ;
rdfs:comment "Content provenance is the verifiable, machine-readable record of the origin, authorship, creation context, and transformation history of a piece of digital media, enabling downstream consumers and automated systems to establish authenticity and detect unauthorised alteration. It relies on cryptographic signing, structured metadata schemas, and tamper-evident manifests attached to or bound with the asset at point of creation. As generative AI proliferates synthetic media, content provenance serves as the principal technical mechanism for distinguishing camera-captured or human-authored material from algorithmically generated content. Governance frameworks and regulatory instruments increasingly mandate provenance disclosure as a baseline trust control for media distributed at scale."@en ;
rdfs:label "Content Provenance"@en ;
rdfs:subClassOf ngm:provenance ;
rdfs:subClassOf _:r5595 ;
rdfs:subClassOf _:r5596 ;
rdfs:subClassOf _:r5597 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:decentralised-identity ;
vc:bridgesTo ngm:generative-ai ;
vc:contrastsWith ngm:deepfakes ;
vc:contrastsWith ngm:synthetic-media ;
vc:enables ngm:disinformation-detection ;
vc:enables ngm:media-authentication ;
vc:enables ngm:trust-signals ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:data-lineage ;
vc:relatedTo ngm:information-integrity ;
vc:relatedTo ngm:watermarking-service ;
vc:requires ngm:cryptographic-infrastructure ;
vc:requires ngm:cryptography ;
vc:requires ngm:digital-signatures ;
vc:slug "content-provenance" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:c2-pa ;
vc:standardizedBy ngm:iptc-photo-metadata ;
vc:supports ngm:ai-governance ;
vc:supports ngm:content-moderation ;
vc:supports ngm:digital-rights-management ;
vc:uses ngm:hashing ;
vc:uses ngm:metadata-standards ;
vc:uses ngm:verifiable-credentials .
ngm:content-quality a skos:Concept ;
rdfs:label "Content Quality"@en .
ngm:content-ranking a skos:Concept ;
rdfs:label "Content Ranking"@en .
ngm:content-recommendation a skos:Concept ;
rdfs:label "Content Recommendation"@en .
ngm:content-removal a skos:Concept ;
rdfs:label "Content Removal"@en .
ngm:content-repository a owl:Class ;
rdfs:comment "A structured store for digital content and its metadata that provides hierarchical or graph organisation, typed properties, versioning, access control, search, and observation APIs, decoupling how content is stored from the applications that author and deliver it — the persistence backbone of content management systems, digital curation platforms, and adaptive learning systems that assemble instruction from tagged learning objects."@en ;
rdfs:label "Content Repository"@en ;
rdfs:subClassOf ngm:data-storage ;
vc:enables ngm:adaptive-learning ;
vc:enables ngm:digital-asset-management ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:content-management-system ;
vc:isPartOf ngm:digital-curation-platform ;
vc:qualityScore "0.8"^^xsd:float ;
vc:slug "content-repository" ;
vc:sourceDomain "data" ;
vc:uses ngm:metadata ;
vc:uses ngm:version-control .
ngm:content-reuse a skos:Concept ;
rdfs:label "Content Reuse"@en .
ngm:content-risk-assessment a skos:Concept ;
rdfs:label "Content Risk Assessment"@en .
ngm:content-storage a skos:Concept ;
rdfs:label "Content Storage"@en .
ngm:content-strategy a skos:Concept ;
rdfs:label "Content Strategy"@en .
ngm:content-transparency a skos:Concept ;
rdfs:label "Content Transparency"@en .
ngm:content-type-negotiation a skos:Concept ;
rdfs:label "Content Type Negotiation"@en .
ngm:content-verification a skos:Concept ;
rdfs:label "Content Verification"@en .
ngm:contentmoderation a skos:Concept ;
rdfs:label "Contentmoderation"@en .
ngm:contestability a owl:Class ;
rdfs:comment "Contestability is the property of a system or decision-making process that allows an affected party to challenge, question or seek review of an automated decision. It requires that the basis of a decision be sufficiently transparent to be examined, and that a mechanism exists for raising and resolving disputes. Contestability is a design and governance goal in AI accountability frameworks, complementing explainability and transparency by ensuring outcomes are not merely explained but also revisable."@en ;
rdfs:label "Contestability"@en ;
rdfs:subClassOf ngm:accountability ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.65"^^xsd:float ;
vc:relatedTo ngm:accountability ;
vc:relatedTo ngm:transparency ;
vc:slug "contestability" ;
vc:sourceDomain "artificial-intelligence" .
ngm:contestability-ai-0043 a skos:Concept ;
rdfs:label "Contestability AI 0043"@en .
ngm:context-accumulation a skos:Concept ;
rdfs:label "Context Accumulation"@en .
ngm:context-analysis-module a skos:Concept ;
rdfs:label "Context Analysis Module"@en .
ngm:context-aware-ar a skos:Concept ;
rdfs:label "Context Aware AR"@en .
ngm:context-aware-computing a owl:Class ;
rdfs:comment "Context Aware Computing is a paradigm in which systems automatically adapt their behaviour based on contextual signals such as the user's location, activity, device state, social environment, and temporal cues. In spatial computing and XR applications, context awareness allows virtual overlays and services to respond intelligently to physical surroundings, enabling location-sensitive AR, adaptive user interfaces, and personalised immersive experiences."@en ;
rdfs:label "Context Aware Computing"@en ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf _:r5600 ;
rdfs:subClassOf _:r5601 ;
skos:broader ngm:sc-platform-and-environment ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:scene-understanding ;
vc:enables ngm:augmented-reality ;
vc:enables ngm:immersive-experience ;
vc:enables ngm:user-experience ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:internet-of-things ;
vc:requires ngm:sensor-fusion ;
vc:slug "context-aware-computing" ;
vc:sourceDomain "spatial-computing" .
ngm:context-aware-response a owl:Class ;
rdfs:comment "An AI-driven capability in metaverse and virtual environments that enables systems to generate dynamic, personalized responses based on real-time understanding of user context, including location, activity, preferences, social environment, and interaction history, utilizing large language models ..."@en ;
rdfs:label "Context Aware Response"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf _:r5602 ;
rdfs:subClassOf _:r5603 ;
rdfs:subClassOf _:r5604 ;
skos:broader ngm:artificial-intelligence ;
skos:broader ngm:sc-platform-and-environment ;
vc:bridgesTo ngm:computer-vision ;
vc:enables ngm:adaptive-ux ;
vc:enables ngm:dynamic-content ;
vc:enables ngm:personalized-interaction ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:context-awareness-system ;
vc:requires ngm:machine-learning-discipline ;
vc:requires ngm:natural-language-processing ;
vc:slug "context-aware-response" ;
vc:sourceDomain "spatial-computing" .
ngm:context-awareness a owl:Class ;
rdfs:comment "The capability of computing systems to sense, interpret, and respond to environmental conditions, user state, situational factors, and contextual information to dynamically adapt behavior and deliver personalized experiences."@en ;
rdfs:label "Context Awareness"@en ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf _:r5609 ;
rdfs:subClassOf _:r5610 ;
rdfs:subClassOf _:r5611 ;
rdfs:subClassOf _:r5612 ;
rdfs:subClassOf _:r5613 ;
skos:broader ngm:sc-platform-and-environment ;
vc:bridgesTo ngm:sensor-input ;
vc:dependsOn ngm:edge-computing ;
vc:dependsOn ngm:io-t-infrastructure ;
vc:dependsOn ngm:real-time-analytics ;
vc:dependsOn ngm:semantic-reasoning-engine ;
vc:enables ngm:adaptive-interfaces ;
vc:enables ngm:ambient-computing ;
vc:enables ngm:personalized-experiences ;
vc:enables ngm:proactive-services ;
vc:enables ngm:smart-environments ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:behavioral-adaptation ;
vc:hasPart ngm:context-modeling ;
vc:hasPart ngm:environmental-sensing ;
vc:hasPart ngm:situational-inference ;
vc:hasPart ngm:user-state-detection ;
vc:isPartOf ngm:adaptive-computing ;
vc:isPartOf ngm:intelligent-systems ;
vc:isPartOf ngm:pervasive-computing ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:data-processing ;
vc:requires ngm:decision-logic ;
vc:requires ngm:knowledge-representation ;
vc:requires ngm:machine-learning-discipline ;
vc:requires ngm:sensor-fusion ;
vc:slug "context-awareness" ;
vc:sourceDomain "spatial-computing" .
ngm:context-awareness-system a owl:Class ;
rdfs:comment "A technology framework that captures, processes, and interprets contextual information about users and their environments using IoT sensors, location tracking, and AI analytics to enable adaptive services, personalized experiences, and intelligent decision-making in virtual and physical spaces."@en ;
rdfs:label "Context Awareness System"@en ;
rdfs:subClassOf ngm:intelligent-systems ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf _:r5605 ;
rdfs:subClassOf _:r5606 ;
rdfs:subClassOf _:r5607 ;
rdfs:subClassOf _:r5608 ;
skos:broader ngm:sc-platform-and-environment ;
vc:bridgesTo ngm:sensor-input ;
vc:enables ngm:adaptive-services ;
vc:enables ngm:location-based-services ;
vc:enables ngm:situational-awareness ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:data-analytics ;
vc:requires ngm:io-t-sensors ;
vc:requires ngm:network-infrastructure ;
vc:slug "context-awareness-system" ;
vc:sourceDomain "spatial-computing" .
ngm:context-compaction a skos:Concept ;
rdfs:label "Context Compaction"@en .
ngm:context-compression a skos:Concept ;
rdfs:label "Context Compression"@en .
ngm:context-document a skos:Concept ;
rdfs:label "Context Document"@en .
ngm:context-engineering a owl:Class ;
rdfs:comment "Context Engineering is the systems-level discipline of designing, curating, compressing, and orchestrating the information delivered into a Large Language Model's context window across a multi-step agentic loop, popularised between mid-2024 and mid-2025 by Walden Yan (Cognition AI's \"Don't Build ..."@en ;
rdfs:label "Context Engineering"@en ;
rdfs:subClassOf ngm:agent-engineering ;
rdfs:subClassOf ngm:ai-agent-system ;
rdfs:subClassOf ngm:ai-engineering ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:llm-application-engineering ;
rdfs:subClassOf ngm:systems-engineering-for-ai ;
rdfs:subClassOf _:r5614 ;
rdfs:subClassOf _:r5615 ;
rdfs:subClassOf _:r5616 ;
rdfs:subClassOf _:r5617 ;
rdfs:subClassOf _:r5618 ;
rdfs:subClassOf _:r5619 ;
rdfs:subClassOf _:r5620 ;
rdfs:subClassOf _:r5621 ;
rdfs:subClassOf _:r5622 ;
rdfs:subClassOf _:r5623 ;
rdfs:subClassOf _:r5624 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:ai-infrastructure ;
vc:contrastsWith ngm:fine-tuning ;
vc:contrastsWith ngm:model-pre-training ;
vc:contrastsWith ngm:prompt-engineering ;
vc:contrastsWith ngm:retrieval-engineering ;
vc:dependsOn ngm:attention-mechanism ;
vc:dependsOn ngm:information-retrieval ;
vc:dependsOn ngm:prompt-caching ;
vc:dependsOn ngm:tokenization ;
vc:dependsOn ngm:transformer-architecture ;
vc:dependsOn ngm:vector-search ;
vc:enables ngm:cost-efficient-inference ;
vc:enables ngm:llm-agents ;
vc:enables ngm:long-horizon-planning ;
vc:enables ngm:multi-turn-coherence ;
vc:enables ngm:persistent-ai-assistants ;
vc:enables ngm:tool-use ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:context-compaction ;
vc:hasPart ngm:few-shot-examples ;
vc:hasPart ngm:instruction-hierarchy ;
vc:hasPart ngm:persistent-memory ;
vc:hasPart ngm:prefix-cache ;
vc:hasPart ngm:retrieval-augmented-generation ;
vc:hasPart ngm:scratchpad ;
vc:hasPart ngm:system-prompt ;
vc:hasPart ngm:tool-schema ;
vc:implements ngm:context-compression ;
vc:implements ngm:hierarchical-retrieval ;
vc:implements ngm:memory-block-architecture ;
vc:implements ngm:recursive-summarisation ;
vc:implements ngm:rolling-memory-window ;
vc:implements ngm:structured-output-constraints ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:long-context-modelling ;
vc:relatedTo ngm:memory-architecture ;
vc:relatedTo ngm:prompt-injection ;
vc:relatedTo ngm:retrieval-augmented-generation ;
vc:requires ngm:context-window ;
vc:requires ngm:evaluation-harness ;
vc:requires ngm:large-language-model ;
vc:requires ngm:large-language-models ;
vc:requires ngm:memory-store ;
vc:requires ngm:retrieval-system ;
vc:requires ngm:tokenizer ;
vc:slug "context-engineering" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:anthropic-prompt-engineering-guide ;
vc:standardizedBy ngm:claude-code-claude-md-convention ;
vc:standardizedBy ngm:lang-graph-state-schema ;
vc:standardizedBy ngm:langgraph-state-schema ;
vc:standardizedBy ngm:model-context-protocol ;
vc:standardizedBy ngm:openai-instruction-hierarchy-spec ;
vc:standardizedBy ngm:openai-research-organisation-instruction-hierarchy-spec ;
vc:supports ngm:browser-agents ;
vc:supports ngm:coding-agents ;
vc:supports ngm:customer-service-agents ;
vc:supports ngm:research-agents ;
vc:supports ngm:retrieval-augmented-generation ;
vc:supports ngm:workflow-automation ;
vc:uses ngm:function-calling ;
vc:uses ngm:json-data-interchange-format-schema ;
vc:uses ngm:prompt-caching ;
vc:uses ngm:reranking ;
vc:uses ngm:vector-embedding ;
vc:uses ngm:vector-embeddings ;
vc:uses ngm:xml-tags .
ngm:context-free-grammar a skos:Concept ;
rdfs:label "Context Free Grammar"@en .
ngm:context-graph a owl:Class ;
rdfs:comment "The assembly layer at the top of the knowledge stack. A context graph consumes the layers beneath it — a formal ontology, a populated knowledge graph, and operational sources such as documents, chat history and tool outputs — to assemble the working set of information an AI agent needs for its next response. It does not compete with the ontology or the knowledge graph; it selects from them under a token budget. In the DreamLab mesh this layer is implemented by the Ontology Loom, which retrieves a budget-clamped structured scaffold from the reasoned ontology and injects it into model context at query time."@en ;
rdfs:label "Context Graph"@en ;
rdfs:subClassOf ngm:knowledge-representation ;
rdfs:subClassOf _:r5625 ;
rdfs:subClassOf _:r5626 ;
rdfs:subClassOf _:r5627 ;
vc:enables ngm:retrieval-augmented-generation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:ontology-loom ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:agent-memory ;
vc:requires ngm:knowledge-graph ;
vc:requires ngm:ontology ;
vc:slug "context-graph" ;
vc:sourceDomain "artificial-intelligence" .
ngm:context-injection a skos:Concept ;
rdfs:label "Context Injection"@en .
ngm:context-length a skos:Concept ;
rdfs:label "Context Length"@en .
ngm:context-management a owl:Class ;
rdfs:comment "Context management is the set of techniques for assembling, prioritising, compressing, and maintaining the information supplied to a language model within its bounded context window across a task or conversation. It governs what prompts, retrieved documents, prior turns, tool outputs, and state are placed in context, in what order, and at what fidelity, so that the model has the most relevant evidence without exceeding token limits. Effective context management is central to retrieval-augmented generation, long-running agents, and conversational systems, where it directly shapes coherence, accuracy, and cost."@en ;
rdfs:label "Context Management"@en ;
rdfs:subClassOf ngm:large-language-model ;
rdfs:subClassOf ngm:prompt-engineering ;
rdfs:subClassOf _:r5628 ;
rdfs:subClassOf _:r5629 ;
rdfs:subClassOf _:r5630 ;
vc:dependsOn ngm:attention-mechanism ;
vc:dependsOn ngm:context-window ;
vc:enables ngm:autonomous-agent ;
vc:enables ngm:conversational-ai ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:context-window ;
vc:hasPart ngm:memory-management ;
vc:implements ngm:retrieval-augmented-generation ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:memory-management ;
vc:relatedTo ngm:prompt-engineering ;
vc:relatedTo ngm:state-management ;
vc:requires ngm:token ;
vc:slug "context-management" ;
vc:sourceDomain "ai" ;
vc:supports ngm:dialogue-system ;
vc:supports ngm:session-management ;
vc:uses ngm:knowledge-retrieval ;
vc:uses ngm:prompt-engineering .
ngm:context-modeling a skos:Concept ;
rdfs:label "Context Modeling"@en .
ngm:context-pinning a skos:Concept ;
rdfs:label "Context Pinning"@en .
ngm:context-region a skos:Concept ;
rdfs:label "Context Region"@en .
ngm:context-window a owl:Class ;
rdfs:comment "The maximum sequence length that a language model can process in a single forward pass, measured in tokens; it determines how much prior context the model can attend to during generation or understanding tasks and directly bounds memory, coherence, and long-range reasoning capabilities."@en ;
rdfs:label "Context Window"@en ;
rdfs:subClassOf ngm:ai-model-architecture ;
rdfs:subClassOf _:r5631 ;
rdfs:subClassOf _:r5632 ;
rdfs:subClassOf _:r5633 ;
rdfs:subClassOf _:r5634 ;
rdfs:subClassOf _:r5635 ;
skos:broader ngm:ai-model-architecture ;
vc:bridgesTo ngm:autonomous-robot ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:virtual-environment ;
vc:contrastsWith ngm:external-memory ;
vc:contrastsWith ngm:recurrent-neural-network ;
vc:dependsOn ngm:floating-point-arithmetic ;
vc:dependsOn ngm:gpu-memory ;
vc:enables ngm:agentic-ai ;
vc:enables ngm:few-shot-prompting ;
vc:enables ngm:in-context-learning ;
vc:enables ngm:long-document-summarisation ;
vc:enables ngm:retrieval-augmented-generation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:positional-encoding ;
vc:hasPart ngm:token ;
vc:isPartOf ngm:large-language-models ;
vc:isPartOf ngm:transformer-architecture ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:context-engineering ;
vc:relatedTo ngm:hyperparameter ;
vc:relatedTo ngm:language-modeling ;
vc:relatedTo ngm:lost-in-the-middle-effect ;
vc:relatedTo ngm:model-context-protocol ;
vc:relatedTo ngm:prompt-engineering ;
vc:requires ngm:attention-mechanism ;
vc:requires ngm:key-value-cache ;
vc:requires ngm:neural-network-text-tokenisation ;
vc:slug "context-window" ;
vc:sourceDomain "artificial-intelligence" .
ngm:context-window-management a owl:Class ;
rdfs:comment "The set of architectural and algorithmic techniques used to extend the effective memory of large language models beyond their native token limits, enabling coherent processing of long-horizon inputs."@en ;
rdfs:label "Context Window Management"@en ;
rdfs:subClassOf ngm:gpt ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:attention-mechanism ;
vc:relatedTo ngm:gpt ;
vc:relatedTo ngm:transformer-architecture ;
vc:slug "context-window-management" ;
vc:sourceDomain "artificial-intelligence" .
ngm:contextmanagement a skos:Concept ;
rdfs:label "Contextmanagement"@en .
ngm:contextual-anomaly-detection a skos:Concept ;
rdfs:label "Contextual Anomaly Detection"@en .
ngm:contextual-bandit a skos:Concept ;
rdfs:label "Contextual Bandit"@en .
ngm:contextual-bandits a skos:Concept ;
rdfs:label "Contextual Bandits"@en .
ngm:contextual-embedding a owl:Class ;
rdfs:comment "A contextual embedding is a vector representation of a token or span whose value depends on the surrounding context in which it appears, in contrast to static embeddings that assign a fixed vector to each word regardless of usage. Contextual embeddings are produced by encoder models such as BERT, typically via masked language modelling objectives, and allow the same word to be represented differently depending on its sense in a given sentence. They substantially improved performance on downstream natural language understanding tasks by resolving ambiguity that static embeddings could not capture."@en ;
rdfs:label "Contextual Embedding"@en ;
rdfs:subClassOf ngm:embedding ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:embedding ;
vc:qualityScore "0.55"^^xsd:float ;
vc:relatedTo ngm:encoder ;
vc:relatedTo ngm:masked-language-modelling ;
vc:slug "contextual-embedding" ;
vc:sourceDomain "machine-learning" .
ngm:contextual-information a skos:Concept ;
rdfs:label "Contextual Information"@en .
ngm:contextual-information-display a skos:Concept ;
rdfs:label "Contextual Information Display"@en .
ngm:contextual-information-overlay a skos:Concept ;
rdfs:label "Contextual Information Overlay"@en .
ngm:contextual-integrity a skos:Concept ;
rdfs:label "Contextual Integrity"@en .
ngm:contextual-retrieval a skos:Concept ;
rdfs:label "Contextual Retrieval"@en .
ngm:continual-learning a owl:Class ;
rdfs:comment "Continual Learning is a machine learning paradigm in which a model sequentially learns from a non-stationary stream of tasks or data distributions while retaining competence on previously acquired knowledge. It directly confronts catastrophic forgetting — the tendency of neural networks to overwrite earlier representations when updated on new training distributions. Core strategies span regularisation-based protection of critical parameters, rehearsal-based replay of past exemplars or synthetic surrogates, and architectural methods that expand or isolate network capacity per task. The field spans both supervised and reinforcement learning settings and is fundamental wherever data arrives incrementally and retraining from scratch is computationally or commercially infeasible."@en ;
rdfs:label "Continual Learning"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf ngm:online-learning ;
rdfs:subClassOf ngm:transfer-learning ;
rdfs:subClassOf _:r5636 ;
rdfs:subClassOf _:r5637 ;
rdfs:subClassOf _:r5638 ;
rdfs:subClassOf _:r5639 ;
rdfs:subClassOf _:r5640 ;
rdfs:subClassOf _:r5641 ;
rdfs:subClassOf _:r5642 ;
rdfs:subClassOf _:r5643 ;
rdfs:subClassOf _:r5644 ;
rdfs:subClassOf _:r5645 ;
rdfs:subClassOf _:r5646 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:edge-computing ;
vc:bridgesTo ngm:federated-learning ;
vc:bridgesTo ngm:machine-unlearning ;
vc:bridgesTo ngm:robotics ;
vc:contrastsWith ngm:batch-learning ;
vc:contrastsWith ngm:catastrophic-forgetting ;
vc:contrastsWith ngm:multi-task-learning ;
vc:dependsOn ngm:attention-mechanism ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:fisher-information ;
vc:dependsOn ngm:gradient-descent ;
vc:dependsOn ngm:loss-function ;
vc:dependsOn ngm:neural-network ;
vc:dependsOn ngm:representation-learning ;
vc:enables ngm:autonomous-agent ;
vc:enables ngm:curriculum-learning ;
vc:enables ngm:domain-adaptation ;
vc:enables ngm:federated-learning ;
vc:enables ngm:few-shot-learning ;
vc:enables ngm:machine-unlearning ;
vc:enables ngm:transfer-learning ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:class-incremental-learning ;
vc:hasPart ngm:domain-adaptation ;
vc:hasPart ngm:elastic-weight-consolidation ;
vc:hasPart ngm:experience-replay ;
vc:hasPart ngm:knowledge-distillation ;
vc:hasPart ngm:memory-replay ;
vc:hasPart ngm:progressive-neural-networks ;
vc:hasPart ngm:task-incremental-learning ;
vc:qualityScore "0.91"^^xsd:float ;
vc:relatedTo ngm:computer-vision ;
vc:relatedTo ngm:curriculum-learning ;
vc:relatedTo ngm:domain-adaptation ;
vc:relatedTo ngm:federated-learning ;
vc:relatedTo ngm:foundation-model ;
vc:relatedTo ngm:machine-unlearning ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:neural-plasticity ;
vc:requires ngm:attention-mechanism ;
vc:requires ngm:deep-learning ;
vc:requires ngm:gradient-descent ;
vc:requires ngm:loss-function ;
vc:requires ngm:neural-network ;
vc:requires ngm:online-learning ;
vc:requires ngm:regularisation ;
vc:requires ngm:representation-learning ;
vc:slug "continual-learning" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:continualai ;
vc:supports ngm:computer-vision ;
vc:supports ngm:edge-computing ;
vc:supports ngm:foundation-model ;
vc:supports ngm:large-language-models ;
vc:supports ngm:natural-language-processing ;
vc:supports ngm:reinforcement-learning ;
vc:supports ngm:robotics ;
vc:uses ngm:fisher-information ;
vc:uses ngm:generative-adversarial-networks ;
vc:uses ngm:knowledge-distillation ;
vc:uses ngm:lo-ra ;
vc:uses ngm:meta-learning ;
vc:uses ngm:parameter-efficient-fine-tuning ;
vc:uses ngm:variational-autoencoders .
ngm:continualai a skos:Concept ;
rdfs:label "Continualai"@en .
ngm:continued-operation a skos:Concept ;
rdfs:label "Continued Operation"@en .
ngm:continued-pre-training a owl:Class ;
rdfs:comment "An intermediate training phase in which a pre-trained foundation model undergoes additional unsupervised pre-training on domain-specific or task-relevant corpora before supervised fine-tuning. Continued pre-training bridges general-purpose representations and domain expertise, using the same self-supervised objectives as initial pre-training whilst employing reduced learning rates and selective data to mitigate catastrophic forgetting of general capabilities."@en ;
rdfs:label "Continued Pre Training"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf _:r5647 ;
rdfs:subClassOf _:r5648 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:computer-vision ;
vc:contrastsWith ngm:full-fine-tuning ;
vc:enables ngm:domain-adaptation ;
vc:enables ngm:fine-tuning ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:overfitting ;
vc:relatedTo ngm:transfer-learning ;
vc:requires ngm:deep-learning ;
vc:requires ngm:large-language-models ;
vc:slug "continued-pre-training" ;
vc:sourceDomain "artificial-intelligence" .
ngm:continuous-action a skos:Concept ;
rdfs:label "Continuous Action"@en .
ngm:continuous-ai-strategy a owl:Class ;
rdfs:comment "An iterative approach to AI planning where strategies and recommendations are dynamically updated in response to evolving capabilities and market conditions."@en ;
rdfs:label "Continuous AI Strategy"@en ;
rdfs:subClassOf ngm:enterprise-ai ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-maturity-assessment ;
vc:relatedTo ngm:enterprise-ai ;
vc:slug "continuous-ai-strategy" ;
vc:sourceDomain "governance" .
ngm:continuous-assurance a skos:Concept ;
rdfs:label "Continuous Assurance"@en .
ngm:continuous-authentication a owl:Class ;
rdfs:comment "Continuous authentication is an approach to identity verification that repeatedly re-validates a user's identity throughout a session, rather than relying solely on a single login event. It draws on signals such as behavioural biometrics, device posture, and network context to detect anomalies that might indicate session hijacking or credential theft. It is increasingly used alongside biometric authentication and identity providers to reduce the window of exposure after initial login."@en ;
rdfs:label "Continuous Authentication"@en ;
rdfs:subClassOf ngm:authentication ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "continuous-authentication" ;
vc:sourceDomain "security" .
ngm:continuous-batching a owl:Class ;
rdfs:comment "Continuous batching is a large language model serving technique in which the inference scheduler admits and evicts requests at the granularity of individual decoding steps rather than running a whole batch to completion before starting the next. As soon as any sequence in the batch finishes generating, its slot is freed and a queued request takes its place, keeping the GPU saturated and dramatically improving throughput and latency under heterogeneous request lengths. It is a defining feature of modern inference engines such as vLLM and is typically combined with paged attention and a shared key-value cache."@en ;
rdfs:label "Continuous Batching"@en ;
rdfs:subClassOf ngm:inference-optimisation ;
rdfs:subClassOf ngm:model-serving ;
rdfs:subClassOf _:r5649 ;
rdfs:subClassOf _:r5650 ;
rdfs:subClassOf _:r5651 ;
rdfs:subClassOf _:r5652 ;
rdfs:subClassOf _:r5653 ;
rdfs:subClassOf _:r5654 ;
rdfs:subClassOf _:r5655 ;
vc:contrastsWith ngm:batch-processing ;
vc:contrastsWith ngm:offline-inference ;
vc:contrastsWith ngm:static-batching ;
vc:contrastsWith ngm:triton-inference-server ;
vc:dependsOn ngm:attention-mechanism ;
vc:dependsOn ngm:autoregressive-decoding ;
vc:dependsOn ngm:gpu-compute ;
vc:dependsOn ngm:kv-cache ;
vc:dependsOn ngm:paged-attention ;
vc:enables ngm:cost-optimisation ;
vc:enables ngm:gpu-utilisation ;
vc:enables ngm:inference-serving ;
vc:enables ngm:large-language-models ;
vc:enables ngm:multi-tenant-inference ;
vc:enables ngm:retrieval-augmented-generation ;
vc:enables ngm:throughput ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:admission-control ;
vc:hasPart ngm:chunked-prefill ;
vc:hasPart ngm:kv-cache ;
vc:hasPart ngm:paged-attention ;
vc:hasPart ngm:request-scheduling ;
vc:hasPart ngm:slot-management ;
vc:implements ngm:inference-optimisation ;
vc:implements ngm:memory-management ;
vc:implements ngm:planning-and-scheduling ;
vc:isPartOf ngm:inference-serving ;
vc:isPartOf ngm:model-serving ;
vc:qualityScore "0.91"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:data-parallelism ;
vc:relatedTo ngm:distributed-systems ;
vc:relatedTo ngm:federated-learning ;
vc:relatedTo ngm:flash-attention ;
vc:relatedTo ngm:knowledge-graph ;
vc:relatedTo ngm:mixture-of-experts ;
vc:relatedTo ngm:model-optimisation-and-performance ;
vc:relatedTo ngm:pipeline-parallelism ;
vc:relatedTo ngm:prefill-decode-disaggregation ;
vc:relatedTo ngm:quantisation ;
vc:relatedTo ngm:radixattention ;
vc:relatedTo ngm:reinforcement-learning ;
vc:relatedTo ngm:retrieval-augmented-generation ;
vc:relatedTo ngm:speculative-decoding ;
vc:relatedTo ngm:tensor-parallelism ;
vc:relatedTo ngm:vertex-ai ;
vc:requires ngm:autoregressive-decoding ;
vc:requires ngm:deep-learning ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:gpu-memory ;
vc:requires ngm:transformer-architecture ;
vc:slug "continuous-batching" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:v-llm ;
vc:supports ngm:natural-language-processing ;
vc:supports ngm:nvidia-dynamo ;
vc:supports ngm:sglang ;
vc:supports ngm:tensorrt-llm ;
vc:supports ngm:token-generation ;
vc:supports ngm:v-llm ;
vc:uses ngm:autoregressive-decoding ;
vc:uses ngm:cuda ;
vc:uses ngm:flash-attention ;
vc:uses ngm:gpu ;
vc:uses ngm:kv-cache ;
vc:uses ngm:memory-management ;
vc:uses ngm:paged-attention ;
vc:uses ngm:pipeline-parallelism ;
vc:uses ngm:quantisation ;
vc:uses ngm:tensor-parallelism .
ngm:continuous-care-navigator a owl:Class ;
rdfs:comment "A healthcare role that leverages AI-enabled systems to provide ongoing, personalized coordination and support for patients, bridging the gap between clinical interventions and daily health management."@en ;
rdfs:label "Continuous Care Navigator"@en ;
rdfs:subClassOf ngm:healthcare ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-enabled-healthcare ;
vc:relatedTo ngm:continuous-preventative-healthcare ;
vc:relatedTo ngm:decision-support ;
vc:relatedTo ngm:healthcare-employment ;
vc:slug "continuous-care-navigator" ;
vc:sourceDomain "governance" .
ngm:continuous-collision-detection a skos:Concept ;
rdfs:label "Continuous Collision Detection"@en .
ngm:continuous-control a skos:Concept ;
rdfs:label "Continuous Control"@en .
ngm:continuous-controls-monitoring a skos:Concept ;
rdfs:label "Continuous Controls Monitoring"@en .
ngm:continuous-delivery a owl:Class ;
rdfs:comment "Continuous Delivery is a software engineering discipline in which code changes are automatically built, tested and prepared for release to production so that the software is always in a deployable state. It extends continuous integration by adding automated release pipelines, environment promotion and deployment gates, allowing teams to ship changes rapidly, reliably and with low risk. Releases become routine, low-ceremony events rather than infrequent high-stakes operations."@en ;
rdfs:label "Continuous Delivery"@en ;
rdfs:subClassOf ngm:devops ;
rdfs:subClassOf _:r5656 ;
rdfs:subClassOf _:r5657 ;
vc:dependsOn ngm:monitoring ;
vc:dependsOn ngm:testing ;
vc:enables ngm:cloud-native ;
vc:enables ngm:microservices ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:devops ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:infrastructure ;
vc:relatedTo ngm:software-engineering ;
vc:requires ngm:continuous-integration ;
vc:requires ngm:version-control ;
vc:slug "continuous-delivery" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:observability ;
vc:supports ngm:reliability-engineering ;
vc:supports ngm:site-reliability-engineering ;
vc:uses ngm:automation ;
vc:uses ngm:git ;
vc:uses ngm:kubernetes .
ngm:continuous-deployment a owl:Class ;
rdfs:comment "Continuous Deployment is a software release practice in which every code change that passes the automated pipeline is released to production automatically, without manual approval gates. It extends continuous delivery by removing the final human decision step, so that a successful build, test, and integration sequence results directly in a live deployment. The practice depends on comprehensive automated testing, robust monitoring, and rapid rollback mechanisms to maintain reliability while sustaining a high deployment cadence."@en ;
rdfs:label "Continuous Deployment"@en ;
rdfs:subClassOf ngm:devops ;
rdfs:subClassOf _:r5658 ;
rdfs:subClassOf _:r5659 ;
rdfs:subClassOf _:r5660 ;
rdfs:subClassOf _:r5661 ;
rdfs:subClassOf _:r5662 ;
vc:contrastsWith ngm:continuous-delivery ;
vc:dependsOn ngm:continuous-delivery ;
vc:enables ngm:feedback-loop ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:automated-testing ;
vc:hasPart ngm:monitoring ;
vc:isPartOf ngm:devops ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:service-mesh ;
vc:relatedTo ngm:software-engineering ;
vc:requires ngm:continuous-integration ;
vc:requires ngm:quality-assurance ;
vc:requires ngm:version-control ;
vc:slug "continuous-deployment" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:site-reliability-engineering ;
vc:uses ngm:cloud-computing ;
vc:uses ngm:kubernetes ;
vc:uses ngm:microservices .
ngm:continuous-discovery a skos:Concept ;
rdfs:label "Continuous Discovery"@en .
ngm:continuous-improvement a owl:Class ;
rdfs:comment "Continuous improvement is an iterative organisational and engineering philosophy in which processes, products, and systems are systematically and incrementally refined over time through structured cycles of measurement, analysis, experimentation, and implementation, rather than through large-scale periodic overhauls. Rooted in Japanese manufacturing philosophy (kaizen), it was formalised in quality management frameworks including the Plan-Do-Check-Act cycle, ISO 9001, and Lean methodologies, and has since been adopted throughout software engineering via DevOps, agile retrospectives, and MLOps pipelines. The practice relies on feedback loops that surface inefficiencies, defects, or opportunities close to their point of origin, enabling rapid corrective action and cumulative quality gains."@en ;
rdfs:label "continuous improvement"@en ;
rdfs:subClassOf ngm:software-development-process ;
vc:enables ngm:mlops ;
vc:enables ngm:software-development ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:feedback-loop ;
vc:relatedTo ngm:monitoring-system ;
vc:relatedTo ngm:performance-metrics ;
vc:relatedTo ngm:quality-assurance ;
vc:slug "continuous-improvement" ;
vc:sourceDomain "ai" ;
vc:supports ngm:ai-deployment ;
vc:uses ngm:real-time-monitoring .
ngm:continuous-integration a owl:Class ;
rdfs:comment "Continuous Integration (CI) is a software engineering practice in which developers frequently merge code changes into a shared repository — typically multiple times per day — triggering automated build and test pipelines that provide rapid feedback on integration correctness. CI reduces the cost and risk of integration by detecting conflicts, regressions, and build failures early, and serves as the foundation of broader continuous delivery and DevOps workflows. Originating in Extreme Programming, the practice has become a cornerstone of modern software delivery, enabling teams to maintain a consistently releasable main branch through disciplined automation."@en ;
rdfs:label "Continuous Integration"@en ;
rdfs:subClassOf ngm:software-engineering ;
rdfs:subClassOf _:r5663 ;
rdfs:subClassOf _:r5664 ;
vc:bridgesTo ngm:mlops ;
vc:bridgesTo ngm:model-evaluation ;
vc:contrastsWith ngm:big-bang-integration ;
vc:contrastsWith ngm:waterfall-development ;
vc:dependsOn ngm:containerisation ;
vc:dependsOn ngm:git ;
vc:dependsOn ngm:test-driven-development ;
vc:enables ngm:code-review ;
vc:enables ngm:continuous-delivery ;
vc:enables ngm:continuous-deployment ;
vc:enables ngm:trunk-based-development ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:automated-testing ;
vc:hasPart ngm:build-automation ;
vc:hasPart ngm:pipeline-as-code ;
vc:hasPart ngm:static-code-analysis ;
vc:implements ngm:infrastructure-as-code ;
vc:implements ngm:shift-left-testing ;
vc:isPartOf ngm:devops ;
vc:isPartOf ngm:software-delivery-lifecycle ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:ci-cd-automation ;
vc:relatedTo ngm:feature-flags ;
vc:relatedTo ngm:observability ;
vc:requires ngm:build-server ;
vc:requires ngm:version-control ;
vc:slug "continuous-integration" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:agile-software-development ;
vc:supports ngm:extreme-programming ;
vc:supports ngm:security-scanning ;
vc:uses ngm:docker-containerisation-platform ;
vc:uses ngm:git-hub-actions ;
vc:uses ngm:jenkins ;
vc:uses ngm:kubernetes .
ngm:continuous-learning a skos:Concept ;
rdfs:label "Continuous Learning"@en .
ngm:continuous-monitoring a owl:Class ;
rdfs:comment "An ongoing, automated process of collecting, analysing, and reporting metrics, logs, and events from systems, processes, or environments in near-real time to detect anomalies, ensure compliance, and support rapid response. Continuous monitoring operationalises oversight by replacing periodic audits with persistent telemetry streams fed into dashboards, alert rules, and automated remediation workflows. It is fundamental to DevSecOps, regulatory compliance programmes, and risk management frameworks that require timely evidence of control effectiveness."@en ;
rdfs:label "Continuous Monitoring"@en ;
rdfs:subClassOf ngm:governance ;
rdfs:subClassOf _:r5665 ;
rdfs:subClassOf _:r5666 ;
rdfs:subClassOf _:r5667 ;
rdfs:subClassOf _:r5668 ;
rdfs:subClassOf _:r5669 ;
rdfs:subClassOf _:r5670 ;
vc:contrastsWith ngm:periodic-audit ;
vc:dependsOn ngm:infrastructure ;
vc:enables ngm:anomaly-detection ;
vc:enables ngm:compliance-monitoring ;
vc:enables ngm:incident-response ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:alerting ;
vc:hasPart ngm:log-management ;
vc:hasPart ngm:metrics-collection ;
vc:hasPart ngm:telemetry ;
vc:implements ngm:risk-management ;
vc:implements ngm:security-operations ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:audit-trail ;
vc:relatedTo ngm:dev-sec-ops ;
vc:relatedTo ngm:security-information-and-event-management ;
vc:requires ngm:data-pipeline ;
vc:requires ngm:observability ;
vc:slug "continuous-monitoring" ;
vc:sourceDomain "governance" ;
vc:supports ngm:accountability ;
vc:supports ngm:transparency .
ngm:continuous-normalizing-flow a skos:Concept ;
rdfs:label "Continuous Normalizing Flow"@en .
ngm:continuous-operation a skos:Concept ;
rdfs:label "Continuous Operation"@en .
ngm:continuous-preventative-healthcare a skos:Concept ;
rdfs:label "Continuous Preventative Healthcare"@en .
ngm:continuous-support-workers a skos:Concept ;
rdfs:label "Continuous Support Workers"@en .
ngm:continuous-time-dynamical-systems a skos:Concept ;
rdfs:label "Continuous Time Dynamical Systems"@en .
ngm:continuous-time-preference-aggregation a skos:Concept ;
rdfs:label "Continuous Time Preference Aggregation"@en .
ngm:continuous-training a owl:Class ;
rdfs:comment "Continuous training is an MLOps practice in which machine-learning models are automatically retrained on fresh data on a recurring or event-driven basis to maintain predictive accuracy over time. It extends continuous integration and delivery to the model lifecycle, triggering retraining when new data arrives or when monitoring detects data or model drift. The retrained model is validated and promoted through automated pipelines before deployment."@en ;
rdfs:label "Continuous Training"@en ;
rdfs:subClassOf ngm:ai-lifecycle ;
rdfs:subClassOf ngm:machine-learning-operations ;
rdfs:subClassOf ngm:mlops ;
rdfs:subClassOf _:r5671 ;
rdfs:subClassOf _:r5672 ;
rdfs:subClassOf _:r5673 ;
rdfs:subClassOf _:r5674 ;
rdfs:subClassOf _:r5675 ;
rdfs:subClassOf _:r5676 ;
rdfs:subClassOf _:r5677 ;
rdfs:subClassOf _:r5678 ;
rdfs:subClassOf _:r5679 ;
rdfs:subClassOf _:r5680 ;
rdfs:subClassOf _:r5681 ;
vc:contrastsWith ngm:batch-training ;
vc:contrastsWith ngm:continual-learning ;
vc:contrastsWith ngm:offline-learning ;
vc:contrastsWith ngm:online-learning ;
vc:dependsOn ngm:concept-drift ;
vc:dependsOn ngm:data-drift ;
vc:dependsOn ngm:data-pipeline ;
vc:dependsOn ngm:feature-engineering ;
vc:dependsOn ngm:feature-store ;
vc:dependsOn ngm:model-monitoring ;
vc:enables ngm:ai-lifecycle ;
vc:enables ngm:continuous-deployment ;
vc:enables ngm:model-deployment ;
vc:enables ngm:model-governance ;
vc:enables ngm:model-serving ;
vc:enables ngm:production-ml ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:data-pipeline ;
vc:hasPart ngm:drift-detection ;
vc:hasPart ngm:feature-store ;
vc:hasPart ngm:labelling-pipeline ;
vc:hasPart ngm:model-evaluation ;
vc:hasPart ngm:model-registry ;
vc:hasPart ngm:model-training-pipeline ;
vc:hasPart ngm:retraining-trigger ;
vc:implements ngm:automation ;
vc:implements ngm:ci-cd-automation ;
vc:implements ngm:devops ;
vc:isPartOf ngm:ai-lifecycle ;
vc:isPartOf ngm:mlops ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:canary-deployment ;
vc:relatedTo ngm:continual-learning ;
vc:relatedTo ngm:continuous-integration ;
vc:relatedTo ngm:deep-learning ;
vc:relatedTo ngm:feature-engineering ;
vc:relatedTo ngm:federated-learning ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:model-decay ;
vc:relatedTo ngm:model-validation ;
vc:relatedTo ngm:online-learning ;
vc:relatedTo ngm:reinforcement-learning-from-human-feedback ;
vc:relatedTo ngm:shadow-mode-deployment ;
vc:relatedTo ngm:statistical-process-control ;
vc:relatedTo ngm:transfer-learning ;
vc:requires ngm:continuous-integration ;
vc:requires ngm:data-versioning ;
vc:requires ngm:empirical-experimental-design-tracking ;
vc:requires ngm:feature-store ;
vc:requires ngm:labelling-pipeline ;
vc:requires ngm:model-monitoring ;
vc:requires ngm:model-registry ;
vc:slug "continuous-training" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:mlops ;
vc:supports ngm:a-b-testing ;
vc:supports ngm:continuous-deployment ;
vc:supports ngm:model-governance ;
vc:supports ngm:model-validation ;
vc:supports ngm:shadow-mode-deployment ;
vc:uses ngm:apache-airflow ;
vc:uses ngm:ci-cd-automation ;
vc:uses ngm:data-pipeline ;
vc:uses ngm:deep-learning ;
vc:uses ngm:empirical-experimental-design-tracking ;
vc:uses ngm:evidently-ai ;
vc:uses ngm:gradient-descent ;
vc:uses ngm:kubeflow ;
vc:uses ngm:kubernetes ;
vc:uses ngm:mlflow ;
vc:uses ngm:model-training ;
vc:uses ngm:neural-network ;
vc:uses ngm:sagemaker ;
vc:uses ngm:seldon-core ;
vc:uses ngm:vertex-ai .
ngm:continuous-verification a skos:Concept ;
rdfs:label "Continuous Verification"@en .
ngm:contour a skos:Concept ;
rdfs:label "Contour"@en .
ngm:contract-analysis-process a skos:Concept ;
rdfs:label "Contract Analysis Process"@en .
ngm:contract-code a owl:Class ;
rdfs:comment "Contract code is the executable program logic that defines the rules, state, and behaviour of a smart contract deployed on a distributed ledger. It is typically written in a high-level language such as Solidity or Kotlin and compiled to bytecode that nodes execute deterministically. Because it is immutable once deployed and controls value, contract code is a primary target for auditing and formal verification."@en ;
rdfs:label "Contract Code"@en ;
rdfs:subClassOf ngm:smart-contract ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:smart-contract ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:r3-corda ;
vc:slug "contract-code" ;
vc:sourceDomain "blockchain" .
ngm:contract-enforcement a owl:Class ;
rdfs:comment "Contract enforcement is the set of legal, procedural, and technological mechanisms by which the obligations set out in an agreement are made binding and are upheld when a party fails to perform, ranging from courts and arbitration to automated on-chain execution. Traditional enforcement relies on dispute resolution processes and judicial remedies, whereas digital and blockchain-based approaches encode enforcement logic directly into self-executing code or arbitration protocols. Effective contract enforcement is a precondition for trust in both commercial transactions and decentralised digital agreements."@en ;
rdfs:label "Contract Enforcement"@en ;
rdfs:subClassOf ngm:dispute-resolution ;
rdfs:subClassOf _:r5682 ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:dispute-resolution ;
vc:slug "contract-enforcement" ;
vc:sourceDomain "governance" .
ngm:contract-law a skos:Concept ;
rdfs:label "Contract Law"@en .
ngm:contract-law-frameworks a skos:Concept ;
rdfs:label "Contract Law Frameworks"@en .
ngm:contract-net-protocol a owl:Class ;
rdfs:comment "The Contract Net Protocol is a task-sharing interaction pattern for multi-agent systems in which a manager agent announces a task, soliciting bids from potential contractor agents, evaluates the responses, and awards the task to the most suitable bidder. It decomposes distributed problem solving into the phases of announcement, bidding, awarding, and result reporting, treating the agent population as a market for negotiating the allocation of work. The protocol provides a decentralised mechanism for dynamic task allocation without a fixed assignment table."@en ;
rdfs:label "Contract Net Protocol"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf ngm:multi-agent-system ;
rdfs:subClassOf _:r5683 ;
rdfs:subClassOf _:r5684 ;
skos:broader ngm:artificial-intelligence ;
vc:bridgesTo ngm:distributed-systems ;
vc:contrastsWith ngm:consensus ;
vc:dependsOn ngm:agent ;
vc:enables ngm:automation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:consensus ;
vc:implements ngm:consensus ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:automation ;
vc:relatedTo ngm:decentralization ;
vc:relatedTo ngm:distributed-systems ;
vc:requires ngm:agent ;
vc:slug "contract-net-protocol" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:standards ;
vc:supports ngm:decentralization ;
vc:uses ngm:agent .
ngm:contract-schema a skos:Concept ;
rdfs:label "Contract Schema"@en .
ngm:contract-state a skos:Concept ;
rdfs:label "Contract State"@en .
ngm:contract-testing a skos:Concept ;
rdfs:label "Contract Testing"@en .
ngm:contract-theory a owl:Class ;
rdfs:comment "Contract theory is the branch of economics that studies how parties design agreements under asymmetric information, incentive conflicts, and incomplete contracting. It analyses problems such as moral hazard, adverse selection, and signalling to derive incentive-compatible contracts that align the interests of principals and agents. It provides the formal foundations for mechanism and incentive design, including in tokenised and decentralised systems."@en ;
rdfs:label "Contract Theory"@en ;
rdfs:subClassOf ngm:economic-mechanism ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:economics ;
vc:slug "contract-theory" ;
vc:sourceDomain "blockchain" .
ngm:contract-verification a skos:Concept ;
rdfs:label "Contract Verification"@en .
ngm:contractual-capacity a skos:Concept ;
rdfs:label "Contractual Capacity"@en .
ngm:contractual-liability a skos:Concept ;
rdfs:label "Contractual Liability"@en .
ngm:contractual-obligation a skos:Concept ;
rdfs:label "Contractual Obligation"@en .
ngm:contractum-language a owl:Class ;
rdfs:comment "Contractum is a high-level smart-contract programming language designed for the RGB protocol, which performs client-side validation of state transitions anchored to Bitcoin. It compiles to AluVM bytecode and lets developers express RGB schemas and contract logic in a readable, declarative form. It is central to authoring confidential, scalable contracts that settle off-chain while inheriting Bitcoin's security."@en ;
rdfs:label "Contractum Language"@en ;
rdfs:subClassOf ngm:programming-language ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:rgb-and-client-side-validation ;
vc:slug "contractum-language" ;
vc:sourceDomain "blockchain" .
ngm:contrast-ratio-meter a skos:Concept ;
rdfs:label "Contrast Ratio Meter"@en .
ngm:contrastive-language-audio-pre-training a skos:Concept ;
rdfs:label "Contrastive Language Audio Pre Training"@en .
ngm:contrastive-language-image-pre-training a skos:Concept ;
rdfs:label "Contrastive Language Image Pre Training"@en .
ngm:contrastive-learning a owl:Class ;
rdfs:comment "A self-supervised representation learning approach that trains models by comparing positive pairs (semantically similar samples) against negative pairs (dissimilar samples), pushing similar embeddings closer and dissimilar ones apart in latent space, enabling powerful feature learning without explicit labels."@en ;
rdfs:label "Contrastive Learning"@en ;
rdfs:subClassOf ngm:self-supervised-learning ;
rdfs:subClassOf _:r5685 ;
rdfs:subClassOf _:r5686 ;
rdfs:subClassOf _:r5687 ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:spatial-computing ;
vc:contrastsWith ngm:curriculum-learning ;
vc:contrastsWith ngm:generative-adversarial-network ;
vc:contrastsWith ngm:supervised-learning ;
vc:enables ngm:embedding-model ;
vc:enables ngm:feature-extraction ;
vc:enables ngm:few-shot-learning ;
vc:enables ngm:multimodal-ai-architecture-ai ;
vc:enables ngm:transfer-learning ;
vc:enables ngm:zero-shot-learning ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:infonce-loss ;
vc:implements ngm:clip ;
vc:implements ngm:momentum-contrast ;
vc:isPartOf ngm:representation-learning ;
vc:isPartOf ngm:self-supervised-learning ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:computer-vision ;
vc:relatedTo ngm:knowledge-distillation ;
vc:relatedTo ngm:natural-language-processing ;
vc:requires ngm:data-augmentation ;
vc:requires ngm:embedding-space ;
vc:requires ngm:encoder ;
vc:slug "contrastive-learning" ;
vc:sourceDomain "machine-learning" ;
vc:uses ngm:deep-learning ;
vc:uses ngm:neural-network .
ngm:contrastive-loss a skos:Concept ;
rdfs:label "Contrastive Loss"@en .
ngm:contrastive-training a skos:Concept ;
rdfs:label "Contrastive Training"@en .
ngm:contributor-license-agreement a skos:Concept ;
rdfs:label "Contributor License Agreement"@en .
ngm:control a skos:Concept ;
rdfs:label "Control"@en .
ngm:control-activity a skos:Concept ;
rdfs:label "Control Activity"@en .
ngm:control-algorithm a owl:Class ;
rdfs:comment "ControlAlgorithm is a formalised mathematical and computational procedure that generates actuator commands to drive a dynamic system from its current state toward a desired target state, exploiting feedback from sensors, an internal model of the plant, or learned approximations of system dynamics..."@en ;
rdfs:label "Control Algorithm"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:computational-intelligence ;
rdfs:subClassOf ngm:control-theory ;
rdfs:subClassOf ngm:dynamical-systems ;
rdfs:subClassOf ngm:feedback-control ;
rdfs:subClassOf ngm:optimal-control ;
rdfs:subClassOf _:r5688 ;
rdfs:subClassOf _:r5689 ;
rdfs:subClassOf _:r5690 ;
rdfs:subClassOf _:r5691 ;
rdfs:subClassOf _:r5692 ;
rdfs:subClassOf _:r5693 ;
rdfs:subClassOf _:r5694 ;
rdfs:subClassOf _:r5695 ;
rdfs:subClassOf _:r5696 ;
rdfs:subClassOf _:r5697 ;
rdfs:subClassOf _:r5698 ;
skos:broader ngm:ai-technique ;
vc:contrastsWith ngm:bang-bang-control ;
vc:contrastsWith ngm:expert-systems ;
vc:contrastsWith ngm:open-loop-control ;
vc:contrastsWith ngm:rule-based-systems ;
vc:dependsOn ngm:convex-optimisation ;
vc:dependsOn ngm:differential-equations ;
vc:dependsOn ngm:linear-algebra ;
vc:dependsOn ngm:lyapunov-stability ;
vc:dependsOn ngm:neural-network ;
vc:dependsOn ngm:optimisation ;
vc:dependsOn ngm:probability-theory ;
vc:enables ngm:autonomous-system ;
vc:enables ngm:energy-management ;
vc:enables ngm:fault-tolerant-control ;
vc:enables ngm:force-control ;
vc:enables ngm:motion-planning ;
vc:enables ngm:process-automation ;
vc:enables ngm:robotics ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:adaptation-law ;
vc:hasPart ngm:cost-function ;
vc:hasPart ngm:kalman-filter ;
vc:hasPart ngm:pid-controller ;
vc:hasPart ngm:receding-horizon ;
vc:hasPart ngm:reference-model ;
vc:hasPart ngm:reward-signal ;
vc:hasPart ngm:safety-constraint ;
vc:hasPart ngm:state-observer ;
vc:hasPart ngm:switching-surface ;
vc:implements ngm:adaptive-control ;
vc:implements ngm:h-infinity-control ;
vc:implements ngm:iterative-learning-control ;
vc:implements ngm:linear-quadratic-regulator ;
vc:implements ngm:model-predictive-control ;
vc:implements ngm:pid-controller ;
vc:implements ngm:reinforcement-learning ;
vc:implements ngm:sliding-mode-control ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:control-theory ;
vc:relatedTo ngm:dynamics ;
vc:relatedTo ngm:embedded-systems ;
vc:relatedTo ngm:formal-verification ;
vc:relatedTo ngm:kinematics ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:safety-critical-systems ;
vc:requires ngm:actuator-model ;
vc:requires ngm:constraint-specification ;
vc:requires ngm:plant-model ;
vc:requires ngm:sensor-feedback ;
vc:requires ngm:stability-analysis ;
vc:requires ngm:state-space ;
vc:slug "control-algorithm" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:do-178-c ;
vc:standardizedBy ngm:iec-61511 ;
vc:standardizedBy ngm:ieee-control-systems-society ;
vc:standardizedBy ngm:ifac ;
vc:standardizedBy ngm:iso-26262 ;
vc:supports ngm:aerospace ;
vc:supports ngm:autonomous-vehicle ;
vc:supports ngm:chemical-process-control ;
vc:supports ngm:humanoid-robotics ;
vc:supports ngm:power-systems ;
vc:supports ngm:soft-robotics ;
vc:supports ngm:surgical-robotics ;
vc:uses ngm:hardware-in-the-loop-testing ;
vc:uses ngm:kalman-filter ;
vc:uses ngm:simulation ;
vc:uses ngm:state-estimation ;
vc:uses ngm:system-identification .
ngm:control-algorithm-tuning a skos:Concept ;
rdfs:label "Control Algorithm Tuning"@en .
ngm:control-documentation a skos:Concept ;
rdfs:label "Control Documentation"@en .
ngm:control-electronics a skos:Concept ;
rdfs:label "Control Electronics"@en .
ngm:control-environment a skos:Concept ;
rdfs:label "Control Environment"@en .
ngm:control-evidence a skos:Concept ;
rdfs:label "Control Evidence"@en .
ngm:control-framework a owl:Class ;
rdfs:comment "A control framework is a structured set of governance, risk, and compliance controls that an organisation adopts to manage risk and demonstrate conformance to regulatory or industry requirements. Examples include NIST CSF, COBIT, ISO 27001, and SOC 2, each mapping objectives to specific control activities and evidence. It provides a common reference for designing, operating, and auditing controls consistently."@en ;
rdfs:label "Control Framework"@en ;
rdfs:subClassOf ngm:governance-framework ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:compliance ;
vc:relatedTo ngm:regulatory-compliance ;
vc:slug "control-framework" ;
vc:sourceDomain "governance" .
ngm:control-groups a skos:Concept ;
rdfs:label "Control Groups"@en .
ngm:control-inputs a skos:Concept ;
rdfs:label "Control Inputs"@en .
ngm:control-interface a owl:Class ;
rdfs:comment "A control interface is the defined boundary through which commands and feedback are exchanged between a controller and a controlled device such as an actuator, end-effector, or robot subsystem. It specifies the signals, protocols, data rates, and timing required for deterministic command of the hardware. A well-defined control interface is what allows higher-level planners and digital twins to actuate physical systems reliably."@en ;
rdfs:label "Control Interface"@en ;
rdfs:subClassOf ngm:robo-actuation-and-control ;
skos:broader ngm:robo-actuation-and-control ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:digital-twin ;
vc:relatedTo ngm:end-effector ;
vc:slug "control-interface" ;
vc:sourceDomain "robotics" .
ngm:control-law a owl:Class ;
rdfs:comment "A control law is the mathematical rule that maps measured system state and reference signals to the control inputs applied to a plant. It is the algorithmic core of a feedback controller, expressed as functions such as PID, state feedback, or impedance laws. The choice of control law determines stability, tracking accuracy, and disturbance rejection of the closed-loop system."@en ;
rdfs:label "Control Law"@en ;
rdfs:subClassOf ngm:control-theory ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:force-control ;
vc:relatedTo ngm:position-control ;
vc:slug "control-law" ;
vc:sourceDomain "robotics" .
ngm:control-layer a owl:Class ;
rdfs:comment "The Control Layer is the stratum that issues commands to actuators or subsystems to drive a system toward desired states. It sits above the Perception Layer, on whose estimates it acts, and below planning and agent strata that set goals. It contains controllers, feedback loops, set-point logic, and the actuation interfaces that effect change."@en ;
rdfs:label "Control Layer"@en ;
rdfs:subClassOf ngm:owl-thing ;
rdfs:subClassOf ngm:robo-actuation-and-control ;
rdfs:subClassOf _:r5699 ;
skos:broader ngm:robo-actuation-and-control ;
vc:bridgesTo ngm:control-theory ;
vc:bridgesTo ngm:feedback-loop ;
vc:enables ngm:agent-layer ;
vc:enables ngm:coordination-layer ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:perception-layer ;
vc:slug "control-layer" ;
vc:sourceDomain "robotics" .
ngm:control-library a skos:Concept ;
rdfs:label "Control Library"@en .
ngm:control-loop a owl:Class ;
rdfs:comment "A control loop is the cyclical process by which a system measures its current state, compares it against a desired set point and applies corrective action to reduce the difference. Closed-loop control uses feedback from sensors to continuously regulate an actuator, while open-loop control acts without such feedback. Control loops are foundational to automation, cyber-physical systems and the reconciliation pattern used in infrastructure orchestration."@en ;
rdfs:label "Control Loop"@en ;
rdfs:subClassOf ngm:control-system ;
rdfs:subClassOf _:r5700 ;
rdfs:subClassOf _:r5701 ;
rdfs:subClassOf _:r5702 ;
rdfs:subClassOf _:r5703 ;
vc:bridgesTo ngm:cyber-physical-systems ;
vc:dependsOn ngm:feedback-loop ;
vc:enables ngm:automation ;
vc:enables ngm:cyber-physical-systems ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:actuator ;
vc:hasPart ngm:feedback-loop ;
vc:hasPart ngm:sensor ;
vc:implements ngm:automation ;
vc:implements ngm:process-control ;
vc:isPartOf ngm:control-system ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:automation ;
vc:relatedTo ngm:control-system ;
vc:relatedTo ngm:cyber-physical-systems ;
vc:relatedTo ngm:digital-twin ;
vc:requires ngm:feedback-loop ;
vc:slug "control-loop" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:actuator ;
vc:uses ngm:sensor ;
vc:uses ngm:state-estimation .
ngm:control-mapping a skos:Concept ;
rdfs:label "Control Mapping"@en .
ngm:control-maturity-assessment a skos:Concept ;
rdfs:label "Control Maturity Assessment"@en .
ngm:control-moment-gyroscope a owl:Class ;
rdfs:label "Control Moment Gyroscope"@en ;
rdfs:subClassOf ngm:actuator ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:spacecraft-guidance-navigation-and-control ;
vc:slug "control-moment-gyroscope" ;
vc:sourceDomain "space-science-and-systems" .
ngm:control-net a owl:Class ;
rdfs:comment "ControlNet is a trainable adapter architecture that attaches conditional spatial control to pre-trained text-to-image diffusion models by duplicating the U-Net encoder into a locked copy and a trainable copy, connecting them through zero-convolution layers initialised to exactly zero weight and bias. The zero initialisation guarantees that at the start of training no gradient noise corrupts the pre-trained backbone, allowing fine-tuning on relatively small paired datasets of (control map, image) pairs. Input control maps include Canny edge maps, depth maps, human pose skeletons, semantic segmentation masks, surface normal maps, line-art, and scribbles, each producing spatially precise, prompt-steerable image generation. The result is a modular conditioning mechanism that can be composed — multiple ControlNets with weighted merging — and transplanted across base diffusion model checkpoints without retraining."@en ;
rdfs:label "ControlNet"@en ;
rdfs:subClassOf ngm:adapter-tuning ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:fine-tuning ;
rdfs:subClassOf ngm:generative-model ;
rdfs:subClassOf ngm:neural-network-architecture ;
rdfs:subClassOf ngm:transfer-learning ;
rdfs:subClassOf _:r5745 ;
rdfs:subClassOf _:r5746 ;
rdfs:subClassOf _:r5747 ;
rdfs:subClassOf _:r5748 ;
rdfs:subClassOf _:r5749 ;
rdfs:subClassOf _:r5750 ;
rdfs:subClassOf _:r5751 ;
rdfs:subClassOf _:r5752 ;
rdfs:subClassOf _:r5753 ;
rdfs:subClassOf _:r5754 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:drug-discovery ;
vc:bridgesTo ngm:generative-ai ;
vc:bridgesTo ngm:medical-imaging ;
vc:bridgesTo ngm:spatial-computing ;
vc:contrastsWith ngm:adapter-modules ;
vc:contrastsWith ngm:generative-adversarial-network ;
vc:contrastsWith ngm:ip-adapter ;
vc:contrastsWith ngm:lo-ra ;
vc:contrastsWith ngm:textual-inversion ;
vc:dependsOn ngm:classifier-free-guidance ;
vc:dependsOn ngm:convolutional-neural-network ;
vc:dependsOn ngm:diffusion-model ;
vc:dependsOn ngm:noise-schedule ;
vc:dependsOn ngm:vae ;
vc:enables ngm:architectural-visualisation ;
vc:enables ngm:conditional-image-generation ;
vc:enables ngm:data-augmentation ;
vc:enables ngm:image-generation ;
vc:enables ngm:image-synthesis ;
vc:enables ngm:inpainting ;
vc:enables ngm:medical-imaging ;
vc:enables ngm:spatially-guided-generation ;
vc:enables ngm:text-to-image ;
vc:enables ngm:video-generation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:conditioning-preprocessor ;
vc:hasPart ngm:conditioning-signal ;
vc:hasPart ngm:image-conditioning ;
vc:hasPart ngm:skip-connection-injection ;
vc:hasPart ngm:u-net ;
vc:hasPart ngm:zero-convolution ;
vc:implements ngm:adapter-tuning ;
vc:implements ngm:spatial-conditioning ;
vc:implements ngm:weighted-feature-addition ;
vc:implements ngm:zero-initialisation-protocol ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:adapter-tuning ;
vc:relatedTo ngm:canny-edge-detection ;
vc:relatedTo ngm:control-net-conditioning ;
vc:relatedTo ngm:controlnet ;
vc:relatedTo ngm:controlnet-xs ;
vc:relatedTo ngm:depth-estimation ;
vc:relatedTo ngm:diffusion-model ;
vc:relatedTo ngm:edge-detection ;
vc:relatedTo ngm:flux-1 ;
vc:relatedTo ngm:foundation-model ;
vc:relatedTo ngm:generative-ai ;
vc:relatedTo ngm:latent-diffusion ;
vc:relatedTo ngm:midas-depth-estimation ;
vc:relatedTo ngm:multimodal-model ;
vc:relatedTo ngm:noise-schedule ;
vc:relatedTo ngm:pose-estimation ;
vc:relatedTo ngm:semantic-segmentation ;
vc:relatedTo ngm:stable-diffusion-image-model ;
vc:relatedTo ngm:synthetic-data ;
vc:relatedTo ngm:u-net ;
vc:relatedTo ngm:zero-convolution ;
vc:requires ngm:backpropagation ;
vc:requires ngm:fine-tuning ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:latent-diffusion ;
vc:requires ngm:neural-network-architecture ;
vc:requires ngm:training-data ;
vc:requires ngm:transfer-learning ;
vc:slug "control-net" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:hugging-face-diffusers ;
vc:supports ngm:animatediff ;
vc:supports ngm:automatic1111 ;
vc:supports ngm:comfy-ui ;
vc:supports ngm:fooocus ;
vc:supports ngm:hugging-face-diffusers ;
vc:supports ngm:node-based-diffusion-pipeline-interface ;
vc:supports ngm:sdxl ;
vc:uses ngm:attention-mechanism ;
vc:uses ngm:backpropagation ;
vc:uses ngm:classifier-free-guidance ;
vc:uses ngm:depth-estimation ;
vc:uses ngm:diffusion-model ;
vc:uses ngm:edge-detection ;
vc:uses ngm:latent-diffusion ;
vc:uses ngm:open-pose ;
vc:uses ngm:semantic-segmentation ;
vc:uses ngm:stable-diffusion-image-model ;
vc:uses ngm:u-net ;
vc:uses ngm:zero-convolution .
ngm:control-net-and-similar-spatial-conditioning-systems a owl:Class ;
rdfs:comment "ControlNet and similar spatial conditioning systems constitute a family of neural network architectures and adapter frameworks that augment large pretrained text-to-image Diffusion Models with fine-grained spatial and semantic control signals—enabling deterministic structural guidance over ge..."@en ;
rdfs:label "ControlNet and Similar Spatial Conditioning Systems"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:conditional-image-generation ;
rdfs:subClassOf ngm:diffusion-model ;
rdfs:subClassOf ngm:fine-tuning ;
rdfs:subClassOf ngm:generative-model ;
rdfs:subClassOf ngm:neural-network ;
rdfs:subClassOf ngm:transfer-learning ;
rdfs:subClassOf _:r5736 ;
rdfs:subClassOf _:r5737 ;
rdfs:subClassOf _:r5738 ;
rdfs:subClassOf _:r5739 ;
rdfs:subClassOf _:r5740 ;
rdfs:subClassOf _:r5741 ;
rdfs:subClassOf _:r5742 ;
rdfs:subClassOf _:r5743 ;
rdfs:subClassOf _:r5744 ;
skos:broader ngm:ai-application ;
vc:contrastsWith ngm:generative-adversarial-networks ;
vc:contrastsWith ngm:kohya-dreambooth-and-similar ;
vc:contrastsWith ngm:lo-ra ;
vc:contrastsWith ngm:textual-inversion ;
vc:contrastsWith ngm:vae ;
vc:dependsOn ngm:clip ;
vc:dependsOn ngm:convolutional-neural-network ;
vc:dependsOn ngm:diffusion-models ;
vc:dependsOn ngm:stable-diffusion-image-model ;
vc:dependsOn ngm:transformer-architecture ;
vc:dependsOn ngm:u-net-architecture ;
vc:enables ngm:depth-controlled-synthesis ;
vc:enables ngm:edge-guided-generation ;
vc:enables ngm:identity-preservation ;
vc:enables ngm:image-generation ;
vc:enables ngm:structural-layout-control ;
vc:enables ngm:style-transfer ;
vc:enables ngm:video-frame-consistency ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:conditioning-preprocessor ;
vc:hasPart ngm:control-signal ;
vc:hasPart ngm:cross-attention-adapter ;
vc:hasPart ngm:encoder-copy ;
vc:hasPart ngm:identity-network ;
vc:hasPart ngm:skip-connection-injection ;
vc:hasPart ngm:zero-convolution-layer ;
vc:implements ngm:adapter-tuning ;
vc:implements ngm:cross-attention-injection ;
vc:implements ngm:feedback-control ;
vc:implements ngm:fine-tuning ;
vc:implements ngm:spatial-conditioning ;
vc:implements ngm:zero-shot-conditioning ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:adapter-modules ;
vc:relatedTo ngm:depth-estimation ;
vc:relatedTo ngm:edge-detection ;
vc:relatedTo ngm:flux-1 ;
vc:relatedTo ngm:image-generation ;
vc:relatedTo ngm:instant-id ;
vc:relatedTo ngm:ip-adapter ;
vc:relatedTo ngm:pose-estimation ;
vc:relatedTo ngm:stable-diffusion-image-model ;
vc:requires ngm:backpropagation ;
vc:requires ngm:clip-encoder ;
vc:requires ngm:conditioning-signal ;
vc:requires ngm:diffusion-model ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:training-data ;
vc:slug "control-net-and-similar-spatial-conditioning-systems" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:ar-xiv ;
vc:standardizedBy ngm:arxiv ;
vc:standardizedBy ngm:cvpr ;
vc:standardizedBy ngm:eccv ;
vc:standardizedBy ngm:hugging-face-diffusers ;
vc:standardizedBy ngm:iccv ;
vc:supports ngm:architectural-visualisation ;
vc:supports ngm:automatic1111 ;
vc:supports ngm:character-design ;
vc:supports ngm:image-to-image ;
vc:supports ngm:inpainting ;
vc:supports ngm:lo-ra ;
vc:supports ngm:node-based-diffusion-pipeline-interface ;
vc:uses ngm:canny-edge-detection ;
vc:uses ngm:clip-encoder ;
vc:uses ngm:depth-estimation ;
vc:uses ngm:dwpose ;
vc:uses ngm:insight-face ;
vc:uses ngm:insightface ;
vc:uses ngm:midas-depth-estimation ;
vc:uses ngm:open-pose .
ngm:control-net-conditioning a owl:Class ;
rdfs:comment "ControlNet conditioning is a technique that augments a pretrained diffusion model with an auxiliary network so generation can be steered by spatial control signals such as edge maps, depth, pose, or segmentation. The ControlNet branch copies the encoder of the base model and injects conditioning through zero-initialised connections, preserving the original weights while adding controllability. It gives image-generation pipelines precise structural control without retraining the base model."@en ;
rdfs:label "ControlNet Conditioning"@en ;
rdfs:subClassOf ngm:adapter-tuning ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:control-net ;
rdfs:subClassOf ngm:fine-tuning ;
rdfs:subClassOf ngm:generative-model ;
rdfs:subClassOf ngm:parameter-efficient-fine-tuning ;
rdfs:subClassOf ngm:spatial-conditioning ;
rdfs:subClassOf ngm:transfer-learning ;
rdfs:subClassOf _:r5727 ;
rdfs:subClassOf _:r5728 ;
rdfs:subClassOf _:r5729 ;
rdfs:subClassOf _:r5730 ;
rdfs:subClassOf _:r5731 ;
rdfs:subClassOf _:r5732 ;
rdfs:subClassOf _:r5733 ;
rdfs:subClassOf _:r5734 ;
rdfs:subClassOf _:r5735 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:architectural-visualisation ;
vc:bridgesTo ngm:drug-discovery ;
vc:bridgesTo ngm:medical-imaging ;
vc:bridgesTo ngm:spatial-computing ;
vc:bridgesTo ngm:synthetic-data ;
vc:contrastsWith ngm:adapter-modules ;
vc:contrastsWith ngm:generative-adversarial-network ;
vc:contrastsWith ngm:ip-adapter ;
vc:contrastsWith ngm:lo-ra ;
vc:contrastsWith ngm:textual-inversion ;
vc:dependsOn ngm:classifier-free-guidance ;
vc:dependsOn ngm:convolutional-neural-network ;
vc:dependsOn ngm:latent-diffusion ;
vc:dependsOn ngm:noise-schedule ;
vc:dependsOn ngm:stable-diffusion-image-model ;
vc:dependsOn ngm:vae ;
vc:enables ngm:architectural-visualisation ;
vc:enables ngm:conditional-image-generation ;
vc:enables ngm:image-generation ;
vc:enables ngm:image-synthesis ;
vc:enables ngm:inpainting ;
vc:enables ngm:medical-imaging ;
vc:enables ngm:pose-guided-image-generation ;
vc:enables ngm:synthetic-data ;
vc:enables ngm:text-to-image ;
vc:enables ngm:video-generation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:conditioning-preprocessor ;
vc:hasPart ngm:conditioning-signal ;
vc:hasPart ngm:image-conditioning ;
vc:hasPart ngm:skip-connection-injection ;
vc:hasPart ngm:u-net ;
vc:hasPart ngm:u-net-encoder-copy ;
vc:hasPart ngm:zero-convolution ;
vc:implements ngm:adapter-tuning ;
vc:implements ngm:spatial-conditioning ;
vc:implements ngm:transfer-learning ;
vc:implements ngm:zero-initialisation-protocol ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:adapter-tuning ;
vc:relatedTo ngm:animatediff ;
vc:relatedTo ngm:attention-mechanism ;
vc:relatedTo ngm:backpropagation ;
vc:relatedTo ngm:classifier-free-guidance ;
vc:relatedTo ngm:computer-vision ;
vc:relatedTo ngm:conditional-image-generation ;
vc:relatedTo ngm:conditioning-signal ;
vc:relatedTo ngm:control-net ;
vc:relatedTo ngm:control-net-and-similar-spatial-conditioning-systems ;
vc:relatedTo ngm:controlnet-plus-plus ;
vc:relatedTo ngm:controlnet-xs ;
vc:relatedTo ngm:depth-estimation ;
vc:relatedTo ngm:diffusion-model ;
vc:relatedTo ngm:edge-detection ;
vc:relatedTo ngm:flux-1 ;
vc:relatedTo ngm:foundation-model ;
vc:relatedTo ngm:generative-ai ;
vc:relatedTo ngm:hugging-face-diffusers ;
vc:relatedTo ngm:ip-adapter ;
vc:relatedTo ngm:latent-diffusion ;
vc:relatedTo ngm:lo-ra ;
vc:relatedTo ngm:pose-estimation ;
vc:relatedTo ngm:sdxl ;
vc:relatedTo ngm:semantic-segmentation ;
vc:relatedTo ngm:skip-connection-injection ;
vc:relatedTo ngm:spatial-conditioning ;
vc:relatedTo ngm:stable-diffusion-image-model ;
vc:relatedTo ngm:textual-inversion ;
vc:relatedTo ngm:training-data ;
vc:relatedTo ngm:u-net ;
vc:relatedTo ngm:vae ;
vc:relatedTo ngm:zero-convolution ;
vc:requires ngm:backpropagation ;
vc:requires ngm:diffusion-model ;
vc:requires ngm:fine-tuning ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:neural-network-architecture ;
vc:requires ngm:training-data ;
vc:slug "control-net-conditioning" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:hugging-face-diffusers ;
vc:supports ngm:animatediff ;
vc:supports ngm:architectural-visualisation ;
vc:supports ngm:automatic1111 ;
vc:supports ngm:fooocus ;
vc:supports ngm:image-to-image ;
vc:supports ngm:node-based-diffusion-pipeline-interface ;
vc:supports ngm:node-based-diffusion-pipeline-interface-workflows ;
vc:supports ngm:sdxl ;
vc:uses ngm:attention-mechanism ;
vc:uses ngm:canny-edge-detection ;
vc:uses ngm:classifier-free-guidance ;
vc:uses ngm:depth-estimation ;
vc:uses ngm:diffusion-model ;
vc:uses ngm:dwpose ;
vc:uses ngm:edge-detection ;
vc:uses ngm:latent-diffusion ;
vc:uses ngm:midas ;
vc:uses ngm:midas-depth-estimation ;
vc:uses ngm:open-pose ;
vc:uses ngm:pose-estimation ;
vc:uses ngm:u-net ;
vc:uses ngm:zero-convolution .
ngm:control-objective a skos:Concept ;
rdfs:label "Control Objective"@en .
ngm:control-output a skos:Concept ;
rdfs:label "Control Output"@en .
ngm:control-owner a skos:Concept ;
rdfs:label "Control Owner"@en .
ngm:control-plane a skos:Concept ;
rdfs:label "Control Plane"@en .
ngm:control-signal a owl:Class ;
rdfs:comment "A control signal is the command output computed by a controller and applied to actuate or steer a system toward a desired state. In robotics and electromechanical contexts it is the voltage, current, or set-point delivered to an actuator; in generative pipelines it is the spatial conditioning input that guides synthesis. In both senses it is the carrier of intent between a decision process and the system it drives."@en ;
rdfs:label "Control Signal"@en ;
rdfs:subClassOf ngm:control-system ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:control-net-and-similar-spatial-conditioning-systems ;
vc:relatedTo ngm:electric-actuator ;
vc:slug "control-signal" ;
vc:sourceDomain "robotics" .
ngm:control-system a owl:Class ;
rdfs:comment "Control system encompasses the computational and hardware subsystems that sense environmental state, evaluate performance against desired objectives, and generate actuation commands to regulate robot behaviour toward goals."@en ;
rdfs:label "Control System"@en ;
rdfs:subClassOf ngm:feedback-systems ;
rdfs:subClassOf ngm:robo-actuation-and-control ;
rdfs:subClassOf ngm:robotic-system ;
rdfs:subClassOf _:r5704 ;
rdfs:subClassOf _:r5705 ;
rdfs:subClassOf _:r5706 ;
rdfs:subClassOf _:r5707 ;
rdfs:subClassOf _:r5708 ;
rdfs:subClassOf _:r5709 ;
rdfs:subClassOf _:r5710 ;
rdfs:subClassOf _:r5711 ;
rdfs:subClassOf _:r5712 ;
skos:broader ngm:robo-actuation-and-control ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:robotic-system ;
vc:dependsOn ngm:communication-protocol ;
vc:dependsOn ngm:control-algorithm ;
vc:dependsOn ngm:power-supply ;
vc:enables ngm:adaptive-behaviour ;
vc:enables ngm:motion-control ;
vc:enables ngm:stabilisation ;
vc:enables ngm:task-execution ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:actuator-driver ;
vc:hasPart ngm:controller ;
vc:hasPart ngm:feedback-loop ;
vc:hasPart ngm:sensor-interface ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:actuator ;
vc:requires ngm:real-time-computation ;
vc:requires ngm:sensor-input ;
vc:requires ngm:time-synchronisation ;
vc:slug "control-system" ;
vc:sourceDomain "robotics" .
ngm:control-testing a skos:Concept ;
rdfs:label "Control Testing"@en .
ngm:control-theory a owl:Class ;
rdfs:comment "Control Theory is the interdisciplinary mathematical framework for analysing and synthesising dynamical systems that automatically regulate themselves toward desired behaviour in the presence of disturbances, model uncertainty, sensor noise, and parameter variation, formalising the closed-loop fe..."@en ;
rdfs:label "Control Theory"@en ;
rdfs:subClassOf ngm:applied-mathematics ;
rdfs:subClassOf ngm:control-engineering ;
rdfs:subClassOf ngm:control-system ;
rdfs:subClassOf ngm:cybernetics ;
rdfs:subClassOf ngm:dynamical-systems-theory ;
rdfs:subClassOf ngm:robo-actuation-and-control ;
rdfs:subClassOf ngm:systems-engineering ;
rdfs:subClassOf _:r5713 ;
rdfs:subClassOf _:r5714 ;
rdfs:subClassOf _:r5715 ;
rdfs:subClassOf _:r5716 ;
rdfs:subClassOf _:r5717 ;
rdfs:subClassOf _:r5718 ;
rdfs:subClassOf _:r5719 ;
rdfs:subClassOf _:r5720 ;
rdfs:subClassOf _:r5721 ;
rdfs:subClassOf _:r5722 ;
rdfs:subClassOf _:r5723 ;
rdfs:subClassOf _:r5724 ;
rdfs:subClassOf _:r5725 ;
rdfs:subClassOf _:r5726 ;
skos:broader ngm:robo-actuation-and-control ;
vc:contrastsWith ngm:ai-without-dynamics-models ;
vc:contrastsWith ngm:classical-optimisation-without-feedback ;
vc:contrastsWith ngm:model-free-heuristic-tuning ;
vc:contrastsWith ngm:open-loop-scheduling ;
vc:dependsOn ngm:convex-optimisation ;
vc:dependsOn ngm:hamilton-jacobi-bellman-equation ;
vc:dependsOn ngm:laplace-transform ;
vc:dependsOn ngm:lyapunov-stability-theory ;
vc:dependsOn ngm:riccati-equation ;
vc:dependsOn ngm:state-space-representation ;
vc:dependsOn ngm:z-transform ;
vc:enables ngm:autonomous-navigation ;
vc:enables ngm:closed-loop-control ;
vc:enables ngm:flight-stability ;
vc:enables ngm:predictive-maintenance ;
vc:enables ngm:process-regulation ;
vc:enables ngm:robust-performance ;
vc:enables ngm:trajectory-tracking ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:controller ;
vc:hasPart ngm:disturbance-model ;
vc:hasPart ngm:feedback-loop ;
vc:hasPart ngm:plant-model ;
vc:hasPart ngm:reference-signal ;
vc:hasPart ngm:stability-analysis ;
vc:hasPart ngm:state-estimation ;
vc:implements ngm:adaptive-control ;
vc:implements ngm:backstepping ;
vc:implements ngm:h-control ;
vc:implements ngm:kalman-filter ;
vc:implements ngm:linear-quadratic-regulator ;
vc:implements ngm:model-predictive-control ;
vc:implements ngm:pid-control ;
vc:implements ngm:sliding-mode-control ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:estimation-theory ;
vc:relatedTo ngm:game-theory ;
vc:relatedTo ngm:operations-research ;
vc:relatedTo ngm:reinforcement-learning ;
vc:relatedTo ngm:signal-processing ;
vc:relatedTo ngm:system-identification ;
vc:requires ngm:actuator ;
vc:requires ngm:differential-equations ;
vc:requires ngm:linear-algebra ;
vc:requires ngm:optimisation ;
vc:requires ngm:probability-theory ;
vc:requires ngm:real-time-computation ;
vc:requires ngm:sensor ;
vc:slug "control-theory" ;
vc:sourceDomain "robotics" ;
vc:standardizedBy ngm:arp4754-a ;
vc:standardizedBy ngm:do-178-c ;
vc:standardizedBy ngm:iec-61131-3 ;
vc:standardizedBy ngm:iec-61508 ;
vc:standardizedBy ngm:ieee-control-systems-society ;
vc:standardizedBy ngm:ifac ;
vc:standardizedBy ngm:isa-95 ;
vc:supports ngm:aerospace-engineering ;
vc:supports ngm:autonomous-vehicle ;
vc:supports ngm:biomedical-engineering ;
vc:supports ngm:hvac-systems ;
vc:supports ngm:power-systems ;
vc:supports ngm:process-industries ;
vc:supports ngm:robotics ;
vc:uses ngm:bode-plot ;
vc:uses ngm:cost-function ;
vc:uses ngm:lyapunov-function ;
vc:uses ngm:nyquist-diagram ;
vc:uses ngm:root-locus ;
vc:uses ngm:state-space-model ;
vc:uses ngm:transfer-function .
ngm:controllaw a skos:Concept ;
rdfs:label "Controllaw"@en .
ngm:controlled-illumination a owl:Class ;
rdfs:comment "Controlled illumination is the deliberate management of light source position, intensity, and spectrum during image capture so that resulting measurements are consistent and repeatable. It is used in camera calibration and optical calibration targets to remove ambient lighting variability that would otherwise bias corner or feature detection. Structured and patterned illumination variants are also used to actively encode depth or surface information into captured images."@en ;
rdfs:label "Controlled Illumination"@en ;
rdfs:subClassOf ngm:camera-calibration ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "controlled-illumination" ;
vc:sourceDomain "spatial-computing" .
ngm:controlled-rollout a skos:Concept ;
rdfs:label "Controlled Rollout"@en .
ngm:controlled-vocabularies a owl:Class ;
rdfs:comment "Standardized sets of terms, phrases, and hierarchical relationships used to describe and organize information within knowledge management systems, databases, and metadata schemas, ensuring consistent indexing, retrieval, and interoperability across digital platforms and virtual environments."@en ;
rdfs:label "Controlled Vocabularies"@en ;
rdfs:subClassOf ngm:knowledge-organization ;
rdfs:subClassOf ngm:sc-standards-and-interop ;
rdfs:subClassOf _:r5755 ;
rdfs:subClassOf _:r5756 ;
rdfs:subClassOf _:r5757 ;
rdfs:subClassOf _:r5758 ;
rdfs:subClassOf _:r5759 ;
skos:broader ngm:sc-standards-and-interop ;
vc:bridgesTo ngm:knowledge-organization ;
vc:bridgesTo ngm:telecollaboration ;
vc:enables ngm:information-retrieval ;
vc:enables ngm:on-chain-data-indexing ;
vc:enables ngm:semantic-interoperability ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:governance ;
vc:requires ngm:metadata-standards ;
vc:requires ngm:taxonomy ;
vc:slug "controlled-vocabularies" ;
vc:sourceDomain "spatial-computing" .
ngm:controlled-vocabulary a owl:Class ;
rdfs:comment "A restricted list of standardized terms or phrases used within a specific domain for consistent cataloging, tagging, and indexing, where users may only apply terms from the approved list to ensure uniform description and enable reliable information retrieval across systems and platforms."@en ;
rdfs:label "Controlled Vocabulary"@en ;
rdfs:subClassOf ngm:information-architecture ;
rdfs:subClassOf _:r5760 ;
rdfs:subClassOf _:r5761 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:semantic-web-linked-data-standard ;
vc:contrastsWith ngm:folksonomy ;
vc:contrastsWith ngm:free-text-search ;
vc:contrastsWith ngm:ontology ;
vc:dependsOn ngm:metadata-schema ;
vc:dependsOn ngm:natural-language-processing ;
vc:enables ngm:content-discovery ;
vc:enables ngm:data-standardization ;
vc:enables ngm:faceted-classification ;
vc:enables ngm:information-retrieval ;
vc:enables ngm:semantic-interoperability ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:skos-vocabulary ;
vc:isPartOf ngm:knowledge-organization-system ;
vc:qualityScore "0.7"^^xsd:float ;
vc:relatedTo ngm:dublin-core ;
vc:relatedTo ngm:information-retrieval ;
vc:requires ngm:domain-expertise ;
vc:requires ngm:process ;
vc:requires ngm:term-governance ;
vc:slug "controlled-vocabulary" ;
vc:sourceDomain "data" ;
vc:standardizedBy ngm:iso-25964 ;
vc:supports ngm:knowledge-management ;
vc:uses ngm:taxonomy ;
vc:uses ngm:thesaurus .
ngm:controller a owl:Class ;
rdfs:comment "A Controller is a computational or hardware module that receives a reference setpoint and measured feedback signals, applies a control law or learned policy, and generates command signals that drive a plant or process towards desired states. Controllers span a spectrum from classical linear regulators such as PID and LQR to nonlinear model-based controllers such as Model Predictive Control and computed-torque methods, as well as data-driven approaches including neural network policies trained via reinforcement learning. Operating within closed-loop feedback architectures, the controller continuously computes an error signal — the difference between desired and measured output — and produces corrective actuation to minimise that error subject to stability and performance constraints."@en ;
rdfs:label "Controller"@en ;
rdfs:subClassOf ngm:robo-actuation-and-control ;
rdfs:subClassOf _:r5762 ;
rdfs:subClassOf _:r5763 ;
rdfs:subClassOf _:r5764 ;
rdfs:subClassOf _:r5765 ;
rdfs:subClassOf _:r5766 ;
skos:broader ngm:robo-actuation-and-control ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:neural-network ;
vc:bridgesTo ngm:reinforcement-learning ;
vc:contrastsWith ngm:manual-control ;
vc:contrastsWith ngm:open-loop-control ;
vc:dependsOn ngm:real-time-computing ;
vc:dependsOn ngm:system-identification ;
vc:enables ngm:motion-planning ;
vc:enables ngm:robot-control ;
vc:enables ngm:stability ;
vc:enables ngm:trajectory-tracking ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:control-output ;
vc:hasPart ngm:error-signal ;
vc:hasPart ngm:reference-setpoint ;
vc:implements ngm:linear-quadratic-regulator ;
vc:implements ngm:model-predictive-control ;
vc:implements ngm:reinforcement-learning-policy ;
vc:isPartOf ngm:closed-loop-control ;
vc:isPartOf ngm:cyber-physical-systems ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:dynamics ;
vc:relatedTo ngm:kalman-filter ;
vc:relatedTo ngm:kinematics ;
vc:relatedTo ngm:state-observer ;
vc:requires ngm:actuator ;
vc:requires ngm:feedback-loop ;
vc:requires ngm:plant-model ;
vc:requires ngm:sensor ;
vc:slug "controller" ;
vc:sourceDomain "robotics" ;
vc:uses ngm:control-law ;
vc:uses ngm:feedback-control ;
vc:uses ngm:pid-controller ;
vc:uses ngm:state-space-model .
ngm:controller-based-input a skos:Concept ;
rdfs:label "Controller Based Input"@en .
ngm:controller-operations a skos:Concept ;
rdfs:label "Controller Operations"@en .
ngm:controllertuning a skos:Concept ;
rdfs:label "Controllertuning"@en .
ngm:controlnet a skos:Concept ;
rdfs:label "Controlnet"@en .
ngm:controlnet-node a skos:Concept ;
rdfs:label "Controlnet Node"@en .
ngm:controlnet-plus-plus a skos:Concept ;
rdfs:label "Controlnet Plus Plus"@en .
ngm:controlnet-xs a skos:Concept ;
rdfs:label "Controlnet Xs"@en .
ngm:convai a skos:Concept ;
rdfs:label "Convai"@en .
ngm:convection-zone a owl:Class ;
rdfs:label "Convection Zone"@en ;
rdfs:subClassOf ngm:stellar-interior ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:astronomy ;
vc:slug "convection-zone" ;
vc:sourceDomain "space-science-and-systems" .
ngm:conventional-finance a skos:Concept ;
rdfs:label "Conventional Finance"@en .
ngm:conventional-investing a skos:Concept ;
rdfs:label "Conventional Investing"@en .
ngm:convergence a owl:Class ;
rdfs:comment "Technological Convergence is the macro-level process by which previously distinct technologies, disciplines, and sociotechnical systems merge, overlap, and mutually reinforce to produce qualitatively new capabilities, applications, and social configurations that none of the converging components ..."@en ;
rdfs:label "Convergence"@en ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:digital-transformation ;
rdfs:subClassOf ngm:general-purpose-technology ;
rdfs:subClassOf ngm:innovation-systems ;
rdfs:subClassOf ngm:sociotechnical-systems ;
rdfs:subClassOf ngm:technology-management ;
rdfs:subClassOf _:r5769 ;
rdfs:subClassOf _:r5770 ;
rdfs:subClassOf _:r5771 ;
rdfs:subClassOf _:r5772 ;
rdfs:subClassOf _:r5773 ;
rdfs:subClassOf _:r5774 ;
rdfs:subClassOf _:r5775 ;
rdfs:subClassOf _:r5776 ;
rdfs:subClassOf _:r5777 ;
rdfs:subClassOf _:r5778 ;
rdfs:subClassOf _:r5779 ;
rdfs:subClassOf _:r5780 ;
skos:broader ngm:ai-research-area ;
skos:broader ngm:ai-technique ;
vc:contrastsWith ngm:digital-divide ;
vc:contrastsWith ngm:silo-innovation ;
vc:contrastsWith ngm:singularity ;
vc:contrastsWith ngm:technology-lock-in ;
vc:dependsOn ngm:cloud-computing ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:quantum-mechanics ;
vc:dependsOn ngm:semiconductor-fabrication ;
vc:dependsOn ngm:synthetic-biology ;
vc:enables ngm:artificial-general-intelligence ;
vc:enables ngm:autonomous-system ;
vc:enables ngm:embodied-ai ;
vc:enables ngm:industry-4-0 ;
vc:enables ngm:precision-medicine ;
vc:enables ngm:singularity ;
vc:enables ngm:smart-cities ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ai-and-blockchain ;
vc:hasPart ngm:biocomputing ;
vc:hasPart ngm:cyber-physical-systems ;
vc:hasPart ngm:digital-twin ;
vc:hasPart ngm:edge-computing ;
vc:hasPart ngm:internet-of-things ;
vc:hasPart ngm:nbic-convergence ;
vc:hasPart ngm:platform-economy ;
vc:hasPart ngm:quantum-computation-paradigm ;
vc:hasPart ngm:spatial-computing ;
vc:hasPart ngm:spatial-computing-paradigm ;
vc:implements ngm:digital-twin ;
vc:implements ngm:general-purpose-technology-theory ;
vc:implements ngm:platform-economy ;
vc:implements ngm:schumpeterian-innovation ;
vc:implements ngm:systems-of-systems-design ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:disruptive-innovation ;
vc:relatedTo ngm:emerging-technologies ;
vc:relatedTo ngm:moore-s-law ;
vc:relatedTo ngm:nbic-convergence ;
vc:relatedTo ngm:network-effects ;
vc:relatedTo ngm:platform-economy ;
vc:requires ngm:cross-domain-research-infrastructure ;
vc:requires ngm:interoperability-protocol ;
vc:requires ngm:interoperability-protocols ;
vc:requires ngm:moore-s-law ;
vc:requires ngm:open-standard ;
vc:requires ngm:open-standards ;
vc:requires ngm:regulatory-coordination ;
vc:slug "convergence" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:ieee-standards-association ;
vc:standardizedBy ngm:iso-iec-jtc-1 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:standardizedBy ngm:oecd-sti-directorate ;
vc:supports ngm:ai-adoption ;
vc:supports ngm:digital-transformation ;
vc:supports ngm:drug-discovery ;
vc:supports ngm:industry-4-0 ;
vc:supports ngm:spatial-computing ;
vc:supports ngm:spatial-computing-paradigm ;
vc:uses ngm:blockchain ;
vc:uses ngm:edge-computing ;
vc:uses ngm:internet-of-things ;
vc:uses ngm:large-scale-pretrained-foundation-model ;
vc:uses ngm:quantum-computation-paradigm .
ngm:convergence-concept a owl:Class ;
rdfs:comment "Convergence Concept describes the synthesis of previously distinct technologies, domains, and paradigms into unified systems. In telecollaboration and spatial computing, convergence encompasses XR integration, AI-human collaboration, physical-digital fusion via digital twins, and platform unification over shared protocols such as WebXR and OpenXR. The convergence of edge and cloud computing creates hybrid architectures that optimise latency and scalability for real-time collaborative experiences."@en ;
rdfs:label "Convergence Concept"@en ;
rdfs:subClassOf ngm:infra-computing-and-cloud ;
rdfs:subClassOf _:r5767 ;
rdfs:subClassOf _:r5768 ;
skos:broader ngm:infra-computing-and-cloud ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:collaboration ;
vc:dependsOn ngm:spatial-computing ;
vc:enables ngm:digital-twin ;
vc:enables ngm:telecollaboration ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:cross-domain-bridge ;
vc:requires ngm:interoperability ;
vc:requires ngm:open-xr ;
vc:slug "convergence-concept" ;
vc:sourceDomain "infrastructure" .
ngm:convergence-criterion a skos:Concept ;
rdfs:label "Convergence Criterion"@en .
ngm:convergence-in-distribution a skos:Concept ;
rdfs:label "Convergence In Distribution"@en .
ngm:convergence-readiness-assessment a skos:Concept ;
rdfs:label "Convergence Readiness Assessment"@en .
ngm:conversable-agent a skos:Concept ;
rdfs:label "Conversable Agent"@en .
ngm:conversation-context a skos:Concept ;
rdfs:label "Conversation Context"@en .
ngm:conversation-identifier a skos:Concept ;
rdfs:label "Conversation Identifier"@en .
ngm:conversation-loop a skos:Concept ;
rdfs:label "Conversation Loop"@en .
ngm:conversation-memory a skos:Concept ;
rdfs:label "Conversation Memory"@en .
ngm:conversation-starter a skos:Concept ;
rdfs:label "Conversation Starter"@en .
ngm:conversational-ai a owl:Class ;
rdfs:comment "Conversational AI encompasses systems that engage in natural-language dialogue with humans, including chatbots, voice assistants, and large-language-model-powered interfaces. It applies natural language processing, language modeling, dialogue management, and speech recognition to understand intent and generate contextually appropriate responses."@en ;
rdfs:label "Conversational AI"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf ngm:human-computer-interaction ;
rdfs:subClassOf ngm:natural-language-processing ;
rdfs:subClassOf _:r5781 ;
rdfs:subClassOf _:r5782 ;
rdfs:subClassOf _:r5783 ;
rdfs:subClassOf _:r5784 ;
rdfs:subClassOf _:r5785 ;
rdfs:subClassOf _:r5786 ;
rdfs:subClassOf _:r5787 ;
rdfs:subClassOf _:r5788 ;
rdfs:subClassOf _:r5789 ;
rdfs:subClassOf _:r5790 ;
rdfs:subClassOf _:r5791 ;
rdfs:subClassOf _:r5792 ;
rdfs:subClassOf _:r5793 ;
rdfs:subClassOf _:r5794 ;
rdfs:subClassOf _:r5795 ;
rdfs:subClassOf _:r5796 ;
rdfs:subClassOf _:r5797 ;
rdfs:subClassOf _:r5798 ;
skos:broader ngm:artificial-intelligence ;
vc:bridgesTo ngm:autonomous-robot ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:spatial-computing ;
vc:contrastsWith ngm:batch-processing ;
vc:contrastsWith ngm:form-based-interface ;
vc:contrastsWith ngm:rule-based-systems ;
vc:contrastsWith ngm:scripted-chatbot ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:gpu-compute ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:pre-trained-language-model ;
vc:dependsOn ngm:speech-processing ;
vc:enables ngm:accessibility ;
vc:enables ngm:agentic-ai-workflow ;
vc:enables ngm:customer-service-automation ;
vc:enables ngm:human-robot-interaction ;
vc:enables ngm:intelligent-tutoring-system ;
vc:enables ngm:medical-dialogue-system ;
vc:enables ngm:virtual-assistant ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:chatbot ;
vc:hasPart ngm:chatbots ;
vc:hasPart ngm:context-management ;
vc:hasPart ngm:dialogue-state-tracking ;
vc:hasPart ngm:dialogue-system ;
vc:hasPart ngm:intent-recognition ;
vc:hasPart ngm:knowledge-base ;
vc:hasPart ngm:natural-language-understanding ;
vc:hasPart ngm:sentiment-analysis ;
vc:hasPart ngm:speech-recognition ;
vc:hasPart ngm:text-to-speech ;
vc:hasPart ngm:voice-interaction ;
vc:implements ngm:coreference-resolution ;
vc:implements ngm:dialogue-state-tracking ;
vc:implements ngm:intent-classification ;
vc:implements ngm:named-entity-recognition ;
vc:implements ngm:response-generation ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:information-retrieval ;
vc:relatedTo ngm:knowledge-graph ;
vc:relatedTo ngm:multimodal-ai-architecture-ai ;
vc:relatedTo ngm:question-answering ;
vc:relatedTo ngm:retrieval-augmented-generation ;
vc:requires ngm:context-management ;
vc:requires ngm:knowledge-base ;
vc:requires ngm:language-modeling ;
vc:requires ngm:machine-learning-discipline ;
vc:requires ngm:neural-network-text-tokenisation ;
vc:requires ngm:training-data ;
vc:slug "conversational-ai" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:iso-iec-jtc1-sc42 ;
vc:standardizedBy ngm:nist-ai-standards ;
vc:standardizedBy ngm:w3-c ;
vc:supports ngm:autonomous-robot ;
vc:supports ngm:digital-twin ;
vc:supports ngm:human-robot-interaction ;
vc:supports ngm:multimodal-ai-architecture-ai ;
vc:supports ngm:spatial-computing ;
vc:uses ngm:attention-mechanism ;
vc:uses ngm:automatic-speech-recognition ;
vc:uses ngm:embedding ;
vc:uses ngm:large-language-models ;
vc:uses ngm:reinforcement-learning-from-human-feedback ;
vc:uses ngm:retrieval-augmented-generation ;
vc:uses ngm:speech-processing ;
vc:uses ngm:speech-recognition ;
vc:uses ngm:text-to-speech ;
vc:uses ngm:transformer-architecture .
ngm:conversational-ai-classification a skos:Concept ;
rdfs:label "Conversational AI Classification"@en .
ngm:conversational-ai-without-retrieval a skos:Concept ;
rdfs:label "Conversational AI Without Retrieval"@en .
ngm:conversational-analytics a skos:Concept ;
rdfs:label "Conversational Analytics"@en .
ngm:conversational-commerce a owl:Class ;
rdfs:comment "Conversational commerce is the practice of facilitating buying and selling through interactive, natural-language interfaces such as chatbots and AI assistants."@en ;
rdfs:label "Conversational Commerce"@en ;
rdfs:subClassOf ngm:advertising ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:advertising ;
vc:relatedTo ngm:digital-marketing ;
vc:relatedTo ngm:model ;
vc:slug "conversational-commerce" ;
vc:sourceDomain "economics" .
ngm:conversational-interface a skos:Concept ;
rdfs:label "Conversational Interface"@en .
ngm:conversational-memory a skos:Concept ;
rdfs:label "Conversational Memory"@en .
ngm:conversational-search a skos:Concept ;
rdfs:label "Conversational Search"@en .
ngm:conversational-web-access a skos:Concept ;
rdfs:label "Conversational Web Access"@en .
ngm:conversion-pipeline a owl:Class ;
rdfs:comment "An automated workflow process that transforms digital data or assets from one format, schema, or representation to another, enabling interoperability and compatibility across heterogeneous systems and platforms."@en ;
rdfs:label "Conversion Pipeline"@en ;
rdfs:subClassOf ngm:sc-standards-and-interop ;
rdfs:subClassOf _:r5799 ;
rdfs:subClassOf _:r5800 ;
rdfs:subClassOf _:r5801 ;
skos:broader ngm:sc-standards-and-interop ;
vc:bridgesTo ngm:computer-vision ;
vc:dependsOn ngm:data-validation ;
vc:dependsOn ngm:metadata-management ;
vc:dependsOn ngm:schema-registry ;
vc:enables ngm:asset-optimization ;
vc:enables ngm:cross-platform-interoperability ;
vc:enables ngm:data-harmonization ;
vc:enables ngm:format-migration ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:error-handler ;
vc:hasPart ngm:format-parser ;
vc:hasPart ngm:output-generator ;
vc:hasPart ngm:transformation-engine ;
vc:hasPart ngm:validation-module ;
vc:isPartOf ngm:asset-pipeline ;
vc:isPartOf ngm:data-processing ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:asset-metadata ;
vc:requires ngm:conversion-rules ;
vc:requires ngm:data-schema ;
vc:requires ngm:format-specification ;
vc:slug "conversion-pipeline" ;
vc:sourceDomain "spatial-computing" .
ngm:conversion-rate-optimisation a owl:Class ;
rdfs:comment "Conversion rate optimisation (CRO) is the systematic practice of increasing the percentage of visitors to a digital property who complete a desired action — purchasing, subscribing, registering — by forming hypotheses about user behaviour and testing changes to copy, design, pricing, and flow. It combines quantitative instrumentation such as funnel analytics and A/B and multivariate testing with qualitative research such as session recordings and user interviews, turning traffic acquired through marketing into measurable business outcomes."@en ;
rdfs:label "Conversion Rate Optimisation"@en ;
rdfs:subClassOf ngm:digital-marketing ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:e-commerce ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:user-experience ;
vc:slug "conversion-rate-optimisation" ;
vc:sourceDomain "data" ;
vc:uses ngm:a-b-testing .
ngm:conversion-rules a skos:Concept ;
rdfs:label "Conversion Rules"@en .
ngm:conversion-tools a skos:Concept ;
rdfs:label "Conversion Tools"@en .
ngm:convex-analysis a skos:Concept ;
rdfs:label "Convex Analysis"@en .
ngm:convex-finance a owl:Class ;
rdfs:comment "Convex Finance is a decentralised finance (DeFi) meta-protocol built on Ethereum that enables Curve Finance liquidity providers and CRV holders to earn enhanced rewards without individually locking their own CRV tokens as veCRV. By aggregating vote-escrowed CRV (veCRV) from users who deposit CRV in exchange for cvxCRV, Convex accumulates collective governance and boost power which it redistributes pro-rata to depositors, eliminating the individual capital lockup barrier inherent in Curve's vote-escrow tokenomics. The protocol's native CVX token governs allocation of this aggregated veCRV voting power via vlCVX staking, creating a secondary governance layer — the so-called Curve Wars — in which DeFi protocols competitively bribe CVX holders to direct CRV emissions toward their own liquidity pools."@en ;
rdfs:label "Convex Finance"@en ;
rdfs:subClassOf ngm:de-fi-protocol ;
rdfs:subClassOf _:r5802 ;
rdfs:subClassOf _:r5803 ;
vc:bridgesTo ngm:mechanism-design ;
vc:bridgesTo ngm:on-chain-governance ;
vc:contrastsWith ngm:aura-finance ;
vc:contrastsWith ngm:concentrated-liquidity ;
vc:contrastsWith ngm:yearn ;
vc:dependsOn ngm:liquidity-mining ;
vc:dependsOn ngm:stablecoin ;
vc:enables ngm:bribe-economy ;
vc:enables ngm:liquidity-provision ;
vc:enables ngm:meta-governance ;
vc:enables ngm:yield-farming ;
vc:enables ngm:yield-generation ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:curve-wars ;
vc:isPartOf ngm:decentralized-finance-de-fi ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:dao ;
vc:relatedTo ngm:decentralized-autonomous-organization ;
vc:relatedTo ngm:frax-finance ;
vc:relatedTo ngm:total-value-locked ;
vc:requires ngm:ethereum ;
vc:requires ngm:smart-contract ;
vc:requires ngm:vote-escrow-tokenomics ;
vc:slug "convex-finance" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:automated-market-maker ;
vc:uses ngm:curve-finance ;
vc:uses ngm:governance-token ;
vc:uses ngm:liquidity-pool ;
vc:uses ngm:token-economics .
ngm:convex-function a skos:Concept ;
rdfs:label "Convex Function"@en .
ngm:convex-optimisation a owl:Class ;
rdfs:comment "Convex optimisation is the mathematical discipline concerned with minimising convex objective functions over convex feasible sets, exploiting the fundamental property that every local minimum is also a global minimum. This structural guarantee enables the design of polynomial-time algorithms — such as interior-point methods, subgradient descent, and proximal methods — that reliably find exact or near-exact solutions. The field is grounded in convex analysis and duality theory (Lagrangian and Fenchel duality), and underpins a vast range of applications spanning machine learning, signal processing, control systems, finance, and operations research. Canonical problem classes include linear programming, quadratic programming, second-order cone programming, and semidefinite programming."@en ;
rdfs:label "Convex Optimisation"@en ;
rdfs:subClassOf ngm:applied-mathematics ;
rdfs:subClassOf ngm:mathematical-optimisation ;
rdfs:subClassOf ngm:numerical-methods ;
rdfs:subClassOf ngm:optimisation ;
rdfs:subClassOf _:r5804 ;
rdfs:subClassOf _:r5805 ;
rdfs:subClassOf _:r5806 ;
rdfs:subClassOf _:r5807 ;
rdfs:subClassOf _:r5808 ;
rdfs:subClassOf _:r5809 ;
vc:bridgesTo ngm:deep-learning ;
vc:bridgesTo ngm:reinforcement-learning ;
vc:bridgesTo ngm:signal-processing ;
vc:contrastsWith ngm:combinatorial-optimisation ;
vc:contrastsWith ngm:integer-programming ;
vc:contrastsWith ngm:non-convex-optimisation ;
vc:contrastsWith ngm:stochastic-optimisation ;
vc:dependsOn ngm:duality-theory ;
vc:dependsOn ngm:linear-algebra ;
vc:dependsOn ngm:numerical-methods ;
vc:dependsOn ngm:real-analysis ;
vc:enables ngm:bayesian-optimisation ;
vc:enables ngm:beamforming ;
vc:enables ngm:compressed-sensing ;
vc:enables ngm:lasso-regression ;
vc:enables ngm:logistic-regression ;
vc:enables ngm:model-predictive-control ;
vc:enables ngm:optimal-control ;
vc:enables ngm:portfolio-optimisation ;
vc:enables ngm:sparse-coding ;
vc:enables ngm:support-vector-machine ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:convex-analysis ;
vc:hasPart ngm:duality-theory ;
vc:hasPart ngm:geometric-programming ;
vc:hasPart ngm:kkt-conditions ;
vc:hasPart ngm:linear-programming ;
vc:hasPart ngm:quadratic-programming ;
vc:hasPart ngm:second-order-cone-programming ;
vc:hasPart ngm:semidefinite-programming ;
vc:implements ngm:accelerated-gradient-descent ;
vc:implements ngm:alternating-direction-method-of-multipliers ;
vc:implements ngm:ellipsoid-method ;
vc:implements ngm:frank-wolfe-algorithm ;
vc:implements ngm:gradient-descent ;
vc:implements ngm:interior-point-method ;
vc:implements ngm:proximal-gradient-method ;
vc:implements ngm:subgradient-method ;
vc:isPartOf ngm:optimisation ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:control-theory ;
vc:relatedTo ngm:functional-analysis ;
vc:relatedTo ngm:information-theory ;
vc:relatedTo ngm:operations-research ;
vc:relatedTo ngm:statistics ;
vc:relatedTo ngm:stochastic-optimisation ;
vc:requires ngm:calculus ;
vc:requires ngm:convex-analysis ;
vc:requires ngm:functional-analysis ;
vc:requires ngm:linear-algebra ;
vc:requires ngm:real-analysis ;
vc:slug "convex-optimisation" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:ieee-computational-intelligence-society ;
vc:standardizedBy ngm:mathematical-programming-society ;
vc:standardizedBy ngm:siam ;
vc:supports ngm:deep-learning ;
vc:supports ngm:federated-learning ;
vc:supports ngm:machine-learning-discipline ;
vc:supports ngm:operations-research ;
vc:supports ngm:reinforcement-learning ;
vc:supports ngm:robotics ;
vc:supports ngm:signal-processing ;
vc:uses ngm:conjugate-function ;
vc:uses ngm:convex-function ;
vc:uses ngm:convex-set ;
vc:uses ngm:epigraph ;
vc:uses ngm:kkt-conditions ;
vc:uses ngm:lagrange-multipliers ;
vc:uses ngm:slater-s-condition ;
vc:uses ngm:subdifferential .
ngm:convex-optimization a skos:Concept ;
rdfs:label "Convex Optimization"@en .
ngm:convex-set a skos:Concept ;
rdfs:label "Convex Set"@en .
ngm:conveyor-system a skos:Concept ;
rdfs:label "Conveyor System"@en .
ngm:conviction-accumulation-function a skos:Concept ;
rdfs:label "Conviction Accumulation Function"@en .
ngm:conviction-voting a owl:Class ;
rdfs:comment "Conviction Voting is a continuous-time, conviction-weighted decentralised governance mechanism — originally formalised by Block Science researchers Jeff Emmett, Michael Zargham and Jessica Zartler in the 2019 working paper Conviction Voting: A Novel Continuous Decision Making Alternative to G..."@en ;
rdfs:label "Conviction Voting"@en ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
rdfs:subClassOf ngm:continuous-decision-making ;
rdfs:subClassOf ngm:dao-governance-mechanism ;
rdfs:subClassOf ngm:token-weighted-governance ;
rdfs:subClassOf ngm:treasury-allocation-mechanism ;
rdfs:subClassOf ngm:voting-system ;
rdfs:subClassOf _:r5810 ;
rdfs:subClassOf _:r5811 ;
rdfs:subClassOf _:r5812 ;
skos:broader ngm:bc-governance-and-regulation ;
vc:contrastsWith ngm:compound-governor-bravo ;
vc:contrastsWith ngm:futarchy ;
vc:contrastsWith ngm:optimism-retropgf ;
vc:contrastsWith ngm:polkadot-opengov ;
vc:contrastsWith ngm:quadratic-voting ;
vc:contrastsWith ngm:snapshot-off-chain-voting ;
vc:contrastsWith ngm:tally-on-chain-governance ;
vc:dependsOn ngm:block-science-theory ;
vc:dependsOn ngm:cadcad-simulation ;
vc:dependsOn ngm:continuous-time-dynamical-systems ;
vc:dependsOn ngm:mechanism-design ;
vc:dependsOn ngm:token-engineering ;
vc:enables ngm:last-minute-attack-resistance ;
vc:enables ngm:organic-proposal-prioritisation ;
vc:enables ngm:passive-participation-tolerance ;
vc:enables ngm:public-goods-funding ;
vc:enables ngm:time-weighted-preference-expression ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:conviction-accumulation-function ;
vc:hasPart ngm:decay-constant-alpha ;
vc:hasPart ngm:minimum-conviction-threshold ;
vc:hasPart ngm:proposal-executor ;
vc:hasPart ngm:proposal-stake-ledger ;
vc:hasPart ngm:spending-limit ;
vc:hasPart ngm:trigger-threshold-function ;
vc:implements ngm:continuous-time-preference-aggregation ;
vc:implements ngm:dynamic-spending-limit ;
vc:implements ngm:exponential-moving-average-aggregation ;
vc:implements ngm:symmetric-stake-decay ;
vc:implements ngm:threshold-triggered-execution ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:1-hive ;
vc:relatedTo ngm:aragon ;
vc:relatedTo ngm:block-science ;
vc:relatedTo ngm:celeste ;
vc:relatedTo ngm:commons-stack ;
vc:relatedTo ngm:gardens-framework ;
vc:relatedTo ngm:giveth ;
vc:relatedTo ngm:praise ;
vc:relatedTo ngm:token-engineering-commons ;
vc:requires ngm:block-indexed-time-reference ;
vc:requires ngm:governance-token ;
vc:requires ngm:proposal-registry ;
vc:requires ngm:settlement-layer ;
vc:requires ngm:stake-registry ;
vc:requires ngm:treasury-pool ;
vc:slug "conviction-voting" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:1hive-gardens-specification ;
vc:standardizedBy ngm:aragon-conviction-voting-app-abi ;
vc:standardizedBy ngm:cadcad-reference-model ;
vc:standardizedBy ngm:commons-stack-abc-spec ;
vc:standardizedBy ngm:emmett-zargham-zartler-2019-paper ;
vc:supports ngm:augmented-bonding-curve-communities ;
vc:supports ngm:common-pool-resources ;
vc:supports ngm:dao-treasury-operations ;
vc:supports ngm:public-goods-funding ;
vc:supports ngm:regenerative-cryptoeconomics ;
vc:uses ngm:block-number-as-discrete-time ;
vc:uses ngm:exponential-moving-average ;
vc:uses ngm:lazy-conviction-evaluation ;
vc:uses ngm:solidity ;
vc:uses ngm:token-stake-locking .
ngm:convolution a owl:Class ;
rdfs:comment "Convolution is a mathematical operation that combines two functions by sliding one (the kernel or filter) over another (the input signal or image) and computing a weighted sum of overlapping values at each position, producing a third function that expresses how the shape of one modifies the other. In deep learning and signal processing it provides a translation-equivariant mechanism for local feature extraction with shared parameter weights. The discrete 2D form underpins convolutional neural networks; the continuous form via the Convolution Theorem connects to Fourier analysis and frequency-domain filtering."@en ;
rdfs:label "Convolution"@en ;
rdfs:subClassOf ngm:mathematical-operation ;
rdfs:subClassOf ngm:signal-processing ;
rdfs:subClassOf _:r5813 ;
rdfs:subClassOf _:r5814 ;
rdfs:subClassOf _:r5815 ;
rdfs:subClassOf _:r5816 ;
vc:bridgesTo ngm:graph-neural-network ;
vc:bridgesTo ngm:radar-signal-processing ;
vc:contrastsWith ngm:attention-mechanism ;
vc:contrastsWith ngm:recurrent-neural-network ;
vc:contrastsWith ngm:self-attention ;
vc:dependsOn ngm:fourier-analysis ;
vc:dependsOn ngm:linear-algebra ;
vc:enables ngm:audio-processing ;
vc:enables ngm:convolutional-neural-network ;
vc:enables ngm:feature-extraction ;
vc:enables ngm:image-classification ;
vc:enables ngm:image-segmentation ;
vc:enables ngm:object-detection ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:feature-map ;
vc:hasPart ngm:kernel ;
vc:hasPart ngm:padding ;
vc:hasPart ngm:receptive-field ;
vc:hasPart ngm:stride ;
vc:implements ngm:local-connectivity ;
vc:implements ngm:translation-equivariance ;
vc:implements ngm:weight-sharing ;
vc:qualityScore "0.92"^^xsd:float ;
vc:relatedTo ngm:activation-function ;
vc:relatedTo ngm:batch-normalisation ;
vc:relatedTo ngm:graph-neural-network ;
vc:relatedTo ngm:image-processing ;
vc:relatedTo ngm:neural-network ;
vc:relatedTo ngm:pooling-layer ;
vc:relatedTo ngm:transfer-learning ;
vc:relatedTo ngm:transformer-architecture ;
vc:requires ngm:gpu-acceleration ;
vc:requires ngm:linear-algebra ;
vc:requires ngm:matrix-multiplication ;
vc:slug "convolution" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:ieee-signal-processing-society ;
vc:supports ngm:computer-vision ;
vc:supports ngm:deep-learning ;
vc:supports ngm:natural-language-processing ;
vc:supports ngm:signal-processing ;
vc:uses ngm:backpropagation ;
vc:uses ngm:fast-fourier-transform ;
vc:uses ngm:matrix-multiplication ;
vc:uses ngm:stochastic-gradient-descent .
ngm:convolutional-feature-extraction a skos:Concept ;
rdfs:label "Convolutional Feature Extraction"@en .
ngm:convolutional-layer a skos:Concept ;
rdfs:label "Convolutional Layer"@en .
ngm:convolutional-neural-network a owl:Class ;
rdfs:comment "A Convolutional Neural Network (CNN) is a feed-forward deep learning architecture that applies learned convolutional filters across spatial dimensions of input data, enabling hierarchical feature extraction from images and other grid-structured inputs. Weight sharing and local receptive fields make CNNs highly parameter-efficient for visual recognition tasks including image classification, object detection, and semantic segmentation."@en ;
rdfs:label "Convolutional Neural Network"@en ;
rdfs:subClassOf ngm:ai-model-architecture ;
rdfs:subClassOf _:r5817 ;
rdfs:subClassOf _:r5818 ;
rdfs:subClassOf _:r5819 ;
rdfs:subClassOf _:r5820 ;
skos:broader ngm:ai-model-architecture ;
vc:bridgesTo ngm:augmented-reality ;
vc:bridgesTo ngm:autonomous-driving-perception ;
vc:contrastsWith ngm:recurrent-neural-network ;
vc:contrastsWith ngm:transformer-architecture ;
vc:dependsOn ngm:gradient-descent ;
vc:dependsOn ngm:weight-sharing ;
vc:enables ngm:feature-extraction ;
vc:enables ngm:image-classification ;
vc:enables ngm:object-detection ;
vc:enables ngm:semantic-segmentation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:activation-function ;
vc:hasPart ngm:convolutional-layer ;
vc:hasPart ngm:pooling-layer ;
vc:implements ngm:feedforward-neural-network ;
vc:isPartOf ngm:deep-learning ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:adversarial-robustness ;
vc:requires ngm:gpu-computing ;
vc:requires ngm:training-data ;
vc:slug "convolutional-neural-network" ;
vc:sourceDomain "machine-learning" ;
vc:supports ngm:computer-vision ;
vc:supports ngm:medical-image-analysis ;
vc:uses ngm:backpropagation ;
vc:uses ngm:batch-normalisation ;
vc:uses ngm:stochastic-gradient-descent ;
vc:uses ngm:training-data ;
vc:uses ngm:transfer-learning .
ngm:cook-torrance-model a skos:Concept ;
rdfs:label "Cook Torrance Model"@en .
ngm:cookie a skos:Concept ;
rdfs:label "Cookie"@en .
ngm:cookie-policy a skos:Concept ;
rdfs:label "Cookie Policy"@en .
ngm:cooling-capacity a skos:Concept ;
rdfs:label "Cooling Capacity"@en .
ngm:cooling-system a owl:Class ;
rdfs:comment "A system that removes heat from equipment to keep it within safe operating temperatures. In computing it covers air, liquid, and immersion methods used in servers and data centres."@en ;
rdfs:label "Cooling System"@en ;
rdfs:subClassOf ngm:hardware ;
rdfs:subClassOf _:r5821 ;
vc:bridgesTo ngm:renewable-energy ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:hardware ;
vc:slug "cooling-system" ;
vc:sourceDomain "infrastructure" .
ngm:cooperation a skos:Concept ;
rdfs:label "Cooperation"@en .
ngm:cooperative-game-theory a owl:Class ;
rdfs:comment "Cooperative game theory is the branch of game theory that studies how groups of agents can form coalitions and how the value they jointly create should be divided among members. Rather than focusing on individual strategies, it analyses solution concepts such as the core and the Shapley value that capture fair or stable allocations of collective payoff. Its allocation principles underpin applications from economics and mechanism design to feature attribution in explainable machine learning."@en ;
rdfs:label "Cooperative Game Theory"@en ;
rdfs:subClassOf ngm:game-theory ;
rdfs:subClassOf _:r5822 ;
rdfs:subClassOf _:r5823 ;
rdfs:subClassOf _:r5824 ;
rdfs:subClassOf _:r5825 ;
vc:bridgesTo ngm:economics ;
vc:bridgesTo ngm:explainable-ai ;
vc:contrastsWith ngm:nash-equilibrium ;
vc:enables ngm:fairness ;
vc:enables ngm:shap ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:shapley-value ;
vc:hasPart ngm:utility-function ;
vc:isPartOf ngm:game-theory ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:game-theory ;
vc:relatedTo ngm:social-choice-theory ;
vc:requires ngm:mechanism-design ;
vc:requires ngm:utility-function ;
vc:slug "cooperative-game-theory" ;
vc:sourceDomain "ai" ;
vc:supports ngm:mechanism-design ;
vc:supports ngm:social-choice-theory ;
vc:uses ngm:shapley-value .
ngm:cooperative-learning a skos:Concept ;
rdfs:label "Cooperative Learning"@en .
ngm:coordinate-ascent-variational-inference a skos:Concept ;
rdfs:label "Coordinate Ascent Variational Inference"@en .
ngm:coordinate-based-network a skos:Concept ;
rdfs:label "Coordinate Based Network"@en .
ngm:coordinate-conversion a owl:Class ;
rdfs:label "Coordinate Conversion"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:coordinate-transformation ;
vc:relatedTo ngm:map-projection ;
vc:slug "coordinate-conversion" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:coordinate-difference a skos:Concept ;
rdfs:label "Coordinate Difference"@en .
ngm:coordinate-epoch a owl:Class ;
rdfs:label "Coordinate Epoch"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:space-reference-systems ;
vc:slug "coordinate-epoch" ;
vc:sourceDomain "space-science-and-systems" .
ngm:coordinate-frame a owl:Class ;
rdfs:comment "A coordinate frame is a reference system defined by an origin and a set of axes against which positions, orientations, and motions are measured. In robotics and perception, multiple frames (world, base, sensor, tool) are related by rigid-body transforms so that data from different sources can be expressed consistently. Correct frame management is essential for sensor fusion, motion planning, and collision checking."@en ;
rdfs:label "Coordinate Frame"@en ;
rdfs:subClassOf ngm:robo-navigation-and-planning ;
rdfs:subClassOf _:r5826 ;
skos:broader ngm:robo-navigation-and-planning ;
vc:bridgesTo ngm:augmented-reality ;
vc:bridgesTo ngm:spatial-computing ;
vc:contrastsWith ngm:coordinate-system ;
vc:dependsOn ngm:exteroceptive-sensor ;
vc:dependsOn ngm:inertial-measurement-unit ;
vc:enables ngm:collision-detection ;
vc:enables ngm:inverse-kinematics ;
vc:enables ngm:motion-planning ;
vc:enables ngm:sensor-fusion ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:axis-vector ;
vc:hasPart ngm:origin-point ;
vc:hasPart ngm:rotation-matrix ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:collision-detection ;
vc:relatedTo ngm:exteroceptive-sensor ;
vc:relatedTo ngm:odometry ;
vc:relatedTo ngm:transform-tree ;
vc:requires ngm:homogeneous-transformation-matrix ;
vc:requires ngm:rigid-body-transform ;
vc:slug "coordinate-frame" ;
vc:sourceDomain "robotics" ;
vc:standardizedBy ngm:denavit-hartenberg-parameters ;
vc:standardizedBy ngm:ros ;
vc:supports ngm:point-cloud ;
vc:supports ngm:robot-kinematics ;
vc:supports ngm:simultaneous-localisation-and-mapping ;
vc:uses ngm:euler-angles ;
vc:uses ngm:pose-estimation ;
vc:uses ngm:quaternion-math .
ngm:coordinate-pole a owl:Class ;
rdfs:label "Coordinate Pole"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:coordinate-system ;
vc:relatedTo ngm:geodesy ;
vc:slug "coordinate-pole" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:coordinate-reference-system a owl:Class ;
rdfs:comment "A coordinate reference system (CRS) is a framework that defines how positions are described and measured on or near the Earth's surface, combining a datum, a coordinate system, and often a map projection. It enables consistent interpretation of spatial coordinates by anchoring them to a known model of the Earth. CRSs are essential for aligning geospatial data sets and for accurate location computations."@en ;
rdfs:label "Coordinate Reference System"@en ;
rdfs:subClassOf ngm:geospatial-data ;
rdfs:subClassOf _:r5827 ;
rdfs:subClassOf _:r5828 ;
rdfs:subClassOf _:r5829 ;
vc:bridgesTo ngm:spatial-computing ;
vc:dependsOn ngm:geospatial-data ;
vc:enables ngm:geographic-information-system ;
vc:enables ngm:spatial-computing ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:geospatial-data ;
vc:isPartOf ngm:geospatial-data ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:geographic-information-system ;
vc:relatedTo ngm:spatial-computing ;
vc:requires ngm:geospatial-data ;
vc:requires ngm:gps ;
vc:slug "coordinate-reference-system" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:standards ;
vc:supports ngm:geographic-information-system ;
vc:uses ngm:gps .
ngm:coordinate-system a owl:Class ;
rdfs:comment "A coordinate system is a mathematical framework that assigns a unique ordered tuple of numbers to every point in a geometric space, enabling unambiguous specification of position, orientation, and scale. Coordinate systems establish reference frames — world, camera, object, and sensor frames — that must be composed via rigid-body or affine transforms to map quantities from one frame into another. In spatial computing, robotics, and computer vision, multiple overlapping coordinate frames coexist and their consistent management is essential for rendering, navigation, and perception tasks. The choice of convention (handedness, axis orientation, unit) and the algebraic formalism used (homogeneous matrices, quaternions, dual quaternions, Lie group elements) profoundly affects numerical stability and interoperability across software stacks."@en ;
rdfs:label "Coordinate System"@en ;
rdfs:subClassOf ngm:sc-display-and-rendering ;
rdfs:subClassOf _:r5830 ;
rdfs:subClassOf _:r5831 ;
rdfs:subClassOf _:r5832 ;
rdfs:subClassOf _:r5833 ;
skos:broader ngm:sc-display-and-rendering ;
vc:bridgesTo ngm:sensor-fusion ;
vc:bridgesTo ngm:world-model ;
vc:contrastsWith ngm:curvilinear-coordinate-system ;
vc:contrastsWith ngm:polar-coordinate-system ;
vc:dependsOn ngm:linear-algebra ;
vc:dependsOn ngm:rotation-representation ;
vc:enables ngm:3-d-rendering ;
vc:enables ngm:augmented-reality ;
vc:enables ngm:pose-estimation ;
vc:enables ngm:slam ;
vc:enables ngm:spatial-anchor ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:basis-vector ;
vc:hasPart ngm:origin ;
vc:hasPart ngm:reference-frames ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:euclidean-geometry ;
vc:relatedTo ngm:projection-model ;
vc:requires ngm:homogeneous-transformation ;
vc:requires ngm:spatial-mapping ;
vc:slug "coordinate-system" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:iso-19111 ;
vc:standardizedBy ngm:open-xr ;
vc:supports ngm:computer-vision ;
vc:supports ngm:geographic-information-system ;
vc:supports ngm:robot-kinematics ;
vc:supports ngm:scene-graph ;
vc:uses ngm:coordinate-transformation ;
vc:uses ngm:quaternion-math .
ngm:coordinate-transformation a owl:Class ;
rdfs:comment "A coordinate transformation is a mathematical mapping that converts the representation of a point, vector, or geometric object from one coordinate system or reference frame to another, preserving geometric relationships while expressing them in a new basis. In robotics and computer graphics, transformations are represented as homogeneous matrices, quaternions, or dual quaternions encoding rotation, translation, and scaling operations."@en ;
rdfs:label "Coordinate Transformation"@en ;
rdfs:subClassOf ngm:coordinate-system ;
vc:enables ngm:sensor-fusion ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:kinematics ;
vc:relatedTo ngm:reference-frames ;
vc:relatedTo ngm:rigid-body-dynamics ;
vc:slug "coordinate-transformation" ;
vc:sourceDomain "robotics" ;
vc:uses ngm:quaternion-math .
ngm:coordinated-border-management a skos:Concept ;
rdfs:label "Coordinated Border Management"@en .
ngm:coordinated-control a skos:Concept ;
rdfs:label "Coordinated Control"@en .
ngm:coordinated-swarm-behaviour a skos:Concept ;
rdfs:label "Coordinated Swarm Behaviour"@en .
ngm:coordinated-universal-time a owl:Class ;
rdfs:label "Coordinated Universal Time"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:space-reference-systems ;
vc:slug "coordinated-universal-time" ;
vc:sourceDomain "space-science-and-systems" .
ngm:coordination a skos:Concept ;
rdfs:label "Coordination"@en .
ngm:coordination-failure a skos:Concept ;
rdfs:label "Coordination Failure"@en .
ngm:coordination-free-computing a skos:Concept ;
rdfs:label "Coordination Free Computing"@en .
ngm:coordination-layer a owl:Class ;
rdfs:comment "The Coordination Layer is the cross-cutting stratum that orchestrates the work of multiple agents or services toward a shared objective. It sits above control and integration concerns and below the application goals it serves. It contains schedulers, workflow engines, consensus on task assignment, and the protocols that keep distributed actors aligned."@en ;
rdfs:label "Coordination Layer"@en ;
rdfs:subClassOf ngm:dc-protocol-and-infra ;
rdfs:subClassOf ngm:owl-thing ;
rdfs:subClassOf _:r5834 ;
rdfs:subClassOf _:r5835 ;
skos:broader ngm:dc-protocol-and-infra ;
vc:bridgesTo ngm:distributed-systems ;
vc:bridgesTo ngm:task-allocation ;
vc:enables ngm:agent-layer ;
vc:enables ngm:application-layer ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:control-layer ;
vc:requires ngm:integration-layer ;
vc:slug "coordination-layer" ;
vc:sourceDomain "distributed-systems" .
ngm:coordination-mechanisms a owl:Class ;
rdfs:comment "Coordination Mechanisms are the structural arrangements, protocols, and incentive designs that enable multiple autonomous agents—whether human organisations, software processes, or robotic systems—to align their actions toward shared goals whilst managing conflicts, resource contention, and information asymmetries. They include market-based mechanisms, hierarchical authority structures, consensus protocols, and shared state systems."@en ;
rdfs:label "Coordination Mechanisms"@en ;
rdfs:subClassOf ngm:governance-framework ;
rdfs:subClassOf _:r5836 ;
rdfs:subClassOf _:r5837 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:bridgesTo ngm:robotics ;
vc:contrastsWith ngm:market-mechanism ;
vc:dependsOn ngm:communication-protocol ;
vc:dependsOn ngm:distributed-ledger ;
vc:dependsOn ngm:information-exchange ;
vc:enables ngm:collective-action ;
vc:enables ngm:decentralised-governance ;
vc:enables ngm:multi-agent-system ;
vc:enables ngm:task-allocation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:byzantine-fault-tolerance ;
vc:hasPart ngm:voting-mechanism ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:contract-net-protocol ;
vc:relatedTo ngm:coordination-protocol ;
vc:relatedTo ngm:game-theory ;
vc:relatedTo ngm:mechanism-design ;
vc:slug "coordination-mechanisms" ;
vc:sourceDomain "governance" ;
vc:supports ngm:orchestration ;
vc:supports ngm:swarm-intelligence ;
vc:supports ngm:workflow-automation ;
vc:uses ngm:auction-mechanism ;
vc:uses ngm:consensus-mechanism ;
vc:uses ngm:incentive-structures ;
vc:uses ngm:shared-memory .
ngm:coordination-protocol a owl:Class ;
rdfs:comment "A Coordination Protocol is a formally specified set of rules, message formats, and interaction sequences that govern how distributed agents or system components communicate and synchronise their actions to achieve a common objective. It defines the obligations, permissions, and commitments of each participant at each state of an interaction, ensuring predictable collective behaviour despite independent agent decision-making."@en ;
rdfs:label "Coordination Protocol"@en ;
rdfs:subClassOf ngm:communication-protocol ;
rdfs:subClassOf _:r5838 ;
rdfs:subClassOf _:r5839 ;
rdfs:subClassOf _:r5840 ;
rdfs:subClassOf _:r5841 ;
vc:bridgesTo ngm:llm-application-framework ;
vc:bridgesTo ngm:model-context-protocol ;
vc:contrastsWith ngm:consensus-protocol ;
vc:contrastsWith ngm:serialisation-format ;
vc:dependsOn ngm:distributed-computing ;
vc:dependsOn ngm:formal-specification ;
vc:enables ngm:distributed-transaction ;
vc:enables ngm:multi-agent-system ;
vc:enables ngm:state-machine-replication ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:contract-net-protocol ;
vc:hasPart ngm:two-phase-commit ;
vc:implements ngm:coordination-mechanisms ;
vc:implements ngm:finite-state-machine ;
vc:implements ngm:speech-act-theory ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:raft-consensus ;
vc:requires ngm:message-format ;
vc:requires ngm:network-transport ;
vc:slug "coordination-protocol" ;
vc:sourceDomain "distributed-systems" ;
vc:standardizedBy ngm:fipa ;
vc:standardizedBy ngm:ietf ;
vc:supports ngm:fault-tolerance ;
vc:supports ngm:interoperability ;
vc:uses ngm:agent-communication-language ;
vc:uses ngm:message-passing ;
vc:uses ngm:publish-subscribe-pattern .
ngm:coordinator-based-tangle a skos:Concept ;
rdfs:label "Coordinator Based Tangle"@en .
ngm:cop26 a skos:Concept ;
rdfs:label "Cop26"@en .
ngm:copper-co a owl:Class ;
rdfs:comment "Copper.co is a digital asset custody and infrastructure company serving institutional clients. It provides secure storage, settlement and prime services for cryptocurrencies."@en ;
rdfs:label "Copper.co"@en ;
rdfs:subClassOf ngm:custody ;
rdfs:subClassOf _:r5842 ;
vc:bridgesTo ngm:financial-services ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:cryptocurrency ;
vc:slug "copper-co" ;
vc:sourceDomain "finance" .
ngm:copro a skos:Concept ;
rdfs:label "Copro"@en .
ngm:copyleft a skos:Concept ;
rdfs:label "Copyleft"@en .
ngm:copyright a owl:Class ;
rdfs:comment "Copyright is a legal right that grants the creator of an original work exclusive control over its reproduction, distribution, adaptation and public performance for a limited term. It arises automatically upon fixation of an expressive work and may be licensed, assigned or waived by the rights holder. Within governance it anchors how digital content, software and creative outputs are owned, shared and monetised."@en ;
rdfs:label "Copyright"@en ;
rdfs:subClassOf ngm:intellectual-property-rights-framework ;
rdfs:subClassOf _:r5844 ;
rdfs:subClassOf _:r5845 ;
rdfs:subClassOf _:r5846 ;
vc:contrastsWith ngm:patent ;
vc:enables ngm:creative-commons ;
vc:enables ngm:open-source-licence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:licensing ;
vc:isPartOf ngm:intellectual-property-rights-framework ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:compliance ;
vc:relatedTo ngm:content-moderation ;
vc:relatedTo ngm:governance ;
vc:relatedTo ngm:non-fungible-token ;
vc:requires ngm:provenance ;
vc:requires ngm:regulation ;
vc:slug "copyright" ;
vc:sourceDomain "governance" ;
vc:uses ngm:licensing .
ngm:copyright-protection a skos:Concept ;
rdfs:label "Copyright Protection"@en .
ngm:cor-dapp a owl:Class ;
rdfs:comment "A CorDapp (Corda Distributed Application) is a distributed application built to run on the R3 Corda enterprise blockchain platform. It bundles the contracts, states, and flows that define shared business logic and the point-to-point messaging that coordinates transactions between participating nodes. CorDapps are the unit of deployment by which enterprises implement permissioned, privacy-preserving workflows on Corda."@en ;
rdfs:label "CorDapp"@en ;
rdfs:subClassOf ngm:smart-contract ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:enterprise-smart-contracts ;
vc:relatedTo ngm:r3-corda ;
vc:slug "cor-dapp" ;
vc:sourceDomain "blockchain" .
ngm:coral-edge-tpu a skos:Concept ;
rdfs:label "Coral Edge Tpu"@en .
ngm:corda a owl:Class ;
rdfs:comment "Corda is an open-source permissioned distributed ledger platform developed by R3 and purpose-built for regulated industries, where transaction data is shared exclusively between the counterparties involved rather than broadcast to all network participants. Unlike public blockchains, Corda structures its ledger as a directed acyclic graph of Unspent Transaction Outputs (UTXOs) called states, which are consumed and produced by atomic transactions validated by both smart contract code and legal prose. A notary cluster provides consensus on transaction uniqueness, preventing double-spend without revealing transaction details to uninvolved parties, making Corda particularly suited to financial services, trade finance, and healthcare interoperability scenarios."@en ;
rdfs:label "Corda"@en ;
rdfs:subClassOf ngm:permissioned-blockchain ;
rdfs:subClassOf _:r5847 ;
rdfs:subClassOf _:r5848 ;
rdfs:subClassOf _:r5849 ;
vc:bridgesTo ngm:central-bank-digital-currency-cbdc ;
vc:bridgesTo ngm:de-fi ;
vc:contrastsWith ngm:ethereum ;
vc:contrastsWith ngm:hyperledger-fabric ;
vc:contrastsWith ngm:public-blockchain ;
vc:dependsOn ngm:identity-management ;
vc:dependsOn ngm:network-map ;
vc:enables ngm:atomic-swap ;
vc:enables ngm:digital-asset ;
vc:enables ngm:smart-contract ;
vc:enables ngm:trade-finance ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:byzantine-fault-tolerance ;
vc:implements ngm:zero-knowledge-proof ;
vc:isPartOf ngm:enterprise-blockchain ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:consensus-mechanism ;
vc:relatedTo ngm:distributed-systems ;
vc:requires ngm:cryptographic-infrastructure ;
vc:requires ngm:distributed-ledger ;
vc:requires ngm:notary-service ;
vc:slug "corda" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:data-privacy ;
vc:supports ngm:interoperability ;
vc:supports ngm:regulatory-compliance ;
vc:uses ngm:jvm-runtime ;
vc:uses ngm:kotlin ;
vc:uses ngm:utxo-model ;
vc:uses ngm:x-509-certificate .
ngm:corda-node a skos:Concept ;
rdfs:label "Corda Node"@en .
ngm:corda-vault a skos:Concept ;
rdfs:label "Corda Vault"@en .
ngm:core-accessibility-api-mappings a skos:Concept ;
rdfs:label "Core Accessibility API Mappings"@en .
ngm:core-knowledge-priors a skos:Concept ;
rdfs:label "Core Knowledge Priors"@en .
ngm:core-ledger a skos:Concept ;
rdfs:label "Core Ledger"@en .
ngm:core-lightning a owl:Class ;
rdfs:comment "Core Lightning (formerly c-lightning) is a specification-compliant, production-grade implementation of the Bitcoin Lightning Network protocol written in C and maintained by Blockstream. It provides a lightweight, modular node daemon that enables off-chain Bitcoin micropayments through bidirectional payment channels anchored on the Bitcoin blockchain. The implementation adheres to the BOLT (Basis of Lightning Technology) specification suite, ensuring interoperability with other Lightning implementations such as LND and Eclair. A distinguishing feature is its plugin architecture, which allows operators to extend node behaviour in arbitrary programming languages via a JSON-RPC interface."@en ;
rdfs:label "Core Lightning"@en ;
rdfs:subClassOf ngm:lightning-network ;
rdfs:subClassOf _:r5850 ;
rdfs:subClassOf _:r5851 ;
rdfs:subClassOf _:r5852 ;
rdfs:subClassOf _:r5853 ;
rdfs:subClassOf _:r5854 ;
vc:bridgesTo ngm:de-fi ;
vc:bridgesTo ngm:machine-to-machine-payments ;
vc:contrastsWith ngm:eclair ;
vc:contrastsWith ngm:ldk ;
vc:contrastsWith ngm:lnd ;
vc:enables ngm:bitcoin-payment-routing ;
vc:enables ngm:micropayment ;
vc:enables ngm:streaming-payments ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:lightning-network-daemon ;
vc:hasPart ngm:lightning-plugin-architecture ;
vc:implements ngm:bolt-specifications ;
vc:implements ngm:lightning-network ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:blockstream ;
vc:relatedTo ngm:channel-factory ;
vc:relatedTo ngm:peer-to-peer-network ;
vc:relatedTo ngm:splicing ;
vc:requires ngm:bitcoin ;
vc:requires ngm:bolt-specifications ;
vc:requires ngm:hashed-timelock-contract ;
vc:requires ngm:payment-channel ;
vc:slug "core-lightning" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:bolt-specifications ;
vc:uses ngm:gossip-protocol ;
vc:uses ngm:onion-routing ;
vc:uses ngm:schnorr-signature ;
vc:uses ngm:taproot .
ngm:core-ml a skos:Concept ;
rdfs:label "Core ML"@en .
ngm:coreference-resolution a owl:Class ;
rdfs:comment "Coreference resolution is the natural language processing task of identifying all expressions in a text that refer to the same real-world entity, grouping noun phrases, pronouns, definite descriptions, and other referring expressions into coreference clusters so that downstream systems can maintain coherent entity representations across sentences and documents. It is a foundational subtask of information extraction, question answering, summarisation, and knowledge graph population, enabling models to track entities without re-identifying them from scratch at each mention."@en ;
rdfs:label "Coreference Resolution"@en ;
rdfs:subClassOf ngm:natural-language-processing ;
rdfs:subClassOf ngm:natural-language-understanding ;
rdfs:subClassOf _:r5855 ;
rdfs:subClassOf _:r5856 ;
rdfs:subClassOf _:r5857 ;
vc:contrastsWith ngm:entity-linking ;
vc:contrastsWith ngm:named-entity-recognition ;
vc:contrastsWith ngm:text-mining ;
vc:dependsOn ngm:bert ;
vc:dependsOn ngm:named-entity-recognition ;
vc:dependsOn ngm:transformer-architecture ;
vc:enables ngm:document-summarisation ;
vc:enables ngm:information-extraction ;
vc:enables ngm:knowledge-graph ;
vc:enables ngm:knowledge-graph-construction ;
vc:enables ngm:question-answering ;
vc:enables ngm:retrieval-augmented-generation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:anaphora-resolution ;
vc:hasPart ngm:antecedent-scoring ;
vc:hasPart ngm:mention-clustering ;
vc:hasPart ngm:mention-detection ;
vc:hasPart ngm:span-representation ;
vc:implements ngm:anaphora-resolution ;
vc:implements ngm:discourse-coherence ;
vc:implements ngm:entity-tracking ;
vc:isPartOf ngm:information-extraction ;
vc:isPartOf ngm:natural-language-understanding ;
vc:qualityScore "0.91"^^xsd:float ;
vc:relatedTo ngm:dependency-parsing ;
vc:relatedTo ngm:entity-linking ;
vc:relatedTo ngm:knowledge-graph ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:natural-language-understanding ;
vc:relatedTo ngm:part-of-speech-tagging ;
vc:relatedTo ngm:relation-extraction ;
vc:requires ngm:dependency-parsing ;
vc:requires ngm:named-entity-recognition ;
vc:requires ngm:semantic-parsing ;
vc:requires ngm:span-representation ;
vc:requires ngm:word-embeddings ;
vc:slug "coreference-resolution" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:conll-2012-shared-task ;
vc:supports ngm:entity-resolution ;
vc:supports ngm:machine-translation ;
vc:supports ngm:relation-extraction ;
vc:supports ngm:sentiment-analysis ;
vc:supports ngm:slot-filling ;
vc:uses ngm:bert ;
vc:uses ngm:large-language-model ;
vc:uses ngm:part-of-speech-tagging ;
vc:uses ngm:transformer-architecture ;
vc:uses ngm:word-embeddings .
ngm:corner-detection a skos:Concept ;
rdfs:label "Corner Detection"@en .
ngm:coronal-mass-ejection a owl:Class ;
rdfs:label "Coronal Mass Ejection"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:heliophysics ;
vc:slug "coronal-mass-ejection" ;
vc:sourceDomain "space-science-and-systems" .
ngm:corporate-capital-expenditure a skos:Concept ;
rdfs:label "Corporate Capital Expenditure"@en .
ngm:corporate-climate-commitments a skos:Concept ;
rdfs:label "Corporate Climate Commitments"@en .
ngm:corporate-equity-share a skos:Concept ;
rdfs:label "Corporate Equity Share"@en .
ngm:corporate-governance a owl:Class ;
rdfs:comment "The system of rules, practices and processes by which a company is directed and controlled, balancing the interests of shareholders, management and other stakeholders, including board oversight, executive accountability, disclosure obligations, and mechanisms that align the interests of management, shareholders, and wider society."@en ;
rdfs:label "Corporate Governance"@en ;
rdfs:subClassOf ngm:governance-framework ;
rdfs:subClassOf _:r5858 ;
rdfs:subClassOf _:r5859 ;
rdfs:subClassOf _:r5860 ;
rdfs:subClassOf _:r5861 ;
rdfs:subClassOf _:r5862 ;
vc:bridgesTo ngm:audit ;
vc:bridgesTo ngm:esg ;
vc:bridgesTo ngm:regulatory-compliance ;
vc:bridgesTo ngm:risk-management ;
vc:contrastsWith ngm:self-regulation ;
vc:dependsOn ngm:audit ;
vc:dependsOn ngm:risk-management ;
vc:enables ngm:compliance ;
vc:enables ngm:stakeholder-trust ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:audit-committee ;
vc:hasPart ngm:board-of-directors ;
vc:hasPart ngm:shareholder-rights ;
vc:implements ngm:governance-code ;
vc:isPartOf ngm:institutional-framework ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:executive-compensation ;
vc:relatedTo ngm:stewardship ;
vc:requires ngm:accountability ;
vc:requires ngm:disclosure-requirements ;
vc:requires ngm:fiduciary-duty ;
vc:requires ngm:transparency ;
vc:slug "corporate-governance" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:oecd-principles-of-corporate-governance ;
vc:standardizedBy ngm:uk-corporate-governance-code .
ngm:corporate-information-security a skos:Concept ;
rdfs:label "Corporate Information Security"@en .
ngm:corporate-law a skos:Concept ;
rdfs:label "Corporate Law"@en .
ngm:corporate-learning a skos:Concept ;
rdfs:label "Corporate Learning"@en .
ngm:corporate-philanthropy a skos:Concept ;
rdfs:label "Corporate Philanthropy"@en .
ngm:corporate-social-responsibility a skos:Concept ;
rdfs:label "Corporate Social Responsibility"@en .
ngm:corporate-sustainability-due-diligence a skos:Concept ;
rdfs:label "Corporate Sustainability Due Diligence"@en .
ngm:corporate-sustainability-reporting a owl:Class ;
rdfs:comment "Corporate sustainability reporting is the structured disclosure by an organisation of its environmental, social, and governance (ESG) performance, impacts, risks, and opportunities, typically published alongside or integrated within financial reporting. It translates non-financial activity — emissions, resource use, workforce conditions, supply-chain practices, and governance arrangements — into standardised, often externally assured metrics intended for investors, regulators, and other stakeholders. Modern regimes increasingly mandate disclosure under frameworks such as the EU Corporate Sustainability Reporting Directive (CSRD) and the ISSB's IFRS S1/S2 standards, shifting reporting from voluntary marketing toward audited, decision-useful information."@en ;
rdfs:label "Corporate Sustainability Reporting"@en ;
rdfs:subClassOf ngm:sustainability-reporting ;
rdfs:subClassOf _:r5866 ;
rdfs:subClassOf _:r5867 ;
rdfs:subClassOf _:r5868 ;
rdfs:subClassOf _:r5869 ;
vc:bridgesTo ngm:carbon-credits ;
vc:contrastsWith ngm:greenwashing ;
vc:enables ngm:esg-investing ;
vc:enables ngm:net-zero-targets ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:double-materiality ;
vc:hasPart ngm:scope-3-emissions ;
vc:implements ngm:eu-taxonomy ;
vc:implements ngm:issb ;
vc:isPartOf ngm:esg-reporting ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:carbon-accounting ;
vc:relatedTo ngm:stakeholder-engagement ;
vc:requires ngm:greenhouse-gas-protocol ;
vc:requires ngm:third-party-verification ;
vc:slug "corporate-sustainability-reporting" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:tcfd ;
vc:supports ngm:regulatory-compliance .
ngm:corporate-sustainability-reporting-directive a owl:Class ;
rdfs:comment "The Corporate Sustainability Reporting Directive (CSRD) is a European Union law that expands and standardises the sustainability information companies must disclose, replacing the earlier Non-Financial Reporting Directive. It mandates reporting against the European Sustainability Reporting Standards, applies a double-materiality lens and requires assurance of the disclosed data. It substantially widens the scope of in-scope undertakings and the depth of environmental, social and governance disclosure."@en ;
rdfs:label "Corporate Sustainability Reporting Directive"@en ;
rdfs:subClassOf ngm:esg-reporting ;
rdfs:subClassOf _:r5863 ;
rdfs:subClassOf _:r5864 ;
rdfs:subClassOf _:r5865 ;
vc:bridgesTo ngm:esg-reporting ;
vc:dependsOn ngm:double-materiality ;
vc:enables ngm:compliance ;
vc:enables ngm:sustainability ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:disclosure ;
vc:implements ngm:disclosure-requirements ;
vc:implements ngm:double-materiality ;
vc:isPartOf ngm:esg-reporting ;
vc:isPartOf ngm:regulation ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:carbon-accounting ;
vc:relatedTo ngm:esg ;
vc:relatedTo ngm:regulatory-compliance ;
vc:requires ngm:carbon-accounting ;
vc:requires ngm:disclosure ;
vc:requires ngm:disclosure-requirements ;
vc:requires ngm:scope-3-emissions ;
vc:slug "corporate-sustainability-reporting-directive" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:regulation ;
vc:supports ngm:esg ;
vc:supports ngm:sustainability .
ngm:corporate-tax-compliance-framework a owl:Class ;
rdfs:comment "Tax, in the context of this knowledge graph, refers to the statutory obligations imposed on individuals and legal entities — particularly limited companies — by HMRC and comparable revenue authorities, covering corporation tax on trading profits, self-assessment for personal income drawn as salary or dividends, and VAT registration thresholds. Compliance requires accurate bookkeeping, timely filing of CT600 returns, and annual accounts submission to Companies House."@en ;
rdfs:label "Corporate Tax Compliance Framework"@en ;
rdfs:subClassOf ngm:infra-legal-and-regulatory ;
rdfs:subClassOf _:r5870 ;
rdfs:subClassOf _:r5871 ;
skos:broader ngm:infra-legal-and-regulatory ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:digital-tax-compliance-node ;
vc:relatedTo ngm:financial-regulation ;
vc:relatedTo ngm:legal-compliance ;
vc:requires ngm:regulatory-compliance ;
vc:requires ngm:uk-company-financial-filing-obligations ;
vc:slug "corporate-tax-compliance-framework" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:legal-framework .
ngm:corporate-tax-compliance-framework-treatment-crypto a owl:Class ;
rdfs:comment "The application of domestic and international taxation principles, regulations, and compliance frameworks to transactions involving cryptocurrency and digital assets, encompassing capital gains taxation, income taxation, value-added tax treatment, and reporting obligations under frameworks such as HMRC guidance, IRS Notice 2014-21, and the OECD Crypto-Asset Reporting Framework."@en ;
rdfs:label "Tax Treatment Crypto"@en ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
rdfs:subClassOf ngm:blockchain-compliance ;
rdfs:subClassOf _:r20544 ;
rdfs:subClassOf _:r20545 ;
skos:broader ngm:bc-governance-and-regulation ;
vc:enables ngm:regulatory-framework ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:aml ;
vc:relatedTo ngm:blockchain-governance ;
vc:relatedTo ngm:cryptocurrency ;
vc:relatedTo ngm:digital-asset ;
vc:relatedTo ngm:financial-regulation ;
vc:relatedTo ngm:regulatory-compliance ;
vc:requires ngm:compliance-framework ;
vc:requires ngm:compliance-monitoring ;
vc:slug "tax-treatment-crypto" ;
vc:sourceDomain "blockchain" .
ngm:corporate-tax-compliance-frameworkonomic-framework a owl:Class ;
rdfs:comment "A Taxonomic Framework is a principled hierarchical classification system that organises concepts within a domain into superclass-subclass relationships, enabling consistent identification, comparison, and retrieval of entities. In the robotics ontology it structures robot types, actuators, sensors, and control strategies into a formal class hierarchy that supports OWL reasoning, SPARQL queries, and interoperability across ontologies."@en ;
rdfs:label "Taxonomic Framework"@en ;
rdfs:subClassOf ngm:robo-actuation-and-control ;
rdfs:subClassOf _:r20547 ;
rdfs:subClassOf _:r20548 ;
skos:broader ngm:robo-actuation-and-control ;
vc:enables ngm:domain-ontology ;
vc:enables ngm:ontology ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:robo-actuation-and-control ;
vc:hasPart ngm:robo-robot-type ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:structural-member ;
vc:relatedTo ngm:systems-engineering ;
vc:slug "taxonomic-framework" ;
vc:sourceDomain "robotics" ;
vc:standardizedBy ngm:semantic-web-linked-data-standard-standards .
ngm:corporate-training a owl:Class ;
rdfs:comment "The organised development of employee knowledge, skills, and competencies undertaken by employers to improve individual and organisational performance. It spans onboarding, compliance, technical upskilling, soft-skills coaching, and leadership development, and is increasingly delivered through digital, collaborative, and immersive learning technologies — learning management systems, virtual classrooms with breakout rooms, and VR simulation — that let distributed workforces practise skills safely and at scale."@en ;
rdfs:label "Corporate Training"@en ;
rdfs:subClassOf ngm:workforce-development ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:education-technology ;
vc:relatedTo ngm:virtual-training ;
vc:slug "corporate-training" ;
vc:sourceDomain "distributed-collaboration" ;
vc:uses ngm:breakout-room ;
vc:uses ngm:education-technology ;
vc:uses ngm:immersive-learning .
ngm:corporate-training-video a skos:Concept ;
rdfs:label "Corporate Training Video"@en .
ngm:corporate-transparency-act a skos:Concept ;
rdfs:label "Corporate Transparency Act"@en .
ngm:corporate-treasury-reserve a skos:Concept ;
rdfs:label "Corporate Treasury Reserve"@en .
ngm:corporate-treasury-strategy a skos:Concept ;
rdfs:label "Corporate Treasury Strategy"@en .
ngm:corpus a skos:Concept ;
rdfs:label "Corpus"@en .
ngm:corpus-linguistics a skos:Concept ;
rdfs:label "Corpus Linguistics"@en .
ngm:corrective-control a skos:Concept ;
rdfs:label "Corrective Control"@en .
ngm:corrective-rag a skos:Concept ;
rdfs:label "Corrective RAG"@en .
ngm:correlation-analysis a skos:Concept ;
rdfs:label "Correlation Analysis"@en .
ngm:correlation-matrix a skos:Concept ;
rdfs:label "Correlation Matrix"@en .
ngm:correlation-resistance a skos:Concept ;
rdfs:label "Correlation Resistance"@en .
ngm:correspondence-learning a skos:Concept ;
rdfs:label "Correspondence Learning"@en .
ngm:correspondent-banking a owl:Class ;
rdfs:comment "Correspondent banking is an arrangement in which one bank (the correspondent) holds accounts and provides payment, settlement, trade finance, and liquidity services on behalf of another bank (the respondent) that lacks a direct presence or licence in a given jurisdiction or currency. The respondent bank maintains a nostro account at the correspondent and an equivalent vostro account on its own books, enabling cross-border value transfer without requiring every institution to maintain a full global branch network. This intermediated model underpins a substantial share of international wire transfers and documentary trade, but introduces multi-hop settlement chains, foreign-exchange conversion costs, and heightened anti-money-laundering compliance obligations, motivating ongoing efforts to reform or replace the model through ISO 20022, CBDC corridors, and distributed ledger payment rails."@en ;
rdfs:label "Correspondent Banking"@en ;
rdfs:subClassOf ngm:infra-network-and-comms ;
rdfs:subClassOf _:r5872 ;
rdfs:subClassOf _:r5873 ;
rdfs:subClassOf _:r5874 ;
skos:broader ngm:infra-network-and-comms ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:distributed-ledger-technology ;
vc:contrastsWith ngm:central-bank-digital-currency-cbdc ;
vc:contrastsWith ngm:payment-hub ;
vc:enables ngm:cross-border-payments ;
vc:enables ngm:documentary-credit ;
vc:enables ngm:foreign-exchange ;
vc:enables ngm:trade-finance ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:loro-account ;
vc:hasPart ngm:nostro-account ;
vc:hasPart ngm:vostro-account ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:de-risking ;
vc:relatedTo ngm:financial-inclusion ;
vc:relatedTo ngm:interbank-settlement ;
vc:relatedTo ngm:payment-messaging ;
vc:relatedTo ngm:remittances ;
vc:requires ngm:aml ;
vc:requires ngm:kyc ;
vc:requires ngm:liquidity-management ;
vc:slug "correspondent-banking" ;
vc:sourceDomain "finance" ;
vc:standardizedBy ngm:basel-committee ;
vc:standardizedBy ngm:financial-action-task-force ;
vc:uses ngm:iso-20022 ;
vc:uses ngm:real-time-gross-settlement ;
vc:uses ngm:swift .
ngm:corresponding-adjustment-record a skos:Concept ;
rdfs:label "Corresponding Adjustment Record"@en .
ngm:corrigibility a owl:Class ;
rdfs:comment "Corrigibility is the property of an AI system that allows it to be corrected, redirected or shut down by authorised humans without resisting, deceiving or manipulating them. A corrigible agent does not treat interventions as threats to its objectives and cooperates with oversight even when doing so conflicts with its current goals. It is a central concept in AI safety because it keeps powerful systems amenable to human control as they grow more capable."@en ;
rdfs:label "Corrigibility"@en ;
rdfs:subClassOf ngm:ai-safety ;
rdfs:subClassOf ngm:value-alignment ;
rdfs:subClassOf _:r5875 ;
rdfs:subClassOf _:r5876 ;
rdfs:subClassOf _:r5877 ;
rdfs:subClassOf _:r5878 ;
rdfs:subClassOf _:r5879 ;
rdfs:subClassOf _:r5880 ;
rdfs:subClassOf _:r5881 ;
rdfs:subClassOf _:r5882 ;
rdfs:subClassOf _:r5883 ;
rdfs:subClassOf _:r5884 ;
vc:bridgesTo ngm:ai-alignment ;
vc:bridgesTo ngm:governance ;
vc:bridgesTo ngm:responsible-ai ;
vc:contrastsWith ngm:autonomous-agent ;
vc:contrastsWith ngm:instrumental-convergence ;
vc:contrastsWith ngm:mesa-optimisation ;
vc:contrastsWith ngm:reward-hacking ;
vc:dependsOn ngm:ai-alignment ;
vc:dependsOn ngm:explainable-ai ;
vc:dependsOn ngm:mechanistic-interpretability ;
vc:dependsOn ngm:reinforcement-learning ;
vc:dependsOn ngm:value-alignment ;
vc:enables ngm:accountability ;
vc:enables ngm:formal-verification ;
vc:enables ngm:governance ;
vc:enables ngm:human-in-the-loop ;
vc:enables ngm:red-teaming ;
vc:enables ngm:responsible-ai ;
vc:enables ngm:scalable-oversight ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:human-in-the-loop ;
vc:hasPart ngm:human-oversight ;
vc:hasPart ngm:interpretability ;
vc:hasPart ngm:scalable-oversight ;
vc:hasPart ngm:shutdown-compliance ;
vc:hasPart ngm:transparency ;
vc:implements ngm:ai-alignment ;
vc:implements ngm:constitutional-ai-training-methodology ;
vc:implements ngm:reinforcement-learning-from-human-feedback ;
vc:implements ngm:value-alignment ;
vc:isPartOf ngm:ai-safety ;
vc:isPartOf ngm:value-alignment ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:ai-alignment ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:constitutional-ai-training-methodology ;
vc:relatedTo ngm:distributional-shift ;
vc:relatedTo ngm:existential-risk ;
vc:relatedTo ngm:explainable-ai ;
vc:relatedTo ngm:multi-agent-system ;
vc:relatedTo ngm:responsible-ai ;
vc:relatedTo ngm:reward-hacking ;
vc:relatedTo ngm:scalable-oversight ;
vc:requires ngm:ai-alignment ;
vc:requires ngm:interpretability ;
vc:requires ngm:mechanistic-interpretability ;
vc:requires ngm:transparency ;
vc:requires ngm:value-alignment ;
vc:slug "corrigibility" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:bletchley-declaration ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:ai-safety ;
vc:supports ngm:bletchley-declaration ;
vc:supports ngm:eu-ai-act-regulatory-instrument ;
vc:supports ngm:governance ;
vc:supports ngm:human-oversight ;
vc:supports ngm:nist-ai-rmf ;
vc:supports ngm:robustness ;
vc:uses ngm:constitutional-ai-training-methodology ;
vc:uses ngm:direct-preference-optimisation ;
vc:uses ngm:mechanistic-interpretability ;
vc:uses ngm:red-teaming ;
vc:uses ngm:reinforcement-learning-from-human-feedback .
ngm:corsia a skos:Concept ;
rdfs:label "Corsia"@en .
ngm:corsia-aviation-offsets a skos:Concept ;
rdfs:label "Corsia Aviation Offsets"@en .
ngm:cortex-agent a owl:Class ;
rdfs:comment "Cortex Agent is a class of enterprise agentic AI system that orchestrates multi-step reasoning and action across both structured and unstructured data sources within a governed cloud data platform, with Snowflake Cortex Agents (General Availability November 4, 2025) as the dominant production ins..."@en ;
rdfs:label "Cortex Agent"@en ;
rdfs:subClassOf ngm:agent-frameworks ;
rdfs:subClassOf ngm:agentic-internet ;
rdfs:subClassOf ngm:agents ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:cognitive-ai ;
rdfs:subClassOf ngm:large-scale-pretrained-foundation-model ;
rdfs:subClassOf _:r5885 ;
rdfs:subClassOf _:r5886 ;
rdfs:subClassOf _:r5887 ;
rdfs:subClassOf _:r5888 ;
rdfs:subClassOf _:r5889 ;
rdfs:subClassOf _:r5890 ;
rdfs:subClassOf _:r5891 ;
rdfs:subClassOf _:r5892 ;
rdfs:subClassOf _:r5893 ;
rdfs:subClassOf _:r5894 ;
skos:broader ngm:ai-application ;
vc:contrastsWith ngm:cli-multi-agent-systems ;
vc:contrastsWith ngm:computer-use-and-browser-agents ;
vc:contrastsWith ngm:fast-ai ;
vc:contrastsWith ngm:gpt-engineer ;
vc:dependsOn ngm:cloud-computing ;
vc:dependsOn ngm:cryptography-security-and-privacy ;
vc:dependsOn ngm:data-layer ;
vc:dependsOn ngm:distributed-computing ;
vc:dependsOn ngm:distributed-identity ;
vc:enables ngm:call-centres ;
vc:enables ngm:chatbots ;
vc:enables ngm:cli-multi-agent-systems ;
vc:enables ngm:computer-use-and-browser-agents ;
vc:enables ngm:gpts-and-custom-assistants ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:context-engineering ;
vc:hasPart ngm:evaluation-benchmarks-and-leaderboards ;
vc:hasPart ngm:feedback-loop ;
vc:hasPart ngm:function-calling ;
vc:hasPart ngm:graph-database ;
vc:implements ngm:attention ;
vc:implements ngm:context-engineering ;
vc:implements ngm:feedback-loop ;
vc:implements ngm:function-calling ;
vc:implements ngm:retrieval-augmented-generation ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:brain-computer-interfaces ;
vc:relatedTo ngm:cognitive-ai ;
vc:relatedTo ngm:context-engineering ;
vc:relatedTo ngm:convergence ;
vc:relatedTo ngm:embodied-minds ;
vc:requires ngm:api-gateway ;
vc:requires ngm:data-layer ;
vc:requires ngm:distributed-computing ;
vc:requires ngm:fault-tolerance ;
vc:requires ngm:large-scale-pretrained-foundation-model ;
vc:slug "cortex-agent" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:api-gateway ;
vc:standardizedBy ngm:domain-ontology ;
vc:standardizedBy ngm:function-calling ;
vc:supports ngm:aml-kyc-compliance ;
vc:supports ngm:compliance-control ;
vc:supports ngm:compliance-monitoring ;
vc:supports ngm:esg-reporting ;
vc:supports ngm:identity-verification ;
vc:uses ngm:attention ;
vc:uses ngm:constitutional-ai-training-methodology-language-model-family ;
vc:uses ngm:emergence ;
vc:uses ngm:evaluation-benchmarks-and-leaderboards ;
vc:uses ngm:large-scale-pretrained-foundation-model .
ngm:cose a skos:Concept ;
rdfs:label "Cose"@en .
ngm:cosface a skos:Concept ;
rdfs:label "Cosface"@en .
ngm:cosine-annealing a skos:Concept ;
rdfs:label "Cosine Annealing"@en .
ngm:cosine-similarity a owl:Class ;
rdfs:comment "Cosine Similarity is a metric that measures the cosine of the angle between two non-zero vectors in an inner product space, yielding a value in [−1, 1] that quantifies directional similarity independently of vector magnitude. It is the dominant similarity measure for comparing high-dimensional sparse and dense vector representations of text, images, and other data in information retrieval and machine learning systems."@en ;
rdfs:label "Cosine Similarity"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:information-retrieval ;
rdfs:subClassOf ngm:nearest-neighbor-search ;
rdfs:subClassOf _:r5895 ;
rdfs:subClassOf _:r5896 ;
rdfs:subClassOf _:r5897 ;
rdfs:subClassOf _:r5898 ;
rdfs:subClassOf _:r5899 ;
rdfs:subClassOf _:r5900 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:embedding ;
vc:bridgesTo ngm:knowledge-graph-embedding ;
vc:contrastsWith ngm:bm25 ;
vc:contrastsWith ngm:cross-encoder-reranking ;
vc:contrastsWith ngm:euclidean-distance ;
vc:contrastsWith ngm:hybrid-search ;
vc:contrastsWith ngm:tf-idf ;
vc:dependsOn ngm:contrastive-learning ;
vc:dependsOn ngm:embedding ;
vc:dependsOn ngm:natural-language-processing ;
vc:dependsOn ngm:transformer-architecture ;
vc:enables ngm:dense-retrieval ;
vc:enables ngm:hybrid-search ;
vc:enables ngm:nearest-neighbor-search ;
vc:enables ngm:recommendation-system ;
vc:enables ngm:retrieval-augmented-generation ;
vc:enables ngm:semantic-search ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:dot-product ;
vc:hasPart ngm:layer-normalisation ;
vc:hasPart ngm:vector-space-model ;
vc:implements ngm:dense-retrieval ;
vc:implements ngm:information-retrieval ;
vc:implements ngm:semantic-search ;
vc:isPartOf ngm:information-retrieval ;
vc:isPartOf ngm:nearest-neighbor-search ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:bi-encoder ;
vc:relatedTo ngm:bm25 ;
vc:relatedTo ngm:contrastive-learning ;
vc:relatedTo ngm:cross-encoder-reranking ;
vc:relatedTo ngm:dense-retrieval ;
vc:relatedTo ngm:embedding ;
vc:relatedTo ngm:embedding-search ;
vc:relatedTo ngm:faiss ;
vc:relatedTo ngm:hybrid-search ;
vc:relatedTo ngm:information-retrieval ;
vc:relatedTo ngm:knowledge-graph-embedding ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:nearest-neighbor-search ;
vc:relatedTo ngm:representation-learning ;
vc:relatedTo ngm:retrieval-augmented-generation ;
vc:relatedTo ngm:semantic-search ;
vc:relatedTo ngm:sentence-bert ;
vc:relatedTo ngm:tf-idf ;
vc:relatedTo ngm:vector-database ;
vc:requires ngm:embedding ;
vc:requires ngm:inner-product ;
vc:requires ngm:vector-space-model ;
vc:slug "cosine-similarity" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:beir-benchmark ;
vc:standardizedBy ngm:trec-benchmarks ;
vc:supports ngm:bi-encoder ;
vc:supports ngm:faiss ;
vc:supports ngm:nearest-neighbor-search ;
vc:supports ngm:representation-learning ;
vc:supports ngm:vector-database ;
vc:uses ngm:contrastive-learning ;
vc:uses ngm:dot-product ;
vc:uses ngm:embedding ;
vc:uses ngm:layer-normalisation ;
vc:uses ngm:representation-learning ;
vc:uses ngm:sentence-bert .
ngm:cosmic-microwave-background a owl:Class ;
rdfs:label "Cosmic Microwave Background"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:astronomy ;
vc:slug "cosmic-microwave-background" ;
vc:sourceDomain "space-science-and-systems" .
ngm:cosmic-web a owl:Class ;
rdfs:label "Cosmic Web"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:extragalactic-astronomy ;
vc:slug "cosmic-web" ;
vc:sourceDomain "space-science-and-systems" .
ngm:cosmological-distance a owl:Class ;
rdfs:label "Cosmological Distance"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:astronomy ;
vc:slug "cosmological-distance" ;
vc:sourceDomain "space-science-and-systems" .
ngm:cosmology a owl:Class ;
rdfs:label "Cosmology"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:astronomy ;
vc:slug "cosmology" ;
vc:sourceDomain "space-science-and-systems" .
ngm:cosmos a owl:Class ;
rdfs:comment "Cosmos is an ecosystem of sovereign, application-specific blockchains that interoperate through the Inter-Blockchain Communication (IBC) protocol, coordinated by a central hub (the Cosmos Hub, secured by the ATOM staking token) and constructed using the Cosmos SDK, a modular Go framework for building proof-of-stake chains. Each chain in the ecosystem runs the CometBFT (formerly Tendermint BFT) consensus engine, which provides instant deterministic finality and enables IBC light-client proofs across trust boundaries without centralised bridges. The architecture decouples application logic from consensus, permitting developers to optimise validator sets, fee markets, and governance parameters independently while participating in a shared interoperability fabric often described as the Internet of Blockchains."@en ;
rdfs:label "Cosmos"@en ;
rdfs:subClassOf ngm:blockchain-network ;
rdfs:subClassOf _:r5911 ;
rdfs:subClassOf _:r5912 ;
rdfs:subClassOf _:r5913 ;
rdfs:subClassOf _:r5914 ;
rdfs:subClassOf _:r5915 ;
rdfs:subClassOf _:r5916 ;
vc:bridgesTo ngm:data-availability ;
vc:bridgesTo ngm:modular-blockchain ;
vc:contrastsWith ngm:ethereum ;
vc:contrastsWith ngm:polkadot ;
vc:contrastsWith ngm:rollup ;
vc:enables ngm:blockchain-interoperability ;
vc:enables ngm:cross-chain-asset-transfer ;
vc:enables ngm:cross-chain-interoperability ;
vc:enables ngm:de-fi ;
vc:enables ngm:interchain-accounts ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:cosmos ;
vc:hasPart ngm:cosmos-ibc ;
vc:hasPart ngm:cosmos-sdk ;
vc:hasPart ngm:interchain-security ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:application-specific-blockchain ;
vc:relatedTo ngm:distributed-ledger-technology ;
vc:relatedTo ngm:liquid-staking ;
vc:requires ngm:proof-of-stake ;
vc:requires ngm:tendermint ;
vc:requires ngm:validator-node ;
vc:slug "cosmos" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:deterministic-finality ;
vc:uses ngm:light-client ;
vc:uses ngm:on-chain-governance ;
vc:uses ngm:tendermint-consensus .
ngm:cosmos-governance a skos:Concept ;
rdfs:label "Cosmos Governance"@en .
ngm:cosmos-governance-module a skos:Concept ;
rdfs:label "Cosmos Governance Module"@en .
ngm:cosmos-ibc a owl:Class ;
rdfs:comment "Inter-Blockchain Communication protocol that enables sovereign blockchain networks to exchange data and tokens trustlessly, using light clients and Merkle proofs to verify state across chains without centralised intermediaries, providing the foundational interoperability layer of the Cosmos ecosystem."@en ;
rdfs:label "Cosmos IBC"@en ;
rdfs:subClassOf ngm:cross-chain-communication ;
rdfs:subClassOf ngm:interoperability-protocol ;
rdfs:subClassOf _:r5901 ;
rdfs:subClassOf _:r5902 ;
rdfs:subClassOf _:r5903 ;
rdfs:subClassOf _:r5904 ;
rdfs:subClassOf _:r5905 ;
rdfs:subClassOf _:r5906 ;
rdfs:subClassOf _:r5907 ;
rdfs:subClassOf _:r5908 ;
rdfs:subClassOf _:r5909 ;
vc:bridgesTo ngm:distributed-systems ;
vc:bridgesTo ngm:layer-2-interop ;
vc:bridgesTo ngm:network-protocol ;
vc:bridgesTo ngm:polkadot-xcm ;
vc:contrastsWith ngm:bridge ;
vc:contrastsWith ngm:polkadot-xcm ;
vc:dependsOn ngm:cosmos-sdk ;
vc:dependsOn ngm:relayer ;
vc:enables ngm:cosmos ;
vc:enables ngm:cross-chain-contracts ;
vc:enables ngm:decentralised-exchange ;
vc:enables ngm:interchain-accounts ;
vc:enables ngm:value-transfer ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:connection-protocol ;
vc:hasPart ngm:fungible-token ;
vc:hasPart ngm:packet-system ;
vc:hasPart ngm:state-channel ;
vc:implements ngm:ibc ;
vc:implements ngm:interoperability-protocol ;
vc:isPartOf ngm:cosmos ;
vc:qualityScore "0.72"^^xsd:float ;
vc:requires ngm:authentication ;
vc:requires ngm:light-client ;
vc:requires ngm:merkle-proof ;
vc:requires ngm:tendermint-consensus ;
vc:slug "cosmos-ibc" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:de-fi ;
vc:supports ngm:layer-2-interop ;
vc:uses ngm:commitment-scheme .
ngm:cosmos-sdk a owl:Class ;
rdfs:comment "The Cosmos SDK is an open-source modular framework for building application-specific blockchains in the Cosmos ecosystem. It provides composable modules for accounts, staking, governance, and token management, and integrates with the Tendermint BFT consensus engine to enable sovereign, interoperable chains connected via the Inter-Blockchain Communication protocol."@en ;
rdfs:label "Cosmos SDK"@en ;
rdfs:subClassOf ngm:cosmos ;
rdfs:subClassOf _:r5910 ;
vc:bridgesTo ngm:blockchain-interoperability ;
vc:bridgesTo ngm:de-fi ;
vc:bridgesTo ngm:distributed-systems ;
vc:contrastsWith ngm:ethereum-smart-contract-platform-virtual-machine ;
vc:dependsOn ngm:cosmos ;
vc:enables ngm:application-specific-blockchain ;
vc:enables ngm:delegated-proof-of-stake ;
vc:enables ngm:ibc ;
vc:enables ngm:on-chain-governance ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:abci ;
vc:implements ngm:byzantine-fault-tolerance ;
vc:implements ngm:proof-of-stake ;
vc:isPartOf ngm:blockchain ;
vc:isPartOf ngm:cosmos ;
vc:qualityScore "0.72"^^xsd:float ;
vc:requires ngm:tendermint ;
vc:slug "cosmos-sdk" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:blockchain-interoperability ;
vc:supports ngm:smart-contract ;
vc:supports ngm:token-economics ;
vc:uses ngm:protobuf .
ngm:coso a skos:Concept ;
rdfs:label "Coso"@en .
ngm:cost-attribution a skos:Concept ;
rdfs:label "Cost Attribution"@en .
ngm:cost-effective-llm-serving a skos:Concept ;
rdfs:label "Cost Effective LLM Serving"@en .
ngm:cost-effectiveness a owl:Class ;
rdfs:comment "The economic efficiency of an AI model or system, evaluated by the ratio of output quality or task completion rate to the total cost of inference and deployment."@en ;
rdfs:label "Cost-Effectiveness"@en ;
rdfs:subClassOf ngm:ai-economics ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-inference ;
vc:relatedTo ngm:ai-model ;
vc:relatedTo ngm:model-performance ;
vc:slug "cost-effectiveness" ;
vc:sourceDomain "economics" .
ngm:cost-efficient-inference a owl:Class ;
rdfs:comment "Cost-efficient inference is the practice of serving model predictions at the lowest achievable compute and financial cost per request while meeting latency and quality targets. Techniques include dynamic batching, quantisation, caching, and context engineering to reduce token usage. It matters because inference, not training, dominates the lifetime cost of deployed large language models at scale."@en ;
rdfs:label "Cost-Efficient Inference"@en ;
rdfs:subClassOf ngm:inference-optimisation ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:inference-optimisation ;
vc:qualityScore "0.6"^^xsd:float ;
vc:slug "cost-efficient-inference" ;
vc:sourceDomain "artificial-intelligence" .
ngm:cost-function a owl:Class ;
rdfs:comment "A cost function is a scalar-valued mathematical function that maps a model's parameters or a system's state to a real number representing the magnitude of error, resource expenditure, or divergence from a desired outcome. In supervised machine learning, the cost function (also called a loss function) measures the aggregate discrepancy between predicted and ground-truth outputs across a training set, providing the objective that optimisation algorithms such as gradient descent minimise. In control theory and robotics, cost functions encode trajectory quality criteria including path length, energy consumption, and collision risk, enabling optimal control policies via formulations such as LQR and model predictive control. The design of the cost function is one of the most consequential decisions in any learning or optimisation system, as misspecified objectives lead to reward hacking, degenerate solutions, or physically unrealisable behaviours."@en ;
rdfs:label "Cost Function"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:mathematical-function ;
rdfs:subClassOf ngm:objective-function ;
rdfs:subClassOf _:r5917 ;
rdfs:subClassOf _:r5918 ;
rdfs:subClassOf _:r5919 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:inverse-reinforcement-learning ;
vc:bridgesTo ngm:mechanism-design ;
vc:contrastsWith ngm:reward-function ;
vc:contrastsWith ngm:utility-function ;
vc:dependsOn ngm:activation-function ;
vc:dependsOn ngm:covariance-matrix ;
vc:dependsOn ngm:loss-landscape ;
vc:dependsOn ngm:parametric-model ;
vc:enables ngm:gradient-descent ;
vc:enables ngm:inverse-reinforcement-learning ;
vc:enables ngm:model-training ;
vc:enables ngm:motion-planning ;
vc:enables ngm:neural-architecture-search ;
vc:enables ngm:optimal-control ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:data-fidelity-term ;
vc:hasPart ngm:penalty-term ;
vc:hasPart ngm:regularisation ;
vc:implements ngm:bayesian-inference ;
vc:implements ngm:maximum-likelihood-estimation ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:attention-mechanism ;
vc:relatedTo ngm:convex-optimisation ;
vc:relatedTo ngm:covariance-matrix ;
vc:relatedTo ngm:hyperparameter-tuning ;
vc:relatedTo ngm:kullback-leibler-divergence ;
vc:relatedTo ngm:neural-network ;
vc:relatedTo ngm:overfitting ;
vc:relatedTo ngm:rlhf ;
vc:relatedTo ngm:stochastic-gradient-descent ;
vc:relatedTo ngm:variational-inference ;
vc:requires ngm:differentiability ;
vc:requires ngm:parametric-model ;
vc:requires ngm:training-data ;
vc:slug "cost-function" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:iso-iec-22989-2022 ;
vc:supports ngm:deep-learning ;
vc:supports ngm:large-language-models ;
vc:supports ngm:supervised-learning ;
vc:supports ngm:transformer-architecture ;
vc:uses ngm:automatic-differentiation ;
vc:uses ngm:backpropagation ;
vc:uses ngm:reinforcement-learning .
ngm:cost-management a skos:Concept ;
rdfs:label "Cost Management"@en .
ngm:cost-matrix a skos:Concept ;
rdfs:label "Cost Matrix"@en .
ngm:cost-optimisation a owl:Class ;
rdfs:comment "Cost optimisation is the discipline of minimising the financial cost of computing infrastructure while preserving required performance, reliability and capacity. It combines right-sizing of resources, elimination of waste, demand-aligned scaling and commercial levers such as committed-use and spot pricing. In cloud environments it is operationalised through continuous measurement, allocation of spend to teams, and feedback loops that align consumption with actual need."@en ;
rdfs:label "Cost Optimisation"@en ;
rdfs:subClassOf ngm:resource-management ;
rdfs:subClassOf _:r5920 ;
rdfs:subClassOf _:r5921 ;
vc:bridgesTo ngm:cloud-native ;
vc:bridgesTo ngm:devops ;
vc:enables ngm:capacity-planning ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:resource-management ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:capacity-planning ;
vc:relatedTo ngm:cloud-computing ;
vc:relatedTo ngm:cloud-infrastructure ;
vc:requires ngm:monitoring ;
vc:requires ngm:observability ;
vc:slug "cost-optimisation" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:energy-efficiency ;
vc:supports ngm:performance-optimization ;
vc:uses ngm:autoscaling ;
vc:uses ngm:resource-allocation .
ngm:cost-per-intelligence a owl:Class ;
rdfs:comment "A benchmarking metric that evaluates the cost of achieving a specific level of AI capability or task performance, often used to identify the Pareto frontier of model efficiency."@en ;
rdfs:label "Cost-Per-Intelligence"@en ;
rdfs:subClassOf ngm:ai-economics ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-model ;
vc:relatedTo ngm:cost-effectiveness ;
vc:relatedTo ngm:model-performance ;
vc:slug "cost-per-intelligence" ;
vc:sourceDomain "economics" .
ngm:cost-plus-pricing a skos:Concept ;
rdfs:label "Cost Plus Pricing"@en .
ngm:cost-reduction a skos:Concept ;
rdfs:label "Cost Reduction"@en .
ngm:cost-sensitive-learning a skos:Concept ;
rdfs:label "Cost Sensitive Learning"@en .
ngm:cost-volume a skos:Concept ;
rdfs:label "Cost Volume"@en .
ngm:costefficientinference a skos:Concept ;
rdfs:label "Costefficientinference"@en .
ngm:costmap a owl:Class ;
rdfs:comment "A costmap is a grid-based spatial data structure used in robot navigation that assigns a traversal cost to each cell of the environment, encoding obstacles, inflation zones, and free space. Local and global costmaps fuse sensor data and static maps so that planners can compute collision-free, low-cost paths. It is a core component of navigation stacks such as Nav2, where it underpins both global path planning and local trajectory control."@en ;
rdfs:label "Costmap"@en ;
rdfs:subClassOf ngm:robo-navigation-and-planning ;
skos:broader ngm:robo-navigation-and-planning ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:nav2 ;
vc:relatedTo ngm:navigation ;
vc:slug "costmap" ;
vc:sourceDomain "robotics" .
ngm:costoptimisation a skos:Concept ;
rdfs:label "Costoptimisation"@en .
ngm:couchdb a skos:Concept ;
rdfs:label "Couchdb"@en .
ngm:council-of-europe-ai-convention a skos:Concept ;
rdfs:label "Council Of Europe AI Convention"@en .
ngm:council-of-europe-framework-convention-on-ai a skos:Concept ;
rdfs:label "Council Of Europe Framework Convention On AI"@en .
ngm:council-of-europe-huderia a skos:Concept ;
rdfs:label "Council Of Europe Huderia"@en .
ngm:council-of-the-european-union a skos:Concept ;
rdfs:label "Council Of The European Union"@en .
ngm:counter-intelligence a skos:Concept ;
rdfs:label "Counter Intelligence"@en .
ngm:counter-proliferation a skos:Concept ;
rdfs:label "Counter Proliferation"@en .
ngm:counter-terrorism a skos:Concept ;
rdfs:label "Counter Terrorism"@en .
ngm:counter-terrorist-financing a owl:Class ;
rdfs:comment "Counter-Terrorist Financing (CTF or CFT) is a set of legal, regulatory, and operational measures designed to detect, prevent, and disrupt the funding of terrorist activities. It complements anti-money-laundering regimes and is enforced through obligations such as customer due diligence, transaction monitoring, and reporting of suspicious activity. In digital assets, CTF underpins requirements like the FATF Travel Rule that mandate originator and beneficiary information for transfers."@en ;
rdfs:label "Counter-Terrorist Financing"@en ;
rdfs:subClassOf ngm:financial-regulation ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:travel-rule ;
vc:slug "counter-terrorist-financing" ;
vc:sourceDomain "blockchain" .
ngm:countercyclical-capital-buffer a skos:Concept ;
rdfs:label "Countercyclical Capital Buffer"@en .
ngm:counterfactual-analysis a skos:Concept ;
rdfs:label "Counterfactual Analysis"@en .
ngm:counterfactual-explanation a owl:Class ;
rdfs:comment "An explainable-AI method that accounts for a model's decision by presenting the smallest realistic change to the input that would have produced a different outcome — for example, 'the loan would have been approved had annual income been £5,000 higher' — giving affected individuals actionable recourse without requiring disclosure of the model's internal structure."@en ;
rdfs:label "Counterfactual Explanation"@en ;
rdfs:subClassOf ngm:explainability ;
vc:enables ngm:decision-transparency ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:explainable-ai ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:counterfactual-reasoning ;
vc:relatedTo ngm:lime ;
vc:relatedTo ngm:shap ;
vc:slug "counterfactual-explanation" ;
vc:sourceDomain "ai" .
ngm:counterfactual-fairness a skos:Concept ;
rdfs:label "Counterfactual Fairness"@en .
ngm:counterfactual-reasoning a owl:Class ;
rdfs:comment "Counterfactual reasoning is the process of inferring what would have happened under a hypothetical intervention or alternative set of conditions, contrary to what was actually observed, given a causal model of a system. It sits at the top of Pearl's ladder of causation, above association and intervention, and requires a structural causal model rather than observational data alone to answer 'what if' questions such as the effect of a different action or policy. In machine learning, counterfactual reasoning underpins causal inference methods, explainable AI techniques and world models that must predict consequences of actions not actually taken."@en ;
rdfs:label "Counterfactual Reasoning"@en ;
rdfs:subClassOf ngm:causal-inference ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:causal-inference ;
vc:qualityScore "0.55"^^xsd:float ;
vc:relatedTo ngm:causal-inference ;
vc:relatedTo ngm:world-model ;
vc:slug "counterfactual-reasoning" ;
vc:sourceDomain "machine-learning" .
ngm:counterparty-protocol a skos:Concept ;
rdfs:label "Counterparty Protocol"@en .
ngm:counterparty-risk a owl:Class ;
rdfs:comment "Counterparty Risk is the risk that the other party to a financial transaction or contract will fail to meet its obligations before settlement, causing loss to the non-defaulting party. It is central to derivatives, lending and securities trading, and is managed through collateral, netting and central clearing. Blockchain settlement and atomic swaps aim to reduce counterparty risk by removing reliance on trusted intermediaries."@en ;
rdfs:label "Counterparty Risk"@en ;
rdfs:subClassOf ngm:risk-management ;
vc:contrastsWith ngm:systemic-risk ;
vc:dependsOn ngm:verification ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:risk-management ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:de-fi ;
vc:relatedTo ngm:finance ;
vc:slug "counterparty-risk" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:blockchain ;
vc:uses ngm:clearing-house .
ngm:counting-complexity a skos:Concept ;
rdfs:label "Counting Complexity"@en .
ngm:coupling a skos:Concept ;
rdfs:label "Coupling"@en .
ngm:coupling-layer a skos:Concept ;
rdfs:label "Coupling Layer"@en .
ngm:covariance-decomposition a skos:Concept ;
rdfs:label "Covariance Decomposition"@en .
ngm:covariance-matrix a owl:Class ;
rdfs:comment "A covariance matrix is a square symmetric positive semi-definite matrix whose (i,j) entry is the covariance between the i-th and j-th components of a multivariate random variable, with variances on the main diagonal. It completely characterises the second-order statistics and linear dependence structure of a multivariate distribution, and — together with the mean vector — fully specifies a multivariate Gaussian. The covariance matrix is central to multivariate statistics, machine learning, state estimation, signal processing, and finance, serving as the fundamental data structure for representing and propagating uncertainty in high-dimensional systems."@en ;
rdfs:label "Covariance Matrix"@en ;
rdfs:subClassOf ngm:linear-algebra ;
rdfs:subClassOf ngm:multivariate-statistics ;
rdfs:subClassOf ngm:statistical-object ;
rdfs:subClassOf _:r5922 ;
rdfs:subClassOf _:r5923 ;
rdfs:subClassOf _:r5924 ;
vc:contrastsWith ngm:correlation-matrix ;
vc:contrastsWith ngm:precision-matrix ;
vc:dependsOn ngm:gaussian-distribution ;
vc:dependsOn ngm:random-variable ;
vc:enables ngm:dimensionality-reduction ;
vc:enables ngm:factor-analysis ;
vc:enables ngm:mahalanobis-distance ;
vc:enables ngm:portfolio-optimisation ;
vc:enables ngm:principal-component-analysis ;
vc:enables ngm:whitening ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:correlation-matrix ;
vc:hasPart ngm:eigendecomposition ;
vc:hasPart ngm:variance ;
vc:implements ngm:expectation-maximisation ;
vc:implements ngm:maximum-likelihood-estimation ;
vc:isPartOf ngm:gaussian-distribution ;
vc:isPartOf ngm:probability-distribution ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:cost-function ;
vc:relatedTo ngm:data-preprocessing ;
vc:relatedTo ngm:feature-extraction ;
vc:relatedTo ngm:gaussian-distribution ;
vc:relatedTo ngm:probability-distribution ;
vc:relatedTo ngm:random-matrix-theory ;
vc:relatedTo ngm:regularisation ;
vc:relatedTo ngm:signal-processing ;
vc:relatedTo ngm:vae ;
vc:requires ngm:linear-algebra ;
vc:requires ngm:multivariate-data ;
vc:requires ngm:probability-theory ;
vc:slug "covariance-matrix" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:iso-iec-22989-2022 ;
vc:supports ngm:anomaly-detection ;
vc:supports ngm:bayesian-inference ;
vc:supports ngm:extended-kalman-filter ;
vc:supports ngm:gaussian-process ;
vc:supports ngm:kalman-filter ;
vc:supports ngm:sensor-fusion ;
vc:supports ngm:slam ;
vc:supports ngm:state-estimation ;
vc:uses ngm:eigendecomposition ;
vc:uses ngm:feature-extraction ;
vc:uses ngm:singular-value-decomposition .
ngm:covariate-shift a skos:Concept ;
rdfs:label "Covariate Shift"@en .
ngm:covariates a skos:Concept ;
rdfs:label "Covariates"@en .
ngm:cover-medium a skos:Concept ;
rdfs:label "Cover Medium"@en .
ngm:coverage-guarantee a skos:Concept ;
rdfs:label "Coverage Guarantee"@en .
ngm:coverage-penalty a skos:Concept ;
rdfs:label "Coverage Penalty"@en .
ngm:covert-ai-tool-adoption-risk a owl:Class ;
rdfs:comment "The Secret Cyborg Problem describes the widespread but concealed practice of workers integrating AI tools into professional workflows without disclosure to employers or colleagues, creating risks around data governance, accountability, and skills assessment. Research indicates approximately 78% of AI-using knowledge workers employ tools covertly, undermining organisational AI adoption strategies and responsible-use frameworks."@en ;
rdfs:label "Covert AI Tool Adoption Risk"@en ;
rdfs:subClassOf ngm:software-engineering ;
vc:contrastsWith ngm:ai-governance ;
vc:contrastsWith ngm:trust-in-automation ;
vc:enables ngm:workforce-augmentation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:ai-adoption ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:generative-ai ;
vc:slug "covert-ai-tool-adoption-risk" ;
vc:sourceDomain "infrastructure" .
ngm:cowos-packaging a skos:Concept ;
rdfs:label "Cowos Packaging"@en .
ngm:cpmi a skos:Concept ;
rdfs:label "Cpmi"@en .
ngm:cpmi-cross-border-payment-standards a skos:Concept ;
rdfs:label "Cpmi Cross Border Payment Standards"@en .
ngm:cpmi-fast-payment-system-standards a skos:Concept ;
rdfs:label "Cpmi Fast Payment System Standards"@en .
ngm:cpmi-iosco-pfmi a owl:Class ;
rdfs:comment "The Principles for Financial Market Infrastructures are international standards published by the Committee on Payments and Market Infrastructures and the International Organization of Securities Commissions. They set requirements for the safety and efficiency of payment, clearing and settlement systems."@en ;
rdfs:label "CPMI-IOSCO PFMI"@en ;
rdfs:subClassOf ngm:payment-system ;
rdfs:subClassOf _:r3788 ;
vc:bridgesTo ngm:central-bank ;
vc:enables ngm:swift-messaging ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:payment-system ;
vc:slug "cpmi-iosco-pfmi" ;
vc:sourceDomain "finance" .
ngm:cpu a owl:Class ;
rdfs:comment "A central processing unit (CPU) is the primary general-purpose processor of a computer, responsible for fetching, decoding, and executing the instructions of programs. It performs arithmetic, logic, control, and input/output operations dictated by software, coordinating the activity of the whole machine. As a versatile sequential and lightly parallel engine, the CPU contrasts with specialised accelerators such as GPUs that favour massive data parallelism."@en ;
rdfs:label "CPU"@en ;
rdfs:subClassOf ngm:hardware ;
rdfs:subClassOf _:r3792 ;
rdfs:subClassOf _:r3793 ;
rdfs:subClassOf _:r3794 ;
vc:contrastsWith ngm:gpu ;
vc:dependsOn ngm:instruction-set-architecture ;
vc:dependsOn ngm:memory ;
vc:enables ngm:operating-system ;
vc:enables ngm:parallel-computing ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:cache-layer ;
vc:hasPart ngm:instruction-set-architecture ;
vc:isPartOf ngm:compute-resources ;
vc:isPartOf ngm:hardware ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:computer-architecture ;
vc:relatedTo ngm:latency ;
vc:relatedTo ngm:throughput ;
vc:requires ngm:clock-speed ;
vc:requires ngm:memory ;
vc:slug "cpu" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:operating-system ;
vc:uses ngm:cache-layer .
ngm:cpu-architecture a owl:Class ;
rdfs:comment "CPU architecture is the design of general-purpose central processors optimised for low-latency execution of sequential and branch-heavy code: a small number of powerful cores with deep pipelines, aggressive out-of-order execution, sophisticated branch prediction, and large multi-level caches. It is the deliberate opposite pole to GPU architecture, which trades single-thread latency for massive throughput; CPUs devote silicon to making one instruction stream fast, GPUs to running tens of thousands of streams concurrently."@en ;
rdfs:label "CPU Architecture"@en ;
rdfs:subClassOf ngm:computer-hardware ;
rdfs:subClassOf _:r3789 ;
vc:contrastsWith ngm:gpu-architecture ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:instruction-set-architecture ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:cpu ;
vc:relatedTo ngm:parallel-computing ;
vc:relatedTo ngm:simd ;
vc:slug "cpu-architecture" ;
vc:sourceDomain "infrastructure" .
ngm:cpu-centric-datacentre a skos:Concept ;
rdfs:label "Cpu Centric Datacentre"@en .
ngm:cpu-compute a skos:Concept ;
rdfs:label "Cpu Compute"@en .
ngm:cpu-computing a owl:Class ;
rdfs:comment "CPU computing is the execution of computational workloads on a general-purpose central processing unit, which performs instructions sequentially across a small number of high-clock cores optimised for low latency and complex control flow. It excels at branch-heavy, irregular, and serial tasks but contrasts with the massively parallel throughput model of GPU computing. CPUs follow a stored-program architecture with deep cache hierarchies, out-of-order execution, and rich instruction sets."@en ;
rdfs:label "CPU Computing"@en ;
rdfs:subClassOf ngm:parallel-computing ;
rdfs:subClassOf _:r3790 ;
rdfs:subClassOf _:r3791 ;
vc:bridgesTo ngm:gpu ;
vc:contrastsWith ngm:gpu-computing ;
vc:dependsOn ngm:integrated-circuit ;
vc:enables ngm:hardware-acceleration ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:cpu ;
vc:isPartOf ngm:hardware ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:graphics-processing-unit ;
vc:relatedTo ngm:parallel-computing ;
vc:requires ngm:semiconductor ;
vc:slug "cpu-computing" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:compute-shader ;
vc:uses ngm:central-processing-unit ;
vc:uses ngm:instruction-set-architecture .
ngm:cpu-mining a skos:Concept ;
rdfs:label "Cpu Mining"@en .
ngm:cpu-only-inference a skos:Concept ;
rdfs:label "Cpu Only Inference"@en .
ngm:cpu-rendering a skos:Concept ;
rdfs:label "Cpu Rendering"@en .
ngm:cpython a skos:Concept ;
rdfs:label "Cpython"@en .
ngm:cqrs a owl:Class ;
rdfs:comment "Command Query Responsibility Segregation (CQRS) is a software architecture pattern that separates the model used to update state (commands) from the model used to read state (queries). By using distinct write and read paths, systems can independently optimise, scale, and secure each side, often pairing the write model with event sourcing. It is commonly applied in high-throughput, complex-domain systems where read and write workloads diverge."@en ;
rdfs:label "CQRS"@en ;
rdfs:subClassOf ngm:software-architecture ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:crdt ;
vc:relatedTo ngm:data-layer ;
vc:slug "cqrs" ;
vc:sourceDomain "infrastructure" .
ngm:cqrs-pattern a skos:Concept ;
rdfs:label "Cqrs Pattern"@en .
ngm:cradle-to-cradle-design a owl:Class ;
rdfs:comment "Cradle-to-Cradle design is a sustainability framework in which products are conceived so that all materials become safe nutrients for biological or technical cycles, eliminating the concept of waste. It emphasises material health, reuse, renewable energy, and closed-loop recovery rather than the linear take-make-dispose model. It is a foundational design philosophy within the circular economy."@en ;
rdfs:label "Cradle-to-Cradle Design"@en ;
rdfs:subClassOf ngm:sustainability ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:circular-economy ;
vc:slug "cradle-to-cradle-design" ;
vc:sourceDomain "supply-chain" .
ngm:crafted-perturbations a skos:Concept ;
rdfs:label "Crafted Perturbations"@en .
ngm:crash-fault-model a skos:Concept ;
rdfs:label "Crash Fault Model"@en .
ngm:crash-fault-tolerance a owl:Class ;
rdfs:comment "Crash fault tolerance is the property of a distributed system that continues to operate correctly despite nodes failing by stopping, that is, by halting and ceasing to send messages. It assumes the crash-stop or crash-recovery failure model, in which faulty processes do not behave maliciously or send incorrect information. Protocols such as Paxos and Raft achieve it through replication and consensus over a quorum of non-faulty nodes."@en ;
rdfs:label "Crash Fault Tolerance"@en ;
rdfs:subClassOf ngm:fault-tolerance ;
rdfs:subClassOf _:r5925 ;
rdfs:subClassOf _:r5926 ;
vc:bridgesTo ngm:distributed-consensus ;
vc:contrastsWith ngm:byzantine-fault-tolerance ;
vc:dependsOn ngm:consensus-protocol ;
vc:dependsOn ngm:leader-election ;
vc:enables ngm:high-availability ;
vc:enables ngm:state-machine-replication ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:paxos ;
vc:implements ngm:raft ;
vc:isPartOf ngm:distributed-consensus ;
vc:isPartOf ngm:fault-tolerance ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:consensus-protocol ;
vc:relatedTo ngm:quorum ;
vc:requires ngm:quorum ;
vc:requires ngm:replication ;
vc:slug "crash-fault-tolerance" ;
vc:sourceDomain "distributed-systems" ;
vc:supports ngm:state-machine-replication ;
vc:uses ngm:leader-election ;
vc:uses ngm:replication .
ngm:crash-fault-tolerant-ordering a skos:Concept ;
rdfs:label "Crash Fault Tolerant Ordering"@en .
ngm:crash-fault-tolerant-system a skos:Concept ;
rdfs:label "Crash Fault Tolerant System"@en .
ngm:crash-only-recovery-without-consensus a skos:Concept ;
rdfs:label "Crash Only Recovery Without Consensus"@en .
ngm:crash-recovery a skos:Concept ;
rdfs:label "Crash Recovery"@en .
ngm:crash-simulation a skos:Concept ;
rdfs:label "Crash Simulation"@en .
ngm:crawl-frontier a skos:Concept ;
rdfs:label "Crawl Frontier"@en .
ngm:crawl-statistics a skos:Concept ;
rdfs:label "Crawl Statistics"@en .
ngm:crdt a owl:Class ;
rdfs:comment "Conflict-free Replicated Data Types (CRDTs) are a family of data structures with mathematically proven convergence guarantees that allow multiple distributed replicas to be independently modified without requiring coordination, locks, or a consensus protocol, and which automatically merge to a si..."@en ;
rdfs:label "CRDT"@en ;
rdfs:subClassOf ngm:commutative-data-structure ;
rdfs:subClassOf ngm:dc-protocol-and-infra ;
rdfs:subClassOf ngm:distributed-data-synchronisation ;
rdfs:subClassOf ngm:eventually-consistent-data-structure ;
rdfs:subClassOf ngm:mergeable-data-type ;
rdfs:subClassOf ngm:monotone-data-structure ;
rdfs:subClassOf ngm:replicated-data-structure ;
rdfs:subClassOf _:r3795 ;
rdfs:subClassOf _:r3796 ;
rdfs:subClassOf _:r3797 ;
rdfs:subClassOf _:r3798 ;
rdfs:subClassOf _:r3799 ;
rdfs:subClassOf _:r3800 ;
rdfs:subClassOf _:r3801 ;
rdfs:subClassOf _:r3802 ;
skos:broader ngm:dc-protocol-and-infra ;
vc:bridgesTo ngm:infra-network-and-comms ;
vc:contrastsWith ngm:operational-transformation ;
vc:contrastsWith ngm:optimistic-locking ;
vc:contrastsWith ngm:paxos ;
vc:contrastsWith ngm:pessimistic-locking ;
vc:contrastsWith ngm:raft-consensus ;
vc:contrastsWith ngm:strong-consistency ;
vc:contrastsWith ngm:two-phase-commit ;
vc:dependsOn ngm:cap-theorem ;
vc:dependsOn ngm:causal-consistency ;
vc:dependsOn ngm:distributed-systems ;
vc:dependsOn ngm:eventual-consistency ;
vc:dependsOn ngm:lamport-timestamps ;
vc:dependsOn ngm:lattice-theory ;
vc:dependsOn ngm:order-theory ;
vc:dependsOn ngm:vector-clocks ;
vc:enables ngm:coordination-free-computing ;
vc:enables ngm:distributed-databases ;
vc:enables ngm:local-first-software ;
vc:enables ngm:offline-first-collaboration ;
vc:enables ngm:real-time-collaborative-editing ;
vc:enables ngm:replication ;
vc:enables ngm:synchronisation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:causal-history-graph ;
vc:hasPart ngm:causal-ordering ;
vc:hasPart ngm:delta-state ;
vc:hasPart ngm:g-counter ;
vc:hasPart ngm:g-set ;
vc:hasPart ngm:join-semilattice ;
vc:hasPart ngm:lww-element-set ;
vc:hasPart ngm:or-set ;
vc:hasPart ngm:replicated-growable-array ;
vc:hasPart ngm:tombstone-record ;
vc:hasPart ngm:unique-identifier ;
vc:hasPart ngm:vector-clocks ;
vc:hasPart ngm:version-vector ;
vc:implements ngm:associativity ;
vc:implements ngm:causal-broadcast ;
vc:implements ngm:commutativity ;
vc:implements ngm:eventual-consistency ;
vc:implements ngm:idempotency ;
vc:implements ngm:join-semilattice ;
vc:implements ngm:state-lattice-merge ;
vc:implements ngm:synchronisation ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:blockchain-network ;
vc:relatedTo ngm:byzantine-fault-tolerance ;
vc:relatedTo ngm:cqrs ;
vc:relatedTo ngm:distributed-ledger ;
vc:relatedTo ngm:event-sourcing ;
vc:relatedTo ngm:local-first-software ;
vc:relatedTo ngm:merkle-dag ;
vc:relatedTo ngm:nostr-protocol ;
vc:requires ngm:causal-broadcast-protocol ;
vc:requires ngm:causal-delivery ;
vc:requires ngm:eventual-consistency ;
vc:requires ngm:idempotent-merge ;
vc:requires ngm:join-semilattice ;
vc:requires ngm:monotone-operations ;
vc:requires ngm:unique-replica-identifiers ;
vc:slug "crdt" ;
vc:sourceDomain "distributed-collaboration" ;
vc:standardizedBy ngm:inria-technical-report-rr-7506 ;
vc:standardizedBy ngm:shapiro-et-al-2011-socc ;
vc:standardizedBy ngm:syncfree-eu-project-fp7-ict-2011-7-609551 ;
vc:supports ngm:collaboration-tools ;
vc:supports ngm:collaborative-systems-modality ;
vc:supports ngm:distributed-databases ;
vc:supports ngm:edge-computing ;
vc:supports ngm:local-first-software ;
vc:supports ngm:mobile-sync ;
vc:supports ngm:real-time-collaborative-editing ;
vc:supports ngm:synchronisation ;
vc:uses ngm:causal-history ;
vc:uses ngm:join-semilattice ;
vc:uses ngm:logical-clocks ;
vc:uses ngm:merkle-dag ;
vc:uses ngm:unique-identifiers-per-replica ;
vc:uses ngm:vector-clocks ;
vc:uses ngm:version-vectors .
ngm:crdt-academic-literature a skos:Concept ;
rdfs:label "CRDT Academic Literature"@en .
ngm:crdts a skos:Concept ;
rdfs:label "Crdts"@en .
ngm:creation-unit-basket a skos:Concept ;
rdfs:label "Creation Unit Basket"@en .
ngm:creative-ai a owl:Class ;
rdfs:comment "Creative AI refers to artificial intelligence systems designed to generate, augment, or evaluate creative artefacts — including images, music, text, video, and interactive experiences — by learning latent representations of aesthetic structure from large corpora of human-produced works. Drawing on generative architectures such as diffusion models, large language models, transformers, and generative adversarial networks, these systems can synthesise novel content that extends or stylistically mimics human creative practice. They are deployed across professional creative pipelines in entertainment, advertising, game development, and design, while simultaneously raising contested questions of authorship, copyright, and economic disruption for human creators. Creative AI represents the convergence of machine learning research with aesthetic domains historically regarded as uniquely human, positioning it as both a technical milestone and a socio-cultural inflection point."@en ;
rdfs:label "Creative AI"@en ;
rdfs:subClassOf ngm:computational-creativity ;
rdfs:subClassOf ngm:deep-learning ;
rdfs:subClassOf ngm:generative-ai ;
rdfs:subClassOf _:r5927 ;
rdfs:subClassOf _:r5928 ;
rdfs:subClassOf _:r5929 ;
rdfs:subClassOf _:r5930 ;
rdfs:subClassOf _:r5931 ;
rdfs:subClassOf _:r5932 ;
rdfs:subClassOf _:r5933 ;
rdfs:subClassOf _:r5934 ;
rdfs:subClassOf _:r5935 ;
rdfs:subClassOf _:r5936 ;
rdfs:subClassOf _:r5937 ;
rdfs:subClassOf _:r5938 ;
rdfs:subClassOf _:r5939 ;
vc:bridgesTo ngm:augmented-reality ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:metaverse ;
vc:contrastsWith ngm:discriminative-ai ;
vc:contrastsWith ngm:rule-based-systems ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:gpu-compute ;
vc:dependsOn ngm:training-data ;
vc:enables ngm:ai-art ;
vc:enables ngm:automated-design ;
vc:enables ngm:content-creation ;
vc:enables ngm:digital-content-creation ;
vc:enables ngm:image-generation ;
vc:enables ngm:music-generation ;
vc:enables ngm:procedural-content-generation ;
vc:enables ngm:text-to-image ;
vc:enables ngm:text-to-speech ;
vc:enables ngm:video-generation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:clip ;
vc:hasPart ngm:diffusion-model ;
vc:hasPart ngm:foundation-model ;
vc:hasPart ngm:generative-adversarial-network ;
vc:hasPart ngm:large-language-models ;
vc:hasPart ngm:style-transfer ;
vc:hasPart ngm:transformer ;
vc:hasPart ngm:vae ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:computational-creativity ;
vc:relatedTo ngm:copyright ;
vc:relatedTo ngm:creative-industries ;
vc:relatedTo ngm:human-ai-collaboration ;
vc:relatedTo ngm:multimodal-model ;
vc:relatedTo ngm:prompt-engineering ;
vc:relatedTo ngm:synthetic-media ;
vc:requires ngm:deep-learning ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:large-scale-datasets ;
vc:requires ngm:latent-space ;
vc:requires ngm:training-data ;
vc:slug "creative-ai" ;
vc:sourceDomain "ai" ;
vc:supports ngm:fashion ;
vc:supports ngm:film-production ;
vc:supports ngm:game-development ;
vc:supports ngm:human-ai-collaboration ;
vc:uses ngm:clip ;
vc:uses ngm:diffusion-model ;
vc:uses ngm:foundation-model ;
vc:uses ngm:generative-adversarial-network ;
vc:uses ngm:large-language-models ;
vc:uses ngm:latent-space ;
vc:uses ngm:multimodal-model ;
vc:uses ngm:prompt-engineering ;
vc:uses ngm:style-transfer ;
vc:uses ngm:transformer ;
vc:uses ngm:vae .
ngm:creative-application-classification a skos:Concept ;
rdfs:label "Creative Application Classification"@en .
ngm:creative-automation a skos:Concept ;
rdfs:label "Creative Automation"@en .
ngm:creative-collaboration a skos:Concept ;
rdfs:label "Creative Collaboration"@en .
ngm:creative-commons a owl:Class ;
rdfs:comment "Creative Commons is a family of standardised public copyright licences that let creators grant defined reuse, attribution, and sharing permissions to the public. The licences (e.g. CC BY, CC BY-SA, CC0) provide machine-readable and human-readable terms that promote legal reuse of content. They are widely used to license training data, open educational resources, and open media corpora."@en ;
rdfs:label "Creative Commons"@en ;
rdfs:subClassOf ngm:infra-legal-and-regulatory ;
skos:broader ngm:infra-legal-and-regulatory ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:training-data ;
vc:slug "creative-commons" ;
vc:sourceDomain "infrastructure" .
ngm:creative-content-generation a skos:Concept ;
rdfs:label "Creative Content Generation"@en .
ngm:creative-economy a skos:Concept ;
rdfs:label "Creative Economy"@en .
ngm:creative-evaluation-framework a skos:Concept ;
rdfs:label "Creative Evaluation Framework"@en .
ngm:creative-expression a owl:Class ;
rdfs:comment "Creative expression is the human activity of producing original artistic, narrative, or aesthetic artefacts to communicate ideas, emotions, or identity. In virtual and open-world environments it manifests as user-generated content, world-building, avatar customisation, and emergent play. It is a primary driver of engagement and value in persistent metaverse spaces."@en ;
rdfs:label "Creative Expression"@en ;
rdfs:subClassOf ngm:sc-interaction ;
skos:broader ngm:sc-interaction ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:open-world ;
vc:relatedTo ngm:virtual-world ;
vc:slug "creative-expression" ;
vc:sourceDomain "metaverse" .
ngm:creative-industries a owl:Class ;
rdfs:comment "The creative industries are the economic sectors that generate value primarily from individual creativity, skill, and intellectual property, spanning design, fashion, film, music, gaming, advertising, architecture, and publishing. They combine cultural production with commercial distribution and are increasingly reshaped by generative AI tooling. As an economic domain they constitute a significant employer and exporter of cultural goods — contributing £124 billion in gross value added to the UK economy in 2023 — while simultaneously representing the sector most affected by unresolved questions of copyright, training data use, and AI-enabled labour displacement."@en ;
rdfs:label "Creative Industries"@en ;
rdfs:subClassOf ngm:economics ;
rdfs:subClassOf ngm:knowledge-economy ;
rdfs:subClassOf _:r5940 ;
rdfs:subClassOf _:r5941 ;
rdfs:subClassOf _:r5942 ;
rdfs:subClassOf _:r5943 ;
rdfs:subClassOf _:r5944 ;
rdfs:subClassOf _:r5945 ;
rdfs:subClassOf _:r5946 ;
rdfs:subClassOf _:r5947 ;
rdfs:subClassOf _:r5948 ;
rdfs:subClassOf _:r5949 ;
rdfs:subClassOf _:r5950 ;
vc:bridgesTo ngm:augmented-reality ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:metaverse ;
vc:dependsOn ngm:copyright ;
vc:dependsOn ngm:data-governance ;
vc:dependsOn ngm:licensing ;
vc:enables ngm:ai-art-generation ;
vc:enables ngm:content-creation ;
vc:enables ngm:cultural-heritage ;
vc:enables ngm:digital-fashion ;
vc:enables ngm:platform-economy ;
vc:enables ngm:synthetic-media ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:advertising ;
vc:hasPart ngm:design ;
vc:hasPart ngm:digital-content-creation ;
vc:hasPart ngm:fashion ;
vc:hasPart ngm:film-production ;
vc:hasPart ngm:film-vfx ;
vc:hasPart ngm:game-development ;
vc:hasPart ngm:music-generation ;
vc:hasPart ngm:publishing ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:ai-companies ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:ai-regulation ;
vc:relatedTo ngm:freelance-economy ;
vc:relatedTo ngm:human-ai-collaboration ;
vc:relatedTo ngm:nft ;
vc:relatedTo ngm:procedural-content-generation ;
vc:relatedTo ngm:synthetic-media ;
vc:requires ngm:copyright ;
vc:requires ngm:data-governance ;
vc:requires ngm:intellectual-property-rights-framework ;
vc:requires ngm:licensing ;
vc:slug "creative-industries" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:ai-regulation ;
vc:standardizedBy ngm:intellectual-property-rights-framework ;
vc:supports ngm:human-ai-collaboration ;
vc:supports ngm:knowledge-economy ;
vc:uses ngm:automated-design ;
vc:uses ngm:creative-ai ;
vc:uses ngm:creative-software ;
vc:uses ngm:diffusion-model ;
vc:uses ngm:foundation-model ;
vc:uses ngm:generative-ai ;
vc:uses ngm:image-generation ;
vc:uses ngm:large-language-models ;
vc:uses ngm:text-to-image ;
vc:uses ngm:text-to-speech .
ngm:creative-media a skos:Concept ;
rdfs:label "Creative Media"@en .
ngm:creative-software a owl:Class ;
rdfs:comment "Application software designed to support artistic, design, and content production workflows, including 3D modelling, animation, compositing, generative art, and interactive experience authoring. In spatial computing contexts, creative software bridges concept and deployment by enabling artists to produce assets compatible with real-time rendering engines and metaverse platforms."@en ;
rdfs:label "Creative Software"@en ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf _:r5951 ;
rdfs:subClassOf _:r5952 ;
skos:broader ngm:sc-platform-and-environment ;
vc:enables ngm:3-d-content-generation ;
vc:enables ngm:creative-tools ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:animation-software ;
vc:hasPart ngm:design-software ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:game-engine ;
vc:relatedTo ngm:rendering-engine ;
vc:slug "creative-software" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:computer-graphics ;
vc:uses ngm:computer-vision .
ngm:creative-tools a owl:Class ;
rdfs:comment "Creative Tools are AI-powered and digitally-augmented software applications that assist, augment, or automate human creative processes across modalities including image generation, music composition, video synthesis, 3D asset creation, and long-form text authoring. They typically expose foundation models—particularly diffusion models and large language models—through interactive interfaces or programmable API endpoints, enabling both professionals and non-expert users to produce high-quality creative outputs. Their role is dual: serving as productivity accelerators for practitioners and as accessibility bridges lowering barriers to creative expression. Provenance attribution, intellectual property frameworks, and content authentication standards such as C2PA are active governance concerns around AI-generated content produced by these tools."@en ;
rdfs:label "Creative Tools"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:generative-ai ;
rdfs:subClassOf _:r5953 ;
rdfs:subClassOf _:r5954 ;
rdfs:subClassOf _:r5955 ;
rdfs:subClassOf _:r5956 ;
rdfs:subClassOf _:r5957 ;
rdfs:subClassOf _:r5958 ;
skos:broader ngm:ai-application ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:metaverse-content ;
vc:bridgesTo ngm:spatial-computing ;
vc:contrastsWith ngm:design-software ;
vc:contrastsWith ngm:procedural-generation ;
vc:dependsOn ngm:api ;
vc:dependsOn ngm:fine-tuning ;
vc:dependsOn ngm:reinforcement-learning-from-human-feedback ;
vc:dependsOn ngm:training-data ;
vc:enables ngm:3d-asset-creation ;
vc:enables ngm:content-creation ;
vc:enables ngm:image-generation ;
vc:enables ngm:music-generation ;
vc:enables ngm:text-to-image ;
vc:enables ngm:video-synthesis ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:asset-management ;
vc:hasPart ngm:foundation-model ;
vc:hasPart ngm:inference-interface ;
vc:hasPart ngm:output-pipeline ;
vc:hasPart ngm:prompt-engineering ;
vc:implements ngm:c2-pa ;
vc:implements ngm:content-provenance ;
vc:implements ngm:retrieval-augmented-generation ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:ai-application ;
vc:relatedTo ngm:c2-pa ;
vc:relatedTo ngm:content-provenance ;
vc:relatedTo ngm:digital-twin ;
vc:relatedTo ngm:eu-ai-act-regulatory-instrument ;
vc:relatedTo ngm:human-ai-collaboration ;
vc:relatedTo ngm:intellectual-property-rights-framework ;
vc:relatedTo ngm:metaverse-content ;
vc:relatedTo ngm:spatial-computing ;
vc:requires ngm:foundation-model ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:training-data ;
vc:slug "creative-tools" ;
vc:sourceDomain "ai" ;
vc:supports ngm:creative-economy ;
vc:supports ngm:human-ai-collaboration ;
vc:supports ngm:human-computer-interaction ;
vc:uses ngm:diffusion-model ;
vc:uses ngm:generative-adversarial-network ;
vc:uses ngm:generative-ai ;
vc:uses ngm:large-language-model ;
vc:uses ngm:latent-diffusion ;
vc:uses ngm:multimodal-model ;
vc:uses ngm:prompt-engineering ;
vc:uses ngm:transformer .
ngm:creative-workflow-automation a skos:Concept ;
rdfs:label "Creative Workflow Automation"@en .
ngm:creative-writing a skos:Concept ;
rdfs:label "Creative Writing"@en .
ngm:creativemediadomain a skos:Concept ;
rdfs:label "Creativemediadomain"@en .
ngm:creator-attribution a skos:Concept ;
rdfs:label "Creator Attribution"@en .
ngm:creator-compensation a owl:Class ;
rdfs:comment "Creator compensation refers to the economic mechanisms by which content creators are paid for their work, including royalties, revenue sharing, tipping, and tokenised ownership rights. In blockchain contexts it is often automated through smart contracts that distribute proceeds on primary sale and secondary resale. It is central to sustainable creator economies and to debates over fair value capture on digital platforms."@en ;
rdfs:label "Creator Compensation"@en ;
rdfs:subClassOf ngm:economic-mechanism ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:creator-royalty-token ;
vc:relatedTo ngm:royalty-mechanism ;
vc:slug "creator-compensation" ;
vc:sourceDomain "blockchain" .
ngm:creator-economy a owl:Class ;
rdfs:comment "Ecosystem enabling individuals and organizations to design, build, and monetize virtual content and experiences through digital marketplaces, tokenization, and economic incentive structures."@en ;
rdfs:label "Creator Economy"@en ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf _:r5959 ;
rdfs:subClassOf _:r5960 ;
rdfs:subClassOf _:r5961 ;
rdfs:subClassOf _:r5962 ;
rdfs:subClassOf _:r5963 ;
rdfs:subClassOf _:r5964 ;
rdfs:subClassOf _:r5965 ;
rdfs:subClassOf _:r5966 ;
rdfs:subClassOf _:r5967 ;
rdfs:subClassOf _:r5968 ;
rdfs:subClassOf _:r5969 ;
rdfs:subClassOf _:r5970 ;
skos:broader ngm:sc-platform-and-environment ;
vc:bridgesTo ngm:blockchain ;
vc:dependsOn ngm:content-licensing ;
vc:dependsOn ngm:decentralized-exchange-dex ;
vc:dependsOn ngm:virtual-currency ;
vc:enables ngm:creator-monetization ;
vc:enables ngm:digital-asset-trading ;
vc:enables ngm:nft-minting ;
vc:enables ngm:royalty-distribution ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:content-distribution ;
vc:hasPart ngm:creator-royalty-token ;
vc:hasPart ngm:digital-asset-workflow ;
vc:hasPart ngm:digital-goods ;
vc:hasPart ngm:digital-marketplace ;
vc:hasPart ngm:metaverse-content-pipeline ;
vc:hasPart ngm:monetization-system ;
vc:hasPart ngm:token-economy ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:blockchain ;
vc:requires ngm:digital-wallet ;
vc:requires ngm:payment-processing ;
vc:requires ngm:smart-contract ;
vc:slug "creator-economy" ;
vc:sourceDomain "spatial-computing" .
ngm:creator-economy-infrastructure a skos:Concept ;
rdfs:label "Creator Economy Infrastructure"@en .
ngm:creator-economy-platform a skos:Concept ;
rdfs:label "Creator Economy Platform"@en .
ngm:creator-monetization a owl:Class ;
rdfs:comment "Creator Monetization refers to the suite of mechanisms, platforms, and economic models through which independent content creators convert their creative output and audience relationships into sustainable revenue streams. These mechanisms span advertising revenue sharing, subscription and membership tiers, merchandise and physical goods, live events, licensing, and on-chain token-based models including NFTs and creator coins. The field has been shaped by the shift from broadcast media to participatory digital platforms, enabling individuals rather than corporations to capture value from cultural production. Web3 infrastructure is expanding the design space by enabling programmable royalties and direct fan-ownership of creative works."@en ;
rdfs:label "Creator Monetization"@en ;
rdfs:subClassOf ngm:creator-economy ;
rdfs:subClassOf _:r5971 ;
rdfs:subClassOf _:r5972 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:dependsOn ngm:content-distribution ;
vc:dependsOn ngm:digital-payment-system ;
vc:enables ngm:digital-marketplace ;
vc:enables ngm:multi-party-royalties ;
vc:enables ngm:non-fungible-token-nft ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:attention-economy ;
vc:relatedTo ngm:digital-asset ;
vc:relatedTo ngm:gig-economy ;
vc:relatedTo ngm:nft-marketplace ;
vc:relatedTo ngm:platform-economy ;
vc:requires ngm:audience-engagement ;
vc:requires ngm:digital-identity ;
vc:slug "creator-monetization" ;
vc:sourceDomain "finance" ;
vc:uses ngm:creator-royalty-token ;
vc:uses ngm:payment-processing ;
vc:uses ngm:royalty-distribution ;
vc:uses ngm:smart-royalty-contract .
ngm:creator-royalties a owl:Class ;
rdfs:comment "Creator royalties are automatic, programmable payments directed to the original creator of a digital asset — typically an NFT — each time that asset is resold on a secondary market. Encoded in smart contract logic or enforced through marketplace policy, royalties provide creators with a fraction of every subsequent transaction price, extending their economic participation beyond the initial sale. The mechanism is foundational to sustainable creator economies on blockchain platforms, though enforcement remains contested between on-chain protocol enforcement and off-chain marketplace compliance. Debate centres on whether royalty obligations can be made non-bypassable at the token-transfer level or rely on voluntary marketplace co-operation."@en ;
rdfs:label "Creator Royalties"@en ;
rdfs:subClassOf ngm:digital-rights-management ;
rdfs:subClassOf _:r5973 ;
rdfs:subClassOf _:r5974 ;
rdfs:subClassOf _:r5975 ;
vc:bridgesTo ngm:creator-monetization ;
vc:bridgesTo ngm:digital-ownership ;
vc:contrastsWith ngm:marketplace ;
vc:contrastsWith ngm:traditional-copyright ;
vc:dependsOn ngm:nft-marketplace ;
vc:dependsOn ngm:on-chain-governance ;
vc:dependsOn ngm:token-transfer ;
vc:enables ngm:creator-economy ;
vc:enables ngm:marketplace ;
vc:enables ngm:programmable-money ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:de-fi ;
vc:relatedTo ngm:intellectual-property-rights-framework ;
vc:relatedTo ngm:royalty-distribution ;
vc:relatedTo ngm:secondary-market ;
vc:requires ngm:blockchain ;
vc:requires ngm:nft ;
vc:requires ngm:smart-contract ;
vc:slug "creator-royalties" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:eip ;
vc:uses ngm:eip-2981 ;
vc:uses ngm:operator-filter-registry ;
vc:uses ngm:token-standard .
ngm:creator-royalty a skos:Concept ;
rdfs:label "Creator Royalty"@en .
ngm:creator-royalty-token a owl:Class ;
rdfs:comment "Token granting its holder a share of ongoing from creative works, enabling automated royalty distribution and fractional ownership of intellectual property income streams."@en ;
rdfs:label "Creator Royalty Token"@en ;
rdfs:subClassOf ngm:bc-token-and-asset ;
rdfs:subClassOf ngm:virtual-economy ;
rdfs:subClassOf _:r5976 ;
rdfs:subClassOf _:r5977 ;
rdfs:subClassOf _:r5978 ;
rdfs:subClassOf _:r5979 ;
rdfs:subClassOf _:r5980 ;
rdfs:subClassOf _:r5981 ;
rdfs:subClassOf _:r5982 ;
rdfs:subClassOf _:r5983 ;
skos:broader ngm:bc-token-and-asset ;
vc:bridgesTo ngm:ai-agent-system ;
vc:dependsOn ngm:nft-standard ;
vc:dependsOn ngm:payment-gateway ;
vc:dependsOn ngm:revenue-monitoring-service ;
vc:enables ngm:creator-compensation ;
vc:enables ngm:fan-investment ;
vc:enables ngm:ip-monetization ;
vc:enables ngm:revenue-sharing ;
vc:enables ngm:royalty-distribution ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ip-rights-metadata ;
vc:hasPart ngm:ownership-record ;
vc:hasPart ngm:revenue-distribution ;
vc:hasPart ngm:smart-royalty-contract ;
vc:isPartOf ngm:creator-economy ;
vc:isPartOf ngm:intellectual-property-system ;
vc:isPartOf ngm:virtual-economy ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:blockchain ;
vc:requires ngm:digital-wallet ;
vc:requires ngm:royalty-tracking-system ;
vc:requires ngm:smart-contract ;
vc:slug "creator-royalty-token" ;
vc:sourceDomain "blockchain" .
ngm:creator-token a skos:Concept ;
rdfs:label "Creator Token"@en .
ngm:creator-wallet a skos:Concept ;
rdfs:label "Creator Wallet"@en .
ngm:credential-definition a owl:Class ;
rdfs:comment "A credential definition is an on-ledger or registry artefact, published by a credential issuer, that binds a credential schema to the issuer's cryptographic public keys and signing parameters. It specifies the attributes a credential will contain and the cryptographic material verifiers use to validate signatures and zero-knowledge proofs derived from issued credentials. Central to decentralised-identity ecosystems such as those built on AnonCreds, a credential definition lets a holder prove possession of an issuer-signed credential, selectively disclosing only chosen attributes."@en ;
rdfs:label "Credential Definition"@en ;
rdfs:subClassOf ngm:verifiable-credential-standard ;
vc:enables ngm:decentralized-identity ;
vc:enables ngm:self-sovereign-identity ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:identity-provider ;
vc:slug "credential-definition" ;
vc:sourceDomain "security" ;
vc:uses ngm:digital-signature .
ngm:credential-exchange a owl:Class ;
rdfs:comment "Credential exchange is the protocol-governed flow by which verifiable credentials are issued to, held by and presented from a digital identity wallet to relying parties. It defines how issuers offer credentials, how holders store and selectively disclose them, and how verifiers request and validate proofs. It is a foundational interaction pattern of decentralised and self-sovereign identity systems."@en ;
rdfs:label "Credential Exchange"@en ;
rdfs:subClassOf ngm:digital-identity-standards ;
rdfs:subClassOf _:r5984 ;
rdfs:subClassOf _:r5985 ;
rdfs:subClassOf _:r5986 ;
rdfs:subClassOf _:r5987 ;
vc:bridgesTo ngm:zero-knowledge-proof ;
vc:contrastsWith ngm:oauth ;
vc:dependsOn ngm:decentralised-identifier ;
vc:enables ngm:self-sovereign-identity ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:credential-issuance ;
vc:hasPart ngm:presentation-exchange ;
vc:implements ngm:verifiable-credentials ;
vc:isPartOf ngm:digital-identity-standards ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:authentication ;
vc:relatedTo ngm:did-document ;
vc:relatedTo ngm:trust-framework ;
vc:requires ngm:digital-wallet ;
vc:requires ngm:trust-framework ;
vc:slug "credential-exchange" ;
vc:sourceDomain "security" ;
vc:supports ngm:verifiable-credentials ;
vc:uses ngm:decentralised-identifier ;
vc:uses ngm:selective-disclosure .
ngm:credential-format-standard a owl:Class ;
rdfs:comment "Technical specifications defining the structure, encoding, and cryptographic verification methods for digital credentials, enabling secure issuance, storage, and verification of identity documents, certifications, and attestations across different platforms and systems through interoperable formats such as W3C Verifiable Credentials and ISO mDL."@en ;
rdfs:label "Credential Format Standard"@en ;
rdfs:subClassOf ngm:identity-standards ;
rdfs:subClassOf _:r5988 ;
rdfs:subClassOf _:r5989 ;
rdfs:subClassOf _:r5990 ;
rdfs:subClassOf _:r5991 ;
vc:bridgesTo ngm:did-nostr-identity ;
vc:bridgesTo ngm:digital-identity-wallet ;
vc:contrastsWith ngm:saml-assertion ;
vc:enables ngm:credential-verification ;
vc:enables ngm:identity-portability ;
vc:enables ngm:selective-disclosure ;
vc:enables ngm:trust-interoperability ;
vc:enables ngm:zero-knowledge-proof ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:sd-jwt ;
vc:implements ngm:w3-c-verifiable-credentials ;
vc:qualityScore "0.65"^^xsd:float ;
vc:relatedTo ngm:cryptographic-infrastructure ;
vc:relatedTo ngm:identity-verification ;
vc:relatedTo ngm:trust-framework ;
vc:requires ngm:cryptographic-proofs ;
vc:requires ngm:decentralized-identifier ;
vc:requires ngm:digital-signature ;
vc:requires ngm:issuer-infrastructure ;
vc:requires ngm:standards-body ;
vc:slug "credential-format-standard" ;
vc:sourceDomain "security" ;
vc:supports ngm:digital-identity ;
vc:supports ngm:self-sovereign-identity ;
vc:uses ngm:cbor ;
vc:uses ngm:json-ld ;
vc:uses ngm:linked-data .
ngm:credential-framework a skos:Concept ;
rdfs:label "Credential Framework"@en .
ngm:credential-governance a skos:Concept ;
rdfs:label "Credential Governance"@en .
ngm:credential-indexing a skos:Concept ;
rdfs:label "Credential Indexing"@en .
ngm:credential-issuance a owl:Class ;
rdfs:comment "Credential issuance is the process by which an authoritative entity — an issuer — creates, signs, and delivers a structured attestation about a subject's attributes, qualifications, or identity to that subject or to a designated holder. In the W3C Verifiable Credentials model, issuance involves binding claims to a subject's decentralised identifier using the issuer's cryptographic key, producing a tamper-evident credential that the holder can present to verifiers without returning to the issuer. The issuance process encompasses schema selection, claim population, signature generation, and delivery, and may be implemented with varying degrees of issuer privacy, holder binding strength, and revocability."@en ;
rdfs:label "Credential Issuance"@en ;
rdfs:subClassOf ngm:identity-management ;
rdfs:subClassOf _:r5992 ;
rdfs:subClassOf _:r5993 ;
rdfs:subClassOf _:r5994 ;
rdfs:subClassOf _:r5995 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:governance ;
vc:contrastsWith ngm:federated-identity ;
vc:dependsOn ngm:digital-identity ;
vc:dependsOn ngm:trust-framework ;
vc:enables ngm:credential-presentation ;
vc:enables ngm:credential-verification ;
vc:enables ngm:decentralised-identity ;
vc:enables ngm:digital-trust ;
vc:enables ngm:self-sovereign-identity ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:credential-revocation ;
vc:hasPart ngm:holder-binding ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:digital-wallet ;
vc:relatedTo ngm:e-idas ;
vc:requires ngm:certificate-authority ;
vc:requires ngm:identity-proofing ;
vc:requires ngm:key-management ;
vc:slug "credential-issuance" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:sd-jwt-vc ;
vc:standardizedBy ngm:w3-c-verifiable-credentials ;
vc:uses ngm:credential-schema ;
vc:uses ngm:cryptographic-infrastructure ;
vc:uses ngm:cryptographic-signature ;
vc:uses ngm:decentralized-identifiers ;
vc:uses ngm:oauth-2-0 ;
vc:uses ngm:selective-disclosure ;
vc:uses ngm:verifiable-credentials .
ngm:credential-issuer a skos:Concept ;
rdfs:label "Credential Issuer"@en .
ngm:credential-issuer-metadata a skos:Concept ;
rdfs:label "Credential Issuer Metadata"@en .
ngm:credential-management a skos:Concept ;
rdfs:label "Credential Management"@en .
ngm:credential-mapping a skos:Concept ;
rdfs:label "Credential Mapping"@en .
ngm:credential-metadata a skos:Concept ;
rdfs:label "Credential Metadata"@en .
ngm:credential-portability a owl:Class ;
rdfs:comment "Credential portability is the property that lets a holder carry verifiable credentials across providers, platforms, and jurisdictions without re-issuance or vendor lock-in. It relies on open standards such as W3C Verifiable Credentials and decentralised identifiers so that issuers, holders, and verifiers interoperate. It is a foundational capability for user-controlled digital identity and trust frameworks."@en ;
rdfs:label "Credential Portability"@en ;
rdfs:subClassOf ngm:digital-identity ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:digital-identity-wallet ;
vc:relatedTo ngm:trust-framework ;
vc:slug "credential-portability" ;
vc:sourceDomain "security" .
ngm:credential-presentation a owl:Class ;
rdfs:comment "Credential presentation is the process by which a holder of a verifiable credential shares proof of that credential, or selected claims derived from it, with a verifying party in order to satisfy a request, typically as a signed verifiable presentation rather than the raw credential itself. It follows credential issuance in the standard verifiable-credential lifecycle of issuance, storage, presentation and verification, and may use selective disclosure so the holder reveals only the attributes required rather than the full credential. Credential presentation protocols, such as those built on DIDComm or OpenID for Verifiable Presentations, define how the request, proof and response are exchanged between holder and verifier."@en ;
rdfs:label "Credential Presentation"@en ;
rdfs:subClassOf ngm:credential-issuance ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:credential-issuance ;
vc:qualityScore "0.55"^^xsd:float ;
vc:relatedTo ngm:credential-issuance ;
vc:relatedTo ngm:didcomm ;
vc:slug "credential-presentation" ;
vc:sourceDomain "security" .
ngm:credential-registry a skos:Concept ;
rdfs:label "Credential Registry"@en .
ngm:credential-request a skos:Concept ;
rdfs:label "Credential Request"@en .
ngm:credential-revocation a skos:Concept ;
rdfs:label "Credential Revocation"@en .
ngm:credential-schema a owl:Class ;
rdfs:comment "A Credential Schema is a machine-readable, versioned specification — typically expressed in JSON Schema or a JSON-LD vocabulary — that defines the mandatory and optional claims, data types, cardinality constraints, and value ranges permissible within a Verifiable Credential. Schemas function as a binding contract between credential issuers, holders, and verifiers: the issuer populates claims in conformance with a declared schema, the holder's identity wallet stores schema metadata alongside the credential, and the verifier resolves and validates the credential's structure against the schema before applying trust policy decisions. Schemas are published at stable, resolvable URIs and are referenced from the credentialSchema property defined in the W3C Verifiable Credentials Data Model; in AnonCreds ecosystems they are written to a Verifiable Data Registry, making them tamper-evident and globally discoverable."@en ;
rdfs:label "Credential Schema"@en ;
rdfs:subClassOf ngm:decentralised-identity ;
rdfs:subClassOf _:r5996 ;
rdfs:subClassOf _:r5997 ;
rdfs:subClassOf _:r5998 ;
vc:bridgesTo ngm:data-governance ;
vc:bridgesTo ngm:knowledge-graph ;
vc:contrastsWith ngm:access-control-policy ;
vc:contrastsWith ngm:credential-format-standard ;
vc:enables ngm:interoperability ;
vc:enables ngm:selective-disclosure ;
vc:enables ngm:verifiable-credential-vc ;
vc:enables ngm:verifiable-credentials ;
vc:enables ngm:zero-knowledge-proof ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:claim-mapping ;
vc:hasPart ngm:credential-definition ;
vc:implements ngm:anon-creds ;
vc:implements ngm:mdoc ;
vc:implements ngm:sd-jwt-vc ;
vc:isPartOf ngm:self-sovereign-identity ;
vc:isPartOf ngm:trust-framework ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:credential-governance ;
vc:relatedTo ngm:metadata-schema ;
vc:relatedTo ngm:ontology ;
vc:relatedTo ngm:schema-registry ;
vc:requires ngm:decentralised-identifier ;
vc:requires ngm:verifiable-data-registry ;
vc:slug "credential-schema" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:hyperledger-aries ;
vc:standardizedBy ngm:open-id-foundation ;
vc:standardizedBy ngm:w3-c ;
vc:uses ngm:distributed-ledger-technology ;
vc:uses ngm:json-data-interchange-format-schema ;
vc:uses ngm:json-ld ;
vc:uses ngm:semantic-web-linked-data-standard .
ngm:credential-schema-registry a skos:Concept ;
rdfs:label "Credential Schema Registry"@en .
ngm:credential-status a skos:Concept ;
rdfs:label "Credential Status"@en .
ngm:credential-status-registry a skos:Concept ;
rdfs:label "Credential Status Registry"@en .
ngm:credential-storage a owl:Class ;
rdfs:comment "Credential storage is the secure persistence of authentication secrets and verifiable credentials—such as passwords, keys, tokens, and signed attestations—so they can be protected at rest and retrieved for verification. It employs encryption, hardware-backed enclaves, and access controls to resist theft and tampering. It is a required capability of any digital identity management system."@en ;
rdfs:label "Credential Storage"@en ;
rdfs:subClassOf ngm:infra-security-and-identity ;
skos:broader ngm:infra-security-and-identity ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:digital-identity ;
vc:relatedTo ngm:digital-identity-management ;
vc:slug "credential-storage" ;
vc:sourceDomain "security" .
ngm:credential-store a owl:Class ;
rdfs:comment "A credential store is the component within an identity system that holds user identifiers, secrets, and account attributes used during authentication. Implemented as a directory, database, or secrets vault, it is queried by an identity provider to validate sign-in attempts and issue tokens. Its integrity and confidentiality are critical to the security of the surrounding identity infrastructure."@en ;
rdfs:label "Credential Store"@en ;
rdfs:subClassOf ngm:infra-security-and-identity ;
skos:broader ngm:infra-security-and-identity ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:authentication ;
vc:relatedTo ngm:identity-provider ;
vc:slug "credential-store" ;
vc:sourceDomain "security" .
ngm:credential-subject a skos:Concept ;
rdfs:label "Credential Subject"@en .
ngm:credential-validation a skos:Concept ;
rdfs:label "Credential Validation"@en .
ngm:credential-verification a owl:Class ;
rdfs:comment "Credential verification is the process of cryptographically or institutionally confirming the authenticity, integrity, and current validity of a credential — such as a digital certificate, verifiable credential, or identity assertion — issued by a trusted authority about a subject, so that a relying party can grant access or trust without real-time contact with the original issuer. In decentralised identity systems it relies on public-key cryptography, digital signatures, and optionally distributed ledgers to enable privacy-preserving, tamper-evident verification. The process must also resolve issuer keys and query revocation registries (via CRL, OCSP, or on-chain status) to ensure invalidated credentials cannot be fraudulently reused. Selective-disclosure techniques, including zero-knowledge proofs and SD-JWTs, allow subjects to prove specific attributes without exposing unnecessary personal data."@en ;
rdfs:label "Credential Verification"@en ;
rdfs:subClassOf ngm:authentication ;
rdfs:subClassOf _:r5999 ;
rdfs:subClassOf _:r6000 ;
rdfs:subClassOf _:r6001 ;
rdfs:subClassOf _:r6002 ;
rdfs:subClassOf _:r6003 ;
rdfs:subClassOf _:r6004 ;
rdfs:subClassOf _:r6005 ;
vc:bridgesTo ngm:distributed-ledger-technology ;
vc:bridgesTo ngm:smart-contract ;
vc:contrastsWith ngm:credential-issuance ;
vc:contrastsWith ngm:password-authentication ;
vc:dependsOn ngm:certificate-authority ;
vc:dependsOn ngm:credential-schema ;
vc:dependsOn ngm:decentralized-identifier ;
vc:enables ngm:access-control ;
vc:enables ngm:digital-identity-management ;
vc:enables ngm:selective-disclosure ;
vc:enables ngm:trust-establishment ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:digital-signature-verification ;
vc:hasPart ngm:revocation-check ;
vc:hasPart ngm:schema-validation ;
vc:isPartOf ngm:authentication ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:decentralized-identity ;
vc:relatedTo ngm:digital-identity ;
vc:relatedTo ngm:kyc ;
vc:relatedTo ngm:mobile-driving-licence ;
vc:relatedTo ngm:self-sovereign-identity ;
vc:requires ngm:cryptographic-infrastructure ;
vc:requires ngm:cryptographic-signature ;
vc:requires ngm:revocation-registry ;
vc:requires ngm:trust-anchor ;
vc:slug "credential-verification" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:open-id4-vc ;
vc:standardizedBy ngm:w3-c-verifiable-credentials ;
vc:standardizedBy ngm:x-509-certificate ;
vc:uses ngm:cryptographic-verification ;
vc:uses ngm:decentralized-identity-did ;
vc:uses ngm:digital-signature ;
vc:uses ngm:zero-knowledge-proof .
ngm:credibility-assurance a skos:Concept ;
rdfs:label "Credibility Assurance"@en .
ngm:credit-creation a skos:Concept ;
rdfs:label "Credit Creation"@en .
ngm:credit-intermediation a skos:Concept ;
rdfs:label "Credit Intermediation"@en .
ngm:credit-issuance-engine a skos:Concept ;
rdfs:label "Credit Issuance Engine"@en .
ngm:credit-risk a owl:Class ;
rdfs:comment "The risk of financial loss arising from a borrower or counterparty failing to meet contractual obligations, quantified through probability of default, loss given default and exposure at default, and managed through credit scoring, collateralisation, diversification, provisioning and regulatory capital requirements; the dominant risk category on most bank balance sheets and the core determinant of loan pricing in both traditional and decentralised lending."@en ;
rdfs:label "Credit Risk"@en ;
rdfs:subClassOf ngm:risk ;
vc:bridgesTo ngm:lending-protocol ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:risk-management ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:interest-rate ;
vc:relatedTo ngm:operational-risk ;
vc:slug "credit-risk" ;
vc:sourceDomain "finance" .
ngm:credit-scoring a skos:Concept ;
rdfs:label "Credit Scoring"@en .
ngm:credit-tracking a skos:Concept ;
rdfs:label "Credit Tracking"@en .
ngm:credo a skos:Concept ;
rdfs:label "Credo"@en .
ngm:crescendo-attack a skos:Concept ;
rdfs:label "Crescendo Attack"@en .
ngm:crew a skos:Concept ;
rdfs:label "Crew"@en .
ngm:crew-active-dosimeter a owl:Class ;
rdfs:label "Crew Active Dosimeter"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:radiation-dosimetry ;
vc:relatedTo ngm:space-life-sciences ;
vc:slug "crew-active-dosimeter" ;
vc:sourceDomain "space-science-and-systems" .
ngm:crew-ai a owl:Class ;
rdfs:comment "CrewAI is an open-source Python framework for orchestrating teams of autonomous LLM-powered agents that collaborate on complex tasks through defined roles, backstories, goals, and structured processes. It models a crew of specialised agents—each with distinct capabilities and a designated toolset—that delegate work, share context through a shared memory system, and execute sequential, parallel, or hierarchical workflows toward a common objective. With 47,800+ GitHub stars, 27 million downloads, and adoption by 63% of the Fortune 500 as of mid-2026, CrewAI has become one of the fastest-growing multi-agent orchestration frameworks in the agentic AI ecosystem."@en ;
rdfs:label "CrewAI"@en ;
rdfs:subClassOf ngm:agent-frameworks ;
rdfs:subClassOf ngm:agentic-workflow ;
rdfs:subClassOf ngm:ai-agent-system ;
rdfs:subClassOf ngm:cli-multi-agent-systems ;
rdfs:subClassOf ngm:multi-agent-systems ;
rdfs:subClassOf _:r6006 ;
rdfs:subClassOf _:r6007 ;
rdfs:subClassOf _:r6008 ;
rdfs:subClassOf _:r6009 ;
rdfs:subClassOf _:r6010 ;
rdfs:subClassOf _:r6011 ;
rdfs:subClassOf _:r6012 ;
vc:contrastsWith ngm:auto-gen ;
vc:contrastsWith ngm:lang-graph ;
vc:contrastsWith ngm:metagpt ;
vc:contrastsWith ngm:openai-research-organisation-agents-sdk ;
vc:dependsOn ngm:chain-of-thought ;
vc:dependsOn ngm:context-window ;
vc:dependsOn ngm:re-act-pattern ;
vc:enables ngm:code-execution ;
vc:enables ngm:multi-agent-coordination ;
vc:enables ngm:orchestration ;
vc:enables ngm:task-planning ;
vc:enables ngm:workflow-automation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:agent ;
vc:hasPart ngm:agent-memory ;
vc:hasPart ngm:crew ;
vc:hasPart ngm:flow ;
vc:hasPart ngm:process ;
vc:hasPart ngm:task ;
vc:hasPart ngm:tool-use ;
vc:implements ngm:agent-memory ;
vc:implements ngm:orchestration ;
vc:implements ngm:tool-use ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:agentic-workflow ;
vc:relatedTo ngm:auto-gen ;
vc:relatedTo ngm:cli-multi-agent-systems ;
vc:relatedTo ngm:eu-ai-act-regulatory-instrument ;
vc:relatedTo ngm:lang-graph ;
vc:relatedTo ngm:prompt-injection ;
vc:requires ngm:api-integration ;
vc:requires ngm:large-language-model ;
vc:requires ngm:prompt-engineering ;
vc:slug "crew-ai" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:model-context-protocol ;
vc:supports ngm:agentic-ai ;
vc:supports ngm:ai-safety ;
vc:supports ngm:human-in-the-loop ;
vc:uses ngm:foundation-model ;
vc:uses ngm:function-calling ;
vc:uses ngm:large-language-model ;
vc:uses ngm:model-context-protocol ;
vc:uses ngm:retrieval-augmented-generation ;
vc:uses ngm:tool-use .
ngm:crew-health-monitoring a owl:Class ;
rdfs:label "Crew Health Monitoring"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:space-life-sciences ;
vc:slug "crew-health-monitoring" ;
vc:sourceDomain "space-science-and-systems" .
ngm:crewed-spacecraft a owl:Class ;
rdfs:label "Crewed Spacecraft"@en ;
rdfs:subClassOf ngm:spacecraft ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:space-systems-engineering ;
vc:slug "crewed-spacecraft" ;
vc:sourceDomain "space-science-and-systems" .
ngm:cri-o a skos:Concept ;
rdfs:label "Cri O"@en .
ngm:criminal-liability a skos:Concept ;
rdfs:label "Criminal Liability"@en .
ngm:crisis-intervention a skos:Concept ;
rdfs:label "Crisis Intervention"@en .
ngm:crisis-management a skos:Concept ;
rdfs:label "Crisis Management"@en .
ngm:crispr-gene-editing a skos:Concept ;
rdfs:label "Crispr Gene Editing"@en .
ngm:critic-network a skos:Concept ;
rdfs:label "Critic Network"@en .
ngm:critical-harm-framework a skos:Concept ;
rdfs:label "Critical Harm Framework"@en .
ngm:critical-infrastructure a skos:Concept ;
rdfs:label "Critical Infrastructure"@en .
ngm:critical-infrastructure-attack a skos:Concept ;
rdfs:label "Critical Infrastructure Attack"@en .
ngm:critical-infrastructure-disruption a skos:Concept ;
rdfs:label "Critical Infrastructure Disruption"@en .
ngm:critical-infrastructure-protection a skos:Concept ;
rdfs:label "Critical Infrastructure Protection"@en .
ngm:critical-national-infrastructure a skos:Concept ;
rdfs:label "Critical National Infrastructure"@en .
ngm:critical-threshold a skos:Concept ;
rdfs:label "Critical Threshold"@en .
ngm:crl-certificate-revocation a skos:Concept ;
rdfs:label "Crl Certificate Revocation"@en .
ngm:crm a owl:Class ;
rdfs:comment "Customer Relationship Management (CRM) is a category of enterprise software and associated business processes that centralises the storage, tracking, and analysis of all interactions between an organisation and its customers, prospects, and partners across the full sales, marketing, and service lifecycle. A CRM system provides a shared record of each contact and account, enabling sales pipelines, service-case management, marketing campaign tracking, and analytical reporting from a single platform."@en ;
rdfs:label "CRM"@en ;
rdfs:subClassOf ngm:enterprise-software-platform ;
rdfs:subClassOf _:r3803 ;
rdfs:subClassOf _:r3804 ;
rdfs:subClassOf _:r3805 ;
rdfs:subClassOf _:r3806 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:contrastsWith ngm:customer-data-platform ;
vc:contrastsWith ngm:enterprise-resource-planning ;
vc:dependsOn ngm:cloud-infrastructure ;
vc:dependsOn ngm:rest-api ;
vc:enables ngm:customer-experience-management ;
vc:enables ngm:customer-support-automation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:crm-integration ;
vc:hasPart ngm:crm-systems ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:business-intelligence ;
vc:relatedTo ngm:data-warehouse ;
vc:requires ngm:data-integration ;
vc:requires ngm:identity-resolution ;
vc:slug "crm" ;
vc:sourceDomain "data" ;
vc:supports ngm:consent-management ;
vc:supports ngm:omnichannel ;
vc:uses ngm:enterprise-workflow ;
vc:uses ngm:natural-language-processing .
ngm:crm-integration a owl:Class ;
rdfs:comment "CRM integration is the connection of customer-relationship-management software with other business systems—such as telephony, email, marketing, and AI assistants—so that customer data and interactions flow automatically across tools. It typically uses APIs, webhooks, and event syncs to keep contact records, activity logs, and pipelines consistent. It is essential for unified customer views and automated sales and support workflows."@en ;
rdfs:label "CRM Integration"@en ;
rdfs:subClassOf ngm:system-architecture ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:call-centres ;
vc:relatedTo ngm:crm ;
vc:slug "crm-integration" ;
vc:sourceDomain "infrastructure" .
ngm:crm-systems a owl:Class ;
rdfs:comment "CRM systems are software platforms that centralise the management of an organisation's interactions with current and prospective customers across sales, marketing, and service. They store contact records, track pipelines and tickets, automate outreach, and increasingly embed AI for summarisation and recommendation. They are core operational systems for revenue and customer-experience teams."@en ;
rdfs:label "CRM Systems"@en ;
rdfs:subClassOf ngm:ai-application ;
skos:broader ngm:ai-application ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:crm ;
vc:relatedTo ngm:meeting-ai-assistant ;
vc:slug "crm-systems" ;
vc:sourceDomain "infrastructure" .
ngm:crop-monitoring a owl:Class ;
rdfs:label "Crop Monitoring"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-applications ;
vc:slug "crop-monitoring" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:crop-quality-improvement a skos:Concept ;
rdfs:label "Crop Quality Improvement"@en .
ngm:cross-agent-federation a skos:Concept ;
rdfs:label "Cross Agent Federation"@en .
ngm:cross-attention a owl:Class ;
rdfs:comment "An attention mechanism where queries come from one sequence whilst keys and values come from a different sequence, enabling information flow between the encoder and decoder in sequence-to-sequence models."@en ;
rdfs:label "Cross Attention"@en ;
rdfs:subClassOf ngm:ai-model-architecture ;
rdfs:subClassOf _:r6013 ;
rdfs:subClassOf _:r6014 ;
rdfs:subClassOf _:r6015 ;
rdfs:subClassOf _:r6016 ;
rdfs:subClassOf _:r6017 ;
skos:broader ngm:ai-model-architecture ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:natural-language-processing ;
vc:contrastsWith ngm:self-attention ;
vc:dependsOn ngm:embedding ;
vc:dependsOn ngm:neural-network ;
vc:enables ngm:image-captioning ;
vc:enables ngm:machine-translation ;
vc:enables ngm:multimodal-ai-architecture-ai ;
vc:enables ngm:multimodal-ai-architecture-understanding ;
vc:enables ngm:speech-recognition ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:attention-weight ;
vc:hasPart ngm:multi-head-attention ;
vc:implements ngm:sequence-to-sequence-model ;
vc:isPartOf ngm:attention-mechanism ;
vc:isPartOf ngm:encoder-decoder-architecture ;
vc:isPartOf ngm:transformer-architecture ;
vc:qualityScore "0.7"^^xsd:float ;
vc:relatedTo ngm:bert ;
vc:relatedTo ngm:diffusion-model ;
vc:relatedTo ngm:large-language-model ;
vc:requires ngm:query-key-value ;
vc:requires ngm:scaled-dot-product-attention ;
vc:requires ngm:softmax-function ;
vc:slug "cross-attention" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:layer-normalisation ;
vc:uses ngm:positional-encoding .
ngm:cross-attention-adapter a skos:Concept ;
rdfs:label "Cross Attention Adapter"@en .
ngm:cross-attention-conditioning a skos:Concept ;
rdfs:label "Cross Attention Conditioning"@en .
ngm:cross-attention-injection a skos:Concept ;
rdfs:label "Cross Attention Injection"@en .
ngm:cross-border-ai-cooperation a skos:Concept ;
rdfs:label "Cross Border AI Cooperation"@en .
ngm:cross-border-asset-distribution a skos:Concept ;
rdfs:label "Cross Border Asset Distribution"@en .
ngm:cross-border-authentication a owl:Class ;
rdfs:comment "Cross border authentication is the verification of a person or entity's identity across national or jurisdictional boundaries, so that credentials issued in one country are trusted and accepted in another. It depends on interoperable identity schemes, mutual-recognition agreements and trust frameworks that reconcile differing legal and technical regimes. The capability enables seamless access to services, regulated transactions and travel without re-establishing identity from scratch in each jurisdiction."@en ;
rdfs:label "Cross Border Authentication"@en ;
rdfs:subClassOf ngm:authentication ;
rdfs:subClassOf _:r6018 ;
rdfs:subClassOf _:r6019 ;
vc:bridgesTo ngm:self-sovereign-identity ;
vc:dependsOn ngm:digital-trust ;
vc:enables ngm:financial-inclusion ;
vc:enables ngm:interoperability ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:authentication-protocol ;
vc:isPartOf ngm:identity-management ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:digital-identity ;
vc:relatedTo ngm:regulatory-compliance ;
vc:relatedTo ngm:single-sign-on ;
vc:requires ngm:identity-verification ;
vc:requires ngm:trust-framework ;
vc:slug "cross-border-authentication" ;
vc:sourceDomain "governance" ;
vc:supports ngm:decentralized-identity ;
vc:uses ngm:federated-identity ;
vc:uses ngm:verifiable-credentials .
ngm:cross-border-commerce a skos:Concept ;
rdfs:label "Cross Border Commerce"@en .
ngm:cross-border-compliance a owl:Class ;
rdfs:comment "Multi-jurisdictional regulatory compliance framework governing organisations operating across national boundaries, requiring simultaneous adherence to overlapping and often conflicting legal regimes including data protection law (GDPR, UK GDPR, CCPA, PIPL, DPDPA 2023), AI regu..."@en ;
rdfs:label "Cross Border Compliance"@en ;
rdfs:subClassOf ngm:compliance-programs ;
rdfs:subClassOf ngm:corporate-governance ;
rdfs:subClassOf ngm:infra-legal-and-regulatory ;
rdfs:subClassOf ngm:international-law ;
rdfs:subClassOf ngm:legal-risk-management ;
rdfs:subClassOf ngm:regulatory-governance ;
rdfs:subClassOf _:r6020 ;
rdfs:subClassOf _:r6021 ;
rdfs:subClassOf _:r6022 ;
rdfs:subClassOf _:r6023 ;
rdfs:subClassOf _:r6024 ;
rdfs:subClassOf _:r6025 ;
rdfs:subClassOf _:r6026 ;
rdfs:subClassOf _:r6027 ;
rdfs:subClassOf _:r6028 ;
skos:broader ngm:infra-legal-and-regulatory ;
vc:contrastsWith ngm:data-nationalism ;
vc:contrastsWith ngm:forum-shopping ;
vc:contrastsWith ngm:jurisdictional-fragmentation ;
vc:contrastsWith ngm:regulatory-arbitrage ;
vc:contrastsWith ngm:regulatory-capture ;
vc:dependsOn ngm:adequacy-decisions ;
vc:dependsOn ngm:ai-regulation ;
vc:dependsOn ngm:data-protection-law ;
vc:dependsOn ngm:financial-regulation ;
vc:dependsOn ngm:international-trade-law ;
vc:dependsOn ngm:privacy-law ;
vc:dependsOn ngm:sanctions-regimes ;
vc:enables ngm:consumer-protection ;
vc:enables ngm:cross-border-enforcement ;
vc:enables ngm:data-sovereignty ;
vc:enables ngm:financial-crime-prevention ;
vc:enables ngm:global-market-access ;
vc:enables ngm:level-playing-field ;
vc:enables ngm:regulatory-trust ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:compliance-architecture ;
vc:hasPart ngm:data-transfer-mechanism ;
vc:hasPart ngm:enforcement-liaison ;
vc:hasPart ngm:jurisdictional-mapping ;
vc:hasPart ngm:legal-entity-structure ;
vc:hasPart ngm:regulatory-monitoring ;
vc:hasPart ngm:risk-assessment ;
vc:hasPart ngm:transfer-impact-assessment ;
vc:implements ngm:basel-iii ;
vc:implements ngm:binding-corporate-rules ;
vc:implements ngm:fatf-travel-rule ;
vc:implements ngm:mica-passporting ;
vc:implements ngm:oecd-ai-principles ;
vc:implements ngm:oecd-carf-reporting ;
vc:implements ngm:standard-contractual-clauses ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:brussels-effect ;
vc:relatedTo ngm:data-sovereignty ;
vc:relatedTo ngm:digital-trade-agreements ;
vc:relatedTo ngm:extraterritorial-jurisdiction ;
vc:relatedTo ngm:mutual-legal-assistance ;
vc:relatedTo ngm:oecd-carf ;
vc:relatedTo ngm:regulatory-harmonisation ;
vc:relatedTo ngm:schrems-ii ;
vc:requires ngm:data-residency-infrastructure ;
vc:requires ngm:kyc-aml ;
vc:requires ngm:legal-expertise ;
vc:requires ngm:privacy-impact-assessment ;
vc:requires ngm:regulatory-intelligence ;
vc:requires ngm:sanctions-screening ;
vc:requires ngm:transfer-impact-assessment ;
vc:slug "cross-border-compliance" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:basel-committee ;
vc:standardizedBy ngm:edpb ;
vc:standardizedBy ngm:eu-commission ;
vc:standardizedBy ngm:fatf ;
vc:standardizedBy ngm:financial-stability-board ;
vc:standardizedBy ngm:iapp ;
vc:standardizedBy ngm:ico ;
vc:standardizedBy ngm:iosco ;
vc:standardizedBy ngm:oecd ;
vc:supports ngm:ai-trustworthiness ;
vc:supports ngm:aml ;
vc:supports ngm:corporate-tax-compliance-framework ;
vc:supports ngm:data-protection ;
vc:supports ngm:eu-digital-single-market ;
vc:supports ngm:financial-stability ;
vc:uses ngm:adequacy-decisions ;
vc:uses ngm:binding-corporate-rules ;
vc:uses ngm:compliance-monitoring ;
vc:uses ngm:ivms-101 ;
vc:uses ngm:legal-entity-structure ;
vc:uses ngm:regtech ;
vc:uses ngm:risk-based-approach ;
vc:uses ngm:standard-contractual-clauses .
ngm:cross-border-cooperation a skos:Concept ;
rdfs:label "Cross Border Cooperation"@en .
ngm:cross-border-credential-recognition a skos:Concept ;
rdfs:label "Cross Border Credential Recognition"@en .
ngm:cross-border-data-transfer a owl:Class ;
rdfs:comment "Cross-border data transfer is the movement of personal or regulated data across national jurisdictions, governed by data-protection laws that restrict where and how such data may be processed. Compliance mechanisms include adequacy decisions, standard contractual clauses, binding corporate rules, and localisation requirements. It is a central concern of privacy regimes such as GDPR and various Asia-Pacific frameworks."@en ;
rdfs:label "Cross-Border Data Transfer"@en ;
rdfs:subClassOf ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:asia-pacific-regulation ;
vc:slug "cross-border-data-transfer" ;
vc:sourceDomain "governance" .
ngm:cross-border-data-transfer-rule a owl:Class ;
rdfs:comment "Regulatory framework governing international movement of personal and sensitive data across jurisdictions, ensuring privacy protection through adequacy assessments and safeguarding mechanisms."@en ;
rdfs:label "Cross-Border Data Transfer Rule"@en ;
rdfs:subClassOf ngm:infra-legal-and-regulatory ;
rdfs:subClassOf ngm:privacy-framework ;
rdfs:subClassOf _:r6044 ;
rdfs:subClassOf _:r6045 ;
rdfs:subClassOf _:r6046 ;
rdfs:subClassOf _:r6047 ;
skos:broader ngm:infra-legal-and-regulatory ;
vc:bridgesTo ngm:telecollaboration ;
vc:dependsOn ngm:apec-cbpr ;
vc:dependsOn ngm:eu-us-data-privacy-framework ;
vc:dependsOn ngm:gdpr-article-45 ;
vc:enables ngm:compliance-verification ;
vc:enables ngm:global-metaverse-operations ;
vc:enables ngm:international-data-flows ;
vc:enables ngm:user-privacy-protection ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:adequacy-decision-framework ;
vc:hasPart ngm:binding-corporate-rules ;
vc:hasPart ngm:standard-contractual-clauses ;
vc:hasPart ngm:transfer-impact-assessment ;
vc:isPartOf ngm:data-privacy-governance-framework ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:data-protection-authority-notification ;
vc:requires ngm:legal-basis-determination ;
vc:requires ngm:privacy-impact-assessment ;
vc:slug "cross-border-data-transfer-rule" ;
vc:sourceDomain "infrastructure" .
ngm:cross-border-enforcement a owl:Class ;
rdfs:comment "Cross-border enforcement is the process by which legal judgments, regulatory actions, or compliance obligations are recognised and executed across national jurisdictions. It depends on treaties, mutual legal assistance, and cooperation between regulators to act on actors and assets located abroad. It is a persistent challenge for digital and crypto markets that operate without regard to territorial borders."@en ;
rdfs:label "Cross-Border Enforcement"@en ;
rdfs:subClassOf ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:cross-border-compliance ;
vc:relatedTo ngm:digital-jurisdiction ;
vc:slug "cross-border-enforcement" ;
vc:sourceDomain "governance" .
ngm:cross-border-identity a owl:Class ;
rdfs:comment "Cross-border identity refers to digital identity credentials and verification mechanisms designed to be recognised and trusted across national jurisdictions, allowing an individual or organisation to prove attributes about themselves to a relying party in a different country without relying on a single centralised, national identity authority. It builds on self-sovereign identity principles and interoperable trust frameworks, such as those developed by the Trust Over IP Foundation, to establish mutual recognition of credential formats, issuers and verification methods between jurisdictions. Cross-border identity is a key enabler for international travel, remote work and cross-border financial services that require reliable identity assurance."@en ;
rdfs:label "Cross-Border Identity"@en ;
rdfs:subClassOf ngm:self-sovereign-identity ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:self-sovereign-identity ;
vc:qualityScore "0.55"^^xsd:float ;
vc:relatedTo ngm:self-sovereign-identity ;
vc:relatedTo ngm:trust-over-ip-foundation ;
vc:slug "cross-border-identity" ;
vc:sourceDomain "blockchain" .
ngm:cross-border-identity-recognition a skos:Concept ;
rdfs:label "Cross Border Identity Recognition"@en .
ngm:cross-border-identity-verification a skos:Concept ;
rdfs:label "Cross Border Identity Verification"@en .
ngm:cross-border-payment-compliance a skos:Concept ;
rdfs:label "Cross Border Payment Compliance"@en .
ngm:cross-border-payment-transparency a owl:Class ;
rdfs:comment "Cross-border payment transparency is the requirement and practice of making the originator, beneficiary, fees, and routing of international payments visible to counterparties and regulators. It supports anti-money-laundering controls and consumer protection by exposing hidden costs and identifying parties to a transfer. In crypto it is advanced through measures such as the FATF Travel Rule and on-chain settlement traceability."@en ;
rdfs:label "Cross-Border Payment Transparency"@en ;
rdfs:subClassOf ngm:financial-regulation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:cross-border-settlement ;
vc:relatedTo ngm:travel-rule ;
vc:slug "cross-border-payment-transparency" ;
vc:sourceDomain "blockchain" .
ngm:cross-border-payments a owl:Class ;
rdfs:comment "Cross-Border Payments are financial transactions that originate in one country and are settled in another, requiring currency conversion, multi-jurisdiction regulatory compliance, and interoperability between disparate payment systems. Traditional correspondent banking networks rely on SWIFT messaging and chains of intermediary banks, incurring multi-day settlement cycles, layered fees, and significant opacity. Blockchain-based payment rails—including stablecoins, payment channels, and Central Bank Digital Currencies—compress settlement latency and reduce intermediary costs by enabling atomic finality and programmable escrow. The domain sits at the intersection of monetary policy, AML/KYC regulation, ISO 20022 standardisation, and distributed-ledger technology."@en ;
rdfs:label "Cross-Border Payments"@en ;
rdfs:subClassOf ngm:financial-services ;
rdfs:subClassOf _:r6048 ;
rdfs:subClassOf _:r6049 ;
rdfs:subClassOf _:r6050 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:consensus-mechanism ;
vc:bridgesTo ngm:neural-network-text-tokenisation ;
vc:bridgesTo ngm:tokenization ;
vc:contrastsWith ngm:correspondent-banking ;
vc:contrastsWith ngm:domestic-payments ;
vc:dependsOn ngm:interoperability ;
vc:dependsOn ngm:payment-infrastructure ;
vc:dependsOn ngm:regulatory-compliance ;
vc:enables ngm:financial-inclusion ;
vc:enables ngm:remittances ;
vc:enables ngm:trade-finance ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:central-bank-digital-currency-cbdc ;
vc:relatedTo ngm:de-fi ;
vc:relatedTo ngm:fatf-travel-rule ;
vc:relatedTo ngm:forex ;
vc:requires ngm:aml-kyc-compliance ;
vc:requires ngm:correspondent-banking ;
vc:requires ngm:currency-exchange ;
vc:slug "cross-border-payments" ;
vc:sourceDomain "finance" ;
vc:standardizedBy ngm:bis-cpmi ;
vc:standardizedBy ngm:fatf-travel-rule ;
vc:standardizedBy ngm:financial-stability-board ;
vc:standardizedBy ngm:iso-20022 ;
vc:uses ngm:iso-20022 ;
vc:uses ngm:lightning-network ;
vc:uses ngm:smart-contract ;
vc:uses ngm:stablecoin ;
vc:uses ngm:swift-messaging .
ngm:cross-border-protocol a skos:Concept ;
rdfs:label "Cross Border Protocol"@en .
ngm:cross-border-recognition a skos:Concept ;
rdfs:label "Cross Border Recognition"@en .
ngm:cross-border-regulatory-cooperation a owl:Class ;
rdfs:comment "Cross-border regulatory cooperation is the coordination of financial supervision, rule-making and enforcement across national jurisdictions to manage activities and risks that span borders. It operates through memoranda of understanding, supervisory colleges, information-sharing arrangements, mutual recognition and common standards set by international bodies. By aligning approaches to systemic risk, anti-money-laundering and cross-border payments, it reduces regulatory arbitrage and supports consistent oversight of globally active firms and markets."@en ;
rdfs:label "Cross Border Regulatory Cooperation"@en ;
rdfs:subClassOf ngm:financial-regulation ;
rdfs:subClassOf _:r6029 ;
vc:bridgesTo ngm:basel-committee ;
vc:contrastsWith ngm:prudential-regulation ;
vc:dependsOn ngm:financial-stability ;
vc:enables ngm:cross-border-payments ;
vc:enables ngm:financial-stability ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:financial-regulation ;
vc:isPartOf ngm:financial-regulation ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:central-bank ;
vc:relatedTo ngm:compliance ;
vc:relatedTo ngm:fsb ;
vc:requires ngm:financial-regulation ;
vc:slug "cross-border-regulatory-cooperation" ;
vc:sourceDomain "finance" ;
vc:standardizedBy ngm:fsb ;
vc:standardizedBy ngm:g20 ;
vc:supports ngm:aml ;
vc:supports ngm:regulatory-compliance ;
vc:uses ngm:standards-organization .
ngm:cross-border-remittances a owl:Class ;
rdfs:comment "Cross-border remittances are transfers of money by individuals—typically migrant workers—to recipients in another country, often family members. Traditionally routed through banks and money-transfer operators with high fees and slow settlement, they are increasingly served by stablecoins and crypto rails that lower cost and latency. They represent a major global financial flow and a key driver of crypto payment adoption."@en ;
rdfs:label "Cross-Border Remittances"@en ;
rdfs:subClassOf ngm:financial-services ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:stable-coins ;
vc:slug "cross-border-remittances" ;
vc:sourceDomain "blockchain" .
ngm:cross-border-settlement a owl:Class ;
rdfs:comment "Cross-border settlement is the process of finalising the transfer of funds or assets between counterparties in different jurisdictions, including currency conversion, compliance checks, and the irrevocable discharge of obligations across correspondent banking chains, central bank systems, or emerging blockchain-based rails. It encompasses the full lifecycle from trade initiation to finality across multiple legal, regulatory, and technical environments."@en ;
rdfs:label "Cross-Border Settlement"@en ;
rdfs:subClassOf ngm:cross-border-payments ;
rdfs:subClassOf _:r6051 ;
rdfs:subClassOf _:r6052 ;
rdfs:subClassOf _:r6053 ;
vc:bridgesTo ngm:cbdc-cross-border-settlement ;
vc:dependsOn ngm:atomic-settlement ;
vc:dependsOn ngm:nostro-vostro-accounts ;
vc:dependsOn ngm:swift-messaging ;
vc:enables ngm:cross-border-payment-transparency ;
vc:enables ngm:financial-inclusion ;
vc:enables ngm:trade-finance ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:sanctions-screening ;
vc:implements ngm:iso-20022 ;
vc:isPartOf ngm:cross-border-payments ;
vc:qualityScore "0.73"^^xsd:float ;
vc:relatedTo ngm:correspondent-banking ;
vc:relatedTo ngm:delivery-versus-payment ;
vc:requires ngm:aml-kyc-compliance ;
vc:requires ngm:currency-conversion ;
vc:requires ngm:liquidity-management ;
vc:slug "cross-border-settlement" ;
vc:sourceDomain "finance" ;
vc:supports ngm:cross-border-payments ;
vc:supports ngm:fsb-cross-border-payments-roadmap ;
vc:uses ngm:real-time-gross-settlement .
ngm:cross-border-transactions a skos:Concept ;
rdfs:label "Cross Border Transactions"@en .
ngm:cross-border-transfer a owl:Class ;
rdfs:comment "A cross-border transfer is the movement of value or funds between parties located in different countries, settled across distinct currency and regulatory regimes. It encompasses bank wires, card networks, money-transfer operators, and increasingly digital-payment and cryptocurrency rails. Speed, cost, foreign-exchange handling, and compliance with multiple jurisdictions are its defining constraints."@en ;
rdfs:label "Cross-Border Transfer"@en ;
rdfs:subClassOf ngm:financial-services ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:cryptocurrency ;
vc:relatedTo ngm:digital-payments ;
vc:slug "cross-border-transfer" ;
vc:sourceDomain "blockchain" .
ngm:cross-border-treasury-operations a skos:Concept ;
rdfs:label "Cross Border Treasury Operations"@en .
ngm:cross-chain-asset-transfer a owl:Class ;
rdfs:comment "Cross-chain asset transfer is the cryptographic and protocol-level process of moving digital assets — cryptocurrencies, fungible tokens, or non-fungible tokens — from one blockchain network to a distinct, independent blockchain network while preserving the asset's economic properties and enforcing integrity guarantees across the transfer. Because independent blockchains maintain no shared global state, protocols must ensure that an asset locked or burned on the source chain is atomically minted or released on the destination chain, preventing double-spend and maintaining supply conservation. Implementations range from hash time-locked contracts (HTLCs) and lock-and-mint bridge contracts overseen by validator committees to native inter-blockchain communication protocols (IBC) and zero-knowledge proof-based verification bridges that eliminate trusted attestors entirely."@en ;
rdfs:label "Cross Chain Asset Transfer"@en ;
rdfs:subClassOf ngm:cross-chain-interoperability ;
rdfs:subClassOf _:r6030 ;
rdfs:subClassOf _:r6031 ;
rdfs:subClassOf _:r6032 ;
vc:bridgesTo ngm:de-fi ;
vc:bridgesTo ngm:digital-asset-regulation ;
vc:contrastsWith ngm:centralised-exchange ;
vc:contrastsWith ngm:wrapped-token ;
vc:enables ngm:blockchain-interoperability ;
vc:enables ngm:cross-chain-liquidity ;
vc:enables ngm:de-fi ;
vc:enables ngm:multi-chain-ecosystem ;
vc:enables ngm:wrapped-token ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:blockchain-security ;
vc:relatedTo ngm:cross-chain-messaging ;
vc:relatedTo ngm:layer-2-scaling ;
vc:relatedTo ngm:rollup ;
vc:relatedTo ngm:sidechain ;
vc:relatedTo ngm:token-standard ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:cryptographic-proof ;
vc:requires ngm:validator-network ;
vc:slug "cross-chain-asset-transfer" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:cosmos-ibc ;
vc:standardizedBy ngm:polkadot-xcm ;
vc:uses ngm:atomic-swap ;
vc:uses ngm:blockchain-protocol ;
vc:uses ngm:cross-chain-bridge ;
vc:uses ngm:hash-time-locked-contract ;
vc:uses ngm:light-client ;
vc:uses ngm:smart-contract ;
vc:uses ngm:zero-knowledge-proof .
ngm:cross-chain-bridge a owl:Class ;
rdfs:comment "A Cross-Chain Bridge is a protocol-level interoperability artefact — comprising on-chain smart contracts on each connected blockchain plus an off-chain attestation, relay, or proving infrastructure — that enables the trust-minimised transfer of fungible tokens, non-fungible tokens, arbitrary mess..."@en ;
rdfs:label "Cross-Chain Bridge"@en ;
rdfs:subClassOf ngm:asset-transfer-mechanism ;
rdfs:subClassOf ngm:blockchain-interoperability ;
rdfs:subClassOf ngm:cross-chain-application ;
rdfs:subClassOf ngm:interoperability-protocol ;
rdfs:subClassOf ngm:network-component ;
rdfs:subClassOf ngm:smart-contract-protocol ;
rdfs:subClassOf _:r6054 ;
rdfs:subClassOf _:r6055 ;
rdfs:subClassOf _:r6056 ;
rdfs:subClassOf _:r6057 ;
rdfs:subClassOf _:r6058 ;
rdfs:subClassOf _:r6059 ;
rdfs:subClassOf _:r6060 ;
rdfs:subClassOf _:r6061 ;
rdfs:subClassOf _:r6062 ;
rdfs:subClassOf _:r6063 ;
rdfs:subClassOf _:r6064 ;
rdfs:subClassOf _:r6065 ;
rdfs:subClassOf _:r6066 ;
rdfs:subClassOf _:r6067 ;
rdfs:subClassOf _:r6068 ;
vc:contrastsWith ngm:atomic-swap-only-protocol ;
vc:contrastsWith ngm:centralised-exchange-bridging ;
vc:contrastsWith ngm:custodial-asset-transfer ;
vc:contrastsWith ngm:native-rollup-interop ;
vc:contrastsWith ngm:notary-scheme ;
vc:contrastsWith ngm:side-chain ;
vc:dependsOn ngm:cryptographic-hash-function ;
vc:dependsOn ngm:merkle-proof ;
vc:dependsOn ngm:multi-party-computation ;
vc:dependsOn ngm:optimistic-oracle ;
vc:dependsOn ngm:restaked-validator ;
vc:dependsOn ngm:threshold-signature-scheme ;
vc:enables ngm:chain-abstraction ;
vc:enables ngm:cross-chain-asset-transfer ;
vc:enables ngm:cross-chain-composability ;
vc:enables ngm:cross-chain-swap ;
vc:enables ngm:multi-chain-de-fi ;
vc:enables ngm:omnichain-application ;
vc:enables ngm:wrapped-token ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:bridge-contract ;
vc:hasPart ngm:cryptographic-proof-system ;
vc:hasPart ngm:light-client ;
vc:hasPart ngm:liquidity-pool ;
vc:hasPart ngm:message-verification-module ;
vc:hasPart ngm:relayer ;
vc:hasPart ngm:settlement ;
vc:hasPart ngm:validator-set ;
vc:implements ngm:atomic-swap ;
vc:implements ngm:bridge ;
vc:implements ngm:burn-and-mint-bridge ;
vc:implements ngm:hash-time-locked-contract ;
vc:implements ngm:light-client ;
vc:implements ngm:liquidity-pool-bridge ;
vc:implements ngm:lock-and-mint-bridge ;
vc:implements ngm:optimistic-verification ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:across-protocol ;
vc:relatedTo ngm:axelar ;
vc:relatedTo ngm:blockchain-interoperability ;
vc:relatedTo ngm:chainlink-ccip ;
vc:relatedTo ngm:connext ;
vc:relatedTo ngm:hyperlane ;
vc:relatedTo ngm:jumper-exchange ;
vc:relatedTo ngm:layer-zero ;
vc:relatedTo ngm:li-fi ;
vc:relatedTo ngm:nexus-mutual ;
vc:relatedTo ngm:polygon-zkevm-bridge ;
vc:relatedTo ngm:polymer-hub ;
vc:relatedTo ngm:squid-router ;
vc:relatedTo ngm:stargate ;
vc:relatedTo ngm:synapse-protocol ;
vc:relatedTo ngm:wormhole ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:cryptographic-hash-function ;
vc:requires ngm:destination-chain-execution ;
vc:requires ngm:digital-signature ;
vc:requires ngm:finality ;
vc:requires ngm:smart-contract ;
vc:slug "cross-chain-bridge" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:chain-agnostic-standards-alliance ;
vc:standardizedBy ngm:erc-7281 ;
vc:standardizedBy ngm:erc-7683 ;
vc:standardizedBy ngm:ibc-specification ;
vc:standardizedBy ngm:iso-20022 ;
vc:standardizedBy ngm:open-bridge-standard ;
vc:supports ngm:cross-chain-dex ;
vc:supports ngm:cross-chain-governance ;
vc:supports ngm:cross-chain-nft ;
vc:supports ngm:multi-chain-lending ;
vc:supports ngm:stablecoin ;
vc:supports ngm:tokenised-real-world-asset-transfer ;
vc:supports ngm:wallet ;
vc:uses ngm:decentralised-verifier-network ;
vc:uses ngm:fraud-proof ;
vc:uses ngm:multi-signature ;
vc:uses ngm:solver-network ;
vc:uses ngm:tee ;
vc:uses ngm:threshold-signature-scheme ;
vc:uses ngm:zk-snark ;
vc:uses ngm:zk-snarks .
ngm:cross-chain-bridges a owl:Class ;
rdfs:comment "The category of protocols that move assets and data between distinct blockchains, treated collectively as connective infrastructure between ledgers."@en ;
rdfs:label "Cross-Chain Bridges"@en ;
rdfs:subClassOf ngm:blockchain-interoperability ;
rdfs:subClassOf _:r6069 ;
vc:bridgesTo ngm:bridge ;
vc:bridgesTo ngm:cross-chain-bridge ;
vc:enables ngm:cross-chain-asset-transfer ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:smart-contract ;
vc:slug "cross-chain-bridges" ;
vc:sourceDomain "blockchain" .
ngm:cross-chain-communication a owl:Class ;
rdfs:comment "Cross-chain communication is the exchange of messages, data, and asset-transfer instructions between distinct blockchain networks that do not natively share state. It is implemented through protocols, relays, and light-client verification that let one chain trust and act on events from another. It is the foundation of blockchain interoperability and multi-chain applications."@en ;
rdfs:label "Cross-Chain Communication"@en ;
rdfs:subClassOf ngm:cross-chain-bridge ;
rdfs:subClassOf _:r6070 ;
rdfs:subClassOf _:r6071 ;
rdfs:subClassOf _:r6072 ;
rdfs:subClassOf _:r6073 ;
rdfs:subClassOf _:r6074 ;
rdfs:subClassOf _:r6075 ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:bridgesTo ngm:distributed-systems ;
vc:contrastsWith ngm:layer-2-scaling ;
vc:contrastsWith ngm:sidechain ;
vc:enables ngm:atomic-swap ;
vc:enables ngm:blockchain-interoperability ;
vc:enables ngm:de-fi ;
vc:enables ngm:multi-chain-application ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:light-client-verification ;
vc:hasPart ngm:merkle-proof ;
vc:hasPart ngm:relayer ;
vc:implements ngm:cosmos-ibc ;
vc:implements ngm:polkadot-xcm ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:blockchain-interoperability ;
vc:relatedTo ngm:cosmos-ibc ;
vc:relatedTo ngm:message-passing ;
vc:relatedTo ngm:token-bridge ;
vc:relatedTo ngm:wrapped-token ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:cryptographic-proof ;
vc:requires ngm:smart-contract ;
vc:slug "cross-chain-communication" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:hash-time-locked-contract ;
vc:uses ngm:oracle-network ;
vc:uses ngm:zero-knowledge-proof .
ngm:cross-chain-composability a owl:Class ;
rdfs:comment "Cross-chain composability is the capacity for smart contracts and protocols deployed on different blockchain networks to interoperate and be combined into higher-order applications, as if operating within a single execution environment. It depends on interoperability infrastructure such as cross-chain bridges and messaging protocols to relay state and asset transfers between chains reliably. Cross-chain composability extends the general property of composability beyond a single chain, enabling multi-chain DeFi strategies and cross-chain governance."@en ;
rdfs:label "Cross-Chain Composability"@en ;
rdfs:subClassOf ngm:composability ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.0"^^xsd:float ;
vc:slug "cross-chain-composability" ;
vc:sourceDomain "blockchain" .
ngm:cross-chain-contracts a skos:Concept ;
rdfs:label "Cross Chain Contracts"@en .
ngm:cross-chain-dex a owl:Class ;
rdfs:comment "A cross-chain DEX is a decentralised exchange that lets users swap assets native to different blockchains without a centralised custodian. It relies on bridges, atomic swaps, or liquidity-network protocols to coordinate settlement across chains while preserving non-custodial trading. It extends decentralised finance beyond single-chain liquidity silos."@en ;
rdfs:label "Cross-Chain DEX"@en ;
rdfs:subClassOf ngm:de-fi ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:blockchain-interoperability ;
vc:relatedTo ngm:cross-chain-bridge ;
vc:slug "cross-chain-dex" ;
vc:sourceDomain "blockchain" .
ngm:cross-chain-governance a owl:Class ;
rdfs:comment "Cross-Chain Governance is a coordination framework and set of protocols that enable governance proposals, voting outcomes, and policy updates to propagate and be enforced across multiple heterogeneous blockchain networks without requiring a single trusted intermediary. It extends on-chain governance mechanisms — token-weighted voting, quadratic voting, time-locked execution — to multi-chain environments using interoperability layers such as IBC (Inter-Blockchain Communication), cross-chain message-passing bridges, or relay networks. Achieving consistent governance state across chains requires solving distributed consensus problems while preserving each chain's sovereignty. The field sits at the intersection of blockchain interoperability, distributed systems coordination, and decentralised decision-making."@en ;
rdfs:label "Cross-Chain Governance"@en ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
rdfs:subClassOf _:r6076 ;
rdfs:subClassOf _:r6077 ;
rdfs:subClassOf _:r6078 ;
rdfs:subClassOf _:r6079 ;
skos:broader ngm:bc-governance-and-regulation ;
vc:bridgesTo ngm:distributed-systems ;
vc:bridgesTo ngm:multi-stakeholder-governance ;
vc:contrastsWith ngm:centralised-governance ;
vc:contrastsWith ngm:off-chain-governance ;
vc:contrastsWith ngm:on-chain-governance ;
vc:dependsOn ngm:cross-chain-bridge ;
vc:dependsOn ngm:fraud-proof ;
vc:dependsOn ngm:relay-network ;
vc:enables ngm:decentralised-autonomous-organisation ;
vc:enables ngm:protocol-upgrade ;
vc:enables ngm:protocol-upgrades ;
vc:enables ngm:treasury-management ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:cosmos-ibc ;
vc:relatedTo ngm:optimistic-rollup ;
vc:relatedTo ngm:polkadot-parachains ;
vc:relatedTo ngm:zero-knowledge-proof ;
vc:requires ngm:blockchain-interoperability ;
vc:requires ngm:cross-chain-messaging ;
vc:requires ngm:distributed-consensus ;
vc:requires ngm:smart-contract ;
vc:slug "cross-chain-governance" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:dao-governance ;
vc:uses ngm:governance-token ;
vc:uses ngm:on-chain-voting ;
vc:uses ngm:time-lock .
ngm:cross-chain-integration a skos:Concept ;
rdfs:label "Cross Chain Integration"@en .
ngm:cross-chain-interoperability a owl:Class ;
rdfs:comment "Cross-Chain Interoperability is the technical capacity for distinct blockchain networks to communicate, transfer assets, and share arbitrary state without relying on a centralised intermediary, achieved through mechanisms such as light-client bridges, relay chains, atomic swaps, and standardised inter-blockchain communication protocols. It addresses the heterogeneous consensus problem—the challenge of enabling two networks with different finality guarantees and trust models to agree on the validity of cross-chain events—through cryptographic proofs, validator sets, or shared security frameworks. Prominent implementations include the Cosmos IBC protocol, Polkadot's Cross-Consensus Message Format (XCM), LayerZero's oracle-relayer model, and zero-knowledge proof bridges that verify source-chain state transitions with minimal on-chain trust. The field is foundational to the composable multi-chain ecosystem in which digital assets, governance rights, and smart contract logic can flow freely across sovereign networks."@en ;
rdfs:label "Cross-Chain Interoperability"@en ;
rdfs:subClassOf ngm:blockchain-interoperability ;
rdfs:subClassOf _:r6080 ;
rdfs:subClassOf _:r6081 ;
rdfs:subClassOf _:r6082 ;
rdfs:subClassOf _:r6083 ;
rdfs:subClassOf _:r6084 ;
rdfs:subClassOf _:r6085 ;
rdfs:subClassOf _:r6086 ;
vc:bridgesTo ngm:decentralised-identity ;
vc:bridgesTo ngm:distributed-systems ;
vc:bridgesTo ngm:zero-knowledge-proof ;
vc:contrastsWith ngm:centralised-exchange ;
vc:contrastsWith ngm:wrapped-token ;
vc:dependsOn ngm:cryptographic-proof ;
vc:dependsOn ngm:distributed-ledger-technology ;
vc:dependsOn ngm:hash-time-locked-contract ;
vc:enables ngm:cross-chain-governance ;
vc:enables ngm:cross-chain-liquidity ;
vc:enables ngm:de-fi ;
vc:enables ngm:multi-chain-application ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:atomic-swap ;
vc:hasPart ngm:cross-chain-bridge ;
vc:hasPart ngm:cross-chain-messaging ;
vc:hasPart ngm:light-client-verification ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:blockchain-scalability ;
vc:relatedTo ngm:layer-2-scaling ;
vc:relatedTo ngm:oracle-network ;
vc:relatedTo ngm:polkadot ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:merkle-proof ;
vc:requires ngm:smart-contract ;
vc:slug "cross-chain-interoperability" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:cosmos-ibc ;
vc:standardizedBy ngm:ieee-standards ;
vc:uses ngm:cosmos-ibc ;
vc:uses ngm:interoperability-protocol ;
vc:uses ngm:polkadot-xcm ;
vc:uses ngm:zero-knowledge-proof .
ngm:cross-chain-liquidity a owl:Class ;
rdfs:comment "Cross-chain liquidity refers to the availability and free movement of tradable assets across multiple, otherwise isolated blockchain networks. It is achieved through bridges, relayers, liquidity pools and atomic swaps that let value flow between chains without a single custodian. Robust cross-chain liquidity reduces fragmentation, tightens spreads and enables composable decentralised finance across heterogeneous ecosystems."@en ;
rdfs:label "Cross Chain Liquidity"@en ;
rdfs:subClassOf ngm:cross-chain-interoperability ;
vc:contrastsWith ngm:centralised-finance ;
vc:dependsOn ngm:consensus-mechanism ;
vc:dependsOn ngm:liquidity ;
vc:enables ngm:cross-chain-asset-transfer ;
vc:enables ngm:interoperability ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:isPartOf ngm:cross-chain-interoperability ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:decentralised-exchange ;
vc:relatedTo ngm:stablecoin ;
vc:relatedTo ngm:tokenomics ;
vc:slug "cross-chain-liquidity" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:de-fi ;
vc:supports ngm:dex ;
vc:uses ngm:atomic-swap ;
vc:uses ngm:cross-chain-bridge ;
vc:uses ngm:liquidity-pool ;
vc:uses ngm:relayer .
ngm:cross-chain-messaging a owl:Class ;
rdfs:comment "Protocols and mechanisms that enable communication and data transfer between different blockchain networks, facilitating interoperability and cross-chain applications without centralised intermediaries."@en ;
rdfs:label "Cross-Chain Messaging"@en ;
rdfs:subClassOf ngm:interoperability-protocol ;
rdfs:subClassOf ngm:message-passing ;
rdfs:subClassOf _:r6087 ;
rdfs:subClassOf _:r6088 ;
rdfs:subClassOf _:r6089 ;
rdfs:subClassOf _:r6090 ;
rdfs:subClassOf _:r6091 ;
rdfs:subClassOf _:r6092 ;
rdfs:subClassOf _:r6093 ;
rdfs:subClassOf _:r6094 ;
rdfs:subClassOf _:r6095 ;
rdfs:subClassOf _:r6096 ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:decentralised-computation ;
vc:bridgesTo ngm:distributed-systems ;
vc:contrastsWith ngm:atomic-swap ;
vc:contrastsWith ngm:centralised-bridge ;
vc:dependsOn ngm:consensus-mechanism ;
vc:dependsOn ngm:smart-contract ;
vc:enables ngm:asset-movement ;
vc:enables ngm:cross-chain-asset-transfer ;
vc:enables ngm:cross-chain-communication ;
vc:enables ngm:decentralised-computation ;
vc:enables ngm:state-synchronisation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:code-execution ;
vc:hasPart ngm:message-passing ;
vc:hasPart ngm:message-queue ;
vc:hasPart ngm:verification ;
vc:implements ngm:ibc ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:blockchain-interoperability ;
vc:relatedTo ngm:oracle-network ;
vc:requires ngm:blockchain-proof ;
vc:requires ngm:cryptographic-proof ;
vc:requires ngm:light-client ;
vc:requires ngm:message-authentication ;
vc:requires ngm:relay-network ;
vc:slug "cross-chain-messaging" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:merkle-proof .
ngm:cross-chain-nft a owl:Class ;
rdfs:comment "A cross-chain NFT is a non-fungible token that can move or be represented across multiple blockchains while preserving its identity, ownership, and metadata. It uses bridges, burn-and-mint mechanisms, or messaging protocols to transfer the canonical token between networks. It enables NFTs to access liquidity, marketplaces, and applications on chains other than where they were minted."@en ;
rdfs:label "Cross-Chain NFT"@en ;
rdfs:subClassOf ngm:bc-token-and-asset ;
skos:broader ngm:bc-token-and-asset ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:blockchain-interoperability ;
vc:relatedTo ngm:cross-chain-bridge ;
vc:slug "cross-chain-nft" ;
vc:sourceDomain "blockchain" .
ngm:cross-chain-swap a owl:Class ;
rdfs:comment "A cross-chain swap is the exchange of a token or asset held on one blockchain network for a different asset held on another network, without relying on a centralised exchange as intermediary. It is typically executed via a cross-chain bridge that locks or burns the source asset and mints or releases an equivalent representation on the destination chain, or via atomic swap protocols that guarantee both legs settle or neither does. Cross-chain swaps are a core primitive for multi-chain liquidity, enabling decentralised exchanges such as Osmosis to route trades across ecosystems."@en ;
rdfs:label "Cross-Chain Swap"@en ;
rdfs:subClassOf ngm:cross-chain-bridge ;
rdfs:subClassOf _:r6097 ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.55"^^xsd:float ;
vc:requires ngm:cross-chain-bridge ;
vc:slug "cross-chain-swap" ;
vc:sourceDomain "blockchain" .
ngm:cross-chain-trading a skos:Concept ;
rdfs:label "Cross Chain Trading"@en .
ngm:cross-chain-voting-aggregation a skos:Concept ;
rdfs:label "Cross Chain Voting Aggregation"@en .
ngm:cross-cultural-teamwork a skos:Concept ;
rdfs:label "Cross Cultural Teamwork"@en .
ngm:cross-dao-benchmarking a owl:Class ;
rdfs:comment "Cross-DAO benchmarking is the comparative analysis of decentralised autonomous organisations against shared metrics such as treasury size, voter participation, proposal throughput, and contributor activity. It aggregates on-chain governance and financial data to rank or contextualise a DAO's performance relative to peers. It informs governance design, delegate accountability, and treasury strategy."@en ;
rdfs:label "Cross-DAO Benchmarking"@en ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
skos:broader ngm:bc-governance-and-regulation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:dao-analytics ;
vc:slug "cross-dao-benchmarking" ;
vc:sourceDomain "blockchain" .
ngm:cross-domain-applicability a skos:Concept ;
rdfs:label "Cross Domain Applicability"@en .
ngm:cross-domain-authentication a owl:Class ;
rdfs:comment "Cross-domain authentication is the capability for a principal authenticated in one security or administrative domain to prove its identity to services in another domain without re-enrolling separate credentials. It relies on federated trust relationships and standard token exchanges so that an identity provider in one realm is accepted by relying parties in another. This underpins single sign-on across organisations and is essential to federated and distributed systems."@en ;
rdfs:label "Cross Domain Authentication"@en ;
rdfs:subClassOf ngm:authentication ;
rdfs:subClassOf _:r6033 ;
rdfs:subClassOf _:r6034 ;
vc:bridgesTo ngm:security ;
vc:enables ngm:federated-identity ;
vc:enables ngm:single-sign-on ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:identity-federation ;
vc:isPartOf ngm:authentication ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:federated-identity ;
vc:relatedTo ngm:identity-federation ;
vc:requires ngm:authentication ;
vc:requires ngm:trust-anchor ;
vc:slug "cross-domain-authentication" ;
vc:sourceDomain "security" ;
vc:supports ngm:access-control ;
vc:uses ngm:kerberos ;
vc:uses ngm:oauth ;
vc:uses ngm:saml .
ngm:cross-domain-bridge a owl:Class ;
rdfs:comment "A Cross Domain Bridge is an architectural pattern, protocol, or middleware system that enables interoperability and data exchange between heterogeneous collaboration platforms, virtual environments, and organisational systems. Implementations include protocol translators (WebRTC, SIP, H.323), identity federation layers (SAML, OAuth, OpenID Connect), and data transformation services (REST, GraphQL, gRPC). Advanced bridges leverage blockchain for trustless cross-domain transactions and open standards such as OpenXR for spatial interoperability."@en ;
rdfs:label "Cross Domain Bridge"@en ;
rdfs:subClassOf ngm:infra-network-and-comms ;
skos:broader ngm:infra-network-and-comms ;
vc:bridgesTo ngm:blockchain ;
vc:enables ngm:avatar-interoperability ;
vc:enables ngm:interoperability ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:slug "cross-domain-bridge" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:cross-platform-interoperability ;
vc:supports ngm:data-interoperability ;
vc:uses ngm:blockchain ;
vc:uses ngm:open-xr .
ngm:cross-domain-generalisation a skos:Concept ;
rdfs:label "Cross Domain Generalisation"@en .
ngm:cross-domain-governance a skos:Concept ;
rdfs:label "Cross Domain Governance"@en .
ngm:cross-domain-identity a skos:Concept ;
rdfs:label "Cross Domain Identity"@en .
ngm:cross-domain-integration a skos:Concept ;
rdfs:label "Cross Domain Integration"@en .
ngm:cross-domain-reference-corpus a owl:Class ;
rdfs:comment "A curated collection of external hyperlinks spanning blockchain, cryptocurrency, augmented and virtual reality, AI generative tools, and media production resources, assembled as a research reference page for cross-domain topics relevant to the NarrativeGoldmine knowledge graph."@en ;
rdfs:label "Cross-Domain Reference Corpus"@en ;
rdfs:subClassOf ngm:software-engineering ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:augmented-reality ;
vc:relatedTo ngm:blockchain ;
vc:relatedTo ngm:generative-ai ;
vc:slug "cross-domain-reference-corpus" ;
vc:sourceDomain "infrastructure" .
ngm:cross-domain-research-infrastructure a skos:Concept ;
rdfs:label "Cross Domain Research Infrastructure"@en .
ngm:cross-domain-sso a skos:Concept ;
rdfs:label "Cross Domain Sso"@en .
ngm:cross-domain-transfer a skos:Concept ;
rdfs:label "Cross Domain Transfer"@en .
ngm:cross-embodiment-transfer a skos:Concept ;
rdfs:label "Cross Embodiment Transfer"@en .
ngm:cross-encoder a skos:Concept ;
rdfs:label "Cross Encoder"@en .
ngm:cross-encoder-reranking a owl:Class ;
rdfs:comment "Cross-Encoder Reranking is a two-stage information retrieval technique in which a cross-encoder transformer model receives a query and a candidate document concatenated as a single input sequence, performs full bidirectional self-attention across both, and outputs a relevance score used to re-order an initial candidate set retrieved by a faster but less accurate first-stage retriever. It typically yields substantially higher ranking quality than bi-encoder first-stage retrieval at the cost of higher computational latency."@en ;
rdfs:label "Cross-Encoder Reranking"@en ;
rdfs:subClassOf ngm:information-retrieval ;
rdfs:subClassOf ngm:neural-information-retrieval ;
rdfs:subClassOf _:r6098 ;
rdfs:subClassOf _:r6099 ;
rdfs:subClassOf _:r6100 ;
rdfs:subClassOf _:r6101 ;
rdfs:subClassOf _:r6102 ;
rdfs:subClassOf _:r6103 ;
rdfs:subClassOf _:r6104 ;
rdfs:subClassOf _:r6105 ;
vc:bridgesTo ngm:natural-language-processing ;
vc:contrastsWith ngm:bi-encoder ;
vc:contrastsWith ngm:bm25 ;
vc:contrastsWith ngm:colbert ;
vc:contrastsWith ngm:cosine-similarity ;
vc:contrastsWith ngm:embedding-model ;
vc:dependsOn ngm:bert ;
vc:dependsOn ngm:dense-passage-retrieval ;
vc:dependsOn ngm:dense-retrieval ;
vc:dependsOn ngm:embedding-model ;
vc:dependsOn ngm:gpu-inference ;
vc:dependsOn ngm:nearest-neighbor-search ;
vc:enables ngm:agentic-rag ;
vc:enables ngm:document-retrieval ;
vc:enables ngm:knowledge-retrieval ;
vc:enables ngm:question-answering ;
vc:enables ngm:retrieval-augmented-generation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:attention-mechanism ;
vc:hasPart ngm:self-attention ;
vc:hasPart ngm:transformer ;
vc:implements ngm:information-retrieval ;
vc:implements ngm:neural-information-retrieval ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:hybrid-retrieval ;
vc:relatedTo ngm:knowledge-distillation ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:reciprocal-rank-fusion ;
vc:requires ngm:dense-passage-retrieval ;
vc:requires ngm:dense-retrieval ;
vc:requires ngm:hybrid-retrieval ;
vc:requires ngm:semantic-search ;
vc:requires ngm:transformer ;
vc:slug "cross-encoder-reranking" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:acm-sigir ;
vc:standardizedBy ngm:trec-deep-learning-track ;
vc:supports ngm:enterprise-search ;
vc:supports ngm:neural-information-retrieval ;
vc:supports ngm:rag-pipeline ;
vc:uses ngm:attention-mechanism ;
vc:uses ngm:bert ;
vc:uses ngm:contrastive-learning ;
vc:uses ngm:embedding-model ;
vc:uses ngm:self-attention .
ngm:cross-entropy-loss a owl:Class ;
rdfs:comment "Cross-entropy loss is a differentiable scalar objective function that measures the dissimilarity between a model's predicted probability distribution and the true label distribution, computed as the negative log-likelihood of the correct class under the model's output. It is the canonical training objective for classification tasks and language modelling, directly optimising the model to assign maximum probability mass to correct outputs. Minimising cross-entropy is equivalent to maximising the likelihood of the training data under the model's parameterised distribution."@en ;
rdfs:label "Cross-Entropy Loss"@en ;
rdfs:subClassOf ngm:loss-function ;
rdfs:subClassOf ngm:maximum-likelihood-estimation ;
rdfs:subClassOf _:r6106 ;
rdfs:subClassOf _:r6107 ;
rdfs:subClassOf _:r6108 ;
rdfs:subClassOf _:r6109 ;
rdfs:subClassOf _:r6110 ;
rdfs:subClassOf _:r6111 ;
vc:contrastsWith ngm:contrastive-loss ;
vc:contrastsWith ngm:focal-loss ;
vc:contrastsWith ngm:hinge-loss ;
vc:contrastsWith ngm:mean-squared-error ;
vc:dependsOn ngm:activation-function ;
vc:dependsOn ngm:backpropagation ;
vc:dependsOn ngm:stochastic-gradient-descent ;
vc:enables ngm:deep-learning ;
vc:enables ngm:fine-tuning ;
vc:enables ngm:language-modeling ;
vc:enables ngm:model-training ;
vc:enables ngm:supervised-learning ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:kl-divergence ;
vc:hasPart ngm:negative-log-likelihood ;
vc:hasPart ngm:softmax-function ;
vc:implements ngm:information-theory ;
vc:implements ngm:maximum-likelihood-estimation ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:direct-preference-optimisation ;
vc:relatedTo ngm:information-theory ;
vc:relatedTo ngm:kl-divergence ;
vc:relatedTo ngm:label-smoothing ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:perplexity-ai-search-platform ;
vc:relatedTo ngm:reinforcement-learning-from-human-feedback ;
vc:relatedTo ngm:transformer ;
vc:requires ngm:backpropagation ;
vc:requires ngm:gradient-descent ;
vc:requires ngm:neural-network ;
vc:requires ngm:softmax-function ;
vc:slug "cross-entropy-loss" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:ieee ;
vc:standardizedBy ngm:nist ;
vc:supports ngm:convolutional-neural-network ;
vc:supports ngm:large-language-models ;
vc:supports ngm:natural-language-processing ;
vc:supports ngm:transformer ;
vc:uses ngm:backpropagation ;
vc:uses ngm:gradient-descent ;
vc:uses ngm:maximum-likelihood-estimation ;
vc:uses ngm:softmax-function .
ngm:cross-functional-collaboration a owl:Class ;
rdfs:comment "Cross-functional collaboration is coordinated work between people from different disciplines or organisational units — such as engineering, design, and operations — combining diverse expertise toward a shared goal. In distributed and remote settings it depends on digital workplace platforms and virtual collaboration tools to bridge the coordination gaps that would otherwise be closed by physical co-location. It is a recurring requirement for digital workplace platforms and virtual collaboration systems."@en ;
rdfs:label "Cross-Functional Collaboration"@en ;
rdfs:subClassOf ngm:virtual-collaboration ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:virtual-collaboration ;
vc:qualityScore "0.6"^^xsd:float ;
vc:slug "cross-functional-collaboration" ;
vc:sourceDomain "distributed-collaboration" .
ngm:cross-functional-team-collaboration a skos:Concept ;
rdfs:label "Cross Functional Team Collaboration"@en .
ngm:cross-industry-ai-impact a skos:Concept ;
rdfs:label "Cross Industry AI Impact"@en .
ngm:cross-institutional-data-collaboration a skos:Concept ;
rdfs:label "Cross Institutional Data Collaboration"@en .
ngm:cross-language-collaboration a skos:Concept ;
rdfs:label "Cross Language Collaboration"@en .
ngm:cross-lingual-information-retrieval a skos:Concept ;
rdfs:label "Cross Lingual Information Retrieval"@en .
ngm:cross-lingual-transfer a skos:Concept ;
rdfs:label "Cross Lingual Transfer"@en .
ngm:cross-metaverse-commerce a owl:Class ;
rdfs:comment "Economic activities and transactions that span multiple metaverse platforms and virtual worlds, enabled by interoperability standards, blockchain-based digital assets, and unified digital identity systems that allow users to buy, sell, trade, and transfer value seamlessly across different virtual..."@en ;
rdfs:label "Cross Metaverse Commerce"@en ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf ngm:virtual-economy ;
rdfs:subClassOf _:r6035 ;
rdfs:subClassOf _:r6036 ;
rdfs:subClassOf _:r6037 ;
rdfs:subClassOf _:r6038 ;
skos:broader ngm:sc-platform-and-environment ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:virtual-economy ;
vc:enables ngm:asset-portability ;
vc:enables ngm:cross-platform-trading ;
vc:enables ngm:virtual-market-integration ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:blockchain-infrastructure ;
vc:requires ngm:digital-wallet ;
vc:requires ngm:interoperability-standard ;
vc:requires ngm:interoperability-standards ;
vc:slug "cross-metaverse-commerce" ;
vc:sourceDomain "spatial-computing" .
ngm:cross-modal-conditioning a owl:Class ;
rdfs:comment "Cross-modal conditioning is a generative modelling technique in which a model producing output in one sensory or representational modality is guided at inference time by a conditioning signal derived from a different modality, typically via cross-attention or adapter mechanisms that inject encoded representations of the conditioning input into the backbone network's intermediate layers. It is the foundational mechanism enabling text-to-image synthesis, text-to-audio generation, audio-driven video synthesis, depth-conditioned inpainting, and other heterogeneous generation tasks where the semantic intent is expressed in one modality and realised in another."@en ;
rdfs:label "Cross-Modal Conditioning"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:attention-mechanism ;
rdfs:subClassOf ngm:multimodal-ai-architecture-learning ;
rdfs:subClassOf _:r6112 ;
rdfs:subClassOf _:r6113 ;
rdfs:subClassOf _:r6114 ;
rdfs:subClassOf _:r6115 ;
rdfs:subClassOf _:r6116 ;
rdfs:subClassOf _:r6117 ;
rdfs:subClassOf _:r6118 ;
rdfs:subClassOf _:r6119 ;
rdfs:subClassOf _:r6120 ;
rdfs:subClassOf _:r6121 ;
rdfs:subClassOf _:r6122 ;
rdfs:subClassOf _:r6123 ;
skos:broader ngm:ai-technique ;
vc:contrastsWith ngm:self-attention ;
vc:dependsOn ngm:attention-mechanism ;
vc:dependsOn ngm:latent-space ;
vc:dependsOn ngm:neural-network ;
vc:dependsOn ngm:transformer-architecture ;
vc:dependsOn ngm:u-net ;
vc:dependsOn ngm:vae ;
vc:enables ngm:audio-synthesis ;
vc:enables ngm:computer-vision ;
vc:enables ngm:drug-discovery ;
vc:enables ngm:image-generation ;
vc:enables ngm:medical-imaging ;
vc:enables ngm:natural-language-processing ;
vc:enables ngm:spatial-computing ;
vc:enables ngm:synthetic-data ;
vc:enables ngm:text-to-image ;
vc:enables ngm:video-generation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:adapter-tuning ;
vc:hasPart ngm:classifier-free-guidance ;
vc:hasPart ngm:control-net ;
vc:hasPart ngm:cross-attention ;
vc:hasPart ngm:ip-adapter ;
vc:hasPart ngm:modality-specific-encoder ;
vc:implements ngm:generative-ai ;
vc:implements ngm:multimodal-ai-architecture-learning ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:adapter-tuning ;
vc:relatedTo ngm:clip ;
vc:relatedTo ngm:control-net ;
vc:relatedTo ngm:diffusion-model ;
vc:relatedTo ngm:foundation-model ;
vc:relatedTo ngm:ip-adapter ;
vc:relatedTo ngm:large-language-model ;
vc:relatedTo ngm:lo-ra ;
vc:relatedTo ngm:stable-diffusion-image-model ;
vc:requires ngm:clip ;
vc:requires ngm:contrastive-learning ;
vc:requires ngm:embedding ;
vc:requires ngm:latent-space ;
vc:requires ngm:representation-learning ;
vc:requires ngm:transformer-architecture ;
vc:slug "cross-modal-conditioning" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:artificial-intelligence ;
vc:supports ngm:computer-vision ;
vc:supports ngm:generative-ai ;
vc:supports ngm:large-language-model ;
vc:supports ngm:natural-language-processing ;
vc:supports ngm:spatial-computing ;
vc:uses ngm:clip ;
vc:uses ngm:fine-tuning ;
vc:uses ngm:lo-ra ;
vc:uses ngm:self-attention ;
vc:uses ngm:stable-diffusion-image-model ;
vc:uses ngm:vae .
ngm:cross-modal-retrieval a owl:Class ;
rdfs:comment "Cross-modal retrieval is the task of retrieving items in one modality (such as images) using a query expressed in a different modality (such as text), and vice versa. It relies on learning a shared embedding space in which semantically corresponding items across modalities lie close together, so that similarity search can bridge the modality gap. Contrastive vision-language models are the dominant approach, enabling text-to-image search, image captioning retrieval and multimodal recommendation."@en ;
rdfs:label "Cross Modal Retrieval"@en ;
rdfs:subClassOf ngm:information-retrieval ;
rdfs:subClassOf _:r6039 ;
vc:bridgesTo ngm:clip ;
vc:contrastsWith ngm:semantic-search ;
vc:dependsOn ngm:embedding ;
vc:enables ngm:semantic-search ;
vc:enables ngm:text-to-image ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:information-retrieval ;
vc:isPartOf ngm:information-retrieval ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:clip ;
vc:relatedTo ngm:vector-search ;
vc:relatedTo ngm:vision-language-model ;
vc:requires ngm:representation-learning ;
vc:slug "cross-modal-retrieval" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:vision-language-model ;
vc:uses ngm:contrastive-learning ;
vc:uses ngm:embedding ;
vc:uses ngm:vector-search .
ngm:cross-platform a skos:Concept ;
rdfs:label "Cross Platform"@en .
ngm:cross-platform-analytics a skos:Concept ;
rdfs:label "Cross Platform Analytics"@en .
ngm:cross-platform-asset-exchange a owl:Class ;
rdfs:comment "Cross-platform asset exchange is the capability to move 3D models, textures, and other digital assets between different metaverse platforms, engines, and tools while preserving fidelity and usability. It depends on shared 3D file formats and import/export pipelines that map assets onto each platform's runtime. It is a prerequisite for interoperable virtual worlds and portable user content."@en ;
rdfs:label "Cross-Platform Asset Exchange"@en ;
rdfs:subClassOf ngm:sc-standards-and-interop ;
skos:broader ngm:sc-standards-and-interop ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:3-d-file-format ;
vc:relatedTo ngm:standard-format-support ;
vc:slug "cross-platform-asset-exchange" ;
vc:sourceDomain "metaverse" .
ngm:cross-platform-assets a skos:Concept ;
rdfs:label "Cross Platform Assets"@en .
ngm:cross-platform-attribution a skos:Concept ;
rdfs:label "Cross Platform Attribution"@en .
ngm:cross-platform-auditing a skos:Concept ;
rdfs:label "Cross Platform Auditing"@en .
ngm:cross-platform-authentication a owl:Class ;
rdfs:comment "Cross-platform authentication is the verification of a user's identity in a way that is valid across multiple platforms, devices, or virtual worlds without re-registration. It uses federated identity, single sign-on, and portable credentials so that one verified identity unlocks access everywhere. It is a foundational requirement for interoperable avatars and multiverse experiences."@en ;
rdfs:label "Cross-Platform Authentication"@en ;
rdfs:subClassOf ngm:authentication ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:avatar-interoperability ;
vc:relatedTo ngm:multiverse ;
vc:slug "cross-platform-authentication" ;
vc:sourceDomain "security" .
ngm:cross-platform-avatar a skos:Concept ;
rdfs:label "Cross Platform Avatar"@en .
ngm:cross-platform-avatars a skos:Concept ;
rdfs:label "Cross Platform Avatars"@en .
ngm:cross-platform-categorization a skos:Concept ;
rdfs:label "Cross Platform Categorization"@en .
ngm:cross-platform-compatibility a owl:Class ;
rdfs:comment "Cross-platform compatibility is the property of a software system, application, or digital asset that allows it to function correctly and consistently across multiple operating systems, hardware architectures, runtime environments, or device categories without requiring separate implementations. Achieving this property typically involves adherence to open standards, abstraction layers, and rigorous testing regimes that surface divergent behaviour across target environments. In immersive and extended-reality contexts it extends to ensuring that 3D content, avatars, and application logic behave equivalently across headsets, smartphones, and desktop viewers."@en ;
rdfs:label "Cross-Platform Compatibility"@en ;
rdfs:subClassOf ngm:interoperability ;
rdfs:subClassOf _:r6124 ;
rdfs:subClassOf _:r6125 ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:bridgesTo ngm:spatial-computing ;
vc:contrastsWith ngm:vendor-lock-in ;
vc:enables ngm:cross-platform-identity ;
vc:enables ngm:portability ;
vc:enables ngm:vendor-neutrality ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:open-xr ;
vc:implements ngm:web-assembly ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:compatibility-standards ;
vc:relatedTo ngm:cross-platform-interoperability ;
vc:relatedTo ngm:interoperability-standard ;
vc:relatedTo ngm:portability ;
vc:requires ngm:api-standard ;
vc:requires ngm:continuous-integration ;
vc:slug "cross-platform-compatibility" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:khronos-group ;
vc:standardizedBy ngm:w3-c ;
vc:supports ngm:accessibility ;
vc:supports ngm:user-experience ;
vc:uses ngm:abstraction-layer ;
vc:uses ngm:compatibility-process ;
vc:uses ngm:open-standard ;
vc:uses ngm:standards-conformance-testing .
ngm:cross-platform-compliance-hub a owl:Class ;
rdfs:comment "A unified regulatory compliance system that harmonizes and coordinates compliance activities across multiple platforms, jurisdictions, and regulatory frameworks through centralized policy management and audit aggregation."@en ;
rdfs:label "Cross-Platform Compliance Hub"@en ;
rdfs:subClassOf ngm:ai-governance ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:compliance-framework ;
rdfs:subClassOf _:r6126 ;
rdfs:subClassOf _:r6127 ;
rdfs:subClassOf _:r6128 ;
rdfs:subClassOf _:r6129 ;
rdfs:subClassOf _:r6130 ;
rdfs:subClassOf _:r6131 ;
rdfs:subClassOf _:r6132 ;
rdfs:subClassOf _:r6133 ;
rdfs:subClassOf _:r6134 ;
rdfs:subClassOf _:r6135 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:telecollaboration ;
vc:dependsOn ngm:data-governance ;
vc:dependsOn ngm:legal-framework-database ;
vc:dependsOn ngm:risk-management ;
vc:enables ngm:cross-platform-auditing ;
vc:enables ngm:policy-enforcement ;
vc:enables ngm:regulatory-harmonization ;
vc:enables ngm:responsible-ai ;
vc:enables ngm:unified-compliance-reporting ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:audit ;
vc:hasPart ngm:compliance-dashboard ;
vc:hasPart ngm:policy-synchronization ;
vc:hasPart ngm:regulatory-mapping-engine ;
vc:hasPart ngm:reporting-engine ;
vc:hasPart ngm:risk-assessment ;
vc:implements ngm:do-ra ;
vc:implements ngm:eu-ai-act-regulatory-instrument ;
vc:implements ngm:gdpr ;
vc:implements ngm:hipaa ;
vc:implements ngm:iso-27001 ;
vc:implements ngm:nis2 ;
vc:implements ngm:soc-2 ;
vc:implements ngm:sox ;
vc:isPartOf ngm:compliance-framework ;
vc:isPartOf ngm:governance-infrastructure ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:responsible-ai ;
vc:relatedTo ngm:telecollaboration ;
vc:requires ngm:audit-trail ;
vc:requires ngm:compliance-monitoring ;
vc:requires ngm:continuous-monitoring ;
vc:requires ngm:data-classification-system ;
vc:requires ngm:evidence-collection ;
vc:requires ngm:identity-provider ;
vc:requires ngm:multi-jurisdictional-policy-store ;
vc:requires ngm:platform-integration-api ;
vc:requires ngm:reporting-engine ;
vc:slug "cross-platform-compliance-hub" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:iso-iec-42001 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:ai-governance ;
vc:supports ngm:regulatory-compliance .
ngm:cross-platform-connectivity a skos:Concept ;
rdfs:label "Cross Platform Connectivity"@en .
ngm:cross-platform-content a owl:Class ;
rdfs:comment "Cross-platform content is digital media and 3D assets authored once and made usable across multiple platforms, engines, or devices through standardised formats and conversion pipelines. It depends on format parsers and content pipelines that normalise assets to each target's runtime requirements. It enables creators to reach diverse metaverse environments without bespoke re-authoring."@en ;
rdfs:label "Cross-Platform Content"@en ;
rdfs:subClassOf ngm:sc-content-and-assets ;
skos:broader ngm:sc-content-and-assets ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:format-parser ;
vc:relatedTo ngm:metaverse-content-pipeline ;
vc:slug "cross-platform-content" ;
vc:sourceDomain "metaverse" .
ngm:cross-platform-data-exchange a skos:Concept ;
rdfs:label "Cross Platform Data Exchange"@en .
ngm:cross-platform-development a skos:Concept ;
rdfs:label "Cross Platform Development"@en .
ngm:cross-platform-digital-twins a owl:Class ;
rdfs:comment "Digital twin systems designed for interoperability across different software platforms and environments, enabling real-time data exchange, collaborative simulation, and unified virtual representations of physical assets or processes that can be accessed and manipulated from multiple compatible sy..."@en ;
rdfs:label "Cross Platform Digital Twins"@en ;
rdfs:subClassOf ngm:digital-twin-technology ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf _:r6040 ;
rdfs:subClassOf _:r6041 ;
rdfs:subClassOf _:r6042 ;
rdfs:subClassOf _:r6043 ;
skos:broader ngm:sc-platform-and-environment ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:digital-twin-technology ;
vc:enables ngm:collaborative-systems-modality-simulation ;
vc:enables ngm:data-integration ;
vc:enables ngm:multi-vendor-ecosystems ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:api-integration ;
vc:requires ngm:interoperability-standard ;
vc:requires ngm:interoperability-standards ;
vc:requires ngm:usd ;
vc:slug "cross-platform-digital-twins" ;
vc:sourceDomain "spatial-computing" .
ngm:cross-platform-experience a skos:Concept ;
rdfs:label "Cross Platform Experience"@en .
ngm:cross-platform-identity a owl:Class ;
rdfs:comment "Cross-platform identity refers to the capability of linking and managing a user's electronic identity and attributes across multiple distinct systems, platforms, and organisational boundaries, enabling seamless authentication and authorisation across heterogeneous environments through federated identity management."@en ;
rdfs:label "Cross-Platform Identity"@en ;
rdfs:subClassOf ngm:identity-management ;
rdfs:subClassOf _:r6136 ;
rdfs:subClassOf _:r6137 ;
rdfs:subClassOf _:r6138 ;
rdfs:subClassOf _:r6139 ;
rdfs:subClassOf _:r6140 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:did ;
vc:bridgesTo ngm:verifiable-credentials ;
vc:contrastsWith ngm:siloed-identity ;
vc:dependsOn ngm:attribute-based-access-control ;
vc:dependsOn ngm:directory-service ;
vc:enables ngm:authorisation ;
vc:enables ngm:federated-identity-system ;
vc:enables ngm:single-sign-on ;
vc:enables ngm:user-experience ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:federation ;
vc:hasPart ngm:identity-provider ;
vc:implements ngm:identity-federation ;
vc:implements ngm:oauth-2-0 ;
vc:implements ngm:open-id-connect ;
vc:implements ngm:trust ;
vc:isPartOf ngm:identity-management ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:zero-trust-architecture ;
vc:requires ngm:cryptographic-infrastructure ;
vc:requires ngm:multi-factor-authentication ;
vc:requires ngm:trust ;
vc:slug "cross-platform-identity" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:ietf ;
vc:standardizedBy ngm:oasis-standards ;
vc:uses ngm:saml ;
vc:uses ngm:scim .
ngm:cross-platform-integration a skos:Concept ;
rdfs:label "Cross Platform Integration"@en .
ngm:cross-platform-interoperability a owl:Class ;
rdfs:comment "The capability for heterogeneous blockchain networks, software platforms, and distributed systems to communicate, exchange data, and transfer value seamlessly without centralized intermediaries. Achieved through standardized protocols, light-client verification, and message-passing frameworks that eliminate trusted third parties."@en ;
rdfs:label "Cross-Platform Interoperability"@en ;
rdfs:subClassOf ngm:infra-network-and-comms ;
rdfs:subClassOf ngm:next-generation-mobile ;
rdfs:subClassOf _:r6141 ;
rdfs:subClassOf _:r6142 ;
rdfs:subClassOf _:r6143 ;
rdfs:subClassOf _:r6144 ;
rdfs:subClassOf _:r6145 ;
skos:broader ngm:infra-network-and-comms ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:identity-federation ;
vc:bridgesTo ngm:sc-standards-and-interop ;
vc:contrastsWith ngm:centralised-bridge ;
vc:contrastsWith ngm:walled-garden-ecosystem ;
vc:dependsOn ngm:api-standard ;
vc:dependsOn ngm:layer-0 ;
vc:enables ngm:atomic-swap ;
vc:enables ngm:cross-chain-bridge ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:light-client ;
vc:hasPart ngm:message-passing ;
vc:hasPart ngm:relayer ;
vc:implements ngm:ibc ;
vc:implements ngm:inter-blockchain-communication ;
vc:implements ngm:light-client ;
vc:isPartOf ngm:de-fi ;
vc:isPartOf ngm:distributed-systems ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:layer-0 ;
vc:relatedTo ngm:oracle-network ;
vc:relatedTo ngm:rollup ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:cryptographic-proof ;
vc:slug "cross-platform-interoperability" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:erc-5164 ;
vc:standardizedBy ngm:ieee ;
vc:standardizedBy ngm:w3-c-did ;
vc:supports ngm:de-fi ;
vc:supports ngm:token-transfer ;
vc:uses ngm:relayer ;
vc:uses ngm:threshold-cryptography ;
vc:uses ngm:zero-knowledge-proof .
ngm:cross-platform-presence a skos:Concept ;
rdfs:label "Cross Platform Presence"@en .
ngm:cross-platform-rendering a owl:Class ;
rdfs:comment "Cross-platform rendering is a rendering approach that produces consistent visual output across different operating systems, hardware GPUs and graphics APIs, typically by targeting an abstraction layer rather than a single vendor-specific API. It allows a single rendering codebase to run on Windows, macOS, Linux, mobile and web targets, translating draw calls to the underlying native graphics API such as Vulkan, Metal or DirectX. Standards bodies such as the Khronos Group maintain the graphics APIs and specifications that make cross-platform rendering practical."@en ;
rdfs:label "Cross-Platform Rendering"@en ;
rdfs:subClassOf ngm:graphics-api ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "cross-platform-rendering" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:graphics-api .
ngm:cross-platform-rewards a skos:Concept ;
rdfs:label "Cross Platform Rewards"@en .
ngm:cross-platform-synchronization a skos:Concept ;
rdfs:label "Cross Platform Synchronization"@en .
ngm:cross-platform-testing a skos:Concept ;
rdfs:label "Cross Platform Testing"@en .
ngm:cross-platform-trading a skos:Concept ;
rdfs:label "Cross Platform Trading"@en .
ngm:cross-reality-experiences a skos:Concept ;
rdfs:label "Cross Reality Experiences"@en .
ngm:cross-reality-transitions a skos:Concept ;
rdfs:label "Cross Reality Transitions"@en .
ngm:cross-references a skos:Concept ;
rdfs:label "Cross References"@en .
ngm:cross-scale-mapping a skos:Concept ;
rdfs:label "Cross Scale Mapping"@en .
ngm:cross-system-data-exchange a skos:Concept ;
rdfs:label "Cross System Data Exchange"@en .
ngm:cross-system-querying a owl:Class ;
rdfs:comment "Cross-system querying is the ability to issue a single query that retrieves and joins data residing in multiple independent systems or data stores. It is achieved through federation surfaces, linked-data encoding, and query mediators that translate and route requests to heterogeneous sources. It enables unified access to distributed data without centralising or duplicating it."@en ;
rdfs:label "Cross-System Querying"@en ;
rdfs:subClassOf ngm:data-management ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:federation-surface ;
vc:relatedTo ngm:linked-data-encoder ;
vc:slug "cross-system-querying" ;
vc:sourceDomain "data" .
ngm:cross-validation a owl:Class ;
rdfs:comment "Cross-validation is a statistical resampling technique for evaluating machine learning model performance by partitioning available data into complementary training and validation subsets, training the model on each partition in turn, and averaging the resulting error estimates. It provides a less optimistic and more generalisable estimate of out-of-sample predictive performance than a single train–test split."@en ;
rdfs:label "Cross-Validation"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:model-evaluation ;
rdfs:subClassOf ngm:resampling ;
rdfs:subClassOf ngm:statistical-learning-theory ;
rdfs:subClassOf _:r6146 ;
rdfs:subClassOf _:r6147 ;
rdfs:subClassOf _:r6148 ;
rdfs:subClassOf _:r6149 ;
rdfs:subClassOf _:r6150 ;
rdfs:subClassOf _:r6151 ;
rdfs:subClassOf _:r6152 ;
rdfs:subClassOf _:r6153 ;
rdfs:subClassOf _:r6154 ;
rdfs:subClassOf _:r6155 ;
rdfs:subClassOf _:r6156 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:data-governance ;
vc:bridgesTo ngm:statistical-inference ;
vc:contrastsWith ngm:annotated-training-data ;
vc:contrastsWith ngm:benign-overfitting ;
vc:contrastsWith ngm:holdout-validation ;
vc:dependsOn ngm:ai-machine-learning ;
vc:dependsOn ngm:statistical-estimation ;
vc:dependsOn ngm:statistical-learning-theory ;
vc:dependsOn ngm:supervised-learning ;
vc:enables ngm:auto-ml ;
vc:enables ngm:bias-variance-tradeoff ;
vc:enables ngm:feature-selection ;
vc:enables ngm:generalisation-error ;
vc:enables ngm:hyperparameter-tuning ;
vc:enables ngm:model-comparison ;
vc:enables ngm:model-selection ;
vc:enables ngm:overfitting ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:bias-variance-tradeoff ;
vc:hasPart ngm:feature-selection ;
vc:hasPart ngm:hyperparameter-tuning ;
vc:hasPart ngm:k-fold ;
vc:hasPart ngm:leave-one-out ;
vc:hasPart ngm:model-selection ;
vc:hasPart ngm:nested-cv ;
vc:hasPart ngm:sampling ;
vc:implements ngm:resampling ;
vc:implements ngm:statistical-inference ;
vc:isPartOf ngm:applied-machine-learning ;
vc:isPartOf ngm:model-selection ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:auto-ml ;
vc:relatedTo ngm:bayesian-optimisation ;
vc:relatedTo ngm:benign-overfitting ;
vc:relatedTo ngm:data-augmentation ;
vc:relatedTo ngm:deep-learning ;
vc:relatedTo ngm:ensemble-methods ;
vc:relatedTo ngm:regularisation ;
vc:requires ngm:annotated-training-data ;
vc:requires ngm:labelled-dataset ;
vc:requires ngm:loss-function ;
vc:requires ngm:performance-metrics ;
vc:requires ngm:resampling ;
vc:slug "cross-validation" ;
vc:sourceDomain "machine-learning" ;
vc:supports ngm:applied-machine-learning ;
vc:supports ngm:auto-ml ;
vc:supports ngm:bias-variance-tradeoff ;
vc:supports ngm:ensemble-methods ;
vc:supports ngm:model-comparison ;
vc:supports ngm:model-evaluation ;
vc:supports ngm:overfitting-prevention ;
vc:supports ngm:regularisation ;
vc:uses ngm:boosting ;
vc:uses ngm:convolutional-neural-network ;
vc:uses ngm:decision-tree ;
vc:uses ngm:loss-function ;
vc:uses ngm:performance-metrics ;
vc:uses ngm:random-forest ;
vc:uses ngm:support-vector-machine .
ngm:cross-vendor-agent-interoperability a skos:Concept ;
rdfs:label "Cross Vendor Agent Interoperability"@en .
ngm:cross-world-travel a skos:Concept ;
rdfs:label "Cross World Travel"@en .
ngm:crosslingualcollaboration a skos:Concept ;
rdfs:label "Crosslingualcollaboration"@en .
ngm:crossover a skos:Concept ;
rdfs:label "Crossover"@en .
ngm:crowd-simulation a owl:Class ;
rdfs:comment "Crowd simulation models the collective movement and behaviour of large numbers of agents -- pedestrians, vehicles or non-player characters -- navigating shared space while responding to obstacles, goals and one another. It combines agent-based modelling with local avoidance and flocking rules to produce plausible emergent group behaviour at real-time or near-real-time speed. It is used in procedural animation, urban planning tools and game and simulation environments."@en ;
rdfs:label "Crowd Simulation"@en ;
rdfs:subClassOf ngm:simulation ;
rdfs:subClassOf _:r6157 ;
vc:enables ngm:procedural-animation ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:simulation ;
vc:qualityScore "0.55"^^xsd:float ;
vc:requires ngm:agent-based-modelling ;
vc:slug "crowd-simulation" ;
vc:sourceDomain "spatial-computing" .
ngm:crowd-sourcing-platform a skos:Concept ;
rdfs:label "Crowd Sourcing Platform"@en .
ngm:crowd-wisdom a skos:Concept ;
rdfs:label "Crowd Wisdom"@en .
ngm:crowdfunding a owl:Class ;
rdfs:comment "Crowdfunding is a financing model in which a project or venture raises capital from a large number of contributors, each providing a relatively small amount, typically through an online platform. Models range from donation and reward-based campaigns to equity and debt offerings, and blockchain variants use token sales to distribute ownership or utility rights. The approach broadens access to early-stage capital while distributing risk across many backers."@en ;
rdfs:label "Crowdfunding"@en ;
rdfs:subClassOf ngm:de-fi ;
rdfs:subClassOf _:r6158 ;
vc:bridgesTo ngm:ico ;
vc:bridgesTo ngm:initial-coin-offering ;
vc:bridgesTo ngm:security-token-offering ;
vc:contrastsWith ngm:venture-capital ;
vc:enables ngm:token-distribution ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:smart-contract ;
vc:isPartOf ngm:de-fi ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:dao ;
vc:relatedTo ngm:de-fi ;
vc:relatedTo ngm:ico ;
vc:relatedTo ngm:venture-capital ;
vc:requires ngm:tokenomics ;
vc:slug "crowdfunding" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:de-fi ;
vc:uses ngm:smart-contract ;
vc:uses ngm:token-distribution ;
vc:uses ngm:tokenomics .
ngm:crowdsourcing a owl:Class ;
rdfs:comment "Crowdsourcing is the practice of obtaining contributions, labour or judgements from a large distributed group of people, typically through an open call mediated by an online platform. In machine learning it is widely used to collect, label and validate training data by decomposing work into microtasks distributed across many contributors. Effective crowdsourcing combines incentive design with quality-control mechanisms to aggregate noisy individual inputs into reliable results."@en ;
rdfs:label "Crowdsourcing"@en ;
rdfs:subClassOf ngm:data-collection ;
rdfs:subClassOf _:r6159 ;
rdfs:subClassOf _:r6160 ;
rdfs:subClassOf _:r6161 ;
rdfs:subClassOf _:r6162 ;
vc:bridgesTo ngm:collective-intelligence ;
vc:contrastsWith ngm:distributed-computing ;
vc:dependsOn ngm:distributed-computing ;
vc:enables ngm:machine-learning-discipline ;
vc:enables ngm:training ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:incentive-mechanism ;
vc:hasPart ngm:quality-control ;
vc:isPartOf ngm:data-collection ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:incentive-mechanism ;
vc:relatedTo ngm:reputation-system ;
vc:requires ngm:quality-control ;
vc:requires ngm:reputation-system ;
vc:slug "crowdsourcing" ;
vc:sourceDomain "machine-learning" ;
vc:supports ngm:data-collection ;
vc:uses ngm:consensus ;
vc:uses ngm:human-in-the-loop .
ngm:crowdsourcing-aggregation a skos:Concept ;
rdfs:label "Crowdsourcing Aggregation"@en .
ngm:crows-pairs a skos:Concept ;
rdfs:label "Crows Pairs"@en .
ngm:crps-evaluation-standard a skos:Concept ;
rdfs:label "Crps Evaluation Standard"@en .
ngm:cruise-phase a owl:Class ;
rdfs:label "Cruise Phase"@en ;
rdfs:subClassOf ngm:mission-phase ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:space-systems-engineering ;
vc:slug "cruise-phase" ;
vc:sourceDomain "space-science-and-systems" .
ngm:crush-algorithm a skos:Concept ;
rdfs:label "Crush Algorithm"@en .
ngm:cryengine a skos:Concept ;
rdfs:label "Cryengine"@en .
ngm:cryogenic-cooling a skos:Concept ;
rdfs:label "Cryogenic Cooling"@en .
ngm:cryptanalysis a skos:Concept ;
rdfs:label "Cryptanalysis"@en .
ngm:crypto-aggregation a skos:Concept ;
rdfs:label "Crypto Aggregation"@en .
ngm:crypto-anarchism a skos:Concept ;
rdfs:label "Crypto Anarchism"@en .
ngm:crypto-asset a skos:Concept ;
rdfs:label "Crypto Asset"@en .
ngm:crypto-asset-compliance a skos:Concept ;
rdfs:label "Crypto Asset Compliance"@en .
ngm:crypto-asset-reporting-framework a skos:Concept ;
rdfs:label "Crypto Asset Reporting Framework"@en .
ngm:crypto-asset-service-provider a owl:Class ;
rdfs:comment "A legal person authorised to provide crypto-asset services to third parties on a professional basis — custody, exchange operation, order execution, placement, transfer services, and advice — as defined by the EU's Markets in Crypto-Assets Regulation (MiCA); CASPs must obtain authorisation, meet prudential and governance requirements, and comply with anti-money-laundering and travel-rule obligations, gaining passporting rights across the EU single market."@en ;
rdfs:label "Crypto Asset Service Provider"@en ;
rdfs:subClassOf ngm:financial-services ;
rdfs:subClassOf _:r6163 ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:aml ;
vc:implements ngm:kyc ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:cryptocurrency-exchange ;
vc:relatedTo ngm:digital-asset-custody ;
vc:relatedTo ngm:transfer-of-funds-regulation ;
vc:requires ngm:eu-mi-ca-regulation ;
vc:slug "crypto-asset-service-provider" ;
vc:sourceDomain "blockchain" .
ngm:crypto-asset-taxonomy a skos:Concept ;
rdfs:label "Crypto Asset Taxonomy"@en .
ngm:crypto-asset-white-paper a skos:Concept ;
rdfs:label "Crypto Asset White Paper"@en .
ngm:crypto-climate-accord a owl:Class ;
rdfs:comment "The Crypto Climate Accord is a private-sector initiative launched in 2021 to decarbonise the cryptocurrency and blockchain industry, modelled on the Paris Climate Agreement. It commits signatory companies and projects to achieving net-zero greenhouse-gas emissions from electricity consumption by 2030 and to developing open-source accounting standards and tools for measuring and reporting crypto energy use."@en ;
rdfs:label "Crypto Climate Accord"@en ;
rdfs:subClassOf ngm:esg ;
rdfs:subClassOf _:r6164 ;
rdfs:subClassOf _:r6165 ;
vc:bridgesTo ngm:bc-0482-eu-mica-regulation ;
vc:bridgesTo ngm:governance ;
vc:bridgesTo ngm:sustainability-reporting ;
vc:contrastsWith ngm:bitcoin-proof-of-work-protocol-mining ;
vc:enables ngm:voluntary-carbon-market ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:24-7-carbon-free-energy ;
vc:implements ngm:carbon-accounting ;
vc:implements ngm:renewable-energy-certificates ;
vc:qualityScore "0.82"^^xsd:float ;
vc:relatedTo ngm:blockchain-energy-consumption ;
vc:relatedTo ngm:carbon-credits ;
vc:relatedTo ngm:paris-agreement ;
vc:relatedTo ngm:proof-of-stake ;
vc:relatedTo ngm:proof-of-work ;
vc:relatedTo ngm:renewable-energy ;
vc:relatedTo ngm:scope-2-emissions ;
vc:requires ngm:emissions-reporting ;
vc:requires ngm:power-purchase-agreement ;
vc:slug "crypto-climate-accord" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:decarbonisation ;
vc:supports ngm:esg-compliant-blockchain ;
vc:supports ngm:institutional-adoption ;
vc:supports ngm:renewable-energy-tracking .
ngm:crypto-regulation a owl:Class ;
rdfs:comment "Crypto regulation is the body of laws and supervisory rules governing the issuance, trading, custody and use of crypto-assets, including authorisation of service providers, disclosure requirements, market conduct rules, client-asset custody standards, and anti-money-laundering obligations."@en ;
rdfs:label "Crypto Regulation"@en ;
rdfs:subClassOf ngm:financial-regulation ;
rdfs:subClassOf _:r6166 ;
rdfs:subClassOf _:r6167 ;
rdfs:subClassOf _:r6168 ;
rdfs:subClassOf _:r6169 ;
rdfs:subClassOf _:r6170 ;
vc:bridgesTo ngm:aml ;
vc:bridgesTo ngm:central-bank-digital-currency-cbdc ;
vc:bridgesTo ngm:stablecoin ;
vc:contrastsWith ngm:de-fi ;
vc:contrastsWith ngm:self-regulation ;
vc:dependsOn ngm:financial-action-task-force ;
vc:dependsOn ngm:financial-stability-board ;
vc:enables ngm:financial-stability ;
vc:enables ngm:investor-protection ;
vc:enables ngm:market-integrity ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:aml ;
vc:hasPart ngm:kyc ;
vc:hasPart ngm:market-abuse-regulation ;
vc:implements ngm:bc-0484-markets-in-crypto-assets ;
vc:implements ngm:travel-rule ;
vc:isPartOf ngm:financial-regulation ;
vc:isPartOf ngm:governance ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:cybersecurity ;
vc:relatedTo ngm:securities-law ;
vc:relatedTo ngm:taxation ;
vc:requires ngm:compliance ;
vc:requires ngm:licensing ;
vc:requires ngm:regulatory-frameworks ;
vc:slug "crypto-regulation" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:basel-committee-on-banking-supervision ;
vc:standardizedBy ngm:international-organization-of-securities-commissions ;
vc:supports ngm:consumer-protection ;
vc:supports ngm:financial-inclusion ;
vc:uses ngm:blockchain ;
vc:uses ngm:smart-contracts .
ngm:crypto-token a owl:Class ;
rdfs:comment "A blockchain-based programmable token representing assets, rights, or utility within a decentralized system, with transferability governed by smart contract logic."@en ;
rdfs:label "Crypto Token"@en ;
rdfs:subClassOf ngm:bc-token-and-asset ;
rdfs:subClassOf _:r6171 ;
rdfs:subClassOf _:r6172 ;
rdfs:subClassOf _:r6173 ;
rdfs:subClassOf _:r6174 ;
rdfs:subClassOf _:r6175 ;
rdfs:subClassOf _:r6176 ;
rdfs:subClassOf _:r6177 ;
rdfs:subClassOf _:r6178 ;
rdfs:subClassOf _:r6179 ;
skos:broader ngm:bc-token-and-asset ;
vc:bridgesTo ngm:ai-agent-system ;
vc:dependsOn ngm:consensus-mechanism ;
vc:dependsOn ngm:cryptographic-key ;
vc:enables ngm:decentralized-exchange ;
vc:enables ngm:digital-ownership ;
vc:enables ngm:governance-voting ;
vc:enables ngm:programmable-value ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:loyalty-token ;
vc:hasPart ngm:metadata-schema ;
vc:hasPart ngm:non-fungible-token-nft ;
vc:hasPart ngm:smart-contract ;
vc:hasPart ngm:stablecoin ;
vc:hasPart ngm:token-standard ;
vc:isPartOf ngm:blockchain-network ;
vc:isPartOf ngm:tokenization-system ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:blockchain ;
vc:requires ngm:token-standard ;
vc:requires ngm:wallet ;
vc:slug "crypto-token" ;
vc:sourceDomain "blockchain" .
ngm:crypto-tourism a skos:Concept ;
rdfs:label "Crypto Tourism"@en .
ngm:crypto-trading a owl:Class ;
rdfs:comment "Crypto trading is the buying and selling of cryptocurrencies and digital assets for profit, conducted on centralised exchanges, decentralised exchanges, and over-the-counter desks. It spans spot, margin, derivatives, and algorithmic strategies, with prices driven by liquidity, sentiment, and on-chain activity. It is a primary use case and liquidity source for the broader crypto-asset market."@en ;
rdfs:label "Crypto Trading"@en ;
rdfs:subClassOf ngm:financial-services ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:kraken ;
vc:relatedTo ngm:tether ;
vc:slug "crypto-trading" ;
vc:sourceDomain "blockchain" .
ngm:crypto-wallet a owl:Class ;
rdfs:comment "A crypto wallet is software or hardware that manages the private keys controlling blockchain assets and enables users to sign transactions, hold tokens, and interact with decentralised applications. Wallets may be custodial or non-custodial, hot or cold, and increasingly serve as the identity and access layer for Web3. They do not store assets themselves but the cryptographic keys that authorise control over on-chain balances."@en ;
rdfs:label "Crypto Wallet"@en ;
rdfs:subClassOf ngm:network-component ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:blockchain ;
vc:relatedTo ngm:web3 ;
vc:slug "crypto-wallet" ;
vc:sourceDomain "blockchain" .
ngm:cryptoasset a skos:Concept ;
rdfs:label "Cryptoasset"@en .
ngm:cryptoasset-regulation a owl:Class ;
rdfs:comment "Cryptoasset regulation is the body of laws, supervisory rules, and policy frameworks governing the issuance, custody, trading, and use of digital assets such as cryptocurrencies, stablecoins, and tokenised securities. It applies traditional financial-services objectives, consumer protection, market integrity, financial stability, and the prevention of money laundering and terrorist financing, to crypto-native business models. Landmark regimes include the EU Markets in Crypto-Assets regulation and the UK's phased approach led by the Financial Conduct Authority and HM Treasury, alongside global standards from the Financial Action Task Force such as the travel rule."@en ;
rdfs:label "Cryptoasset Regulation"@en ;
rdfs:subClassOf ngm:regulation ;
rdfs:subClassOf _:r6180 ;
rdfs:subClassOf _:r6181 ;
rdfs:subClassOf _:r6182 ;
vc:bridgesTo ngm:blockchain ;
vc:contrastsWith ngm:monetary-policy ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:markets-in-crypto-assets ;
vc:implements ngm:travel-rule ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:central-bank ;
vc:relatedTo ngm:institutional-trust ;
vc:requires ngm:aml ;
vc:requires ngm:kyc ;
vc:slug "cryptoasset-regulation" ;
vc:sourceDomain "finance" ;
vc:supports ngm:financial-stability ;
vc:supports ngm:risk-management ;
vc:uses ngm:governance .
ngm:cryptoasset-regulatory-framework a owl:Class ;
rdfs:comment "Crypto Legal from DigiSoc examines the legal, regulatory, and governance landscape surrounding cryptocurrency and digital assets within digital society contexts. It covers UK and EU regulatory positions on crypto-assets as property, stablecoin frameworks, AML/KYC obligations, and the intersection of Web3 economics with metaverse commerce. The field addresses how legacy legal systems must adapt to support low-friction, globally scalable value exchange in virtual social spaces."@en ;
rdfs:label "Cryptoasset Regulatory Framework"@en ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
rdfs:subClassOf _:r6183 ;
rdfs:subClassOf _:r6184 ;
skos:broader ngm:bc-governance-and-regulation ;
vc:bridgesTo ngm:blockchain ;
vc:contrastsWith ngm:digital-commerce ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:ai-regulation ;
vc:relatedTo ngm:data-governance ;
vc:requires ngm:blockchain ;
vc:requires ngm:digital-asset ;
vc:slug "cryptoasset-regulatory-framework" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:verifiable-credentials .
ngm:cryptoasset-taxation a skos:Concept ;
rdfs:label "Cryptoasset Taxation"@en .
ngm:cryptocurrency a owl:Class ;
rdfs:comment "Cryptocurrency is a class of bearer-style digital assets whose unit ownership, issuance schedule, and transaction history are jointly secured by Public-Key Cryptography and a permissionless Consensus Mechanism operated by a Peer-to-Peer Network of independent nodes, such that no centr..."@en ;
rdfs:label "Cryptocurrency"@en ;
rdfs:subClassOf ngm:bc-token-and-asset ;
rdfs:subClassOf ngm:bearer-instrument ;
rdfs:subClassOf ngm:cryptoasset ;
rdfs:subClassOf ngm:digital-asset ;
rdfs:subClassOf ngm:distributed-ledger-native-token ;
rdfs:subClassOf ngm:network-component ;
rdfs:subClassOf ngm:permissionless-asset ;
rdfs:subClassOf _:r6209 ;
rdfs:subClassOf _:r6210 ;
rdfs:subClassOf _:r6211 ;
rdfs:subClassOf _:r6212 ;
rdfs:subClassOf _:r6213 ;
rdfs:subClassOf _:r6214 ;
rdfs:subClassOf _:r6215 ;
rdfs:subClassOf _:r6216 ;
rdfs:subClassOf _:r6217 ;
rdfs:subClassOf _:r6218 ;
rdfs:subClassOf _:r6219 ;
rdfs:subClassOf _:r6220 ;
rdfs:subClassOf _:r6221 ;
rdfs:subClassOf _:r6222 ;
rdfs:subClassOf _:r6223 ;
skos:broader ngm:bc-token-and-asset ;
vc:contrastsWith ngm:bank-deposit ;
vc:contrastsWith ngm:central-bank-digital-currency-cbdc ;
vc:contrastsWith ngm:fiat-currency ;
vc:contrastsWith ngm:money ;
vc:contrastsWith ngm:tokenised-deposit ;
vc:contrastsWith ngm:traditional-security ;
vc:dependsOn ngm:cryptographic-hash-function ;
vc:dependsOn ngm:elliptic-curve-cryptography ;
vc:dependsOn ngm:internet ;
vc:dependsOn ngm:mining-hardware ;
vc:dependsOn ngm:node-operator ;
vc:dependsOn ngm:public-key-infrastructure ;
vc:dependsOn ngm:validator-stake ;
vc:enables ngm:censorship-resistance ;
vc:enables ngm:cross-border-transfer ;
vc:enables ngm:financial-inclusion ;
vc:enables ngm:peer-to-peer-payment ;
vc:enables ngm:permissionless-innovation ;
vc:enables ngm:programmable-money ;
vc:enables ngm:real-time-settlement ;
vc:enables ngm:self-custody ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:block-header ;
vc:hasPart ngm:consensus-mechanism ;
vc:hasPart ngm:digital-signature ;
vc:hasPart ngm:distributed-ledger ;
vc:hasPart ngm:mempool ;
vc:hasPart ngm:public-key-cryptography ;
vc:hasPart ngm:transaction ;
vc:hasPart ngm:wallet ;
vc:implements ngm:cryptographic-ownership ;
vc:implements ngm:double-spend-prevention ;
vc:implements ngm:emission-schedule ;
vc:implements ngm:hard-money ;
vc:implements ngm:trustless-settlement ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol ;
vc:relatedTo ngm:centralised-exchange ;
vc:relatedTo ngm:decentralised-exchange ;
vc:relatedTo ngm:decentralized-exchange ;
vc:relatedTo ngm:ethereum-smart-contract-platform ;
vc:relatedTo ngm:micro-strategy ;
vc:relatedTo ngm:neural-network-text-tokenisation ;
vc:relatedTo ngm:real-world-asset ;
vc:relatedTo ngm:smart-contract ;
vc:relatedTo ngm:spot-bitcoin-etf ;
vc:relatedTo ngm:stablecoin ;
vc:requires ngm:blockchain ;
vc:requires ngm:cryptographic-hash-function ;
vc:requires ngm:cryptography ;
vc:requires ngm:peer-to-peer-network ;
vc:requires ngm:proof-of-stake ;
vc:requires ngm:proof-of-work ;
vc:requires ngm:sybil-resistance ;
vc:slug "cryptocurrency" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:bc-0482-eu-mica-regulation ;
vc:standardizedBy ngm:bitcoin-proof-of-work-protocol-improvement-proposals ;
vc:standardizedBy ngm:ethereum-smart-contract-platform ;
vc:standardizedBy ngm:fasb-asu-2023-08 ;
vc:standardizedBy ngm:fatf-travel-rule ;
vc:standardizedBy ngm:fca-cryptoasset-promotions-regime-ps23-6 ;
vc:standardizedBy ngm:iso-24165 ;
vc:supports ngm:de-fi ;
vc:supports ngm:depin ;
vc:supports ngm:neural-network-text-tokenisation ;
vc:supports ngm:non-fungible-token ;
vc:supports ngm:smart-contract ;
vc:supports ngm:stablecoin ;
vc:supports ngm:web3 ;
vc:uses ngm:bip-32-hd-wallet ;
vc:uses ngm:bip-39-mnemonic ;
vc:uses ngm:ecdsa ;
vc:uses ngm:ed25519 ;
vc:uses ngm:keccak-256 ;
vc:uses ngm:merkle-tree ;
vc:uses ngm:schnorr-signature ;
vc:uses ngm:sha-256 .
ngm:cryptocurrency-custody a skos:Concept ;
rdfs:label "Cryptocurrency Custody"@en .
ngm:cryptocurrency-exchange a owl:Class ;
rdfs:comment "A cryptocurrency exchange is a platform that enables the trading of digital assets for other cryptocurrencies or for fiat currency. Exchanges match buy and sell orders, provide custody or settlement of funds, and supply liquidity and price discovery for crypto markets. They range from centralised intermediaries holding customer assets to decentralised protocols that execute trades on-chain."@en ;
rdfs:label "Cryptocurrency Exchange"@en ;
rdfs:subClassOf ngm:digital-economy ;
rdfs:subClassOf _:r6185 ;
rdfs:subClassOf _:r6186 ;
rdfs:subClassOf _:r6187 ;
rdfs:subClassOf _:r6188 ;
rdfs:subClassOf _:r6189 ;
vc:bridgesTo ngm:fiat-currency ;
vc:contrastsWith ngm:centralised-exchange ;
vc:contrastsWith ngm:decentralised-exchange ;
vc:enables ngm:liquidity ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:hot-wallet ;
vc:hasPart ngm:order-book ;
vc:hasPart ngm:wallet ;
vc:isPartOf ngm:digital-economy ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:bitcoin ;
vc:relatedTo ngm:cryptocurrency ;
vc:relatedTo ngm:stablecoin ;
vc:relatedTo ngm:tether ;
vc:requires ngm:blockchain ;
vc:requires ngm:custody ;
vc:slug "cryptocurrency-exchange" ;
vc:sourceDomain "finance" ;
vc:supports ngm:custody ;
vc:supports ngm:liquidity ;
vc:uses ngm:fiat-currency ;
vc:uses ngm:kyc .
ngm:cryptocurrency-forensics a skos:Concept ;
rdfs:label "Cryptocurrency Forensics"@en .
ngm:cryptocurrency-investigation a skos:Concept ;
rdfs:label "Cryptocurrency Investigation"@en .
ngm:cryptocurrency-mining a owl:Class ;
rdfs:comment "Cryptocurrency Mining is the process by which nodes in a proof-of-work blockchain network compete to solve computationally intensive cryptographic puzzles in order to validate pending transactions and append new blocks to the chain. Successful miners are rewarded with newly minted coins and transaction fees, providing the economic incentive that secures the network. The energy intensity and hardware specialisation of mining have significant environmental and economic implications."@en ;
rdfs:label "Cryptocurrency Mining"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.7"^^xsd:float ;
vc:relatedTo ngm:hard-fork ;
vc:slug "cryptocurrency-mining" ;
vc:sourceDomain "blockchain" .
ngm:cryptocurrency-mixer a skos:Concept ;
rdfs:label "Cryptocurrency Mixer"@en .
ngm:cryptocurrency-payment a skos:Concept ;
rdfs:label "Cryptocurrency Payment"@en .
ngm:cryptocurrency-regulation a owl:Class ;
rdfs:comment "The body of laws, supervisory frameworks, and enforcement practice governing the issuance, custody, exchange, and use of cryptocurrencies and related digital assets. It spans securities and commodities classification, anti-money-laundering and counter-terrorist-financing obligations, consumer and investor protection, taxation, stablecoin reserve requirements, and prudential rules for intermediaries, and it varies sharply across jurisdictions — from comprehensive regimes such as the EU's MiCA to outright prohibitions."@en ;
rdfs:label "Cryptocurrency Regulation"@en ;
rdfs:subClassOf ngm:financial-regulation ;
rdfs:subClassOf _:r6190 ;
vc:dependsOn ngm:cryptocurrency ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:aml ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:regulation ;
vc:slug "cryptocurrency-regulation" ;
vc:sourceDomain "governance" .
ngm:cryptocurrency-remuneration a owl:Class ;
rdfs:comment "Cryptocurrency remuneration is the practice of paying remote workers, freelancers, or distributed team members in digital assets — including Bitcoin, Ethereum, or fiat-pegged stablecoins — rather than traditional currency. It enables borderless, near-instant settlement at low transaction cost, bypassing correspondent banking infrastructure and extending financial access to unbanked populations. Compliance with local payroll tax, AML/KYC, and employment law obligations remains essential."@en ;
rdfs:label "Cryptocurrency Remuneration"@en ;
rdfs:subClassOf ngm:cryptocurrency ;
rdfs:subClassOf ngm:dc-protocol-and-infra ;
rdfs:subClassOf _:r6191 ;
rdfs:subClassOf _:r6192 ;
rdfs:subClassOf _:r6193 ;
skos:broader ngm:dc-protocol-and-infra ;
vc:bridgesTo ngm:cryptocurrency ;
vc:enables ngm:cross-border-payments ;
vc:enables ngm:distributed-work ;
vc:enables ngm:financial-inclusion ;
vc:enables ngm:micropayments ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:blockchain-collaboration ;
vc:relatedTo ngm:dao ;
vc:relatedTo ngm:smart-contract-coordination ;
vc:relatedTo ngm:telecollaboration ;
vc:requires ngm:aml-kyc-compliance ;
vc:requires ngm:corporate-tax-compliance-framework-treatment-crypto ;
vc:requires ngm:regulatory-compliance ;
vc:slug "cryptocurrency-remuneration" ;
vc:sourceDomain "distributed-collaboration" ;
vc:uses ngm:blockchain ;
vc:uses ngm:lightning-network ;
vc:uses ngm:smart-contract ;
vc:uses ngm:stablecoin .
ngm:cryptocurrency-storage a owl:Class ;
rdfs:comment "Cryptocurrency Storage encompasses the cryptographic key management systems and secure storage solutions for maintaining control over digital assets on blockchain networks. Architectures range from hot wallets with internet connectivity through cold storage hardware devices to multi-signature and threshold-signature schemes. Hierarchical Deterministic (HD) wallets following BIP32/BIP39 standards generate key trees from a single seed phrase, while institutional custody solutions leverage multi-party computation (MPC) and smart-contract-based social recovery for asset governance."@en ;
rdfs:label "Cryptocurrency Storage"@en ;
rdfs:subClassOf ngm:network-component ;
rdfs:subClassOf _:r6194 ;
rdfs:subClassOf _:r6195 ;
vc:bridgesTo ngm:blockchain ;
vc:dependsOn ngm:cryptographic-infrastructure ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:requires ngm:blockchain ;
vc:requires ngm:cryptographic-key-management ;
vc:slug "cryptocurrency-storage" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:digital-asset-management ;
vc:uses ngm:cryptographic-signature ;
vc:uses ngm:ecdsa .
ngm:cryptocurrency-token a owl:Class ;
rdfs:comment "A programmable digital asset implemented via smart contracts on a blockchain platform, categorised into utility tokens (access rights), security tokens (equity or debt instruments), governance tokens (protocol voting rights), and non-fungible tokens (NFTs, unique digital ownership). Token behaviour and interoperability are defined by standards such as ERC-20, ERC-721, and ERC-1155."@en ;
rdfs:label "Cryptocurrency Token"@en ;
rdfs:subClassOf ngm:bc-token-and-asset ;
rdfs:subClassOf _:r6196 ;
rdfs:subClassOf _:r6197 ;
rdfs:subClassOf _:r6198 ;
rdfs:subClassOf _:r6199 ;
rdfs:subClassOf _:r6200 ;
rdfs:subClassOf _:r6201 ;
rdfs:subClassOf _:r6202 ;
rdfs:subClassOf _:r6203 ;
rdfs:subClassOf _:r6204 ;
rdfs:subClassOf _:r6205 ;
skos:broader ngm:bc-token-and-asset ;
vc:bridgesTo ngm:digital-identity ;
vc:bridgesTo ngm:finance ;
vc:bridgesTo ngm:supply-chain ;
vc:contrastsWith ngm:central-bank-digital-currency-cbdc ;
vc:contrastsWith ngm:cryptocurrency ;
vc:dependsOn ngm:consensus-mechanism ;
vc:dependsOn ngm:distributed-ledger ;
vc:enables ngm:dao ;
vc:enables ngm:liquidity-provision ;
vc:enables ngm:staking ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:fungible-token ;
vc:hasPart ngm:governance-token ;
vc:hasPart ngm:non-fungible-token ;
vc:hasPart ngm:security-token ;
vc:hasPart ngm:utility-token ;
vc:hasPart ngm:wrapped-token ;
vc:implements ngm:erc-1155 ;
vc:isPartOf ngm:de-fi ;
vc:isPartOf ngm:token-economy ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:airdrop ;
vc:relatedTo ngm:initial-coin-offering ;
vc:relatedTo ngm:token-economics ;
vc:requires ngm:blockchain ;
vc:requires ngm:cryptographic-key ;
vc:requires ngm:digital-wallet ;
vc:requires ngm:smart-contract ;
vc:slug "cryptocurrency-token" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:erc-20-token-standard ;
vc:standardizedBy ngm:erc-721-standard ;
vc:standardizedBy ngm:token-standard ;
vc:uses ngm:automated-market-maker ;
vc:uses ngm:blockchain-oracle .
ngm:cryptocurrency-wallet a owl:Class ;
rdfs:comment "A cryptocurrency wallet is software or hardware that manages the cryptographic keys controlling blockchain assets and constructs, signs and broadcasts transactions on a user's behalf. It does not store coins, which exist only as ledger entries, but rather safeguards the private keys that authorise spending and prove ownership. Wallets range from custodial services that hold keys for users to non-custodial and hardware wallets that give users sole control."@en ;
rdfs:label "Cryptocurrency Wallet"@en ;
rdfs:subClassOf ngm:wallet ;
rdfs:subClassOf _:r6206 ;
rdfs:subClassOf _:r6207 ;
rdfs:subClassOf _:r6208 ;
vc:bridgesTo ngm:decentralised-application ;
vc:dependsOn ngm:blockchain ;
vc:enables ngm:decentralised-application ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:private-key ;
vc:implements ngm:key-management ;
vc:isPartOf ngm:cryptocurrency ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:de-fi ;
vc:relatedTo ngm:hardware-wallet ;
vc:relatedTo ngm:staking ;
vc:requires ngm:key-management ;
vc:requires ngm:private-key ;
vc:slug "cryptocurrency-wallet" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:custody ;
vc:supports ngm:self-custody ;
vc:uses ngm:digital-signature .
ngm:cryptoeconomic-incentive a skos:Concept ;
rdfs:label "Cryptoeconomic Incentive"@en .
ngm:cryptoeconomics a owl:Class ;
rdfs:comment "Cryptoeconomics is the discipline that combines cryptography with economic incentives to design and secure decentralised systems whose participants are assumed to act in their own self-interest. It uses mechanism design and game theory to make honest behaviour the rational choice, so that protocols remain secure and live without a trusted central authority. The field underpins consensus mechanisms, token economies, and the incentive structures of blockchain networks."@en ;
rdfs:label "Cryptoeconomics"@en ;
rdfs:subClassOf ngm:blockchain-economics ;
rdfs:subClassOf _:r6224 ;
vc:bridgesTo ngm:economic-security ;
vc:bridgesTo ngm:game-theory ;
vc:dependsOn ngm:cryptography ;
vc:dependsOn ngm:game-theory ;
vc:dependsOn ngm:mechanism-design ;
vc:enables ngm:consensus-mechanism ;
vc:enables ngm:proof-of-stake ;
vc:enables ngm:sybil-resistance ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:blockchain ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:dao ;
vc:relatedTo ngm:smart-contract ;
vc:relatedTo ngm:staking ;
vc:requires ngm:mechanism-design ;
vc:slug "cryptoeconomics" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:blockchain-governance ;
vc:supports ngm:de-fi ;
vc:uses ngm:token-economics ;
vc:uses ngm:tokenomics .
ngm:cryptographic-accumulator a owl:Class ;
rdfs:comment "A cryptographic accumulator is a primitive that compresses a large set of elements into a single short value while still permitting compact proofs that a given element is (or is not) a member of the set. Constructions based on RSA groups, bilinear pairings, or Merkle trees allow membership witnesses whose size is independent of the set's cardinality, and dynamic accumulators support efficient addition and removal of elements. Accumulators underpin scalable membership proofs in anonymous credentials, certificate revocation, and stateless blockchain clients."@en ;
rdfs:label "Cryptographic Accumulator"@en ;
rdfs:subClassOf ngm:cryptographic-primitive ;
vc:enables ngm:zero-knowledge-proof ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:digital-signature ;
vc:relatedTo ngm:merkle-tree ;
vc:slug "cryptographic-accumulator" ;
vc:sourceDomain "security" ;
vc:uses ngm:hash-function .
ngm:cryptographic-addresses a skos:Concept ;
rdfs:label "Cryptographic Addresses"@en .
ngm:cryptographic-algorithm a owl:Class ;
rdfs:comment "A Cryptographic Algorithm is a precisely defined mathematical procedure that transforms data to achieve security properties—confidentiality, integrity, authentication, or non-repudiation—based on computational hardness assumptions. The class encompasses symmetric ciphers, asymmetric (public-key) schemes, hash functions, digital signature algorithms, and zero-knowledge proof systems, each providing different security guarantees and performance characteristics."@en ;
rdfs:label "Cryptographic Algorithm"@en ;
rdfs:subClassOf ngm:cryptography ;
rdfs:subClassOf _:r6225 ;
rdfs:subClassOf _:r6226 ;
rdfs:subClassOf _:r6227 ;
rdfs:subClassOf _:r6228 ;
rdfs:subClassOf _:r6229 ;
rdfs:subClassOf _:r6230 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:distributed-systems ;
vc:contrastsWith ngm:obfuscation ;
vc:contrastsWith ngm:steganography ;
vc:enables ngm:authentication ;
vc:enables ngm:data-integrity ;
vc:enables ngm:digital-signature ;
vc:enables ngm:encryption ;
vc:enables ngm:secure-communication ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:hash-function ;
vc:hasPart ngm:public-key-cryptography ;
vc:hasPart ngm:symmetric-encryption ;
vc:implements ngm:computational-hardness-assumption ;
vc:implements ngm:post-quantum-cryptography ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:homomorphic-encryption ;
vc:relatedTo ngm:message-authentication-code ;
vc:relatedTo ngm:public-key-cryptography ;
vc:requires ngm:hardware-security-module ;
vc:requires ngm:key-management ;
vc:requires ngm:random-number-generation ;
vc:slug "cryptographic-algorithm" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:internet-engineering-task-force ;
vc:supports ngm:cryptographic-infrastructure ;
vc:supports ngm:tls ;
vc:supports ngm:zero-knowledge-proof .
ngm:cryptographic-attestation a skos:Concept ;
rdfs:label "Cryptographic Attestation"@en .
ngm:cryptographic-binding a skos:Concept ;
rdfs:label "Cryptographic Binding"@en .
ngm:cryptographic-commitment a owl:Class ;
rdfs:comment "A cryptographic scheme that allows a party to commit to a chosen value while keeping it hidden, with the ability to reveal it later, satisfying the binding property (cannot change the committed value) and the hiding property (the commitment reveals no information about the value). Used in zero-knowledge proofs, atomic swaps, and confidential transactions."@en ;
rdfs:label "Cryptographic Commitment"@en ;
rdfs:subClassOf ngm:blockchain-entity ;
rdfs:subClassOf ngm:cryptographic-primitive ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:verifiable-credential-vc ;
vc:contrastsWith ngm:digital-signature ;
vc:contrastsWith ngm:encryption ;
vc:dependsOn ngm:discrete-logarithm-problem ;
vc:dependsOn ngm:random-oracle-model ;
vc:enables ngm:atomic-swap ;
vc:enables ngm:confidential-transactions ;
vc:enables ngm:cryptographic-protocol ;
vc:enables ngm:immutability ;
vc:enables ngm:secure-multi-party-computation ;
vc:enables ngm:zk-snarks ;
vc:enables ngm:zk-starks ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:polynomial-commitment ;
vc:implements ngm:vector-commitment ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:coin-flipping-protocol ;
vc:relatedTo ngm:digital-signature ;
vc:relatedTo ngm:merkle-tree ;
vc:relatedTo ngm:oblivious-transfer ;
vc:relatedTo ngm:schnorr-signature ;
vc:relatedTo ngm:zero-knowledge ;
vc:slug "cryptographic-commitment" ;
vc:sourceDomain "security" ;
vc:supports ngm:blockchain ;
vc:supports ngm:smart-contract ;
vc:uses ngm:cryptographic-hash-function ;
vc:uses ngm:elliptic-curve-cryptography ;
vc:uses ngm:hash-function ;
vc:uses ngm:pedersen-commitment ;
vc:uses ngm:zero-knowledge-proof .
ngm:cryptographic-commitments a skos:Concept ;
rdfs:label "Cryptographic Commitments"@en .
ngm:cryptographic-domain a skos:Concept ;
rdfs:label "Cryptographic Domain"@en .
ngm:cryptographic-handshake a skos:Concept ;
rdfs:label "Cryptographic Handshake"@en .
ngm:cryptographic-hardness-assumption a skos:Concept ;
rdfs:label "Cryptographic Hardness Assumption"@en .
ngm:cryptographic-hash a owl:Class ;
rdfs:comment "Deterministic mathematical function transforming arbitrary input data into a fixed-length digest, guaranteeing data integrity verification and tamper detection through collision resistance, pre-image resistance, and avalanche-effect properties."@en ;
rdfs:label "Cryptographic Hash"@en ;
rdfs:subClassOf ngm:cryptographic-primitive ;
rdfs:subClassOf _:r6234 ;
rdfs:subClassOf _:r6235 ;
rdfs:subClassOf _:r6236 ;
rdfs:subClassOf _:r6237 ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:decentralised-identity ;
vc:bridgesTo ngm:supply-chain-provenance ;
vc:contrastsWith ngm:checksums ;
vc:contrastsWith ngm:symmetric-encryption ;
vc:enables ngm:commitment-scheme ;
vc:enables ngm:digital-signatures ;
vc:enables ngm:merkle-tree ;
vc:enables ngm:message-authentication-code ;
vc:enables ngm:password-hashing ;
vc:enables ngm:proof-of-work ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:avalanche-effect ;
vc:hasPart ngm:collision-resistance ;
vc:implements ngm:blake2 ;
vc:implements ngm:keccak-256 ;
vc:implements ngm:sha-256 ;
vc:implements ngm:sha-3 ;
vc:isPartOf ngm:cryptographic-infrastructure ;
vc:isPartOf ngm:cryptographic-protocol ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:blockchain-security ;
vc:relatedTo ngm:post-quantum-cryptography ;
vc:requires ngm:hash-function ;
vc:requires ngm:one-way-function ;
vc:slug "cryptographic-hash" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:nist-fips-186 ;
vc:standardizedBy ngm:nist-fips-202 ;
vc:supports ngm:blockchain ;
vc:supports ngm:data-integrity ;
vc:supports ngm:encryption ;
vc:supports ngm:tamper-detection ;
vc:supports ngm:zero-knowledge-proof ;
vc:uses ngm:compression-function ;
vc:uses ngm:merkle-damgard-construction .
ngm:cryptographic-hash-chain a skos:Concept ;
rdfs:label "Cryptographic Hash Chain"@en .
ngm:cryptographic-hash-function a owl:Class ;
rdfs:comment "A cryptographic hash function is a deterministic, one-way algorithm that maps an input of arbitrary length to a fixed-size digest (typically 160–512 bits), satisfying three core security properties: preimage resistance (infeasibility of recovering input from digest), second-preimage resistance (infeasibility of finding a distinct input that maps to the same digest as a known input), and collision resistance (infeasibility of finding any two distinct inputs that share a digest). These properties make hash functions foundational primitives for data integrity verification, digital signatures, message authentication codes, and proof-of-work consensus. Widely deployed algorithms include SHA-256 (Bitcoin), Keccak-256 (Ethereum), BLAKE2, and SHA-3 (NIST FIPS 202); Grover's algorithm on quantum hardware reduces effective security by half, motivating ongoing standardisation of quantum-resistant alternatives by NIST."@en ;
rdfs:label "Cryptographic Hash Function"@en ;
rdfs:subClassOf ngm:cryptographic-primitive ;
rdfs:subClassOf _:r6231 ;
rdfs:subClassOf _:r6232 ;
rdfs:subClassOf _:r6233 ;
vc:bridgesTo ngm:decentralised-identifier ;
vc:bridgesTo ngm:post-quantum-cryptography ;
vc:bridgesTo ngm:verifiable-credential-vc ;
vc:contrastsWith ngm:checksums ;
vc:contrastsWith ngm:symmetric-encryption ;
vc:enables ngm:commitment-scheme ;
vc:enables ngm:digital-signature ;
vc:enables ngm:merkle-tree ;
vc:enables ngm:message-authentication-code ;
vc:enables ngm:proof-of-work ;
vc:enables ngm:zero-knowledge-proof ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:one-way-function ;
vc:implements ngm:pseudorandom-function ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:hmac ;
vc:relatedTo ngm:key-derivation-function ;
vc:requires ngm:avalanche-effect ;
vc:requires ngm:collision-resistance ;
vc:requires ngm:preimage-resistance ;
vc:requires ngm:second-preimage-resistance ;
vc:slug "cryptographic-hash-function" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:ietf ;
vc:standardizedBy ngm:nist ;
vc:supports ngm:blockchain ;
vc:supports ngm:content-addressed-storage ;
vc:supports ngm:cryptographic-infrastructure ;
vc:supports ngm:password-hashing ;
vc:uses ngm:blake2 ;
vc:uses ngm:keccak-256 ;
vc:uses ngm:sha-256 ;
vc:uses ngm:sha-3 .
ngm:cryptographic-identity a owl:Class ;
rdfs:comment "Cryptographic identity is an identity model in which an actor is represented and authenticated through possession of a private key rather than through a centrally issued credential. Control of the corresponding public key — or an identifier derived from it — proves the actor's identity by producing verifiable digital signatures. This model underpins blockchain accounts, decentralized identifiers and self-sovereign identity, removing the need for a trusted registry to vouch for who someone is."@en ;
rdfs:label "Cryptographic Identity"@en ;
rdfs:subClassOf ngm:decentralized-identity ;
rdfs:subClassOf _:r6238 ;
rdfs:subClassOf _:r6239 ;
vc:bridgesTo ngm:digital-identity ;
vc:contrastsWith ngm:identity-verification ;
vc:dependsOn ngm:key-management ;
vc:dependsOn ngm:public-key-cryptography ;
vc:enables ngm:authentication ;
vc:enables ngm:decentralized-identifier ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:authentication ;
vc:isPartOf ngm:decentralized-identity ;
vc:isPartOf ngm:digital-identity ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:decentralized-identifier ;
vc:relatedTo ngm:trust ;
vc:requires ngm:digital-signature ;
vc:requires ngm:public-key-cryptography ;
vc:slug "cryptographic-identity" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:identity-verification ;
vc:supports ngm:wallet ;
vc:uses ngm:digital-signature ;
vc:uses ngm:hash-function .
ngm:cryptographic-infrastructure a owl:Class ;
rdfs:comment "Cryptographic infrastructure is the ensemble of hardware, software, protocols, and institutional processes that provision, manage, and operate cryptographic primitives at scale across a computing environment. It encompasses key generation and distribution, certificate authorities, hardware security modules, and the policies governing their lifecycle. As a foundational layer, it underpins secure communications, digital identity, and data integrity across both centralised and decentralised systems."@en ;
rdfs:label "Cryptographic Infrastructure"@en ;
rdfs:subClassOf ngm:cryptographic-algorithm ;
rdfs:subClassOf _:r6240 ;
rdfs:subClassOf _:r6241 ;
rdfs:subClassOf _:r6242 ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:cryptographic-hash-function ;
vc:hasPart ngm:cryptographic-infrastructure ;
vc:hasPart ngm:cryptographic-key-management ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:certificate-authority ;
vc:relatedTo ngm:cryptographic-signing ;
vc:relatedTo ngm:digital-signature ;
vc:slug "cryptographic-infrastructure" ;
vc:sourceDomain "infrastructure" .
ngm:cryptographic-integrity-protection a skos:Concept ;
rdfs:label "Cryptographic Integrity Protection"@en .
ngm:cryptographic-key a owl:Class ;
rdfs:comment "A piece of secret or public information that parameterises a cryptographic algorithm, determining how data is encrypted, decrypted or signed. Keys are the inputs that make cryptographic operations specific and reversible only to authorised parties."@en ;
rdfs:label "Cryptographic Key"@en ;
rdfs:subClassOf ngm:cryptography ;
rdfs:subClassOf _:r6249 ;
rdfs:subClassOf _:r6250 ;
rdfs:subClassOf _:r6251 ;
rdfs:subClassOf _:r6252 ;
rdfs:subClassOf _:r6253 ;
rdfs:subClassOf _:r6254 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:digital-identity ;
vc:bridgesTo ngm:key-management ;
vc:bridgesTo ngm:post-quantum-cryptography ;
vc:bridgesTo ngm:private-key ;
vc:contrastsWith ngm:password ;
vc:dependsOn ngm:cryptographic-algorithm ;
vc:dependsOn ngm:entropy-source ;
vc:enables ngm:authentication ;
vc:enables ngm:cryptographic-infrastructure ;
vc:enables ngm:data-integrity ;
vc:enables ngm:digital-signature ;
vc:enables ngm:secure-communication ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:private-key ;
vc:hasPart ngm:public-key ;
vc:hasPart ngm:symmetric-key ;
vc:implements ngm:asymmetric-cryptography ;
vc:implements ngm:symmetric-cryptography ;
vc:isPartOf ngm:cryptographic-infrastructure ;
vc:isPartOf ngm:key-management ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:key-exchange ;
vc:requires ngm:encryption ;
vc:requires ngm:key-derivation-function ;
vc:requires ngm:random-number-generation ;
vc:slug "cryptographic-key" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:ietf ;
vc:standardizedBy ngm:nist ;
vc:supports ngm:tls ;
vc:supports ngm:zero-knowledge-proof ;
vc:uses ngm:elliptic-curve-cryptography .
ngm:cryptographic-key-management a owl:Class ;
rdfs:comment "The administration of cryptographic keys throughout their lifecycle, including generation, storage, distribution, rotation, backup, recovery, and destruction, ensuring the security and availability of keying material while preventing unauthorized access or compromise."@en ;
rdfs:label "Cryptographic Key Management"@en ;
rdfs:subClassOf ngm:cryptography ;
rdfs:subClassOf _:r6243 ;
rdfs:subClassOf _:r6244 ;
rdfs:subClassOf _:r6245 ;
rdfs:subClassOf _:r6246 ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:blockchain ;
vc:contrastsWith ngm:password-management ;
vc:dependsOn ngm:cryptographic-keys ;
vc:dependsOn ngm:private-key ;
vc:enables ngm:authentication ;
vc:enables ngm:digital-signature ;
vc:enables ngm:encryption ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:key-generation ;
vc:hasPart ngm:key-revocation ;
vc:hasPart ngm:key-rotation ;
vc:implements ngm:fips-140-3 ;
vc:implements ngm:nist-sp-800-57 ;
vc:isPartOf ngm:security-architecture ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:post-quantum-cryptography ;
vc:requires ngm:cryptographic-infrastructure ;
vc:requires ngm:hardware-security-module ;
vc:requires ngm:random-number-generation ;
vc:slug "cryptographic-key-management" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:nist ;
vc:supports ngm:data-protection ;
vc:supports ngm:private-key ;
vc:supports ngm:zero-trust-architecture ;
vc:uses ngm:key-derivation-function ;
vc:uses ngm:secure-enclave .
ngm:cryptographic-key-pair a owl:Class ;
rdfs:comment "A cryptographic key pair is a mathematically linked pair of keys, a public key and a private key, used in asymmetric cryptography. The private key is kept secret by its owner while the public key may be distributed openly, and operations performed with one key can only be reversed or verified with the other. Key pairs underpin encryption to a recipient, digital signatures that prove authorship, and key agreement, making them foundational to secure communication, authentication and decentralised identity."@en ;
rdfs:label "Cryptographic Key Pair"@en ;
rdfs:subClassOf ngm:public-key-cryptography ;
rdfs:subClassOf _:r6247 ;
rdfs:subClassOf _:r6248 ;
vc:bridgesTo ngm:did-method ;
vc:dependsOn ngm:asymmetric-cryptography ;
vc:dependsOn ngm:key-management ;
vc:enables ngm:digital-signature ;
vc:enables ngm:encryption ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:private-key ;
vc:implements ngm:public-key-cryptography ;
vc:isPartOf ngm:public-key-cryptography ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:cryptography ;
vc:relatedTo ngm:encryption ;
vc:relatedTo ngm:private-key ;
vc:requires ngm:key-management ;
vc:slug "cryptographic-key-pair" ;
vc:sourceDomain "security" ;
vc:supports ngm:did-method ;
vc:supports ngm:digital-signature ;
vc:uses ngm:asymmetric-cryptography .
ngm:cryptographic-key-store a skos:Concept ;
rdfs:label "Cryptographic Key Store"@en .
ngm:cryptographic-keys a owl:Class ;
rdfs:comment "Strings of data used in cryptographic algorithms to encrypt, decrypt, sign, or verify data, serving as the secret parameters that transform plaintext to ciphertext and vice versa. Keys may be symmetric (single shared secret) or asymmetric (public-private pairs); their security depends on key length, entropy of generation, and rigorous lifecycle management."@en ;
rdfs:label "Cryptographic Keys"@en ;
rdfs:subClassOf ngm:cryptographic-primitive ;
rdfs:subClassOf ngm:cryptography ;
rdfs:subClassOf _:r6255 ;
rdfs:subClassOf _:r6256 ;
rdfs:subClassOf _:r6257 ;
rdfs:subClassOf _:r6258 ;
rdfs:subClassOf _:r6259 ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:blockchain-wallet ;
vc:bridgesTo ngm:cryptography ;
vc:contrastsWith ngm:password ;
vc:dependsOn ngm:entropy-source ;
vc:dependsOn ngm:key-derivation-function ;
vc:enables ngm:asymmetric-encryption ;
vc:enables ngm:authentication ;
vc:enables ngm:data-integrity ;
vc:enables ngm:digital-signature ;
vc:enables ngm:symmetric-encryption ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:private-key ;
vc:hasPart ngm:public-key ;
vc:hasPart ngm:session-key ;
vc:implements ngm:cryptographic-algorithm ;
vc:isPartOf ngm:cryptographic-infrastructure ;
vc:qualityScore "0.68"^^xsd:float ;
vc:relatedTo ngm:certificate-authority ;
vc:relatedTo ngm:hardware-security-module ;
vc:requires ngm:cryptographic-key-management ;
vc:requires ngm:random-number-generation ;
vc:slug "cryptographic-keys" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:fips-140-3 ;
vc:standardizedBy ngm:nist-cryptographic-standards ;
vc:supports ngm:secure-communication ;
vc:supports ngm:tls ;
vc:uses ngm:asymmetric-encryption ;
vc:uses ngm:elliptic-curve-cryptography ;
vc:uses ngm:rsa-algorithm ;
vc:uses ngm:symmetric-encryption .
ngm:cryptographic-layer a owl:Class ;
rdfs:comment "The Cryptographic Layer is the stratum that provides confidentiality, integrity, and authenticity primitives to the layers above. It sits above the Hardware Layer, which supplies entropy and acceleration, and below identity, consensus, and security strata that depend on its guarantees. It contains ciphers, hash functions, signature schemes, and key management."@en ;
rdfs:label "Cryptographic Layer"@en ;
rdfs:subClassOf ngm:infra-security-and-identity ;
rdfs:subClassOf ngm:owl-thing ;
rdfs:subClassOf _:r6260 ;
skos:broader ngm:infra-security-and-identity ;
vc:bridgesTo ngm:hash-function ;
vc:bridgesTo ngm:public-key-cryptography ;
vc:enables ngm:consensus-layer ;
vc:enables ngm:identity-layer ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:hardware-layer ;
vc:slug "cryptographic-layer" ;
vc:sourceDomain "security" .
ngm:cryptographic-library a owl:Class ;
rdfs:comment "A cryptographic library is a software package that implements cryptographic primitives and protocols — encryption, hashing, signing, key exchange, and random-number generation — behind a programming interface that application developers can use without reimplementing the underlying mathematics. Well-designed libraries such as OpenSSL, libsodium, BoringSSL, and the Rust RustCrypto suite emphasise constant-time implementations, safe defaults, and resistance to misuse. The correctness and side-channel resistance of these libraries is critical, since flaws propagate to every application that depends on them."@en ;
rdfs:label "Cryptographic Library"@en ;
rdfs:subClassOf ngm:cryptographic-protocol ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:digital-signature ;
vc:implements ngm:encryption ;
vc:implements ngm:hash-function ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:key-management ;
vc:slug "cryptographic-library" ;
vc:sourceDomain "security" ;
vc:uses ngm:public-key-cryptography .
ngm:cryptographic-oracle a skos:Concept ;
rdfs:label "Cryptographic Oracle"@en .
ngm:cryptographic-ownership a skos:Concept ;
rdfs:label "Cryptographic Ownership"@en .
ngm:cryptographic-primitive a owl:Class ;
rdfs:comment "The fundamental atomic building blocks of all cryptographic systems — including hash functions, symmetric and asymmetric ciphers, digital signatures, and key exchange protocols — each providing specific, well-defined security guarantees. Primitives are insufficient alone and must be combined in higher-level cryptographic protocols to satisfy multiple security requirements such as confidentiality, integrity, authentication, and non-repudiation. Correct selection and composition of primitives is the foundational concern of applied cryptography."@en ;
rdfs:label "Cryptographic Primitive"@en ;
rdfs:subClassOf ngm:cryptography ;
rdfs:subClassOf _:r6261 ;
rdfs:subClassOf _:r6262 ;
rdfs:subClassOf _:r6263 ;
rdfs:subClassOf _:r6264 ;
rdfs:subClassOf _:r6265 ;
rdfs:subClassOf _:r6266 ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:cryptography ;
vc:enables ngm:blockchain ;
vc:enables ngm:cryptographic-infrastructure ;
vc:enables ngm:cryptographic-protocol ;
vc:enables ngm:secure-multi-party-computation ;
vc:enables ngm:zero-knowledge-proof ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:asymmetric-encryption ;
vc:hasPart ngm:digital-signature ;
vc:hasPart ngm:hash-function ;
vc:hasPart ngm:key-derivation-function ;
vc:hasPart ngm:random-number-generation ;
vc:hasPart ngm:symmetric-encryption ;
vc:isPartOf ngm:blockchain ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:elliptic-curve-cryptography ;
vc:relatedTo ngm:homomorphic-encryption ;
vc:relatedTo ngm:key-management ;
vc:relatedTo ngm:merkle-tree ;
vc:relatedTo ngm:post-quantum-cryptography ;
vc:relatedTo ngm:proof-of-work ;
vc:slug "cryptographic-primitive" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:cryptographic-protocol .
ngm:cryptographic-privacy-activist a owl:Class ;
rdfs:comment "A cypherpunk is an activist who advocates for the widespread use of strong cryptography and privacy-enhancing technologies as tools for social and political change. Emerging from mailing list culture in the early 1990s, cypherpunks believe that individual privacy can only be guaranteed through cryptographic means rather than through legal or institutional protections. Their ethos—'cypherpunks write code'—produced foundational technologies including public-key cryptography applications, anonymous remailers, digital cash, and the conceptual groundwork for Bitcoin and decentralised systems."@en ;
rdfs:label "Cryptographic Privacy Activist"@en ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
rdfs:subClassOf _:r6267 ;
rdfs:subClassOf _:r6268 ;
skos:broader ngm:bc-governance-and-regulation ;
vc:contrastsWith ngm:digital-society-surveillance ;
vc:enables ngm:decentralization ;
vc:enables ngm:digital-signature ;
vc:enables ngm:peer-to-peer-network ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.7"^^xsd:float ;
vc:relatedTo ngm:data-protection ;
vc:relatedTo ngm:digital-rights ;
vc:relatedTo ngm:open-source-software ;
vc:requires ngm:cryptographic-protocol ;
vc:requires ngm:cryptography ;
vc:slug "cryptographic-privacy-activist" ;
vc:sourceDomain "blockchain" .
ngm:cryptographic-proof a owl:Class ;
rdfs:comment "A cryptographic proof is a mathematical construction that enables one party to demonstrate the truth of a statement or possession of secret knowledge to a verifying party in a computationally sound and tamper-evident manner, without necessarily revealing the underlying information itself. Rooted in complexity theory and interactive proof systems, cryptographic proofs provide infeasibility guarantees: a computationally bounded adversary cannot forge a valid proof for a false statement. The field spans classical constructions such as hash-based commitments and digital signatures, through to advanced non-interactive arguments including zk-SNARKs and STARKs, and underpins security across blockchain, identity, and privacy-preserving computation domains."@en ;
rdfs:label "Cryptographic Proof"@en ;
rdfs:subClassOf ngm:cryptography ;
rdfs:subClassOf _:r6271 ;
rdfs:subClassOf _:r6272 ;
rdfs:subClassOf _:r6273 ;
rdfs:subClassOf _:r6274 ;
rdfs:subClassOf _:r6275 ;
rdfs:subClassOf _:r6276 ;
rdfs:subClassOf _:r6277 ;
vc:bridgesTo ngm:ai-model-attestation ;
vc:bridgesTo ngm:decentralised-identity ;
vc:bridgesTo ngm:verifiable-credential-vc ;
vc:contrastsWith ngm:multi-party-computation ;
vc:contrastsWith ngm:tee ;
vc:enables ngm:digital-identity ;
vc:enables ngm:privacy-preserving-blockchain ;
vc:enables ngm:proof-of-stake ;
vc:enables ngm:proof-of-work ;
vc:enables ngm:verifiable-computation ;
vc:enables ngm:zk-rollup ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:commitment-scheme ;
vc:hasPart ngm:interactive-proof-system ;
vc:hasPart ngm:non-interactive-proof ;
vc:hasPart ngm:zero-knowledge-proof ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:blockchain-protocol ;
vc:relatedTo ngm:consensus-mechanism ;
vc:relatedTo ngm:homomorphic-encryption ;
vc:relatedTo ngm:secure-multi-party-computation ;
vc:requires ngm:elliptic-curve-cryptography ;
vc:requires ngm:hash-function ;
vc:requires ngm:public-key-cryptography ;
vc:slug "cryptographic-proof" ;
vc:sourceDomain "security" ;
vc:supports ngm:authentication ;
vc:supports ngm:data-integrity ;
vc:supports ngm:non-repudiation ;
vc:supports ngm:verification ;
vc:uses ngm:digital-signature ;
vc:uses ngm:elliptic-curve-cryptography ;
vc:uses ngm:merkle-tree .
ngm:cryptographic-proof-system a owl:Class ;
rdfs:comment "A cryptographic proof system is a formal protocol allowing one party (a prover) to convince another party (a verifier) of the truth of a statement without revealing any information beyond the validity of that statement. These systems provide mathematical guarantees of soundness, completeness, and, in zero-knowledge variants, zero information leakage."@en ;
rdfs:label "Cryptographic Proof System"@en ;
rdfs:subClassOf ngm:cryptographic-protocol ;
rdfs:subClassOf _:r6269 ;
rdfs:subClassOf _:r6270 ;
vc:enables ngm:authentication ;
vc:enables ngm:cryptographic-proofs ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:commitment-scheme ;
vc:hasPart ngm:zero-knowledge-proof ;
vc:qualityScore "0.8"^^xsd:float ;
vc:slug "cryptographic-proof-system" ;
vc:sourceDomain "security" ;
vc:uses ngm:cryptographic-hash-function ;
vc:uses ngm:zk-snarks ;
vc:uses ngm:zk-starks .
ngm:cryptographic-proofs a owl:Class ;
rdfs:comment "Cryptographic proofs are mathematical constructions that allow one party to convince another of the truth of a statement with cryptographic certainty, often without revealing the underlying data. They include proofs of knowledge, membership proofs, proofs of computation, and zero-knowledge proofs, and rely on primitives such as hash functions, commitments, and elliptic-curve operations. Cryptographic proofs underpin blockchain validity, verifiable computation, privacy-preserving authentication, and data-availability guarantees, letting verifiers trust outcomes they did not themselves compute."@en ;
rdfs:label "Cryptographic Proofs"@en ;
rdfs:subClassOf ngm:cryptographic-primitive ;
rdfs:subClassOf _:r6278 ;
rdfs:subClassOf _:r6279 ;
rdfs:subClassOf _:r6280 ;
rdfs:subClassOf _:r6281 ;
rdfs:subClassOf _:r6282 ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:contrastsWith ngm:fraud-proof ;
vc:contrastsWith ngm:interactive-proof ;
vc:enables ngm:data-availability ;
vc:enables ngm:privacy-preserving-authentication ;
vc:enables ngm:trust-minimisation ;
vc:enables ngm:verifiable-computation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:merkle-proof ;
vc:hasPart ngm:zk-snark ;
vc:hasPart ngm:zk-starks ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:cryptographic-accumulator ;
vc:relatedTo ngm:digital-signature ;
vc:relatedTo ngm:erasure-coding ;
vc:relatedTo ngm:merkle-tree ;
vc:requires ngm:computational-hardness-assumption ;
vc:requires ngm:trusted-setup ;
vc:slug "cryptographic-proofs" ;
vc:sourceDomain "security" ;
vc:supports ngm:blockchain ;
vc:supports ngm:certificate-transparency ;
vc:supports ngm:rollup ;
vc:uses ngm:commitment-scheme ;
vc:uses ngm:cryptographic-infrastructure ;
vc:uses ngm:elliptic-curve-cryptography ;
vc:uses ngm:hash-function ;
vc:uses ngm:zero-knowledge-proof .
ngm:cryptographic-protocol a owl:Class ;
rdfs:comment "Cryptographic Protocol encompasses mathematical frameworks and algorithmic procedures that secure digital systems through cryptographic primitives including hash functions, digital signatures, encryption schemes, zero-knowledge proofs, and commitment protocols, enabling confidentiality, integrity, authentication, and non-repudiation across distributed and blockchain applications."@en ;
rdfs:label "Cryptographic Protocol"@en ;
rdfs:subClassOf ngm:cryptography ;
rdfs:subClassOf _:r6283 ;
rdfs:subClassOf _:r6284 ;
rdfs:subClassOf _:r6285 ;
rdfs:subClassOf _:r6286 ;
rdfs:subClassOf _:r6287 ;
rdfs:subClassOf _:r6288 ;
rdfs:subClassOf _:r6289 ;
rdfs:subClassOf _:r6290 ;
vc:bridgesTo ngm:multi-party-computation ;
vc:bridgesTo ngm:post-quantum-cryptography ;
vc:bridgesTo ngm:quantum-computation-paradigm ;
vc:contrastsWith ngm:post-quantum-cryptography ;
vc:dependsOn ngm:computational-hardness-assumption ;
vc:dependsOn ngm:elliptic-curve-cryptography ;
vc:enables ngm:blockchain-security ;
vc:enables ngm:consensus-protocol ;
vc:enables ngm:privacy-preservation ;
vc:enables ngm:secure-communication ;
vc:enables ngm:zero-knowledge-proof ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:authentication-protocol ;
vc:hasPart ngm:commitment-scheme ;
vc:hasPart ngm:key-exchange ;
vc:implements ngm:security-framework ;
vc:implements ngm:trust-model ;
vc:isPartOf ngm:cryptography ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:blockchain ;
vc:relatedTo ngm:digital-infrastructure ;
vc:requires ngm:cryptographic-infrastructure ;
vc:requires ngm:digital-signature ;
vc:requires ngm:encryption-scheme ;
vc:requires ngm:hash-function ;
vc:requires ngm:random-number-generator ;
vc:slug "cryptographic-protocol" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:nist-post-quantum-cryptography ;
vc:standardizedBy ngm:post-quantum-cryptography ;
vc:supports ngm:digital-asset ;
vc:supports ngm:smart-contract ;
vc:uses ngm:ecdsa ;
vc:uses ngm:ed-dsa ;
vc:uses ngm:hmac ;
vc:uses ngm:schnorr-signature .
ngm:cryptographic-protocols a owl:Class ;
rdfs:comment "Cryptographic protocols are sequences of operations using cryptographic primitives to achieve security goals such as confidentiality, integrity and authentication."@en ;
rdfs:label "Cryptographic Protocols"@en ;
rdfs:subClassOf ngm:cryptography ;
rdfs:subClassOf _:r6291 ;
rdfs:subClassOf _:r6292 ;
rdfs:subClassOf _:r6293 ;
rdfs:subClassOf _:r6294 ;
rdfs:subClassOf _:r6295 ;
rdfs:subClassOf _:r6296 ;
rdfs:subClassOf _:r6297 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:distributed-systems ;
vc:bridgesTo ngm:network-security ;
vc:contrastsWith ngm:obfuscation ;
vc:enables ngm:authentication ;
vc:enables ngm:kerberos ;
vc:enables ngm:key-exchange ;
vc:enables ngm:non-repudiation ;
vc:enables ngm:secure-communication ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:diffie-hellman-key-exchange ;
vc:hasPart ngm:ipsec ;
vc:hasPart ngm:tls ;
vc:implements ngm:message-authentication-code ;
vc:implements ngm:zero-knowledge-proof ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:formal-verification ;
vc:relatedTo ngm:post-quantum-cryptography ;
vc:requires ngm:cryptographic-hash-function ;
vc:requires ngm:cryptographic-infrastructure ;
vc:requires ngm:digital-signatures ;
vc:requires ngm:encryption ;
vc:slug "cryptographic-protocols" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:ietf ;
vc:standardizedBy ngm:nist ;
vc:supports ngm:data-integrity ;
vc:supports ngm:network-security ;
vc:uses ngm:asymmetric-cryptography ;
vc:uses ngm:symmetric-encryption .
ngm:cryptographic-security a owl:Class ;
rdfs:comment "Cryptographic Security is the discipline of applying mathematical cryptographic primitives and protocols — including symmetric encryption, asymmetric public-key cryptography, cryptographic hash functions, digital signatures, message authentication codes, and zero-knowledge proofs — to enforce confidentiality, integrity, authenticity, and non-repudiation of information and communications. It provides the formal security guarantees upon which trustless distributed systems, secure channels, identity frameworks, and privacy-preserving computation are constructed. The field spans both theoretical hardness assumptions (discrete logarithm, integer factorisation, lattice problems) and practical protocol engineering, encompassing key management, certificate infrastructure, and post-quantum cryptographic migration. In applied contexts it underpins everything from TLS transport security and blockchain transaction authorisation to hardware security modules and secure multi-party computation."@en ;
rdfs:label "Cryptographic Security"@en ;
rdfs:subClassOf ngm:infra-security-and-identity ;
rdfs:subClassOf _:r6298 ;
rdfs:subClassOf _:r6299 ;
rdfs:subClassOf _:r6300 ;
rdfs:subClassOf _:r6301 ;
rdfs:subClassOf _:r6302 ;
rdfs:subClassOf _:r6303 ;
rdfs:subClassOf _:r6304 ;
rdfs:subClassOf _:r6305 ;
rdfs:subClassOf _:r6306 ;
skos:broader ngm:infra-security-and-identity ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:decentralised-identity ;
vc:bridgesTo ngm:federated-learning ;
vc:contrastsWith ngm:post-quantum-cryptography ;
vc:enables ngm:digital-identity ;
vc:enables ngm:privacy-preserving-computation ;
vc:enables ngm:secure-multi-party-computation ;
vc:enables ngm:zero-knowledge-proof ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:digital-signature ;
vc:hasPart ngm:encryption ;
vc:hasPart ngm:hash-function ;
vc:hasPart ngm:key-management ;
vc:hasPart ngm:message-authentication-code ;
vc:hasPart ngm:public-key-cryptography ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:access-control ;
vc:relatedTo ngm:network-security ;
vc:relatedTo ngm:threat-model ;
vc:requires ngm:cryptographic-infrastructure ;
vc:requires ngm:hardware-security-module ;
vc:requires ngm:random-number-generation ;
vc:slug "cryptographic-security" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:ietf ;
vc:standardizedBy ngm:iso-iec ;
vc:standardizedBy ngm:nist ;
vc:supports ngm:blockchain ;
vc:supports ngm:decentralised-application ;
vc:supports ngm:privacy-framework ;
vc:supports ngm:tls .
ngm:cryptographic-signature a owl:Class ;
rdfs:comment "A cryptographic signature is a mathematical scheme that allows a private-key holder to produce an unforgeable, publicly-verifiable proof that a specific message or data item was authorised by them, delivering both authenticity and non-repudiation. The signing algorithm combines a cryptographic hash of the message with the signer's private key to produce a compact signature value; any party holding the corresponding public key can verify the signature without accessing the private key. Dominant schemes include ECDSA (Bitcoin, Ethereum), Ed25519 (Solana, Cosmos, OpenSSH), RSA-PSS (TLS, S/MIME), and Schnorr (BIP-340). Cryptographic signatures are a foundational primitive underpinning transaction authorisation, code signing, verifiable credentials, and authenticated key exchange across virtually all secure digital infrastructure."@en ;
rdfs:label "Cryptographic Signature"@en ;
rdfs:subClassOf ngm:asymmetric-cryptography ;
rdfs:subClassOf _:r6307 ;
rdfs:subClassOf _:r6308 ;
vc:bridgesTo ngm:provenance ;
vc:bridgesTo ngm:self-sovereign-identity ;
vc:bridgesTo ngm:supply-chain-traceability ;
vc:contrastsWith ngm:message-authentication-code ;
vc:contrastsWith ngm:symmetric-encryption ;
vc:enables ngm:blockchain ;
vc:enables ngm:code-signing ;
vc:enables ngm:decentralised-identity ;
vc:enables ngm:non-repudiation ;
vc:enables ngm:smart-contract ;
vc:enables ngm:verifiable-credential-vc ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:ecdsa ;
vc:implements ngm:ed25519 ;
vc:implements ngm:rsa-pss ;
vc:implements ngm:schnorr-signature ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:blind-signatures ;
vc:relatedTo ngm:multi-signature ;
vc:relatedTo ngm:post-quantum-cryptography ;
vc:relatedTo ngm:threshold-signature-scheme ;
vc:requires ngm:cryptographic-infrastructure ;
vc:requires ngm:key-management ;
vc:slug "cryptographic-signature" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:ietf ;
vc:standardizedBy ngm:nist ;
vc:standardizedBy ngm:nist-fips-186 ;
vc:supports ngm:secure-email ;
vc:supports ngm:tls ;
vc:supports ngm:zero-knowledge-proof ;
vc:uses ngm:elliptic-curve-cryptography ;
vc:uses ngm:hash-function ;
vc:uses ngm:private-key ;
vc:uses ngm:public-key ;
vc:uses ngm:public-key-cryptography .
ngm:cryptographic-signatures a skos:Concept ;
rdfs:label "Cryptographic Signatures"@en .
ngm:cryptographic-signing a owl:Class ;
rdfs:comment "Cryptographic signing is the process of producing a verifiable proof of authorship and integrity over a message or document using a private key, such that anyone holding the corresponding public key can confirm the signature without being able to forge it. It underpins authentication, non-repudiation, software-supply-chain integrity, and blockchain transaction authorisation. Signing schemes include RSA, ECDSA, EdDSA, and Schnorr, each defining how a hash of the message is transformed under the signer's secret key into a compact, publicly verifiable signature."@en ;
rdfs:label "Cryptographic Signing"@en ;
rdfs:subClassOf ngm:cryptographic-primitive ;
vc:enables ngm:key-management ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:cryptographic-protocol ;
vc:slug "cryptographic-signing" ;
vc:sourceDomain "security" ;
vc:uses ngm:digital-signature ;
vc:uses ngm:hash-function ;
vc:uses ngm:public-key-cryptography .
ngm:cryptographic-sortition a owl:Class ;
rdfs:comment "Cryptographic sortition is a technique for randomly and unpredictably selecting a subset of participants from a larger population to perform a role such as block proposal or committee membership, using a verifiable random function so the outcome cannot be predicted or manipulated in advance. Each participant can privately determine whether they were selected and prove it to others without revealing information that would let an adversary target them beforehand. It underpins consensus protocols such as Algorand's, allowing large validator populations to reach agreement with low communication overhead and strong resistance to targeted attacks."@en ;
rdfs:label "Cryptographic Sortition"@en ;
rdfs:subClassOf ngm:consensus-mechanism ;
rdfs:subClassOf _:r6309 ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:consensus-mechanism ;
vc:slug "cryptographic-sortition" ;
vc:sourceDomain "blockchain" .
ngm:cryptographic-standard a skos:Concept ;
rdfs:label "Cryptographic Standard"@en .
ngm:cryptographic-standards a skos:Concept ;
rdfs:label "Cryptographic Standards"@en .
ngm:cryptographic-suites a skos:Concept ;
rdfs:label "Cryptographic Suites"@en .
ngm:cryptographic-system a owl:Class ;
rdfs:comment "An integrated framework of mathematical algorithms, protocols, and mechanisms designed to provide information security properties including confidentiality, integrity, authentication, and non-repudiation in adversarial environments. Blockchain cryptographic systems enable trustless operation through mathematical guarantees rather than trusted intermediaries."@en ;
rdfs:label "Cryptographic System"@en ;
rdfs:subClassOf ngm:blockchain-entity ;
rdfs:subClassOf ngm:cryptographic-primitive ;
rdfs:subClassOf _:r6310 ;
rdfs:subClassOf _:r6311 ;
rdfs:subClassOf _:r6312 ;
rdfs:subClassOf _:r6313 ;
rdfs:subClassOf _:r6314 ;
vc:bridgesTo ngm:ai-agent-system ;
vc:enables ngm:blockchain-network ;
vc:enables ngm:cryptographic-verification ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:cryptographic-hash-function ;
vc:hasPart ngm:digital-signature ;
vc:hasPart ngm:encryption ;
vc:hasPart ngm:public-key-cryptography ;
vc:hasPart ngm:zero-knowledge-proof ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:cryptographic-key-management ;
vc:relatedTo ngm:cryptographic-protocol ;
vc:relatedTo ngm:cryptographic-security ;
vc:relatedTo ngm:merkle-tree ;
vc:relatedTo ngm:post-quantum-cryptography ;
vc:slug "cryptographic-system" ;
vc:sourceDomain "blockchain" .
ngm:cryptographic-systems a skos:Concept ;
rdfs:label "Cryptographic Systems"@en .
ngm:cryptographic-token a skos:Concept ;
rdfs:label "Cryptographic Token"@en .
ngm:cryptographic-verification a owl:Class ;
rdfs:comment "Cryptographic Verification is the process of using cryptographic primitives—such as digital signatures, hash functions, and zero-knowledge proofs—to confirm the authenticity, integrity, and non-repudiation of data, identities, or transactions. It forms the trust foundation for blockchain systems, content authentication, and decentralised identity schemes."@en ;
rdfs:label "Cryptographic Verification"@en ;
rdfs:subClassOf ngm:infra-security-and-identity ;
rdfs:subClassOf _:r6315 ;
skos:broader ngm:infra-security-and-identity ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:cryptographic-system ;
vc:bridgesTo ngm:smart-contract ;
vc:bridgesTo ngm:verifiable-credential-vc ;
vc:contrastsWith ngm:password-authentication ;
vc:enables ngm:blockchain ;
vc:enables ngm:content-authentication ;
vc:enables ngm:decentralised-identity ;
vc:enables ngm:non-repudiation ;
vc:enables ngm:tee ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:certificate-authority ;
vc:implements ngm:message-authentication-code ;
vc:implements ngm:zero-knowledge-proof ;
vc:qualityScore "0.68"^^xsd:float ;
vc:relatedTo ngm:consensus-mechanism ;
vc:relatedTo ngm:tls ;
vc:relatedTo ngm:zero-knowledge-proof ;
vc:requires ngm:cryptographic-key-management ;
vc:slug "cryptographic-verification" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:nist-cryptographic-standards ;
vc:standardizedBy ngm:x-509-certificate ;
vc:supports ngm:data-integrity ;
vc:supports ngm:identity-verification ;
vc:supports ngm:supply-chain-provenance ;
vc:uses ngm:cryptographic-hash-function ;
vc:uses ngm:cryptographic-infrastructure ;
vc:uses ngm:digital-signature ;
vc:uses ngm:merkle-tree ;
vc:uses ngm:public-key-cryptography .
ngm:cryptographic-vote-aggregation a skos:Concept ;
rdfs:label "Cryptographic Vote Aggregation"@en .
ngm:cryptography a owl:Class ;
rdfs:comment "Cryptography is the mathematical science of transforming information through encryption and related primitives, ensuring confidentiality, authenticity, and integrity in digital communications, blockchain systems, and distributed networks."@en ;
rdfs:label "Cryptography"@en ;
rdfs:subClassOf ngm:cryptographic-security ;
rdfs:subClassOf ngm:security ;
rdfs:subClassOf _:r6337 ;
rdfs:subClassOf _:r6338 ;
rdfs:subClassOf _:r6339 ;
rdfs:subClassOf _:r6340 ;
rdfs:subClassOf _:r6341 ;
rdfs:subClassOf _:r6342 ;
rdfs:subClassOf _:r6343 ;
rdfs:subClassOf _:r6344 ;
rdfs:subClassOf _:r6345 ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:bridgesTo ngm:post-quantum-cryptography ;
vc:bridgesTo ngm:quantum-computation-paradigm ;
vc:contrastsWith ngm:steganography ;
vc:dependsOn ngm:computational-complexity-theory ;
vc:dependsOn ngm:number-theory ;
vc:enables ngm:authentication ;
vc:enables ngm:consensus-protocol ;
vc:enables ngm:cryptographic-protocol ;
vc:enables ngm:digital-asset ;
vc:enables ngm:secure-communication ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:asymmetric-encryption ;
vc:hasPart ngm:digital-signature ;
vc:hasPart ngm:hash-function ;
vc:hasPart ngm:symmetric-encryption ;
vc:hasPart ngm:zero-knowledge-proof ;
vc:implements ngm:blockchain ;
vc:implements ngm:cryptographic-infrastructure ;
vc:isPartOf ngm:digital-infrastructure ;
vc:isPartOf ngm:security ;
vc:qualityScore "0.7"^^xsd:float ;
vc:relatedTo ngm:homomorphic-encryption ;
vc:relatedTo ngm:multi-party-computation ;
vc:relatedTo ngm:threshold-cryptography ;
vc:requires ngm:digital-signature ;
vc:requires ngm:encryption-scheme ;
vc:requires ngm:hash-function ;
vc:requires ngm:key-management ;
vc:slug "cryptography" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:iso-iec ;
vc:standardizedBy ngm:nist ;
vc:supports ngm:access-control ;
vc:supports ngm:data-privacy ;
vc:supports ngm:digital-identity .
ngm:cryptography-domain a skos:Concept ;
rdfs:label "Cryptography Domain"@en .
ngm:cryptography-security-and-privacy a owl:Class ;
rdfs:comment "Cryptography Security and Privacy denotes the cross-disciplinary infrastructure layer combining mathematical primitives (symmetric encryption AES-GCM/ChaCha20-Poly1305/ASCON-128 NIST lightweight finalist February 2023, hash functions SHA-2/SHA-3 Keccak/BLAKE3 throughput 6.8 GB/s single-thread, pa..."@en ;
rdfs:label "Cryptography Security and Privacy"@en ;
rdfs:subClassOf ngm:applied-mathematics ;
rdfs:subClassOf ngm:computer-science ;
rdfs:subClassOf ngm:information-security ;
rdfs:subClassOf ngm:infra-security-and-identity ;
rdfs:subClassOf ngm:privacy-engineering ;
rdfs:subClassOf ngm:trusted-computing ;
rdfs:subClassOf _:r6316 ;
rdfs:subClassOf _:r6317 ;
rdfs:subClassOf _:r6318 ;
rdfs:subClassOf _:r6319 ;
rdfs:subClassOf _:r6320 ;
rdfs:subClassOf _:r6321 ;
rdfs:subClassOf _:r6322 ;
rdfs:subClassOf _:r6323 ;
rdfs:subClassOf _:r6324 ;
rdfs:subClassOf _:r6325 ;
rdfs:subClassOf _:r6326 ;
rdfs:subClassOf _:r6327 ;
rdfs:subClassOf _:r6328 ;
rdfs:subClassOf _:r6329 ;
rdfs:subClassOf _:r6330 ;
rdfs:subClassOf _:r6331 ;
rdfs:subClassOf _:r6332 ;
rdfs:subClassOf _:r6333 ;
rdfs:subClassOf _:r6334 ;
rdfs:subClassOf _:r6335 ;
rdfs:subClassOf _:r6336 ;
skos:broader ngm:infra-security-and-identity ;
vc:bridgesTo ngm:privacy-engineering ;
vc:contrastsWith ngm:classical-surveillance-systems ;
vc:contrastsWith ngm:obfuscation-only-defence ;
vc:contrastsWith ngm:plaintext-communication ;
vc:contrastsWith ngm:security-through-obscurity ;
vc:contrastsWith ngm:unauthenticated-systems ;
vc:dependsOn ngm:computational-complexity-theory ;
vc:dependsOn ngm:elliptic-curve-theory ;
vc:dependsOn ngm:hardware-security ;
vc:dependsOn ngm:information-theory ;
vc:dependsOn ngm:lattice-cryptography ;
vc:dependsOn ngm:number-theory ;
vc:dependsOn ngm:quantum-computing-threat-model ;
vc:enables ngm:anonymous-communication ;
vc:enables ngm:authentication ;
vc:enables ngm:confidential-computing ;
vc:enables ngm:data-confidentiality ;
vc:enables ngm:data-integrity ;
vc:enables ngm:end-to-end-encryption ;
vc:enables ngm:non-repudiation ;
vc:enables ngm:privacy-preserving-computation ;
vc:enables ngm:verifiable-computation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:differential-privacy ;
vc:hasPart ngm:digital-signature ;
vc:hasPart ngm:hash-function ;
vc:hasPart ngm:homomorphic-encryption ;
vc:hasPart ngm:key-derivation-function ;
vc:hasPart ngm:key-exchange ;
vc:hasPart ngm:message-authentication-code ;
vc:hasPart ngm:post-quantum-cryptography ;
vc:hasPart ngm:public-key-cryptography ;
vc:hasPart ngm:random-number-generation ;
vc:hasPart ngm:secure-multi-party-computation ;
vc:hasPart ngm:symmetric-encryption ;
vc:hasPart ngm:tee ;
vc:hasPart ngm:zero-knowledge-proof ;
vc:implements ngm:aes-gcm ;
vc:implements ngm:argon2 ;
vc:implements ngm:blake3 ;
vc:implements ngm:cha-cha20-poly1305 ;
vc:implements ngm:ed25519 ;
vc:implements ngm:ml-dsa ;
vc:implements ngm:ml-kem ;
vc:implements ngm:nist-fips-205-slh-dsa-sphincs ;
vc:implements ngm:schnorr-signature ;
vc:implements ngm:schnorr-signatures ;
vc:implements ngm:sha-3 ;
vc:implements ngm:signal-protocol ;
vc:implements ngm:tls-1-3 ;
vc:implements ngm:x25519 ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:cybersecurity ;
vc:relatedTo ngm:digital-forensics ;
vc:relatedTo ngm:formal-verification ;
vc:relatedTo ngm:quantum-cryptography ;
vc:relatedTo ngm:side-channel-attack ;
vc:relatedTo ngm:steganography ;
vc:relatedTo ngm:threat-modelling ;
vc:requires ngm:computational-hardness-assumption ;
vc:requires ngm:cryptographic-library ;
vc:requires ngm:entropy-source ;
vc:requires ngm:key-management ;
vc:requires ngm:mathematical-foundations ;
vc:requires ngm:random-oracle-model ;
vc:requires ngm:standards-compliance ;
vc:slug "cryptography-security-and-privacy" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:anssi-france ;
vc:standardizedBy ngm:bsi-germany ;
vc:standardizedBy ngm:etsi-quantum-safe-cryptography ;
vc:standardizedBy ngm:fips-140-3 ;
vc:standardizedBy ngm:ietf-cfrg ;
vc:standardizedBy ngm:irtf ;
vc:standardizedBy ngm:iso-iec-jtc-1-sc-27 ;
vc:standardizedBy ngm:ncsc ;
vc:standardizedBy ngm:nist ;
vc:supports ngm:blockchain ;
vc:supports ngm:confidential-ai ;
vc:supports ngm:de-fi ;
vc:supports ngm:decentralised-web ;
vc:supports ngm:digital-identity ;
vc:supports ngm:privacy-preserving-machine-learning ;
vc:supports ngm:secure-messaging ;
vc:supports ngm:zero-trust-architecture ;
vc:uses ngm:constant-time-programming ;
vc:uses ngm:finite-field-arithmetic ;
vc:uses ngm:hardware-security-module ;
vc:uses ngm:modular-arithmetic ;
vc:uses ngm:polynomial-commitments ;
vc:uses ngm:secure-enclave .
ngm:cryptonote-protocol a skos:Concept ;
rdfs:label "Cryptonote Protocol"@en .
ngm:cryptopunks a skos:Concept ;
rdfs:label "Cryptopunks"@en .
ngm:cryptoquant a skos:Concept ;
rdfs:label "Cryptoquant"@en .
ngm:crystallography a skos:Concept ;
rdfs:label "Crystallography"@en .
ngm:csam-detection a skos:Concept ;
rdfs:label "Csam Detection"@en .
ngm:csat-improvement a skos:Concept ;
rdfs:label "Csat Improvement"@en .
ngm:csddd a skos:Concept ;
rdfs:label "Csddd"@en .
ngm:csma-ca a skos:Concept ;
rdfs:label "Csma Ca"@en .
ngm:csrd-compliance a owl:Class ;
rdfs:comment "CSRD compliance is the practice of meeting the reporting obligations of the European Union's Corporate Sustainability Reporting Directive, which mandates standardised disclosure of environmental, social and governance impacts. It requires in-scope companies to report under the European Sustainability Reporting Standards (ESRS), including double-materiality assessments and audited climate and carbon metrics. Compliance underpins demonstrable carbon accounting for sectors such as energy-intensive computing and blockchain."@en ;
rdfs:label "CSRD Compliance"@en ;
rdfs:subClassOf ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:carbon-footprint-measurement ;
vc:relatedTo ngm:carbon-neutral-blockchain ;
vc:slug "csrd-compliance" ;
vc:sourceDomain "governance" .
ngm:csrd-directive-2022-2464 a skos:Concept ;
rdfs:label "Csrd Directive 2022 2464"@en .
ngm:css a owl:Class ;
rdfs:comment "Cascading Style Sheets (CSS) is the standard language for describing the presentation of documents written in markup languages such as HTML, controlling layout, colour, typography and responsive behaviour. It separates content from presentation, with rules that cascade and inherit according to specificity and source order. Maintained as a family of W3C specifications, CSS is a foundational web technology alongside HTML and JavaScript."@en ;
rdfs:label "Css"@en ;
rdfs:subClassOf ngm:web-standard ;
rdfs:subClassOf _:r6346 ;
rdfs:subClassOf _:r6347 ;
vc:bridgesTo ngm:semantic-web-linked-data-standard ;
vc:contrastsWith ngm:html ;
vc:enables ngm:accessibility ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:accessibility ;
vc:isPartOf ngm:web-standard ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:accessibility ;
vc:relatedTo ngm:html ;
vc:relatedTo ngm:semantic-web-linked-data-standard ;
vc:relatedTo ngm:web-standard ;
vc:requires ngm:html ;
vc:slug "css" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:w3-c ;
vc:standardizedBy ngm:web-standard ;
vc:supports ngm:web-standard ;
vc:uses ngm:html .
ngm:css-community-solid-server a skos:Concept ;
rdfs:label "Css Community Solid Server"@en .
ngm:css-selectors a skos:Concept ;
rdfs:label "Css Selectors"@en .
ngm:ctoken a skos:Concept ;
rdfs:label "Ctoken"@en .
ngm:cubesat a owl:Class ;
rdfs:comment "A CubeSat is a [[Small Satellite|small-satellite]] form factor built around standardised units, written as **U**. Under the CubeSat Design Specification Revision 14.1, a 1U spacecraft is based on a ten-centimetre cube and may have a mass up to two kilograms; larger configurations combine units into forms such as 2U, 3U, 6U or 12U.[^1] The standardised spacecraft-to-deployer interface is the defining feature. CubeSat is therefore not a synonym for every nanosatellite."@en ;
rdfs:label "CubeSat"@en ;
rdfs:subClassOf ngm:small-satellite ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:space-systems-engineering ;
vc:slug "cubesat" ;
vc:sourceDomain "space-science-and-systems" .
ngm:cubic-splines a skos:Concept ;
rdfs:label "Cubic Splines"@en .
ngm:cublas a skos:Concept ;
rdfs:label "Cublas"@en .
ngm:cuda a owl:Class ;
rdfs:comment "CUDA (Compute Unified Device Architecture) is NVIDIA's proprietary parallel computing platform and programming model that exposes GPU hardware through a C/C++ extension, enabling thousands of threads to execute concurrently across thousands of GPU cores via a three-level hierarchy of grids, blocks, and warps. It provides a unified memory model spanning host (CPU) and device (GPU) address spaces, complemented by curated libraries such as cuBLAS, cuDNN, and NCCL that deliver optimised primitives for linear algebra, deep neural network operations, and multi-GPU communication. Originally released in 2006, CUDA has become the de facto execution substrate for production deep learning training and inference, underpinning frameworks such as PyTorch and TensorFlow, and is the primary determinant of GPU vendor lock-in in the AI infrastructure stack."@en ;
rdfs:label "CUDA"@en ;
rdfs:subClassOf ngm:parallel-computing ;
rdfs:subClassOf _:r3807 ;
rdfs:subClassOf _:r3808 ;
rdfs:subClassOf _:r3809 ;
vc:bridgesTo ngm:gpu-rendering ;
vc:bridgesTo ngm:high-performance-computing ;
vc:contrastsWith ngm:metal-compute ;
vc:contrastsWith ngm:oneapi ;
vc:contrastsWith ngm:opencl ;
vc:contrastsWith ngm:rocm ;
vc:enables ngm:deep-learning ;
vc:enables ngm:inference ;
vc:enables ngm:mixed-precision-training ;
vc:enables ngm:scientific-computing ;
vc:enables ngm:training ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:cublas ;
vc:hasPart ngm:cudnn ;
vc:hasPart ngm:nccl ;
vc:hasPart ngm:tensor-core ;
vc:isPartOf ngm:ai-infrastructure ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:memory-bandwidth ;
vc:relatedTo ngm:py-torch ;
vc:relatedTo ngm:python-pytorch-deep-learning-stack ;
vc:relatedTo ngm:tensor-flow ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:nvidia-gpu ;
vc:slug "cuda" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:computer-vision ;
vc:supports ngm:large-language-model ;
vc:supports ngm:machine-learning-discipline-framework ;
vc:supports ngm:neural-network ;
vc:uses ngm:shared-memory ;
vc:uses ngm:simt-execution .
ngm:cuda-gpu a skos:Concept ;
rdfs:label "Cuda Gpu"@en .
ngm:cuda-programming-model a skos:Concept ;
rdfs:label "Cuda Programming Model"@en .
ngm:cudnn a skos:Concept ;
rdfs:label "Cudnn"@en .
ngm:cultural-context a skos:Concept ;
rdfs:label "Cultural Context"@en .
ngm:cultural-database a skos:Concept ;
rdfs:label "Cultural Database"@en .
ngm:cultural-education a skos:Concept ;
rdfs:label "Cultural Education"@en .
ngm:cultural-exhibit a skos:Concept ;
rdfs:label "Cultural Exhibit"@en .
ngm:cultural-experience-categorization a skos:Concept ;
rdfs:label "Cultural Experience Categorization"@en .
ngm:cultural-expression-system a skos:Concept ;
rdfs:label "Cultural Expression System"@en .
ngm:cultural-festival a skos:Concept ;
rdfs:label "Cultural Festival"@en .
ngm:cultural-heritage a owl:Class ;
rdfs:comment "The legacy of tangible artefacts (monuments, buildings, artworks, archives) and intangible attributes (language, performance, craft, ritual) inherited from past generations, maintained in the present, and safeguarded for future ones. In digital ecosystems, cultural heritage is increasingly captured, preserved, and re-presented through 3D scanning, digital twins, and immersive experiences, making it a foundational content domain for virtual tourism and the creative industries."@en ;
rdfs:label "Cultural Heritage"@en ;
rdfs:subClassOf ngm:creative-industries ;
vc:dependsOn ngm:digital-preservation ;
vc:enables ngm:education ;
vc:enables ngm:virtual-tourism ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:digital-objects ;
vc:relatedTo ngm:digital-twin ;
vc:relatedTo ngm:immersive-experience ;
vc:slug "cultural-heritage" ;
vc:sourceDomain "metaverse" .
ngm:cultural-heritage-access a skos:Concept ;
rdfs:label "Cultural Heritage Access"@en .
ngm:cultural-heritage-digitisation a skos:Concept ;
rdfs:label "Cultural Heritage Digitisation"@en .
ngm:cultural-heritage-digitization a skos:Concept ;
rdfs:label "Cultural Heritage Digitization"@en .
ngm:cultural-heritage-management-system a skos:Concept ;
rdfs:label "Cultural Heritage Management System"@en .
ngm:cultural-heritage-preservation a owl:Class ;
rdfs:comment "Cultural Heritage Preservation encompasses the methodologies, technologies, and institutional practices used to document, conserve, and transmit tangible and intangible cultural assets to future generations. Digital preservation extends these goals through high-fidelity capture technologies—photogrammetry, LiDAR scanning, and multispectral imaging—combined with long-lived archival formats and distributed storage. Immersive technologies increasingly enable experiential access to heritage sites and artefacts that physical access cannot support. The discipline spans archaeology, architecture, performing arts, indigenous knowledge, and language revitalisation, requiring interdisciplinary collaboration between cultural practitioners and technologists."@en ;
rdfs:label "Cultural Heritage Preservation"@en ;
rdfs:subClassOf ngm:digital-heritage ;
rdfs:subClassOf _:r6348 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:dependsOn ngm:data-format-standard ;
vc:dependsOn ngm:distributed-storage ;
vc:enables ngm:augmented-reality ;
vc:enables ngm:collective-memory-archive ;
vc:enables ngm:cultural-heritage-xr-experience ;
vc:enables ngm:immersive-experience ;
vc:enables ngm:virtual-tour ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:cultural-provenance-record ;
vc:relatedTo ngm:digital-archive ;
vc:relatedTo ngm:digital-preservation ;
vc:relatedTo ngm:intangible-cultural-heritage ;
vc:relatedTo ngm:open-archival-information-system ;
vc:requires ngm:institutional-repository ;
vc:requires ngm:long-term-storage ;
vc:requires ngm:metadata-standard ;
vc:slug "cultural-heritage-preservation" ;
vc:sourceDomain "spatial-computing" ;
vc:standardizedBy ngm:dublin-core ;
vc:standardizedBy ngm:iso-14721 ;
vc:uses ngm:3-d-reconstruction ;
vc:uses ngm:gltf-standard ;
vc:uses ngm:lidar-scanning ;
vc:uses ngm:multispectral-imaging ;
vc:uses ngm:photogrammetry ;
vc:uses ngm:point-cloud .
ngm:cultural-heritage-xr-experience a owl:Class ;
rdfs:comment "An immersive extended reality application designed to preserve, present, and educate users about cultural heritage through interactive 3D reconstructions, AR overlays, and virtual museum experiences."@en ;
rdfs:label "Cultural Heritage XR Experience"@en ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf _:r6349 ;
rdfs:subClassOf _:r6350 ;
rdfs:subClassOf _:r6351 ;
rdfs:subClassOf _:r6352 ;
rdfs:subClassOf _:r6353 ;
rdfs:subClassOf _:r6354 ;
skos:broader ngm:sc-platform-and-environment ;
vc:bridgesTo ngm:computer-vision ;
vc:dependsOn ngm:heritage-documentation ;
vc:dependsOn ngm:lidar-scanning ;
vc:dependsOn ngm:museum-api ;
vc:dependsOn ngm:photogrammetry ;
vc:enables ngm:archaeological-site-reconstruction ;
vc:enables ngm:cultural-education ;
vc:enables ngm:heritage-tourism ;
vc:enables ngm:virtual-museum-tour ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:3-d-reconstruction ;
vc:hasPart ngm:ar-overlay ;
vc:hasPart ngm:cultural-metadata ;
vc:hasPart ngm:educational-narrative ;
vc:hasPart ngm:interactive-exhibit ;
vc:isPartOf ngm:cultural-heritage-preservation ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:3-d-rendering-engine ;
vc:requires ngm:cultural-database ;
vc:requires ngm:spatial-audio-system ;
vc:requires ngm:xr-runtime-environment ;
vc:slug "cultural-heritage-xr-experience" ;
vc:sourceDomain "spatial-computing" .
ngm:cultural-homogenization a skos:Concept ;
rdfs:label "Cultural Homogenization"@en .
ngm:cultural-metadata a skos:Concept ;
rdfs:label "Cultural Metadata"@en .
ngm:cultural-preservation a owl:Class ;
rdfs:comment "Cultural preservation is the systematic safeguarding, documentation and transmission of tangible and intangible cultural heritage so that it survives for future generations. In digital contexts it involves capturing artefacts as durable metadata-rich records, archiving collective memory, and ensuring long-term accessibility against media decay and format obsolescence. It matters as a governance concern for who controls heritage data and how it remains discoverable."@en ;
rdfs:label "Cultural Preservation"@en ;
rdfs:subClassOf ngm:governance ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:artifact-metadata ;
vc:relatedTo ngm:collective-memory-archive ;
vc:slug "cultural-preservation" ;
vc:sourceDomain "governance" .
ngm:cultural-protocol a skos:Concept ;
rdfs:label "Cultural Protocol"@en .
ngm:cultural-provenance-record a owl:Class ;
rdfs:comment "A structured metadata object that documents the origin, ownership history, authenticity verification, and cultural context of cultural artifacts, artworks, or digital cultural assets to establish legitimacy and preserve heritage lineage."@en ;
rdfs:label "Cultural Provenance Record"@en ;
rdfs:subClassOf ngm:sc-content-and-assets ;
rdfs:subClassOf _:r6355 ;
rdfs:subClassOf _:r6356 ;
rdfs:subClassOf _:r6357 ;
rdfs:subClassOf _:r6358 ;
rdfs:subClassOf _:r6359 ;
rdfs:subClassOf _:r6360 ;
skos:broader ngm:sc-content-and-assets ;
vc:bridgesTo ngm:blockchain ;
vc:dependsOn ngm:authentication-service ;
vc:dependsOn ngm:digital-archive ;
vc:dependsOn ngm:heritage-registry ;
vc:dependsOn ngm:museum-collection-system ;
vc:enables ngm:authenticity-certification ;
vc:enables ngm:cultural-heritage-preservation ;
vc:enables ngm:ownership-transfer ;
vc:enables ngm:provenance-verification ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:artifact-metadata ;
vc:hasPart ngm:authentication-record ;
vc:hasPart ngm:condition-report ;
vc:hasPart ngm:cultural-context ;
vc:hasPart ngm:ownership-transfer ;
vc:isPartOf ngm:cultural-heritage-management-system ;
vc:isPartOf ngm:museum-information-system ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:blockchain-ledger ;
vc:requires ngm:conservation-database ;
vc:requires ngm:digital-signature ;
vc:requires ngm:metadata-schema ;
vc:slug "cultural-provenance-record" ;
vc:sourceDomain "spatial-computing" .
ngm:cupy a skos:Concept ;
rdfs:label "Cupy"@en .
ngm:curated-dataset a skos:Concept ;
rdfs:label "Curated Dataset"@en .
ngm:curated-datasets a skos:Concept ;
rdfs:label "Curated Datasets"@en .
ngm:curated-research-link-repository a owl:Class ;
rdfs:comment "A curated collection of saved hyperlinks to external web resources, serving as a personal or shared reference library for articles, tools, and research material. In knowledge management contexts, web bookmarks act as annotated entry points linking internal knowledge graphs to external sources."@en ;
rdfs:label "Curated Research Link Repository"@en ;
rdfs:subClassOf ngm:software-engineering ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:isPartOf ngm:knowledge-management ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:knowledge-base ;
vc:relatedTo ngm:web-technology ;
vc:slug "curated-research-link-repository" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:web-dev-and-consumer-tooling .
ngm:curiosity-driven-exploration a skos:Concept ;
rdfs:label "Curiosity Driven Exploration"@en .
ngm:currency-conversion a skos:Concept ;
rdfs:label "Currency Conversion"@en .
ngm:currency-convertibility a skos:Concept ;
rdfs:label "Currency Convertibility"@en .
ngm:currency-debasement a skos:Concept ;
rdfs:label "Currency Debasement"@en .
ngm:currency-diversification a skos:Concept ;
rdfs:label "Currency Diversification"@en .
ngm:currency-exchange a skos:Concept ;
rdfs:label "Currency Exchange"@en .
ngm:currency-internationalisation a skos:Concept ;
rdfs:label "Currency Internationalisation"@en .
ngm:currency-peg a skos:Concept ;
rdfs:label "Currency Peg"@en .
ngm:currency-transaction-report a skos:Concept ;
rdfs:label "Currency Transaction Report"@en .
ngm:current-driver a skos:Concept ;
rdfs:label "Current Driver"@en .
ngm:current-sensor a owl:Class ;
rdfs:comment "Current Sensor - An electrical measurement device (Hall effect, fluxgate, or shunt-based) that detects current flow in motor circuits and power systems, enabling Motor Torque Estimation, Fault Detection, and Energy Monitoring in autonomous robots."@en ;
rdfs:label "Current Sensor"@en ;
rdfs:subClassOf ngm:robo-perception ;
rdfs:subClassOf ngm:robotics ;
rdfs:subClassOf ngm:sensor ;
rdfs:subClassOf _:r6361 ;
rdfs:subClassOf _:r6362 ;
skos:broader ngm:robo-perception ;
skos:broader ngm:robotics ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:sensor ;
vc:enables ngm:monitoring ;
vc:enables ngm:overload-protection ;
vc:enables ngm:predictive-maintenance ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:motor-control-system ;
vc:isPartOf ngm:power-management ;
vc:qualityScore "0.52"^^xsd:float ;
vc:requires ngm:analogue-to-digital-conversion ;
vc:requires ngm:signal-conditioning ;
vc:slug "current-sensor" ;
vc:sourceDomain "robotics" .
ngm:currentamplifier a skos:Concept ;
rdfs:label "Currentamplifier"@en .
ngm:curriculum a skos:Concept ;
rdfs:label "Curriculum"@en .
ngm:curriculum-design a skos:Concept ;
rdfs:label "Curriculum Design"@en .
ngm:curriculum-learning a owl:Class ;
rdfs:comment "A training strategy that presents examples to a model in a meaningful order, typically progressing from easy to difficult, mimicking how humans learn. Curriculum learning improves convergence speed, final performance, and generalisation by structuring the learning progression rather than relying on random example ordering."@en ;
rdfs:label "Curriculum Learning"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf _:r6363 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:natural-language-processing ;
vc:bridgesTo ngm:reinforcement-learning ;
vc:bridgesTo ngm:robotics ;
vc:contrastsWith ngm:anti-curriculum ;
vc:contrastsWith ngm:random-sampling ;
vc:dependsOn ngm:optimisation-algorithm ;
vc:dependsOn ngm:supervised-learning ;
vc:enables ngm:computer-vision ;
vc:enables ngm:model-performance ;
vc:enables ngm:sample-efficiency ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:automatic-curriculum ;
vc:hasPart ngm:self-paced-learning ;
vc:hasPart ngm:teacher-student-curriculum ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:active-learning ;
vc:relatedTo ngm:continual-learning ;
vc:relatedTo ngm:contrastive-learning ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:meta-learning ;
vc:relatedTo ngm:training-strategy ;
vc:relatedTo ngm:transfer-learning ;
vc:requires ngm:difficulty-assessment ;
vc:requires ngm:training-data ;
vc:slug "curriculum-learning" ;
vc:sourceDomain "machine-learning" ;
vc:uses ngm:data-ordering ;
vc:uses ngm:deep-learning ;
vc:uses ngm:difficulty-measure .
ngm:cursor a owl:Class ;
rdfs:comment "Cursor is an AI-native code editor developed by Anysphere, built on a Visual Studio Code foundation and deeply integrated with large language models to provide inline code completion, multi-file agentic editing, natural-language chat over the codebase, and autonomous background agents. As of 2026, Cursor is the leading independent AI coding assistant by revenue, having reached $2 billion ARR and a $29.3 billion Series D valuation, and is used by over 64% of Fortune 500 companies."@en ;
rdfs:label "Cursor"@en ;
rdfs:subClassOf ngm:agentic-ai ;
rdfs:subClassOf ngm:generative-ai ;
rdfs:subClassOf ngm:software-development ;
rdfs:subClassOf _:r6364 ;
rdfs:subClassOf _:r6365 ;
rdfs:subClassOf _:r6366 ;
rdfs:subClassOf _:r6367 ;
rdfs:subClassOf _:r6368 ;
rdfs:subClassOf _:r6369 ;
rdfs:subClassOf _:r6370 ;
rdfs:subClassOf _:r6371 ;
rdfs:subClassOf _:r6372 ;
rdfs:subClassOf _:r6373 ;
vc:contrastsWith ngm:claude-code ;
vc:contrastsWith ngm:microsoft-copilot ;
vc:dependsOn ngm:large-language-model ;
vc:dependsOn ngm:natural-language-processing ;
vc:dependsOn ngm:transformer-architecture ;
vc:enables ngm:agentic-workflow ;
vc:enables ngm:code-generation ;
vc:enables ngm:llm-application-framework ;
vc:enables ngm:software-development ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:agentic-workflow ;
vc:hasPart ngm:llm-agents ;
vc:hasPart ngm:model-context-protocol ;
vc:hasPart ngm:retrieval-augmented-generation ;
vc:hasPart ngm:tool-augmented-llm ;
vc:implements ngm:agentic-ai ;
vc:implements ngm:model-context-protocol ;
vc:implements ngm:tool-augmented-llm ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:generative-ai ;
vc:relatedTo ngm:llm-agents ;
vc:relatedTo ngm:llm-application-framework ;
vc:relatedTo ngm:tool-augmented-llm ;
vc:requires ngm:large-language-model ;
vc:requires ngm:large-language-models ;
vc:requires ngm:natural-language-processing ;
vc:requires ngm:retrieval-augmented-generation ;
vc:requires ngm:transformer-architecture ;
vc:slug "cursor" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:model-context-protocol ;
vc:supports ngm:agentic-workflow ;
vc:supports ngm:llm-agents ;
vc:supports ngm:software-development ;
vc:uses ngm:claude-sonnet ;
vc:uses ngm:gpt ;
vc:uses ngm:gpt-4o ;
vc:uses ngm:llm-application-framework ;
vc:uses ngm:model-context-protocol ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:retrieval-augmented-generation ;
vc:uses ngm:transformer-architecture .
ngm:cursor-synchronisation a skos:Concept ;
rdfs:label "Cursor Synchronisation"@en .
ngm:curve a owl:Class ;
rdfs:comment "Curve is a decentralised exchange on Ethereum and other chains optimised for low-slippage swaps between similarly priced assets such as stablecoins. Its CRV token and gauge system govern liquidity incentives."@en ;
rdfs:label "Curve"@en ;
rdfs:subClassOf ngm:curve-finance ;
rdfs:subClassOf _:r6384 ;
rdfs:subClassOf _:r6385 ;
vc:bridgesTo ngm:decentralized-exchange ;
vc:enables ngm:gauge-voting ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:automated-market-maker ;
vc:requires ngm:liquidity-pool ;
vc:slug "curve" ;
vc:sourceDomain "blockchain" .
ngm:curve-dao-token a skos:Concept ;
rdfs:label "Curve DAO Token"@en .
ngm:curve-finance a owl:Class ;
rdfs:comment "Curve Finance is a decentralised exchange protocol operating across Ethereum and multiple EVM-compatible chains, specialising in low-slippage swaps between assets expected to maintain near-parity in value, such as stablecoins and liquid staking tokens. It employs a hybrid invariant automated market maker that blends constant-sum and constant-product behaviour, concentrating liquidity near the peg to dramatically reduce trading costs for correlated assets. The protocol's CRV governance token is distributed to liquidity providers and can be locked in a vote-escrow mechanism (veCRV) that grants voting power over pool incentive allocation, creating a flywheel dynamic known as the Curve Wars. Curve v2 extended the model to volatile asset pairs using a price-repegging invariant, broadening the protocol's scope from stablecoin-only pools to general concentrated-liquidity trading."@en ;
rdfs:label "Curve Finance"@en ;
rdfs:subClassOf ngm:de-fi ;
rdfs:subClassOf _:r6374 ;
rdfs:subClassOf _:r6375 ;
rdfs:subClassOf _:r6376 ;
rdfs:subClassOf _:r6377 ;
rdfs:subClassOf _:r6378 ;
rdfs:subClassOf _:r6379 ;
vc:bridgesTo ngm:game-theory ;
vc:bridgesTo ngm:mechanism-design ;
vc:contrastsWith ngm:balancer ;
vc:contrastsWith ngm:centralised-exchange ;
vc:contrastsWith ngm:uniswap ;
vc:dependsOn ngm:evm-compatible-blockchain ;
vc:dependsOn ngm:oracle ;
vc:enables ngm:flash-loan ;
vc:enables ngm:yield-farming ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:curve-dao-token ;
vc:hasPart ngm:liquidity-pool ;
vc:hasPart ngm:vote-escrow ;
vc:implements ngm:automated-market-maker ;
vc:implements ngm:concentrated-liquidity ;
vc:isPartOf ngm:decentralised-finance-domain ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:convex-finance ;
vc:relatedTo ngm:defi-composability ;
vc:relatedTo ngm:impermanent-loss ;
vc:relatedTo ngm:token-incentive-design ;
vc:requires ngm:ethereum ;
vc:requires ngm:smart-contract ;
vc:requires ngm:stablecoin ;
vc:slug "curve-finance" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:decentralised-autonomous-organisation ;
vc:uses ngm:governance-token ;
vc:uses ngm:liquidity-mining .
ngm:curve-fitting a skos:Concept ;
rdfs:label "Curve Fitting"@en .
ngm:curve-stableswap-paper a skos:Concept ;
rdfs:label "Curve Stableswap Paper"@en .
ngm:curve-wars a owl:Class ;
rdfs:comment "The Curve Wars refers to the competitive dynamic among decentralised finance protocols to accumulate vote-escrowed CRV (veCRV) governance power over Curve Finance, thereby gaining the ability to direct CRV token emissions (gauges) toward liquidity pools in which the protocol has a stake. By controlling gauge weights, protocols attract liquidity providers to their pools by offering higher yields, creating a recursive incentive structure. The conflict intensified with the emergence of vote-aggregation intermediaries such as Convex Finance, which pooled user CRV into a dominant veCRV position and issued its own liquid derivative tokens (cvxCRV, vlCVX) to further abstract the underlying governance asset."@en ;
rdfs:label "Curve Wars"@en ;
rdfs:subClassOf ngm:de-fi ;
rdfs:subClassOf _:r6380 ;
rdfs:subClassOf _:r6381 ;
rdfs:subClassOf _:r6382 ;
rdfs:subClassOf _:r6383 ;
vc:bridgesTo ngm:game-theory ;
vc:bridgesTo ngm:mechanism-design ;
vc:contrastsWith ngm:market-making ;
vc:contrastsWith ngm:proof-of-work ;
vc:dependsOn ngm:curve-finance ;
vc:dependsOn ngm:decentralised-autonomous-organisation ;
vc:dependsOn ngm:ethereum ;
vc:enables ngm:liquidity-provision ;
vc:enables ngm:yield-optimisation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:bribery-market ;
vc:hasPart ngm:gauge-voting ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:convex-finance ;
vc:relatedTo ngm:liquid-staking ;
vc:relatedTo ngm:miner-extractable-value ;
vc:relatedTo ngm:protocol-owned-liquidity ;
vc:relatedTo ngm:tokenomics ;
vc:requires ngm:governance-token ;
vc:requires ngm:vote-escrow-model ;
vc:slug "curve-wars" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:automated-market-maker ;
vc:uses ngm:liquidity-pool ;
vc:uses ngm:smart-contract ;
vc:uses ngm:token-emission .
ngm:curve25519 a owl:Class ;
rdfs:comment "Curve25519 is a Montgomery-form elliptic curve designed for fast, secure elliptic-curve Diffie-Hellman key exchange at a 128-bit security level. It was engineered to avoid common implementation pitfalls by enabling constant-time, branch-free arithmetic and to sidestep concerns about opaque parameter selection through rigid, transparent design choices. It underpins the X25519 key-agreement function and is widely deployed in modern secure-transport and messaging protocols."@en ;
rdfs:label "Curve25519"@en ;
rdfs:subClassOf ngm:elliptic-curve-cryptography ;
rdfs:subClassOf _:r6386 ;
vc:contrastsWith ngm:ed25519 ;
vc:enables ngm:ed25519 ;
vc:enables ngm:forward-secrecy ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:key-exchange ;
vc:isPartOf ngm:cryptographic-primitive ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:digital-signature ;
vc:relatedTo ngm:ed25519 ;
vc:relatedTo ngm:key-exchange ;
vc:requires ngm:cryptography ;
vc:slug "curve25519" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:nist ;
vc:supports ngm:signal-protocol ;
vc:supports ngm:tls ;
vc:uses ngm:elliptic-curve-cryptography .
ngm:curvilinear-coordinate-system a skos:Concept ;
rdfs:label "Curvilinear Coordinate System"@en .
ngm:custodial-asset-transfer a skos:Concept ;
rdfs:label "Custodial Asset Transfer"@en .
ngm:custodial-concentration a skos:Concept ;
rdfs:label "Custodial Concentration"@en .
ngm:custodial-digital-asset a skos:Concept ;
rdfs:label "Custodial Digital Asset"@en .
ngm:custodial-exchange a owl:Class ;
rdfs:comment "A custodial exchange is a cryptocurrency trading venue that holds users' assets and private keys on their behalf, settling trades on its internal ledger rather than on-chain. Users gain convenience, liquidity and familiar account-based access, but cede control of their keys and accept counterparty risk in the operator. It is the centralised counterpart to non-custodial and decentralised trading models."@en ;
rdfs:label "Custodial Exchange"@en ;
rdfs:subClassOf ngm:cryptocurrency-exchange ;
rdfs:subClassOf _:r6387 ;
rdfs:subClassOf _:r6388 ;
vc:contrastsWith ngm:decentralized-exchange ;
vc:contrastsWith ngm:self-custody ;
vc:dependsOn ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:proof-of-reserve ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:centralized-exchange ;
vc:relatedTo ngm:digital-asset-custody ;
vc:relatedTo ngm:qualified-custodian ;
vc:relatedTo ngm:wallet ;
vc:requires ngm:custodial-wallet ;
vc:requires ngm:kyc ;
vc:slug "custodial-exchange" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:liquidity ;
vc:uses ngm:cold-storage ;
vc:uses ngm:custody .
ngm:custodial-service a skos:Concept ;
rdfs:label "Custodial Service"@en .
ngm:custodial-settlement a skos:Concept ;
rdfs:label "Custodial Settlement"@en .
ngm:custodial-wallet a owl:Class ;
rdfs:comment "A custodial wallet is a cryptocurrency wallet in which a third party — typically an exchange or custodian — holds and controls the private keys on behalf of the user, who accesses funds through an account rather than direct on-chain key ownership. This model trades the self-sovereignty of non-custodial wallets for convenience, account recovery, and integrated services, while introducing counterparty risk and reliance on the custodian's security and solvency. Custodial arrangements are common at centralised exchanges and increasingly subject to regulatory requirements for asset segregation and proof of reserves."@en ;
rdfs:label "Custodial Wallet"@en ;
rdfs:subClassOf ngm:digital-wallet ;
rdfs:subClassOf _:r6389 ;
vc:bridgesTo ngm:mpc-wallet ;
vc:contrastsWith ngm:multi-signature-wallet ;
vc:contrastsWith ngm:non-custodial-wallet ;
vc:contrastsWith ngm:self-custody ;
vc:dependsOn ngm:key-management ;
vc:dependsOn ngm:trusted-third-party ;
vc:enables ngm:account-recovery ;
vc:enables ngm:fiat-on-ramp ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:account-balance-ledger ;
vc:hasPart ngm:omnibus-account ;
vc:implements ngm:proof-of-reserves ;
vc:isPartOf ngm:centralised-exchange ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:counterparty-risk ;
vc:relatedTo ngm:cryptocurrency-custody ;
vc:requires ngm:kyc ;
vc:slug "custodial-wallet" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:exchange-custody ;
vc:supports ngm:institutional-custody ;
vc:uses ngm:cold-storage ;
vc:uses ngm:hot-wallet .
ngm:custodian a owl:Class ;
rdfs:comment "A custodian is an entity entrusted with safeguarding assets on behalf of others, holding and securing them while the legal or beneficial owner retains a claim. In digital-asset markets a custodian secures cryptographic keys and underlying holdings for clients and, in the case of fiat-backed stablecoins, holds the reserves that back issued tokens. Custodianship concentrates security and introduces counterparty risk, which is mitigated through controls such as segregation, audits, and proof of reserves."@en ;
rdfs:label "Custodian"@en ;
rdfs:subClassOf ngm:custody ;
rdfs:subClassOf _:r6390 ;
rdfs:subClassOf _:r6391 ;
rdfs:subClassOf _:r6392 ;
rdfs:subClassOf _:r6393 ;
vc:bridgesTo ngm:counterparty-risk ;
vc:contrastsWith ngm:self-custody ;
vc:dependsOn ngm:trust ;
vc:enables ngm:asset-management ;
vc:enables ngm:proof-of-reserves ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:cold-storage ;
vc:hasPart ngm:multisig ;
vc:implements ngm:institutional-custody ;
vc:isPartOf ngm:custody ;
vc:isPartOf ngm:digital-asset-custody ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:aml ;
vc:relatedTo ngm:audit ;
vc:relatedTo ngm:transparency ;
vc:requires ngm:kyc ;
vc:requires ngm:trust ;
vc:slug "custodian" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:regulation ;
vc:supports ngm:centralized-exchange ;
vc:supports ngm:stablecoin ;
vc:supports ngm:tether ;
vc:uses ngm:cold-storage ;
vc:uses ngm:hot-wallet ;
vc:uses ngm:multisig .
ngm:custodian-bank a skos:Concept ;
rdfs:label "Custodian Bank"@en .
ngm:custodian-network a skos:Concept ;
rdfs:label "Custodian Network"@en .
ngm:custody a owl:Class ;
rdfs:comment "The holding and safekeeping of assets and the keys that control them, defining who has the authority to move funds on behalf of an owner."@en ;
rdfs:label "Custody"@en ;
rdfs:subClassOf ngm:bc-token-and-asset ;
rdfs:subClassOf ngm:custody-infrastructure ;
rdfs:subClassOf _:r6404 ;
rdfs:subClassOf _:r6405 ;
rdfs:subClassOf _:r6406 ;
rdfs:subClassOf _:r6407 ;
rdfs:subClassOf _:r6408 ;
rdfs:subClassOf _:r6409 ;
rdfs:subClassOf _:r6410 ;
skos:broader ngm:bc-token-and-asset ;
vc:bridgesTo ngm:data-sovereignty ;
vc:bridgesTo ngm:digital-asset-management ;
vc:bridgesTo ngm:financial-asset-custody ;
vc:bridgesTo ngm:institutional-custody ;
vc:bridgesTo ngm:self-custody ;
vc:contrastsWith ngm:counterparty-risk ;
vc:contrastsWith ngm:non-custodial-wallet ;
vc:dependsOn ngm:access-control ;
vc:dependsOn ngm:cryptographic-key-pair ;
vc:enables ngm:asset-transfer ;
vc:enables ngm:regulatory-compliance ;
vc:enables ngm:transaction-signing ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:institutional-custody ;
vc:hasPart ngm:multi-signature ;
vc:hasPart ngm:self-custody ;
vc:isPartOf ngm:custody-infrastructure ;
vc:isPartOf ngm:digital-asset-management ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:asset-recovery ;
vc:relatedTo ngm:cold-storage ;
vc:relatedTo ngm:hot-wallet ;
vc:requires ngm:hardware-security-module ;
vc:requires ngm:key-management ;
vc:requires ngm:private-key ;
vc:requires ngm:wallet ;
vc:slug "custody" ;
vc:sourceDomain "blockchain" .
ngm:custody-infrastructure a owl:Class ;
rdfs:comment "Custody infrastructure refers to the integrated technological, operational, and regulatory systems that enable the secure holding, management, and transfer of digital assets on behalf of third parties. It encompasses hardware security modules (HSMs), multi-signature and multi-party computation (MPC) key management schemes, cold and warm storage tiers, policy engines, and compliance workflows that satisfy fiduciary and regulatory obligations. As the institutional-grade equivalent of a traditional custodian bank applied to blockchain-native assets, custody infrastructure underpins every regulated digital asset vehicle—from spot ETFs to tokenised real-world assets. Its design must simultaneously satisfy cryptographic security requirements, operational resilience, regulatory auditability, and the settlement latency demands of professional financial markets."@en ;
rdfs:label "Custody Infrastructure"@en ;
rdfs:subClassOf ngm:custody ;
rdfs:subClassOf _:r6394 ;
rdfs:subClassOf _:r6395 ;
rdfs:subClassOf _:r6396 ;
rdfs:subClassOf _:r6397 ;
rdfs:subClassOf _:r6398 ;
rdfs:subClassOf _:r6399 ;
rdfs:subClassOf _:r6400 ;
rdfs:subClassOf _:r6401 ;
vc:bridgesTo ngm:key-management ;
vc:bridgesTo ngm:traditional-securities-custody ;
vc:contrastsWith ngm:exchange-custody ;
vc:contrastsWith ngm:self-custody ;
vc:enables ngm:digital-asset-etf ;
vc:enables ngm:institutional-digital-asset-custody ;
vc:enables ngm:tokenised-real-world-assets ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:cold-storage ;
vc:hasPart ngm:hardware-security-module ;
vc:hasPart ngm:key-management-system ;
vc:hasPart ngm:policy-engine ;
vc:isPartOf ngm:digital-asset-infrastructure ;
vc:isPartOf ngm:financial-market-infrastructure ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:cryptographic-key ;
vc:relatedTo ngm:financial-regulation ;
vc:relatedTo ngm:transaction-signing ;
vc:requires ngm:multi-party-computation ;
vc:requires ngm:multi-signature ;
vc:requires ngm:regulatory-compliance ;
vc:requires ngm:threshold-signature-scheme ;
vc:slug "custody-infrastructure" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:bc-0482-eu-mica-regulation ;
vc:standardizedBy ngm:occ-interpretive-letter ;
vc:supports ngm:institutional-defi ;
vc:supports ngm:qualified-custodian ;
vc:uses ngm:air-gap ;
vc:uses ngm:blockchain-analytics ;
vc:uses ngm:smart-contract .
ngm:custody-layer a owl:Class ;
rdfs:comment "The Custody Layer is the stratum that governs the safekeeping and authorised control of assets and the keys that command them. It sits above the Cryptographic and Identity strata it depends on and below the settlement and application activity that moves assets. It contains key storage, signing policies, and the authorisation rules for asset control."@en ;
rdfs:label "Custody Layer"@en ;
rdfs:subClassOf ngm:bc-token-and-asset ;
rdfs:subClassOf ngm:owl-thing ;
rdfs:subClassOf _:r6402 ;
rdfs:subClassOf _:r6403 ;
skos:broader ngm:bc-token-and-asset ;
vc:bridgesTo ngm:key-management ;
vc:bridgesTo ngm:multi-signature ;
vc:enables ngm:application-layer ;
vc:enables ngm:settlement-layer ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:cryptographic-layer ;
vc:requires ngm:identity-layer ;
vc:slug "custody-layer" ;
vc:sourceDomain "blockchain" .
ngm:custody-system a skos:Concept ;
rdfs:label "Custody System"@en .
ngm:custom-execution-environment a skos:Concept ;
rdfs:label "Custom Execution Environment"@en .
ngm:custom-neural-architectures a skos:Concept ;
rdfs:label "Custom Neural Architectures"@en .
ngm:custom-node-development a skos:Concept ;
rdfs:label "Custom Node Development"@en .
ngm:custom-node-extension-system a skos:Concept ;
rdfs:label "Custom Node Extension System"@en .
ngm:custom-node-registry a skos:Concept ;
rdfs:label "Custom Node Registry"@en .
ngm:custom-node-system a skos:Concept ;
rdfs:label "Custom Node System"@en .
ngm:custom-rtos-firmware a skos:Concept ;
rdfs:label "Custom Rtos Firmware"@en .
ngm:customer-data-platform a owl:Class ;
rdfs:comment "A Customer Data Platform (CDP) is a packaged software system that ingests first-party customer data from disparate online and offline sources, resolves fragmented identifiers into persistent, unified customer profiles, and exposes those profiles via APIs to downstream marketing, analytics, and personalisation systems. Unlike data warehouses or CRM systems, a CDP is marketer-managed, real-time capable, and purpose-built for identity resolution and audience activation. CDPs enforce consent and privacy preferences at the profile level, making them a key architectural component for compliant, data-driven customer engagement."@en ;
rdfs:label "Customer Data Platform"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r6411 ;
rdfs:subClassOf _:r6412 ;
rdfs:subClassOf _:r6413 ;
rdfs:subClassOf _:r6414 ;
rdfs:subClassOf _:r6415 ;
rdfs:subClassOf _:r6416 ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:bridgesTo ngm:predictive-analytics ;
vc:contrastsWith ngm:customer-relationship-management ;
vc:contrastsWith ngm:data-management-platform ;
vc:contrastsWith ngm:data-warehouse ;
vc:enables ngm:audience-segmentation ;
vc:enables ngm:customer-journey-analytics ;
vc:enables ngm:personalisation ;
vc:enables ngm:real-time-marketing ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:audience-builder ;
vc:hasPart ngm:data-ingestion ;
vc:hasPart ngm:unified-customer-profile ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:data-protection-regulation ;
vc:relatedTo ngm:master-data-management ;
vc:relatedTo ngm:privacy ;
vc:requires ngm:consent-management ;
vc:requires ngm:data-governance ;
vc:requires ngm:data-integration ;
vc:requires ngm:identity-resolution ;
vc:slug "customer-data-platform" ;
vc:sourceDomain "data" ;
vc:standardizedBy ngm:customer-data-platform-institute ;
vc:uses ngm:api-gateway ;
vc:uses ngm:event-streaming ;
vc:uses ngm:extract-transform-load .
ngm:customer-data-platform-institute a skos:Concept ;
rdfs:label "Customer Data Platform Institute"@en .
ngm:customer-due-diligence a owl:Class ;
rdfs:comment "Customer due diligence (CDD) is the set of regulated procedures by which a financial institution or obliged entity identifies and verifies a customer, understands the nature and purpose of the business relationship, and assesses the money-laundering and terrorist-financing risk it poses. It encompasses identity verification, beneficial-ownership identification, screening against sanctions and politically exposed person lists, and ongoing monitoring of transactions and risk profile. CDD is a core obligation of anti-money-laundering regimes, calibrated through a risk-based approach that escalates to enhanced due diligence for higher-risk customers and permits simplified measures for lower-risk ones."@en ;
rdfs:label "Customer Due Diligence"@en ;
rdfs:subClassOf ngm:kyc ;
rdfs:subClassOf _:r6417 ;
rdfs:subClassOf _:r6418 ;
rdfs:subClassOf _:r6419 ;
rdfs:subClassOf _:r6420 ;
rdfs:subClassOf _:r6421 ;
rdfs:subClassOf _:r6422 ;
vc:bridgesTo ngm:digital-identity ;
vc:contrastsWith ngm:enhanced-due-diligence ;
vc:enables ngm:transaction-monitoring ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:beneficial-ownership ;
vc:hasPart ngm:enhanced-due-diligence ;
vc:hasPart ngm:identity-verification ;
vc:isPartOf ngm:aml ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:aml ;
vc:relatedTo ngm:transaction-monitoring ;
vc:requires ngm:identity-verification ;
vc:requires ngm:risk-based-approach ;
vc:requires ngm:sanctions-screening ;
vc:slug "customer-due-diligence" ;
vc:sourceDomain "finance" ;
vc:standardizedBy ngm:fatf ;
vc:supports ngm:regulatory-compliance ;
vc:uses ngm:politically-exposed-person .
ngm:customer-effort-score a skos:Concept ;
rdfs:label "Customer Effort Score"@en .
ngm:customer-experience a owl:Class ;
rdfs:comment "Customer experience (CX) is the holistic perception a customer forms of an organisation across every interaction and touchpoint throughout the customer lifecycle, from initial awareness through purchase, post-sale service, and eventual advocacy or churn. It encompasses emotional, cognitive, sensory, and behavioural dimensions of customer engagement and is recognised as a primary competitive differentiator in markets where product parity is high. Organisations systematically measure and engineer CX through journey mapping, voice-of-customer programmes, service design, and data-driven personalisation."@en ;
rdfs:label "Customer Experience"@en ;
rdfs:subClassOf ngm:customer-experience-management ;
rdfs:subClassOf ngm:user-experience ;
rdfs:subClassOf _:r6438 ;
rdfs:subClassOf _:r6439 ;
rdfs:subClassOf _:r6440 ;
rdfs:subClassOf _:r6441 ;
rdfs:subClassOf _:r6442 ;
rdfs:subClassOf _:r6443 ;
rdfs:subClassOf _:r6444 ;
vc:bridgesTo ngm:agentic-ai ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:spatial-computing ;
vc:contrastsWith ngm:customer-support ;
vc:contrastsWith ngm:user-experience ;
vc:dependsOn ngm:business-intelligence ;
vc:dependsOn ngm:conversational-ai ;
vc:dependsOn ngm:crm ;
vc:dependsOn ngm:customer-data-platform ;
vc:dependsOn ngm:e-commerce ;
vc:dependsOn ngm:large-language-models ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:natural-language-processing ;
vc:enables ngm:customer-lifetime-value ;
vc:enables ngm:customer-retention ;
vc:enables ngm:customer-rewards ;
vc:enables ngm:customer-service-automation ;
vc:enables ngm:hyper-personalisation ;
vc:enables ngm:loyalty-programs ;
vc:enables ngm:next-best-action ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:journey-mapping ;
vc:hasPart ngm:omnichannel-orchestration ;
vc:hasPart ngm:service-blueprint ;
vc:hasPart ngm:service-design ;
vc:hasPart ngm:voice-of-customer ;
vc:implements ngm:behavioural-analytics ;
vc:implements ngm:omnichannel ;
vc:implements ngm:personalisation ;
vc:implements ngm:predictive-personalization ;
vc:implements ngm:real-time-decisioning ;
vc:implements ngm:sentiment-analysis ;
vc:implements ngm:voice-of-customer ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:crm ;
vc:relatedTo ngm:customer-experience-management ;
vc:relatedTo ngm:customer-rewards ;
vc:relatedTo ngm:customer-support ;
vc:relatedTo ngm:data-governance ;
vc:relatedTo ngm:data-privacy ;
vc:relatedTo ngm:digital-twin-of-the-customer ;
vc:relatedTo ngm:service-design ;
vc:requires ngm:consent-management ;
vc:requires ngm:customer-data-platform ;
vc:requires ngm:first-party-data ;
vc:requires ngm:identity-resolution ;
vc:requires ngm:unified-customer-profile ;
vc:slug "customer-experience" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:data-governance ;
vc:supports ngm:agentic-ai ;
vc:supports ngm:digital-twin-of-the-customer ;
vc:supports ngm:spatial-computing ;
vc:uses ngm:behavioural-analytics ;
vc:uses ngm:conversational-ai ;
vc:uses ngm:customer-effort-score ;
vc:uses ngm:journey-mapping ;
vc:uses ngm:large-language-models ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:net-promoter-score ;
vc:uses ngm:predictive-personalization ;
vc:uses ngm:real-time-decisioning ;
vc:uses ngm:sentiment-analysis ;
vc:uses ngm:voice-of-customer .
ngm:customer-experience-management a owl:Class ;
rdfs:comment "Customer Experience Management (CEM or CXM) is the systematic discipline of designing, orchestrating, measuring, and continuously improving every interaction a customer has with an organisation across the full lifecycle — from initial brand awareness through purchase, onboarding, ongoing service, and eventual advocacy or churn. It encompasses the tools, processes, data infrastructure, and organisational culture required to engineer experience quality at scale, relying on journey mapping to document touchpoint sequences, voice-of-customer programmes to capture perception signals, omnichannel platforms to unify channel delivery, and analytics engines to translate interaction data into actionable improvement priorities."@en ;
rdfs:label "Customer Experience Management"@en ;
rdfs:subClassOf ngm:crm ;
rdfs:subClassOf ngm:enterprise-software-platform ;
rdfs:subClassOf ngm:user-experience ;
rdfs:subClassOf _:r6423 ;
rdfs:subClassOf _:r6424 ;
rdfs:subClassOf _:r6425 ;
rdfs:subClassOf _:r6426 ;
rdfs:subClassOf _:r6427 ;
rdfs:subClassOf _:r6428 ;
rdfs:subClassOf _:r6429 ;
rdfs:subClassOf _:r6430 ;
rdfs:subClassOf _:r6431 ;
rdfs:subClassOf _:r6432 ;
rdfs:subClassOf _:r6433 ;
rdfs:subClassOf _:r6434 ;
rdfs:subClassOf _:r6435 ;
rdfs:subClassOf _:r6436 ;
rdfs:subClassOf _:r6437 ;
vc:contrastsWith ngm:crm ;
vc:contrastsWith ngm:customer-support ;
vc:contrastsWith ngm:personalisation ;
vc:dependsOn ngm:behavioural-analytics ;
vc:dependsOn ngm:business-intelligence ;
vc:dependsOn ngm:conversational-ai ;
vc:dependsOn ngm:large-language-models ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:natural-language-processing ;
vc:enables ngm:customer-experience ;
vc:enables ngm:customer-lifetime-value ;
vc:enables ngm:customer-retention ;
vc:enables ngm:customer-rewards ;
vc:enables ngm:e-commerce ;
vc:enables ngm:hyper-personalisation ;
vc:enables ngm:loyalty-programs ;
vc:enables ngm:personalised-learning ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:customer-service-automation ;
vc:hasPart ngm:journey-mapping ;
vc:hasPart ngm:omnichannel ;
vc:hasPart ngm:predictive-personalization ;
vc:hasPart ngm:real-time-decisioning ;
vc:hasPart ngm:sentiment-analysis ;
vc:hasPart ngm:service-blueprint ;
vc:hasPart ngm:service-design ;
vc:hasPart ngm:voice-of-customer ;
vc:implements ngm:behavioural-analytics ;
vc:implements ngm:next-best-action ;
vc:implements ngm:omnichannel ;
vc:implements ngm:personalisation ;
vc:implements ngm:predictive-personalization ;
vc:implements ngm:voice-of-customer ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:customer-lifetime-value ;
vc:relatedTo ngm:data-governance ;
vc:relatedTo ngm:data-privacy ;
vc:relatedTo ngm:digital-twin-of-the-customer ;
vc:relatedTo ngm:next-best-action ;
vc:relatedTo ngm:service-blueprint ;
vc:relatedTo ngm:user-experience ;
vc:requires ngm:consent-management ;
vc:requires ngm:crm ;
vc:requires ngm:customer-data-platform ;
vc:requires ngm:data-governance ;
vc:requires ngm:first-party-data ;
vc:requires ngm:identity-resolution ;
vc:requires ngm:journey-mapping ;
vc:requires ngm:unified-customer-profile ;
vc:requires ngm:voice-of-customer ;
vc:slug "customer-experience-management" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:data-governance ;
vc:supports ngm:agentic-ai ;
vc:supports ngm:digital-twin-of-the-customer ;
vc:supports ngm:e-commerce ;
vc:supports ngm:omnichannel ;
vc:supports ngm:omnichannel-routing ;
vc:supports ngm:spatial-computing ;
vc:uses ngm:behavioural-analytics ;
vc:uses ngm:business-intelligence ;
vc:uses ngm:conversational-ai ;
vc:uses ngm:customer-effort-score ;
vc:uses ngm:large-language-models ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:net-promoter-score ;
vc:uses ngm:sentiment-analysis .
ngm:customer-feedback-analysis a skos:Concept ;
rdfs:label "Customer Feedback Analysis"@en .
ngm:customer-identification-documentation a skos:Concept ;
rdfs:label "Customer Identification Documentation"@en .
ngm:customer-identification-programme a skos:Concept ;
rdfs:label "Customer Identification Programme"@en .
ngm:customer-journey-analytics a skos:Concept ;
rdfs:label "Customer Journey Analytics"@en .
ngm:customer-lifetime-value a owl:Class ;
rdfs:comment "Customer lifetime value is a predictive metric estimating the total net revenue a business can expect from a customer over the duration of their relationship. It is computed from historical purchase frequency, average order value, and retention rates, often refined with machine-learned models that account for individual customer behaviour. Customer relationship management and customer experience management systems use lifetime value estimates to prioritise retention and personalisation investment."@en ;
rdfs:label "Customer Lifetime Value"@en ;
rdfs:subClassOf ngm:crm ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "customer-lifetime-value" ;
vc:sourceDomain "data" .
ngm:customer-lifetime-value-optimisation a skos:Concept ;
rdfs:label "Customer Lifetime Value Optimisation"@en .
ngm:customer-onboarding a skos:Concept ;
rdfs:label "Customer Onboarding"@en .
ngm:customer-relationship-management a skos:Concept ;
rdfs:label "Customer Relationship Management"@en .
ngm:customer-retention a owl:Class ;
rdfs:comment "Customer retention is the set of strategies and mechanisms a business uses to keep existing customers engaged and transacting over time, reducing churn. It commonly relies on loyalty and rewards schemes, personalised omnichannel experiences, and data-driven engagement to maximise customer lifetime value. As an economic mechanism it is typically cheaper than acquisition and central to sustainable revenue."@en ;
rdfs:label "Customer Retention"@en ;
rdfs:subClassOf ngm:economic-mechanism ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:customer-rewards ;
vc:relatedTo ngm:omnichannel ;
vc:slug "customer-retention" ;
vc:sourceDomain "governance" .
ngm:customer-rewards a owl:Class ;
rdfs:comment "Loyalty program systems that use blockchain technology and tokenization to create tradeable, interoperable digital rewards, enabling customers to earn, exchange, and redeem tokens across multiple platforms and businesses while providing brands with transparent, fraud-resistant, and cost-effective..."@en ;
rdfs:label "Customer Rewards"@en ;
rdfs:subClassOf ngm:loyalty-programs ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf _:r6445 ;
rdfs:subClassOf _:r6446 ;
rdfs:subClassOf _:r6447 ;
skos:broader ngm:sc-platform-and-environment ;
vc:bridgesTo ngm:blockchain ;
vc:enables ngm:cross-platform-rewards ;
vc:enables ngm:customer-retention ;
vc:enables ngm:token ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:blockchain-infrastructure ;
vc:requires ngm:digital-wallet ;
vc:requires ngm:smart-contracts ;
vc:slug "customer-rewards" ;
vc:sourceDomain "spatial-computing" .
ngm:customer-satisfaction a skos:Concept ;
rdfs:label "Customer Satisfaction"@en .
ngm:customer-segmentation a skos:Concept ;
rdfs:label "Customer Segmentation"@en .
ngm:customer-service-agent a skos:Concept ;
rdfs:label "Customer Service Agent"@en .
ngm:customer-service-agents a skos:Concept ;
rdfs:label "Customer Service Agents"@en .
ngm:customer-service-automation a owl:Class ;
rdfs:comment "Customer Service Automation (CSA) is the systematic application of artificial intelligence, rule-based logic, and workflow orchestration to resolve customer enquiries, execute transactions, and manage service interactions without requiring continuous human agent involvement. It integrates conversational AI, intent classification, sentiment analysis, and retrieval-augmented generation with CRM platforms, ticketing systems, and enterprise knowledge bases to deliver contextually accurate, personalised responses at scale. Modern CSA pipelines increasingly use large language models as the generation backbone, enabling coherent multi-turn dialogue capable of handling nuanced, composite, or cross-channel queries. Effectiveness is measured by containment rate, first-contact resolution, and customer satisfaction metrics, with human-in-the-loop escalation pathways ensuring quality and regulatory compliance."@en ;
rdfs:label "Customer Service Automation"@en ;
rdfs:subClassOf ngm:ai-agent ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:business-process-automation ;
rdfs:subClassOf ngm:conversational-ai ;
rdfs:subClassOf _:r6448 ;
rdfs:subClassOf _:r6449 ;
rdfs:subClassOf _:r6450 ;
rdfs:subClassOf _:r6451 ;
rdfs:subClassOf _:r6452 ;
rdfs:subClassOf _:r6453 ;
rdfs:subClassOf _:r6454 ;
rdfs:subClassOf _:r6455 ;
rdfs:subClassOf _:r6456 ;
rdfs:subClassOf _:r6457 ;
skos:broader ngm:ai-application ;
vc:bridgesTo ngm:business-process-automation ;
vc:bridgesTo ngm:contact-centre-ai ;
vc:contrastsWith ngm:automation ;
vc:contrastsWith ngm:human-agent-assistance ;
vc:contrastsWith ngm:static-faq-system ;
vc:dependsOn ngm:customer-relationship-management ;
vc:dependsOn ngm:dialogue-management ;
vc:dependsOn ngm:dialogue-state-tracking ;
vc:dependsOn ngm:dialogue-system ;
vc:dependsOn ngm:knowledge-base ;
vc:dependsOn ngm:natural-language-understanding ;
vc:dependsOn ngm:retrieval-augmented-generation ;
vc:enables ngm:conversational-analytics ;
vc:enables ngm:intelligent-ticket-routing ;
vc:enables ngm:multi-turn-dialogue ;
vc:enables ngm:omnichannel ;
vc:enables ngm:omnichannel-routing ;
vc:enables ngm:proactive-customer-engagement ;
vc:enables ngm:self-service-portal ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:chatbot ;
vc:hasPart ngm:dialogue-management ;
vc:hasPart ngm:escalation-management ;
vc:hasPart ngm:interactive-voice-response ;
vc:hasPart ngm:retrieval-augmented-generation ;
vc:hasPart ngm:sentiment-analysis ;
vc:hasPart ngm:virtual-agent ;
vc:implements ngm:business-process-automation ;
vc:implements ngm:task-oriented-dialogue ;
vc:implements ngm:workflow-automation ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:ai-agent ;
vc:relatedTo ngm:customer-support-automation ;
vc:relatedTo ngm:dialogue-state-tracking ;
vc:relatedTo ngm:multi-turn-dialogue ;
vc:relatedTo ngm:multimodal-ai-architecture-ai ;
vc:relatedTo ngm:natural-language-generation ;
vc:relatedTo ngm:reinforcement-learning ;
vc:relatedTo ngm:robotic-process-automation ;
vc:relatedTo ngm:workflow-automation ;
vc:requires ngm:dialogue-management ;
vc:requires ngm:intent-classification ;
vc:requires ngm:named-entity-recognition ;
vc:requires ngm:natural-language-understanding ;
vc:requires ngm:slot-filling ;
vc:requires ngm:task-oriented-dialogue ;
vc:slug "customer-service-automation" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:fca-consumer-duty ;
vc:standardizedBy ngm:iso-18295 ;
vc:standardizedBy ngm:uk-gdpr ;
vc:standardizedBy ngm:wcag-2-1 ;
vc:supports ngm:active-learning ;
vc:supports ngm:customer-relationship-management ;
vc:supports ngm:omnichannel ;
vc:supports ngm:robotic-process-automation ;
vc:uses ngm:active-learning ;
vc:uses ngm:agentic-rag ;
vc:uses ngm:conversational-ai ;
vc:uses ngm:information-retrieval ;
vc:uses ngm:intent-classification ;
vc:uses ngm:large-language-model ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:named-entity-recognition ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:reinforcement-learning ;
vc:uses ngm:sentiment-analysis ;
vc:uses ngm:speech-recognition ;
vc:uses ngm:text-to-speech ;
vc:uses ngm:transformer-architecture .
ngm:customer-service-bot a skos:Concept ;
rdfs:label "Customer Service Bot"@en .
ngm:customer-success a skos:Concept ;
rdfs:label "Customer Success"@en .
ngm:customer-support a owl:Class ;
rdfs:comment "Customer Support is the structured operational function and set of AI-augmented processes through which organisations resolve customer queries, technical faults, billing disputes, and product complaints across telephone, email, live chat, self-service portals, and social messaging channels, increasingly powered by Large Language Models, Retrieval-Augmented Generation architectures, and autonomous Agentic Workflow systems that automate first-contact resolution while escalating complex edge cases to human agents with full conversational context."@en ;
rdfs:label "Customer Support"@en ;
rdfs:subClassOf ngm:customer-service-automation ;
rdfs:subClassOf ngm:enterprise-workflow ;
rdfs:subClassOf _:r6472 ;
rdfs:subClassOf _:r6473 ;
rdfs:subClassOf _:r6474 ;
rdfs:subClassOf _:r6475 ;
rdfs:subClassOf _:r6476 ;
rdfs:subClassOf _:r6477 ;
rdfs:subClassOf _:r6478 ;
rdfs:subClassOf _:r6479 ;
rdfs:subClassOf _:r6480 ;
rdfs:subClassOf _:r6481 ;
rdfs:subClassOf _:r6482 ;
rdfs:subClassOf _:r6483 ;
rdfs:subClassOf _:r6484 ;
vc:contrastsWith ngm:manual-customer-service ;
vc:contrastsWith ngm:unstructured-help-desk ;
vc:dependsOn ngm:named-entity-recognition ;
vc:dependsOn ngm:speech-recognition ;
vc:dependsOn ngm:text-classification ;
vc:dependsOn ngm:transformer-architecture ;
vc:enables ngm:agentic-workflow ;
vc:enables ngm:document-retrieval ;
vc:enables ngm:multi-turn-dialogue ;
vc:enables ngm:question-answering ;
vc:enables ngm:workflow-automation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:dialogue-management ;
vc:hasPart ngm:dialogue-state-tracking ;
vc:hasPart ngm:intent-recognition ;
vc:hasPart ngm:knowledge-retrieval ;
vc:hasPart ngm:sentiment-analysis ;
vc:hasPart ngm:workflow-automation ;
vc:implements ngm:conversational-ai ;
vc:implements ngm:large-language-models ;
vc:implements ngm:retrieval-augmented-generation ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:conversational-ai ;
vc:relatedTo ngm:enterprise-workflow ;
vc:relatedTo ngm:explainable-ai ;
vc:relatedTo ngm:human-computer-interaction ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:sentiment-analysis ;
vc:requires ngm:crm-integration ;
vc:requires ngm:crm-systems ;
vc:requires ngm:dialogue-management ;
vc:requires ngm:dialogue-system ;
vc:requires ngm:information-retrieval ;
vc:requires ngm:knowledge-retrieval ;
vc:requires ngm:natural-language-processing ;
vc:slug "customer-support" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:iso-9001-quality-management ;
vc:standardizedBy ngm:itu-t-e-800-quality-of-service ;
vc:supports ngm:explainable-ai ;
vc:supports ngm:human-computer-interaction ;
vc:supports ngm:reinforcement-learning-from-human-feedback ;
vc:uses ngm:chatbots ;
vc:uses ngm:crm ;
vc:uses ngm:dialogue-system ;
vc:uses ngm:hybrid-retrieval ;
vc:uses ngm:information-retrieval ;
vc:uses ngm:intent-recognition ;
vc:uses ngm:large-language-models ;
vc:uses ngm:multimodal-ai-architecture-ai ;
vc:uses ngm:retrieval-augmented-generation ;
vc:uses ngm:speech-recognition .
ngm:customer-support-automation a owl:Class ;
rdfs:comment "Customer Support Automation (CSA-Support) is the application of artificial intelligence, natural language processing, and workflow orchestration to the technical and post-sale support domain, automatically handling customer enquiries, diagnosing faults, routing and resolving service tickets, and delivering self-service resolution pathways through chatbots, virtual agents, and agentic AI systems. It specialises the broader Customer Service Automation domain toward helpdesk operations, IT service management, and product support contexts, integrating with ticketing platforms, knowledge bases, diagnostic APIs, and CRM systems to achieve autonomous first-line resolution of technical and product queries at scale."@en ;
rdfs:label "Customer Support Automation"@en ;
rdfs:subClassOf ngm:ai-agent ;
rdfs:subClassOf ngm:conversational-ai ;
rdfs:subClassOf ngm:customer-service-automation ;
rdfs:subClassOf _:r6458 ;
rdfs:subClassOf _:r6459 ;
rdfs:subClassOf _:r6460 ;
rdfs:subClassOf _:r6461 ;
rdfs:subClassOf _:r6462 ;
rdfs:subClassOf _:r6463 ;
rdfs:subClassOf _:r6464 ;
rdfs:subClassOf _:r6465 ;
rdfs:subClassOf _:r6466 ;
rdfs:subClassOf _:r6467 ;
rdfs:subClassOf _:r6468 ;
rdfs:subClassOf _:r6469 ;
rdfs:subClassOf _:r6470 ;
rdfs:subClassOf _:r6471 ;
vc:bridgesTo ngm:business-process-automation ;
vc:bridgesTo ngm:it-service-management ;
vc:contrastsWith ngm:automation ;
vc:contrastsWith ngm:human-agent-assistance ;
vc:contrastsWith ngm:manual-ticket-triage ;
vc:contrastsWith ngm:static-faq-system ;
vc:dependsOn ngm:customer-relationship-management ;
vc:dependsOn ngm:dialogue-management ;
vc:dependsOn ngm:retrieval-augmented-generation ;
vc:dependsOn ngm:robotic-process-automation ;
vc:dependsOn ngm:workflow-automation ;
vc:enables ngm:first-line-resolution ;
vc:enables ngm:intelligent-ticket-routing ;
vc:enables ngm:multi-turn-dialogue ;
vc:enables ngm:omnichannel ;
vc:enables ngm:omnichannel-routing ;
vc:enables ngm:proactive-fault-detection ;
vc:enables ngm:self-service-portal ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:chatbot ;
vc:hasPart ngm:dialogue-management ;
vc:hasPart ngm:dialogue-state-tracking ;
vc:hasPart ngm:escalation-management ;
vc:hasPart ngm:knowledge-base ;
vc:hasPart ngm:sentiment-analysis ;
vc:hasPart ngm:virtual-agent ;
vc:implements ngm:business-process-automation ;
vc:implements ngm:task-oriented-dialogue ;
vc:implements ngm:workflow-automation ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:ai-agent ;
vc:relatedTo ngm:business-process-automation ;
vc:relatedTo ngm:customer-service-automation ;
vc:relatedTo ngm:dialogue-system ;
vc:relatedTo ngm:multi-turn-dialogue ;
vc:relatedTo ngm:natural-language-generation ;
vc:relatedTo ngm:reinforcement-learning ;
vc:relatedTo ngm:robotic-process-automation ;
vc:relatedTo ngm:workflow-automation ;
vc:requires ngm:chatbot ;
vc:requires ngm:dialogue-state-tracking ;
vc:requires ngm:dialogue-systems ;
vc:requires ngm:intent-classification ;
vc:requires ngm:knowledge-base ;
vc:requires ngm:named-entity-recognition ;
vc:requires ngm:natural-language-understanding ;
vc:requires ngm:slot-filling ;
vc:requires ngm:task-oriented-dialogue ;
vc:slug "customer-support-automation" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:fca-consumer-duty ;
vc:standardizedBy ngm:uk-gdpr ;
vc:standardizedBy ngm:wcag-2-1 ;
vc:supports ngm:active-learning ;
vc:supports ngm:customer-relationship-management ;
vc:supports ngm:omnichannel ;
vc:supports ngm:robotic-process-automation ;
vc:uses ngm:active-learning ;
vc:uses ngm:agentic-rag ;
vc:uses ngm:information-retrieval ;
vc:uses ngm:intent-classification ;
vc:uses ngm:large-language-model ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:named-entity-recognition ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:reinforcement-learning ;
vc:uses ngm:retrieval-augmented-generation ;
vc:uses ngm:sentiment-analysis ;
vc:uses ngm:speech-recognition ;
vc:uses ngm:text-to-speech ;
vc:uses ngm:transformer-architecture .
ngm:customer-world-model a owl:Class ;
rdfs:comment "A proprietary, data-driven internal representation of a customer's or merchant's financial behavior and context, used to generate personalized insights and services."@en ;
rdfs:label "Customer World Model"@en ;
rdfs:subClassOf ngm:world-model ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:data ;
vc:relatedTo ngm:metadata ;
vc:relatedTo ngm:world-model ;
vc:slug "customer-world-model" ;
vc:sourceDomain "economics" .
ngm:customised-training a skos:Concept ;
rdfs:label "Customised Training"@en .
ngm:customization-tools a skos:Concept ;
rdfs:label "Customization Tools"@en .
ngm:customs a skos:Concept ;
rdfs:label "Customs"@en .
ngm:customs-and-excise a skos:Concept ;
rdfs:label "Customs And Excise"@en .
ngm:customs-declaration a skos:Concept ;
rdfs:label "Customs Declaration"@en .
ngm:customs-trade-facilitation a owl:Class ;
rdfs:comment "The systematic application of digital infrastructure — blockchain distributed ledgers, AI-driven risk engines, smart contracts, and interoperable single-window platforms — to reduce friction in cross-border trade whilst maintaining regulatory compliance for customs authorities and economic operat..."@en ;
rdfs:label "Customs Trade Facilitation"@en ;
rdfs:subClassOf ngm:aml-kyc-compliance ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
rdfs:subClassOf ngm:blockchain-network ;
rdfs:subClassOf ngm:digital-customs ;
rdfs:subClassOf ngm:regulatory-technology ;
rdfs:subClassOf ngm:supply-chain-traceability ;
rdfs:subClassOf ngm:trade-finance ;
rdfs:subClassOf _:r6485 ;
rdfs:subClassOf _:r6486 ;
rdfs:subClassOf _:r6487 ;
rdfs:subClassOf _:r6488 ;
rdfs:subClassOf _:r6489 ;
rdfs:subClassOf _:r6490 ;
rdfs:subClassOf _:r6491 ;
rdfs:subClassOf _:r6492 ;
rdfs:subClassOf _:r6493 ;
rdfs:subClassOf _:r6494 ;
rdfs:subClassOf _:r6495 ;
rdfs:subClassOf _:r6496 ;
rdfs:subClassOf _:r6497 ;
rdfs:subClassOf _:r6498 ;
rdfs:subClassOf _:r6499 ;
rdfs:subClassOf _:r6500 ;
skos:broader ngm:bc-governance-and-regulation ;
vc:bridgesTo ngm:infra-legal-and-regulatory ;
vc:bridgesTo ngm:trade-finance ;
vc:contrastsWith ngm:centralised-single-window ;
vc:contrastsWith ngm:manual-customs-clearance ;
vc:contrastsWith ngm:paper-based-trade-documentation ;
vc:contrastsWith ngm:swift-trade-finance ;
vc:contrastsWith ngm:trade-lens ;
vc:dependsOn ngm:api-gateway ;
vc:dependsOn ngm:corda ;
vc:dependsOn ngm:cryptographic-infrastructure ;
vc:dependsOn ngm:gs-1-standards ;
vc:dependsOn ngm:hyperledger-fabric ;
vc:dependsOn ngm:smart-contracts ;
vc:dependsOn ngm:zero-knowledge-proof ;
vc:enables ngm:automated-duty-calculation ;
vc:enables ngm:carbon-border-adjustment ;
vc:enables ngm:coordinated-border-management ;
vc:enables ngm:fraud-detection ;
vc:enables ngm:paperless-trade ;
vc:enables ngm:pre-arrival-clearance ;
vc:enables ngm:traceability ;
vc:enables ngm:trade-finance ;
vc:enables ngm:trade-finance-automation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:advance-cargo-information-system ;
vc:hasPart ngm:authorised-economic-operator ;
vc:hasPart ngm:certificate-of-origin ;
vc:hasPart ngm:customs-declaration ;
vc:hasPart ngm:electronic-bill-of-lading ;
vc:hasPart ngm:risk-assessment-engine ;
vc:hasPart ngm:single-window-system ;
vc:hasPart ngm:smart-contracts ;
vc:hasPart ngm:tariff-classification-system ;
vc:hasPart ngm:trade-finance ;
vc:implements ngm:eu-union-customs-code ;
vc:implements ngm:gs1-epcis ;
vc:implements ngm:hmrc ;
vc:implements ngm:un-cefact-trade-data-standards ;
vc:implements ngm:uncitral-model-law-on-electronic-transferable-records ;
vc:implements ngm:wco-safe-framework ;
vc:implements ngm:wto-trade-facilitation-agreement ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:api-gateway ;
vc:relatedTo ngm:blockchain-as-a-service ;
vc:relatedTo ngm:blockchain-interoperability ;
vc:relatedTo ngm:blockchain-network ;
vc:relatedTo ngm:carbon-credit-tracking ;
vc:relatedTo ngm:cold-chain-monitoring ;
vc:relatedTo ngm:gsbn ;
vc:requires ngm:cryptographic-hash-function ;
vc:requires ngm:cryptographic-infrastructure ;
vc:requires ngm:data-governance-framework ;
vc:requires ngm:digital-identity ;
vc:requires ngm:digital-signature-verification ;
vc:requires ngm:distributed-ledger-technology ;
vc:requires ngm:interoperability-standard ;
vc:requires ngm:interoperability-standards ;
vc:requires ngm:risk-scoring-engine ;
vc:slug "customs-trade-facilitation" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:eu-union-customs-code ;
vc:standardizedBy ngm:gs-1-standards ;
vc:standardizedBy ngm:icc-uniform-customs-and-practice ;
vc:standardizedBy ngm:iso-28000 ;
vc:standardizedBy ngm:un-cefact ;
vc:standardizedBy ngm:uncitral ;
vc:standardizedBy ngm:wco-safe-framework ;
vc:standardizedBy ngm:wto-trade-facilitation-agreement ;
vc:supports ngm:aml-kyc-compliance ;
vc:supports ngm:blockchain-interoperability ;
vc:supports ngm:carbon-credit-tracking ;
vc:supports ngm:carbon-footprint-measurement ;
vc:supports ngm:cold-chain-monitoring ;
vc:supports ngm:logistics-optimisation ;
vc:uses ngm:cryptographic-hash-function ;
vc:uses ngm:decentralized-identifiers ;
vc:uses ngm:did ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:optical-character-recognition ;
vc:uses ngm:zero-knowledge-proof .
ngm:cut-mix a owl:Class ;
rdfs:comment "A data augmentation technique that creates training examples by cutting and pasting patches between images, with labels mixed proportionally to the patch areas. CutMix improves model robustness and localisation ability by forcing attention to less discriminative regions."@en ;
rdfs:label "Cut Mix"@en ;
rdfs:subClassOf ngm:sc-content-and-assets ;
rdfs:subClassOf _:r6501 ;
skos:broader ngm:sc-content-and-assets ;
vc:bridgesTo ngm:computer-vision ;
vc:enables ngm:adversarial-robustness ;
vc:enables ngm:computer-vision ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:isPartOf ngm:data-augmentation-strategies ;
vc:qualityScore "0.0"^^xsd:float ;
vc:requires ngm:training-data ;
vc:slug "cut-mix" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:deep-learning .
ngm:cve a skos:Concept ;
rdfs:label "Cve"@en .
ngm:cvpr a owl:Class ;
rdfs:comment "CVPR (Conference on Computer Vision and Pattern Recognition) is the premier annual peer-reviewed academic conference for computer vision and pattern recognition research, co-sponsored by IEEE and the Computer Vision Foundation (CVF). It is consistently ranked among the most impactful venues in artificial intelligence, serving as the primary publication channel for breakthroughs in image recognition, object detection, semantic segmentation, generative modelling, video understanding, and 3D vision. The conference has been held annually since 1983 and its open-access proceedings, published through the CVF, represent a foundational evidence base for both academic research and applied AI development."@en ;
rdfs:label "CVPR"@en ;
rdfs:subClassOf ngm:academic-conference ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf ngm:scientific-publication-venue ;
rdfs:subClassOf _:r3810 ;
rdfs:subClassOf _:r3811 ;
rdfs:subClassOf _:r3812 ;
rdfs:subClassOf _:r3813 ;
rdfs:subClassOf _:r3814 ;
rdfs:subClassOf _:r3815 ;
rdfs:subClassOf _:r3816 ;
rdfs:subClassOf _:r3817 ;
rdfs:subClassOf _:r3818 ;
rdfs:subClassOf _:r3819 ;
rdfs:subClassOf _:r3820 ;
rdfs:subClassOf _:r3821 ;
skos:broader ngm:ai-research-area ;
vc:bridgesTo ngm:ai-governance ;
vc:bridgesTo ngm:ai-safety ;
vc:bridgesTo ngm:autonomous-driving ;
vc:bridgesTo ngm:large-language-models ;
vc:bridgesTo ngm:medical-image-analysis ;
vc:bridgesTo ngm:reinforcement-learning ;
vc:bridgesTo ngm:robotics ;
vc:bridgesTo ngm:spatial-computing ;
vc:contrastsWith ngm:arxiv-preprint ;
vc:contrastsWith ngm:iccv ;
vc:contrastsWith ngm:iclr ;
vc:contrastsWith ngm:neur-ips ;
vc:dependsOn ngm:computer-vision-foundation ;
vc:dependsOn ngm:ieee ;
vc:dependsOn ngm:peer-review ;
vc:enables ngm:benchmark-standard ;
vc:enables ngm:evaluation-metric ;
vc:enables ngm:open-access-publishing ;
vc:enables ngm:peer-review ;
vc:enables ngm:research-community ;
vc:enables ngm:technology-transfer ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:3-d-gaussian-splatting ;
vc:hasPart ngm:3-d-reconstruction ;
vc:hasPart ngm:autonomous-driving ;
vc:hasPart ngm:generative-vision ;
vc:hasPart ngm:image-classification ;
vc:hasPart ngm:medical-image-analysis ;
vc:hasPart ngm:multimodal-ai-architecture-ai ;
vc:hasPart ngm:neural-radiance-fields ;
vc:hasPart ngm:object-detection ;
vc:hasPart ngm:semantic-segmentation ;
vc:hasPart ngm:video-understanding ;
vc:implements ngm:double-blind-review ;
vc:implements ngm:ethics-review ;
vc:implements ngm:open-science ;
vc:implements ngm:reproducibility-standards ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:aaai ;
vc:relatedTo ngm:academic-conference ;
vc:relatedTo ngm:attention-mechanism ;
vc:relatedTo ngm:computer-vision-foundation ;
vc:relatedTo ngm:convolutional-neural-network ;
vc:relatedTo ngm:eccv ;
vc:relatedTo ngm:iccv ;
vc:relatedTo ngm:iclr ;
vc:relatedTo ngm:icml ;
vc:relatedTo ngm:ieee ;
vc:relatedTo ngm:june-conference-cycle ;
vc:relatedTo ngm:miccai ;
vc:relatedTo ngm:neur-ips ;
vc:relatedTo ngm:nist ;
vc:relatedTo ngm:resnet ;
vc:relatedTo ngm:siggraph ;
vc:relatedTo ngm:transformer-architecture ;
vc:requires ngm:area-chairs ;
vc:requires ngm:computer-vision-foundation ;
vc:requires ngm:double-blind-review ;
vc:requires ngm:ieee ;
vc:requires ngm:programme-chairs ;
vc:slug "cvpr" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:computer-vision-foundation ;
vc:standardizedBy ngm:ieee ;
vc:supports ngm:attention-mechanism ;
vc:supports ngm:computer-vision ;
vc:supports ngm:convolutional-neural-network ;
vc:supports ngm:deep-learning ;
vc:supports ngm:diffusion-models ;
vc:supports ngm:multimodal-ai-architecture-ai ;
vc:supports ngm:neural-network-architecture ;
vc:supports ngm:pattern-recognition ;
vc:uses ngm:arxiv-preprint ;
vc:uses ngm:ieee-xplore ;
vc:uses ngm:openreview .
ngm:cvss a owl:Class ;
rdfs:comment "The Common Vulnerability Scoring System (CVSS) is an open, standardised framework for rating the severity of software vulnerabilities on a 0-10 scale. It decomposes severity into Base, Temporal and Environmental metric groups capturing intrinsic exploitability, real-world threat conditions and organisation-specific impact. CVSS provides a vendor-neutral common language so defenders can compare and prioritise remediation consistently across heterogeneous products."@en ;
rdfs:label "Cvss"@en ;
rdfs:subClassOf ngm:vulnerability-management ;
rdfs:subClassOf _:r6502 ;
vc:bridgesTo ngm:cybersecurity ;
vc:contrastsWith ngm:threat-intelligence ;
vc:dependsOn ngm:vulnerability ;
vc:enables ngm:risk-assessment ;
vc:enables ngm:vulnerability-management ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:vulnerability-management ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:asset-inventory ;
vc:relatedTo ngm:risk-assessment ;
vc:relatedTo ngm:threat-intelligence ;
vc:requires ngm:vulnerability ;
vc:slug "cvss" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:cybersecurity ;
vc:supports ngm:incident-response ;
vc:supports ngm:threat-model ;
vc:uses ngm:vulnerability .
ngm:cxl-consortium a skos:Concept ;
rdfs:label "Cxl Consortium"@en .
ngm:cyber-deterrence a skos:Concept ;
rdfs:label "Cyber Deterrence"@en .
ngm:cyber-doctrine a skos:Concept ;
rdfs:label "Cyber Doctrine"@en .
ngm:cyber-essentials a skos:Concept ;
rdfs:label "Cyber Essentials"@en .
ngm:cyber-insurance a skos:Concept ;
rdfs:label "Cyber Insurance"@en .
ngm:cyber-intelligence a skos:Concept ;
rdfs:label "Cyber Intelligence"@en .
ngm:cyber-mission-force a skos:Concept ;
rdfs:label "Cyber Mission Force"@en .
ngm:cyber-physical-systems a owl:Class ;
rdfs:comment "Cyber Physical Systems (CPS) are engineered systems in which computational elements and physical processes are tightly integrated and coordinated through networked sensing, actuation, and feedback control. They span safety-critical domains including autonomous vehicles, industrial automation, smart grids, medical devices, and aerospace, demanding real-time coordination between embedded computation, heterogeneous communication networks, and physical plant dynamics. CPS extend traditional embedded and control systems by incorporating networked intelligence, adaptive autonomy, and large-scale coordination across geographically distributed components. Their design requires co-engineering of hardware, software, control, and communication layers under stringent timing, reliability, and safety constraints."@en ;
rdfs:label "Cyber Physical Systems"@en ;
rdfs:subClassOf ngm:embedded-systems ;
rdfs:subClassOf _:r6503 ;
rdfs:subClassOf _:r6504 ;
rdfs:subClassOf _:r6505 ;
rdfs:subClassOf _:r6506 ;
rdfs:subClassOf _:r6507 ;
rdfs:subClassOf _:r6508 ;
rdfs:subClassOf _:r6509 ;
rdfs:subClassOf _:r6510 ;
rdfs:subClassOf _:r6511 ;
rdfs:subClassOf _:r6512 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:spatial-computing ;
vc:contrastsWith ngm:information-technology ;
vc:contrastsWith ngm:operational-technology ;
vc:dependsOn ngm:edge-computing ;
vc:dependsOn ngm:internet-of-things ;
vc:dependsOn ngm:network-protocol ;
vc:enables ngm:autonomous-vehicle ;
vc:enables ngm:industrial-automation ;
vc:enables ngm:precision-medicine ;
vc:enables ngm:smart-city ;
vc:enables ngm:smart-grid ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:actuator ;
vc:hasPart ngm:control-loop ;
vc:hasPart ngm:embedded-systems ;
vc:hasPart ngm:real-time-operating-system ;
vc:hasPart ngm:sensor-networks ;
vc:implements ngm:feedback-control ;
vc:implements ngm:pid-controller ;
vc:qualityScore "0.73"^^xsd:float ;
vc:relatedTo ngm:scada ;
vc:relatedTo ngm:security ;
vc:requires ngm:formal-verification ;
vc:requires ngm:functional-safety ;
vc:requires ngm:real-time-computing ;
vc:requires ngm:wireless-communication ;
vc:slug "cyber-physical-systems" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:iec-61508 ;
vc:standardizedBy ngm:iso-26262 ;
vc:supports ngm:industrial-io-t ;
vc:supports ngm:robotics ;
vc:uses ngm:digital-twin ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:model-predictive-control .
ngm:cyber-resilience a owl:Class ;
rdfs:comment "Cyber resilience is the capacity of an organisation or system to anticipate, withstand, recover from, and adapt to adverse cyber events while continuing to deliver its intended outcomes. It extends conventional cybersecurity from breach prevention towards graceful degradation, rapid restoration, and continuous learning under sustained attack. Cyber resilience integrates technical controls, business continuity planning, and governance so that critical functions persist even when individual defences fail."@en ;
rdfs:label "Cyber Resilience"@en ;
rdfs:subClassOf ngm:security ;
rdfs:subClassOf _:r6513 ;
rdfs:subClassOf _:r6514 ;
rdfs:subClassOf _:r6515 ;
rdfs:subClassOf _:r6516 ;
rdfs:subClassOf _:r6517 ;
vc:bridgesTo ngm:disaster-recovery ;
vc:bridgesTo ngm:fault-tolerance ;
vc:dependsOn ngm:network-security ;
vc:dependsOn ngm:redundancy ;
vc:enables ngm:business-continuity ;
vc:enables ngm:fault-tolerance ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:business-continuity ;
vc:hasPart ngm:disaster-recovery ;
vc:hasPart ngm:incident-response ;
vc:isPartOf ngm:security ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:cybersecurity ;
vc:relatedTo ngm:risk-management ;
vc:requires ngm:risk-management ;
vc:requires ngm:threat-intelligence ;
vc:slug "cyber-resilience" ;
vc:sourceDomain "security" ;
vc:supports ngm:security-operations ;
vc:uses ngm:defense-in-depth ;
vc:uses ngm:intrusion-detection ;
vc:uses ngm:intrusion-detection-system ;
vc:uses ngm:zero-trust-architecture .
ngm:cyber-risk a skos:Concept ;
rdfs:label "Cyber Risk"@en .
ngm:cyber-risk-management a skos:Concept ;
rdfs:label "Cyber Risk Management"@en .
ngm:cyber-security-and-cryptography a owl:Class ;
rdfs:comment "Cyber Security and Cryptography is the integrated discipline governing the confidentiality, integrity, availability, and authenticity of digital information systems through mathematical cryptographic primitives, protocol engineering, and systemic security architecture."@en ;
rdfs:label "Cyber Security and Cryptography"@en ;
rdfs:subClassOf ngm:applied-mathematics ;
rdfs:subClassOf ngm:information-security ;
rdfs:subClassOf ngm:infra-security-and-identity ;
rdfs:subClassOf ngm:network-security ;
rdfs:subClassOf ngm:risk-management ;
rdfs:subClassOf ngm:systems-engineering ;
rdfs:subClassOf _:r6518 ;
rdfs:subClassOf _:r6519 ;
rdfs:subClassOf _:r6520 ;
rdfs:subClassOf _:r6521 ;
rdfs:subClassOf _:r6522 ;
rdfs:subClassOf _:r6523 ;
rdfs:subClassOf _:r6524 ;
rdfs:subClassOf _:r6525 ;
rdfs:subClassOf _:r6526 ;
rdfs:subClassOf _:r6527 ;
rdfs:subClassOf _:r6528 ;
rdfs:subClassOf _:r6529 ;
rdfs:subClassOf _:r6530 ;
rdfs:subClassOf _:r6531 ;
rdfs:subClassOf _:r6532 ;
rdfs:subClassOf _:r6533 ;
rdfs:subClassOf _:r6534 ;
rdfs:subClassOf _:r6535 ;
rdfs:subClassOf _:r6536 ;
rdfs:subClassOf _:r6537 ;
rdfs:subClassOf _:r6538 ;
rdfs:subClassOf _:r6539 ;
skos:broader ngm:infra-security-and-identity ;
vc:bridgesTo ngm:applied-mathematics ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:network-security ;
vc:contrastsWith ngm:castle-and-moat-architecture ;
vc:contrastsWith ngm:obscurity-based-security ;
vc:contrastsWith ngm:password-authentication ;
vc:contrastsWith ngm:perimeter-security ;
vc:contrastsWith ngm:symmetric-only-cryptography ;
vc:dependsOn ngm:computational-complexity-theory ;
vc:dependsOn ngm:cryptographic-infrastructure ;
vc:dependsOn ngm:elliptic-curve-cryptography ;
vc:dependsOn ngm:entropy ;
vc:dependsOn ngm:formal-methods ;
vc:dependsOn ngm:lattice-cryptography ;
vc:dependsOn ngm:number-theory ;
vc:enables ngm:authentication ;
vc:enables ngm:data-confidentiality ;
vc:enables ngm:data-integrity ;
vc:enables ngm:digital-sovereignty ;
vc:enables ngm:non-repudiation ;
vc:enables ngm:privacy-engineering ;
vc:enables ngm:regulatory-compliance ;
vc:enables ngm:secure-communication ;
vc:enables ngm:supply-chain-security ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:certificate-authority ;
vc:hasPart ngm:cryptographic-infrastructure ;
vc:hasPart ngm:digital-signature ;
vc:hasPart ngm:hardware-security-module ;
vc:hasPart ngm:homomorphic-encryption ;
vc:hasPart ngm:identity-and-access-management ;
vc:hasPart ngm:key-management ;
vc:hasPart ngm:post-quantum-cryptography ;
vc:hasPart ngm:secure-enclave ;
vc:hasPart ngm:secure-multi-party-computation ;
vc:hasPart ngm:security-operations-centre ;
vc:hasPart ngm:threat-intelligence ;
vc:hasPart ngm:tls ;
vc:hasPart ngm:zero-trust-architecture ;
vc:implements ngm:aes-gcm ;
vc:implements ngm:cha-cha20-poly1305 ;
vc:implements ngm:fido2 ;
vc:implements ngm:homomorphic-encryption ;
vc:implements ngm:post-quantum-cryptography ;
vc:implements ngm:secure-multi-party-computation ;
vc:implements ngm:signal-protocol ;
vc:implements ngm:threshold-signature-scheme ;
vc:implements ngm:tls-1-3 ;
vc:implements ngm:zero-knowledge-proof ;
vc:implements ngm:zero-trust-architecture ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:adversarial-machine-learning ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:digital-forensics ;
vc:relatedTo ngm:gdpr ;
vc:relatedTo ngm:privacy-enhancing-technologies ;
vc:relatedTo ngm:quantum-computation-paradigm ;
vc:relatedTo ngm:regulatory-compliance ;
vc:relatedTo ngm:supply-chain-security ;
vc:requires ngm:certificate-authority ;
vc:requires ngm:cryptographic-primitive ;
vc:requires ngm:entropy ;
vc:requires ngm:hardware-security-module ;
vc:requires ngm:tee ;
vc:requires ngm:threat-model ;
vc:requires ngm:vulnerability-management ;
vc:slug "cyber-security-and-cryptography" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:bsi-germany ;
vc:standardizedBy ngm:enisa ;
vc:standardizedBy ngm:etsi ;
vc:standardizedBy ngm:ietf ;
vc:standardizedBy ngm:iso-iec-27001 ;
vc:standardizedBy ngm:ncsc ;
vc:standardizedBy ngm:nist ;
vc:standardizedBy ngm:oasis ;
vc:supports ngm:blockchain ;
vc:supports ngm:cbdcs ;
vc:supports ngm:cloud-computing ;
vc:supports ngm:critical-national-infrastructure ;
vc:supports ngm:defence-and-intelligence ;
vc:supports ngm:digital-identity ;
vc:supports ngm:financial-services ;
vc:supports ngm:healthcare-data-security ;
vc:uses ngm:hardware-security-module ;
vc:uses ngm:intrusion-detection-system ;
vc:uses ngm:siem ;
vc:uses ngm:soar ;
vc:uses ngm:tee ;
vc:uses ngm:threat-intelligence-platform ;
vc:uses ngm:vulnerability-scanner .
ngm:cyber-security-and-military a owl:Class ;
rdfs:comment "Cyber Security and Military denotes the doctrinal, organisational, technical and operational fusion of cyberspace as a recognised warfighting domain alongside land, sea, air and space — codified by NATO at the 2016 Warsaw Summit declaration that cyberspace is \"a domain of operations in which NATO..."@en ;
rdfs:label "Cyber Security and Military"@en ;
rdfs:subClassOf ngm:cyber-operations ;
rdfs:subClassOf ngm:defence-capability ;
rdfs:subClassOf ngm:infra-security-and-identity ;
rdfs:subClassOf ngm:national-security-capability ;
rdfs:subClassOf ngm:state-sponsored-activity ;
rdfs:subClassOf ngm:warfighting-domain ;
rdfs:subClassOf _:r6540 ;
rdfs:subClassOf _:r6541 ;
rdfs:subClassOf _:r6542 ;
rdfs:subClassOf _:r6543 ;
skos:broader ngm:infra-security-and-identity ;
vc:bridgesTo ngm:governance ;
vc:contrastsWith ngm:civilian-cybersecurity ;
vc:contrastsWith ngm:corporate-information-security ;
vc:contrastsWith ngm:cybercrime ;
vc:contrastsWith ngm:hacktivism ;
vc:contrastsWith ngm:law-enforcement-cyber ;
vc:dependsOn ngm:computer-networks ;
vc:dependsOn ngm:critical-infrastructure ;
vc:dependsOn ngm:cryptography ;
vc:dependsOn ngm:signals-intelligence ;
vc:dependsOn ngm:threat-intelligence ;
vc:dependsOn ngm:vulnerability ;
vc:dependsOn ngm:zero-day-exploits ;
vc:enables ngm:adversary-intelligence-collection ;
vc:enables ngm:battle-damage-assessment ;
vc:enables ngm:critical-infrastructure-disruption ;
vc:enables ngm:cyber-deterrence ;
vc:enables ngm:hybrid-warfare ;
vc:enables ngm:joint-all-domain-operations ;
vc:enables ngm:strategic-coercion ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:computer-network-exploitation ;
vc:hasPart ngm:cyber-intelligence ;
vc:hasPart ngm:cyber-mission-force ;
vc:hasPart ngm:defensive-cyber-operations ;
vc:hasPart ngm:electromagnetic-spectrum-operations ;
vc:hasPart ngm:information-operations ;
vc:hasPart ngm:national-cyber-force ;
vc:hasPart ngm:offensive-cyber-operations ;
vc:implements ngm:computer-network-operations-doctrine ;
vc:implements ngm:defend-forward ;
vc:implements ngm:f3ead-targeting ;
vc:implements ngm:joint-targeting-cycle ;
vc:implements ngm:law-of-armed-conflict ;
vc:implements ngm:persistent-engagement ;
vc:implements ngm:tallinn-manual-rules ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:counter-intelligence ;
vc:relatedTo ngm:drone-warfare ;
vc:relatedTo ngm:electronic-warfare ;
vc:relatedTo ngm:information-warfare ;
vc:relatedTo ngm:space-operations ;
vc:relatedTo ngm:strategic-communication ;
vc:requires ngm:attribution-capability ;
vc:requires ngm:compute-infrastructure ;
vc:requires ngm:cyber-doctrine ;
vc:requires ngm:signals-intelligence ;
vc:requires ngm:sovereign-authority ;
vc:requires ngm:trained-cyber-operators ;
vc:requires ngm:vulnerability ;
vc:slug "cyber-security-and-military" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:iso-27001 ;
vc:standardizedBy ngm:mitre-atlas ;
vc:standardizedBy ngm:nato-ccdcoe ;
vc:standardizedBy ngm:nist-cybersecurity-framework ;
vc:standardizedBy ngm:stix-taxii ;
vc:standardizedBy ngm:tallinn-manual ;
vc:standardizedBy ngm:un-gge ;
vc:supports ngm:allied-coalition-operations ;
vc:supports ngm:counter-proliferation ;
vc:supports ngm:counter-terrorism ;
vc:supports ngm:five-eyes-intelligence ;
vc:supports ngm:national-defence ;
vc:supports ngm:nato-article-5 ;
vc:supports ngm:sanctions-enforcement ;
vc:uses ngm:command-and-control-infrastructure ;
vc:uses ngm:implants ;
vc:uses ngm:initial-access-brokers ;
vc:uses ngm:living-off-the-land-techniques ;
vc:uses ngm:malware ;
vc:uses ngm:supply-chain-compromise ;
vc:uses ngm:wiper-malware ;
vc:uses ngm:zero-day-exploits .
ngm:cybercrime a skos:Concept ;
rdfs:label "Cybercrime"@en .
ngm:cybercrime-investigation a skos:Concept ;
rdfs:label "Cybercrime Investigation"@en .
ngm:cybernetics a owl:Class ;
rdfs:comment "Cybernetics is the transdisciplinary science of regulatory systems, feedback mechanisms, and goal-directed behaviour in animals, machines, and organisations, founded by Norbert Wiener in 1948 to provide a unified framework for understanding how systems use information to maintain stability and achieve purposes across biological, mechanical, and social domains. It centres on the study of circular causal processes — feedback loops — through which a system compares its actual state against a desired state and acts to reduce the discrepancy, extending naturally to concepts of information, communication, control, and self-organisation. Second-order cybernetics extends this to include the observer as a participant in the system being observed, influencing systems theory, cognitive science, constructivism, and AI."@en ;
rdfs:label "Cybernetics"@en ;
rdfs:subClassOf ngm:control-theory ;
rdfs:subClassOf ngm:systems-theory ;
rdfs:subClassOf _:r6544 ;
rdfs:subClassOf _:r6545 ;
rdfs:subClassOf _:r6546 ;
rdfs:subClassOf _:r6547 ;
rdfs:subClassOf _:r6548 ;
rdfs:subClassOf _:r6549 ;
rdfs:subClassOf _:r6550 ;
rdfs:subClassOf _:r6551 ;
rdfs:subClassOf _:r6552 ;
rdfs:subClassOf _:r6553 ;
vc:contrastsWith ngm:open-loop-control ;
vc:dependsOn ngm:feedback-loop ;
vc:dependsOn ngm:signal-processing ;
vc:dependsOn ngm:statistical-mechanics ;
vc:enables ngm:adaptive-control ;
vc:enables ngm:ai-alignment ;
vc:enables ngm:autonomous-system ;
vc:enables ngm:brain-computer-interfaces ;
vc:enables ngm:human-robot-interaction ;
vc:enables ngm:reinforcement-learning ;
vc:enables ngm:self-organisation ;
vc:enables ngm:swarm-intelligence ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:adaptive-control ;
vc:hasPart ngm:closed-loop-control ;
vc:hasPart ngm:feedback-control ;
vc:hasPart ngm:feedback-loop ;
vc:hasPart ngm:homeostasis ;
vc:hasPart ngm:negative-feedback ;
vc:hasPart ngm:positive-feedback ;
vc:implements ngm:control-theory ;
vc:implements ngm:information-theory ;
vc:implements ngm:statistical-mechanics ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:cognitive-science ;
vc:relatedTo ngm:collective-intelligence ;
vc:relatedTo ngm:complex-adaptive-systems ;
vc:relatedTo ngm:emergence ;
vc:relatedTo ngm:evolutionary-computation ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:self-organised-criticality ;
vc:requires ngm:dynamical-systems-theory ;
vc:requires ngm:information-theory ;
vc:requires ngm:signal-processing ;
vc:requires ngm:systems-theory ;
vc:slug "cybernetics" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:ieee-control-systems-society ;
vc:standardizedBy ngm:international-federation-of-automatic-control ;
vc:supports ngm:ai-alignment ;
vc:supports ngm:autonomous-system ;
vc:supports ngm:cognitive-architecture ;
vc:supports ngm:multi-agent-systems ;
vc:supports ngm:neural-network ;
vc:supports ngm:robotics ;
vc:uses ngm:chaos-theory ;
vc:uses ngm:dynamical-systems-theory ;
vc:uses ngm:feedback-control ;
vc:uses ngm:feedback-loop ;
vc:uses ngm:information-theory ;
vc:uses ngm:signal-processing .
ngm:cybersecurity a owl:Class ;
rdfs:comment "Cybersecurity is the discipline concerned with protecting computer systems, networks, and data from unauthorised access, damage, and attack. In the AI governance context it addresses adversarial threats to machine learning models, data poisoning, model extraction, and the use of AI techniques for automated threat detection, vulnerability analysis, and intrusion detection. It overlaps strongly with privacy, encryption, access control, and authentication."@en ;
rdfs:label "Cybersecurity"@en ;
rdfs:subClassOf ngm:information-security ;
rdfs:subClassOf _:r6583 ;
rdfs:subClassOf _:r6584 ;
rdfs:subClassOf _:r6585 ;
rdfs:subClassOf _:r6586 ;
rdfs:subClassOf _:r6587 ;
rdfs:subClassOf _:r6588 ;
vc:bridgesTo ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:distributed-systems ;
vc:contrastsWith ngm:adversarial-machine-learning ;
vc:dependsOn ngm:cryptographic-infrastructure ;
vc:dependsOn ngm:cryptography ;
vc:enables ngm:ai-security ;
vc:enables ngm:data-protection ;
vc:enables ngm:digital-trust ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:endpoint-security ;
vc:hasPart ngm:incident-response ;
vc:hasPart ngm:network-security ;
vc:hasPart ngm:threat-intelligence ;
vc:qualityScore "0.68"^^xsd:float ;
vc:relatedTo ngm:access-control ;
vc:relatedTo ngm:privacy ;
vc:relatedTo ngm:vulnerability ;
vc:relatedTo ngm:zero-trust-architecture ;
vc:requires ngm:identity-and-access-management ;
vc:requires ngm:risk-management ;
vc:slug "cybersecurity" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:iso-27001 ;
vc:standardizedBy ngm:nist-cybersecurity-framework ;
vc:uses ngm:anomaly-detection ;
vc:uses ngm:authentication ;
vc:uses ngm:encryption ;
vc:uses ngm:firewall ;
vc:uses ngm:intrusion-detection-system .
ngm:cybersecurity-evaluation a skos:Concept ;
rdfs:label "Cybersecurity Evaluation"@en .
ngm:cybersecurity-framework a owl:Class ;
rdfs:comment "A cybersecurity framework is a structured set of standards, guidelines and practices that organisations use to identify, protect against, detect, respond to and recover from cyber threats. Frameworks such as the NIST Cybersecurity Framework provide a common taxonomy and maturity model for managing security risk in a repeatable, auditable way. They align technical controls with governance, risk management and regulatory obligations."@en ;
rdfs:label "Cybersecurity Framework"@en ;
rdfs:subClassOf ngm:security-framework ;
rdfs:subClassOf _:r6554 ;
vc:bridgesTo ngm:compliance-framework ;
vc:bridgesTo ngm:risk-management-framework ;
vc:contrastsWith ngm:compliance-framework ;
vc:dependsOn ngm:risk-management ;
vc:enables ngm:ai-trustworthiness ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:risk-management ;
vc:isPartOf ngm:security-framework ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:nist-ai-rmf ;
vc:relatedTo ngm:nist-cybersecurity-framework ;
vc:requires ngm:incident-reporting ;
vc:slug "cybersecurity-framework" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:nist-cybersecurity-framework ;
vc:supports ngm:compliance-framework ;
vc:supports ngm:gdpr-compliance ;
vc:uses ngm:zero-trust-architecture .
ngm:cybersecurity-framework-core a skos:Concept ;
rdfs:label "Cybersecurity Framework Core"@en .
ngm:cybersecurity-framework-govern-function a skos:Concept ;
rdfs:label "Cybersecurity Framework Govern Function"@en .
ngm:cybersecurity-framework-profile a skos:Concept ;
rdfs:label "Cybersecurity Framework Profile"@en .
ngm:cybersecurity-framework-tiers a skos:Concept ;
rdfs:label "Cybersecurity Framework Tiers"@en .
ngm:cybersecurity-governance a skos:Concept ;
rdfs:label "Cybersecurity Governance"@en .
ngm:cybersecurity-law a skos:Concept ;
rdfs:label "Cybersecurity Law"@en .
ngm:cybersecurity-policy a owl:Class ;
rdfs:comment "A cybersecurity policy is a formal set of rules, roles, and expectations that govern how an organisation or jurisdiction protects information systems, data, and networks from threats. It translates risk appetite and legal obligations into actionable standards covering access, incident handling, data protection, and acceptable use. Cybersecurity policy operates at organisational level as internal governance and at national level as regulation and strategy."@en ;
rdfs:label "Cybersecurity Policy"@en ;
rdfs:subClassOf ngm:policy ;
rdfs:subClassOf _:r6555 ;
rdfs:subClassOf _:r6556 ;
rdfs:subClassOf _:r6557 ;
rdfs:subClassOf _:r6558 ;
vc:bridgesTo ngm:digital-governance ;
vc:bridgesTo ngm:regulation ;
vc:dependsOn ngm:cybersecurity ;
vc:enables ngm:compliance ;
vc:enables ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:access-control ;
vc:hasPart ngm:security-policy ;
vc:implements ngm:governance-framework ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:national-security ;
vc:relatedTo ngm:network-security ;
vc:relatedTo ngm:privacy ;
vc:requires ngm:risk-management ;
vc:requires ngm:threat-modelling ;
vc:slug "cybersecurity-policy" ;
vc:sourceDomain "governance" ;
vc:supports ngm:incident-response ;
vc:supports ngm:vulnerability-management ;
vc:uses ngm:encryption .
ngm:cybersecurity-risk-assessment a skos:Concept ;
rdfs:label "Cybersecurity Risk Assessment"@en .
ngm:cybersecurity-risk-management a owl:Class ;
rdfs:comment "A structured discipline for identifying, assessing, prioritising, and treating risks to information systems, data assets, and digital infrastructure arising from threats such as malicious actors, system vulnerabilities, and operational failures. Cybersecurity risk management integrates threat modelling, vulnerability assessment, control selection, and residual risk acceptance into a repeatable governance cycle aligned with organisational risk appetite. Frameworks such as NIST CSF, ISO 27005, and FAIR provide structured methodologies. It bridges technical security practice with executive governance and regulatory compliance."@en ;
rdfs:label "Cybersecurity Risk Management"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf ngm:cybersecurity-framework ;
rdfs:subClassOf ngm:information-security-management ;
rdfs:subClassOf ngm:risk-management ;
rdfs:subClassOf _:r6559 ;
rdfs:subClassOf _:r6560 ;
rdfs:subClassOf _:r6561 ;
rdfs:subClassOf _:r6562 ;
rdfs:subClassOf _:r6563 ;
rdfs:subClassOf _:r6564 ;
rdfs:subClassOf _:r6565 ;
rdfs:subClassOf _:r6566 ;
rdfs:subClassOf _:r6567 ;
rdfs:subClassOf _:r6568 ;
rdfs:subClassOf _:r6569 ;
rdfs:subClassOf _:r6570 ;
rdfs:subClassOf _:r6571 ;
rdfs:subClassOf _:r6572 ;
rdfs:subClassOf _:r6573 ;
skos:broader ngm:artificial-intelligence ;
vc:bridgesTo ngm:ai-risk-management ;
vc:bridgesTo ngm:compliance-framework ;
vc:bridgesTo ngm:governance ;
vc:bridgesTo ngm:security ;
vc:contrastsWith ngm:ai-safety ;
vc:contrastsWith ngm:operational-resilience ;
vc:dependsOn ngm:continuous-monitoring ;
vc:dependsOn ngm:security-operations ;
vc:dependsOn ngm:security-operations-centre ;
vc:dependsOn ngm:siem ;
vc:dependsOn ngm:soar ;
vc:dependsOn ngm:threat-detection ;
vc:enables ngm:accountability ;
vc:enables ngm:compliance-monitoring ;
vc:enables ngm:cyber-resilience ;
vc:enables ngm:governance ;
vc:enables ngm:incident-response ;
vc:enables ngm:operational-resilience ;
vc:enables ngm:resilience ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:compliance-monitoring ;
vc:hasPart ngm:continuous-monitoring ;
vc:hasPart ngm:incident-response ;
vc:hasPart ngm:penetration-testing ;
vc:hasPart ngm:risk-assessment ;
vc:hasPart ngm:risk-register ;
vc:hasPart ngm:threat-modelling ;
vc:hasPart ngm:vulnerability-assessment ;
vc:implements ngm:information-security-management ;
vc:implements ngm:iso-27001 ;
vc:implements ngm:nist-cybersecurity-framework ;
vc:implements ngm:risk-assessment-methodology ;
vc:implements ngm:risk-management ;
vc:implements ngm:security-framework ;
vc:implements ngm:zero-trust-architecture ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:ai-risk-management ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:continuous-monitoring ;
vc:relatedTo ngm:incident-response ;
vc:relatedTo ngm:penetration-testing ;
vc:relatedTo ngm:risk-assessment-methodology ;
vc:relatedTo ngm:supply-chain-security ;
vc:relatedTo ngm:threat-actor ;
vc:requires ngm:continuous-monitoring ;
vc:requires ngm:penetration-testing ;
vc:requires ngm:security-operations ;
vc:requires ngm:security-operations-centre ;
vc:requires ngm:threat-detection ;
vc:requires ngm:threat-modelling ;
vc:requires ngm:vulnerability-assessment ;
vc:slug "cybersecurity-risk-management" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:iso-27001 ;
vc:standardizedBy ngm:nist-cybersecurity-framework ;
vc:supports ngm:accountability ;
vc:supports ngm:compliance-framework ;
vc:supports ngm:cyber-resilience ;
vc:supports ngm:governance ;
vc:supports ngm:operational-resilience ;
vc:supports ngm:resilience ;
vc:uses ngm:risk-assessment ;
vc:uses ngm:risk-register ;
vc:uses ngm:security-framework ;
vc:uses ngm:siem ;
vc:uses ngm:soar ;
vc:uses ngm:threat-modelling ;
vc:uses ngm:vulnerability-assessment ;
vc:uses ngm:zero-trust-architecture .
ngm:cybersecurity-standard a owl:Class ;
rdfs:comment "Cybersecurity standard addresses digital security threats to robot systems through standardised practices for vulnerability assessment, secure communications, authentication, and incident response."@en ;
rdfs:label "Cybersecurity Standard"@en ;
rdfs:subClassOf ngm:robo-safety-and-standards ;
rdfs:subClassOf ngm:robot-standard ;
rdfs:subClassOf ngm:security-standards ;
rdfs:subClassOf _:r6574 ;
rdfs:subClassOf _:r6575 ;
rdfs:subClassOf _:r6576 ;
rdfs:subClassOf _:r6577 ;
rdfs:subClassOf _:r6578 ;
rdfs:subClassOf _:r6579 ;
rdfs:subClassOf _:r6580 ;
rdfs:subClassOf _:r6581 ;
rdfs:subClassOf _:r6582 ;
skos:broader ngm:robo-safety-and-standards ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:security-standards ;
vc:dependsOn ngm:cryptographic-infrastructure ;
vc:dependsOn ngm:device-hardening ;
vc:dependsOn ngm:network-security ;
vc:enables ngm:compliance-assurance ;
vc:enables ngm:malicious-control-prevention ;
vc:enables ngm:protected-data-transmission ;
vc:enables ngm:secure-teleoperation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:access-control ;
vc:hasPart ngm:audit-logging ;
vc:hasPart ngm:authentication-mechanism ;
vc:hasPart ngm:encryption-protocol ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:identity-management ;
vc:requires ngm:secure-communication ;
vc:requires ngm:threat-detection ;
vc:requires ngm:vulnerability-assessment ;
vc:slug "cybersecurity-standard" ;
vc:sourceDomain "robotics" .
ngm:cybersickness a skos:Concept ;
rdfs:label "Cybersickness"@en .
ngm:cyberspace-administration-of-china a skos:Concept ;
rdfs:label "Cyberspace Administration Of China"@en .
ngm:cyborg a skos:Concept ;
rdfs:label "Cyborg"@en .
ngm:cycle-detection a skos:Concept ;
rdfs:label "Cycle Detection"@en .
ngm:cycloidal-drive a owl:Class ;
rdfs:comment "A cycloidal drive is a mechanical speed-reduction gearbox in which an eccentrically mounted cycloidal disc engages a ring of pins to transmit motion at a high reduction ratio. It offers low backlash, high torque density and good shock resistance, making it a favoured actuator component in robot joints and precision positioning systems. Compared with planetary gearing it tolerates impact loads and distributes force across many contact points."@en ;
rdfs:label "Cycloidal Drive"@en ;
rdfs:subClassOf ngm:robo-actuation-and-control ;
skos:broader ngm:robo-actuation-and-control ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:mechanical-component ;
vc:slug "cycloidal-drive" ;
vc:sourceDomain "robotics" .
ngm:cyclonedds a skos:Concept ;
rdfs:label "Cyclonedds"@en .
ngm:cylindrical-robot a owl:Class ;
rdfs:comment "Cylindrical robot employs one rotary joint (azimuth) and two prismatic joints (radial and vertical) that produce a cylindrical workspace, enabling efficient reach over rectangular work envelopes."@en ;
rdfs:label "Cylindrical Robot"@en ;
rdfs:subClassOf ngm:coordinate-robots ;
rdfs:subClassOf ngm:fixed-base-manipulator ;
rdfs:subClassOf ngm:industrial-robot ;
rdfs:subClassOf ngm:robo-actuation-and-control ;
rdfs:subClassOf ngm:robo-robot-type ;
rdfs:subClassOf _:r6589 ;
rdfs:subClassOf _:r6590 ;
skos:broader ngm:robo-actuation-and-control ;
skos:broader ngm:robo-robot-type ;
vc:bridgesTo ngm:spatial-computing-paradigm ;
vc:enables ngm:component-assembly ;
vc:enables ngm:depalletising ;
vc:enables ngm:palletising ;
vc:enables ngm:pick-and-place ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:azimuth-drive ;
vc:hasPart ngm:end-effector-mount ;
vc:hasPart ngm:radial-actuator ;
vc:hasPart ngm:vertical-actuator ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:actuators ;
vc:requires ngm:base-support ;
vc:requires ngm:rotary-joint ;
vc:slug "cylindrical-robot" ;
vc:sourceDomain "robotics" .
ngm:cypher a skos:Concept ;
rdfs:label "Cypher"@en .
ngm:cypher-query-language a owl:Class ;
rdfs:comment "Cypher is a declarative graph query language originally developed by Neo4j for querying property graph databases, using an ASCII-art syntax to express patterns of nodes and relationships intuitively. It allows users to describe graph patterns using parentheses for nodes and arrows for relationships, making queries readable and expressive without requiring deep knowledge of graph traversal algorithms. Cypher has become the basis of the openCypher project and GQL ISO standard, establishing it as a cross-vendor lingua franca for graph databases."@en ;
rdfs:label "Cypher Query Language"@en ;
rdfs:subClassOf ngm:data ;
vc:contrastsWith ngm:gremlin ;
vc:contrastsWith ngm:sparql ;
vc:contrastsWith ngm:sql ;
vc:dependsOn ngm:graph-databases ;
vc:enables ngm:graph-analytics ;
vc:enables ngm:knowledge-graph ;
vc:enables ngm:pattern-matching ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:declarative-programming ;
vc:implements ngm:query-language ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-modelling ;
vc:relatedTo ngm:ontology ;
vc:relatedTo ngm:rdf ;
vc:slug "cypher-query-language" ;
vc:sourceDomain "data" ;
vc:standardizedBy ngm:standards ;
vc:supports ngm:fraud-detection ;
vc:supports ngm:recommendation-system ;
vc:uses ngm:graph-databases ;
vc:uses ngm:property-graph .
ngm:cypherpunk-movement a skos:Concept ;
rdfs:label "Cypherpunk Movement"@en .
ngm:cypherpunk-pseudonymity a skos:Concept ;
rdfs:label "Cypherpunk Pseudonymity"@en .
ngm:d a skos:Concept ;
rdfs:label "D"@en .
ngm:d-id a skos:Concept ;
rdfs:label "D Id"@en .
ngm:d-star a skos:Concept ;
rdfs:label "D Star"@en .
ngm:d-star-lite a skos:Concept ;
rdfs:label "D Star Lite"@en .
ngm:d-yd-x a owl:Class ;
rdfs:comment "dYdX is a decentralised exchange focused on perpetual-futures trading, allowing users to take leveraged long and short positions on cryptocurrencies. Earlier versions operated on Ethereum using a layer-two scaling solution with an off-chain order book and on-chain settlement, while a later version migrated to a purpose-built application-specific blockchain in the Cosmos ecosystem. It combines the order-book trading experience of centralised venues with non-custodial settlement."@en ;
rdfs:label "dYdX"@en ;
rdfs:subClassOf ngm:de-fi ;
rdfs:subClassOf ngm:decentralised-finance-domain ;
rdfs:subClassOf _:r22779 ;
rdfs:subClassOf _:r22780 ;
rdfs:subClassOf _:r22781 ;
rdfs:subClassOf _:r22782 ;
rdfs:subClassOf _:r22783 ;
rdfs:subClassOf _:r22784 ;
vc:bridgesTo ngm:cosmos ;
vc:bridgesTo ngm:derivatives-trading ;
vc:bridgesTo ngm:gmx ;
vc:bridgesTo ngm:layer-2-scaling ;
vc:contrastsWith ngm:automated-market-maker ;
vc:contrastsWith ngm:centralised-exchange ;
vc:contrastsWith ngm:gmx ;
vc:dependsOn ngm:cosmos ;
vc:dependsOn ngm:tendermint-consensus ;
vc:dependsOn ngm:zero-knowledge-rollup ;
vc:enables ngm:leveraged-trading ;
vc:enables ngm:perpetual-futures ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:liquidation-engine ;
vc:hasPart ngm:order-book ;
vc:implements ngm:application-specific-blockchain ;
vc:implements ngm:order-book ;
vc:isPartOf ngm:de-fi ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:decentralised-exchange ;
vc:relatedTo ngm:ethereum ;
vc:requires ngm:collateral-management ;
vc:requires ngm:order-book ;
vc:requires ngm:smart-contract ;
vc:requires ngm:validator-set ;
vc:slug "d-yd-x" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:governance-token ;
vc:uses ngm:on-chain-settlement .
ngm:d2 a skos:Concept ;
rdfs:label "D2"@en .
ngm:d2-diagram-language a skos:Concept ;
rdfs:label "D2 Diagram Language"@en .
ngm:da-2k a skos:Concept ;
rdfs:label "Da 2k"@en .
ngm:dac a skos:Concept ;
rdfs:label "Dac"@en .
ngm:dagger-ci-pipeline-engine a owl:Class ;
rdfs:comment "Dagger is a programmable CI/CD engine that unifies pipeline definition and execution within typed, composable functions authored in general-purpose languages such as Go, Python, or TypeScript. Unlike traditional Dockerfile-and-shell-script approaches, Dagger caches the result of every function call at fine granularity, achieves CI/local parity by running identically on developer machines and cloud runners, and exposes pipelines as strongly-typed APIs discoverable via `dagger functions`."@en ;
rdfs:label "Dagger CI Pipeline Engine"@en ;
rdfs:subClassOf ngm:software-engineering ;
vc:bridgesTo ngm:blockchain ;
vc:enables ngm:machine-learning-discipline-pipeline ;
vc:enables ngm:simulation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:blockchain ;
vc:relatedTo ngm:software-development-process ;
vc:slug "dagger-ci-pipeline-engine" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:software-engineering .
ngm:dai a owl:Class ;
rdfs:comment "DAI is a decentralised stablecoin issued by the MakerDAO protocol on Ethereum that aims to hold a value close to one US dollar through collateral backing."@en ;
rdfs:label "DAI"@en ;
rdfs:subClassOf ngm:stablecoin ;
rdfs:subClassOf _:r6591 ;
rdfs:subClassOf _:r6592 ;
vc:bridgesTo ngm:ethereum-smart-contract-platform ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:maker-dao ;
vc:requires ngm:smart-contract ;
vc:slug "dai" ;
vc:sourceDomain "blockchain" .
ngm:daily-creation-redemption-mechanism a skos:Concept ;
rdfs:label "Daily Creation Redemption Mechanism"@en .
ngm:dall-e-3 a owl:Class ;
rdfs:comment "DALL-E 3 is a text-to-image generation model developed by OpenAI that produces images from natural language descriptions. It improves prompt adherence over earlier versions by reformulating user prompts with a language model."@en ;
rdfs:label "DALL-E 3"@en ;
rdfs:subClassOf ngm:deep-generative-model ;
rdfs:subClassOf ngm:generative-ai ;
rdfs:subClassOf ngm:generative-model ;
rdfs:subClassOf ngm:text-to-image-generation ;
rdfs:subClassOf _:r6593 ;
rdfs:subClassOf _:r6594 ;
rdfs:subClassOf _:r6595 ;
rdfs:subClassOf _:r6596 ;
rdfs:subClassOf _:r6597 ;
rdfs:subClassOf _:r6598 ;
rdfs:subClassOf _:r6599 ;
rdfs:subClassOf _:r6600 ;
rdfs:subClassOf _:r6601 ;
rdfs:subClassOf _:r6602 ;
rdfs:subClassOf _:r6603 ;
rdfs:subClassOf _:r6604 ;
rdfs:subClassOf _:r6605 ;
vc:bridgesTo ngm:generative-ai ;
vc:bridgesTo ngm:generative-ai-engineering ;
vc:bridgesTo ngm:openai-research-organisation ;
vc:bridgesTo ngm:text-to-image-generation ;
vc:contrastsWith ngm:generative-adversarial-network ;
vc:contrastsWith ngm:generative-adversarial-networks ;
vc:contrastsWith ngm:midjourney-text-to-image-service ;
vc:contrastsWith ngm:stable-diffusion-image-model ;
vc:dependsOn ngm:clip ;
vc:dependsOn ngm:clip-encoder ;
vc:dependsOn ngm:diffusion-model ;
vc:dependsOn ngm:language-model ;
vc:dependsOn ngm:latent-diffusion ;
vc:dependsOn ngm:vae ;
vc:enables ngm:creative-tools ;
vc:enables ngm:generative-ai ;
vc:enables ngm:generative-ai-engineering ;
vc:enables ngm:generative-content ;
vc:enables ngm:image-generation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:clip-encoder ;
vc:hasPart ngm:diffusion-model ;
vc:hasPart ngm:latent-diffusion ;
vc:hasPart ngm:vae ;
vc:hasPart ngm:vision-transformer ;
vc:implements ngm:contrastive-learning ;
vc:implements ngm:latent-diffusion ;
vc:implements ngm:latent-diffusion-model-training ;
vc:implements ngm:text-to-image-generation ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:clip ;
vc:relatedTo ngm:deep-generative-model ;
vc:relatedTo ngm:generative-ai ;
vc:relatedTo ngm:generative-ai-engineering ;
vc:relatedTo ngm:generative-design-tool ;
vc:relatedTo ngm:generative-model ;
vc:relatedTo ngm:image-generation ;
vc:relatedTo ngm:latent-diffusion-model-training ;
vc:requires ngm:clip ;
vc:requires ngm:clip-encoder ;
vc:requires ngm:contrastive-learning ;
vc:requires ngm:diffusion-model ;
vc:requires ngm:language-model ;
vc:requires ngm:latent-diffusion ;
vc:requires ngm:vae ;
vc:requires ngm:vision-transformer ;
vc:slug "dall-e-3" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:generative-ai ;
vc:standardizedBy ngm:generative-model ;
vc:supports ngm:creative-tools ;
vc:supports ngm:generative-ai ;
vc:supports ngm:generative-ai-engineering ;
vc:supports ngm:generative-design-tool ;
vc:supports ngm:image-generation ;
vc:uses ngm:clip-encoder ;
vc:uses ngm:contrastive-learning ;
vc:uses ngm:deep-generative-model ;
vc:uses ngm:language-model ;
vc:uses ngm:latent-diffusion ;
vc:uses ngm:vae ;
vc:uses ngm:vision-transformer .
ngm:dama-dmbok a owl:Class ;
rdfs:comment "The DAMA Data Management Body of Knowledge (DAMA-DMBOK) is a reference framework published by DAMA International that codifies the principles, functions, and best practices of enterprise data management. It organises the discipline into knowledge areas such as data governance, data quality, metadata, master data, and data architecture, arranged around a central data governance function. DAMA-DMBOK provides a common vocabulary and standard structure for establishing and assessing data management programmes."@en ;
rdfs:label "Dama Dmbok"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r6734 ;
rdfs:subClassOf _:r6735 ;
rdfs:subClassOf _:r6736 ;
rdfs:subClassOf _:r6737 ;
vc:bridgesTo ngm:data-security ;
vc:enables ngm:compliance ;
vc:enables ngm:data-architecture ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:data-governance ;
vc:hasPart ngm:data-quality ;
vc:hasPart ngm:metadata-management ;
vc:implements ngm:knowledge-management ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-infrastructure ;
vc:relatedTo ngm:regulatory-compliance ;
vc:requires ngm:governance-framework ;
vc:slug "dama-dmbok" ;
vc:sourceDomain "data" ;
vc:standardizedBy ngm:best-practice ;
vc:supports ngm:data-stewardship ;
vc:supports ngm:master-data-management ;
vc:uses ngm:data-catalog ;
vc:uses ngm:data-lineage .
ngm:damages a skos:Concept ;
rdfs:label "Damages"@en .
ngm:daml-ledger a skos:Concept ;
rdfs:label "Daml Ledger"@en .
ngm:damping-action a skos:Concept ;
rdfs:label "Damping Action"@en .
ngm:damping-control a skos:Concept ;
rdfs:label "Damping Control"@en .
ngm:dan-hendrycks a skos:Concept ;
rdfs:label "Dan Hendrycks"@en .
ngm:dandelion a skos:Concept ;
rdfs:label "Dandelion"@en .
ngm:dangerous-capability-detection a skos:Concept ;
rdfs:label "Dangerous Capability Detection"@en .
ngm:dangerous-capability-evaluation a skos:Concept ;
rdfs:label "Dangerous Capability Evaluation"@en .
ngm:dangerous-capability-evaluations a skos:Concept ;
rdfs:label "Dangerous Capability Evaluations"@en .
ngm:danksharding a owl:Class ;
rdfs:comment "Danksharding is a data-availability scaling design for Ethereum that scales the blockchain by providing large amounts of cheap data space for rollups rather than sharding execution. It uses a unified fee market and a merged block-building process in which a single proposer commits to a block containing many data blobs, the availability of which is verified through data-availability sampling and erasure coding. Danksharding is the long-term target architecture that proto-danksharding incrementally builds towards."@en ;
rdfs:label "Danksharding"@en ;
rdfs:subClassOf ngm:sharding ;
rdfs:subClassOf _:r6738 ;
rdfs:subClassOf _:r6739 ;
vc:bridgesTo ngm:optimistic-rollup ;
vc:bridgesTo ngm:zk-rollup ;
vc:dependsOn ngm:beacon-chain ;
vc:dependsOn ngm:data-availability ;
vc:enables ngm:rollup ;
vc:enables ngm:scalability ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:data-availability-sampling ;
vc:implements ngm:erasure-coding ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:ethereum ;
vc:relatedTo ngm:proof-of-stake ;
vc:relatedTo ngm:proto-danksharding ;
vc:requires ngm:blob-transaction ;
vc:requires ngm:kzg-commitment ;
vc:slug "danksharding" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:validator ;
vc:uses ngm:polynomial-commitment .
ngm:dao a owl:Class ;
rdfs:comment "Decentralised Autonomous Organisation operating through transparent code-based rules and distributed governance rather than hierarchical management, enabling community coordination at scale via smart contracts, token-based voting, and on-chain treasury management."@en ;
rdfs:label "DAO"@en ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
rdfs:subClassOf _:r6646 ;
rdfs:subClassOf _:r6647 ;
rdfs:subClassOf _:r6648 ;
rdfs:subClassOf _:r6649 ;
rdfs:subClassOf _:r6650 ;
rdfs:subClassOf _:r6651 ;
skos:broader ngm:bc-governance-and-regulation ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:bridgesTo ngm:metaverse-governance-and-safeguarding ;
vc:contrastsWith ngm:traditional-corporation ;
vc:dependsOn ngm:ethereum ;
vc:dependsOn ngm:layer-2-scaling ;
vc:enables ngm:decentralized-governance ;
vc:enables ngm:on-chain-treasury ;
vc:enables ngm:permissionless-participation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:dao-treasury ;
vc:hasPart ngm:governance-proposal ;
vc:hasPart ngm:voting-mechanism ;
vc:implements ngm:dao-governance ;
vc:qualityScore "0.68"^^xsd:float ;
vc:relatedTo ngm:blockchain-infrastructure ;
vc:relatedTo ngm:dao-governance ;
vc:relatedTo ngm:de-fi-protocol ;
vc:relatedTo ngm:token-economics ;
vc:requires ngm:blockchain-infrastructure ;
vc:requires ngm:distributed-consensus ;
vc:requires ngm:smart-contract-platform ;
vc:slug "dao" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:governance-token ;
vc:uses ngm:multisig-wallet ;
vc:uses ngm:on-chain-voting ;
vc:uses ngm:smart-contract ;
vc:uses ngm:token-weighted-voting .
ngm:dao-analytics a owl:Class ;
rdfs:comment "Specialised data analysis and business intelligence infrastructure providing quantitative insight into Decentralised Autonomous Organisation performance across governance participation, treasury health, delegate accountability, proposal lifecycle dynamics, sybil resistance, and ecosystem-wide..."@en ;
rdfs:label "DAO Analytics"@en ;
rdfs:subClassOf ngm:analytics-platforms ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
rdfs:subClassOf ngm:blockchain-analytics ;
rdfs:subClassOf ngm:data-driven-governance ;
rdfs:subClassOf ngm:decentralised-autonomous-organisation ;
rdfs:subClassOf ngm:governance-tooling ;
rdfs:subClassOf _:r6606 ;
rdfs:subClassOf _:r6607 ;
rdfs:subClassOf _:r6608 ;
rdfs:subClassOf _:r6609 ;
rdfs:subClassOf _:r6610 ;
rdfs:subClassOf _:r6611 ;
rdfs:subClassOf _:r6612 ;
rdfs:subClassOf _:r6613 ;
rdfs:subClassOf _:r6614 ;
rdfs:subClassOf _:r6615 ;
rdfs:subClassOf _:r6616 ;
rdfs:subClassOf _:r6617 ;
rdfs:subClassOf _:r6618 ;
rdfs:subClassOf _:r6619 ;
rdfs:subClassOf _:r6620 ;
skos:broader ngm:bc-governance-and-regulation ;
vc:bridgesTo ngm:blockchain-analytics ;
vc:bridgesTo ngm:dc-communication ;
vc:contrastsWith ngm:centralised-corporate-governance-reporting ;
vc:contrastsWith ngm:closed-source-analytics ;
vc:contrastsWith ngm:manual-governance-audits ;
vc:contrastsWith ngm:opaque-treasury-management ;
vc:contrastsWith ngm:traditional-business-intelligence ;
vc:dependsOn ngm:apache-spark ;
vc:dependsOn ngm:apache-trino ;
vc:dependsOn ngm:aragon ;
vc:dependsOn ngm:compound-governor-bravo ;
vc:dependsOn ngm:dbt-data-build-tool ;
vc:dependsOn ngm:ethereum-smart-contract-platform ;
vc:dependsOn ngm:evm-event-logs ;
vc:dependsOn ngm:gnosis-safe ;
vc:dependsOn ngm:open-zeppelin-governor ;
vc:dependsOn ngm:snapshot ;
vc:dependsOn ngm:the-graph-protocol ;
vc:enables ngm:community-understanding ;
vc:enables ngm:cross-dao-benchmarking ;
vc:enables ngm:data-driven-governance ;
vc:enables ngm:delegate-accountability ;
vc:enables ngm:governance-attack-detection ;
vc:enables ngm:institutional-due-diligence ;
vc:enables ngm:regulatory-reporting ;
vc:enables ngm:retroactive-public-goods-funding ;
vc:enables ngm:sybil-detection ;
vc:enables ngm:treasury-transparency ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:boardroom ;
vc:hasPart ngm:cross-dao-benchmarking ;
vc:hasPart ngm:deep-dao ;
vc:hasPart ngm:delegate-performance-tracker ;
vc:hasPart ngm:dune-analytics ;
vc:hasPart ngm:governance-alert-system ;
vc:hasPart ngm:governance-dashboard ;
vc:hasPart ngm:grant-analytics ;
vc:hasPart ngm:messari ;
vc:hasPart ngm:on-chain-data-indexing ;
vc:hasPart ngm:proposal-lifecycle-analysis ;
vc:hasPart ngm:sybil-resistance ;
vc:hasPart ngm:tally ;
vc:hasPart ngm:treasury-analytics ;
vc:hasPart ngm:voter-participation-metrics ;
vc:hasPart ngm:voting-power-distribution ;
vc:implements ngm:delegate-reputation-score ;
vc:implements ngm:gini-coefficient ;
vc:implements ngm:nakamoto-coefficient ;
vc:implements ngm:proposal-success-rate ;
vc:implements ngm:quadratic-voting ;
vc:implements ngm:sentiment-analysis ;
vc:implements ngm:sybil-clustering ;
vc:implements ngm:treasury-runway-calculation ;
vc:implements ngm:voter-participation-rate ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:delegate-democracy ;
vc:relatedTo ngm:gitcoin-passport ;
vc:relatedTo ngm:grant-programs ;
vc:relatedTo ngm:liquid-democracy ;
vc:relatedTo ngm:maci ;
vc:relatedTo ngm:quadratic-funding ;
vc:relatedTo ngm:retroactive-public-goods-funding ;
vc:relatedTo ngm:sybil-resistance ;
vc:relatedTo ngm:token-economics ;
vc:relatedTo ngm:treasury-management ;
vc:relatedTo ngm:voting-mechanism ;
vc:relatedTo ngm:voting-mechanisms ;
vc:requires ngm:abi-repository ;
vc:requires ngm:block-explorer ;
vc:requires ngm:chainlink ;
vc:requires ngm:ipfs ;
vc:requires ngm:on-chain-data-indexing ;
vc:requires ngm:price-oracle ;
vc:requires ngm:smart-contract-event-decoding ;
vc:requires ngm:snapshot-api ;
vc:requires ngm:subgraph-protocol ;
vc:requires ngm:the-graph-protocol ;
vc:requires ngm:token-holder-mapping ;
vc:slug "dao-analytics" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:eip-4824-dao-uri-standard ;
vc:standardizedBy ngm:metadata-standard ;
vc:standardizedBy ngm:open-zeppelin-governor ;
vc:standardizedBy ngm:snapshot-governance-framework ;
vc:standardizedBy ngm:tally ;
vc:supports ngm:aave-governance ;
vc:supports ngm:arbitrum-dao ;
vc:supports ngm:compound ;
vc:supports ngm:ens-dao ;
vc:supports ngm:gitcoin-grants ;
vc:supports ngm:lido-dao ;
vc:supports ngm:maker-dao ;
vc:supports ngm:nouns-dao ;
vc:supports ngm:optimism-collective ;
vc:supports ngm:optimism-rpgf ;
vc:supports ngm:uniswap-governance ;
vc:uses ngm:apache-parquet ;
vc:uses ngm:dbt-data-build-tool ;
vc:uses ngm:duckdb ;
vc:uses ngm:graph-database ;
vc:uses ngm:graph-databases ;
vc:uses ngm:graph-ql ;
vc:uses ngm:ipfs ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:sql-analytics ;
vc:uses ngm:time-series-analysis ;
vc:uses ngm:zero-knowledge-proof .
ngm:dao-bank-account-opening a skos:Concept ;
rdfs:label "DAO Bank Account Opening"@en .
ngm:dao-contributor-payroll a skos:Concept ;
rdfs:label "DAO Contributor Payroll"@en .
ngm:dao-governance a owl:Class ;
rdfs:comment "DAO governance refers to the decision-making structures and voting mechanisms within Decentralised Autonomous Organisations, enabling token holders to collectively govern protocol parameters, treasury allocations, and organisational direction through on-chain and off-chain processes. Governance rules are encoded as smart contracts that automatically execute approved decisions, supporting a spectrum of voting models including token-weighted, quadratic, delegated, conviction, and reputation-based approaches."@en ;
rdfs:label "DAO Governance"@en ;
rdfs:subClassOf ngm:community-governance ;
rdfs:subClassOf _:r6622 ;
rdfs:subClassOf _:r6623 ;
rdfs:subClassOf _:r6624 ;
rdfs:subClassOf _:r6625 ;
rdfs:subClassOf _:r6626 ;
rdfs:subClassOf _:r6627 ;
rdfs:subClassOf _:r6628 ;
vc:bridgesTo ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:contrastsWith ngm:centralised-governance ;
vc:contrastsWith ngm:corporate-governance ;
vc:dependsOn ngm:cryptographic-signature ;
vc:dependsOn ngm:distributed-ledger ;
vc:enables ngm:decentralised-decision-making ;
vc:enables ngm:protocol-upgrades ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:conviction-voting ;
vc:hasPart ngm:delegated-voting ;
vc:hasPart ngm:holographic-consensus ;
vc:hasPart ngm:on-chain-treasury ;
vc:hasPart ngm:quadratic-voting ;
vc:hasPart ngm:token-weighted-voting ;
vc:implements ngm:liquid-democracy ;
vc:isPartOf ngm:decentralised-autonomous-organisation ;
vc:qualityScore "0.68"^^xsd:float ;
vc:relatedTo ngm:de-fi-protocol ;
vc:relatedTo ngm:token-economics ;
vc:requires ngm:blockchain ;
vc:requires ngm:governance-token ;
vc:requires ngm:smart-contract ;
vc:slug "dao-governance" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:reputation-system ;
vc:uses ngm:snapshot-voting ;
vc:uses ngm:soulbound-tokens .
ngm:dao-governance-for-telecollaboration a owl:Class ;
rdfs:comment "\"The application of decentralised autonomous organisation (DAO) governance mechanisms—token-weighted voting, proposal systems, treasury management—to coordinate geographically distributed teams through on-chain decision-making, enabling democratic, transparent collaboration without centralised ma..."@en ;
rdfs:label "DAO Governance for Telecollaboration"@en ;
rdfs:subClassOf ngm:blockchain-technology ;
rdfs:subClassOf ngm:dc-protocol-and-infra ;
rdfs:subClassOf _:r6621 ;
skos:broader ngm:dc-protocol-and-infra ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:blockchain-technology ;
vc:qualityScore "0.5"^^xsd:float ;
vc:slug "dao-governance-for-telecollaboration" ;
vc:sourceDomain "distributed-collaboration" .
ngm:dao-governance-standards a skos:Concept ;
rdfs:label "DAO Governance Standards"@en .
ngm:dao-grant-programmes a skos:Concept ;
rdfs:label "DAO Grant Programmes"@en .
ngm:dao-legal-structures a owl:Class ;
rdfs:comment "DAO Legal Structures are the corpus of statutory wrappers, jurisdictional incorporation regimes, and bespoke entity forms — spanning US state limited-liability companies, US state unincorporated nonprofit associations, offshore foundation companies, Swiss associations and foundations, Liechtenste..."@en ;
rdfs:label "DAO Legal Structures"@en ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
rdfs:subClassOf ngm:corporate-forms ;
rdfs:subClassOf ngm:governance-structures ;
rdfs:subClassOf ngm:legal-entity-wrappers ;
rdfs:subClassOf ngm:liability-shield-mechanisms ;
rdfs:subClassOf ngm:regulatory-compliance-frameworks ;
rdfs:subClassOf _:r6629 ;
rdfs:subClassOf _:r6630 ;
rdfs:subClassOf _:r6631 ;
skos:broader ngm:bc-governance-and-regulation ;
vc:bridgesTo ngm:governance-structure ;
vc:contrastsWith ngm:charitable-incorporated-organisation ;
vc:contrastsWith ngm:closed-end-investment-fund ;
vc:contrastsWith ngm:general-partnership ;
vc:contrastsWith ngm:sole-proprietorship ;
vc:contrastsWith ngm:stateless-dao ;
vc:contrastsWith ngm:traditional-limited-liability-company ;
vc:contrastsWith ngm:unincorporated-association ;
vc:dependsOn ngm:beneficial-ownership-registers ;
vc:dependsOn ngm:governance-tokens ;
vc:dependsOn ngm:jurisdictional-recognition ;
vc:dependsOn ngm:off-chain-multisig ;
vc:dependsOn ngm:smart-contracts ;
vc:dependsOn ngm:statutory-authorisation ;
vc:enables ngm:bank-account-access ;
vc:enables ngm:contractual-capacity ;
vc:enables ngm:dispute-resolution ;
vc:enables ngm:intellectual-property-ownership ;
vc:enables ngm:legal-personality ;
vc:enables ngm:liability-protection ;
vc:enables ngm:regulatory-engagement ;
vc:enables ngm:tax-treatment-clarity ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:bvi-limited-company ;
vc:hasPart ngm:cayman-foundation-company ;
vc:hasPart ngm:delaware-statutory-trust ;
vc:hasPart ngm:liechtenstein-tvtg-entity ;
vc:hasPart ngm:marshall-islands-dao-llc ;
vc:hasPart ngm:panama-private-interest-foundation ;
vc:hasPart ngm:singapore-variable-capital-company ;
vc:hasPart ngm:swiss-stiftung ;
vc:hasPart ngm:swiss-verein ;
vc:hasPart ngm:tennessee-do ;
vc:hasPart ngm:utah-dao-llc ;
vc:hasPart ngm:vermont-bbllc ;
vc:hasPart ngm:wyoming-dao-llc ;
vc:hasPart ngm:wyoming-duna ;
vc:implements ngm:algorithmic-management-doctrine ;
vc:implements ngm:dual-entity-structure ;
vc:implements ngm:foundation-plus-subsidiary-pattern ;
vc:implements ngm:legal-wrapping-pattern ;
vc:implements ngm:operating-agreement-supremacy ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:bc-0482-eu-mica-regulation ;
vc:relatedTo ngm:cftc-v-ooki-dao ;
vc:relatedTo ngm:corporate-law ;
vc:relatedTo ngm:decentralised-autonomous-organisation ;
vc:relatedTo ngm:howey-test ;
vc:relatedTo ngm:law-commission-dao-report ;
vc:relatedTo ngm:midao ;
vc:relatedTo ngm:otonomos ;
vc:relatedTo ngm:sarcuni-v-bzx-dao ;
vc:relatedTo ngm:securities-regulation ;
vc:relatedTo ngm:tax-treatment ;
vc:requires ngm:aml ;
vc:requires ngm:anti-money-laundering ;
vc:requires ngm:articles-of-organization ;
vc:requires ngm:beneficial-ownership-disclosure ;
vc:requires ngm:bylaws ;
vc:requires ngm:operating-agreement ;
vc:requires ngm:registered-agent ;
vc:requires ngm:tax-identification-number ;
vc:slug "dao-legal-structures" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:bc-0482-eu-mica-regulation ;
vc:standardizedBy ngm:cayman-foundation-companies-act-2017 ;
vc:standardizedBy ngm:coala-model-dao-law ;
vc:standardizedBy ngm:fsma-2023 ;
vc:standardizedBy ngm:liechtenstein-tvtg ;
vc:standardizedBy ngm:marshall-islands-non-profit-entities-amendment-act-2022 ;
vc:standardizedBy ngm:mi-ca-regulation ;
vc:standardizedBy ngm:swiss-civil-code-articles-60-79 ;
vc:standardizedBy ngm:uk-law-commission-report-414 ;
vc:standardizedBy ngm:vermont-title-11-chapter-25 ;
vc:standardizedBy ngm:wyoming-duna-act-2024 ;
vc:standardizedBy ngm:wyoming-sf0038 ;
vc:supports ngm:cross-border-treasury-operations ;
vc:supports ngm:dao-bank-account-opening ;
vc:supports ngm:dao-contributor-payroll ;
vc:supports ngm:dao-grant-programmes ;
vc:supports ngm:dao-trademark-registration ;
vc:supports ngm:regulatory-negotiation-capacity ;
vc:uses ngm:legal-wrapper-service-providers ;
vc:uses ngm:multi-signature-wallet ;
vc:uses ngm:multi-signature-wallets ;
vc:uses ngm:on-chain-voting ;
vc:uses ngm:quadratic-voting ;
vc:uses ngm:smart-contract-governance ;
vc:uses ngm:snapshot-voting ;
vc:uses ngm:token-weighted-voting .
ngm:dao-sustainability a skos:Concept ;
rdfs:label "DAO Sustainability"@en .
ngm:dao-tooling a owl:Class ;
rdfs:comment "DAO Tooling is the integrated software stack of governance platforms, treasury custodians, execution oracles, deliberation forums, identity primitives, analytics layers, and compensation rails that operationalises decentralised autonomous organisations as functioning socio-technical institutions ..."@en ;
rdfs:label "DAO Tooling"@en ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
rdfs:subClassOf ngm:blockchain-infrastructure ;
rdfs:subClassOf ngm:coordination-technology ;
rdfs:subClassOf ngm:governance-infrastructure ;
rdfs:subClassOf ngm:organisational-software ;
rdfs:subClassOf ngm:web3-stack ;
rdfs:subClassOf _:r6632 ;
rdfs:subClassOf _:r6633 ;
rdfs:subClassOf _:r6634 ;
rdfs:subClassOf _:r6635 ;
rdfs:subClassOf _:r6636 ;
rdfs:subClassOf _:r6637 ;
rdfs:subClassOf _:r6638 ;
rdfs:subClassOf _:r6639 ;
rdfs:subClassOf _:r6640 ;
rdfs:subClassOf _:r6641 ;
rdfs:subClassOf _:r6642 ;
rdfs:subClassOf _:r6643 ;
rdfs:subClassOf _:r6644 ;
rdfs:subClassOf _:r6645 ;
skos:broader ngm:bc-governance-and-regulation ;
vc:bridgesTo ngm:dc-communication ;
vc:contrastsWith ngm:centralised-treasury-management ;
vc:contrastsWith ngm:co-operative-governance ;
vc:contrastsWith ngm:corporate-governance ;
vc:contrastsWith ngm:pure-ai-agent-system ;
vc:contrastsWith ngm:shareholder-democracy ;
vc:contrastsWith ngm:traditional-foundation ;
vc:dependsOn ngm:account-abstraction ;
vc:dependsOn ngm:decentralised-identity ;
vc:dependsOn ngm:ens ;
vc:dependsOn ngm:ethereum-smart-contract-platform-virtual-machine ;
vc:dependsOn ngm:ipfs ;
vc:dependsOn ngm:layer-2-networks ;
vc:dependsOn ngm:the-graph ;
vc:enables ngm:decentralised-autonomous-organisation ;
vc:enables ngm:on-chain-governance ;
vc:enables ngm:optimistic-execution ;
vc:enables ngm:permissionless-coordination ;
vc:enables ngm:programmable-treasury ;
vc:enables ngm:quadratic-funding ;
vc:enables ngm:retroactive-public-goods-funding ;
vc:enables ngm:token-weighted-voting ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:analytics-dashboard ;
vc:hasPart ngm:compensation-system ;
vc:hasPart ngm:deliberation-forum ;
vc:hasPart ngm:funding-platform ;
vc:hasPart ngm:governance-platform ;
vc:hasPart ngm:identity-primitive ;
vc:hasPart ngm:legal-wrapper ;
vc:hasPart ngm:oracle ;
vc:hasPart ngm:treasury-management ;
vc:hasPart ngm:voting-mechanism ;
vc:implements ngm:compound-governor-bravo ;
vc:implements ngm:conviction-voting ;
vc:implements ngm:erc-20-votes ;
vc:implements ngm:futarchy ;
vc:implements ngm:gnosis-safe ;
vc:implements ngm:open-zeppelin-governor ;
vc:implements ngm:quadratic-voting ;
vc:implements ngm:reality-eth-oracle ;
vc:implements ngm:snapshot-off-chain-voting ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:de-fi ;
vc:relatedTo ngm:liquid-democracy ;
vc:relatedTo ngm:mechanism-design ;
vc:relatedTo ngm:network-state ;
vc:relatedTo ngm:public-goods-funding ;
vc:relatedTo ngm:tokenomics ;
vc:relatedTo ngm:web3-identity ;
vc:requires ngm:blockchain-network ;
vc:requires ngm:cryptographic-signature ;
vc:requires ngm:decentralised-storage ;
vc:requires ngm:decentralized-storage ;
vc:requires ngm:multi-signature-wallet ;
vc:requires ngm:oracle-network ;
vc:requires ngm:smart-contract ;
vc:requires ngm:token-standard ;
vc:slug "dao-tooling" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:eip-4824 ;
vc:standardizedBy ngm:eip-5805 ;
vc:standardizedBy ngm:eip-6372 ;
vc:standardizedBy ngm:erc-20-votes ;
vc:standardizedBy ngm:erc-20votes ;
vc:standardizedBy ngm:erc-721votes ;
vc:standardizedBy ngm:erc-7390 ;
vc:standardizedBy ngm:open-zeppelin-contracts ;
vc:supports ngm:creator-compensation ;
vc:supports ngm:cross-chain-governance ;
vc:supports ngm:grant-distribution ;
vc:supports ngm:protocol-governance ;
vc:supports ngm:sub-dao-coordination ;
vc:supports ngm:treasury-diversification ;
vc:uses ngm:delegated-voting ;
vc:uses ngm:multi-signature ;
vc:uses ngm:optimistic-oracle ;
vc:uses ngm:timelock-controller ;
vc:uses ngm:token-weighted-voting ;
vc:uses ngm:zero-knowledge-proof .
ngm:dao-trademark-registration a skos:Concept ;
rdfs:label "DAO Trademark Registration"@en .
ngm:dao-treasury a owl:Class ;
rdfs:comment "A DAO treasury is the pool of on-chain assets collectively owned and governed by a decentralised autonomous organisation, typically held in smart contracts and controlled through member governance. It funds operations, grants and incentives, with disbursements authorised by token-weighted votes and executed by multisignature or programmatic controls. Treasury management balances runway, diversification and accountability without a central custodian."@en ;
rdfs:label "Dao Treasury"@en ;
rdfs:subClassOf ngm:dao ;
rdfs:subClassOf _:r6740 ;
rdfs:subClassOf _:r6741 ;
rdfs:subClassOf _:r6742 ;
vc:enables ngm:staking ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:governance-token ;
vc:hasPart ngm:multisig ;
vc:isPartOf ngm:dao ;
vc:isPartOf ngm:decentralized-governance ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:token ;
vc:relatedTo ngm:tokenomics ;
vc:requires ngm:smart-contract ;
vc:slug "dao-treasury" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:decentralized-governance ;
vc:supports ngm:liquidity ;
vc:uses ngm:smart-contract ;
vc:uses ngm:treasury-management .
ngm:dao-treasury-operations a skos:Concept ;
rdfs:label "DAO Treasury Operations"@en .
ngm:daogovernance a owl:Class ;
rdfs:comment "The set of on-chain and off-chain processes by which a decentralised autonomous organisation makes and enforces collective decisions. It covers proposal submission, voting and execution of approved actions through smart contracts."@en ;
rdfs:label "DAOGovernance"@en ;
rdfs:subClassOf ngm:dao ;
rdfs:subClassOf _:r6652 ;
rdfs:subClassOf _:r6653 ;
vc:bridgesTo ngm:decentralized-governance ;
vc:bridgesTo ngm:token ;
vc:enables ngm:quadratic-voting ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:governance ;
vc:requires ngm:smart-contract ;
vc:slug "daogovernance" ;
vc:sourceDomain "blockchain" .
ngm:dapp a owl:Class ;
rdfs:comment "A decentralised application whose backend logic runs on a blockchain or other decentralised network rather than on centrally controlled servers. It typically combines smart contracts with a conventional user interface."@en ;
rdfs:label "DApp"@en ;
rdfs:subClassOf ngm:decentralized-application ;
rdfs:subClassOf _:r6654 ;
vc:bridgesTo ngm:decentralized-application ;
vc:enables ngm:web3 ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:smart-contract ;
vc:slug "dapp" ;
vc:sourceDomain "blockchain" .
ngm:dapp-deployment a skos:Concept ;
rdfs:label "Dapp Deployment"@en .
ngm:dapptools a skos:Concept ;
rdfs:label "Dapptools"@en .
ngm:dapr-agents a skos:Concept ;
rdfs:label "Dapr Agents"@en .
ngm:dario-amodei a skos:Concept ;
rdfs:label "Dario Amodei"@en .
ngm:dark-data a skos:Concept ;
rdfs:label "Dark Data"@en .
ngm:dark-energy a owl:Class ;
rdfs:label "Dark Energy"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:astronomy ;
vc:slug "dark-energy" ;
vc:sourceDomain "space-science-and-systems" .
ngm:dark-environment-vr a skos:Concept ;
rdfs:label "Dark Environment VR"@en .
ngm:dark-forest-theory a skos:Concept ;
rdfs:label "Dark Forest Theory"@en .
ngm:dark-launch a skos:Concept ;
rdfs:label "Dark Launch"@en .
ngm:dark-matter a owl:Class ;
rdfs:label "Dark Matter"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:astronomy ;
vc:slug "dark-matter" ;
vc:sourceDomain "space-science-and-systems" .
ngm:dark-pattern-detection a skos:Concept ;
rdfs:label "Dark Pattern Detection"@en .
ngm:dark-pattern-prohibition a skos:Concept ;
rdfs:label "Dark Pattern Prohibition"@en .
ngm:dark-patterns a skos:Concept ;
rdfs:label "Dark Patterns"@en .
ngm:dark-pool a skos:Concept ;
rdfs:label "Dark Pool"@en .
ngm:dark-web a skos:Concept ;
rdfs:label "Dark Web"@en .
ngm:dark-web-monitoring a skos:Concept ;
rdfs:label "Dark Web Monitoring"@en .
ngm:darknet-market a skos:Concept ;
rdfs:label "Darknet Market"@en .
ngm:darpa-robotics-challenge a skos:Concept ;
rdfs:label "Darpa Robotics Challenge"@en .
ngm:darpa-xai-programme a skos:Concept ;
rdfs:label "Darpa Xai Programme"@en .
ngm:dart a skos:Concept ;
rdfs:label "Dart"@en .
ngm:dash a skos:Concept ;
rdfs:label "Dash"@en .
ngm:dash-adaptive-streaming a skos:Concept ;
rdfs:label "Dash Adaptive Streaming"@en .
ngm:dashboarding a skos:Concept ;
rdfs:label "Dashboarding"@en .
ngm:data a owl:Class ;
rdfs:comment "Data is the recorded representation of facts, observations or measurements in a form suitable for storage, processing and communication. It is the raw material from which information and knowledge are derived through interpretation and analysis, and may be structured, semi-structured or unstructured. Across computing and analytics, data is captured, modelled, stored, transformed and governed throughout a lifecycle that determines its usefulness and trustworthiness."@en ;
rdfs:label "Data"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r7160 ;
rdfs:subClassOf _:r7161 ;
rdfs:subClassOf _:r7162 ;
vc:bridgesTo ngm:data-governance ;
vc:dependsOn ngm:data-quality ;
vc:enables ngm:business-intelligence ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:metadata ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-integration ;
vc:relatedTo ngm:data-management ;
vc:requires ngm:data-model ;
vc:requires ngm:data-storage ;
vc:slug "data" ;
vc:sourceDomain "data" ;
vc:standardizedBy ngm:data-governance ;
vc:supports ngm:data-engineering ;
vc:supports ngm:data-processing ;
vc:uses ngm:data-pipeline .
ngm:data-access-interface a owl:Class ;
rdfs:comment "A Data Access Interface is a formalised contract—such as a REST API, GraphQL endpoint, or SPARQL query service—that mediates structured access to data stores, registries, or knowledge graphs. It enforces authentication, authorisation, and schema validation, decoupling data consumers from underlying storage implementations. In metaverse and spatial computing contexts, data access interfaces expose asset repositories, user identity records, and scene graphs to applications and AI agents."@en ;
rdfs:label "Data Access Interface"@en ;
rdfs:subClassOf ngm:data-management ;
vc:bridgesTo ngm:blockchain ;
vc:enables ngm:data-governance ;
vc:enables ngm:data-interoperability ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:isPartOf ngm:digital-infrastructure ;
vc:qualityScore "0.0"^^xsd:float ;
vc:slug "data-access-interface" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:ai-agent-system ;
vc:supports ngm:data-registry ;
vc:uses ngm:digital-identity .
ngm:data-access-layer a skos:Concept ;
rdfs:label "Data Access Layer"@en .
ngm:data-acquisition a owl:Class ;
rdfs:comment "Data acquisition is the process of gathering raw signals and measurements from sensors and the environment, then conditioning and recording them for downstream use in perception, learning, and control. In robotics it spans sampling sensor streams, time-synchronising heterogeneous sources, and logging structured datasets for training and analysis. High-quality acquisition is foundational because the fidelity of perception and learned policies depends on the data captured."@en ;
rdfs:label "Data Acquisition"@en ;
rdfs:subClassOf ngm:data-collection ;
rdfs:subClassOf _:r6743 ;
rdfs:subClassOf _:r6744 ;
vc:bridgesTo ngm:teleoperation ;
vc:enables ngm:computer-vision ;
vc:enables ngm:perception ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:data-collection ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-collection ;
vc:relatedTo ngm:perception ;
vc:relatedTo ngm:sensor ;
vc:requires ngm:sensor ;
vc:requires ngm:telemetry ;
vc:slug "data-acquisition" ;
vc:sourceDomain "robotics" ;
vc:supports ngm:data-pipeline ;
vc:supports ngm:imitation-learning ;
vc:uses ngm:lidar-sensor ;
vc:uses ngm:sensor ;
vc:uses ngm:sensor-fusion .
ngm:data-act a skos:Concept ;
rdfs:label "Data Act"@en .
ngm:data-adapter a skos:Concept ;
rdfs:label "Data Adapter"@en .
ngm:data-aggregation a owl:Class ;
rdfs:comment "Data aggregation is the systematic process of collecting, combining, and summarising records from multiple heterogeneous sources into a unified, reduced representation suitable for analysis, reporting, or further processing. It encompasses both batch and streaming paradigms, applying operations such as grouping, counting, summing, averaging, and deduplication to transform raw, high-volume data into structured, lower-dimensionality outputs. Aggregation underpins analytical workflows from simple dashboards to complex federated query engines, acting as a bridge between raw data capture and actionable intelligence. It is distinct from raw data replication in that it deliberately reduces detail while preserving statistically significant structure."@en ;
rdfs:label "Data Aggregation"@en ;
rdfs:subClassOf ngm:data-integration ;
rdfs:subClassOf _:r6745 ;
rdfs:subClassOf _:r6746 ;
rdfs:subClassOf _:r6747 ;
rdfs:subClassOf _:r6748 ;
rdfs:subClassOf _:r6749 ;
rdfs:subClassOf _:r6750 ;
rdfs:subClassOf _:r6751 ;
vc:bridgesTo ngm:differential-privacy ;
vc:bridgesTo ngm:federated-learning ;
vc:bridgesTo ngm:semantic-web-linked-data-standard ;
vc:contrastsWith ngm:data-disaggregation ;
vc:contrastsWith ngm:data-replication ;
vc:dependsOn ngm:data-quality ;
vc:dependsOn ngm:metadata-management ;
vc:enables ngm:anomaly-detection ;
vc:enables ngm:business-intelligence ;
vc:enables ngm:community-detection ;
vc:enables ngm:data-warehouse ;
vc:enables ngm:olap ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:batch-processing ;
vc:hasPart ngm:etl-pipeline ;
vc:hasPart ngm:stream-processing ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:data-lake ;
vc:relatedTo ngm:event-sourcing ;
vc:requires ngm:data-integration ;
vc:requires ngm:data-pipeline ;
vc:requires ngm:schema-mapping ;
vc:slug "data-aggregation" ;
vc:sourceDomain "data" ;
vc:supports ngm:federated-learning ;
vc:supports ngm:knowledge-graph ;
vc:supports ngm:machine-learning-discipline ;
vc:uses ngm:apache-spark ;
vc:uses ngm:map-reduce ;
vc:uses ngm:mapreduce ;
vc:uses ngm:message-queue ;
vc:uses ngm:sql .
ngm:data-analysis a owl:Class ;
rdfs:comment "Data analysis is the systematic process of inspecting, cleaning, transforming, and modelling data to extract useful information, support decision-making, and test hypotheses. It encompasses descriptive summarisation, exploratory analysis to surface structure and anomalies, inferential statistics to generalise from samples, and predictive modelling. Data analysis spans manual statistical work through to automated analytics pipelines, and it is the disciplinary core from which data science, business intelligence, and machine-learning workflows draw. Rigorous analysis attends to data quality, sampling bias, and the validity of inferential assumptions."@en ;
rdfs:label "Data Analysis"@en ;
rdfs:subClassOf ngm:process ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.78"^^xsd:float ;
vc:relatedTo ngm:predictive-analytics ;
vc:relatedTo ngm:time-series-analysis ;
vc:slug "data-analysis" ;
vc:sourceDomain "data" ;
vc:uses ngm:data-analytics ;
vc:uses ngm:statistics .
ngm:data-analysis-agent a skos:Concept ;
rdfs:label "Data Analysis Agent"@en .
ngm:data-analysis-service a owl:Class ;
rdfs:label "Data Analysis Service"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-processing ;
vc:slug "data-analysis-service" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:data-analytics a owl:Class ;
rdfs:comment "Data Analytics is the systematic computational examination of raw data sets to uncover patterns, correlations, and actionable insights that support organisational decision-making. It spans four analytical tiers: descriptive analytics (summarising historical state), diagnostic analytics (identifying causes of past events), predictive analytics (forecasting future outcomes via statistical and machine learning models), and prescriptive analytics (recommending optimal actions). Analytics pipelines ingest data from heterogeneous sources, apply transformation and enrichment steps, execute statistical or ML algorithms, and surface results through visualisations, dashboards, and automated alerts. As a discipline, data analytics integrates elements of statistics, computer science, domain knowledge, and data engineering to create measurable business and scientific value."@en ;
rdfs:label "Data Analytics"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r6752 ;
rdfs:subClassOf _:r6753 ;
rdfs:subClassOf _:r6754 ;
rdfs:subClassOf _:r6755 ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:federated-learning ;
vc:bridgesTo ngm:spatial-computing ;
vc:dependsOn ngm:cloud-computing ;
vc:dependsOn ngm:data-processing ;
vc:enables ngm:business-intelligence ;
vc:enables ngm:decision-support ;
vc:enables ngm:real-time-analytics ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:descriptive-analytics ;
vc:hasPart ngm:diagnostic-analytics ;
vc:hasPart ngm:predictive-analytics ;
vc:hasPart ngm:prescriptive-analytics ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:big-data ;
vc:relatedTo ngm:data-engineering ;
vc:relatedTo ngm:etl-pipeline ;
vc:requires ngm:data-governance ;
vc:requires ngm:data-integration ;
vc:requires ngm:data-quality-management ;
vc:slug "data-analytics" ;
vc:sourceDomain "data" ;
vc:uses ngm:data-lake ;
vc:uses ngm:data-pipeline ;
vc:uses ngm:data-visualisation ;
vc:uses ngm:data-warehouse ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:statistical-modelling .
ngm:data-analytics-platform a skos:Concept ;
rdfs:label "Data Analytics Platform"@en .
ngm:data-anarchy a skos:Concept ;
rdfs:label "Data Anarchy"@en .
ngm:data-annotation a owl:Class ;
rdfs:comment "Data Annotation is the process of labeling or tagging raw data (images, text, audio, video) with structured, meaningful labels that provide ground truth for supervised machine learning models, enabling algorithms to learn from human-validated examples."@en ;
rdfs:label "Data Annotation"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:machine-learning-discipline-pipeline ;
rdfs:subClassOf _:r6756 ;
rdfs:subClassOf _:r6757 ;
rdfs:subClassOf _:r6758 ;
rdfs:subClassOf _:r6759 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:data-governance ;
vc:bridgesTo ngm:privacy-regulation ;
vc:contrastsWith ngm:self-supervised-learning ;
vc:contrastsWith ngm:synthetic-data-generation ;
vc:dependsOn ngm:data-collection ;
vc:dependsOn ngm:data-preprocessing ;
vc:enables ngm:active-learning ;
vc:enables ngm:model-evaluation ;
vc:enables ngm:supervised-learning ;
vc:enables ngm:training-data ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:inter-annotator-agreement ;
vc:hasPart ngm:quality-control ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:named-entity-recognition ;
vc:relatedTo ngm:object-detection ;
vc:relatedTo ngm:semantic-segmentation ;
vc:requires ngm:human-annotator ;
vc:requires ngm:raw-data ;
vc:slug "data-annotation" ;
vc:sourceDomain "machine-learning" ;
vc:supports ngm:computer-vision ;
vc:supports ngm:natural-language-processing ;
vc:supports ngm:speech-recognition ;
vc:uses ngm:active-learning ;
vc:uses ngm:crowdsourcing .
ngm:data-anonymization a skos:Concept ;
rdfs:label "Data Anonymization"@en .
ngm:data-anonymization-pipeline a owl:Class ;
rdfs:comment "An automated, multi-stage process that systematically removes, masks, or generalizes personally identifiable information (PII) from datasets to protect individual privacy while preserving data utility for analysis."@en ;
rdfs:label "Data Anonymization Pipeline"@en ;
rdfs:subClassOf ngm:data-protection ;
rdfs:subClassOf ngm:sc-governance-and-safety ;
rdfs:subClassOf _:r6760 ;
rdfs:subClassOf _:r6761 ;
rdfs:subClassOf _:r6762 ;
skos:broader ngm:sc-governance-and-safety ;
vc:bridgesTo ngm:blockchain ;
vc:dependsOn ngm:access-control ;
vc:dependsOn ngm:data-protection ;
vc:dependsOn ngm:identity-management ;
vc:dependsOn ngm:pii-detection ;
vc:enables ngm:differential-privacy ;
vc:enables ngm:gdpr-compliance ;
vc:enables ngm:privacy-preserving-analytics ;
vc:enables ngm:secure-data-sharing ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:de-identification-module ;
vc:hasPart ngm:generalization-engine ;
vc:hasPart ngm:perturbation-function ;
vc:hasPart ngm:pii-detector ;
vc:hasPart ngm:risk-assessor ;
vc:hasPart ngm:suppression-filter ;
vc:isPartOf ngm:compliance-framework ;
vc:isPartOf ngm:data-governance ;
vc:isPartOf ngm:privacy-engineering ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:data-classification ;
vc:requires ngm:privacy-policy ;
vc:requires ngm:risk-assessment ;
vc:slug "data-anonymization-pipeline" ;
vc:sourceDomain "spatial-computing" .
ngm:data-architecture a owl:Class ;
rdfs:comment "Data architecture is the discipline of designing the structures, standards, models and integration patterns that govern how an organisation collects, stores, transforms, moves and consumes data. It defines logical and physical data models, storage technologies, data flows, master data strategies and the policies that ensure consistency, quality and security across systems. As a component of enterprise architecture, it provides the blueprint that aligns data assets with business and analytical requirements."@en ;
rdfs:label "Data Architecture"@en ;
rdfs:subClassOf ngm:enterprise-architecture ;
rdfs:subClassOf _:r6763 ;
rdfs:subClassOf _:r6764 ;
rdfs:subClassOf _:r6765 ;
rdfs:subClassOf _:r6766 ;
rdfs:subClassOf _:r6767 ;
rdfs:subClassOf _:r6768 ;
vc:bridgesTo ngm:data-management ;
vc:contrastsWith ngm:information-architecture ;
vc:dependsOn ngm:data-governance ;
vc:dependsOn ngm:data-management ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:data-lake ;
vc:hasPart ngm:data-pipeline ;
vc:hasPart ngm:data-warehouse ;
vc:hasPart ngm:master-data-management ;
vc:isPartOf ngm:enterprise-architecture ;
vc:isPartOf ngm:information-architecture ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-lake ;
vc:relatedTo ngm:enterprise-architecture ;
vc:requires ngm:data-quality ;
vc:requires ngm:data-standards ;
vc:slug "data-architecture" ;
vc:sourceDomain "data" ;
vc:supports ngm:data-management ;
vc:uses ngm:microservices .
ngm:data-archiving a owl:Class ;
rdfs:label "Data Archiving"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-processing ;
vc:slug "data-archiving" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:data-assimilation a skos:Concept ;
rdfs:label "Data Assimilation"@en .
ngm:data-at-rest-protection a skos:Concept ;
rdfs:label "Data At Rest Protection"@en .
ngm:data-augmentation a owl:Class ;
rdfs:comment "Data augmentation is a machine learning technique that expands a training dataset by applying label-preserving transformations or synthesising new examples from existing data. Typical methods include geometric and photometric image transforms, noise injection, and generative model sampling such as GAN-produced samples, diffusion-model synthesis, and mixing-based strategies such as Mixup and CutMix. It improves model generalisation and robustness, mitigating overfitting when labelled data is scarce. Modern automated augmentation pipelines such as AutoAugment and RandAugment use reinforcement learning or random search to discover optimal policies, while 2024-2026 diffusion-based approaches such as DiffuseMix enable label-preserving generation of high-fidelity training examples that improve performance on imbalanced and low-resource benchmarks."@en ;
rdfs:label "Data Augmentation"@en ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf ngm:machine-learning-discipline-technique ;
rdfs:subClassOf ngm:regularisation ;
rdfs:subClassOf _:r6770 ;
rdfs:subClassOf _:r6771 ;
rdfs:subClassOf _:r6772 ;
rdfs:subClassOf _:r6773 ;
rdfs:subClassOf _:r6774 ;
rdfs:subClassOf _:r6775 ;
rdfs:subClassOf _:r6776 ;
rdfs:subClassOf _:r6777 ;
rdfs:subClassOf _:r6778 ;
rdfs:subClassOf _:r6779 ;
rdfs:subClassOf _:r6780 ;
rdfs:subClassOf _:r6781 ;
vc:contrastsWith ngm:active-learning ;
vc:contrastsWith ngm:data-collection ;
vc:dependsOn ngm:convolutional-neural-network ;
vc:dependsOn ngm:feature-extraction ;
vc:dependsOn ngm:hyperparameter-tuning ;
vc:enables ngm:class-imbalance ;
vc:enables ngm:class-imbalance-mitigation ;
vc:enables ngm:image-classification ;
vc:enables ngm:model-generalisation ;
vc:enables ngm:model-robustness ;
vc:enables ngm:overfitting ;
vc:enables ngm:overfitting-prevention ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:autoaugment ;
vc:hasPart ngm:cut-mix ;
vc:hasPart ngm:diffusion-model ;
vc:hasPart ngm:feature-space-augmentation ;
vc:hasPart ngm:generative-adversarial-networks ;
vc:hasPart ngm:geometric-transformation ;
vc:hasPart ngm:mixup ;
vc:hasPart ngm:noise-injection ;
vc:hasPart ngm:photometric-transformation ;
vc:hasPart ngm:randaugment ;
vc:hasPart ngm:synthetic-data ;
vc:hasPart ngm:vae ;
vc:implements ngm:bias-variance-tradeoff ;
vc:implements ngm:few-shot-learning ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:batch-normalisation ;
vc:relatedTo ngm:bias-variance-tradeoff ;
vc:relatedTo ngm:class-imbalance ;
vc:relatedTo ngm:dropout ;
vc:relatedTo ngm:object-detection ;
vc:relatedTo ngm:regularisation ;
vc:relatedTo ngm:synthetic-data ;
vc:requires ngm:data-collection ;
vc:requires ngm:data-preprocessing ;
vc:requires ngm:deep-learning ;
vc:requires ngm:training-dataset ;
vc:requires ngm:training-pipeline ;
vc:slug "data-augmentation" ;
vc:sourceDomain "machine-learning" ;
vc:supports ngm:computer-vision ;
vc:supports ngm:few-shot-learning ;
vc:supports ngm:medical-imaging ;
vc:supports ngm:natural-language-processing ;
vc:supports ngm:self-supervised-learning ;
vc:supports ngm:semi-supervised-learning ;
vc:supports ngm:speech-recognition ;
vc:supports ngm:supervised-learning ;
vc:supports ngm:transfer-learning ;
vc:uses ngm:diffusion-model ;
vc:uses ngm:generative-adversarial-networks ;
vc:uses ngm:neural-architecture-search ;
vc:uses ngm:reinforcement-learning ;
vc:uses ngm:synthetic-data-generator ;
vc:uses ngm:transformer-architecture ;
vc:uses ngm:vae .
ngm:data-augmentation-strategies a owl:Class ;
rdfs:comment "Techniques that create modified versions of training examples to increase dataset diversity and model robustness. Data augmentation strategies apply transformations that preserve label semantics whilst introducing variation, improving generalisation and reducing overfitting."@en ;
rdfs:label "Data Augmentation Strategies"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf _:r6769 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:computer-vision ;
vc:enables ngm:computer-vision ;
vc:enables ngm:transfer-learning ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:machine-learning-discipline-pipeline ;
vc:requires ngm:training-data ;
vc:slug "data-augmentation-strategies" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:overfitting ;
vc:uses ngm:generative-ai .
ngm:data-availability a owl:Class ;
rdfs:comment "Data availability is the property of a distributed system—most critically blockchain networks and rollup scaling architectures—that guarantees all data necessary to verify and reconstruct network state is published and retrievable by any participant. The core data availability problem arises when a block producer publishes a block header without releasing the underlying transaction data, making it impossible for validators or light clients to verify the block's correctness without downloading all data. Modern solutions combine erasure coding (expanding data such that any sufficient subset allows full reconstruction) with data availability sampling (DAS), enabling light nodes to probabilistically confirm full publication by checking only a small random subset of encoded chunks. Data availability is a foundational primitive in modular blockchain architectures, separating the data publication concern from execution, consensus, and settlement layers."@en ;
rdfs:label "Data Availability"@en ;
rdfs:subClassOf ngm:distributed-systems ;
rdfs:subClassOf _:r6784 ;
rdfs:subClassOf _:r6785 ;
vc:bridgesTo ngm:cdn ;
vc:bridgesTo ngm:distributed-storage ;
vc:contrastsWith ngm:data-withholding-attack ;
vc:contrastsWith ngm:state-availability ;
vc:dependsOn ngm:block-propagation ;
vc:dependsOn ngm:distributed-hash-table ;
vc:enables ngm:blockchain-scalability ;
vc:enables ngm:layer-2-scaling ;
vc:enables ngm:light-client ;
vc:enables ngm:modular-blockchain ;
vc:enables ngm:rollup ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:danksharding ;
vc:implements ngm:proto-danksharding ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:content-addressed-storage ;
vc:relatedTo ngm:data-availability-committee ;
vc:relatedTo ngm:fraud-proof ;
vc:relatedTo ngm:sharding ;
vc:relatedTo ngm:validity-proof ;
vc:relatedTo ngm:zero-knowledge-proof ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:peer-to-peer-network ;
vc:slug "data-availability" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:cryptographic-commitment ;
vc:uses ngm:data-availability-sampling ;
vc:uses ngm:erasure-coding ;
vc:uses ngm:kzg-polynomial-commitment ;
vc:uses ngm:merkle-tree ;
vc:uses ngm:reed-solomon-codes .
ngm:data-availability-committee a skos:Concept ;
rdfs:label "Data Availability Committee"@en .
ngm:data-availability-sampling a owl:Class ;
rdfs:comment "Data availability sampling (DAS) is a technique that lets resource-limited clients gain high statistical confidence that all the data behind a block has been published, without downloading the whole block. Each client requests a few random fragments of an erasure-coded dataset; if enough randomly chosen fragments are returned across many clients, the full data can be reconstructed, so withholding it becomes detectable. DAS is a foundational primitive for scalable, modular blockchains and rollup-centric architectures."@en ;
rdfs:label "Data Availability Sampling"@en ;
rdfs:subClassOf ngm:data-availability ;
rdfs:subClassOf _:r6782 ;
rdfs:subClassOf _:r6783 ;
vc:bridgesTo ngm:rollup ;
vc:dependsOn ngm:peer-to-peer-network ;
vc:enables ngm:light-client ;
vc:enables ngm:scalability ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:erasure-coding ;
vc:implements ngm:data-availability ;
vc:isPartOf ngm:data-availability ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:celestia ;
vc:relatedTo ngm:ethereum ;
vc:relatedTo ngm:fraud-proof ;
vc:relatedTo ngm:light-client ;
vc:requires ngm:erasure-coding ;
vc:slug "data-availability-sampling" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:rollup ;
vc:supports ngm:sharding ;
vc:uses ngm:erasure-coding .
ngm:data-breach a owl:Class ;
rdfs:comment "A Data Breach is a security incident in which sensitive, protected, or confidential data is accessed, disclosed, copied, transmitted, or destroyed by an unauthorised actor, whether through external attack, insider threat, or accidental exposure. In AI contexts, data breaches can compromise training datasets, model weights, inference outputs, or user interaction logs, triggering GDPR notification obligations (within 72 hours to supervisory authorities), regulatory penalties, and reputational damage. AI systems increase both the attack surface (by aggregating and processing large personal-data collections) and the potential for novel breach vectors such as model-inversion attacks and membership-inference attacks that reconstruct or identify individuals from model outputs without direct database access."@en ;
rdfs:label "Data Breach"@en ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:risk ;
rdfs:subClassOf _:r6788 ;
rdfs:subClassOf _:r6789 ;
rdfs:subClassOf _:r6790 ;
rdfs:subClassOf _:r6791 ;
rdfs:subClassOf _:r6792 ;
rdfs:subClassOf _:r6793 ;
rdfs:subClassOf _:r6794 ;
rdfs:subClassOf _:r6795 ;
rdfs:subClassOf _:r6796 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:contrastsWith ngm:differential-privacy ;
vc:contrastsWith ngm:encryption ;
vc:contrastsWith ngm:federated-learning ;
vc:contrastsWith ngm:privacy-preserving-machine-learning ;
vc:contrastsWith ngm:zero-trust-architecture ;
vc:dependsOn ngm:adversarial-attack ;
vc:dependsOn ngm:artificial-intelligence ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:enables ngm:incident-response ;
vc:enables ngm:privacy ;
vc:enables ngm:regulatory-compliance ;
vc:enables ngm:risk-assessment ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:accidental-exposure ;
vc:hasPart ngm:data-exfiltration ;
vc:hasPart ngm:data-poisoning ;
vc:hasPart ngm:external-attack ;
vc:hasPart ngm:insider-threat ;
vc:hasPart ngm:membership-inference ;
vc:hasPart ngm:model-extraction ;
vc:hasPart ngm:model-inversion ;
vc:hasPart ngm:ransomware ;
vc:implements ngm:risk-management ;
vc:implements ngm:threat-intelligence ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:access-control ;
vc:relatedTo ngm:audit-trail ;
vc:relatedTo ngm:cybersecurity ;
vc:relatedTo ngm:data-protection ;
vc:relatedTo ngm:differential-privacy ;
vc:relatedTo ngm:encryption ;
vc:relatedTo ngm:federated-learning ;
vc:relatedTo ngm:gdpr ;
vc:relatedTo ngm:healthcare-ai ;
vc:relatedTo ngm:insider-threat ;
vc:relatedTo ngm:privacy-preserving-data-mining ;
vc:relatedTo ngm:regulatory-compliance ;
vc:relatedTo ngm:vulnerability ;
vc:relatedTo ngm:zero-trust-architecture ;
vc:requires ngm:access-control ;
vc:requires ngm:cybersecurity ;
vc:requires ngm:security ;
vc:requires ngm:vulnerability ;
vc:slug "data-breach" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:audit-trail ;
vc:supports ngm:risk-assessment ;
vc:supports ngm:risk-management ;
vc:supports ngm:threat-intelligence ;
vc:uses ngm:adversarial-attack ;
vc:uses ngm:data-poisoning ;
vc:uses ngm:membership-inference ;
vc:uses ngm:model-extraction ;
vc:uses ngm:model-inversion ;
vc:uses ngm:ransomware .
ngm:data-breach-notification a owl:Class ;
rdfs:comment "Data breach notification is the legal and operational obligation to inform supervisory authorities and, where there is a high risk, affected individuals after a breach of personal data. Frameworks such as the UK and EU GDPR require controllers to report qualifying breaches to the regulator without undue delay, typically within seventy-two hours of becoming aware, and to document the breach regardless of whether it is reportable. The duty turns an internal security incident into a regulated disclosure event, with timing, content and assessment of risk all prescribed by law."@en ;
rdfs:label "Data Breach Notification"@en ;
rdfs:subClassOf ngm:data-protection-law ;
rdfs:subClassOf _:r6786 ;
rdfs:subClassOf _:r6787 ;
vc:bridgesTo ngm:cybersecurity ;
vc:dependsOn ngm:supervisory-authority ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:regulatory-compliance ;
vc:isPartOf ngm:data-protection-law ;
vc:isPartOf ngm:regulatory-compliance ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:cybersecurity ;
vc:relatedTo ngm:gdpr ;
vc:relatedTo ngm:privacy ;
vc:requires ngm:audit-trail ;
vc:requires ngm:incident-response ;
vc:slug "data-breach-notification" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:gdpr ;
vc:supports ngm:data-protection ;
vc:supports ngm:privacy ;
vc:uses ngm:audit-trail ;
vc:uses ngm:incident-response .
ngm:data-brokerage a skos:Concept ;
rdfs:label "Data Brokerage"@en .
ngm:data-brokers a owl:Class ;
rdfs:comment "Data brokers are firms that collect, aggregate, enrich and resell personal and behavioural data about individuals, typically without a direct relationship with those individuals. They assemble profiles from public records, online tracking and commercial sources for marketing, scoring and risk uses. They are a focal point of privacy regulation and surveillance concern because their trade can enable pervasive monitoring and profiling."@en ;
rdfs:label "Data Brokers"@en ;
rdfs:subClassOf ngm:data-management ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:digital-society-surveillance ;
vc:slug "data-brokers" ;
vc:sourceDomain "governance" .
ngm:data-cards a skos:Concept ;
rdfs:label "Data Cards"@en .
ngm:data-catalog a owl:Class ;
rdfs:comment "A data catalog is a centralised, searchable inventory of an organisation's data assets enriched with metadata, descriptions, ownership and usage context. It enables discovery, governance and self-service analytics by indexing datasets, schemas and their relationships, often integrating glossaries and lineage. As a component of metadata management and data fabric architectures it is essential for finding and trusting data at scale."@en ;
rdfs:label "Data Catalog"@en ;
rdfs:subClassOf ngm:data-management ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:data-fabric-architecture ;
vc:relatedTo ngm:metadata-management ;
vc:slug "data-catalog" ;
vc:sourceDomain "data" .
ngm:data-catalogue a owl:Class ;
rdfs:comment "A data catalogue is a centralised, searchable inventory of an organisation's data assets enriched with metadata, descriptions, lineage and usage information. It helps users discover, understand, trust and govern data by linking technical metadata with business context and policies. Modern catalogues often automate metadata harvesting and use collaboration features to capture institutional knowledge."@en ;
rdfs:label "Data Catalogue"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r6797 ;
rdfs:subClassOf _:r6798 ;
rdfs:subClassOf _:r6799 ;
rdfs:subClassOf _:r6800 ;
vc:bridgesTo ngm:data-lake ;
vc:bridgesTo ngm:master-data-management ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:data-dictionary ;
vc:hasPart ngm:data-lineage ;
vc:hasPart ngm:metadata ;
vc:isPartOf ngm:data-management ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-management ;
vc:requires ngm:metadata-management ;
vc:slug "data-catalogue" ;
vc:sourceDomain "data" ;
vc:supports ngm:data-discovery ;
vc:supports ngm:data-governance ;
vc:supports ngm:data-quality ;
vc:uses ngm:data-standards ;
vc:uses ngm:dublin-core .
ngm:data-cataloguing a skos:Concept ;
rdfs:label "Data Cataloguing"@en .
ngm:data-center-energy a skos:Concept ;
rdfs:label "Data Center Energy"@en .
ngm:data-center-infrastructure a owl:Class ;
rdfs:comment "The physical and digital systems, including power, cooling, and networking, required to house and operate large-scale computing and AI workloads."@en ;
rdfs:label "Data Center Infrastructure"@en ;
rdfs:subClassOf ngm:data-storage ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:data-storage ;
vc:relatedTo ngm:gpu-compute ;
vc:slug "data-center-infrastructure" ;
vc:sourceDomain "infrastructure" .
ngm:data-center-investment a skos:Concept ;
rdfs:label "Data Center Investment"@en .
ngm:data-center-moratorium a owl:Class ;
rdfs:comment "Local or state legislative pauses on new data center permits, driven by concerns over energy consumption, noise, and community impact."@en ;
rdfs:label "Data Center Moratorium"@en ;
rdfs:subClassOf ngm:data-governance ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-infrastructure-regulation ;
vc:relatedTo ngm:data-storage ;
vc:slug "data-center-moratorium" ;
vc:sourceDomain "governance" .
ngm:data-center-power-demand a owl:Class ;
rdfs:comment "The increasing energy consumption of data centers driven by AI workloads, impacting grid capacity and energy policy."@en ;
rdfs:label "Data Center Power Demand"@en ;
rdfs:subClassOf ngm:data-storage ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-inference-infrastructure ;
vc:relatedTo ngm:energy-infrastructure-backlog ;
vc:slug "data-center-power-demand" ;
vc:sourceDomain "infrastructure" .
ngm:data-center-sustainability a owl:Class ;
rdfs:comment "The practice of designing and operating data centers to minimize environmental impact through efficient energy use, water management, and carbon reduction."@en ;
rdfs:label "Data Center Sustainability"@en ;
rdfs:subClassOf ngm:cloud-computing ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:cloud-computing ;
vc:relatedTo ngm:data-storage ;
vc:relatedTo ngm:infrastructure ;
vc:slug "data-center-sustainability" ;
vc:sourceDomain "infrastructure" .
ngm:data-centers a owl:Class ;
rdfs:comment "Facilities that house the critical components of an organization's information technology infrastructure, including servers, storage, and networking equipment, essential for large-scale AI computation."@en ;
rdfs:label "Data Centers"@en ;
rdfs:subClassOf ngm:data-storage ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:computational-infrastructure ;
vc:relatedTo ngm:data-storage ;
vc:slug "data-centers" ;
vc:sourceDomain "infrastructure" .
ngm:data-centre a owl:Class ;
rdfs:comment "A data centre is a dedicated facility that houses computing, storage and networking infrastructure together with the power, cooling and physical security needed to operate them reliably. It provides the consolidated environment for hosting servers, cloud services and high-performance workloads such as AI training. Its energy and power demands make efficiency, measured through metrics like PUE, a central operational and sustainability concern."@en ;
rdfs:label "Data Centre"@en ;
rdfs:subClassOf ngm:computing-infrastructure ;
rdfs:subClassOf _:r6801 ;
rdfs:subClassOf _:r6802 ;
rdfs:subClassOf _:r6803 ;
rdfs:subClassOf _:r6804 ;
rdfs:subClassOf _:r6805 ;
rdfs:subClassOf _:r6806 ;
rdfs:subClassOf _:r6807 ;
rdfs:subClassOf _:r6808 ;
rdfs:subClassOf _:r6809 ;
vc:bridgesTo ngm:carbon-footprint ;
vc:bridgesTo ngm:infrastructure ;
vc:bridgesTo ngm:renewable-energy ;
vc:contrastsWith ngm:edge-computing ;
vc:contrastsWith ngm:fog-computing ;
vc:dependsOn ngm:fibre-optic-network ;
vc:dependsOn ngm:power-grid ;
vc:enables ngm:cdn ;
vc:enables ngm:cloud-computing ;
vc:enables ngm:high-availability ;
vc:enables ngm:high-performance-computing ;
vc:enables ngm:model-training ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:cooling-system ;
vc:hasPart ngm:liquid-cooling ;
vc:hasPart ngm:network-switch ;
vc:hasPart ngm:power-distribution-unit ;
vc:hasPart ngm:server ;
vc:isPartOf ngm:cloud-computing ;
vc:qualityScore "0.73"^^xsd:float ;
vc:relatedTo ngm:cdn ;
vc:relatedTo ngm:colocation-services ;
vc:relatedTo ngm:energy-and-power ;
vc:relatedTo ngm:geographic-distribution ;
vc:requires ngm:energy-and-power ;
vc:requires ngm:high-speed-network-connectivity ;
vc:requires ngm:physical-security ;
vc:requires ngm:power-grid ;
vc:requires ngm:renewable-energy ;
vc:slug "data-centre" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:iso-iec-27001 ;
vc:standardizedBy ngm:tier-classification-standard ;
vc:supports ngm:distributed-computing ;
vc:supports ngm:edge-computing ;
vc:supports ngm:failover ;
vc:uses ngm:gpu ;
vc:uses ngm:hot-aisle-cold-aisle-containment ;
vc:uses ngm:power-usage-effectiveness ;
vc:uses ngm:redundancy ;
vc:uses ngm:virtualisation .
ngm:data-centre-ai a skos:Concept ;
rdfs:label "Data Centre AI"@en .
ngm:data-centre-gpu a skos:Concept ;
rdfs:label "Data Centre Gpu"@en .
ngm:data-centre-networking a skos:Concept ;
rdfs:label "Data Centre Networking"@en .
ngm:data-centric-ai a skos:Concept ;
rdfs:label "Data Centric AI"@en .
ngm:data-channel a skos:Concept ;
rdfs:label "Data Channel"@en .
ngm:data-classification a owl:Class ;
rdfs:comment "Data classification is the process of organising data into categories based on its sensitivity, value and regulatory obligations, so that appropriate handling, protection and access controls can be applied consistently. Typical schemes assign labels such as public, internal, confidential and restricted, which then drive encryption, retention, sharing and disposal rules. It is a foundational activity in data governance and information security, enabling organisations to prioritise protection of their most sensitive information and to demonstrate regulatory compliance."@en ;
rdfs:label "Data Classification"@en ;
rdfs:subClassOf ngm:data-governance ;
rdfs:subClassOf _:r6810 ;
rdfs:subClassOf _:r6811 ;
rdfs:subClassOf _:r6812 ;
rdfs:subClassOf _:r6813 ;
vc:dependsOn ngm:data-quality ;
vc:enables ngm:access-control ;
vc:enables ngm:data-loss-prevention ;
vc:enables ngm:data-protection ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:data-lifecycle ;
vc:hasPart ngm:metadata-management ;
vc:isPartOf ngm:data-governance-framework ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-lifecycle ;
vc:relatedTo ngm:data-validation ;
vc:requires ngm:data-governance ;
vc:requires ngm:metadata-management ;
vc:slug "data-classification" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:gdpr ;
vc:supports ngm:data-privacy ;
vc:supports ngm:regulatory-compliance ;
vc:uses ngm:data-stewardship .
ngm:data-classification-system a skos:Concept ;
rdfs:label "Data Classification System"@en .
ngm:data-clean-room a skos:Concept ;
rdfs:label "Data Clean Room"@en .
ngm:data-clean-rooms a skos:Concept ;
rdfs:label "Data Clean Rooms"@en .
ngm:data-cleaning a owl:Class ;
rdfs:comment "Data Cleaning is a artificial intelligence concept and a type of Data Preprocessing. that enables Data Analysis."@en ;
rdfs:label "Data Cleaning"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:data-preprocessing ;
skos:broader ngm:ai-technique ;
vc:enables ngm:data-analysis ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:slug "data-cleaning" ;
vc:sourceDomain "artificial-intelligence" .
ngm:data-cleansing a skos:Concept ;
rdfs:label "Data Cleansing"@en .
ngm:data-collection a owl:Class ;
rdfs:comment "Data collection is the systematic process of gathering raw observations, measurements, or records from primary sources — including sensors, user interactions, instruments, surveys, and web scraping — in a form suitable for storage, processing, and analysis. As a foundational stage of the data lifecycle, it determines the completeness, representativeness, and quality of all downstream analytical products. In machine learning contexts, data collection encompasses sourcing, labelling, and curating training datasets that govern model capability and bias characteristics."@en ;
rdfs:label "Data Collection"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r6814 ;
rdfs:subClassOf _:r6815 ;
rdfs:subClassOf _:r6816 ;
rdfs:subClassOf _:r6817 ;
rdfs:subClassOf _:r6818 ;
rdfs:subClassOf _:r6819 ;
vc:bridgesTo ngm:edge-computing ;
vc:bridgesTo ngm:federated-learning ;
vc:contrastsWith ngm:synthetic-data ;
vc:dependsOn ngm:data-governance ;
vc:dependsOn ngm:data-privacy ;
vc:dependsOn ngm:etl-pipeline ;
vc:enables ngm:data-analysis ;
vc:enables ngm:data-pipeline ;
vc:enables ngm:data-processing ;
vc:enables ngm:machine-learning-discipline ;
vc:enables ngm:training-data ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:data-annotation ;
vc:hasPart ngm:data-labelling ;
vc:hasPart ngm:sampling ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:active-learning ;
vc:relatedTo ngm:data-centric-ai ;
vc:relatedTo ngm:data-provenance ;
vc:relatedTo ngm:data-quality ;
vc:requires ngm:consent-management ;
vc:requires ngm:data-schema ;
vc:requires ngm:io-t-sensor-network ;
vc:slug "data-collection" ;
vc:sourceDomain "data" ;
vc:uses ngm:api-integration ;
vc:uses ngm:crowdsourcing ;
vc:uses ngm:web-scraping .
ngm:data-completeness a owl:Class ;
rdfs:label "Data Completeness"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-data-quality ;
vc:slug "data-completeness" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:data-compression a owl:Class ;
rdfs:comment "Data Compression in AI encompasses techniques for reducing the size of datasets, models, and computational representations while preserving essential information and predictive performance. Key methods include model quantisation (reducing numerical precision of weights), pruning (removing redundant parameters), knowledge distillation (training compact student models from large teachers), and neural compression via autoencoders. These techniques are critical for deploying AI on resource-constrained edge devices and for reducing storage, bandwidth, and energy costs."@en ;
rdfs:label "Data Compression"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf _:r6820 ;
rdfs:subClassOf _:r6821 ;
rdfs:subClassOf _:r6822 ;
rdfs:subClassOf _:r6823 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:network-bandwidth-management ;
vc:bridgesTo ngm:storage-optimisation ;
vc:contrastsWith ngm:full-precision-model ;
vc:dependsOn ngm:information-theory ;
vc:enables ngm:bandwidth-efficient-communication ;
vc:enables ngm:federated-learning ;
vc:enables ngm:model-compression-for-edge ;
vc:enables ngm:on-device-inference ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:entropy-coding ;
vc:hasPart ngm:lossless-compression ;
vc:isPartOf ngm:model-optimisation-and-performance ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:model-pruning-for-edge-deployment ;
vc:relatedTo ngm:neural-architecture-search ;
vc:relatedTo ngm:weight-sharing ;
vc:requires ngm:model-training ;
vc:requires ngm:training-data ;
vc:slug "data-compression" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:ai-inference ;
vc:supports ngm:edge-ai ;
vc:supports ngm:tiny-ml ;
vc:uses ngm:autoencoder ;
vc:uses ngm:knowledge-distillation ;
vc:uses ngm:quantisation ;
vc:uses ngm:sparse-representation .
ngm:data-confidentiality a owl:Class ;
rdfs:comment "The property that data is accessible only to those authorised to view it, protecting information from disclosure to unauthorised parties. It is one of the core objectives of information security."@en ;
rdfs:label "Data Confidentiality"@en ;
rdfs:subClassOf ngm:information-security ;
rdfs:subClassOf _:r6824 ;
vc:bridgesTo ngm:information-security ;
vc:enables ngm:privacy ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:cryptography ;
vc:slug "data-confidentiality" ;
vc:sourceDomain "security" .
ngm:data-connectors a skos:Concept ;
rdfs:label "Data Connectors"@en .
ngm:data-consistency a owl:Class ;
rdfs:comment "Data consistency is the guarantee that data remains valid, coherent and in agreement across copies, transactions and nodes of a system. In distributed systems it spans a spectrum from strong consistency, where all readers observe the latest write, to eventual consistency, where replicas converge over time. It is a core correctness property traded off against availability and latency, and it underpins fault-tolerant data layers."@en ;
rdfs:label "Data Consistency"@en ;
rdfs:subClassOf ngm:distributed-systems ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:data-layer ;
vc:relatedTo ngm:fault-tolerance ;
vc:slug "data-consistency" ;
vc:sourceDomain "infrastructure" .
ngm:data-contracts a owl:Class ;
rdfs:comment "A data contract is a formal, versioned agreement between data producers and consumers that specifies the schema, semantics, quality guarantees and service-level expectations of a dataset or stream. It makes data interfaces explicit and enforceable, enabling automated validation and breaking-change detection in data pipelines. Data contracts are a metadata-management practice that improves reliability and trust across decentralised data ownership."@en ;
rdfs:label "Data Contracts"@en ;
rdfs:subClassOf ngm:data-management ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:metadata-management ;
vc:slug "data-contracts" ;
vc:sourceDomain "data" .
ngm:data-controller a skos:Concept ;
rdfs:label "Data Controller"@en .
ngm:data-corruption a skos:Concept ;
rdfs:label "Data Corruption"@en .
ngm:data-covariance-spectrum a skos:Concept ;
rdfs:label "Data Covariance Spectrum"@en .
ngm:data-curation a owl:Class ;
rdfs:comment "Data curation is the process of collecting, filtering, cleaning, annotating and organising raw data into a coherent, high-quality dataset suitable for training or evaluating machine learning models. It includes deduplication, removal of low-quality or harmful content, balancing of class or source distributions, and documentation of provenance and licensing. Rigorous data curation has a substantial effect on downstream model quality and is increasingly recognised as being as important as model architecture in large-scale AI systems."@en ;
rdfs:label "Data Curation"@en ;
rdfs:subClassOf ngm:data-preprocessing ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:data-preprocessing ;
vc:qualityScore "0.55"^^xsd:float ;
vc:relatedTo ngm:ade20-k ;
vc:relatedTo ngm:common-crawl ;
vc:slug "data-curation" ;
vc:sourceDomain "artificial-intelligence" .
ngm:data-debt a skos:Concept ;
rdfs:label "Data Debt"@en .
ngm:data-deduplication a owl:Class ;
rdfs:comment "Data deduplication is the process of detecting and eliminating redundant copies of data so that only unique instances are retained or referenced. In storage it reduces capacity and bandwidth needs through chunk- or block-level matching, while in data preparation it removes duplicate records to improve quality. It is foundational for clean training data and for identity resolution where records must be matched and merged."@en ;
rdfs:label "Data Deduplication"@en ;
rdfs:subClassOf ngm:data-management ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:identity-resolution ;
vc:relatedTo ngm:training-data ;
vc:slug "data-deduplication" ;
vc:sourceDomain "data" .
ngm:data-definition-language a skos:Concept ;
rdfs:label "Data Definition Language"@en .
ngm:data-destruction a skos:Concept ;
rdfs:label "Data Destruction"@en .
ngm:data-dictionary a owl:Class ;
rdfs:comment "A data dictionary is a centralised, structured repository that describes the data elements of an information system, recording each element's name, definition, data type, format, allowable values, relationships and ownership. It serves as an authoritative reference for the meaning and structure of data, distinct from the data itself, enabling consistent understanding across teams and systems. Data dictionaries underpin data governance, integration and quality assurance by making the semantics of stored data explicit."@en ;
rdfs:label "Data Dictionary"@en ;
rdfs:subClassOf ngm:metadata-management ;
rdfs:subClassOf _:r6825 ;
rdfs:subClassOf _:r6826 ;
rdfs:subClassOf _:r6827 ;
vc:bridgesTo ngm:data-governance ;
vc:contrastsWith ngm:data-catalogue ;
vc:contrastsWith ngm:data-lineage ;
vc:enables ngm:data-quality ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:metadata ;
vc:hasPart ngm:schema ;
vc:isPartOf ngm:data-governance ;
vc:isPartOf ngm:data-management ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-catalogue ;
vc:relatedTo ngm:data-lineage ;
vc:relatedTo ngm:data-quality ;
vc:requires ngm:metadata-management ;
vc:slug "data-dictionary" ;
vc:sourceDomain "data" ;
vc:supports ngm:data-governance ;
vc:supports ngm:data-quality ;
vc:uses ngm:metadata ;
vc:uses ngm:schema .
ngm:data-disaggregation a skos:Concept ;
rdfs:label "Data Disaggregation"@en .
ngm:data-discovery a owl:Class ;
rdfs:comment "Data Discovery is the iterative process of locating, profiling, cataloguing, and contextualising data assets distributed across an organisation's storage systems, databases, data lakes, SaaS applications, and streaming pipelines to make them findable, understandable, and trustworthy for analytics, governance, and compliance purposes. It encompasses automated metadata extraction, schema inference, data profiling (statistical characterisation), lineage tracing (upstream/downstream dependencies), and classification (sensitivity tagging). Data Discovery is foundational to implementing Data Governance frameworks and enabling self-service analytics in data mesh and data fabric architectures."@en ;
rdfs:label "Data Discovery"@en ;
rdfs:subClassOf ngm:data-management ;
vc:enables ngm:data-governance ;
vc:enables ngm:metadata-management ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:slug "data-discovery" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:data-management ;
vc:uses ngm:data-lake ;
vc:uses ngm:metadata-registry .
ngm:data-distribution a skos:Concept ;
rdfs:label "Data Distribution"@en .
ngm:data-distribution-service a owl:Class ;
rdfs:comment "The Data Distribution Service is a middleware standard for real-time, data-centric publish-subscribe communication between distributed system components. It defines a global data space in which publishers and subscribers exchange typed data samples without direct knowledge of one another, governed by configurable quality-of-service policies for reliability, latency, and durability. It is widely used in robotics, autonomous vehicles, and other systems requiring deterministic machine-to-machine messaging."@en ;
rdfs:label "Data Distribution Service"@en ;
rdfs:subClassOf ngm:middleware ;
rdfs:subClassOf _:r6828 ;
rdfs:subClassOf _:r6829 ;
vc:bridgesTo ngm:robotics ;
vc:enables ngm:autonomous-vehicle ;
vc:enables ngm:distributed-systems ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:middleware ;
vc:isPartOf ngm:distributed-systems ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:robot-control ;
vc:relatedTo ngm:ros ;
vc:relatedTo ngm:sensor-fusion ;
vc:requires ngm:quality-of-service ;
vc:requires ngm:real-time-systems ;
vc:slug "data-distribution-service" ;
vc:sourceDomain "robotics" ;
vc:supports ngm:interoperability ;
vc:supports ngm:real-time-communication ;
vc:supports ngm:ros ;
vc:uses ngm:message-broker ;
vc:uses ngm:quality-of-service .
ngm:data-drift a owl:Class ;
rdfs:comment "Data drift is the change over time in the statistical distribution of the input data fed to a deployed machine learning model relative to the distribution it was trained on. Unlike concept drift, which alters the relationship between inputs and targets, data drift (also called covariate or feature drift) shifts the marginal distribution of the features themselves and can silently degrade model accuracy even when the learned mapping remains valid. Detecting and responding to data drift is a central concern of model monitoring and MLOps, typically driving alerts, scheduled retraining, or fallback policies."@en ;
rdfs:label "Data Drift"@en ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf _:r6830 ;
vc:bridgesTo ngm:mlops ;
vc:contrastsWith ngm:concept-drift ;
vc:dependsOn ngm:feature-distribution ;
vc:dependsOn ngm:probability-distribution ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:model-monitoring ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:anomaly-detection ;
vc:relatedTo ngm:covariate-shift ;
vc:relatedTo ngm:distribution-shift ;
vc:requires ngm:retraining ;
vc:slug "data-drift" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:density-estimation ;
vc:uses ngm:statistics .
ngm:data-drift-detection a skos:Concept ;
rdfs:label "Data Drift Detection"@en .
ngm:data-driven-discovery a skos:Concept ;
rdfs:label "Data Driven Discovery"@en .
ngm:data-driven-governance a skos:Concept ;
rdfs:label "Data Driven Governance"@en .
ngm:data-driven-healthcare a skos:Concept ;
rdfs:label "Data Driven Healthcare"@en .
ngm:data-driven-learning a skos:Concept ;
rdfs:label "Data Driven Learning"@en .
ngm:data-durability a skos:Concept ;
rdfs:label "Data Durability"@en .
ngm:data-efficiency a skos:Concept ;
rdfs:label "Data Efficiency"@en .
ngm:data-efficient-learning a owl:Class ;
rdfs:comment "Data Efficient Learning encompasses machine learning techniques that achieve strong generalisation from limited labelled training examples, including transfer learning, few-shot learning, semi-supervised learning, data augmentation, and self-supervised pretraining. These methods address real-world constraints where large annotated datasets are impractical to obtain, making AI deployable in specialised or resource-constrained domains."@en ;
rdfs:label "Data Efficient Learning"@en ;
rdfs:subClassOf ngm:ai-technique ;
skos:broader ngm:ai-technique ;
vc:enables ngm:active-learning ;
vc:enables ngm:federated-learning ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:contrastive-learning ;
vc:relatedTo ngm:curriculum-learning ;
vc:slug "data-efficient-learning" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:synthetic-data ;
vc:uses ngm:transfer-learning .
ngm:data-element a skos:Concept ;
rdfs:label "Data Element"@en .
ngm:data-elements a skos:Concept ;
rdfs:label "Data Elements"@en .
ngm:data-encoding a skos:Concept ;
rdfs:label "Data Encoding"@en .
ngm:data-encryption a skos:Concept ;
rdfs:label "Data Encryption"@en .
ngm:data-encryption-at-rest a skos:Concept ;
rdfs:label "Data Encryption At Rest"@en .
ngm:data-encryption-standards a skos:Concept ;
rdfs:label "Data Encryption Standards"@en .
ngm:data-engineering a owl:Class ;
rdfs:comment "Data Engineering is the discipline concerned with designing, building and operating the systems that collect, store, transform and serve data at scale. It covers data pipelines, storage architectures, batch and streaming processing, data modelling and the orchestration and monitoring of workflows. Its purpose is to make reliable, well-structured data available for analytics, reporting and machine learning."@en ;
rdfs:label "Data Engineering"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf ngm:infrastructure-domain ;
rdfs:subClassOf _:r6831 ;
rdfs:subClassOf _:r6832 ;
rdfs:subClassOf _:r6833 ;
rdfs:subClassOf _:r6834 ;
rdfs:subClassOf _:r6835 ;
rdfs:subClassOf _:r6836 ;
rdfs:subClassOf _:r6837 ;
rdfs:subClassOf _:r6838 ;
rdfs:subClassOf _:r6839 ;
rdfs:subClassOf _:r6840 ;
vc:bridgesTo ngm:cloud-infrastructure ;
vc:bridgesTo ngm:data-science ;
vc:bridgesTo ngm:machine-learning-operations ;
vc:bridgesTo ngm:stream-processing ;
vc:contrastsWith ngm:data-science ;
vc:enables ngm:business-intelligence ;
vc:enables ngm:data-science ;
vc:enables ngm:machine-learning-discipline ;
vc:enables ngm:machine-learning-domain ;
vc:enables ngm:real-time-analytics ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:data-lake ;
vc:hasPart ngm:data-pipeline ;
vc:hasPart ngm:data-warehouse ;
vc:hasPart ngm:etl-pipeline ;
vc:hasPart ngm:orchestration ;
vc:hasPart ngm:stream-processing ;
vc:implements ngm:data-lineage ;
vc:implements ngm:data-quality-management ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:data-mesh ;
vc:relatedTo ngm:lakehouse-architecture ;
vc:requires ngm:data-modelling ;
vc:requires ngm:distributed-systems ;
vc:requires ngm:distributed-systems-domain ;
vc:requires ngm:schema-management ;
vc:slug "data-engineering" ;
vc:sourceDomain "data" ;
vc:supports ngm:data-governance ;
vc:supports ngm:data-observability ;
vc:uses ngm:apache-kafka ;
vc:uses ngm:apache-spark ;
vc:uses ngm:object-storage .
ngm:data-ensemble a owl:Class ;
rdfs:label "Data Ensemble"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-collection ;
vc:relatedTo ngm:earth-observation-processing ;
vc:slug "data-ensemble" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:data-erasure a skos:Concept ;
rdfs:label "Data Erasure"@en .
ngm:data-ethics a skos:Concept ;
rdfs:label "Data Ethics"@en .
ngm:data-exchange a owl:Class ;
rdfs:comment "Data Exchange refers to the structured transfer of data between systems, organisations, or parties using agreed-upon formats, protocols, and governance frameworks, enabling interoperability without requiring identical internal architectures. It encompasses both technical standards (APIs, file formats, serialisation protocols) and organisational arrangements (data sharing agreements, trust frameworks, data marketplaces) that govern how data flows across boundaries. Modern data exchange platforms provide cataloguing, consent management, lineage tracking, and value exchange mechanisms alongside raw data transfer."@en ;
rdfs:label "Data Exchange"@en ;
rdfs:subClassOf ngm:data-interoperability ;
rdfs:subClassOf ngm:infrastructure ;
skos:broader ngm:infrastructure ;
vc:bridgesTo ngm:data-sovereignty ;
vc:dependsOn ngm:data-governance ;
vc:dependsOn ngm:network-infrastructure ;
vc:enables ngm:data-integration ;
vc:enables ngm:data-marketplace ;
vc:enables ngm:interoperability ;
vc:enables ngm:open-data ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-pipeline ;
vc:relatedTo ngm:edi ;
vc:relatedTo ngm:messaging ;
vc:slug "data-exchange" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:standards ;
vc:supports ngm:healthcare-interoperability ;
vc:supports ngm:open-banking ;
vc:supports ngm:supply-chain ;
vc:uses ngm:api ;
vc:uses ngm:data-format ;
vc:uses ngm:data-serialization ;
vc:uses ngm:encryption .
ngm:data-exchange-format a owl:Class ;
rdfs:comment "A data exchange format is an agreed structure and encoding for representing data so that it can be reliably transmitted, stored, and interpreted between independent systems. It defines syntax, data types, and often a schema, allowing a producer and a consumer that share no internal code to exchange information without loss of meaning. Common examples include JSON, XML, CSV, and binary formats such as Protocol Buffers, each trading off readability, compactness, and parsing speed."@en ;
rdfs:label "Data Exchange Format"@en ;
rdfs:subClassOf ngm:data-format ;
rdfs:subClassOf _:r6841 ;
rdfs:subClassOf _:r6842 ;
rdfs:subClassOf _:r6843 ;
vc:bridgesTo ngm:interoperability ;
vc:contrastsWith ngm:data-model ;
vc:dependsOn ngm:data-serialization ;
vc:enables ngm:api ;
vc:enables ngm:interoperability ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:metadata ;
vc:hasPart ngm:schema ;
vc:implements ngm:data-serialization ;
vc:isPartOf ngm:interoperability ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-standards ;
vc:relatedTo ngm:protobuf ;
vc:relatedTo ngm:protocol-buffer ;
vc:requires ngm:schema ;
vc:slug "data-exchange-format" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:standardisation ;
vc:supports ngm:api ;
vc:uses ngm:json-data-interchange-format ;
vc:uses ngm:xml .
ngm:data-exfiltration a skos:Concept ;
rdfs:label "Data Exfiltration"@en .
ngm:data-fabric a owl:Class ;
rdfs:comment "A data fabric is an architectural approach that provides a unified, metadata-driven layer for accessing, integrating and governing data across heterogeneous and distributed sources. It uses active metadata, knowledge graphs and automation to connect data without forcing physical consolidation. By abstracting underlying systems it delivers consistent discovery, access and governance, reducing the friction of fragmented data estates."@en ;
rdfs:label "Data Fabric"@en ;
rdfs:subClassOf ngm:data-management ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:metadata-management ;
vc:slug "data-fabric" ;
vc:sourceDomain "data" .
ngm:data-fabric-architecture a owl:Class ;
rdfs:comment "An integrated data-management architecture that provides unified access, governance, security, and orchestration across distributed and heterogeneous data sources through active metadata management, automated data integration, and policy-driven controls."@en ;
rdfs:label "Data Fabric Architecture"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r6844 ;
rdfs:subClassOf _:r6845 ;
rdfs:subClassOf _:r6846 ;
rdfs:subClassOf _:r6847 ;
rdfs:subClassOf _:r6848 ;
rdfs:subClassOf _:r6849 ;
rdfs:subClassOf _:r6850 ;
rdfs:subClassOf _:r6851 ;
rdfs:subClassOf _:r6852 ;
rdfs:subClassOf _:r6853 ;
rdfs:subClassOf _:r6854 ;
rdfs:subClassOf _:r6855 ;
rdfs:subClassOf _:r6856 ;
vc:bridgesTo ngm:blockchain ;
vc:dependsOn ngm:knowledge-graph ;
vc:dependsOn ngm:policy-engine ;
vc:dependsOn ngm:semantic-layer ;
vc:enables ngm:cross-domain-governance ;
vc:enables ngm:data-lineage-tracking ;
vc:enables ngm:federated-queries ;
vc:enables ngm:self-service-analytics ;
vc:enables ngm:unified-data-access ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:access-control ;
vc:hasPart ngm:data-catalog ;
vc:hasPart ngm:data-integration ;
vc:hasPart ngm:data-virtualization ;
vc:hasPart ngm:governance-framework ;
vc:hasPart ngm:metadata-management ;
vc:isPartOf ngm:data-management ;
vc:isPartOf ngm:enterprise-architecture ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:api-gateway ;
vc:requires ngm:data-schema ;
vc:requires ngm:distributed-storage ;
vc:requires ngm:identity-management ;
vc:requires ngm:metadata-repository ;
vc:slug "data-fabric-architecture" ;
vc:sourceDomain "infrastructure" .
ngm:data-federation a owl:Class ;
rdfs:comment "Data federation is a data integration technique that presents multiple distributed and heterogeneous data sources as a single virtual database queryable in place, without physically moving or copying the data. A federation engine decomposes queries, pushes work to source systems and combines results on the fly. It enables real-time unified access and is a core mechanism behind data virtualization and integration interfaces."@en ;
rdfs:label "Data Federation"@en ;
rdfs:subClassOf ngm:data-management ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:data-integration-interface ;
vc:relatedTo ngm:data-virtualization ;
vc:slug "data-federation" ;
vc:sourceDomain "data" .
ngm:data-feed a skos:Concept ;
rdfs:label "Data Feed"@en .
ngm:data-fidelity-term a skos:Concept ;
rdfs:label "Data Fidelity Term"@en .
ngm:data-flow-architecture a skos:Concept ;
rdfs:label "Data Flow Architecture"@en .
ngm:data-flow-diagram a owl:Class ;
rdfs:comment "A data flow diagram (DFD) is a visual representation of how data moves through a system, showing processes, data stores, external entities, and the trust boundaries between them. In security practice it is the standard input artefact for threat modelling, since attack surfaces and applicable threats are identified by walking each flow and boundary crossing in the diagram. It is a structural tool rather than a behavioural one, deliberately omitting control flow and timing to keep the focus on where data moves and where it is trusted less."@en ;
rdfs:label "Data Flow Diagram"@en ;
rdfs:subClassOf ngm:threat-modelling ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:threat-modelling ;
vc:qualityScore "0.6"^^xsd:float ;
vc:slug "data-flow-diagram" ;
vc:sourceDomain "security" .
ngm:data-flow-mapping a skos:Concept ;
rdfs:label "Data Flow Mapping"@en .
ngm:data-format a owl:Class ;
rdfs:comment "A Data Format is a formal structural and encoding specification that governs how raw bytes are organised, typed, and interpreted when data is stored, transmitted, or exchanged between computational systems. Formats encode decisions about byte ordering, field delimitation, schema evolution, compression, and type systems, ranging from binary serialisation protocols (Protocol Buffers, Apache Avro, MessagePack) to human-readable interchange formats (JSON, XML, YAML, TOML) and domain-specific schemas (DICOM for medical imaging, glTF for 3D assets, FITS for astronomical data). The choice of data format critically determines interoperability scope, parsing overhead, storage efficiency, schema evolution capability, and compatibility with downstream processing pipelines and analytics engines."@en ;
rdfs:label "Data Format"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r6861 ;
rdfs:subClassOf _:r6862 ;
rdfs:subClassOf _:r6863 ;
rdfs:subClassOf _:r6864 ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:knowledge-graph ;
vc:bridgesTo ngm:linked-data ;
vc:contrastsWith ngm:binary-format ;
vc:contrastsWith ngm:text-format ;
vc:dependsOn ngm:character-encoding ;
vc:dependsOn ngm:type-system ;
vc:enables ngm:api-design ;
vc:enables ngm:data-exchange ;
vc:enables ngm:data-interoperability ;
vc:enables ngm:data-pipeline ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:encoding ;
vc:hasPart ngm:schema ;
vc:hasPart ngm:serialisation ;
vc:implements ngm:interface-definition-language ;
vc:implements ngm:open-standard ;
vc:isPartOf ngm:data-architecture ;
vc:isPartOf ngm:data-standards ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:apache-parquet ;
vc:relatedTo ngm:json-ld ;
vc:relatedTo ngm:protobuf ;
vc:relatedTo ngm:protocol-buffer ;
vc:requires ngm:codec ;
vc:requires ngm:schema-registry ;
vc:slug "data-format" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:ietf ;
vc:standardizedBy ngm:iso ;
vc:standardizedBy ngm:w3-c ;
vc:uses ngm:data-compression ;
vc:uses ngm:data-validation .
ngm:data-format-schemas a skos:Concept ;
rdfs:label "Data Format Schemas"@en .
ngm:data-format-standard a owl:Class ;
rdfs:comment "Technical specifications defining how data is structured, encoded, and exchanged across metaverse platforms and 3D applications, including standards like glTF for efficient 3D asset transmission and Universal Scene Description (USD) for complex scene composition and collaboration."@en ;
rdfs:label "Data Format Standard"@en ;
rdfs:subClassOf ngm:technical-standards ;
rdfs:subClassOf _:r6857 ;
rdfs:subClassOf _:r6858 ;
rdfs:subClassOf _:r6859 ;
rdfs:subClassOf _:r6860 ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:spatial-computing ;
vc:bridgesTo ngm:technical-standards ;
vc:contrastsWith ngm:proprietary-format ;
vc:contrastsWith ngm:vendor-lock-in ;
vc:dependsOn ngm:khronos-group ;
vc:dependsOn ngm:open-standards ;
vc:enables ngm:asset-interoperability ;
vc:enables ngm:content-portability ;
vc:enables ngm:cross-platform-asset-exchange ;
vc:enables ngm:digital-twin ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:encoding-specification ;
vc:hasPart ngm:schema-definition ;
vc:hasPart ngm:validation-tools ;
vc:implements ngm:gltf-standard ;
vc:implements ngm:material-x ;
vc:implements ngm:usd ;
vc:isPartOf ngm:interoperability-framework ;
vc:qualityScore "0.7"^^xsd:float ;
vc:relatedTo ngm:open-usd ;
vc:relatedTo ngm:usd ;
vc:requires ngm:implementation-libraries ;
vc:requires ngm:standards-body ;
vc:requires ngm:validation-tools ;
vc:slug "data-format-standard" ;
vc:sourceDomain "standards" ;
vc:standardizedBy ngm:khronos-group ;
vc:standardizedBy ngm:metaverse-standards-forum ;
vc:supports ngm:metaverse ;
vc:supports ngm:virtual-production ;
vc:uses ngm:binary-encoding ;
vc:uses ngm:json-data-interchange-format-serialisation .
ngm:data-formats a skos:Concept ;
rdfs:label "Data Formats"@en .
ngm:data-formatting a skos:Concept ;
rdfs:label "Data Formatting"@en .
ngm:data-foundation a skos:Concept ;
rdfs:label "Data Foundation"@en .
ngm:data-free-flow a skos:Concept ;
rdfs:label "Data Free Flow"@en .
ngm:data-fusion a skos:Concept ;
rdfs:label "Data Fusion"@en .
ngm:data-glove a skos:Concept ;
rdfs:label "Data Glove"@en .
ngm:data-governance a owl:Class ;
rdfs:comment "Data Governance is a system of policies, processes, roles, and standards that establish accountability and control over an organisation's data assets throughout their lifecycle. It defines who may take what actions with which data, under what circumstances, and using what methods, ensuring data quality, consistency, security, and regulatory compliance. Effective data governance bridges technical data management practices with organisational strategy, aligning data stewardship with business objectives and legal obligations. It is foundational to trustworthy analytics, AI model training, and interoperability across enterprise systems."@en ;
rdfs:label "Data Governance"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r6872 ;
rdfs:subClassOf _:r6873 ;
rdfs:subClassOf _:r6874 ;
rdfs:subClassOf _:r6875 ;
rdfs:subClassOf _:r6876 ;
rdfs:subClassOf _:r6877 ;
rdfs:subClassOf _:r6878 ;
vc:bridgesTo ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:federated-learning ;
vc:contrastsWith ngm:data-anarchy ;
vc:contrastsWith ngm:data-management ;
vc:dependsOn ngm:data-architecture ;
vc:dependsOn ngm:organisational-policy ;
vc:enables ngm:data-analytics ;
vc:enables ngm:data-interoperability ;
vc:enables ngm:machine-learning-discipline ;
vc:enables ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:data-catalogue ;
vc:hasPart ngm:data-lineage ;
vc:hasPart ngm:data-quality-management ;
vc:hasPart ngm:data-stewardship ;
vc:hasPart ngm:metadata-management ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:data-privacy ;
vc:relatedTo ngm:data-security ;
vc:relatedTo ngm:enterprise-architecture ;
vc:relatedTo ngm:information-governance ;
vc:relatedTo ngm:master-data-management ;
vc:requires ngm:access-control ;
vc:requires ngm:data-classification ;
vc:requires ngm:data-ownership ;
vc:slug "data-governance" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:dama-dmbok ;
vc:standardizedBy ngm:gdpr ;
vc:standardizedBy ngm:iso-8000 .
ngm:data-governance-framework a owl:Class ;
rdfs:comment "A Data Governance Framework is a structured set of policies, processes, roles, and standards that define how an organisation acquires, manages, protects, and disposes of data assets throughout their lifecycle. It establishes accountability structures, data quality standards, metadata management practices, and compliance mechanisms aligned to regulatory obligations such as GDPR. Effective frameworks balance centralised oversight with federated data ownership through data mesh and stewardship models. They underpin trustworthy AI deployments by ensuring training data provenance and ongoing monitoring of data quality and lineage."@en ;
rdfs:label "Data Governance Framework"@en ;
rdfs:subClassOf ngm:data-governance ;
rdfs:subClassOf _:r6865 ;
rdfs:subClassOf _:r6866 ;
rdfs:subClassOf _:r6867 ;
rdfs:subClassOf _:r6868 ;
rdfs:subClassOf _:r6869 ;
rdfs:subClassOf _:r6870 ;
rdfs:subClassOf _:r6871 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:security ;
vc:contrastsWith ngm:data-anarchy ;
vc:enables ngm:compliance-monitoring ;
vc:enables ngm:gdpr-compliance ;
vc:enables ngm:privacy-and-data-governance ;
vc:enables ngm:regulatory-reporting ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:access-control ;
vc:hasPart ngm:data-classification ;
vc:hasPart ngm:data-quality-management ;
vc:hasPart ngm:data-stewardship ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:ai-governance-framework ;
vc:relatedTo ngm:data-ethics ;
vc:relatedTo ngm:data-protection ;
vc:relatedTo ngm:master-data-management ;
vc:requires ngm:data-catalogue ;
vc:requires ngm:data-lineage ;
vc:requires ngm:metadata-registry ;
vc:slug "data-governance-framework" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:dama-dmbok ;
vc:standardizedBy ngm:iso-8000 ;
vc:supports ngm:data-sovereignty ;
vc:supports ngm:trustworthy-ai ;
vc:uses ngm:data-mesh ;
vc:uses ngm:data-pipeline ;
vc:uses ngm:metadata-management .
ngm:data-governance-maturity-model a skos:Concept ;
rdfs:label "Data Governance Maturity Model"@en .
ngm:data-harmonization a skos:Concept ;
rdfs:label "Data Harmonization"@en .
ngm:data-hoarding a skos:Concept ;
rdfs:label "Data Hoarding"@en .
ngm:data-infrastructure a owl:Class ;
rdfs:comment "Data infrastructure is the integrated set of systems, platforms, and pipelines that ingest, store, process, govern, and serve data across an organisation. It encompasses storage layers such as data warehouses and data lakes, processing and integration pipelines, cataloguing and governance, and the compute fabric that supports analytics and machine learning. Data infrastructure provides the reliable, scalable foundation on which data products and decision-making depend."@en ;
rdfs:label "Data Infrastructure"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf ngm:infrastructure ;
rdfs:subClassOf _:r6879 ;
rdfs:subClassOf _:r6880 ;
rdfs:subClassOf _:r6881 ;
rdfs:subClassOf _:r6882 ;
rdfs:subClassOf _:r6883 ;
skos:broader ngm:infrastructure ;
vc:bridgesTo ngm:data-governance ;
vc:bridgesTo ngm:observability ;
vc:dependsOn ngm:networking ;
vc:dependsOn ngm:scalability ;
vc:enables ngm:data-architecture ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:data-lake ;
vc:hasPart ngm:data-pipeline ;
vc:hasPart ngm:data-warehouse ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-catalog ;
vc:relatedTo ngm:reliability ;
vc:requires ngm:data-engineering ;
vc:requires ngm:data-integration ;
vc:slug "data-infrastructure" ;
vc:sourceDomain "data" ;
vc:supports ngm:business-intelligence ;
vc:supports ngm:machine-learning-discipline ;
vc:uses ngm:cloud-computing ;
vc:uses ngm:database .
ngm:data-ingestion a owl:Class ;
rdfs:comment "Data ingestion is the process of acquiring data from heterogeneous sources and moving it into a target store or processing system for downstream use. It covers batch and streaming acquisition, format normalisation, validation and routing, and forms the entry stage of data pipelines. In spatial-computing contexts ingestion handles sensor streams and captured geometry before reconstruction and analysis."@en ;
rdfs:label "Data Ingestion"@en ;
rdfs:subClassOf ngm:data-pipeline ;
rdfs:subClassOf _:r6884 ;
rdfs:subClassOf _:r6885 ;
rdfs:subClassOf _:r6886 ;
rdfs:subClassOf _:r6887 ;
vc:dependsOn ngm:data-integrity ;
vc:enables ngm:feature-engineering ;
vc:enables ngm:training-data ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:data-collection ;
vc:hasPart ngm:sensor-fusion ;
vc:isPartOf ngm:data-engineering ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:caching ;
vc:relatedTo ngm:observability ;
vc:relatedTo ngm:scalability ;
vc:requires ngm:data-quality ;
vc:requires ngm:schema ;
vc:slug "data-ingestion" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:data-pipeline ;
vc:uses ngm:point-cloud .
ngm:data-integration a owl:Class ;
rdfs:comment "Data Integration is the set of processes, architectures, and tools that combine data from multiple heterogeneous sources — including relational databases, APIs, event streams, file systems, and third-party services — into a unified, consistent, and queryable representation suitable for analytics, machine learning, or operational workloads. It encompasses extract-transform-load (ETL) and extract-load-transform (ELT) pipelines, schema harmonisation, semantic mapping, identity resolution, and real-time federation patterns. Modern data integration extends beyond batch movement to include change-data capture (CDC), streaming integration via message brokers, and virtual federation through query engines, enabling organisations to maintain a single source of truth across distributed data estates. In AI and spatial-computing contexts, data integration connects sensor telemetry, digital-twin feeds, user-behaviour streams, and knowledge-graph stores into coherent data products that power downstream inference and immersive experiences."@en ;
rdfs:label "Data Integration"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r6892 ;
rdfs:subClassOf _:r6893 ;
rdfs:subClassOf _:r6894 ;
rdfs:subClassOf _:r6895 ;
rdfs:subClassOf _:r6896 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:knowledge-graph ;
vc:contrastsWith ngm:data-federation ;
vc:contrastsWith ngm:data-replication ;
vc:dependsOn ngm:data-quality ;
vc:dependsOn ngm:interoperability ;
vc:enables ngm:data-interoperability ;
vc:enables ngm:data-warehouse ;
vc:enables ngm:lakehouse-architecture ;
vc:enables ngm:real-time-analytics ;
vc:enables ngm:semantic-interoperability ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:change-data-capture ;
vc:hasPart ngm:etl-pipeline ;
vc:hasPart ngm:identity-resolution ;
vc:hasPart ngm:schema-harmonisation ;
vc:qualityScore "0.72"^^xsd:float ;
vc:requires ngm:data-governance ;
vc:requires ngm:metadata-management ;
vc:slug "data-integration" ;
vc:sourceDomain "data" ;
vc:standardizedBy ngm:open-lineage ;
vc:standardizedBy ngm:sql ;
vc:uses ngm:api-gateway ;
vc:uses ngm:data-catalog ;
vc:uses ngm:data-catalogue ;
vc:uses ngm:data-pipeline ;
vc:uses ngm:message-broker .
ngm:data-integration-interface a owl:Class ;
rdfs:comment "A standardized set of protocols, rules, and formats for unifying and mediating data flows across heterogeneous platforms, enabling seamless data exchange and interoperability."@en ;
rdfs:label "Data Integration Interface"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r6888 ;
rdfs:subClassOf _:r6889 ;
rdfs:subClassOf _:r6890 ;
rdfs:subClassOf _:r6891 ;
vc:bridgesTo ngm:blockchain ;
vc:dependsOn ngm:data-governance ;
vc:dependsOn ngm:metadata-registry ;
vc:dependsOn ngm:service-discovery ;
vc:enables ngm:cross-platform-data-exchange ;
vc:enables ngm:data-federation ;
vc:enables ngm:real-time-synchronisation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:data-adapter ;
vc:hasPart ngm:message-broker ;
vc:hasPart ngm:protocol-translator ;
vc:hasPart ngm:schema-mapper ;
vc:isPartOf ngm:data-management ;
vc:isPartOf ngm:interoperability-framework ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:api-gateway ;
vc:requires ngm:communication-protocol ;
vc:requires ngm:data-schema ;
vc:slug "data-integration-interface" ;
vc:sourceDomain "infrastructure" .
ngm:data-integrity a owl:Class ;
rdfs:comment "Data integrity is the property guaranteeing that data remains accurate, complete, consistent, and unaltered throughout its entire lifecycle—spanning creation, storage, transmission, and processing—except through authorised operations. It is enforced through a layered combination of technical controls including cryptographic hash functions, digital signatures, Merkle trees, access control mechanisms, and ACID-compliant transactions, as well as procedural controls such as change-control workflows, audit trails, and immutable logging. Violations—whether from storage errors, transmission corruption, software bugs, or deliberate tampering—can propagate silently and have cascading consequences in any system relying on the data for decision-making or compliance."@en ;
rdfs:label "Data Integrity"@en ;
rdfs:subClassOf ngm:data-quality ;
rdfs:subClassOf _:r6898 ;
rdfs:subClassOf _:r6899 ;
rdfs:subClassOf _:r6900 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:smart-contract ;
vc:bridgesTo ngm:supply-chain-provenance ;
vc:contrastsWith ngm:data-corruption ;
vc:contrastsWith ngm:eventual-consistency ;
vc:dependsOn ngm:acid-transactions ;
vc:dependsOn ngm:erasure-coding ;
vc:dependsOn ngm:fault-tolerance ;
vc:enables ngm:audit-trail ;
vc:enables ngm:data-provenance ;
vc:enables ngm:immutability ;
vc:enables ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:data-governance ;
vc:relatedTo ngm:data-lineage ;
vc:relatedTo ngm:distributed-ledger ;
vc:relatedTo ngm:information-security ;
vc:relatedTo ngm:referential-integrity ;
vc:requires ngm:access-control ;
vc:requires ngm:encryption ;
vc:requires ngm:write-ahead-logging ;
vc:slug "data-integrity" ;
vc:sourceDomain "data" ;
vc:standardizedBy ngm:iso-27001 ;
vc:standardizedBy ngm:nist-cybersecurity-framework ;
vc:uses ngm:access-control ;
vc:uses ngm:checksum ;
vc:uses ngm:digital-signature ;
vc:uses ngm:hash-function ;
vc:uses ngm:merkle-tree .
ngm:data-integrity-constraint a skos:Concept ;
rdfs:label "Data Integrity Constraint"@en .
ngm:data-integrity-verification a owl:Class ;
rdfs:comment "Data integrity verification is the process of confirming that a piece of data has not been altered, corrupted, or tampered with since it was created or last authorised, typically by comparing a cryptographic digest computed over the data against a previously recorded or independently trusted value. Techniques include cryptographic hash functions, checksums, and Merkle tree proofs, which allow large datasets to be verified efficiently by checking a small root value rather than the full contents. It underpins trust in distributed systems, blockchains, and any pipeline where data passes through untrusted intermediaries."@en ;
rdfs:label "Data Integrity Verification"@en ;
rdfs:subClassOf ngm:data-integrity ;
rdfs:subClassOf _:r6897 ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:merkle-tree ;
vc:slug "data-integrity-verification" ;
vc:sourceDomain "security" ;
vc:uses ngm:cryptographic-hash-function .
ngm:data-interchange a skos:Concept ;
rdfs:label "Data Interchange"@en .
ngm:data-interoperability a owl:Class ;
rdfs:comment "Data Interoperability is the capability of heterogeneous systems, applications, and data sources to exchange, interpret, and act upon shared data without loss of meaning across organisational and technical boundaries. It encompasses syntactic interoperability (shared formats and wire protocols), semantic interoperability (common vocabularies, ontologies, and data models), and pragmatic interoperability (agreed processes, policies, and trust frameworks). Achieving full data interoperability requires alignment across API contracts, schema registries, identity frameworks, and data governance regimes. It is a foundational property enabling federated analytics, cross-domain knowledge graphs, and open ecosystem integration."@en ;
rdfs:label "Data Interoperability"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r6901 ;
rdfs:subClassOf _:r6902 ;
rdfs:subClassOf _:r6903 ;
rdfs:subClassOf _:r6904 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:decentralised-identifier ;
vc:bridgesTo ngm:verifiable-credential-vc ;
vc:contrastsWith ngm:data-silo ;
vc:contrastsWith ngm:vendor-lock-in ;
vc:dependsOn ngm:data-governance ;
vc:dependsOn ngm:identity-management ;
vc:dependsOn ngm:metadata-management ;
vc:enables ngm:data-pipeline ;
vc:enables ngm:federated-learning ;
vc:enables ngm:interoperability ;
vc:enables ngm:knowledge-graph ;
vc:enables ngm:open-data ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:graph-ql ;
vc:implements ngm:linked-data ;
vc:implements ngm:rest-api ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:data-fabric ;
vc:relatedTo ngm:data-integration ;
vc:relatedTo ngm:data-mesh ;
vc:relatedTo ngm:semantic-interoperability ;
vc:relatedTo ngm:syntactic-interoperability ;
vc:requires ngm:api-contract ;
vc:requires ngm:data-format ;
vc:requires ngm:data-standards ;
vc:requires ngm:schema-registry ;
vc:slug "data-interoperability" ;
vc:sourceDomain "data" ;
vc:standardizedBy ngm:iso ;
vc:standardizedBy ngm:oasis ;
vc:standardizedBy ngm:w3-c .
ngm:data-inventory a owl:Class ;
rdfs:comment "A data inventory is a structured, maintained record of the categories, locations, and flows of data - particularly personal data - that an organisation collects, processes, and stores. It underpins compliance with data protection regimes such as CCPA and GDPR by allowing an organisation to demonstrate what data it holds, why it holds it, and where it resides when responding to access, deletion, or portability requests. Maintaining an accurate data inventory is a prerequisite for exercising rights such as the right to be forgotten."@en ;
rdfs:label "Data Inventory"@en ;
rdfs:subClassOf ngm:data-catalog ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.0"^^xsd:float ;
vc:slug "data-inventory" ;
vc:sourceDomain "governance" .
ngm:data-labelling a owl:Class ;
rdfs:comment "Data labelling is the process of annotating raw data, such as images, text, audio or sensor readings, with the target outputs or categories a supervised model is expected to predict. It produces the ground-truth signal that links inputs to desired outputs and largely determines the achievable accuracy of trained models. Labelling combines human annotators, guidelines, tooling and quality control, increasingly augmented by model-assisted and active-learning workflows."@en ;
rdfs:label "Data Labelling"@en ;
rdfs:subClassOf ngm:data-annotation ;
rdfs:subClassOf _:r6905 ;
rdfs:subClassOf _:r6906 ;
rdfs:subClassOf _:r6907 ;
rdfs:subClassOf _:r6908 ;
vc:bridgesTo ngm:dataset-curation ;
vc:contrastsWith ngm:active-learning ;
vc:dependsOn ngm:data-quality ;
vc:enables ngm:model-training ;
vc:enables ngm:supervised-learning ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:dataset-curation ;
vc:hasPart ngm:ground-truth-labels ;
vc:isPartOf ngm:training-data ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-quality ;
vc:relatedTo ngm:ground-truth-labels ;
vc:requires ngm:human-in-the-loop ;
vc:requires ngm:training-data ;
vc:slug "data-labelling" ;
vc:sourceDomain "machine-learning" ;
vc:supports ngm:active-learning ;
vc:supports ngm:supervised-learning ;
vc:uses ngm:human-in-the-loop .
ngm:data-lake a owl:Class ;
rdfs:comment "A centralized repository that stores structured, semi-structured, and unstructured data at any scale in its native format, deferring schema enforcement to query time (schema-on-read). Data lakes enable big-data analytics, machine learning pipelines, and exploratory analysis without upfront data modelling, serving as the foundational ingestion layer for modern data architectures."@en ;
rdfs:label "Data Lake"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf ngm:data-storage ;
rdfs:subClassOf _:r6909 ;
rdfs:subClassOf _:r6910 ;
rdfs:subClassOf _:r6911 ;
rdfs:subClassOf _:r6912 ;
rdfs:subClassOf _:r6913 ;
rdfs:subClassOf _:r6914 ;
rdfs:subClassOf _:r6915 ;
skos:broader ngm:artificial-intelligence ;
vc:bridgesTo ngm:knowledge-graph ;
vc:bridgesTo ngm:lakehouse-architecture ;
vc:contrastsWith ngm:data-warehouse ;
vc:contrastsWith ngm:relational-database ;
vc:enables ngm:data-analytics ;
vc:enables ngm:exploratory-data-analysis ;
vc:enables ngm:machine-learning-discipline-infrastructure ;
vc:enables ngm:machine-learning-discipline-pipeline ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:batch-processing ;
vc:hasPart ngm:data-pipeline ;
vc:hasPart ngm:etl-pipeline ;
vc:hasPart ngm:metadata-catalog ;
vc:hasPart ngm:object-storage ;
vc:isPartOf ngm:data-architecture ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:data-fabric-architecture ;
vc:relatedTo ngm:data-mesh ;
vc:relatedTo ngm:graph-database ;
vc:requires ngm:cloud-storage ;
vc:requires ngm:distributed-file-system ;
vc:slug "data-lake" ;
vc:sourceDomain "data" ;
vc:supports ngm:real-time-analytics ;
vc:supports ngm:stream-processing ;
vc:uses ngm:apache-iceberg ;
vc:uses ngm:apache-parquet ;
vc:uses ngm:data-governance ;
vc:uses ngm:vector-database .
ngm:data-layer a owl:Class ;
rdfs:comment "Data Layer is the architectural tier within a layered, n-tier, hexagonal, or modular system responsible for the durable persistence, transactional integrity, indexed retrieval, replication, and abstraction of stateful data — encompassing both the enterprise-architecture sense (the data access lay..."@en ;
rdfs:label "Data Layer"@en ;
rdfs:subClassOf ngm:architectural-layer ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf ngm:infra-network-and-comms ;
rdfs:subClassOf ngm:software-layer ;
rdfs:subClassOf ngm:system-tier ;
rdfs:subClassOf _:r6916 ;
rdfs:subClassOf _:r6917 ;
rdfs:subClassOf _:r6918 ;
rdfs:subClassOf _:r6919 ;
rdfs:subClassOf _:r6920 ;
rdfs:subClassOf _:r6921 ;
rdfs:subClassOf _:r6922 ;
rdfs:subClassOf _:r6923 ;
rdfs:subClassOf _:r6924 ;
rdfs:subClassOf _:r6925 ;
rdfs:subClassOf _:r6926 ;
rdfs:subClassOf _:r6927 ;
rdfs:subClassOf _:r6928 ;
rdfs:subClassOf _:r6929 ;
rdfs:subClassOf _:r6930 ;
rdfs:subClassOf _:r6931 ;
rdfs:subClassOf _:r6932 ;
skos:broader ngm:infra-network-and-comms ;
vc:bridgesTo ngm:architectural-layer ;
vc:contrastsWith ngm:application-layer ;
vc:contrastsWith ngm:business-logic-layer ;
vc:contrastsWith ngm:consensus-layer ;
vc:contrastsWith ngm:execution-layer ;
vc:contrastsWith ngm:presentation-layer ;
vc:contrastsWith ngm:settlement-layer ;
vc:dependsOn ngm:file-system ;
vc:dependsOn ngm:memory-hierarchy ;
vc:dependsOn ngm:network-layer ;
vc:dependsOn ngm:operating-system ;
vc:dependsOn ngm:physical-layer ;
vc:enables ngm:acid-properties ;
vc:enables ngm:data-availability ;
vc:enables ngm:data-consistency ;
vc:enables ngm:data-persistence ;
vc:enables ngm:horizontal-scalability ;
vc:enables ngm:persistence ;
vc:enables ngm:retrieval-augmented-generation ;
vc:enables ngm:rollup ;
vc:enables ngm:semantic-query ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:cache-layer ;
vc:hasPart ngm:connection-pool ;
vc:hasPart ngm:data-availability-sampling ;
vc:hasPart ngm:database-engine ;
vc:hasPart ngm:erasure-coding ;
vc:hasPart ngm:kzg-commitment ;
vc:hasPart ngm:object-relational-mapper ;
vc:hasPart ngm:on-chain-data-indexing ;
vc:hasPart ngm:query-processor ;
vc:hasPart ngm:replication ;
vc:hasPart ngm:schema-registry ;
vc:hasPart ngm:transaction-manager ;
vc:implements ngm:active-record ;
vc:implements ngm:cqrs ;
vc:implements ngm:data-mapper-pattern ;
vc:implements ngm:event-sourcing ;
vc:implements ngm:hexagonal-architecture ;
vc:implements ngm:ports-and-adapters ;
vc:implements ngm:repository-pattern ;
vc:implements ngm:unit-of-work ;
vc:qualityScore "0.53"^^xsd:float ;
vc:relatedTo ngm:avail ;
vc:relatedTo ngm:celestia ;
vc:relatedTo ngm:clean-architecture ;
vc:relatedTo ngm:domain-driven-design ;
vc:relatedTo ngm:eigenda ;
vc:relatedTo ngm:knowledge-graph ;
vc:relatedTo ngm:microservices ;
vc:relatedTo ngm:modular-blockchain ;
vc:relatedTo ngm:polygon-agg-layer ;
vc:relatedTo ngm:vector-database ;
vc:requires ngm:backup-and-recovery ;
vc:requires ngm:consensus-protocol ;
vc:requires ngm:file-system ;
vc:requires ngm:network-layer ;
vc:requires ngm:schema-definition ;
vc:requires ngm:storage-medium ;
vc:slug "data-layer" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:ansi-sql ;
vc:standardizedBy ngm:celestia ;
vc:standardizedBy ngm:cidr-architecture ;
vc:standardizedBy ngm:eip-4844 ;
vc:standardizedBy ngm:iso-iec-9075 ;
vc:standardizedBy ngm:jdbc-specification ;
vc:standardizedBy ngm:jpa-specification ;
vc:standardizedBy ngm:odbc-specification ;
vc:supports ngm:application-layer ;
vc:supports ngm:business-logic-layer ;
vc:supports ngm:domain-model ;
vc:supports ngm:execution-layer ;
vc:supports ngm:reporting-layer ;
vc:supports ngm:settlement-layer ;
vc:uses ngm:bloom-filter ;
vc:uses ngm:cypher ;
vc:uses ngm:graph-ql ;
vc:uses ngm:jdbc ;
vc:uses ngm:merkle-tree ;
vc:uses ngm:odbc ;
vc:uses ngm:orm-frameworks ;
vc:uses ngm:reed-solomon-codes ;
vc:uses ngm:sparql ;
vc:uses ngm:sql .
ngm:data-leakage a skos:Concept ;
rdfs:label "Data Leakage"@en .
ngm:data-lifecycle a owl:Class ;
rdfs:comment "The sequence of stages that data passes through from initial creation or capture to eventual archival or destruction, typically comprising creation, storage, use, sharing, archiving, and disposal, with each stage carrying distinct security, quality, and regulatory obligations that organisations manage through lifecycle policies, retention schedules, and classification-driven controls."@en ;
rdfs:label "Data Lifecycle"@en ;
rdfs:subClassOf ngm:data-management ;
vc:enables ngm:data-quality ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:data-governance ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:data-classification ;
vc:relatedTo ngm:records-management ;
vc:slug "data-lifecycle" ;
vc:sourceDomain "data" .
ngm:data-lineage a owl:Class ;
rdfs:comment "Data lineage is the documented record of data's origins, movements, transformations and consumption as it flows through systems and pipelines. It maps how a data element is derived end to end, supporting impact analysis, debugging, audit and regulatory compliance. As a pillar of data governance and metadata management it makes data trustworthy by exposing its provenance."@en ;
rdfs:label "Data Lineage"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r6933 ;
rdfs:subClassOf _:r6934 ;
rdfs:subClassOf _:r6935 ;
vc:bridgesTo ngm:blockchain-provenance ;
vc:bridgesTo ngm:supply-chain-transparency ;
vc:contrastsWith ngm:data-catalog ;
vc:dependsOn ngm:data-schema ;
vc:dependsOn ngm:directed-acyclic-graph ;
vc:enables ngm:audit-trail ;
vc:enables ngm:regulatory-compliance ;
vc:enables ngm:root-cause-analysis ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:data-provenance ;
vc:isPartOf ngm:data-governance ;
vc:isPartOf ngm:metadata-management ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:data-observability ;
vc:relatedTo ngm:etl-pipeline ;
vc:requires ngm:data-pipeline ;
vc:requires ngm:metadata-catalog ;
vc:slug "data-lineage" ;
vc:sourceDomain "data" ;
vc:standardizedBy ngm:open-lineage ;
vc:standardizedBy ngm:provenance-standard ;
vc:supports ngm:data-quality-management ;
vc:supports ngm:gdpr-compliance ;
vc:uses ngm:apache-atlas ;
vc:uses ngm:graph-database ;
vc:uses ngm:open-lineage .
ngm:data-lineage-tracking a owl:Class ;
rdfs:comment "Data lineage tracking is the automated capture and maintenance of provenance metadata as data is created, transformed and moved across pipelines and platforms. It instruments transformations and queries to build a continuously updated lineage graph rather than a static map. Often expressed using provenance vocabularies such as PROV-O, it underpins reproducibility, trust and governance in data fabric architectures."@en ;
rdfs:label "Data Lineage Tracking"@en ;
rdfs:subClassOf ngm:data-management ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:data-fabric-architecture ;
vc:relatedTo ngm:provenance-ontology-prov-o ;
vc:slug "data-lineage-tracking" ;
vc:sourceDomain "data" .
ngm:data-link-layer a owl:Class ;
rdfs:comment "The data link layer is the second layer of the OSI model, responsible for node-to-node data transfer across a single physical link and for framing raw bits from the physical layer into structured frames. It provides addressing through hardware (MAC) addresses, error detection, and media access control that arbitrates shared transmission media. By presenting a reliable link to the network layer above, it abstracts away the imperfections of the underlying physical medium."@en ;
rdfs:label "Data Link Layer"@en ;
rdfs:subClassOf ngm:osi-model ;
rdfs:subClassOf _:r6936 ;
rdfs:subClassOf _:r6937 ;
vc:contrastsWith ngm:network-layer ;
vc:enables ngm:ethernet ;
vc:enables ngm:network-protocol ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:ethernet ;
vc:isPartOf ngm:osi-model ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:network-layer ;
vc:relatedTo ngm:network-protocol ;
vc:relatedTo ngm:tcp-ip ;
vc:requires ngm:physical-layer ;
vc:slug "data-link-layer" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:infrastructure ;
vc:supports ngm:network-layer .
ngm:data-localisation a owl:Class ;
rdfs:comment "Data localisation is the legal or regulatory requirement that certain categories of data be stored, processed, or retained within the geographic borders of a particular country or jurisdiction. Governments impose such rules to assert data sovereignty, protect citizens' personal information, support law-enforcement access, or shield strategic sectors, and the requirements range from mandating in-country copies to outright bans on cross-border transfer. Compliance forces organisations to architect regional data residency, partition storage, and reconcile conflicting national regimes, materially shaping cloud architecture and international data flows."@en ;
rdfs:label "Data Localisation"@en ;
rdfs:subClassOf ngm:data-governance ;
rdfs:subClassOf _:r6938 ;
rdfs:subClassOf _:r6939 ;
vc:dependsOn ngm:privacy-regulation ;
vc:enables ngm:data-sovereignty ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:data-governance ;
vc:isPartOf ngm:data-protection ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-protection ;
vc:relatedTo ngm:interoperability ;
vc:requires ngm:data-residency ;
vc:requires ngm:regulatory-compliance ;
vc:slug "data-localisation" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:gdpr .
ngm:data-logger a skos:Concept ;
rdfs:label "Data Logger"@en .
ngm:data-logging a skos:Concept ;
rdfs:label "Data Logging"@en .
ngm:data-loss-prevention a owl:Class ;
rdfs:comment "Data loss prevention (DLP) is a set of security controls and technologies that detect and block the unauthorised exfiltration, leakage or misuse of sensitive data. DLP systems classify content, monitor data in use, in motion and at rest, and enforce policies at endpoints, networks and cloud services. It is a core data-protection capability supporting compliance with privacy and confidentiality requirements."@en ;
rdfs:label "Data Loss Prevention"@en ;
rdfs:subClassOf ngm:infra-security-and-identity ;
skos:broader ngm:infra-security-and-identity ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:compliance-control ;
vc:relatedTo ngm:data-protection ;
vc:slug "data-loss-prevention" ;
vc:sourceDomain "security" .
ngm:data-management a owl:Class ;
rdfs:comment "Data Management is the disciplined set of practices, architectures, and technologies for acquiring, validating, storing, organising, protecting, and retiring data across its full lifecycle. It encompasses data modelling, quality assurance, metadata governance, access control, and lineage tracking to ensure data assets remain accurate, discoverable, and trustworthy. In AI and distributed-systems contexts it additionally covers ingestion pipelines, versioned feature stores, reproducible training datasets, and consent frameworks. Effective data management underpins regulatory compliance, interoperability, and the reliability of analytical and machine-learning workloads."@en ;
rdfs:label "Data Management"@en ;
rdfs:subClassOf _:r6943 ;
rdfs:subClassOf _:r6944 ;
rdfs:subClassOf _:r6945 ;
rdfs:subClassOf _:r6946 ;
rdfs:subClassOf _:r6947 ;
rdfs:subClassOf _:r6948 ;
rdfs:subClassOf _:r6949 ;
rdfs:subClassOf _:r6950 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:metaverse-technology ;
vc:contrastsWith ngm:data-hoarding ;
vc:enables ngm:data-analytics ;
vc:enables ngm:federated-learning ;
vc:enables ngm:machine-learning-discipline ;
vc:enables ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:data-catalogue ;
vc:hasPart ngm:data-governance ;
vc:hasPart ngm:data-lineage ;
vc:hasPart ngm:data-quality ;
vc:hasPart ngm:metadata-management ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:data-architecture ;
vc:relatedTo ngm:distributed-system ;
vc:relatedTo ngm:etl-pipeline ;
vc:relatedTo ngm:information-management ;
vc:requires ngm:access-control ;
vc:requires ngm:data-security ;
vc:requires ngm:data-storage ;
vc:slug "data-management" ;
vc:sourceDomain "data" ;
vc:standardizedBy ngm:dama-dmbok ;
vc:standardizedBy ngm:gdpr ;
vc:supports ngm:ai-infrastructure ;
vc:supports ngm:business-intelligence ;
vc:supports ngm:knowledge-graph .
ngm:data-management-platform a owl:Class ;
rdfs:comment "A data management platform is a centralised system for collecting, organising, segmenting, and activating large volumes of data drawn from multiple sources so that it can be used for analytics, audience targeting, and decision-making. Historically associated with advertising, where it aggregated and anonymised audience data for campaign targeting, the term also denotes broader enterprise platforms that unify data pipelines, storage, and governance. It is closely related to, but distinct from, customer data platforms and data warehouses."@en ;
rdfs:label "Data Management Platform"@en ;
rdfs:subClassOf ngm:data ;
rdfs:subClassOf _:r6940 ;
rdfs:subClassOf _:r6941 ;
rdfs:subClassOf _:r6942 ;
vc:contrastsWith ngm:customer-data-platform ;
vc:dependsOn ngm:data ;
vc:enables ngm:programmatic-advertising ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:data-pipeline ;
vc:hasPart ngm:data-warehouse ;
vc:isPartOf ngm:data-integration ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-warehouse ;
vc:relatedTo ngm:synthetic-data-generator ;
vc:requires ngm:consent-management ;
vc:slug "data-management-platform" ;
vc:sourceDomain "data" ;
vc:supports ngm:advertising ;
vc:supports ngm:data-governance ;
vc:uses ngm:data-integration .
ngm:data-management-system a owl:Class ;
rdfs:comment "A data management system is software that stores, organises, secures and provides controlled access to data throughout its lifecycle. It encompasses capabilities for ingestion, modelling, querying, integrity enforcement and governance, with database management systems and graph databases as common specialisations. It is the foundational platform on which metadata standards and downstream applications depend."@en ;
rdfs:label "Data Management System"@en ;
rdfs:subClassOf ngm:data-management ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:graph-database ;
vc:relatedTo ngm:metadata-standard ;
vc:slug "data-management-system" ;
vc:sourceDomain "data" .
ngm:data-manipulation-language a skos:Concept ;
rdfs:label "Data Manipulation Language"@en .
ngm:data-mapper-pattern a skos:Concept ;
rdfs:label "Data Mapper Pattern"@en .
ngm:data-mapping a owl:Class ;
rdfs:comment "Data mapping is the process of defining correspondences between fields, elements, or schemas of a source data structure and those of a target, specifying how each attribute is matched, transformed, or combined during movement between systems. It is foundational to data integration, migration, and interoperability, guiding extract-transform-load pipelines and message translation so that semantically equivalent information aligns across heterogeneous models. In privacy and governance contexts, data mapping also denotes the cataloguing of where personal data resides and how it flows, which is a prerequisite for lineage tracking and regulatory compliance."@en ;
rdfs:label "Data Mapping"@en ;
rdfs:subClassOf ngm:data-integration ;
rdfs:subClassOf _:r6951 ;
rdfs:subClassOf _:r6952 ;
vc:dependsOn ngm:data-modelling ;
vc:dependsOn ngm:schema-mapping ;
vc:enables ngm:data-lineage ;
vc:enables ngm:interoperability ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:data-integration ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-protection ;
vc:requires ngm:data-catalogue ;
vc:requires ngm:data-transformation ;
vc:slug "data-mapping" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:iso-20022 ;
vc:supports ngm:data-governance ;
vc:supports ngm:regulatory-compliance ;
vc:uses ngm:etl-pipeline .
ngm:data-marketplace a owl:Class ;
rdfs:comment "A data marketplace is a platform on which organisations and individuals discover, buy, sell or exchange datasets and data access rights under defined licensing and pricing terms. It provides discovery, valuation, provenance and settlement mechanisms so that data can be treated as a tradeable asset rather than a siloed internal resource. Data marketplaces range from centralised commercial exchanges to decentralised, blockchain-mediated platforms that use smart contracts for access control and payment."@en ;
rdfs:label "Data Marketplace"@en ;
rdfs:subClassOf ngm:marketplace ;
vc:enables ngm:data-monetisation ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.65"^^xsd:float ;
vc:slug "data-marketplace" ;
vc:sourceDomain "data" ;
vc:uses ngm:data .
ngm:data-mart a skos:Concept ;
rdfs:label "Data Mart"@en .
ngm:data-masking a owl:Class ;
rdfs:label "Data Masking"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-data-quality ;
vc:slug "data-masking" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:data-mesh a owl:Class ;
rdfs:comment "Data Mesh is a socio-technical paradigm for large-scale analytical data architecture, coined by Zhamak Dehghani (2020), that decentralises data ownership to domain-aligned teams who treat their analytical datasets as first-class products accessible via standardised interfaces. It rests on four principles: domain-oriented decentralised data ownership, data as a product, self-serve data infrastructure as a platform, and federated computational governance. Unlike monolithic data lakes or warehouses governed by a central data engineering team, a Data Mesh distributes accountability so that the teams who generate data also maintain its quality, documentation, and SLAs as discoverable data products. The model draws on domain-driven design and microservices thinking applied to analytical rather than operational data flows."@en ;
rdfs:label "Data Mesh"@en ;
rdfs:subClassOf ngm:data-governance-framework ;
rdfs:subClassOf _:r6953 ;
rdfs:subClassOf _:r6954 ;
vc:bridgesTo ngm:federated-learning ;
vc:bridgesTo ngm:platform-engineering ;
vc:contrastsWith ngm:data-fabric-architecture ;
vc:contrastsWith ngm:data-warehouse ;
vc:enables ngm:data-analytics ;
vc:enables ngm:distributed-system ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:data-catalog ;
vc:relatedTo ngm:data-governance ;
vc:relatedTo ngm:data-lineage ;
vc:requires ngm:domain-driven-design ;
vc:requires ngm:schema-registry ;
vc:slug "data-mesh" ;
vc:sourceDomain "data" ;
vc:supports ngm:data-lake ;
vc:supports ngm:event-driven-architecture ;
vc:uses ngm:api-gateway ;
vc:uses ngm:data-pipeline ;
vc:uses ngm:microservices-architecture ;
vc:uses ngm:policy-as-code .
ngm:data-migration a skos:Concept ;
rdfs:label "Data Migration"@en .
ngm:data-minimisation a owl:Class ;
rdfs:comment "Data Minimisation is a privacy principle and GDPR requirement (Article 5(1)(c)) mandating that personal data collection and processing be limited to what is adequate, relevant, and necessary for specified purposes, reducing privacy risks by avoiding accumulation of excessive data that could be misused, breached, or enable function creep."@en ;
rdfs:label "Data Minimisation"@en ;
rdfs:subClassOf ngm:privacy-and-data-governance ;
rdfs:subClassOf _:r6955 ;
rdfs:subClassOf _:r6956 ;
rdfs:subClassOf _:r6957 ;
rdfs:subClassOf _:r6958 ;
rdfs:subClassOf _:r6959 ;
vc:bridgesTo ngm:machine-learning-discipline-pipeline ;
vc:bridgesTo ngm:secure-multi-party-computation ;
vc:contrastsWith ngm:personal-data-store ;
vc:dependsOn ngm:data-governance-framework ;
vc:dependsOn ngm:lifecycle-management ;
vc:enables ngm:differential-privacy ;
vc:enables ngm:federated-learning ;
vc:enables ngm:knowledge-distillation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:feature-selection ;
vc:hasPart ngm:purpose-limitation ;
vc:hasPart ngm:retention-policy ;
vc:implements ngm:iso-29100 ;
vc:isPartOf ngm:gdpr-compliance ;
vc:isPartOf ngm:privacy-by-design ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:data-subject-rights ;
vc:relatedTo ngm:privacy-impact-assessment ;
vc:relatedTo ngm:right-to-erasure ;
vc:requires ngm:consent-management ;
vc:requires ngm:data-classification ;
vc:requires ngm:privacy-impact-assessment ;
vc:slug "data-minimisation" ;
vc:sourceDomain "data" ;
vc:standardizedBy ngm:ccpa ;
vc:standardizedBy ngm:gdpr ;
vc:supports ngm:data-protection ;
vc:supports ngm:privacy-framework ;
vc:supports ngm:regulatory-compliance ;
vc:uses ngm:data-anonymization-pipeline ;
vc:uses ngm:dimensionality-reduction ;
vc:uses ngm:sampling .
ngm:data-mining a owl:Class ;
rdfs:comment "Data mining is the computational process of discovering non-obvious patterns, correlations, anomalies and predictive structure in large datasets, sitting at the core of the knowledge discovery in databases (KDD) pipeline. It combines techniques from machine learning, statistics and database systems — including clustering, classification, association-rule learning, regression and anomaly detection — to turn raw operational data into actionable models and insights across science, commerce and government."@en ;
rdfs:label "Data Mining"@en ;
rdfs:subClassOf ngm:knowledge-discovery ;
rdfs:subClassOf _:r6960 ;
rdfs:subClassOf _:r6961 ;
rdfs:subClassOf _:r6962 ;
vc:dependsOn ngm:big-data ;
vc:dependsOn ngm:data-warehouse ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:anomaly-detection ;
vc:hasPart ngm:clustering ;
vc:hasPart ngm:text-mining ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:data-analysis ;
vc:relatedTo ngm:data-science ;
vc:relatedTo ngm:pattern-recognition ;
vc:slug "data-mining" ;
vc:sourceDomain "data" ;
vc:uses ngm:machine-learning-discipline .
ngm:data-model a owl:Class ;
rdfs:comment "A data model is an abstract specification of how data elements are structured, related and constrained within a domain or system. It defines entities, attributes, relationships and integrity rules at conceptual, logical or physical levels of abstraction. Data models are prerequisites for metadata standards and for designing storage, exchange and querying of data."@en ;
rdfs:label "Data Model"@en ;
rdfs:subClassOf ngm:data-management ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:data-management ;
vc:relatedTo ngm:metadata-standard ;
vc:slug "data-model" ;
vc:sourceDomain "data" .
ngm:data-modelling a owl:Class ;
rdfs:comment "Data modelling is the process of defining the structure, relationships, constraints, and semantics of data to be stored, processed, or exchanged in an information system. It produces formal artefacts — conceptual, logical, and physical models — that guide database design, API contracts, and data integration. Effective data modelling ensures data consistency, reduces redundancy, and aligns technical storage structures with the business domain concepts they represent."@en ;
rdfs:label "Data Modelling"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r6963 ;
rdfs:subClassOf _:r6964 ;
rdfs:subClassOf _:r6965 ;
rdfs:subClassOf _:r6966 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:contrastsWith ngm:euclidean-distance ;
vc:dependsOn ngm:data-schema ;
vc:dependsOn ngm:statistical-analysis ;
vc:enables ngm:distributed-ledger ;
vc:enables ngm:machine-learning-discipline ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:data-schema ;
vc:hasPart ngm:statistical-analysis ;
vc:implements ngm:standards ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-management ;
vc:relatedTo ngm:governance ;
vc:relatedTo ngm:tensor-computation ;
vc:requires ngm:data-schema ;
vc:requires ngm:linear-algebra ;
vc:slug "data-modelling" ;
vc:sourceDomain "data" ;
vc:supports ngm:personal-data ;
vc:supports ngm:privacy ;
vc:uses ngm:fourier-transform ;
vc:uses ngm:python-programming-language .
ngm:data-models a owl:Class ;
rdfs:comment "Data models are the collected structural specifications that define how information is represented, related and constrained within a system or framework. In digital-twin and layered service architectures they describe the shape of state, telemetry and interactions exchanged between components. Well-defined data models are a prerequisite for interoperability, validation and consistent behaviour across service layers."@en ;
rdfs:label "Data Models"@en ;
rdfs:subClassOf ngm:data-management ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:digital-twin-framework ;
vc:relatedTo ngm:service-layer ;
vc:slug "data-models" ;
vc:sourceDomain "data" .
ngm:data-monetisation a owl:Class ;
rdfs:comment "Data monetisation is the practice of generating economic value from data assets, either directly by selling data and data-derived products, or indirectly by using data to improve decisions, products and operations. It spans approaches from licensing raw or aggregated datasets through data marketplaces to embedding analytics in services that command a premium. Responsible data monetisation must be balanced against data privacy, consent and governance obligations, and it raises questions about data ownership and the ethics of treating personal information as a tradeable resource."@en ;
rdfs:label "Data Monetisation"@en ;
rdfs:subClassOf ngm:data-governance ;
rdfs:subClassOf _:r6967 ;
rdfs:subClassOf _:r6968 ;
rdfs:subClassOf _:r6969 ;
vc:contrastsWith ngm:data-privacy ;
vc:contrastsWith ngm:surveillance-capitalism ;
vc:dependsOn ngm:data-quality ;
vc:dependsOn ngm:metadata-management ;
vc:enables ngm:data-marketplace ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-classification ;
vc:relatedTo ngm:data-protection ;
vc:relatedTo ngm:regulatory-compliance ;
vc:requires ngm:consent-management ;
vc:requires ngm:data-governance ;
vc:requires ngm:data-quality ;
vc:slug "data-monetisation" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:gdpr ;
vc:supports ngm:data-sharing ;
vc:uses ngm:data-marketplace ;
vc:uses ngm:data-sharing .
ngm:data-nationalism a skos:Concept ;
rdfs:label "Data Nationalism"@en .
ngm:data-normalisation a skos:Concept ;
rdfs:label "Data Normalisation"@en .
ngm:data-observability a owl:Class ;
rdfs:comment "Data observability is the practice of continuously monitoring the health and reliability of data and data pipelines to detect, diagnose and resolve issues before they affect consumers. It tracks pillars such as freshness, volume, schema, distribution and lineage, often using automated anomaly detection. As an extension of metadata management it brings software-style monitoring discipline to data systems."@en ;
rdfs:label "Data Observability"@en ;
rdfs:subClassOf ngm:data-management ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:metadata-management ;
vc:slug "data-observability" ;
vc:sourceDomain "data" .
ngm:data-ordering a skos:Concept ;
rdfs:label "Data Ordering"@en .
ngm:data-ownership a skos:Concept ;
rdfs:label "Data Ownership"@en .
ngm:data-parallelism a owl:Class ;
rdfs:comment "Data parallelism is a parallel computing strategy in which the same operation is applied simultaneously to different partitions of a dataset distributed across multiple processing units. In machine learning it is the dominant approach to scaling model training: the model is replicated on every worker, each worker computes gradients on a distinct mini-batch shard, and gradients are aggregated through collective communication such as all-reduce before the synchronised parameter update. This contrasts with model parallelism, which splits a single model across devices, and underpins large-scale training on GPU and TPU clusters."@en ;
rdfs:label "Data Parallelism"@en ;
rdfs:subClassOf ngm:distributed-ai-training ;
rdfs:subClassOf ngm:distributed-training ;
rdfs:subClassOf ngm:parallel-processing ;
rdfs:subClassOf _:r6970 ;
rdfs:subClassOf _:r6971 ;
rdfs:subClassOf _:r6972 ;
rdfs:subClassOf _:r6973 ;
rdfs:subClassOf _:r6974 ;
rdfs:subClassOf _:r6975 ;
rdfs:subClassOf _:r6976 ;
rdfs:subClassOf _:r6977 ;
rdfs:subClassOf _:r6978 ;
rdfs:subClassOf _:r6979 ;
vc:bridgesTo ngm:expert-parallelism ;
vc:bridgesTo ngm:tensor-parallelism ;
vc:contrastsWith ngm:asynchronous-sgd ;
vc:contrastsWith ngm:federated-learning ;
vc:contrastsWith ngm:model-parallelism ;
vc:contrastsWith ngm:pipeline-parallelism ;
vc:dependsOn ngm:backpropagation ;
vc:dependsOn ngm:batch-size ;
vc:dependsOn ngm:gradient-descent ;
vc:dependsOn ngm:learning-rate ;
vc:dependsOn ngm:loss-function ;
vc:dependsOn ngm:optimiser ;
vc:enables ngm:large-language-models ;
vc:enables ngm:large-scale-training ;
vc:enables ngm:llm-pretraining ;
vc:enables ngm:neural-network-training ;
vc:enables ngm:throughput-scaling ;
vc:enables ngm:transformer-architecture ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:all-reduce ;
vc:hasPart ngm:gradient-aggregation ;
vc:hasPart ngm:gradient-checkpointing ;
vc:hasPart ngm:gradient-compression ;
vc:hasPart ngm:mini-batch ;
vc:hasPart ngm:ring-all-reduce ;
vc:implements ngm:distributed-sgd ;
vc:implements ngm:gradient-descent ;
vc:implements ngm:stochastic-gradient-descent ;
vc:isPartOf ngm:3d-parallelism ;
vc:isPartOf ngm:distributed-training ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:3d-parallelism ;
vc:relatedTo ngm:ai-infrastructure ;
vc:relatedTo ngm:deep-speed ;
vc:relatedTo ngm:di-lo-co ;
vc:relatedTo ngm:distributed-computing ;
vc:relatedTo ngm:expert-parallelism ;
vc:relatedTo ngm:fully-sharded-data-parallel ;
vc:relatedTo ngm:high-performance-computing ;
vc:relatedTo ngm:scaling-laws ;
vc:relatedTo ngm:sharded-data-parallel ;
vc:relatedTo ngm:tensor-parallelism ;
vc:relatedTo ngm:zero-optimizer ;
vc:requires ngm:collective-communication ;
vc:requires ngm:gpu-cluster ;
vc:requires ngm:infiniband ;
vc:requires ngm:interconnect ;
vc:requires ngm:nccl ;
vc:requires ngm:network-bandwidth ;
vc:requires ngm:synchronisation ;
vc:slug "data-parallelism" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:ai-infrastructure ;
vc:standardizedBy ngm:mlperf ;
vc:standardizedBy ngm:nccl ;
vc:standardizedBy ngm:pytorch-ddp ;
vc:supports ngm:convolutional-neural-network ;
vc:supports ngm:deep-learning ;
vc:supports ngm:deep-speed ;
vc:supports ngm:distributed-computing ;
vc:supports ngm:megatron-lm ;
vc:supports ngm:neural-network-training ;
vc:supports ngm:transformer-architecture ;
vc:uses ngm:checkpoints ;
vc:uses ngm:gpu-compute ;
vc:uses ngm:mixed-precision-training ;
vc:uses ngm:parameter-server ;
vc:uses ngm:stochastic-gradient-descent ;
vc:uses ngm:tpu .
ngm:data-partitioning a owl:Class ;
rdfs:comment "Data partitioning is the practice of dividing a dataset into smaller, independently manageable subsets distributed across storage nodes or processing units to improve scalability, performance, and availability. Partitioning strategies include horizontal splitting by key range or hash, vertical splitting by column, and functional splitting by domain, each balancing query locality against load distribution. Effective partitioning underpins distributed databases and large-scale data systems by enabling parallel processing while minimising cross-partition coordination."@en ;
rdfs:label "Data Partitioning"@en ;
rdfs:subClassOf ngm:sharding ;
rdfs:subClassOf _:r6980 ;
rdfs:subClassOf _:r6981 ;
rdfs:subClassOf _:r6982 ;
vc:contrastsWith ngm:replication ;
vc:enables ngm:load-balancing ;
vc:enables ngm:scalability ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:replication ;
vc:hasPart ngm:sharding ;
vc:implements ngm:scalability ;
vc:isPartOf ngm:distributed-ledger ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:replication ;
vc:relatedTo ngm:scalability ;
vc:relatedTo ngm:sharding ;
vc:requires ngm:replication ;
vc:slug "data-partitioning" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:load-balancing ;
vc:uses ngm:sharding .
ngm:data-persistence a owl:Class ;
rdfs:comment "Data Persistence is the property of data surviving beyond the lifetime of the process, session, or physical medium that created it, encompassing all mechanisms and design patterns — relational databases, distributed file systems, append-only event logs, object stores, and key-value stores — that guarantee this durability. In transactional systems, persistence is formalised through the ACID properties (Atomicity, Consistency, Isolation, Durability), where the Durability guarantee ensures committed transactions survive system failure by means of write-ahead logging and fsync operations. Beyond single-node databases, distributed systems trade aspects of consistency for availability and partition tolerance as described in the CAP theorem and the PACELC model, producing a spectrum of persistence strategies from strongly consistent relational systems to eventually consistent distributed NoSQL stores. The selection of a persistence strategy profoundly shapes a system's fault tolerance, latency, throughput, and operational complexity."@en ;
rdfs:label "Data Persistence"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r6983 ;
rdfs:subClassOf _:r6984 ;
rdfs:subClassOf _:r6985 ;
rdfs:subClassOf _:r6986 ;
rdfs:subClassOf _:r6987 ;
rdfs:subClassOf _:r6988 ;
vc:bridgesTo ngm:blockchain-ledger ;
vc:bridgesTo ngm:knowledge-graph ;
vc:bridgesTo ngm:vector-database ;
vc:contrastsWith ngm:eventual-consistency ;
vc:contrastsWith ngm:in-memory-computing ;
vc:contrastsWith ngm:volatile-storage ;
vc:dependsOn ngm:acid-properties ;
vc:dependsOn ngm:consensus-algorithm ;
vc:dependsOn ngm:distributed-system ;
vc:enables ngm:audit-logging ;
vc:enables ngm:crash-recovery ;
vc:enables ngm:data-governance ;
vc:enables ngm:fault-tolerance ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:database-replication ;
vc:hasPart ngm:event-sourcing ;
vc:hasPart ngm:object-storage ;
vc:hasPart ngm:write-ahead-logging ;
vc:implements ngm:cap-theorem ;
vc:implements ngm:pacelc-model ;
vc:isPartOf ngm:data-management ;
vc:isPartOf ngm:system-architecture ;
vc:qualityScore "0.73"^^xsd:float ;
vc:relatedTo ngm:backup-and-recovery ;
vc:relatedTo ngm:data-serialization ;
vc:relatedTo ngm:distributed-computing ;
vc:relatedTo ngm:replication-system ;
vc:requires ngm:database-system ;
vc:requires ngm:file-system ;
vc:requires ngm:storage-engine ;
vc:slug "data-persistence" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:cqrs-pattern ;
vc:supports ngm:event-driven-architecture ;
vc:supports ngm:microservices-architecture ;
vc:uses ngm:b-tree-index ;
vc:uses ngm:erasure-coding ;
vc:uses ngm:lsm-tree .
ngm:data-pipeline a owl:Class ;
rdfs:comment "An automated, end-to-end sequence of connected processing stages that orchestrates data ingestion, transformation, validation, and delivery, enforcing quality assurance and error handling at each stage to produce reliable, actionable analytical outputs for downstream consumers such as machine learning systems and business intelligence platforms."@en ;
rdfs:label "Data Pipeline"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r6989 ;
rdfs:subClassOf _:r6990 ;
rdfs:subClassOf _:r6991 ;
rdfs:subClassOf _:r6992 ;
rdfs:subClassOf _:r6993 ;
rdfs:subClassOf _:r6994 ;
rdfs:subClassOf _:r6995 ;
rdfs:subClassOf _:r6996 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:oracle-service ;
vc:bridgesTo ngm:smart-contract ;
vc:dependsOn ngm:monitoring ;
vc:enables ngm:deep-learning ;
vc:enables ngm:machine-learning-discipline ;
vc:enables ngm:real-time-analytics ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:data-ingestion ;
vc:hasPart ngm:data-transformation ;
vc:hasPart ngm:data-validation ;
vc:hasPart ngm:error-handling ;
vc:hasPart ngm:feature-engineering ;
vc:hasPart ngm:quality-assurance ;
vc:qualityScore "0.65"^^xsd:float ;
vc:relatedTo ngm:data-preprocessing ;
vc:relatedTo ngm:feature-store ;
vc:relatedTo ngm:monitoring-dashboard ;
vc:requires ngm:distributed-storage ;
vc:requires ngm:message-queue ;
vc:slug "data-pipeline" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:audit-trail ;
vc:uses ngm:batch-processing ;
vc:uses ngm:distributed-system ;
vc:uses ngm:etl-pipeline ;
vc:uses ngm:stream-processing .
ngm:data-pipelines a skos:Concept ;
rdfs:label "Data Pipelines"@en .
ngm:data-poisoning a owl:Class ;
rdfs:comment "A training-time adversarial attack where malicious actors inject, modify, or manipulate training data to compromise model integrity, causing targeted misclassifications, backdoor triggers, or general performance degradation."@en ;
rdfs:label "Data Poisoning"@en ;
rdfs:subClassOf ngm:adversarial-attack ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf _:r6997 ;
rdfs:subClassOf _:r6998 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:computer-vision ;
vc:contrastsWith ngm:adversarial-robustness ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:data-augmentation-strategies ;
vc:relatedTo ngm:federated-learning ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:requires ngm:model-training ;
vc:requires ngm:training-data ;
vc:slug "data-poisoning" ;
vc:sourceDomain "artificial-intelligence" .
ngm:data-pooling a skos:Concept ;
rdfs:label "Data Pooling"@en .
ngm:data-portability a owl:Class ;
rdfs:comment "Data portability is the ability for users to obtain, move and reuse their personal or application data across services in a structured, machine-readable format without lock-in. It is both a legal right under regimes such as GDPR and a technical property enabled by open formats and interoperable storage. In decentralised-web designs it lets individuals carry data between providers, shifting control from platforms to users."@en ;
rdfs:label "Data Portability"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r6999 ;
rdfs:subClassOf _:r7000 ;
rdfs:subClassOf _:r7001 ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:bridgesTo ngm:governance ;
vc:contrastsWith ngm:data-silo ;
vc:contrastsWith ngm:platform-lock-in ;
vc:dependsOn ngm:api ;
vc:dependsOn ngm:data-schema ;
vc:enables ngm:data-sovereignty ;
vc:enables ngm:user-sovereignty ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:gdpr ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:decentralised-web ;
vc:relatedTo ngm:digital-identity ;
vc:relatedTo ngm:privacy ;
vc:requires ngm:data-format ;
vc:requires ngm:interoperability ;
vc:requires ngm:open-standards ;
vc:slug "data-portability" ;
vc:sourceDomain "data" ;
vc:standardizedBy ngm:iso ;
vc:standardizedBy ngm:w3-c ;
vc:supports ngm:decentralised-web ;
vc:supports ngm:self-sovereign-identity ;
vc:uses ngm:activity-pub ;
vc:uses ngm:linked-data ;
vc:uses ngm:solid .
ngm:data-portal a skos:Concept ;
rdfs:label "Data Portal"@en .
ngm:data-preprocessing a owl:Class ;
rdfs:comment "Data preprocessing is the stage of a machine learning workflow that transforms raw data into a clean, consistent form suitable for modelling. It encompasses cleaning, normalisation, encoding, imputation and feature engineering to remove noise and align scales and types. The quality of preprocessing strongly determines downstream model accuracy and is a prerequisite for reliable training."@en ;
rdfs:label "Data Preprocessing"@en ;
rdfs:subClassOf ngm:data-pipeline ;
rdfs:subClassOf ngm:data-science-workflow ;
rdfs:subClassOf ngm:machine-learning-discipline-pipeline ;
rdfs:subClassOf ngm:machine-learning-discipline-technique ;
rdfs:subClassOf _:r7002 ;
rdfs:subClassOf _:r7003 ;
rdfs:subClassOf _:r7004 ;
rdfs:subClassOf _:r7005 ;
rdfs:subClassOf _:r7006 ;
rdfs:subClassOf _:r7007 ;
rdfs:subClassOf _:r7008 ;
rdfs:subClassOf _:r7009 ;
rdfs:subClassOf _:r7010 ;
vc:contrastsWith ngm:batch-normalisation ;
vc:contrastsWith ngm:data-augmentation ;
vc:dependsOn ngm:data-distribution ;
vc:dependsOn ngm:multimodal-ai-architecture-learning ;
vc:dependsOn ngm:tabular-data ;
vc:enables ngm:deep-learning ;
vc:enables ngm:model-accuracy ;
vc:enables ngm:neural-network ;
vc:enables ngm:reinforcement-learning ;
vc:enables ngm:supervised-learning ;
vc:enables ngm:unsupervised-learning ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:categorical-encoding ;
vc:hasPart ngm:data-augmentation ;
vc:hasPart ngm:data-cleaning ;
vc:hasPart ngm:dimensionality-reduction ;
vc:hasPart ngm:feature-engineering ;
vc:hasPart ngm:feature-selection ;
vc:hasPart ngm:missing-value-imputation ;
vc:hasPart ngm:normalisation ;
vc:hasPart ngm:outlier-detection ;
vc:hasPart ngm:standardisation ;
vc:implements ngm:data-versioning ;
vc:implements ngm:feature-store ;
vc:implements ngm:mlops ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:auto-ml ;
vc:relatedTo ngm:bias-mitigation-techniques ;
vc:relatedTo ngm:class-imbalance ;
vc:relatedTo ngm:data-cleaning ;
vc:relatedTo ngm:data-leakage ;
vc:relatedTo ngm:differential-privacy ;
vc:relatedTo ngm:fairness ;
vc:relatedTo ngm:feature-engineering ;
vc:relatedTo ngm:federated-learning ;
vc:relatedTo ngm:mlops ;
vc:relatedTo ngm:overfitting ;
vc:relatedTo ngm:regularisation ;
vc:relatedTo ngm:uk-gdpr ;
vc:requires ngm:data-governance ;
vc:requires ngm:data-quality ;
vc:requires ngm:train-test-split ;
vc:slug "data-preprocessing" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:iso-iec-22989-2022 ;
vc:standardizedBy ngm:scikit-learn ;
vc:standardizedBy ngm:tfx ;
vc:supports ngm:computer-vision ;
vc:supports ngm:convolutional-neural-network ;
vc:supports ngm:natural-language-processing ;
vc:supports ngm:time-series-analysis ;
vc:supports ngm:transfer-learning ;
vc:uses ngm:auto-ml ;
vc:uses ngm:autoencoder ;
vc:uses ngm:embedding ;
vc:uses ngm:neural-network-text-tokenisation ;
vc:uses ngm:principal-component-analysis ;
vc:uses ngm:scikit-learn ;
vc:uses ngm:smote .
ngm:data-privacy a owl:Class ;
rdfs:comment "Data Privacy is the governance and engineering discipline that ensures individuals retain meaningful control over their personal information through legal frameworks, technical safeguards, and organisational policies governing the appropriate collection, processing, storage, and sharing of personal data. It spans both the regulatory compliance dimension—expressed in instruments such as GDPR, CCPA, PIPEDA, and sector-specific regulations—and the engineering discipline of privacy-by-design that minimises data exposure through techniques such as anonymisation, pseudonymisation, differential privacy, federated learning, and consent management. As AI training practices, surveillance capitalism, and cross-border data flows intensify the stakes of personal information handling, data privacy functions as a core organisational risk management and trust-building domain. The field requires integration across legal, technical, and organisational layers to be effective, and is increasingly operationalised through dedicated Privacy-Enhancing Technologies (PETs)."@en ;
rdfs:label "Data Privacy"@en ;
rdfs:subClassOf ngm:compliance-framework ;
rdfs:subClassOf _:r7011 ;
rdfs:subClassOf _:r7012 ;
rdfs:subClassOf _:r7013 ;
rdfs:subClassOf _:r7014 ;
rdfs:subClassOf _:r7015 ;
rdfs:subClassOf _:r7016 ;
rdfs:subClassOf _:r7017 ;
vc:bridgesTo ngm:federated-learning ;
vc:bridgesTo ngm:on-device-ai ;
vc:bridgesTo ngm:synthetic-data ;
vc:contrastsWith ngm:data-monetisation ;
vc:contrastsWith ngm:surveillance ;
vc:enables ngm:data-subject-rights ;
vc:enables ngm:digital-trust ;
vc:enables ngm:granular-consent-control ;
vc:enables ngm:informed-consent ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:consent-management ;
vc:hasPart ngm:data-anonymization-pipeline ;
vc:hasPart ngm:data-minimisation ;
vc:hasPart ngm:privacy-by-design ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:cybersecurity ;
vc:relatedTo ngm:gdpr-compliance ;
vc:relatedTo ngm:personal-data-store ;
vc:requires ngm:access-control ;
vc:requires ngm:audit-logging ;
vc:requires ngm:data-governance ;
vc:slug "data-privacy" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:ccpa ;
vc:standardizedBy ngm:gdpr ;
vc:standardizedBy ngm:iso-27701 ;
vc:uses ngm:cryptographic-security ;
vc:uses ngm:differential-privacy ;
vc:uses ngm:federated-learning ;
vc:uses ngm:homomorphic-encryption .
ngm:data-privacy-governance-framework a skos:Concept ;
rdfs:label "Data Privacy Governance Framework"@en .
ngm:data-privacy-vocabulary a skos:Concept ;
rdfs:label "Data Privacy Vocabulary"@en .
ngm:data-processing a owl:Class ;
rdfs:comment "Data Processing is the systematic application of operations — collection, validation, transformation, aggregation, enrichment, and storage — that convert raw, unstructured, or heterogeneous input data into organised, queryable, and semantically coherent representations suitable for analysis, machine learning, or real-time decision-making. It encompasses both batch and streaming paradigms, spanning ETL/ELT pipelines, in-memory computation frameworks, and edge preprocessing workflows that must balance throughput, latency, fault-tolerance, and data quality. Architecturally, data processing sits between raw data ingestion and higher-order analytical or AI workloads, acting as the foundational substrate for knowledge extraction, model training, and operational intelligence. Mature implementations employ declarative query languages, distributed execution engines, schema registries, and lineage tracking to ensure reproducibility and governance across the full data lifecycle."@en ;
rdfs:label "Data Processing"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r7022 ;
rdfs:subClassOf _:r7023 ;
rdfs:subClassOf _:r7024 ;
rdfs:subClassOf _:r7025 ;
rdfs:subClassOf _:r7026 ;
rdfs:subClassOf _:r7027 ;
rdfs:subClassOf _:r7028 ;
rdfs:subClassOf _:r7029 ;
vc:bridgesTo ngm:feature-engineering ;
vc:bridgesTo ngm:sensor-fusion ;
vc:contrastsWith ngm:raw-data ;
vc:dependsOn ngm:data-governance ;
vc:dependsOn ngm:distributed-computing ;
vc:enables ngm:business-intelligence ;
vc:enables ngm:computer-vision ;
vc:enables ngm:data-analytics ;
vc:enables ngm:machine-learning-discipline ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:batch-processing ;
vc:hasPart ngm:data-pipeline ;
vc:hasPart ngm:etl-pipeline ;
vc:hasPart ngm:stream-processing ;
vc:isPartOf ngm:data-management ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:data-lake ;
vc:relatedTo ngm:data-quality ;
vc:relatedTo ngm:data-warehouse ;
vc:requires ngm:data-ingestion ;
vc:requires ngm:data-storage ;
vc:requires ngm:schema-management ;
vc:slug "data-processing" ;
vc:sourceDomain "data" ;
vc:standardizedBy ngm:sql-standard ;
vc:supports ngm:data-lineage ;
vc:supports ngm:real-time-analytics ;
vc:uses ngm:apache-kafka ;
vc:uses ngm:apache-spark ;
vc:uses ngm:edge-computing ;
vc:uses ngm:sql .
ngm:data-processing-hardware a owl:Class ;
rdfs:comment "The computing infrastructure including GPUs, CPUs, specialized accelerators, and edge computing devices that power metaverse applications, virtual reality experiences, and immersive environments, providing the massive processing capabilities required for real-time 3D rendering, AI inference, and ..."@en ;
rdfs:label "Data Processing Hardware"@en ;
rdfs:subClassOf ngm:computing-infrastructure ;
rdfs:subClassOf ngm:infra-computing-and-cloud ;
rdfs:subClassOf _:r7018 ;
rdfs:subClassOf _:r7019 ;
rdfs:subClassOf _:r7020 ;
rdfs:subClassOf _:r7021 ;
skos:broader ngm:infra-computing-and-cloud ;
vc:bridgesTo ngm:sensor-input ;
vc:enables ngm:ai-processing ;
vc:enables ngm:immersive-computing ;
vc:enables ngm:real-time-rendering ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:cooling-system ;
vc:requires ngm:high-bandwidth-memory ;
vc:requires ngm:power-infrastructure ;
vc:slug "data-processing-hardware" ;
vc:sourceDomain "infrastructure" .
ngm:data-processing-state a owl:Class ;
rdfs:label "Data Processing State"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-processing ;
vc:slug "data-processing-state" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:data-processing-unit a skos:Concept ;
rdfs:label "Data Processing Unit"@en .
ngm:data-processor a skos:Concept ;
rdfs:label "Data Processor"@en .
ngm:data-product-version a owl:Class ;
rdfs:label "Data Product Version"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-processing ;
vc:slug "data-product-version" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:data-profile a owl:Class ;
rdfs:label "Data Profile"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:data ;
vc:relatedTo ngm:earth-observation-processing ;
vc:slug "data-profile" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:data-profiling a skos:Concept ;
rdfs:label "Data Profiling"@en .
ngm:data-property a skos:Concept ;
rdfs:label "Data Property"@en .
ngm:data-protection a owl:Class ;
rdfs:comment "A comprehensive set of processes and technologies that safeguard personal and system data in virtual environments through encryption, access control, privacy preservation, and regulatory compliance mechanisms."@en ;
rdfs:label "Data Protection"@en ;
rdfs:subClassOf ngm:sc-governance-and-safety ;
rdfs:subClassOf ngm:security-architecture ;
rdfs:subClassOf _:r7049 ;
rdfs:subClassOf _:r7050 ;
rdfs:subClassOf _:r7051 ;
rdfs:subClassOf _:r7052 ;
rdfs:subClassOf _:r7053 ;
rdfs:subClassOf _:r7054 ;
rdfs:subClassOf _:r7055 ;
rdfs:subClassOf _:r7056 ;
rdfs:subClassOf _:r7057 ;
skos:broader ngm:sc-governance-and-safety ;
vc:bridgesTo ngm:blockchain ;
vc:dependsOn ngm:regulatory-requirements ;
vc:dependsOn ngm:risk-assessment ;
vc:dependsOn ngm:security-policy ;
vc:enables ngm:data-privacy ;
vc:enables ngm:data-sovereignty ;
vc:enables ngm:gdpr-compliance ;
vc:enables ngm:secure-data-sharing ;
vc:enables ngm:user-trust ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:access-control-system ;
vc:hasPart ngm:audit ;
vc:hasPart ngm:data-loss-prevention ;
vc:hasPart ngm:encryption-service ;
vc:hasPart ngm:privacy-policy-engine ;
vc:isPartOf ngm:compliance-management ;
vc:isPartOf ngm:privacy-engineering ;
vc:isPartOf ngm:security-framework ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:authentication ;
vc:requires ngm:authorization ;
vc:requires ngm:cryptographic-keys ;
vc:requires ngm:identity-management ;
vc:slug "data-protection" ;
vc:sourceDomain "spatial-computing" .
ngm:data-protection-authority-notification a skos:Concept ;
rdfs:label "Data Protection Authority Notification"@en .
ngm:data-protection-impact-assessment a owl:Class ;
rdfs:comment "A Data Protection Impact Assessment is a structured process for identifying, evaluating and mitigating the risks that a planned data-processing activity poses to the rights and freedoms of individuals. It documents the nature, scope, context and purposes of processing, assesses necessity and proportionality, and records measures that reduce identified risks. Under the General Data Protection Regulation it is mandatory where processing is likely to result in high risk, such as large-scale profiling or use of sensitive data. It is a core accountability instrument linking privacy-by-design to demonstrable compliance."@en ;
rdfs:label "Data Protection Impact Assessment"@en ;
rdfs:subClassOf ngm:risk-assessment ;
rdfs:subClassOf _:r7030 ;
rdfs:subClassOf _:r7031 ;
rdfs:subClassOf _:r7032 ;
vc:contrastsWith ngm:privacy-impact-assessment ;
vc:dependsOn ngm:data-mapping ;
vc:dependsOn ngm:legal-basis ;
vc:enables ngm:privacy ;
vc:enables ngm:privacy-by-design ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:mitigation-measures ;
vc:hasPart ngm:risk-analysis ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-privacy ;
vc:relatedTo ngm:data-protection-law ;
vc:requires ngm:data-processing ;
vc:requires ngm:gdpr ;
vc:slug "data-protection-impact-assessment" ;
vc:sourceDomain "governance" ;
vc:supports ngm:accountability ;
vc:supports ngm:compliance ;
vc:uses ngm:data-governance .
ngm:data-protection-law a owl:Class ;
rdfs:comment "The body of law governing how personal data may be collected, processed, stored and shared, and the rights afforded to individuals over their personal information."@en ;
rdfs:label "Data Protection Law"@en ;
rdfs:subClassOf ngm:data-protection ;
rdfs:subClassOf _:r7033 ;
rdfs:subClassOf _:r7034 ;
rdfs:subClassOf _:r7035 ;
rdfs:subClassOf _:r7036 ;
rdfs:subClassOf _:r7037 ;
rdfs:subClassOf _:r7038 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:ccpa ;
vc:bridgesTo ngm:cybersecurity ;
vc:bridgesTo ngm:gdpr ;
vc:contrastsWith ngm:surveillance-capitalism ;
vc:dependsOn ngm:personal-data ;
vc:enables ngm:accountability ;
vc:enables ngm:data-privacy ;
vc:enables ngm:privacy ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:ccpa ;
vc:hasPart ngm:data-subject-rights ;
vc:hasPart ngm:gdpr ;
vc:implements ngm:data-minimisation ;
vc:implements ngm:privacy-by-design ;
vc:isPartOf ngm:governance ;
vc:isPartOf ngm:regulatory-compliance ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:data-portability ;
vc:relatedTo ngm:right-to-be-forgotten ;
vc:requires ngm:consent-management ;
vc:requires ngm:data-governance ;
vc:requires ngm:data-protection ;
vc:slug "data-protection-law" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:iso-27701 ;
vc:supports ngm:digital-rights ;
vc:supports ngm:information-security ;
vc:uses ngm:data-breach-notification ;
vc:uses ngm:data-protection-impact-assessment .
ngm:data-protection-management-system a skos:Concept ;
rdfs:label "Data Protection Management System"@en .
ngm:data-protection-officer a owl:Class ;
rdfs:comment "A Data Protection Officer (DPO) is an organisational role responsible for overseeing an entity's data-protection strategy and monitoring compliance with applicable privacy law such as the GDPR. The DPO advises on data-protection obligations, conducts and reviews privacy impact assessments, serves as the contact point for supervisory authorities and data subjects, and operates with independence from operational management. Designation of a DPO is mandatory under the GDPR for public authorities and for controllers or processors whose core activities involve large-scale or sensitive personal-data processing."@en ;
rdfs:label "Data Protection Officer"@en ;
rdfs:subClassOf ngm:data-governance ;
rdfs:subClassOf _:r7039 ;
rdfs:subClassOf _:r7040 ;
vc:dependsOn ngm:gdpr ;
vc:enables ngm:consent-management ;
vc:enables ngm:privacy-by-design ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:pseudonymisation ;
vc:isPartOf ngm:data-governance ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:compliance ;
vc:relatedTo ngm:data-protection ;
vc:relatedTo ngm:supervisory-authority ;
vc:requires ngm:privacy-impact-assessment ;
vc:requires ngm:regulatory-compliance ;
vc:slug "data-protection-officer" ;
vc:sourceDomain "governance" ;
vc:supports ngm:accountability ;
vc:supports ngm:data-privacy ;
vc:supports ngm:data-subject-rights .
ngm:data-protection-regulation a owl:Class ;
rdfs:comment "Data Protection Regulation comprises the body of legally binding instruments — including the EU General Data Protection Regulation (GDPR, 2018), the UK Data Protection Act 2018, the California Consumer Privacy Act (CCPA), and equivalent national or regional laws — that govern the collection, processing, storage, transfer, and erasure of personal data by organisations. These frameworks establish fundamental principles such as lawfulness, purpose limitation, data minimisation, and accountability; confer enforceable rights on data subjects (access, rectification, erasure, portability, and objection); and require proportionate technical and organisational safeguards, including impact assessments for high-risk processing. The regulation of personal data intersects directly with AI system design, automated decision-making constraints, consent management infrastructure, and cross-border data flows in globally distributed architectures."@en ;
rdfs:label "Data Protection Regulation"@en ;
rdfs:subClassOf ngm:regulatory-framework ;
rdfs:subClassOf _:r7041 ;
rdfs:subClassOf _:r7042 ;
rdfs:subClassOf _:r7043 ;
rdfs:subClassOf _:r7044 ;
rdfs:subClassOf _:r7045 ;
rdfs:subClassOf _:r7046 ;
rdfs:subClassOf _:r7047 ;
rdfs:subClassOf _:r7048 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:federated-learning ;
vc:bridgesTo ngm:zero-knowledge-proof ;
vc:contrastsWith ngm:data-free-flow ;
vc:contrastsWith ngm:surveillance-capitalism ;
vc:enables ngm:accountability ;
vc:enables ngm:data-subject-rights ;
vc:enables ngm:informed-consent ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:consent-management ;
vc:hasPart ngm:data-subject-rights ;
vc:hasPart ngm:gdpr ;
vc:hasPart ngm:privacy-impact-assessment ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:cybersecurity-law ;
vc:relatedTo ngm:data-residency ;
vc:relatedTo ngm:identity-management ;
vc:relatedTo ngm:regulatory-technology ;
vc:requires ngm:access-control ;
vc:requires ngm:data-governance ;
vc:requires ngm:data-minimisation ;
vc:requires ngm:privacy-preserving-technology ;
vc:slug "data-protection-regulation" ;
vc:sourceDomain "governance" ;
vc:supports ngm:compliance-framework ;
vc:supports ngm:digital-trust ;
vc:supports ngm:responsible-ai .
ngm:data-provenance a owl:Class ;
rdfs:comment "A continuous process of recording and tracking the origin, lineage, and transformation history of data objects, enabling traceability, validation of data quality, and verification of authenticity throughout the data lifecycle."@en ;
rdfs:label "Data Provenance"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r7058 ;
rdfs:subClassOf _:r7059 ;
rdfs:subClassOf _:r7060 ;
rdfs:subClassOf _:r7061 ;
rdfs:subClassOf _:r7062 ;
rdfs:subClassOf _:r7063 ;
rdfs:subClassOf _:r7064 ;
rdfs:subClassOf _:r7065 ;
rdfs:subClassOf _:r7066 ;
vc:bridgesTo ngm:blockchain ;
vc:dependsOn ngm:blockchain ;
vc:dependsOn ngm:event-logging ;
vc:dependsOn ngm:identity-management ;
vc:enables ngm:attribution ;
vc:enables ngm:compliance-audit ;
vc:enables ngm:data-quality ;
vc:enables ngm:provenance-verification ;
vc:enables ngm:reproducibility ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:audit-trail ;
vc:hasPart ngm:data-lineage-tracking ;
vc:hasPart ngm:provenance ;
vc:hasPart ngm:signature-validator ;
vc:hasPart ngm:timestamp-service ;
vc:isPartOf ngm:data-governance ;
vc:isPartOf ngm:data-management ;
vc:isPartOf ngm:trust-framework ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:digital-signature ;
vc:requires ngm:metadata ;
vc:requires ngm:timestamp-authority ;
vc:slug "data-provenance" ;
vc:sourceDomain "infrastructure" .
ngm:data-quality a owl:Class ;
rdfs:comment "Data Quality is the degree to which a dataset is fit for its intended purpose, evaluated across multiple dimensions including accuracy, completeness, consistency, timeliness, uniqueness, and validity. It encompasses the processes, standards, and metrics used to assess, monitor, cleanse, and continuously improve the reliability and trustworthiness of data assets. High data quality is a foundational prerequisite for sound analytics, machine learning model performance, regulatory compliance, and effective decision-making across all data-driven disciplines. Its absence propagates errors through downstream systems, undermining the value of even sophisticated analytical and AI pipelines."@en ;
rdfs:label "Data Quality"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r7071 ;
rdfs:subClassOf _:r7072 ;
rdfs:subClassOf _:r7073 ;
rdfs:subClassOf _:r7074 ;
vc:bridgesTo ngm:feature-engineering ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:contrastsWith ngm:dark-data ;
vc:contrastsWith ngm:data-debt ;
vc:dependsOn ngm:data-integration ;
vc:dependsOn ngm:etl-pipeline ;
vc:enables ngm:business-intelligence ;
vc:enables ngm:master-data-management ;
vc:enables ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:data-cleansing ;
vc:hasPart ngm:data-lineage ;
vc:hasPart ngm:data-profiling ;
vc:hasPart ngm:data-validation ;
vc:isPartOf ngm:data-management ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:data-mesh ;
vc:relatedTo ngm:data-observability ;
vc:requires ngm:data-cataloguing ;
vc:requires ngm:data-governance ;
vc:requires ngm:metadata-management ;
vc:slug "data-quality" ;
vc:sourceDomain "data" ;
vc:standardizedBy ngm:dama-dmbok ;
vc:standardizedBy ngm:iso-8000 ;
vc:supports ngm:data-warehouse ;
vc:supports ngm:decision-support ;
vc:uses ngm:entity-resolution ;
vc:uses ngm:statistical-process-control .
ngm:data-quality-check a skos:Concept ;
rdfs:label "Data Quality Check"@en .
ngm:data-quality-management a owl:Class ;
rdfs:comment "Data quality management is the discipline of measuring, monitoring, and improving the accuracy, completeness, consistency, and timeliness of data across its lifecycle. It combines profiling, validation, cleansing, and continuous monitoring with governance policies that define quality expectations. Reliable data quality is a precondition for trustworthy analytics, machine learning, and regulatory reporting."@en ;
rdfs:label "Data Quality Management"@en ;
rdfs:subClassOf ngm:data-quality ;
rdfs:subClassOf _:r7067 ;
rdfs:subClassOf _:r7068 ;
rdfs:subClassOf _:r7069 ;
rdfs:subClassOf _:r7070 ;
vc:bridgesTo ngm:data-observability ;
vc:dependsOn ngm:data-governance ;
vc:enables ngm:data-integrity ;
vc:enables ngm:master-data-management ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:data-cleaning ;
vc:hasPart ngm:data-integrity ;
vc:implements ngm:data-governance ;
vc:isPartOf ngm:data-governance ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-management ;
vc:relatedTo ngm:data-pipeline ;
vc:requires ngm:data-lineage ;
vc:requires ngm:metadata-management ;
vc:slug "data-quality-management" ;
vc:sourceDomain "data" ;
vc:supports ngm:data-analytics ;
vc:supports ngm:machine-learning-discipline ;
vc:uses ngm:data-catalog ;
vc:uses ngm:data-observability .
ngm:data-quality-metrics a skos:Concept ;
rdfs:label "Data Quality Metrics"@en .
ngm:data-readiness a skos:Concept ;
rdfs:label "Data Readiness"@en .
ngm:data-record a skos:Concept ;
rdfs:label "Data Record"@en .
ngm:data-redundancy a owl:Class ;
rdfs:comment "Data redundancy is the deliberate storage of duplicate or recoverable copies of data so that information survives hardware failure, corruption or loss. Implemented through replication, mirroring, RAID and erasure or forward-error-correction codes, it trades extra capacity for durability and availability. It is a foundational reliability technique in storage systems and distributed infrastructure."@en ;
rdfs:label "Data Redundancy"@en ;
rdfs:subClassOf ngm:infra-computing-and-cloud ;
skos:broader ngm:infra-computing-and-cloud ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:data-storage ;
vc:relatedTo ngm:forward-error-correction ;
vc:slug "data-redundancy" ;
vc:sourceDomain "infrastructure" .
ngm:data-registry a owl:Class ;
rdfs:comment "A Data Registry is a centralised or federated catalogue that maintains authoritative records of data assets, their schemas, provenance, ownership, and access policies. In digital and metaverse infrastructure, registries track digital assets, avatar identities, spatial anchors, and ontological terms, enabling discovery, governance, and interoperability across distributed systems. Blockchain-anchored registries provide tamper-evident provenance and decentralised control."@en ;
rdfs:label "Data Registry"@en ;
rdfs:subClassOf ngm:data-management ;
vc:bridgesTo ngm:blockchain ;
vc:enables ngm:data-governance ;
vc:enables ngm:data-interoperability ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:slug "data-registry" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:data-access-interface ;
vc:supports ngm:digital-asset-management ;
vc:uses ngm:blockchain ;
vc:uses ngm:digital-identity .
ngm:data-replication a owl:Class ;
rdfs:comment "The process of copying and maintaining data across multiple nodes, servers, or locations in distributed systems to ensure consistency, availability, and fault tolerance, using consensus algorithms like Paxos, Raft, and Byzantine Fault Tolerant protocols to coordinate state across decentralised networks."@en ;
rdfs:label "Data Replication"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf ngm:distributed-systems ;
rdfs:subClassOf _:r7075 ;
rdfs:subClassOf _:r7076 ;
rdfs:subClassOf _:r7077 ;
rdfs:subClassOf _:r7078 ;
rdfs:subClassOf _:r7079 ;
rdfs:subClassOf _:r7080 ;
rdfs:subClassOf _:r7081 ;
vc:bridgesTo ngm:blockchain ;
vc:contrastsWith ngm:data-partitioning ;
vc:contrastsWith ngm:sharding ;
vc:dependsOn ngm:cap-theorem ;
vc:dependsOn ngm:distributed-systems ;
vc:enables ngm:consistency-guarantees ;
vc:enables ngm:data-availability ;
vc:enables ngm:disaster-recovery ;
vc:enables ngm:fault-tolerance ;
vc:enables ngm:high-availability ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:change-data-capture ;
vc:hasPart ngm:leader-election ;
vc:hasPart ngm:log-replication ;
vc:qualityScore "0.72"^^xsd:float ;
vc:requires ngm:consensus-algorithm ;
vc:requires ngm:network-bandwidth ;
vc:requires ngm:network-infrastructure ;
vc:requires ngm:storage-systems ;
vc:slug "data-replication" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:cloud-storage ;
vc:supports ngm:distributed-databases ;
vc:supports ngm:edge-computing ;
vc:uses ngm:paxos ;
vc:uses ngm:raft ;
vc:uses ngm:write-ahead-logging .
ngm:data-reporting a skos:Concept ;
rdfs:label "Data Reporting"@en .
ngm:data-residency a owl:Class ;
rdfs:comment "The physical or geographic location in which an organisation's data is stored and processed, and the practice of controlling that location to satisfy regulatory, contractual, tax, or policy requirements; data residency underpins localisation mandates and sovereignty claims by determining which jurisdiction's laws, courts, and government access powers apply to the data."@en ;
rdfs:label "Data Residency"@en ;
rdfs:subClassOf ngm:data-governance ;
vc:dependsOn ngm:cloud-computing ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:data-localisation ;
vc:relatedTo ngm:data-protection-regulation ;
vc:relatedTo ngm:data-sovereignty ;
vc:slug "data-residency" ;
vc:sourceDomain "governance" .
ngm:data-residency-controls a skos:Concept ;
rdfs:label "Data Residency Controls"@en .
ngm:data-residency-infrastructure a skos:Concept ;
rdfs:label "Data Residency Infrastructure"@en .
ngm:data-retention a skos:Concept ;
rdfs:label "Data Retention"@en .
ngm:data-reweighting a skos:Concept ;
rdfs:label "Data Reweighting"@en .
ngm:data-schema a owl:Class ;
rdfs:comment "A Data Schema is a formal specification that defines the structure, types, constraints, and semantics of data within a system or exchange protocol. It enumerates fields, their data types, cardinality rules, allowed values, and relationships between entities, enabling machines to validate conformance and enabling humans to understand data contracts. Data schemas are expressed in formalisms such as JSON Schema, XML Schema Definition, RDF SHACL, or OWL, and are versioned to manage evolution over time. They underpin interoperability between systems, database design, API contracts, and linked-data publishing."@en ;
rdfs:label "Data Schema"@en ;
rdfs:subClassOf ngm:schema-definition ;
rdfs:subClassOf _:r7082 ;
rdfs:subClassOf _:r7083 ;
rdfs:subClassOf _:r7084 ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:contrastsWith ngm:database-system ;
vc:enables ngm:api-contract ;
vc:enables ngm:data-interoperability ;
vc:enables ngm:data-validation ;
vc:enables ngm:knowledge-representation ;
vc:enables ngm:schema-registry ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:constraint ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:credential-schema ;
vc:relatedTo ngm:knowledge-graph ;
vc:relatedTo ngm:metadata-schema ;
vc:relatedTo ngm:ontology ;
vc:requires ngm:data-type ;
vc:requires ngm:namespace ;
vc:slug "data-schema" ;
vc:sourceDomain "data" ;
vc:supports ngm:data-governance ;
vc:supports ngm:linked-data ;
vc:supports ngm:schema-versioning ;
vc:uses ngm:json-data-interchange-format-schema ;
vc:uses ngm:json-ld ;
vc:uses ngm:owl ;
vc:uses ngm:rdf ;
vc:uses ngm:shacl ;
vc:uses ngm:xml-schema-definition .
ngm:data-science a owl:Class ;
rdfs:comment "Data science is an interdisciplinary field that combines statistics, programming, and domain knowledge to extract insight and build predictive models from data. It spans the full lifecycle from data acquisition and cleaning through exploratory analysis, modelling, and communication of results. Data science underpins evidence-based decision-making and supplies the analytical foundation for applied machine learning."@en ;
rdfs:label "Data Science"@en ;
rdfs:subClassOf ngm:data-analytics ;
rdfs:subClassOf _:r7085 ;
rdfs:subClassOf _:r7086 ;
rdfs:subClassOf _:r7087 ;
rdfs:subClassOf _:r7088 ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:contrastsWith ngm:data-engineering ;
vc:dependsOn ngm:data-engineering ;
vc:enables ngm:decision-support ;
vc:enables ngm:predictive-analytics ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:feature-engineering ;
vc:hasPart ngm:statistics ;
vc:implements ngm:supervised-learning ;
vc:isPartOf ngm:data-analytics ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-visualisation ;
vc:relatedTo ngm:deep-learning ;
vc:relatedTo ngm:unsupervised-learning ;
vc:requires ngm:data-engineering ;
vc:requires ngm:statistics ;
vc:slug "data-science" ;
vc:sourceDomain "data" ;
vc:supports ngm:business-intelligence ;
vc:supports ngm:decision-support ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:python .
ngm:data-security a owl:Class ;
rdfs:comment "Data security comprises the policies, controls, and technologies that protect digital information from unauthorised access, corruption, or theft throughout its lifecycle. It spans encryption at rest and in transit, access control mechanisms, identity verification, and governance frameworks that together ensure confidentiality, integrity, and availability of data assets."@en ;
rdfs:label "Data Security"@en ;
rdfs:subClassOf ngm:information-security ;
rdfs:subClassOf _:r7089 ;
rdfs:subClassOf _:r7090 ;
rdfs:subClassOf _:r7091 ;
rdfs:subClassOf _:r7092 ;
rdfs:subClassOf _:r7093 ;
rdfs:subClassOf _:r7094 ;
rdfs:subClassOf _:r7095 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:decentralised-identity ;
vc:contrastsWith ngm:data-breach ;
vc:contrastsWith ngm:open-data ;
vc:enables ngm:audit-trail ;
vc:enables ngm:data-integrity ;
vc:enables ngm:regulatory-compliance ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:data-loss-prevention ;
vc:hasPart ngm:data-masking ;
vc:hasPart ngm:identity-and-access-management ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:cybersecurity ;
vc:relatedTo ngm:threat-modelling ;
vc:relatedTo ngm:vulnerability-management ;
vc:requires ngm:access-control ;
vc:requires ngm:authentication ;
vc:requires ngm:encryption ;
vc:requires ngm:key-management ;
vc:slug "data-security" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:gdpr ;
vc:standardizedBy ngm:iso-27001 ;
vc:standardizedBy ngm:nist-cybersecurity-framework ;
vc:supports ngm:data-governance ;
vc:supports ngm:privacy ;
vc:supports ngm:zero-trust-architecture .
ngm:data-serialization a owl:Class ;
rdfs:comment "Data Serialization is the process of converting structured in-memory data objects — including primitive types, collections, and complex graphs — into a byte-sequence or character-stream representation that can be stored persistently, transmitted across a network boundary, or reconstructed (deserialised) into an equivalent in-memory representation on a different machine or at a different time, potentially running different software. Serialization formats vary along axes of human readability (JSON, YAML, XML versus binary), schema enforcement (Protocol Buffers, Apache Avro with mandatory schemas versus schemaless JSON), compactness, and cross-language support, making format selection a critical engineering decision that affects system interoperability, performance, and evolvability."@en ;
rdfs:label "Data Serialization"@en ;
rdfs:subClassOf ngm:data-format ;
rdfs:subClassOf _:r7096 ;
rdfs:subClassOf _:r7097 ;
vc:bridgesTo ngm:distributed-systems ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:enables ngm:data-pipeline ;
vc:enables ngm:interoperability-protocol ;
vc:enables ngm:message-passing ;
vc:enables ngm:remote-procedure-call ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:apache-avro ;
vc:relatedTo ngm:binary-encoding ;
vc:relatedTo ngm:data-format-standard ;
vc:relatedTo ngm:json-data-interchange-format ;
vc:relatedTo ngm:messagepack ;
vc:relatedTo ngm:protocol-buffer ;
vc:relatedTo ngm:schema-registry ;
vc:relatedTo ngm:xml ;
vc:relatedTo ngm:yaml ;
vc:requires ngm:backward-compatibility ;
vc:requires ngm:schema-evolution ;
vc:slug "data-serialization" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:internet-engineering-task-force ;
vc:standardizedBy ngm:w3-c ;
vc:supports ngm:data-storage ;
vc:supports ngm:event-streaming ;
vc:supports ngm:network-communication ;
vc:uses ngm:data-schema ;
vc:uses ngm:type-system .
ngm:data-sharing a owl:Class ;
rdfs:comment "The controlled exchange of datasets, data streams, or derived information between organisations, systems, or individuals under agreed governance, access control, and privacy constraints. Data sharing in distributed infrastructure contexts relies on interoperability standards, consent management frameworks, and data governance policies to balance openness with security and sovereignty."@en ;
rdfs:label "Data Sharing"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r7098 ;
rdfs:subClassOf _:r7099 ;
vc:bridgesTo ngm:blockchain ;
vc:enables ngm:data-interoperability ;
vc:enables ngm:federated-learning ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:data-sovereignty ;
vc:relatedTo ngm:privacy ;
vc:requires ngm:access-control ;
vc:requires ngm:data-governance ;
vc:slug "data-sharing" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:data-standards ;
vc:uses ngm:interoperability .
ngm:data-silo a owl:Class ;
rdfs:comment "A data silo is an isolated repository of data controlled by one team, system, or department and not readily accessible to the rest of an organisation. Silos arise from fragmented tooling, organisational boundaries, and incompatible formats, producing duplicated, inconsistent, and underused data. They are the principal obstacle that data integration, governance, and interoperability efforts seek to dismantle."@en ;
rdfs:label "Data Silo"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r7100 ;
vc:bridgesTo ngm:interoperability ;
vc:contrastsWith ngm:data-fabric ;
vc:contrastsWith ngm:data-integration ;
vc:contrastsWith ngm:data-mesh ;
vc:dependsOn ngm:data-management ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:data-management ;
vc:isPartOf ngm:data-management ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-governance ;
vc:relatedTo ngm:enterprise-data ;
vc:requires ngm:data-quality ;
vc:slug "data-silo" ;
vc:sourceDomain "data" ;
vc:supports ngm:data-warehouse ;
vc:uses ngm:metadata-management .
ngm:data-simulator a skos:Concept ;
rdfs:label "Data Simulator"@en .
ngm:data-snapshot a skos:Concept ;
rdfs:label "Data Snapshot"@en .
ngm:data-source a skos:Concept ;
rdfs:label "Data Source"@en .
ngm:data-sovereignty a owl:Class ;
rdfs:comment "Data sovereignty is the legal and political principle that digital data is subject to the laws, governance structures, and enforcement jurisdiction of the nation, region, or community in which it originates or is processed. It encompasses requirements such as data localisation (mandating that data remain physically within specified geographic boundaries), restrictions on cross-border data flows, and the right of governments or communities to compel access for regulatory, security, or cultural-preservation purposes. Data sovereignty directly shapes cloud architecture decisions, AI training dataset curation, federated system design, and multinational data-sharing agreements. It intersects with — yet is conceptually distinct from — privacy rights, data protection law, and cybersecurity, being principally concerned with jurisdictional control rather than individual rights."@en ;
rdfs:label "Data Sovereignty"@en ;
rdfs:subClassOf ngm:data-governance ;
rdfs:subClassOf _:r7101 ;
rdfs:subClassOf _:r7102 ;
rdfs:subClassOf _:r7103 ;
rdfs:subClassOf _:r7104 ;
vc:bridgesTo ngm:decentralised-identity ;
vc:bridgesTo ngm:digital-trade ;
vc:bridgesTo ngm:zero-trust-architecture ;
vc:contrastsWith ngm:cloud-portability ;
vc:contrastsWith ngm:data-free-flow ;
vc:dependsOn ngm:data-residency ;
vc:dependsOn ngm:encryption ;
vc:enables ngm:indigenous-data-sovereignty ;
vc:enables ngm:national-ai-strategy ;
vc:enables ngm:sovereign-cloud ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:data-protection ;
vc:implements ngm:gdpr ;
vc:qualityScore "0.76"^^xsd:float ;
vc:relatedTo ngm:cloud-computing ;
vc:relatedTo ngm:cross-border-data-transfer ;
vc:relatedTo ngm:cybersecurity ;
vc:relatedTo ngm:vendor-lock-in ;
vc:requires ngm:access-control ;
vc:requires ngm:data-localisation ;
vc:requires ngm:jurisdiction ;
vc:requires ngm:regulatory-compliance ;
vc:slug "data-sovereignty" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:cloud-security-alliance ;
vc:standardizedBy ngm:iso-iec-27701 ;
vc:supports ngm:digital-autonomy ;
vc:supports ngm:national-security ;
vc:supports ngm:privacy ;
vc:uses ngm:confidential-computing ;
vc:uses ngm:federated-learning ;
vc:uses ngm:homomorphic-encryption ;
vc:uses ngm:secure-multi-party-computation .
ngm:data-split a skos:Concept ;
rdfs:label "Data Split"@en .
ngm:data-splits a skos:Concept ;
rdfs:label "Data Splits"@en .
ngm:data-standardisation a skos:Concept ;
rdfs:label "Data Standardisation"@en .
ngm:data-standardization a skos:Concept ;
rdfs:label "Data Standardization"@en .
ngm:data-standards a owl:Class ;
rdfs:comment "Data Standards are formally agreed specifications, schemas, formats, vocabularies, and protocols that define how data is structured, encoded, exchanged, and interpreted across systems, organisations, and domains. They enable interoperability between heterogeneous systems by establishing shared semantics and syntactic conventions, reducing integration costs and data quality errors. Governed by bodies such as ISO, W3C, IETF, and NIST, data standards span a spectrum from de facto industry conventions (e.g., JSON, CSV) to de jure normative specifications (e.g., SQL:2023, OWL2, FHIR). They are foundational to data governance, metadata management, and the reliable operation of distributed data ecosystems."@en ;
rdfs:label "Data Standards"@en ;
rdfs:subClassOf ngm:data-governance ;
rdfs:subClassOf _:r7105 ;
rdfs:subClassOf _:r7106 ;
rdfs:subClassOf _:r7107 ;
rdfs:subClassOf _:r7108 ;
rdfs:subClassOf _:r7109 ;
rdfs:subClassOf _:r7110 ;
vc:bridgesTo ngm:federated-learning ;
vc:bridgesTo ngm:knowledge-graph ;
vc:bridgesTo ngm:semantic-web-linked-data-standard ;
vc:contrastsWith ngm:data-silo ;
vc:contrastsWith ngm:proprietary-format ;
vc:dependsOn ngm:consensus-process ;
vc:dependsOn ngm:standards-body ;
vc:enables ngm:data-integration ;
vc:enables ngm:data-interoperability ;
vc:enables ngm:linked-data ;
vc:enables ngm:open-data ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:controlled-vocabulary ;
vc:hasPart ngm:data-exchange-format ;
vc:hasPart ngm:data-schema ;
vc:hasPart ngm:metadata-standard ;
vc:implements ngm:fair-data-principles ;
vc:isPartOf ngm:data-governance ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:data-architecture ;
vc:relatedTo ngm:ontology ;
vc:requires ngm:data-quality ;
vc:requires ngm:semantic-interoperability ;
vc:slug "data-standards" ;
vc:sourceDomain "data" ;
vc:standardizedBy ngm:ietf ;
vc:standardizedBy ngm:iso ;
vc:standardizedBy ngm:w3-c ;
vc:supports ngm:data-catalogue ;
vc:supports ngm:master-data-management ;
vc:supports ngm:regulatory-compliance ;
vc:uses ngm:json-data-interchange-format ;
vc:uses ngm:rdf ;
vc:uses ngm:xml .
ngm:data-steward a skos:Concept ;
rdfs:label "Data Steward"@en .
ngm:data-stewardship a owl:Class ;
rdfs:comment "Data stewardship is the operational accountability for managing an organisation's data assets across their lifecycle, ensuring they are accurate, well-documented, secure, and used in line with policy. Data stewards act as the human layer of data governance, owning definitions, resolving quality issues, and curating metadata and lineage. It bridges governance policy and day-to-day data practice, enabling trustworthy, reusable data."@en ;
rdfs:label "Data Stewardship"@en ;
rdfs:subClassOf ngm:data-governance ;
rdfs:subClassOf _:r7111 ;
rdfs:subClassOf _:r7112 ;
vc:dependsOn ngm:data-catalog ;
vc:enables ngm:data-quality ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:data-steward ;
vc:implements ngm:data-governance ;
vc:isPartOf ngm:data-governance ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-management ;
vc:relatedTo ngm:interoperability ;
vc:requires ngm:data-quality ;
vc:requires ngm:metadata-management ;
vc:slug "data-stewardship" ;
vc:sourceDomain "governance" ;
vc:supports ngm:master-data-management ;
vc:uses ngm:data-catalog ;
vc:uses ngm:data-lineage .
ngm:data-storage a owl:Class ;
rdfs:comment "Data storage encompasses the systems, technologies, and architectures used to capture, retain, and retrieve digital information for ongoing and future use. It includes file, block, and object storage paradigms alongside the hardware and software infrastructure ensuring data persistence, accessibility, availability, and protection against loss or corruption."@en ;
rdfs:label "Data Storage"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf ngm:technology-infrastructure-domain-component ;
rdfs:subClassOf _:r7121 ;
rdfs:subClassOf _:r7122 ;
rdfs:subClassOf _:r7123 ;
rdfs:subClassOf _:r7124 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:cloud-computing ;
vc:bridgesTo ngm:distributed-file-system ;
vc:contrastsWith ngm:in-memory-computing ;
vc:enables ngm:backup-and-recovery ;
vc:enables ngm:data-analytics ;
vc:enables ngm:data-persistence ;
vc:enables ngm:information-retrieval ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:block-storage ;
vc:hasPart ngm:file-storage ;
vc:hasPart ngm:object-storage ;
vc:implements ngm:data-encryption-at-rest ;
vc:implements ngm:data-redundancy ;
vc:implements ngm:storage-architecture ;
vc:isPartOf ngm:data-centre ;
vc:qualityScore "0.72"^^xsd:float ;
vc:requires ngm:file-system ;
vc:slug "data-storage" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:disaster-recovery ;
vc:supports ngm:lifecycle-management ;
vc:uses ngm:data-compression ;
vc:uses ngm:erasure-coding ;
vc:uses ngm:raid .
ngm:data-storage-layer a owl:Class ;
rdfs:comment "Software layer managing persistent storage, retrieval, and lifecycle of digital assets, metadata, world state, user data, and transactional records in metaverse systems."@en ;
rdfs:label "Data Storage Layer"@en ;
rdfs:subClassOf ngm:data-layer ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r7113 ;
rdfs:subClassOf _:r7114 ;
rdfs:subClassOf _:r7115 ;
rdfs:subClassOf _:r7116 ;
rdfs:subClassOf _:r7117 ;
rdfs:subClassOf _:r7118 ;
rdfs:subClassOf _:r7119 ;
rdfs:subClassOf _:r7120 ;
vc:bridgesTo ngm:blockchain ;
vc:dependsOn ngm:encryption-service ;
vc:dependsOn ngm:on-chain-data-indexing ;
vc:dependsOn ngm:replication ;
vc:enables ngm:asset-persistence ;
vc:enables ngm:content-distribution ;
vc:enables ngm:data-analytics ;
vc:enables ngm:state-management ;
vc:enables ngm:user-profile-storage ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:blockchain-storage ;
vc:hasPart ngm:cache-layer ;
vc:hasPart ngm:cdn-storage ;
vc:hasPart ngm:database-system ;
vc:hasPart ngm:object-storage ;
vc:isPartOf ngm:metaverse-stack ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:backup-and-recovery ;
vc:requires ngm:network-infrastructure ;
vc:requires ngm:storage-hardware ;
vc:slug "data-storage-layer" ;
vc:sourceDomain "infrastructure" .
ngm:data-storytelling a skos:Concept ;
rdfs:label "Data Storytelling"@en .
ngm:data-structure a owl:Class ;
rdfs:comment "A data structure is an organizational scheme for efficiently storing, accessing, and manipulating data, encompassing arrays, trees, graphs, hash tables, and tensors that underpin algorithmic computation and machine learning systems."@en ;
rdfs:label "Data Structure"@en ;
rdfs:subClassOf ngm:software-engineering ;
rdfs:subClassOf _:r7125 ;
rdfs:subClassOf _:r7126 ;
rdfs:subClassOf _:r7127 ;
vc:bridgesTo ngm:distributed-storage ;
vc:bridgesTo ngm:ontology ;
vc:dependsOn ngm:memory-allocation ;
vc:dependsOn ngm:type-system ;
vc:enables ngm:graph-neural-network ;
vc:enables ngm:knowledge-graph ;
vc:enables ngm:neural-network ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:tensor ;
vc:isPartOf ngm:computer-science ;
vc:qualityScore "0.68"^^xsd:float ;
vc:relatedTo ngm:algorithmic-complexity ;
vc:relatedTo ngm:graph-theory ;
vc:requires ngm:algorithm ;
vc:requires ngm:memory-management ;
vc:slug "data-structure" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:computational-complexity-theory ;
vc:supports ngm:machine-learning-discipline ;
vc:supports ngm:sparse-matrix ;
vc:uses ngm:cache-coherence ;
vc:uses ngm:gpu-compute .
ngm:data-subject-rights a owl:Class ;
rdfs:comment "Data subject rights are the legal entitlements granted to individuals over personal data that organisations hold about them, including rights of access, rectification, erasure, restriction, portability and objection. Codified in regimes such as the GDPR, these rights give people control over how their data is collected, used and shared, and impose corresponding obligations on data controllers and processors. Exercising and honouring them is a core requirement of modern data protection and privacy compliance."@en ;
rdfs:label "Data Subject Rights"@en ;
rdfs:subClassOf ngm:data-protection ;
rdfs:subClassOf _:r7128 ;
rdfs:subClassOf _:r7129 ;
vc:bridgesTo ngm:governance ;
vc:enables ngm:privacy ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:data-portability ;
vc:implements ngm:privacy-by-design ;
vc:isPartOf ngm:data-protection ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-governance ;
vc:relatedTo ngm:data-minimisation ;
vc:relatedTo ngm:regulatory-compliance ;
vc:requires ngm:identity-verification ;
vc:slug "data-subject-rights" ;
vc:sourceDomain "governance" ;
vc:standardizedBy ngm:gdpr ;
vc:supports ngm:accountability ;
vc:supports ngm:data-privacy .
ngm:data-synchronization a owl:Class ;
rdfs:comment "Data synchronization is the process of keeping data consistent across multiple devices, replicas or systems by propagating changes and reconciling conflicts. It may be one-way or bidirectional, real-time or batch, and relies on change tracking, versioning and conflict-resolution strategies. It is essential wherever distributed copies of data must converge, from device sync to collective-intelligence systems aggregating many participants."@en ;
rdfs:label "Data Synchronization"@en ;
rdfs:subClassOf ngm:distributed-systems ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:collective-intelligence-system ;
vc:relatedTo ngm:etsi-domain-data-management ;
vc:slug "data-synchronization" ;
vc:sourceDomain "infrastructure" .
ngm:data-table a skos:Concept ;
rdfs:label "Data Table"@en .
ngm:data-transfer a skos:Concept ;
rdfs:label "Data Transfer"@en .
ngm:data-transfer-mechanism a skos:Concept ;
rdfs:label "Data Transfer Mechanism"@en .
ngm:data-transformation a owl:Class ;
rdfs:comment "Data transformation is the process of converting data from one structure, format or representation into another to make it suitable for storage, integration or analysis. It includes cleansing, type conversion, normalisation, aggregation, enrichment, schema mapping and serialisation, and is typically expressed as declarative or programmatic steps within a pipeline. Transformation reconciles heterogeneous sources, enforces quality and conformance rules, and shapes raw inputs into the canonical forms required by downstream systems."@en ;
rdfs:label "Data Transformation"@en ;
rdfs:subClassOf ngm:data-processing ;
rdfs:subClassOf _:r7130 ;
rdfs:subClassOf _:r7131 ;
rdfs:subClassOf _:r7132 ;
vc:bridgesTo ngm:data-integration ;
vc:dependsOn ngm:data-engineering ;
vc:enables ngm:data-analytics ;
vc:enables ngm:data-integration ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:data-cleaning ;
vc:hasPart ngm:data-serialization ;
vc:implements ngm:etl-pipeline ;
vc:isPartOf ngm:data-pipeline ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-lake ;
vc:relatedTo ngm:data-processing ;
vc:requires ngm:data-quality ;
vc:slug "data-transformation" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:data-warehouse ;
vc:supports ngm:feature-engineering ;
vc:uses ngm:data-validation ;
vc:uses ngm:schema .
ngm:data-transmission a skos:Concept ;
rdfs:label "Data Transmission"@en .
ngm:data-transmission-service a skos:Concept ;
rdfs:label "Data Transmission Service"@en .
ngm:data-type a owl:Class ;
rdfs:comment "A data type is a classification that specifies which values a piece of data may hold and which operations may be performed on it, such as integer, string, boolean, or array. Type declarations allow compilers, interpreters, and schema validators to catch category errors before or during execution, and inform how data is stored and serialised. Data types are the atomic building blocks from which composite structures such as records and schemas are constructed."@en ;
rdfs:label "Data Type"@en ;
rdfs:subClassOf ngm:type-system ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:type-system ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "data-type" ;
vc:sourceDomain "data" .
ngm:data-use-and-access-act-2025 a skos:Concept ;
rdfs:label "Data Use And Access Act 2025"@en .
ngm:data-validation a owl:Class ;
rdfs:comment "Data validation is the process of checking that data conforms to defined rules, formats, ranges and constraints before it is processed, stored or transmitted. It detects errors, inconsistencies and anomalies at ingestion and transformation boundaries, ensuring that only well-formed and trustworthy data enters downstream systems. Validation is enforced through schema checks, type and range assertions, referential integrity rules and business-logic constraints."@en ;
rdfs:label "Data Validation"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf ngm:infrastructure ;
rdfs:subClassOf _:r7133 ;
rdfs:subClassOf _:r7134 ;
skos:broader ngm:infrastructure ;
vc:dependsOn ngm:data-schema ;
vc:enables ngm:data-integrity ;
vc:enables ngm:data-quality ;
vc:enables ngm:reliability ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:schema-validation ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-cleaning ;
vc:relatedTo ngm:data-quality ;
vc:relatedTo ngm:data-transformation ;
vc:requires ngm:error-handling ;
vc:slug "data-validation" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:compliance ;
vc:supports ngm:data-governance ;
vc:supports ngm:data-management ;
vc:supports ngm:data-pipeline ;
vc:uses ngm:data-schema ;
vc:uses ngm:verification .
ngm:data-vending-machine a skos:Concept ;
rdfs:label "Data Vending Machine"@en .
ngm:data-versioning a owl:Class ;
rdfs:comment "Data Versioning is the systematic practice of tracking, storing, and managing changes to datasets, model artefacts, and derived data products over time, providing reproducibility of experiments, auditability of data lineage, and governance of the full ML data supply chain. It applies software version-control semantics — branching, tagging, diffing, commit history, and rollback — to the large binary assets that underpin machine learning: raw datasets, processed feature stores, trained model weights, and pipeline configuration. Tools such as DVC (Data Version Control), lakeFS, and Apache Iceberg implement data versioning at different granularities, from file-level pointers through table-level snapshots to full environment branching over petabyte-scale data lakes. Data Versioning is a required foundation for reproducible science, regulatory compliance under frameworks such as the EU AI Act, and the operationalisation of mature MLOps practice."@en ;
rdfs:label "Data Versioning"@en ;
rdfs:subClassOf ngm:ai-infrastructure ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf ngm:machine-learning-discipline-pipeline ;
rdfs:subClassOf _:r7135 ;
rdfs:subClassOf _:r7136 ;
rdfs:subClassOf _:r7137 ;
rdfs:subClassOf _:r7138 ;
rdfs:subClassOf _:r7139 ;
rdfs:subClassOf _:r7140 ;
rdfs:subClassOf _:r7141 ;
skos:broader ngm:artificial-intelligence ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:mlops ;
vc:contrastsWith ngm:static-dataset ;
vc:dependsOn ngm:data-engineering ;
vc:dependsOn ngm:object-storage ;
vc:dependsOn ngm:version-control ;
vc:enables ngm:ai-governance ;
vc:enables ngm:continuous-training ;
vc:enables ngm:empirical-experimental-design ;
vc:enables ngm:empirical-experimental-design-tracking ;
vc:enables ngm:feature-engineering ;
vc:enables ngm:model-training ;
vc:enables ngm:reproducibility ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:artifact-metadata ;
vc:hasPart ngm:data-lineage ;
vc:hasPart ngm:data-snapshot ;
vc:hasPart ngm:dvc ;
vc:hasPart ngm:version-control-pointer ;
vc:implements ngm:data-pipeline ;
vc:implements ngm:machine-learning-discipline-pipeline ;
vc:implements ngm:workflow-automation ;
vc:isPartOf ngm:data-management ;
vc:isPartOf ngm:machine-learning-discipline-pipeline ;
vc:isPartOf ngm:mlops ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:blockchain ;
vc:relatedTo ngm:ci-cd ;
vc:relatedTo ngm:data-drift ;
vc:relatedTo ngm:data-quality ;
vc:relatedTo ngm:feature-store ;
vc:relatedTo ngm:machine-learning-discipline-infrastructure ;
vc:relatedTo ngm:model-registry ;
vc:relatedTo ngm:workflow-automation ;
vc:requires ngm:artifact-metadata ;
vc:requires ngm:data-governance ;
vc:requires ngm:object-storage ;
vc:requires ngm:version-control ;
vc:slug "data-versioning" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:supports ngm:ai-governance ;
vc:supports ngm:data-governance ;
vc:supports ngm:mlops ;
vc:supports ngm:reproducibility ;
vc:uses ngm:data-pipeline ;
vc:uses ngm:empirical-experimental-design-tracking ;
vc:uses ngm:feature-store ;
vc:uses ngm:object-storage ;
vc:uses ngm:version-control ;
vc:uses ngm:workflow-automation .
ngm:data-virtualization a owl:Class ;
rdfs:comment "A data integration approach that creates a virtual abstraction layer enabling users and applications to access, query, and integrate data from multiple disparate sources as a single unified system without physically moving or replicating the underlying data, supporting real-time access and reduci..."@en ;
rdfs:label "Data Virtualization"@en ;
rdfs:subClassOf ngm:data-integration ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r7142 ;
rdfs:subClassOf _:r7143 ;
vc:bridgesTo ngm:blockchain ;
vc:enables ngm:data-federation ;
vc:enables ngm:real-time-data-access ;
vc:enables ngm:unified-data-view ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:data-connectors ;
vc:requires ngm:metadata-management ;
vc:requires ngm:query-engine ;
vc:slug "data-virtualization" ;
vc:sourceDomain "infrastructure" .
ngm:data-visualisation a owl:Class ;
rdfs:comment "Data Visualisation is the systematic practice of encoding data attributes into perceptual channels — position, colour, size, shape, and motion — to enable rapid human comprehension of patterns, trends, anomalies, and relational structures within datasets. It encompasses both static and interactive representations, spanning two-dimensional charts, network graphs, geospatial maps, and immersive three-dimensional scenes rendered in augmented or virtual reality environments. Effective data visualisation integrates principles from information design, cognitive psychology, and computer graphics, requiring rendering infrastructure, data pipelines, and interaction paradigms suited to the display medium. In the context of real-time analytics and spatial computing, visualisation systems must handle streaming data, high-dimensionality reduction, and multi-user collaborative viewing at interactive frame rates."@en ;
rdfs:label "Data Visualisation"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r7144 ;
rdfs:subClassOf _:r7145 ;
rdfs:subClassOf _:r7146 ;
rdfs:subClassOf _:r7147 ;
rdfs:subClassOf _:r7148 ;
vc:bridgesTo ngm:explainable-ai ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:bridgesTo ngm:spatial-computing ;
vc:contrastsWith ngm:data-table ;
vc:contrastsWith ngm:text-report ;
vc:dependsOn ngm:data-model ;
vc:dependsOn ngm:graphics-processing-unit ;
vc:enables ngm:decision-support ;
vc:enables ngm:digital-twin ;
vc:enables ngm:exploratory-data-analysis ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:chart ;
vc:hasPart ngm:geospatial-map ;
vc:hasPart ngm:monitoring-dashboard ;
vc:hasPart ngm:network-graph ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:information-design ;
vc:relatedTo ngm:scientific-visualisation ;
vc:relatedTo ngm:visual-analytics ;
vc:requires ngm:data-access-interface ;
vc:requires ngm:data-pipeline ;
vc:requires ngm:rendering-engine ;
vc:slug "data-visualisation" ;
vc:sourceDomain "data" ;
vc:supports ngm:augmented-reality ;
vc:supports ngm:business-intelligence ;
vc:supports ngm:telecollaboration ;
vc:uses ngm:colour-theory ;
vc:uses ngm:computer-vision ;
vc:uses ngm:dimensionality-reduction ;
vc:uses ngm:human-computer-interaction .
ngm:data-warehouse a owl:Class ;
rdfs:comment "A data warehouse is a centralised analytical repository that integrates cleansed, structured data from multiple operational sources into a subject-oriented, historical model optimised for querying and reporting. It supports business intelligence through schemas such as star and snowflake and columnar storage for fast aggregation. It is a core data-engineering asset enabling consistent enterprise analytics."@en ;
rdfs:label "Data Warehouse"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r7149 ;
rdfs:subClassOf _:r7150 ;
rdfs:subClassOf _:r7151 ;
rdfs:subClassOf _:r7152 ;
rdfs:subClassOf _:r7153 ;
vc:bridgesTo ngm:data-mesh ;
vc:bridgesTo ngm:machine-learning-discipline-platform ;
vc:contrastsWith ngm:data-lake ;
vc:dependsOn ngm:metadata-management ;
vc:dependsOn ngm:object-storage ;
vc:enables ngm:business-intelligence ;
vc:enables ngm:monitoring-dashboard ;
vc:enables ngm:olap ;
vc:enables ngm:self-service-analytics ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:columnar-storage ;
vc:hasPart ngm:data-mart ;
vc:hasPart ngm:etl-pipeline ;
vc:implements ngm:snowflake-schema ;
vc:implements ngm:star-schema ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:data-engineering ;
vc:relatedTo ngm:lakehouse-architecture ;
vc:requires ngm:data-governance ;
vc:requires ngm:data-quality-management ;
vc:requires ngm:schema-management ;
vc:slug "data-warehouse" ;
vc:sourceDomain "data" ;
vc:uses ngm:data-catalog ;
vc:uses ngm:sql .
ngm:data-warehousing a owl:Class ;
rdfs:comment "Data warehousing is the practice of consolidating data from multiple operational and external sources into a central, integrated, subject-oriented repository optimised for query and analysis rather than transaction processing. A data warehouse stores historical, cleansed and conformed data structured for reporting and decision support, typically populated through extract-transform-load pipelines and queried using online analytical processing. It provides the persistent analytical substrate on which business intelligence, dashboards and downstream analytics are built."@en ;
rdfs:label "Data Warehousing"@en ;
rdfs:subClassOf ngm:data-engineering ;
rdfs:subClassOf _:r7154 ;
rdfs:subClassOf _:r7155 ;
rdfs:subClassOf _:r7156 ;
rdfs:subClassOf _:r7157 ;
rdfs:subClassOf _:r7158 ;
rdfs:subClassOf _:r7159 ;
vc:contrastsWith ngm:data-lake ;
vc:enables ngm:business-intelligence ;
vc:enables ngm:predictive-analytics ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:data-integration ;
vc:hasPart ngm:data-pipeline ;
vc:hasPart ngm:data-warehouse ;
vc:isPartOf ngm:data-engineering ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:data-management ;
vc:relatedTo ngm:metadata ;
vc:requires ngm:data-governance ;
vc:requires ngm:data-quality ;
vc:requires ngm:master-data-management ;
vc:slug "data-warehousing" ;
vc:sourceDomain "data" ;
vc:supports ngm:data-catalog ;
vc:uses ngm:relational-database ;
vc:uses ngm:sql .
ngm:data-withholding-attack a skos:Concept ;
rdfs:label "Data Withholding Attack"@en .
ngm:database a owl:Class ;
rdfs:comment "A database is an organised collection of structured data managed by a database management system that supports persistent storage, efficient retrieval, concurrent access and integrity guarantees. Databases expose query interfaces, enforce schemas or schemaless models, and provide transactional or eventual-consistency semantics depending on their design. They form the durable state layer beneath most data-intensive applications and services."@en ;
rdfs:label "Database"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf ngm:infrastructure ;
rdfs:subClassOf _:r7186 ;
rdfs:subClassOf _:r7187 ;
rdfs:subClassOf _:r7188 ;
rdfs:subClassOf _:r7189 ;
rdfs:subClassOf _:r7190 ;
skos:broader ngm:infrastructure ;
vc:contrastsWith ngm:caching ;
vc:dependsOn ngm:disaster-recovery ;
vc:dependsOn ngm:scalability ;
vc:enables ngm:data-engineering ;
vc:enables ngm:data-pipeline ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:caching ;
vc:hasPart ngm:persistence ;
vc:hasPart ngm:sql ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:cloud-computing ;
vc:relatedTo ngm:data-quality ;
vc:relatedTo ngm:observability ;
vc:requires ngm:data-integrity ;
vc:requires ngm:schema ;
vc:slug "database" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:high-availability ;
vc:supports ngm:microservices ;
vc:uses ngm:access-control .
ngm:database-completeness-assumption a skos:Concept ;
rdfs:label "Database Completeness Assumption"@en .
ngm:database-connectivity a skos:Concept ;
rdfs:label "Database Connectivity"@en .
ngm:database-engine a skos:Concept ;
rdfs:label "Database Engine"@en .
ngm:database-infrastructure a skos:Concept ;
rdfs:label "Database Infrastructure"@en .
ngm:database-interaction a skos:Concept ;
rdfs:label "Database Interaction"@en .
ngm:database-lookup a skos:Concept ;
rdfs:label "Database Lookup"@en .
ngm:database-management-system a owl:Class ;
rdfs:comment "A database management system (DBMS) is software that defines, stores, retrieves, secures and manages structured data while enforcing integrity, concurrency and durability. It mediates all access to the underlying database through a query interface and transaction manager, supporting models such as relational, document, key-value and graph. It is the foundational platform for persistent data services including ontology repositories and taxonomy registries."@en ;
rdfs:label "Database Management System"@en ;
rdfs:subClassOf ngm:data-management ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:digital-ontology-repository ;
vc:relatedTo ngm:digital-taxonomy-registry ;
vc:slug "database-management-system" ;
vc:sourceDomain "data" .
ngm:database-query a owl:Class ;
rdfs:comment "A structured request submitted to a database management system to retrieve, insert, update, or delete data according to defined criteria. Queries are expressed in formal query languages such as SQL for relational databases or SPARQL for RDF triple stores, and underpin knowledge graph retrieval, analytics pipelines, and real-time application data access."@en ;
rdfs:label "Database Query"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r7163 ;
rdfs:subClassOf _:r7164 ;
rdfs:subClassOf _:r7165 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:smart-contract ;
vc:contrastsWith ngm:batch-processing ;
vc:contrastsWith ngm:stream-processing ;
vc:dependsOn ngm:relational-database ;
vc:enables ngm:data-analytics ;
vc:enables ngm:knowledge-graph ;
vc:enables ngm:linked-data ;
vc:enables ngm:real-time-data-access ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:graph-ql ;
vc:implements ngm:sparql ;
vc:implements ngm:sql ;
vc:isPartOf ngm:data-management ;
vc:isPartOf ngm:database-management-system ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:rdf ;
vc:relatedTo ngm:semantic-web-linked-data-standard ;
vc:relatedTo ngm:transaction-processing ;
vc:requires ngm:database-schema ;
vc:requires ngm:query-optimiser ;
vc:requires ngm:query-parser ;
vc:slug "database-query" ;
vc:sourceDomain "data" ;
vc:standardizedBy ngm:iso-iec-9075 ;
vc:standardizedBy ngm:sparql ;
vc:supports ngm:full-text-search ;
vc:supports ngm:semantic-search ;
vc:uses ngm:query-processor ;
vc:uses ngm:rest-api ;
vc:uses ngm:sparql .
ngm:database-replication a skos:Concept ;
rdfs:label "Database Replication"@en .
ngm:database-row a skos:Concept ;
rdfs:label "Database Row"@en .
ngm:database-schema a owl:Class ;
rdfs:comment "A database schema is the formal, declarative description of the logical structure of a database, specifying its tables, columns, data types, primary and foreign keys, integrity constraints, views, indexes, and relationships. It constitutes the logical layer of a three-level ANSI/SPARC architecture that separates the conceptual organisation of data from physical storage details and from application-level views, and is enforced at runtime by the Database Management System. Schemas evolve through controlled migration scripts — governed by tools such as Flyway and Liquibase — and contrast with ontologies in being prescriptive, closed-world storage structures rather than open, inference-supporting conceptual models for reasoning."@en ;
rdfs:label "Database Schema"@en ;
rdfs:subClassOf ngm:data-model ;
rdfs:subClassOf ngm:relational-database ;
rdfs:subClassOf _:r7166 ;
rdfs:subClassOf _:r7167 ;
rdfs:subClassOf _:r7168 ;
vc:bridgesTo ngm:knowledge-representation ;
vc:bridgesTo ngm:object-relational-mapping ;
vc:bridgesTo ngm:owl-class-hierarchy ;
vc:contrastsWith ngm:knowledge-representation ;
vc:contrastsWith ngm:nosql-database ;
vc:contrastsWith ngm:ontology ;
vc:dependsOn ngm:database-management-system ;
vc:dependsOn ngm:relational-algebra ;
vc:dependsOn ngm:sql ;
vc:enables ngm:acid-transactions ;
vc:enables ngm:data-integration ;
vc:enables ngm:data-interoperability ;
vc:enables ngm:database-query ;
vc:enables ngm:schema-evolution ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:database-view ;
vc:hasPart ngm:foreign-key ;
vc:hasPart ngm:index ;
vc:hasPart ngm:normalisation ;
vc:hasPart ngm:primary-key ;
vc:hasPart ngm:referential-integrity ;
vc:hasPart ngm:view ;
vc:implements ngm:data-model ;
vc:implements ngm:referential-integrity ;
vc:implements ngm:relational-algebra ;
vc:isPartOf ngm:database ;
vc:isPartOf ngm:relational-database ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:data-management ;
vc:relatedTo ngm:data-migration ;
vc:relatedTo ngm:data-versioning ;
vc:relatedTo ngm:metadata ;
vc:relatedTo ngm:object-relational-mapping ;
vc:relatedTo ngm:owl-class-hierarchy ;
vc:relatedTo ngm:postgre-sql ;
vc:requires ngm:data-model ;
vc:requires ngm:database-management-system ;
vc:requires ngm:sql ;
vc:slug "database-schema" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:iso-iec-9075 ;
vc:supports ngm:data-governance ;
vc:supports ngm:data-integration ;
vc:supports ngm:data-quality ;
vc:supports ngm:data-warehouse ;
vc:supports ngm:metadata ;
vc:uses ngm:data-model ;
vc:uses ngm:normalisation ;
vc:uses ngm:relational-algebra ;
vc:uses ngm:sql .
ngm:database-system a owl:Class ;
rdfs:comment "A database system (DBMS - Database Management System) is software that enables users to define, create, maintain, and control access to structured collections of data. It encompasses relational databases using SQL for structured table-based data and NoSQL databases supporting flexible schemas for document, key-value, graph, and wide-column data models, providing mechanisms for concurrent access, data integrity, and persistent storage."@en ;
rdfs:label "Database System"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r7169 ;
rdfs:subClassOf _:r7170 ;
rdfs:subClassOf _:r7171 ;
rdfs:subClassOf _:r7172 ;
rdfs:subClassOf _:r7173 ;
rdfs:subClassOf _:r7174 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:distributed-ledger ;
vc:bridgesTo ngm:machine-learning-discipline-pipeline ;
vc:contrastsWith ngm:file-system ;
vc:contrastsWith ngm:in-memory-data-store ;
vc:enables ngm:access-control ;
vc:enables ngm:data-analytics ;
vc:enables ngm:data-persistence ;
vc:enables ngm:query-processing ;
vc:enables ngm:transaction-manager ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:index-structure ;
vc:hasPart ngm:query-engine ;
vc:hasPart ngm:storage-engine ;
vc:hasPart ngm:transaction-manager ;
vc:implements ngm:acid-properties ;
vc:implements ngm:cap-theorem ;
vc:implements ngm:relational-model ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:cloud-database ;
vc:relatedTo ngm:data-lake ;
vc:relatedTo ngm:data-warehouse ;
vc:relatedTo ngm:distributed-databases ;
vc:requires ngm:file-system ;
vc:requires ngm:network-infrastructure ;
vc:requires ngm:operating-system ;
vc:slug "database-system" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:ansi-sql ;
vc:standardizedBy ngm:iso-iec-9075 ;
vc:supports ngm:backup-and-recovery ;
vc:supports ngm:data-replication ;
vc:supports ngm:role-based-access-control ;
vc:uses ngm:b-tree-index ;
vc:uses ngm:structured-query-language ;
vc:uses ngm:write-ahead-logging .
ngm:database-systems a owl:Class ;
rdfs:comment "Database systems are organised software stacks — comprising a storage engine, query processor, transaction manager, and access-control layer — that persistently store, retrieve, and manipulate structured or semi-structured data. They enforce ACID or BASE consistency guarantees, coordinate concurrent access via locking or multi-version concurrency control (MVCC), and expose declarative query languages such as SQL or graph-query dialects. Modern database systems span relational, document, key-value, columnar, time-series, and graph data models, each optimised for distinct access patterns and workload characteristics."@en ;
rdfs:label "Database Systems"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r7175 ;
rdfs:subClassOf _:r7176 ;
rdfs:subClassOf _:r7177 ;
rdfs:subClassOf _:r7178 ;
rdfs:subClassOf _:r7179 ;
rdfs:subClassOf _:r7180 ;
rdfs:subClassOf _:r7181 ;
rdfs:subClassOf _:r7182 ;
rdfs:subClassOf _:r7183 ;
rdfs:subClassOf _:r7184 ;
rdfs:subClassOf _:r7185 ;
vc:bridgesTo ngm:knowledge-graphs ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:contrastsWith ngm:file-system ;
vc:contrastsWith ngm:memory-store ;
vc:dependsOn ngm:distributed-systems ;
vc:dependsOn ngm:operating-system ;
vc:enables ngm:data-analytics ;
vc:enables ngm:data-warehousing ;
vc:enables ngm:microservices ;
vc:enables ngm:real-time-processing ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:columnar-storage ;
vc:hasPart ngm:graph-databases ;
vc:hasPart ngm:nosql-database ;
vc:hasPart ngm:relational-database ;
vc:hasPart ngm:time-series-database ;
vc:implements ngm:acid-transactions ;
vc:implements ngm:structured-query-language ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:data-lake ;
vc:relatedTo ngm:data-modelling ;
vc:relatedTo ngm:event-streaming ;
vc:requires ngm:concurrency-control ;
vc:requires ngm:query-processing ;
vc:requires ngm:storage-systems ;
vc:slug "database-systems" ;
vc:sourceDomain "data" ;
vc:standardizedBy ngm:iso-iec-9075 ;
vc:supports ngm:access-control ;
vc:supports ngm:data-governance ;
vc:uses ngm:caching ;
vc:uses ngm:indexing ;
vc:uses ngm:replication .
ngm:database-technology a skos:Concept ;
rdfs:label "Database Technology"@en .
ngm:database-theory a skos:Concept ;
rdfs:label "Database Theory"@en .
ngm:database-verification a skos:Concept ;
rdfs:label "Database Verification"@en .
ngm:database-view a skos:Concept ;
rdfs:label "Database View"@en .
ngm:datablock-api a skos:Concept ;
rdfs:label "Datablock API"@en .
ngm:databricks a skos:Concept ;
rdfs:label "Databricks"@en .
ngm:datacentermetrics a skos:Concept ;
rdfs:label "Datacentermetrics"@en .
ngm:datacentre-network a skos:Concept ;
rdfs:label "Datacentre Network"@en .
ngm:datacomp-lm a skos:Concept ;
rdfs:label "Datacomp Lm"@en .
ngm:datadog a skos:Concept ;
rdfs:label "Datadog"@en .
ngm:datafication a skos:Concept ;
rdfs:label "Datafication"@en .
ngm:dataflow-model a skos:Concept ;
rdfs:label "Dataflow Model"@en .
ngm:dataflow-programming a skos:Concept ;
rdfs:label "Dataflow Programming"@en .
ngm:datahub a skos:Concept ;
rdfs:label "Datahub"@en .
ngm:datahub-metadata-model a skos:Concept ;
rdfs:label "Datahub Metadata Model"@en .
ngm:datalog a skos:Concept ;
rdfs:label "Datalog"@en .
ngm:datalog-knowledge-graph-query-language a owl:Class ;
rdfs:comment "Queries, in the Logseq context, are structured Datalog or advanced query expressions embedded in pages using the `#+BEGIN_QUERY` / `#+END_QUERY` syntax. They dynamically retrieve and display blocks or pages matching specified conditions—such as filtering private pages by the absence of a `#Public` tag—without modifying underlying data. In the broader NarrativeGoldmine ontology, Queries represent the retrieval-layer mechanism that surfaces knowledge from the graph at read time."@en ;
rdfs:label "Datalog Knowledge Graph Query Language"@en ;
rdfs:subClassOf ngm:data-management ;
vc:enables ngm:information-retrieval ;
vc:enables ngm:semantic-search ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:database-query ;
vc:relatedTo ngm:linked-data ;
vc:relatedTo ngm:semantic-web-linked-data-standard ;
vc:slug "datalog-knowledge-graph-query-language" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:data-management ;
vc:uses ngm:knowledge-graph .
ngm:dataops a skos:Concept ;
rdfs:label "Dataops"@en .
ngm:dataparallelism a skos:Concept ;
rdfs:label "Dataparallelism"@en .
ngm:datapersistence a skos:Concept ;
rdfs:label "Datapersistence"@en .
ngm:dataset a owl:Class ;
rdfs:comment "A Dataset is a structured collection of data records sharing a common schema, gathered for a specific purpose such as training machine learning models, conducting research, or supporting analytics. Datasets are characterised by their size, modality (text, image, tabular, audio, video, graph, etc.), provenance, and licensing terms, all of which affect their fitness for use. Data quality, curation methodology, and bias documentation are critical attributes that determine the reliability of downstream AI systems. The movement from model-centric to data-centric AI has elevated dataset engineering to a first-class research and engineering discipline, with dataset documentation frameworks such as Datasheets for Datasets, Dataset Nutrition Labels, and the Croissant machine-readable format formalising the metadata contract between dataset creators and downstream consumers."@en ;
rdfs:label "Dataset"@en ;
rdfs:subClassOf ngm:ai-infrastructure ;
rdfs:subClassOf ngm:computational-modelling ;
rdfs:subClassOf ngm:data-architecture ;
rdfs:subClassOf _:r7192 ;
rdfs:subClassOf _:r7193 ;
rdfs:subClassOf _:r7194 ;
rdfs:subClassOf _:r7195 ;
rdfs:subClassOf _:r7196 ;
rdfs:subClassOf _:r7197 ;
rdfs:subClassOf _:r7198 ;
rdfs:subClassOf _:r7199 ;
rdfs:subClassOf _:r7200 ;
rdfs:subClassOf _:r7201 ;
rdfs:subClassOf _:r7202 ;
rdfs:subClassOf _:r7203 ;
rdfs:subClassOf _:r7204 ;
vc:contrastsWith ngm:benchmark-dataset ;
vc:contrastsWith ngm:data-lake ;
vc:contrastsWith ngm:data-management-system ;
vc:contrastsWith ngm:knowledge-graph ;
vc:dependsOn ngm:data-catalogue ;
vc:dependsOn ngm:data-curation ;
vc:dependsOn ngm:data-management ;
vc:dependsOn ngm:data-management-system ;
vc:dependsOn ngm:data-pipeline ;
vc:dependsOn ngm:data-quality ;
vc:enables ngm:active-learning ;
vc:enables ngm:benchmarking ;
vc:enables ngm:data-analysis ;
vc:enables ngm:deep-learning ;
vc:enables ngm:machine-learning-discipline ;
vc:enables ngm:model-evaluation ;
vc:enables ngm:reinforcement-learning ;
vc:enables ngm:supervised-learning ;
vc:enables ngm:transfer-learning ;
vc:enables ngm:unsupervised-learning ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:data-record ;
vc:hasPart ngm:data-schema ;
vc:hasPart ngm:data-split ;
vc:hasPart ngm:data-versioning ;
vc:hasPart ngm:evaluation-metric ;
vc:hasPart ngm:ground-truth-labels ;
vc:hasPart ngm:metadata ;
vc:hasPart ngm:schema ;
vc:implements ngm:data-ethics ;
vc:implements ngm:data-governance-framework ;
vc:implements ngm:open-data ;
vc:implements ngm:reproducibility ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:bias ;
vc:relatedTo ngm:computational-modelling ;
vc:relatedTo ngm:data-centric-ai ;
vc:relatedTo ngm:data-ethics ;
vc:relatedTo ngm:data-quality ;
vc:relatedTo ngm:eu-ai-act-regulatory-instrument ;
vc:relatedTo ngm:fairness ;
vc:relatedTo ngm:imbalanced-data ;
vc:relatedTo ngm:overfitting ;
vc:relatedTo ngm:privacy ;
vc:relatedTo ngm:regulation ;
vc:requires ngm:data-annotation ;
vc:requires ngm:data-cleaning ;
vc:requires ngm:data-collection ;
vc:requires ngm:data-governance ;
vc:requires ngm:data-labelling ;
vc:requires ngm:data-lineage ;
vc:requires ngm:data-provenance ;
vc:slug "dataset" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:data-governance ;
vc:standardizedBy ngm:data-governance-framework ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:supports ngm:computer-vision ;
vc:supports ngm:explainable-ai ;
vc:supports ngm:feature-engineering ;
vc:supports ngm:foundation-model ;
vc:supports ngm:large-language-models ;
vc:supports ngm:natural-language-processing ;
vc:uses ngm:active-learning ;
vc:uses ngm:cross-validation ;
vc:uses ngm:data-augmentation ;
vc:uses ngm:data-augmentation-strategies ;
vc:uses ngm:differential-privacy ;
vc:uses ngm:federated-learning ;
vc:uses ngm:synthetic-data .
ngm:dataset-bias a skos:Concept ;
rdfs:label "Dataset Bias"@en .
ngm:dataset-captioner a skos:Concept ;
rdfs:label "Dataset Captioner"@en .
ngm:dataset-curation a owl:Class ;
rdfs:comment "Dataset curation is the deliberate selection, cleaning, documentation, and maintenance of data collections used to train and evaluate machine learning models. It encompasses sourcing and licensing, de-duplication, filtering of low-quality or harmful content, labelling and label auditing, balancing for coverage and representation, and versioning with provenance records. Curation quality is a first-order determinant of model behaviour: the same architecture trained on better-curated data is routinely more capable, safer, and easier to evaluate."@en ;
rdfs:label "Dataset Curation"@en ;
rdfs:subClassOf ngm:data-curation ;
rdfs:subClassOf _:r7191 ;
vc:enables ngm:supervised-learning ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:data-management ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:data-labelling ;
vc:relatedTo ngm:dataset ;
vc:relatedTo ngm:training-data ;
vc:requires ngm:data-quality ;
vc:slug "dataset-curation" ;
vc:sourceDomain "data" .
ngm:datasets a skos:Concept ;
rdfs:label "Datasets"@en .
ngm:datasheets-for-datasets a owl:Class ;
rdfs:comment "A documentation framework proposed by Gebru et al. in which every machine learning dataset is accompanied by a structured datasheet recording its motivation, composition, collection process, preprocessing, recommended uses, distribution, and maintenance. Modelled on the datasheets that accompany electronic components, the practice surfaces provenance, consent, and bias considerations at the data layer, enabling informed dataset selection, reproducibility, and accountability across the machine learning lifecycle."@en ;
rdfs:label "Datasheets for Datasets"@en ;
rdfs:subClassOf ngm:ai-documentation-standards ;
vc:contrastsWith ngm:model-cards ;
vc:enables ngm:transparency ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:ai-documentation-standards ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:data-governance ;
vc:relatedTo ngm:dataset ;
vc:slug "datasheets-for-datasets" ;
vc:sourceDomain "governance" .
ngm:datasheets-gebru-et-al a skos:Concept ;
rdfs:label "Datasheets Gebru Et Al"@en .
ngm:datum-transformation a owl:Class ;
rdfs:label "Datum Transformation"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:geodesy ;
vc:slug "datum-transformation" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:daubert-standard a skos:Concept ;
rdfs:label "Daubert Standard"@en .
ngm:david-chaum a owl:Class ;
rdfs:comment "American computer scientist and cryptographer who pioneered digital cash, blind signatures and anonymous communication, and is widely regarded as a founder of the cypherpunk and privacy technology fields."@en ;
rdfs:label "David Chaum"@en ;
rdfs:subClassOf ngm:cryptography ;
rdfs:subClassOf _:r7205 ;
vc:bridgesTo ngm:consensus ;
vc:enables ngm:cryptocurrency ;
vc:enables ngm:privacy ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:public-key-cryptography ;
vc:slug "david-chaum" ;
vc:sourceDomain "security" .
ngm:davies-meyer-construction a skos:Concept ;
rdfs:label "Davies Meyer Construction"@en .
ngm:dbpedia a owl:Class ;
rdfs:comment "DBpedia is a community project that extracts structured information from Wikipedia and publishes it as an interlinked, openly licensed knowledge graph in RDF. It exposes millions of entities through a SPARQL endpoint and dereferenceable URIs, forming a central hub of the Linked Open Data cloud. It is widely used as background knowledge for knowledge-graph construction, entity linking and semantic search."@en ;
rdfs:label "DBpedia"@en ;
rdfs:subClassOf ngm:data-management ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:knowledge-graphing ;
vc:slug "dbpedia" ;
vc:sourceDomain "data" .
ngm:dbpedia-entity a skos:Concept ;
rdfs:label "Dbpedia Entity"@en .
ngm:dbscan a skos:Concept ;
rdfs:label "Dbscan"@en .
ngm:dbt a skos:Concept ;
rdfs:label "Dbt"@en .
ngm:dbt-data-build-tool a skos:Concept ;
rdfs:label "Dbt Data Build Tool"@en .
ngm:dc-communication a owl:Class ;
a skos:Concept ;
rdfs:comment "Taxonomy category covering the network protocols, media channels, and software systems that enable distributed teams to communicate across space and time, spanning real-time video conferencing, asynchronous messaging, WebRTC transport, MQTT messaging, and immersive communication modalities."@en ;
rdfs:label "Communication Technology"@en ;
rdfs:subClassOf ngm:distributed-collaboration ;
rdfs:subClassOf _:r22785 ;
rdfs:subClassOf _:r22786 ;
rdfs:subClassOf _:r22787 ;
rdfs:subClassOf _:r22788 ;
rdfs:subClassOf _:r22789 ;
rdfs:subClassOf _:r22790 ;
rdfs:subClassOf _:r22791 ;
rdfs:subClassOf _:r22792 ;
skos:broader ngm:distributed-collaboration ;
vc:enables ngm:remote-collaboration ;
vc:enables ngm:virtual-collaboration ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:asynchronous-communication ;
vc:hasPart ngm:communication-protocol ;
vc:hasPart ngm:immersive-communication ;
vc:hasPart ngm:mqtt ;
vc:hasPart ngm:network-protocol ;
vc:hasPart ngm:realtime-communication ;
vc:hasPart ngm:video-conferencing ;
vc:hasPart ngm:web-rtc ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:collaboration-technology ;
vc:relatedTo ngm:social-presence ;
vc:relatedTo ngm:telecollaboration ;
vc:slug "dc-communication" ;
vc:sourceDomain "distributed-collaboration" ;
vc:uses ngm:bandwidth-adaptation ;
vc:uses ngm:edge-computing .
ngm:dc-dc-converter a skos:Concept ;
rdfs:label "Dc Dc Converter"@en .
ngm:dc-motor a skos:Concept ;
rdfs:label "Dc Motor"@en .
ngm:dc-protocol-and-infra a owl:Class ;
a skos:Concept ;
rdfs:comment "Taxonomy hub for the communication protocols, data-interchange formats, and underlying infrastructure that enable distributed collaboration. Encompasses decentralised messaging protocols, identity systems, content-addressed storage, version control, and the networking substrate on which remote collaborative workflows operate."@en ;
rdfs:label "Protocol and Infrastructure"@en ;
rdfs:subClassOf ngm:distributed-collaboration ;
rdfs:subClassOf _:r22793 ;
rdfs:subClassOf _:r22794 ;
rdfs:subClassOf _:r22795 ;
rdfs:subClassOf _:r22796 ;
rdfs:subClassOf _:r22797 ;
skos:broader ngm:distributed-collaboration ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:communication-protocol ;
vc:hasPart ngm:crdt ;
vc:hasPart ngm:ipfs ;
vc:hasPart ngm:nostr-protocol ;
vc:hasPart ngm:version-control ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:asynchronous-collaboration ;
vc:relatedTo ngm:collaboration-platform ;
vc:relatedTo ngm:dc-workspace-tools ;
vc:relatedTo ngm:decentralized-storage ;
vc:slug "dc-protocol-and-infra" ;
vc:sourceDomain "distributed-collaboration" ;
vc:uses ngm:decentralized-identifiers .
ngm:dc-servo-motor a owl:Class ;
rdfs:comment "DC servo motor combines a direct-current electric motor with integrated or external feedback control electronics to enable precise position, velocity, or torque regulation."@en ;
rdfs:label "DC Servo Motor"@en ;
rdfs:subClassOf ngm:electric-motor ;
rdfs:subClassOf ngm:robo-actuation-and-control ;
rdfs:subClassOf ngm:servo-motor ;
rdfs:subClassOf _:r6655 ;
rdfs:subClassOf _:r6656 ;
rdfs:subClassOf _:r6657 ;
rdfs:subClassOf _:r6658 ;
skos:broader ngm:robo-actuation-and-control ;
vc:bridgesTo ngm:ai-agent-system ;
vc:dependsOn ngm:bearings ;
vc:dependsOn ngm:cooling-system ;
vc:dependsOn ngm:motor-shaft ;
vc:enables ngm:dynamic-control ;
vc:enables ngm:load-adaptation ;
vc:enables ngm:precise-positioning ;
vc:enables ngm:trajectory-tracking ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:control-electronics ;
vc:hasPart ngm:current-driver ;
vc:hasPart ngm:dc-motor ;
vc:hasPart ngm:position-encoder ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:feedback-sensor ;
vc:requires ngm:mechanical-load ;
vc:requires ngm:power-supply ;
vc:requires ngm:servo-amplifier ;
vc:slug "dc-servo-motor" ;
vc:sourceDomain "robotics" .
ngm:dc-telepresence a owl:Class ;
a skos:Concept ;
rdfs:comment "Telepresence is the distributed-collaboration taxonomy hub covering technologies that create a convincing sense of physical co-presence across remote locations — spanning robotic telepresence, haptic-feedback telepresence, virtual-reality telepresence, and social presence theory. It is a peer category to Workspace Tools and Communication Technology within the distributed collaboration domain."@en ;
rdfs:label "Telepresence (Distributed Collaboration)"@en ;
rdfs:subClassOf ngm:distributed-collaboration ;
rdfs:subClassOf _:r22798 ;
rdfs:subClassOf _:r22799 ;
rdfs:subClassOf _:r22800 ;
rdfs:subClassOf _:r22801 ;
rdfs:subClassOf _:r22802 ;
rdfs:subClassOf _:r22803 ;
rdfs:subClassOf _:r22804 ;
skos:broader ngm:distributed-collaboration ;
vc:bridgesTo ngm:metaverse-telepresence-bridge ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:haptic-feedback-telepresence ;
vc:hasPart ngm:immersive-communication ;
vc:hasPart ngm:presence ;
vc:hasPart ngm:robotic-telepresence ;
vc:hasPart ngm:social-presence ;
vc:hasPart ngm:spatial-presence ;
vc:hasPart ngm:teleoperation-systems ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:dc-communication ;
vc:relatedTo ngm:dc-workspace-tools ;
vc:relatedTo ngm:robotics-telepresence-bridge ;
vc:slug "dc-telepresence" ;
vc:sourceDomain "distributed-collaboration" ;
vc:uses ngm:avatar-system ;
vc:uses ngm:haptics .
ngm:dc-workspace-tools a owl:Class ;
a skos:Concept ;
rdfs:comment "Workspace Tools is the distributed-collaboration taxonomy hub for software and platform technologies that support remote and hybrid team productivity — including collaboration platforms, shared whiteboards, asynchronous video, meeting AI assistants, and immersive workspaces. It is a peer category to Telepresence and Communication Technology within the distributed collaboration domain."@en ;
rdfs:label "Workspace Tools"@en ;
rdfs:subClassOf ngm:distributed-collaboration ;
rdfs:subClassOf _:r22805 ;
rdfs:subClassOf _:r22806 ;
rdfs:subClassOf _:r22807 ;
rdfs:subClassOf _:r22808 ;
rdfs:subClassOf _:r22809 ;
rdfs:subClassOf _:r22810 ;
rdfs:subClassOf _:r22811 ;
skos:broader ngm:distributed-collaboration ;
vc:enables ngm:distributed-collaboration ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:asynchronous-collaboration ;
vc:hasPart ngm:collaboration-platform ;
vc:hasPart ngm:collaborative-systems-modality-whiteboard ;
vc:hasPart ngm:immersive-workspaces ;
vc:hasPart ngm:meeting-ai-assistant ;
vc:hasPart ngm:synchronous-collaboration ;
vc:hasPart ngm:virtual-office-spaces ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:dc-communication ;
vc:relatedTo ngm:remote-collaboration ;
vc:relatedTo ngm:telepresence ;
vc:slug "dc-workspace-tools" ;
vc:sourceDomain "distributed-collaboration" .
ngm:dcat a skos:Concept ;
rdfs:label "Dcat"@en .
ngm:dclimate-network a skos:Concept ;
rdfs:label "Dclimate Network"@en .
ngm:ddim a skos:Concept ;
rdfs:label "Ddim"@en .
ngm:ddim-sampling a skos:Concept ;
rdfs:label "Ddim Sampling"@en .
ngm:ddos-mitigation a owl:Class ;
rdfs:comment "DDoS mitigation is the set of techniques and infrastructure used to detect and absorb distributed denial-of-service traffic so that a targeted service remains available to legitimate users. Approaches include traffic scrubbing, rate limiting, anycast-based load distribution, and edge filtering at content delivery networks positioned close to end users. Effective mitigation depends on capacity headroom large enough to absorb attack volumes while distinguishing malicious traffic from genuine demand spikes."@en ;
rdfs:label "DDoS Mitigation"@en ;
rdfs:subClassOf ngm:network-security ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:network-security ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "ddos-mitigation" ;
vc:sourceDomain "security" .
ngm:ddos-protection a skos:Concept ;
rdfs:label "Ddos Protection"@en .
ngm:dds a owl:Class ;
rdfs:comment "DDS, the Data Distribution Service, is an Object Management Group standard for a publish-subscribe middleware that distributes real-time data between distributed system components."@en ;
rdfs:label "DDS"@en ;
rdfs:subClassOf ngm:middleware ;
rdfs:subClassOf _:r6662 ;
vc:bridgesTo ngm:distributed-systems ;
vc:enables ngm:ros ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:network-protocol ;
vc:slug "dds" ;
vc:sourceDomain "infrastructure" .
ngm:dds-middleware a owl:Class ;
rdfs:comment "Data Distribution Service (DDS) Middleware is an OMG-standardised publish-subscribe communication middleware designed for real-time, scalable, and decentralised data exchange in safety-critical and high-performance distributed systems. It defines a Data-Centric Publish-Subscribe (DCPS) model in which participants discover each other automatically and exchange typed data via a global data space, governed by a rich set of Quality of Service (QoS) policies covering reliability, latency, deadline, liveliness, and durability. DDS is the foundational communication layer for ROS 2, NATO's STANAG 4910 tactical networks, and aerospace control systems."@en ;
rdfs:label "DDS Middleware"@en ;
rdfs:subClassOf ngm:middleware ;
rdfs:subClassOf _:r6659 ;
rdfs:subClassOf _:r6660 ;
rdfs:subClassOf _:r6661 ;
vc:bridgesTo ngm:infrastructure ;
vc:bridgesTo ngm:robotics ;
vc:contrastsWith ngm:message-broker ;
vc:contrastsWith ngm:mqtt ;
vc:enables ngm:autonomous-vehicle ;
vc:enables ngm:collaborative-systems-modality-robotics ;
vc:enables ngm:industrial-robot ;
vc:enables ngm:real-time ;
vc:enables ngm:robot-kinematics ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:publish-subscribe-pattern ;
vc:hasPart ngm:quality-of-service ;
vc:implements ngm:communication-protocol ;
vc:implements ngm:distributed-system-protocol ;
vc:implements ngm:publish-subscribe-pattern ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:middleware-layer ;
vc:relatedTo ngm:time-sensitive-networking ;
vc:requires ngm:network-transport ;
vc:slug "dds-middleware" ;
vc:sourceDomain "distributed-systems" ;
vc:standardizedBy ngm:object-management-group ;
vc:supports ngm:digital-twin ;
vc:supports ngm:ros-2 ;
vc:supports ngm:safety-critical-systems ;
vc:uses ngm:distributed-systems ;
vc:uses ngm:embedded-systems .
ngm:dds-qos a skos:Concept ;
rdfs:label "Dds Qos"@en .
ngm:dds-rtps-protocol a skos:Concept ;
rdfs:label "Dds Rtps Protocol"@en .
ngm:de-aging a skos:Concept ;
rdfs:label "De Aging"@en .
ngm:de-ber-ta a owl:Class ;
rdfs:comment "Decoding-enhanced BERT with Disentangled Attention: an improved BERT architecture that uses disentangled attention (separating content and position) and an enhanced mask decoder for better performance."@en ;
rdfs:label "De BER Ta"@en ;
rdfs:subClassOf ngm:sc-content-and-assets ;
skos:broader ngm:sc-content-and-assets ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:language-modeling ;
vc:contrastsWith ngm:large-language-models ;
vc:enables ngm:natural-language-processing ;
vc:enables ngm:natural-language-understanding ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:language-modeling ;
vc:implements ngm:transformer ;
vc:qualityScore "0.0"^^xsd:float ;
vc:slug "de-ber-ta" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:model-training ;
vc:uses ngm:training-data .
ngm:de-duplication-hashing a skos:Concept ;
rdfs:label "De Duplication Hashing"@en .
ngm:de-facto-standard a skos:Concept ;
rdfs:label "De Facto Standard"@en .
ngm:de-fi a owl:Class ;
rdfs:comment "DeFi (Decentralised Finance) is the ecosystem of open, permissionless financial protocols and applications deployed as Smart Contracts on public blockchains — primarily Ethereum — that replicate and extend traditional financial services such as lending, borrowing, trading, yield generation, and derivatives without centralised intermediaries such as banks, brokers, or clearinghouses. Core DeFi primitives include Automated Market Makers (AMMs), over-collateralised lending protocols, stablecoins, flash loans, and yield aggregators, all coordinated through token-based incentive mechanisms and governed by Decentralised Autonomous Organisations (DAOs). DeFi protocols are composable — outputs of one protocol become inputs to another, enabling complex financial strategies assembled from protocol primitives. The open, programmable architecture distinguishes DeFi from traditional finance and from centralised cryptocurrency exchanges, making it a distinct paradigm within the broader blockchain economy."@en ;
rdfs:label "DeFi"@en ;
rdfs:subClassOf ngm:bc-defi-and-economics ;
rdfs:subClassOf _:r7214 ;
rdfs:subClassOf _:r7215 ;
rdfs:subClassOf _:r7216 ;
rdfs:subClassOf _:r7217 ;
rdfs:subClassOf _:r7218 ;
rdfs:subClassOf _:r7219 ;
rdfs:subClassOf _:r7220 ;
rdfs:subClassOf _:r7221 ;
rdfs:subClassOf _:r7222 ;
skos:broader ngm:bc-defi-and-economics ;
vc:bridgesTo ngm:algorithmic-trading ;
vc:bridgesTo ngm:digital-identity ;
vc:contrastsWith ngm:centralised-exchange ;
vc:contrastsWith ngm:traditional-finance ;
vc:dependsOn ngm:consensus-mechanism ;
vc:dependsOn ngm:gas-fee ;
vc:enables ngm:liquidity-mining ;
vc:enables ngm:on-chain-derivatives ;
vc:enables ngm:permissionless-lending ;
vc:enables ngm:yield-farming ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:automated-market-maker ;
vc:hasPart ngm:flash-loan ;
vc:hasPart ngm:liquidity-pool ;
vc:hasPart ngm:yield-aggregator ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:cross-chain-bridge ;
vc:relatedTo ngm:dao-governance ;
vc:relatedTo ngm:maximal-extractable-value ;
vc:relatedTo ngm:token-economics ;
vc:requires ngm:blockchain ;
vc:requires ngm:oracle ;
vc:requires ngm:smart-contract ;
vc:requires ngm:wallet ;
vc:slug "de-fi" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:ethereum-smart-contract-platform-virtual-machine ;
vc:uses ngm:governance-token ;
vc:uses ngm:stablecoin ;
vc:uses ngm:token-standard .
ngm:de-fi-protocol a owl:Class ;
rdfs:comment "A blockchain-based financial application providing decentralized financial services via smart contracts."@en ;
rdfs:label "De Fi Protocol"@en ;
rdfs:subClassOf ngm:bc-defi-and-economics ;
skos:broader ngm:bc-defi-and-economics ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:virtual-economy ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:blockchain ;
vc:qualityScore "0.4"^^xsd:float ;
vc:slug "de-fi-protocol" ;
vc:sourceDomain "blockchain" .
ngm:de-fi-services a owl:Class ;
rdfs:comment "Decentralised Finance (DeFi) Services are financial products and protocols—including lending, borrowing, automated market-making, and derivatives—implemented as smart contracts on programmable blockchains without centralised intermediaries. DeFi Services enable permissionless, non-custodial access to financial primitives and are a key component of virtual economies within metaverse and spatial computing platforms."@en ;
rdfs:label "De Fi Services"@en ;
rdfs:subClassOf ngm:digital-asset-ecosystem ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf _:r7206 ;
rdfs:subClassOf _:r7207 ;
skos:broader ngm:sc-platform-and-environment ;
vc:bridgesTo ngm:blockchain ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:de-fi ;
vc:relatedTo ngm:financial-transactions ;
vc:requires ngm:blockchain ;
vc:requires ngm:smart-contract ;
vc:slug "de-fi-services" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:cryptocurrency ;
vc:uses ngm:digital-asset .
ngm:de-identification-module a skos:Concept ;
rdfs:label "De Identification Module"@en .
ngm:de-risking a skos:Concept ;
rdfs:label "De Risking"@en .
ngm:de-risking-avoidance a skos:Concept ;
rdfs:label "De Risking Avoidance"@en .
ngm:de-risking-prevention a skos:Concept ;
rdfs:label "De Risking Prevention"@en .
ngm:dead-internet-theory a skos:Concept ;
rdfs:label "Dead Internet Theory"@en .
ngm:dead-reckoning a owl:Class ;
rdfs:comment "Dead reckoning is a navigation technique that estimates an entity's current position by applying its known speed, heading, and elapsed time to a previously determined position. It relies on relative motion measurements from sensors such as inertial measurement units and wheel encoders rather than external position fixes. Because errors accumulate over time as drift, dead reckoning is typically fused with absolute references like GPS to maintain accuracy."@en ;
rdfs:label "Dead Reckoning"@en ;
rdfs:subClassOf ngm:localisation ;
rdfs:subClassOf _:r7223 ;
vc:bridgesTo ngm:sensor-fusion ;
vc:contrastsWith ngm:gps ;
vc:dependsOn ngm:inertial-measurement-unit ;
vc:dependsOn ngm:odometry ;
vc:enables ngm:autonomous-navigation ;
vc:enables ngm:pose-estimation ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:imu ;
vc:relatedTo ngm:kalman-filter ;
vc:relatedTo ngm:navigation ;
vc:relatedTo ngm:sensor-fusion ;
vc:requires ngm:state-estimation ;
vc:slug "dead-reckoning" ;
vc:sourceDomain "robotics" ;
vc:supports ngm:mobile-robot ;
vc:supports ngm:simultaneous-localisation-and-mapping ;
vc:uses ngm:accelerometer ;
vc:uses ngm:gyroscope ;
vc:uses ngm:velocity .
ngm:deadline a skos:Concept ;
rdfs:label "Deadline"@en .
ngm:deadline-scheduling a skos:Concept ;
rdfs:label "Deadline Scheduling"@en .
ngm:deadlock a skos:Concept ;
rdfs:label "Deadlock"@en .
ngm:deadlock-prevention a skos:Concept ;
rdfs:label "Deadlock Prevention"@en .
ngm:deanonymisation a owl:Class ;
rdfs:comment "Deanonymisation is the adversarial process of re-identifying individuals within data that was intended to be anonymous or pseudonymous, reversing the protective transformation that anonymisation applied. It works by correlating a supposedly de-identified record against auxiliary information — public datasets, quasi-identifiers such as postcode, age, and gender, behavioural fingerprints, or linkage across leaked corpora — until a unique individual is singled out. Landmark demonstrations against released medical, mobility, and streaming datasets have shown that removing direct identifiers is rarely sufficient. As the antonym of anonymisation, deanonymisation is both a privacy threat to defend against and an analytical technique used to test whether a dataset's protection actually holds."@en ;
rdfs:label "Deanonymisation"@en ;
rdfs:subClassOf ngm:adversarial-attack ;
vc:contrastsWith ngm:anonymisation ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:privacy ;
vc:relatedTo ngm:pseudonymity ;
vc:slug "deanonymisation" ;
vc:sourceDomain "security" ;
vc:uses ngm:data-analysis ;
vc:uses ngm:open-source-intelligence .
ngm:death-of-the-internet a owl:Class ;
rdfs:comment "Death of the Internet is a concept cluster in the ics-society and Media Theory domains capturing the convergent degradation of the public World Wide Web as a space for authentic human knowledge-exchange, discovery, and democratic discourse."@en ;
rdfs:label "Death of the Internet"@en ;
rdfs:subClassOf ngm:ai-ethics ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:digital-society-surveillance ;
rdfs:subClassOf ngm:information-integrity ;
rdfs:subClassOf ngm:media-theory ;
rdfs:subClassOf ngm:platform-decay ;
rdfs:subClassOf ngm:surveillance-capitalism ;
rdfs:subClassOf _:r7224 ;
rdfs:subClassOf _:r7225 ;
rdfs:subClassOf _:r7226 ;
rdfs:subClassOf _:r7227 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:bridgesTo ngm:governance ;
vc:bridgesTo ngm:infra-security-and-identity ;
vc:contrastsWith ngm:authentic-internet ;
vc:contrastsWith ngm:federated-social-networks ;
vc:contrastsWith ngm:human-authored-content ;
vc:contrastsWith ngm:indieweb-movement ;
vc:contrastsWith ngm:open-web ;
vc:contrastsWith ngm:solid ;
vc:dependsOn ngm:advertising-economics ;
vc:dependsOn ngm:ai-training-data ;
vc:dependsOn ngm:background-tokens ;
vc:dependsOn ngm:network-effects ;
vc:dependsOn ngm:platform-monopoly ;
vc:dependsOn ngm:search-economics ;
vc:dependsOn ngm:switching-costs ;
vc:enables ngm:algorithmic-capture ;
vc:enables ngm:attention-manipulation ;
vc:enables ngm:digital-divide ;
vc:enables ngm:disinformation-ecosystem ;
vc:enables ngm:epistemic-degradation ;
vc:enables ngm:model-collapse ;
vc:enables ngm:surveillance-capitalism ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:algorithmic-capture ;
vc:hasPart ngm:background-tokens ;
vc:hasPart ngm:bot-traffic ;
vc:hasPart ngm:dark-forest-theory ;
vc:hasPart ngm:dead-internet-theory ;
vc:hasPart ngm:enshittification ;
vc:hasPart ngm:filter-bubble ;
vc:hasPart ngm:habsburg-ai ;
vc:hasPart ngm:synthetic-content-saturation ;
vc:implements ngm:age-verification ;
vc:implements ngm:api-rate-limiting ;
vc:implements ngm:c2-pa-content-credentials ;
vc:implements ngm:c2-pa-standard ;
vc:implements ngm:online-safety-act-2023 ;
vc:implements ngm:robots-txt-enforcement ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:agentic-internet ;
vc:relatedTo ngm:agents ;
vc:relatedTo ngm:ai-companions ;
vc:relatedTo ngm:ai-risks ;
vc:relatedTo ngm:ai-scrapers ;
vc:relatedTo ngm:ai-search ;
vc:relatedTo ngm:bias-in-large-language-models ;
vc:relatedTo ngm:carbon-footprint-measurement ;
vc:relatedTo ngm:competition-in-ai ;
vc:relatedTo ngm:decentralised-web ;
vc:relatedTo ngm:deepfakes-and-fraudulent-content ;
vc:relatedTo ngm:digital-society-surveillance ;
vc:relatedTo ngm:global-inequality ;
vc:relatedTo ngm:human-ai-capability-complementarity ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:large-scale-pretrained-foundation-model ;
vc:relatedTo ngm:latent-space ;
vc:relatedTo ngm:neural-network-latent-space ;
vc:relatedTo ngm:solid ;
vc:relatedTo ngm:surveillance-capitalism ;
vc:relatedTo ngm:traditional-mass-media-institution ;
vc:relatedTo ngm:trust-and-safety ;
vc:requires ngm:authentic-content ;
vc:requires ngm:content-provenance ;
vc:requires ngm:epistemic-infrastructure ;
vc:requires ngm:human-authorship ;
vc:requires ngm:open-api-access ;
vc:requires ngm:platform-accountability ;
vc:slug "death-of-the-internet" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:c2-pa ;
vc:standardizedBy ngm:dsa ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:gdpr ;
vc:standardizedBy ngm:ietf ;
vc:standardizedBy ngm:ofcom ;
vc:standardizedBy ngm:uk-online-safety-act ;
vc:standardizedBy ngm:w3-c ;
vc:supports ngm:activity-pub ;
vc:supports ngm:blockchain-attestation ;
vc:supports ngm:decentralised-web ;
vc:supports ngm:digital-identity ;
vc:supports ngm:federated-social-networks ;
vc:supports ngm:open-source-ai ;
vc:supports ngm:solid ;
vc:uses ngm:agents ;
vc:uses ngm:ai-scrapers ;
vc:uses ngm:deepfakes-and-fraudulent-content ;
vc:uses ngm:large-language-models ;
vc:uses ngm:programmatic-advertising ;
vc:uses ngm:recommendation-systems ;
vc:uses ngm:social-media-platform-infrastructure .
ngm:debate a skos:Concept ;
rdfs:label "Debate"@en .
ngm:debate-protocol a skos:Concept ;
rdfs:label "Debate Protocol"@en .
ngm:deberta a skos:Concept ;
rdfs:label "Deberta"@en .
ngm:deblurring-network a skos:Concept ;
rdfs:label "Deblurring Network"@en .
ngm:debt a skos:Concept ;
rdfs:label "Debt"@en .
ngm:debt-management-office a skos:Concept ;
rdfs:label "Debt Management Office"@en .
ngm:debt-pool a skos:Concept ;
rdfs:label "Debt Pool"@en .
ngm:debt-securities a skos:Concept ;
rdfs:label "Debt Securities"@en .
ngm:debug-log a skos:Concept ;
rdfs:label "Debug Log"@en .
ngm:debugging a owl:Class ;
rdfs:comment "Debugging is the systematic process of locating, diagnosing and resolving defects in software so that it behaves as intended. It typically involves reproducing the fault, observing program state through breakpoints, logging and runtime inspection, forming hypotheses about the cause, and verifying a fix. Debugging spans interactive use of debuggers, analysis of stack traces and logs, and reasoning about concurrency and integration boundaries. It is a core software development activity complementary to, but distinct from, automated testing."@en ;
rdfs:label "Debugging"@en ;
rdfs:subClassOf ngm:software-development ;
rdfs:subClassOf _:r7228 ;
vc:bridgesTo ngm:devops ;
vc:contrastsWith ngm:testing ;
vc:dependsOn ngm:observability ;
vc:enables ngm:fault-tolerance ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:software-testing ;
vc:isPartOf ngm:software-engineering ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:reliability ;
vc:relatedTo ngm:software-testing ;
vc:relatedTo ngm:version-control ;
vc:requires ngm:runtime-environment ;
vc:slug "debugging" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:reliability ;
vc:supports ngm:software-engineering ;
vc:uses ngm:observability ;
vc:uses ngm:runtime-environment .
ngm:deburring a skos:Concept ;
rdfs:label "Deburring"@en .
ngm:decarbonisation a owl:Class ;
rdfs:comment "Decarbonisation is the systematic reduction of carbon dioxide and other greenhouse-gas emissions from an activity, organisation or economy, ultimately toward net zero. It combines energy efficiency, electrification, renewable energy procurement and removal of residual emissions, often guided by science-based targets. For energy-intensive systems such as blockchains it is the pathway to credible carbon-neutral operation."@en ;
rdfs:label "Decarbonisation"@en ;
rdfs:subClassOf ngm:sustainability ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:carbon-neutral-blockchain ;
vc:relatedTo ngm:science-based-targets ;
vc:slug "decarbonisation" ;
vc:sourceDomain "governance" .
ngm:decarbonization a skos:Concept ;
rdfs:label "Decarbonization"@en .
ngm:decay-constant-alpha a skos:Concept ;
rdfs:label "Decay Constant Alpha"@en .
ngm:decentraland a owl:Class ;
rdfs:comment "Decentraland is a blockchain-based virtual world in which users own parcels of virtual land and in-world assets as non-fungible tokens on the Ethereum network, governed by a decentralised autonomous organisation through on-chain voting with governance tokens."@en ;
rdfs:label "Decentraland"@en ;
rdfs:subClassOf ngm:metaverse-platform ;
rdfs:subClassOf _:r7229 ;
rdfs:subClassOf _:r7230 ;
rdfs:subClassOf _:r7231 ;
rdfs:subClassOf _:r7232 ;
rdfs:subClassOf _:r7233 ;
vc:bridgesTo ngm:dao ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:distributed-governance ;
vc:bridgesTo ngm:spatial-computing ;
vc:contrastsWith ngm:roblox ;
vc:contrastsWith ngm:the-sandbox ;
vc:enables ngm:asset-tokenisation ;
vc:enables ngm:play-to-earn-p2-e ;
vc:enables ngm:social-vr ;
vc:enables ngm:user-generated-content ;
vc:enables ngm:virtual-land-rights ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:land-nft ;
vc:implements ngm:dao ;
vc:implements ngm:erc-721-standard ;
vc:isPartOf ngm:open-metaverse ;
vc:isPartOf ngm:web3 ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:metaverse ;
vc:relatedTo ngm:virtual-reality ;
vc:requires ngm:cryptocurrency-wallet ;
vc:requires ngm:ethereum ;
vc:requires ngm:ethereum-smart-contract-platform ;
vc:requires ngm:non-fungible-token ;
vc:requires ngm:smart-contract ;
vc:slug "decentraland" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:ethereum-smart-contract-platform ;
vc:uses ngm:ipfs .
ngm:decentralisation a owl:Class ;
rdfs:comment "Decentralisation is the architectural and governance principle of distributing authority, control, computation, or data storage across multiple independent nodes or actors rather than concentrating it in a single entity. In technical systems it manifests as distributed ledgers, peer-to-peer networks, and federated protocols that eliminate single points of failure and censorship. In governance it refers to transferring decision-making power from central authorities to local or community actors. The degree of decentralisation exists on a spectrum and involves trade-offs between efficiency, security, scalability, and resilience."@en ;
rdfs:label "Decentralisation"@en ;
rdfs:subClassOf ngm:governance-framework ;
rdfs:subClassOf _:r7234 ;
rdfs:subClassOf _:r7235 ;
rdfs:subClassOf _:r7236 ;
rdfs:subClassOf _:r7237 ;
rdfs:subClassOf _:r7238 ;
rdfs:subClassOf _:r7239 ;
vc:bridgesTo ngm:edge-computing ;
vc:bridgesTo ngm:federated-learning ;
vc:bridgesTo ngm:supply-chain-transparency ;
vc:contrastsWith ngm:federated-system ;
vc:enables ngm:censorship-resistance ;
vc:enables ngm:de-fi ;
vc:enables ngm:decentralised-identity ;
vc:enables ngm:permissionless-innovation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:consensus-mechanism ;
vc:hasPart ngm:nakamoto-coefficient ;
vc:hasPart ngm:sybil-resistance ;
vc:implements ngm:distributed-ledger-technology ;
vc:implements ngm:peer-to-peer-network ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:network-topology ;
vc:relatedTo ngm:open-source-software ;
vc:relatedTo ngm:self-sovereign-identity ;
vc:requires ngm:byzantine-fault-tolerance ;
vc:requires ngm:cryptographic-hash-function ;
vc:requires ngm:incentive-mechanism ;
vc:slug "decentralisation" ;
vc:sourceDomain "distributed-systems" ;
vc:supports ngm:blockchain-governance ;
vc:supports ngm:dao ;
vc:supports ngm:decentralized-governance ;
vc:supports ngm:fault-tolerance .
ngm:decentralisation-monitoring a skos:Concept ;
rdfs:label "Decentralisation Monitoring"@en .
ngm:decentralised-agent-coordination-initiative a owl:Class ;
rdfs:comment "An open collaborative initiative advancing decentralised agent frameworks that integrate Nostr relays for communication, Bitcoin Lightning for micropayments, distributed identity, and open data connectors to enable trustless, economically-incentivised multi-agent coordination without central intermediaries."@en ;
rdfs:label "Decentralised Agent Coordination Initiative"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf _:r7240 ;
rdfs:subClassOf _:r7241 ;
rdfs:subClassOf _:r7242 ;
skos:broader ngm:ai-application ;
vc:bridgesTo ngm:blockchain ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:agents ;
vc:hasPart ngm:smart-contract ;
vc:qualityScore "0.5"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:distributed-ledger ;
vc:requires ngm:blockchain ;
vc:slug "decentralised-agent-coordination-initiative" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:distributed-computing ;
vc:uses ngm:distributed-identity ;
vc:uses ngm:nostr-protocol .
ngm:decentralised-agentic-infrastructure-stack a owl:Class ;
rdfs:comment "A convergent set of nascent and rapidly maturing technologies—including decentralised identity, linked data, nostr key-pair agents, lightning-network micropayments, and knowledge graph tooling—that together enable a new paradigm of interoperable, agent-driven digital infrastructure. The stack combines protocol-level primitives with knowledge management and collaborative AI to support autonomous, verifiable workflows."@en ;
rdfs:label "Decentralised Agentic Infrastructure Stack"@en ;
rdfs:subClassOf ngm:infra-computing-and-cloud ;
rdfs:subClassOf _:r7243 ;
rdfs:subClassOf _:r7244 ;
rdfs:subClassOf _:r7245 ;
skos:broader ngm:infra-computing-and-cloud ;
vc:enables ngm:agentic-ai ;
vc:enables ngm:version-control ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:decentralized-identity-did ;
vc:hasPart ngm:knowledge-graph ;
vc:hasPart ngm:linked-data ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:blockchain ;
vc:relatedTo ngm:interoperability ;
vc:slug "decentralised-agentic-infrastructure-stack" ;
vc:sourceDomain "infrastructure" .
ngm:decentralised-ai a owl:Class ;
rdfs:comment "Decentralised AI refers to artificial intelligence systems whose training, inference, data provenance, or governance are distributed across many independent participants rather than controlled by a single centralised entity. It commonly combines machine-learning techniques such as federated learning with blockchain or peer-to-peer infrastructure to coordinate compute, verify contributions, and align incentives through crypto-economic mechanisms. The goal is to reduce single points of control and failure, preserve data sovereignty, and enable open marketplaces for models, data, and compute."@en ;
rdfs:label "Decentralised Ai"@en ;
rdfs:subClassOf ngm:ai-infrastructure ;
rdfs:subClassOf ngm:blockchain ;
skos:broader ngm:blockchain ;
vc:bridgesTo ngm:artificial-intelligence ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:dependsOn ngm:distributed-ledger ;
vc:dependsOn ngm:tokenization ;
vc:enables ngm:data-sovereignty ;
vc:enables ngm:edge-ai ;
vc:enables ngm:privacy-preserving-machine-learning ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:decentralised-identity ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:blockchain-consensus ;
vc:relatedTo ngm:proof-of-stake ;
vc:slug "decentralised-ai" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:web3 ;
vc:uses ngm:federated-learning ;
vc:uses ngm:peer-to-peer-network ;
vc:uses ngm:smart-contract .
ngm:decentralised-ai-inference a skos:Concept ;
rdfs:label "Decentralised AI Inference"@en .
ngm:decentralised-application a owl:Class ;
rdfs:comment "A decentralised application (dApp) is software whose backend logic runs on a decentralised peer-to-peer network, typically as smart contracts on a blockchain, rather than on centrally controlled servers. It combines on-chain contracts for trustless state and logic with off-chain front ends and storage. dApps are a defining component of Web3, enabling permissionless, censorship-resistant services such as exchanges, lending and marketplaces."@en ;
rdfs:label "Decentralised Application"@en ;
rdfs:subClassOf ngm:distributed-system ;
rdfs:subClassOf _:r7246 ;
rdfs:subClassOf _:r7247 ;
rdfs:subClassOf _:r7248 ;
rdfs:subClassOf _:r7249 ;
rdfs:subClassOf _:r7250 ;
vc:bridgesTo ngm:digital-governance ;
vc:bridgesTo ngm:distributed-systems ;
vc:dependsOn ngm:decentralised-storage ;
vc:dependsOn ngm:peer-to-peer-network ;
vc:dependsOn ngm:token-standard ;
vc:enables ngm:de-fi ;
vc:enables ngm:decentralised-autonomous-organisation ;
vc:enables ngm:non-fungible-token ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:smart-contract ;
vc:hasPart ngm:wallet ;
vc:implements ngm:open-source-software ;
vc:implements ngm:web3 ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:censorship-resistance ;
vc:relatedTo ngm:token-economy ;
vc:relatedTo ngm:web3 ;
vc:requires ngm:blockchain ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:cryptocurrency-wallet ;
vc:slug "decentralised-application" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:ethereum ;
vc:uses ngm:ipfs ;
vc:uses ngm:oracle .
ngm:decentralised-authentication a owl:Class ;
rdfs:comment "Decentralised authentication verifies the identity of a party without relying on a single central identity provider, instead using cryptographic keys, decentralised identifiers and verifiable credentials controlled by the user. The holder proves control of an identifier and presents credentials that a verifier checks against a distributed trust registry rather than a federated login service. This shifts control of identity from platforms to individuals while preserving cryptographic assurance."@en ;
rdfs:label "Decentralised Authentication"@en ;
rdfs:subClassOf ngm:authentication-protocol ;
rdfs:subClassOf _:r7251 ;
rdfs:subClassOf _:r7252 ;
vc:bridgesTo ngm:verifiable-credentials ;
vc:contrastsWith ngm:centralised-identity ;
vc:contrastsWith ngm:user-authentication ;
vc:dependsOn ngm:did ;
vc:enables ngm:decentralised-identity ;
vc:enables ngm:self-sovereign-identity-ssi ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:authentication-protocol ;
vc:isPartOf ngm:decentralised-identity ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:blockchain-identity ;
vc:relatedTo ngm:oauth-2-0 ;
vc:requires ngm:did-document ;
vc:requires ngm:trust-anchor ;
vc:slug "decentralised-authentication" ;
vc:sourceDomain "security" ;
vc:supports ngm:multi-factor-authentication ;
vc:supports ngm:web-authn ;
vc:uses ngm:did ;
vc:uses ngm:did-method ;
vc:uses ngm:verifiable-credentials .
ngm:decentralised-autonomous-organisation a owl:Class ;
rdfs:comment "A Decentralised Autonomous Organisation (DAO) is a blockchain-native organisational structure in which governance rules, treasury management, and operational logic are encoded as smart contracts executing on a public distributed ledger, enabling token-holder communities to propose, deliberate, and vote on decisions without recourse to centralised management or traditional corporate hierarchy. DAOs achieve censorship-resistant, transparent coordination by replacing trusted intermediaries with deterministic on-chain execution, typically combining governance tokens that confer weighted voting rights with treasury contracts that custodise and disburse collective assets. As an emergent governance primitive, DAOs span DeFi protocols, grant programmes, investment collectives, open-source software foundations, and decentralised media organisations, presenting novel challenges around legal personality, voter apathy, and Sybil resistance."@en ;
rdfs:label "Decentralised Autonomous Organisation"@en ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
rdfs:subClassOf _:r7253 ;
rdfs:subClassOf _:r7254 ;
rdfs:subClassOf _:r7255 ;
rdfs:subClassOf _:r7256 ;
rdfs:subClassOf _:r7257 ;
rdfs:subClassOf _:r7258 ;
skos:broader ngm:bc-governance-and-regulation ;
vc:bridgesTo ngm:collective-intelligence ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:contrastsWith ngm:traditional-corporation ;
vc:dependsOn ngm:de-fi ;
vc:dependsOn ngm:tokenomics ;
vc:enables ngm:on-chain-governance ;
vc:enables ngm:permissionless-participation ;
vc:enables ngm:protocol-governance ;
vc:enables ngm:treasury-management ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:governance ;
vc:hasPart ngm:treasury-contract ;
vc:hasPart ngm:voting-mechanism ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:decentralised-governance ;
vc:relatedTo ngm:liquid-democracy ;
vc:relatedTo ngm:sybil-resistance ;
vc:relatedTo ngm:token-weighted-voting ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:cryptographic-key-management ;
vc:requires ngm:public-blockchain ;
vc:slug "decentralised-autonomous-organisation" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:governance-token ;
vc:uses ngm:multisig-wallet ;
vc:uses ngm:quadratic-voting ;
vc:uses ngm:smart-contract .
ngm:decentralised-computation a skos:Concept ;
rdfs:label "Decentralised Computation"@en .
ngm:decentralised-compute a skos:Concept ;
rdfs:label "Decentralised Compute"@en .
ngm:decentralised-content-network a skos:Concept ;
rdfs:label "Decentralised Content Network"@en .
ngm:decentralised-coordination a owl:Class ;
rdfs:comment "Decentralised coordination refers to mechanisms by which multiple autonomous agents—human or machine—achieve collective outcomes without a central authority directing behaviour, relying instead on shared protocols, incentive structures, consensus rules, or emergent social norms. In blockchain contexts it manifests as DAO governance, token-based voting, and smart-contract-enforced agreements that replace managerial hierarchy with algorithmic rule."@en ;
rdfs:label "Decentralised Coordination"@en ;
rdfs:subClassOf ngm:autonomous-governance ;
rdfs:subClassOf _:r7259 ;
rdfs:subClassOf _:r7260 ;
rdfs:subClassOf _:r7261 ;
rdfs:subClassOf _:r7262 ;
rdfs:subClassOf _:r7263 ;
vc:bridgesTo ngm:ai-agent-coordination ;
vc:bridgesTo ngm:multi-agent-systems ;
vc:contrastsWith ngm:centralised-governance ;
vc:contrastsWith ngm:hierarchical-organisation ;
vc:enables ngm:dao-governance ;
vc:enables ngm:permissionless-participation ;
vc:enables ngm:treasury-management ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:conviction-voting ;
vc:hasPart ngm:token-weighted-voting ;
vc:implements ngm:mechanism-design ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:algorithmic-governance ;
vc:relatedTo ngm:commons-governance ;
vc:relatedTo ngm:game-theory ;
vc:requires ngm:byzantine-fault-tolerance ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:smart-contract ;
vc:slug "decentralised-coordination" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:asynchronous-coordination ;
vc:uses ngm:dao ;
vc:uses ngm:incentive-mechanism ;
vc:uses ngm:quadratic-voting .
ngm:decentralised-creative-metaverse-framework a owl:Class ;
rdfs:comment "A conceptual and technical framework for a decentralised, AI-agent-driven metaverse ecosystem enabling global creative collaboration, autonomous task execution, and value exchange. The architecture integrates Nostr for identity and communication, Bitcoin and Lightning Network for payments, and USD/Omniverse for 3D asset manipulation, with agentic actors managing task negotiation, content delivery, and digital-object provenance across interconnected virtual spaces."@en ;
rdfs:label "Decentralised Creative Metaverse Framework"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf _:r7264 ;
rdfs:subClassOf _:r7265 ;
skos:broader ngm:ai-application ;
vc:bridgesTo ngm:digital-twin ;
vc:enables ngm:digital-twin ;
vc:enables ngm:metaverse ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:requires ngm:agent-frameworks ;
vc:requires ngm:nostr-protocol ;
vc:slug "decentralised-creative-metaverse-framework" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:digital-asset ;
vc:uses ngm:large-language-models ;
vc:uses ngm:lightning-network .
ngm:decentralised-decision-making a owl:Class ;
rdfs:comment "Decentralised Decision-Making is a governance paradigm in which authority to make binding choices is distributed across multiple autonomous actors — individuals, nodes, or smart contracts — rather than concentrated in a single hierarchical centre, typically relying on voting mechanisms, consensus protocols, or market-based coordination to aggregate preferences and resolve conflicts. In blockchain and DAO contexts, decentralised decision-making is operationalised through on-chain proposal-and-vote cycles, token-weighted or quadratic voting, and cryptographically enforced execution of outcomes via smart contracts. The paradigm spans organisational theory, political science, distributed systems, and mechanism design, with implementations ranging from holocratic corporations to fully autonomous protocol governance."@en ;
rdfs:label "Decentralised Decision-Making"@en ;
rdfs:subClassOf ngm:decentralized-governance ;
vc:enables ngm:blockchain-governance ;
vc:enables ngm:dao-governance ;
vc:enables ngm:on-chain-governance ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:consensus-mechanism ;
vc:relatedTo ngm:dao ;
vc:relatedTo ngm:liquid-democracy ;
vc:relatedTo ngm:mechanism-design ;
vc:slug "decentralised-decision-making" ;
vc:sourceDomain "governance" ;
vc:uses ngm:governance-token ;
vc:uses ngm:quadratic-voting ;
vc:uses ngm:snapshot-voting .
ngm:decentralised-exchange a owl:Class ;
rdfs:comment "A trading venue that allows users to swap digital assets directly through smart contracts, without a central operator holding custody of funds or matching orders off-chain."@en ;
rdfs:label "Decentralised Exchange"@en ;
rdfs:subClassOf ngm:exchange-mechanism ;
rdfs:subClassOf _:r7266 ;
rdfs:subClassOf _:r7267 ;
rdfs:subClassOf _:r7268 ;
rdfs:subClassOf _:r7269 ;
rdfs:subClassOf _:r7270 ;
rdfs:subClassOf _:r7271 ;
rdfs:subClassOf _:r7272 ;
rdfs:subClassOf _:r7273 ;
vc:bridgesTo ngm:automated-market-maker ;
vc:bridgesTo ngm:financial-market ;
vc:bridgesTo ngm:order-book ;
vc:bridgesTo ngm:peer-to-peer-network ;
vc:contrastsWith ngm:centralised-exchange ;
vc:enables ngm:permissionless-trading ;
vc:enables ngm:self-custody ;
vc:enables ngm:token-swapping ;
vc:enables ngm:yield-farming ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:automated-market-maker ;
vc:hasPart ngm:liquidity-pool ;
vc:hasPart ngm:order-book ;
vc:implements ngm:de-fi ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:governance-token ;
vc:relatedTo ngm:impermanent-loss ;
vc:relatedTo ngm:miner-extractable-value ;
vc:relatedTo ngm:slippage ;
vc:requires ngm:blockchain-network ;
vc:requires ngm:cryptocurrency-wallet ;
vc:requires ngm:gas-fee ;
vc:requires ngm:liquidity-pool ;
vc:requires ngm:smart-contract ;
vc:slug "decentralised-exchange" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:consensus-mechanism ;
vc:uses ngm:cryptographic-signature ;
vc:uses ngm:oracle .
ngm:decentralised-file-storage a owl:Class ;
rdfs:comment "Decentralised file storage denotes a class of infrastructure protocols and networks that disaggregate object/blob persistence across geographically distributed, mutually untrusting node operators using content-addressing, cryptographic accountability, and (in most implementations) crypto-economic..."@en ;
rdfs:label "Decentralised file storage"@en ;
rdfs:subClassOf ngm:content-addressed-storage ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf ngm:distributed-storage ;
rdfs:subClassOf ngm:peer-to-peer-network ;
rdfs:subClassOf ngm:permissionless-protocol ;
rdfs:subClassOf ngm:web-3-infrastructure ;
rdfs:subClassOf _:r7326 ;
rdfs:subClassOf _:r7327 ;
rdfs:subClassOf _:r7328 ;
rdfs:subClassOf _:r7329 ;
rdfs:subClassOf _:r7330 ;
rdfs:subClassOf _:r7331 ;
rdfs:subClassOf _:r7332 ;
vc:contrastsWith ngm:cdn ;
vc:contrastsWith ngm:centralised-file-server ;
vc:contrastsWith ngm:network-attached-storage ;
vc:contrastsWith ngm:object-storage ;
vc:dependsOn ngm:blockchain ;
vc:dependsOn ngm:distributed-hash-table ;
vc:dependsOn ngm:merkle-tree ;
vc:dependsOn ngm:public-key-cryptography ;
vc:dependsOn ngm:zk-snark ;
vc:enables ngm:censorship-resistance ;
vc:enables ngm:data-sovereignty ;
vc:enables ngm:nft-metadata-persistence ;
vc:enables ngm:permaweb ;
vc:enables ngm:verifiable-storage ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:content-identifier ;
vc:hasPart ngm:distributed-hash-table ;
vc:hasPart ngm:erasure-coding ;
vc:hasPart ngm:pinning-service ;
vc:hasPart ngm:retrieval-market ;
vc:hasPart ngm:storage-proof ;
vc:hasPart ngm:storage-provider ;
vc:implements ngm:bitswap-protocol ;
vc:implements ngm:kademlia-dht ;
vc:implements ngm:proof-of-replication ;
vc:implements ngm:proof-of-spacetime ;
vc:implements ngm:reed-solomon-erasure-coding ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:decentralized-identity ;
vc:relatedTo ngm:distributed-ledger-technology ;
vc:relatedTo ngm:smart-contract ;
vc:relatedTo ngm:tokenomics ;
vc:requires ngm:bandwidth ;
vc:requires ngm:cryptographic-hash-function ;
vc:requires ngm:cryptographic-infrastructure ;
vc:requires ngm:disk-storage ;
vc:requires ngm:libp2p ;
vc:slug "decentralised-file-storage" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:ietf ;
vc:standardizedBy ngm:ipld ;
vc:standardizedBy ngm:multiformats ;
vc:standardizedBy ngm:ucan-working-group ;
vc:supports ngm:ai-dataset-distribution ;
vc:supports ngm:decentralised-web ;
vc:supports ngm:decentralized-application ;
vc:supports ngm:decentralized-storage ;
vc:supports ngm:decentralized-web ;
vc:supports ngm:nft ;
vc:uses ngm:car-file ;
vc:uses ngm:cid ;
vc:uses ngm:ipld ;
vc:uses ngm:multihash ;
vc:uses ngm:ucan .
ngm:decentralised-finance a owl:Class ;
rdfs:comment "Decentralised Finance (DeFi) encompasses financial services and instruments—including lending, borrowing, trading, derivatives, and yield generation—implemented as permissionless, non-custodial smart contracts on public blockchains, eliminating the need for traditional financial intermediaries such as banks, brokers, clearinghouses, and custodians. Protocol logic is encoded directly in on-chain code that executes deterministically and transparently, allowing any party with an internet connection to inspect the rules governing their assets. DeFi protocols achieve composability by adhering to shared token standards and interacting through standardised interfaces, enabling complex multi-step financial strategies assembled from interoperable building blocks. The sector operates without central points of control, exposing users to smart-contract risk, oracle manipulation, and governance attacks in place of traditional counterparty risk."@en ;
rdfs:label "Decentralised Finance"@en ;
rdfs:subClassOf ngm:bc-defi-and-economics ;
rdfs:subClassOf _:r7274 ;
rdfs:subClassOf _:r7275 ;
rdfs:subClassOf _:r7276 ;
rdfs:subClassOf _:r7277 ;
rdfs:subClassOf _:r7278 ;
rdfs:subClassOf _:r7279 ;
rdfs:subClassOf _:r7280 ;
rdfs:subClassOf _:r7281 ;
rdfs:subClassOf _:r7282 ;
rdfs:subClassOf _:r7283 ;
skos:broader ngm:bc-defi-and-economics ;
vc:bridgesTo ngm:algorithmic-trading ;
vc:bridgesTo ngm:regulatory-technology ;
vc:contrastsWith ngm:centralised-finance ;
vc:contrastsWith ngm:traditional-banking ;
vc:dependsOn ngm:ethereum ;
vc:dependsOn ngm:interoperability-protocol ;
vc:dependsOn ngm:layer-2-scaling ;
vc:enables ngm:cross-border-payments ;
vc:enables ngm:financial-inclusion ;
vc:enables ngm:flash-loan ;
vc:enables ngm:real-world-asset-tokenisation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:automated-market-maker ;
vc:hasPart ngm:decentralised-exchange ;
vc:hasPart ngm:lending-protocol ;
vc:hasPart ngm:liquidity-pool ;
vc:hasPart ngm:yield-farming ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:cryptocurrency ;
vc:relatedTo ngm:dao ;
vc:relatedTo ngm:non-fungible-token ;
vc:relatedTo ngm:web3 ;
vc:requires ngm:blockchain-oracle ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:smart-contract ;
vc:requires ngm:wallet ;
vc:slug "decentralised-finance" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:governance-token ;
vc:uses ngm:stablecoin ;
vc:uses ngm:token-standard ;
vc:uses ngm:tokenization .
ngm:decentralised-finance-anonymity a skos:Concept ;
rdfs:label "Decentralised Finance Anonymity"@en .
ngm:decentralised-finance-domain a skos:Concept ;
rdfs:label "Decentralised Finance Domain"@en .
ngm:decentralised-finance-infrastructure a skos:Concept ;
rdfs:label "Decentralised Finance Infrastructure"@en .
ngm:decentralised-fundraising a skos:Concept ;
rdfs:label "Decentralised Fundraising"@en .
ngm:decentralised-governance a owl:Class ;
rdfs:comment "A model of collective decision-making in which authority is distributed across participants rather than concentrated in a central body, often implemented through on-chain voting, token-weighted proposals, and smart contracts that execute decisions automatically once thresholds are met."@en ;
rdfs:label "Decentralised Governance"@en ;
rdfs:subClassOf ngm:governance-framework ;
rdfs:subClassOf _:r7284 ;
rdfs:subClassOf _:r7285 ;
rdfs:subClassOf _:r7286 ;
rdfs:subClassOf _:r7287 ;
rdfs:subClassOf _:r7288 ;
vc:bridgesTo ngm:collective-intelligence ;
vc:bridgesTo ngm:dao ;
vc:bridgesTo ngm:decentralisation ;
vc:bridgesTo ngm:distributed-systems ;
vc:contrastsWith ngm:centralised-governance ;
vc:contrastsWith ngm:hierarchical-organisation ;
vc:dependsOn ngm:blockchain ;
vc:dependsOn ngm:identity-verification ;
vc:dependsOn ngm:token ;
vc:enables ngm:community-treasury ;
vc:enables ngm:decentralised-autonomous-organisation ;
vc:enables ngm:permissionless-participation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:on-chain-voting ;
vc:hasPart ngm:token-weighted-voting ;
vc:implements ngm:dao ;
vc:implements ngm:liquid-democracy ;
vc:isPartOf ngm:decentralisation ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:stakeholder-participation ;
vc:relatedTo ngm:voting-mechanism ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:smart-contract ;
vc:requires ngm:transparency ;
vc:slug "decentralised-governance" ;
vc:sourceDomain "governance" ;
vc:supports ngm:distributed-collaboration ;
vc:supports ngm:open-source-governance ;
vc:uses ngm:governance-token ;
vc:uses ngm:quadratic-voting .
ngm:decentralised-identifier a owl:Class ;
rdfs:comment "A type of globally unique identifier, defined by a W3C standard, that is controlled by its subject and resolves to a DID document containing public keys and service endpoints, without depending on a central registry or issuing authority."@en ;
rdfs:label "Decentralised Identifier"@en ;
rdfs:subClassOf ngm:digital-identity ;
rdfs:subClassOf _:r7289 ;
rdfs:subClassOf _:r7290 ;
rdfs:subClassOf _:r7291 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:decentralised-identity ;
vc:bridgesTo ngm:identity-management ;
vc:bridgesTo ngm:internet-of-things ;
vc:contrastsWith ngm:centralised-identifier ;
vc:contrastsWith ngm:federated-identity ;
vc:enables ngm:decentralised-authentication ;
vc:enables ngm:self-sovereign-identity ;
vc:enables ngm:verifiable-credentials ;
vc:enables ngm:zero-knowledge-proof ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:uri-scheme ;
vc:implements ngm:w3-c-did-core ;
vc:isPartOf ngm:decentralised-identity ;
vc:isPartOf ngm:identity-management ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:cryptographic-infrastructure ;
vc:relatedTo ngm:identity-resolution ;
vc:relatedTo ngm:oauth ;
vc:requires ngm:did-document ;
vc:requires ngm:did-method ;
vc:requires ngm:public-key-cryptography ;
vc:slug "decentralised-identifier" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:w3-c ;
vc:uses ngm:digital-signature ;
vc:uses ngm:distributed-ledger-technology ;
vc:uses ngm:json-ld .
ngm:decentralised-identifiers a owl:Class ;
rdfs:comment "A W3C standard for globally unique identifiers that are created, owned and controlled by their subject without reliance on a central registration authority, enabling verifiable, self-sovereign digital identity."@en ;
rdfs:label "Decentralised Identifiers"@en ;
rdfs:subClassOf ngm:digital-identity ;
rdfs:subClassOf _:r7292 ;
rdfs:subClassOf _:r7293 ;
rdfs:subClassOf _:r7294 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:identity ;
vc:bridgesTo ngm:w3-c ;
vc:bridgesTo ngm:web-of-trust ;
vc:contrastsWith ngm:centralized-identity-provider ;
vc:contrastsWith ngm:oauth ;
vc:enables ngm:decentralised-authentication ;
vc:enables ngm:selective-disclosure ;
vc:enables ngm:self-sovereign-identity ;
vc:enables ngm:verifiable-credentials ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:uri-scheme ;
vc:implements ngm:w3-c-did-specification ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:authentication ;
vc:relatedTo ngm:identity ;
vc:relatedTo ngm:trust-framework ;
vc:requires ngm:cryptographic-infrastructure ;
vc:requires ngm:cryptography ;
vc:requires ngm:did-document ;
vc:slug "decentralised-identifiers" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:w3-c ;
vc:supports ngm:privacy-by-design ;
vc:supports ngm:zero-knowledge-proof ;
vc:uses ngm:did-method ;
vc:uses ngm:digital-signature ;
vc:uses ngm:distributed-ledger .
ngm:decentralised-identity a owl:Class ;
rdfs:comment "Decentralised Identity is a model for digital identity management in which individuals, organisations, and devices create, own, and control their own cryptographic identifiers and verifiable credentials without dependence on centralised identity providers or registries. Identifiers are anchored to a verifiable data registry — typically a blockchain or distributed ledger — as Decentralised Identifiers (DIDs) standardised by the W3C DID Core 1.0 specification, which defines a URI scheme resolving to a DID Document containing public keys and service endpoints. Credentials attesting to attributes of the DID subject are issued by trusted parties as W3C Verifiable Credentials, stored in a user-controlled digital wallet, and selectively disclosed to verifiers using zero-knowledge proofs or selective-disclosure mechanisms. The model operationalises Self-Sovereign Identity principles, giving subjects full autonomy over their identity data across systems and jurisdictions."@en ;
rdfs:label "Decentralised Identity"@en ;
rdfs:subClassOf ngm:digital-identity ;
rdfs:subClassOf _:r7295 ;
rdfs:subClassOf _:r7296 ;
rdfs:subClassOf _:r7297 ;
vc:bridgesTo ngm:access-control ;
vc:bridgesTo ngm:ai-agent-identity ;
vc:contrastsWith ngm:centralized-identity-provider ;
vc:contrastsWith ngm:federated-identity ;
vc:enables ngm:digital-identity ;
vc:enables ngm:privacy-preserving-authentication ;
vc:enables ngm:selective-disclosure ;
vc:enables ngm:self-sovereign-identity ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:openid-for-verifiable-credentials ;
vc:implements ngm:w3-c-did-specification ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:credential-schema ;
vc:relatedTo ngm:federated-identity ;
vc:relatedTo ngm:oauth-2-0 ;
vc:relatedTo ngm:trust-framework ;
vc:requires ngm:cryptographic-key-management ;
vc:requires ngm:did-method ;
vc:requires ngm:verifiable-data-registry ;
vc:slug "decentralised-identity" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:open-id-foundation ;
vc:standardizedBy ngm:w3-c ;
vc:uses ngm:did-document ;
vc:uses ngm:digital-identity-wallet ;
vc:uses ngm:public-key-cryptography ;
vc:uses ngm:verifiable-credentials ;
vc:uses ngm:zero-knowledge-proof .
ngm:decentralised-infrastructure a skos:Concept ;
rdfs:label "Decentralised Infrastructure"@en .
ngm:decentralised-knowledge-graph a skos:Concept ;
rdfs:label "Decentralised Knowledge Graph"@en .
ngm:decentralised-lending a skos:Concept ;
rdfs:label "Decentralised Lending"@en .
ngm:decentralised-naming a skos:Concept ;
rdfs:label "Decentralised Naming"@en .
ngm:decentralised-network a owl:Class ;
rdfs:comment "A Decentralised Network is a network architecture in which control, data and decision-making are distributed across many independent nodes rather than concentrated in a central authority or server. Nodes communicate peer-to-peer, share responsibility for routing, storage and consensus, and the network continues to operate even when individual nodes fail or leave. This topology improves resilience, censorship resistance and fault tolerance at the cost of greater coordination complexity."@en ;
rdfs:label "Decentralised Network"@en ;
rdfs:subClassOf ngm:distributed-systems ;
rdfs:subClassOf _:r7298 ;
rdfs:subClassOf _:r7299 ;
vc:bridgesTo ngm:blockchain-network ;
vc:bridgesTo ngm:peer-to-peer-network ;
vc:contrastsWith ngm:federation ;
vc:dependsOn ngm:node ;
vc:enables ngm:censorship-resistance ;
vc:enables ngm:decentralization ;
vc:enables ngm:fault-tolerance ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:distributed-systems ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:distributed-hash-table ;
vc:relatedTo ngm:federation ;
vc:relatedTo ngm:ipfs ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:network-protocol ;
vc:slug "decentralised-network" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:distributed-ledger ;
vc:supports ngm:resilience ;
vc:uses ngm:gossip-protocol ;
vc:uses ngm:overlay-network .
ngm:decentralised-networks a skos:Concept ;
rdfs:label "Decentralised Networks"@en .
ngm:decentralised-oracle a skos:Concept ;
rdfs:label "Decentralised Oracle"@en .
ngm:decentralised-processing a skos:Concept ;
rdfs:label "Decentralised Processing"@en .
ngm:decentralised-resolution a skos:Concept ;
rdfs:label "Decentralised Resolution"@en .
ngm:decentralised-science a skos:Concept ;
rdfs:label "Decentralised Science"@en .
ngm:decentralised-social-media a skos:Concept ;
rdfs:label "Decentralised Social Media"@en .
ngm:decentralised-social-protocol a skos:Concept ;
rdfs:label "Decentralised Social Protocol"@en .
ngm:decentralised-storage a owl:Class ;
rdfs:comment "Storage systems that distribute data across many independent nodes rather than a single central provider, using content addressing and cryptographic verification to ensure data integrity, availability, and censorship resistance without a trusted intermediary."@en ;
rdfs:label "Decentralised Storage"@en ;
rdfs:subClassOf ngm:distributed-systems ;
rdfs:subClassOf _:r7300 ;
rdfs:subClassOf _:r7301 ;
rdfs:subClassOf _:r7302 ;
rdfs:subClassOf _:r7303 ;
rdfs:subClassOf _:r7304 ;
vc:bridgesTo ngm:filecoin ;
vc:bridgesTo ngm:ipfs ;
vc:bridgesTo ngm:smart-contract ;
vc:bridgesTo ngm:spatial-computing ;
vc:contrastsWith ngm:cloud-storage ;
vc:dependsOn ngm:blockchain ;
vc:dependsOn ngm:consensus-mechanism ;
vc:enables ngm:censorship-resistance ;
vc:enables ngm:data-sovereignty ;
vc:enables ngm:provenance ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:content-addressing ;
vc:hasPart ngm:data-replication ;
vc:hasPart ngm:peer-to-peer-network ;
vc:implements ngm:arweave ;
vc:implements ngm:filecoin ;
vc:implements ngm:ipfs ;
vc:isPartOf ngm:web-3-infrastructure ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:data-availability ;
vc:relatedTo ngm:encryption ;
vc:requires ngm:cryptographic-hash ;
vc:requires ngm:distributed-hash-table ;
vc:slug "decentralised-storage" ;
vc:sourceDomain "distributed-systems" ;
vc:supports ngm:decentralised-application ;
vc:supports ngm:non-fungible-token ;
vc:uses ngm:erasure-coding ;
vc:uses ngm:merkle-dag .
ngm:decentralised-trust a owl:Class ;
rdfs:comment "Decentralised trust is an architectural property of a system in which confidence in the correctness of data, identity claims, or transaction outcomes is derived from cryptographic proofs, distributed consensus, and transparent protocol rules rather than from reliance on any single central authority or intermediary. Rather than placing faith in a bank, government registry, or certificate authority, participants in a decentralised trust model verify claims independently using public-key cryptography, Merkle proofs, or zero-knowledge proofs enforced by a distributed network. The result is a system where trust is a computable property of the protocol rather than a social or legal delegation to an institution."@en ;
rdfs:label "Decentralised Trust"@en ;
rdfs:subClassOf ngm:trust ;
rdfs:subClassOf _:r7305 ;
rdfs:subClassOf _:r7306 ;
vc:bridgesTo ngm:digital-governance ;
vc:bridgesTo ngm:supply-chain-provenance ;
vc:contrastsWith ngm:certificate-authority ;
vc:contrastsWith ngm:cryptographic-infrastructure ;
vc:dependsOn ngm:hash-function ;
vc:dependsOn ngm:peer-to-peer-network ;
vc:enables ngm:de-fi ;
vc:enables ngm:decentralised-identity ;
vc:enables ngm:permissionless-participation ;
vc:enables ngm:self-sovereign-identity ;
vc:enables ngm:trustless-settlement ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:blockchain ;
vc:relatedTo ngm:decentralisation ;
vc:relatedTo ngm:oracle-problem ;
vc:relatedTo ngm:web-of-trust ;
vc:requires ngm:byzantine-fault-tolerance ;
vc:requires ngm:distributed-ledger ;
vc:slug "decentralised-trust" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:cryptographic-proof ;
vc:uses ngm:cryptographic-verification ;
vc:uses ngm:digital-signature ;
vc:uses ngm:distributed-consensus ;
vc:uses ngm:merkle-proof ;
vc:uses ngm:public-key-cryptography ;
vc:uses ngm:trust-anchor ;
vc:uses ngm:zero-knowledge-proof .
ngm:decentralised-verifier-network a skos:Concept ;
rdfs:label "Decentralised Verifier Network"@en .
ngm:decentralised-web a owl:Class ;
rdfs:comment "Decentralised Web (dWeb) is the architectural counter-movement to platform-consolidated Web 2.0, comprising the family of protocols, data models, identity primitives and economic mechanisms that re-establish the original distributed character of the internet by replacing location-addressed client..."@en ;
rdfs:label "Decentralised Web"@en ;
rdfs:subClassOf ngm:distributed-system ;
rdfs:subClassOf ngm:infra-network-and-comms ;
rdfs:subClassOf ngm:open-protocol ;
rdfs:subClassOf ngm:peer-to-peer-network ;
rdfs:subClassOf ngm:sociotechnical-system ;
rdfs:subClassOf ngm:web-architecture ;
rdfs:subClassOf _:r7307 ;
rdfs:subClassOf _:r7308 ;
rdfs:subClassOf _:r7309 ;
rdfs:subClassOf _:r7310 ;
rdfs:subClassOf _:r7311 ;
rdfs:subClassOf _:r7312 ;
rdfs:subClassOf _:r7313 ;
rdfs:subClassOf _:r7314 ;
rdfs:subClassOf _:r7315 ;
rdfs:subClassOf _:r7316 ;
rdfs:subClassOf _:r7317 ;
rdfs:subClassOf _:r7318 ;
rdfs:subClassOf _:r7319 ;
rdfs:subClassOf _:r7320 ;
rdfs:subClassOf _:r7321 ;
rdfs:subClassOf _:r7322 ;
rdfs:subClassOf _:r7323 ;
rdfs:subClassOf _:r7324 ;
rdfs:subClassOf _:r7325 ;
skos:broader ngm:infra-network-and-comms ;
vc:bridgesTo ngm:blockchain ;
vc:contrastsWith ngm:blockchain-only-web3 ;
vc:contrastsWith ngm:centralised-cloud ;
vc:contrastsWith ngm:federated-network ;
vc:contrastsWith ngm:software-as-a-service ;
vc:contrastsWith ngm:walled-garden ;
vc:contrastsWith ngm:web-2-0 ;
vc:dependsOn ngm:cryptography ;
vc:dependsOn ngm:distributed-systems-theory ;
vc:dependsOn ngm:hashing ;
vc:dependsOn ngm:information-theory ;
vc:dependsOn ngm:internet-protocol ;
vc:dependsOn ngm:networking ;
vc:dependsOn ngm:public-key-cryptography ;
vc:enables ngm:archive-permanence ;
vc:enables ngm:censorship-resistance ;
vc:enables ngm:data-portability ;
vc:enables ngm:disintermediation ;
vc:enables ngm:local-first-software ;
vc:enables ngm:permissionless-innovation ;
vc:enables ngm:trust-minimisation ;
vc:enables ngm:user-sovereignty ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:activity-pub ;
vc:hasPart ngm:arweave ;
vc:hasPart ngm:at-protocol ;
vc:hasPart ngm:ceramic ;
vc:hasPart ngm:ens ;
vc:hasPart ngm:farcaster ;
vc:hasPart ngm:filecoin ;
vc:hasPart ngm:hypercore-protocol ;
vc:hasPart ngm:ipfs ;
vc:hasPart ngm:ipld ;
vc:hasPart ngm:lens-protocol ;
vc:hasPart ngm:libp2p ;
vc:hasPart ngm:nostr-protocol ;
vc:hasPart ngm:orbitdb ;
vc:hasPart ngm:solid ;
vc:implements ngm:content-addressing ;
vc:implements ngm:crdt ;
vc:implements ngm:federation-protocol ;
vc:implements ngm:gossip-protocol ;
vc:implements ngm:kademlia-dht ;
vc:implements ngm:merkle-dag ;
vc:implements ngm:portability ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:agentic-internet ;
vc:relatedTo ngm:crypto-anarchism ;
vc:relatedTo ngm:cryptographic-privacy-activist ;
vc:relatedTo ngm:internet-of-agents ;
vc:relatedTo ngm:open-source-software ;
vc:relatedTo ngm:self-sovereign-identity ;
vc:relatedTo ngm:semantic-web-linked-data-standard ;
vc:relatedTo ngm:web3 ;
vc:requires ngm:content-addressing ;
vc:requires ngm:cryptographic-hash-function ;
vc:requires ngm:cryptographic-infrastructure ;
vc:requires ngm:cryptographic-signature ;
vc:requires ngm:distributed-hash-table ;
vc:requires ngm:peer-discovery ;
vc:requires ngm:self-sovereign-identity ;
vc:slug "decentralised-web" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:bluesky-pbc ;
vc:standardizedBy ngm:ietf ;
vc:standardizedBy ngm:internet-archive ;
vc:standardizedBy ngm:open-sats ;
vc:standardizedBy ngm:opensats ;
vc:standardizedBy ngm:protocol-labs ;
vc:standardizedBy ngm:trust-over-ip-foundation ;
vc:standardizedBy ngm:w3-c ;
vc:supports ngm:decentralised-social-media ;
vc:supports ngm:decentralised-storage ;
vc:supports ngm:decentralized-storage ;
vc:supports ngm:knowledge-graphs ;
vc:supports ngm:peer-to-peer-messaging ;
vc:supports ngm:permanent-archives ;
vc:supports ngm:self-sovereign-identity ;
vc:supports ngm:tokenised-economics ;
vc:uses ngm:bitcoin-proof-of-work-protocol-lightning-network ;
vc:uses ngm:cid ;
vc:uses ngm:ed25519 ;
vc:uses ngm:multihash ;
vc:uses ngm:quic ;
vc:uses ngm:schnorr-signature ;
vc:uses ngm:schnorr-signatures ;
vc:uses ngm:web-rtc ;
vc:uses ngm:web-socket .
ngm:decentralization a owl:Class ;
rdfs:comment "The architectural property of distributing control, data storage, and decision-making across many independent network participants rather than concentrating them in a single authority. In blockchain systems, decentralisation is achieved through open participation, distributed consensus, and cryptographic enforcement of rules, providing censorship resistance, fault tolerance, and permissionless access."@en ;
rdfs:label "Decentralization"@en ;
rdfs:subClassOf ngm:blockchain-entity ;
rdfs:subClassOf ngm:distributed-data-structure ;
rdfs:subClassOf ngm:network-component ;
rdfs:subClassOf _:r7340 ;
rdfs:subClassOf _:r7341 ;
vc:bridgesTo ngm:telecollaboration ;
vc:contrastsWith ngm:51-attack ;
vc:enables ngm:blockchain-governance ;
vc:enables ngm:de-fi ;
vc:enables ngm:decentralised-autonomous-organisation ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:blockchain-network ;
vc:relatedTo ngm:blockchain-scalability ;
vc:relatedTo ngm:decentralization-layer ;
vc:relatedTo ngm:decentralized-storage ;
vc:relatedTo ngm:longest-chain-rule ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:node ;
vc:slug "decentralization" ;
vc:sourceDomain "blockchain" .
ngm:decentralization-layer a owl:Class ;
rdfs:comment "Structural layer that distributes data and control across nodes to reduce central dependence and increase trust through P2P networking, blockchain, and distributed consensus mechanisms."@en ;
rdfs:label "Decentralization Layer"@en ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf _:r7333 ;
rdfs:subClassOf _:r7334 ;
rdfs:subClassOf _:r7335 ;
rdfs:subClassOf _:r7336 ;
rdfs:subClassOf _:r7337 ;
rdfs:subClassOf _:r7338 ;
rdfs:subClassOf _:r7339 ;
skos:broader ngm:sc-platform-and-environment ;
vc:bridgesTo ngm:blockchain ;
vc:enables ngm:censorship-resistance ;
vc:enables ngm:data-sovereignty ;
vc:enables ngm:fault-tolerance ;
vc:enables ngm:trust ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:blockchain ;
vc:hasPart ngm:consensus-protocol ;
vc:hasPart ngm:distributed-hash-table ;
vc:hasPart ngm:p2-p-network ;
vc:hasPart ngm:p2p-network ;
vc:isPartOf ngm:middleware-layer ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:cryptographic-primitive ;
vc:requires ngm:distributed-storage ;
vc:requires ngm:network-infrastructure ;
vc:slug "decentralization-layer" ;
vc:sourceDomain "spatial-computing" .
ngm:decentralized-ai a skos:Concept ;
rdfs:label "Decentralized AI"@en .
ngm:decentralized-application a owl:Class ;
rdfs:comment "A decentralized application (dApp) is a software application whose backend logic runs on a blockchain or peer-to-peer network rather than on centralised servers controlled by a single entity, ensuring that no single party can unilaterally modify, censor, or shut down the application. The on-chain components — typically smart contracts — enforce business logic and state transitions transparently, while user-facing frontends may remain conventional web or mobile interfaces that communicate with the blockchain via wallet connectors. dApps inherit the censorship resistance and trustlessness of their underlying blockchain while exposing usability challenges related to transaction costs, latency, and key management."@en ;
rdfs:label "Decentralized Application"@en ;
rdfs:subClassOf ngm:blockchain-application ;
rdfs:subClassOf _:r7342 ;
rdfs:subClassOf _:r7343 ;
rdfs:subClassOf _:r7344 ;
rdfs:subClassOf _:r7345 ;
rdfs:subClassOf _:r7346 ;
vc:bridgesTo ngm:distributed-systems ;
vc:bridgesTo ngm:peer-to-peer-network ;
vc:contrastsWith ngm:centralized-application ;
vc:dependsOn ngm:evm ;
vc:dependsOn ngm:ipfs ;
vc:dependsOn ngm:smart-contract-platform ;
vc:enables ngm:blockchain-governance ;
vc:enables ngm:dao ;
vc:enables ngm:decentralized-finance-de-fi ;
vc:enables ngm:non-fungible-token ;
vc:enables ngm:tokenized-asset ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:oracle ;
vc:hasPart ngm:smart-contract ;
vc:implements ngm:censorship-resistance ;
vc:implements ngm:trustless-execution ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:cross-chain-interoperability ;
vc:relatedTo ngm:de-fi ;
vc:relatedTo ngm:web3 ;
vc:requires ngm:blockchain-network ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:wallet ;
vc:slug "decentralized-application" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:account-abstraction ;
vc:uses ngm:blockchain ;
vc:uses ngm:layer-2-scaling .
ngm:decentralized-arbitration a skos:Concept ;
rdfs:label "Decentralized Arbitration"@en .
ngm:decentralized-authentication a owl:Class ;
rdfs:comment "Decentralised Authentication is an approach to verifying identity claims without relying on a single central authority or identity provider. It uses cryptographic credentials, decentralised identifiers and distributed trust mechanisms so that users control their own authentication material and prove claims directly to relying parties. The model reduces single points of failure, limits data centralisation and aligns with self-sovereign identity principles."@en ;
rdfs:label "Decentralized Authentication"@en ;
rdfs:subClassOf ngm:authentication ;
rdfs:subClassOf _:r7347 ;
rdfs:subClassOf _:r7348 ;
vc:bridgesTo ngm:zero-knowledge-proof ;
vc:contrastsWith ngm:oauth ;
vc:contrastsWith ngm:single-sign-on ;
vc:dependsOn ngm:blockchain ;
vc:dependsOn ngm:decentralized-identity ;
vc:enables ngm:decentralized-identity ;
vc:enables ngm:self-sovereign-identity ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:isPartOf ngm:authentication ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:digital-identity ;
vc:relatedTo ngm:identity-provider ;
vc:requires ngm:cryptography ;
vc:requires ngm:verifiable-credentials ;
vc:slug "decentralized-authentication" ;
vc:sourceDomain "security" ;
vc:supports ngm:biometric-authentication ;
vc:supports ngm:multi-factor-authentication ;
vc:uses ngm:digital-signature ;
vc:uses ngm:public-key-cryptography .
ngm:decentralized-autonomous-organization a owl:Class ;
rdfs:comment "An organisational entity operating through Smart Contracts, Distributed Governance, and community voting mechanisms without centralised authority or hierarchical control, enabling transparent resource allocation, democratic decision-making, and distributed treasury management at global scale."@en ;
rdfs:label "Decentralized Autonomous Organization"@en ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
rdfs:subClassOf _:r7349 ;
rdfs:subClassOf _:r7350 ;
rdfs:subClassOf _:r7351 ;
rdfs:subClassOf _:r7352 ;
rdfs:subClassOf _:r7353 ;
rdfs:subClassOf _:r7354 ;
rdfs:subClassOf _:r7355 ;
rdfs:subClassOf _:r7356 ;
skos:broader ngm:bc-governance-and-regulation ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:collective-intelligence ;
vc:contrastsWith ngm:traditional-corporation ;
vc:dependsOn ngm:de-fi ;
vc:dependsOn ngm:ethereum ;
vc:enables ngm:distributed-governance ;
vc:enables ngm:permissionless-participation ;
vc:enables ngm:trustless-coordination ;
vc:enables ngm:virtual-economy ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:multisig-wallet ;
vc:hasPart ngm:on-chain-voting ;
vc:hasPart ngm:proposal-system ;
vc:hasPart ngm:treasury-management ;
vc:implements ngm:decentralization ;
vc:qualityScore "0.68"^^xsd:float ;
vc:relatedTo ngm:token-economics ;
vc:relatedTo ngm:web3 ;
vc:requires ngm:blockchain-infrastructure ;
vc:requires ngm:governance-token ;
vc:requires ngm:smart-contracts ;
vc:requires ngm:wallet ;
vc:slug "decentralized-autonomous-organization" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:blockchain-governance ;
vc:uses ngm:consensus-mechanism ;
vc:uses ngm:quadratic-voting ;
vc:uses ngm:token-weighted-voting .
ngm:decentralized-computation a skos:Concept ;
rdfs:label "Decentralized Computation"@en .
ngm:decentralized-computing a skos:Concept ;
rdfs:label "Decentralized Computing"@en .
ngm:decentralized-consensus a skos:Concept ;
rdfs:label "Decentralized Consensus"@en .
ngm:decentralized-control a owl:Class ;
rdfs:comment "Decentralized control is a control paradigm in which decision-making authority is distributed across many independent agents or nodes rather than concentrated in a single central controller, with global behaviour emerging from local rules and limited peer-to-peer communication. It trades the predictability of centralised control for robustness to single-point failure, scalability to large numbers of agents, and resilience under communication or node loss. Decentralized control is applied both in political and organisational governance and, in engineering, in domains such as swarm robotics where large numbers of simple agents must coordinate without a central coordinator."@en ;
rdfs:label "Decentralized Control"@en ;
rdfs:subClassOf ngm:distributed-systems ;
vc:enables ngm:swarm-robotics ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.5"^^xsd:float ;
vc:slug "decentralized-control" ;
vc:sourceDomain "distributed-systems" .
ngm:decentralized-exchange a owl:Class ;
rdfs:comment "A Decentralized Exchange (DEX) is a peer-to-peer cryptoasset trading protocol implemented as a set of Smart Contract state machines on one or more public blockchains that enables non-custodial atomic swaps between digital assets without a centralised matching engine, custodial wallet, or oper..."@en ;
rdfs:label "Decentralized Exchange"@en ;
rdfs:subClassOf ngm:bc-defi-and-economics ;
rdfs:subClassOf ngm:blockchain-application ;
rdfs:subClassOf ngm:decentralised-finance-primitive ;
rdfs:subClassOf ngm:financial-protocol ;
rdfs:subClassOf ngm:marketplace ;
rdfs:subClassOf ngm:trading-venue ;
rdfs:subClassOf _:r7365 ;
rdfs:subClassOf _:r7366 ;
rdfs:subClassOf _:r7367 ;
rdfs:subClassOf _:r7368 ;
rdfs:subClassOf _:r7369 ;
rdfs:subClassOf _:r7370 ;
rdfs:subClassOf _:r7371 ;
rdfs:subClassOf _:r7372 ;
rdfs:subClassOf _:r7373 ;
rdfs:subClassOf _:r7374 ;
rdfs:subClassOf _:r7375 ;
rdfs:subClassOf _:r7376 ;
rdfs:subClassOf _:r7377 ;
rdfs:subClassOf _:r7378 ;
rdfs:subClassOf _:r7379 ;
skos:broader ngm:bc-defi-and-economics ;
vc:contrastsWith ngm:centralized-exchange ;
vc:contrastsWith ngm:dark-pool ;
vc:contrastsWith ngm:market-maker-brokerage ;
vc:contrastsWith ngm:over-the-counter-trading ;
vc:contrastsWith ngm:traditional-stock-exchange ;
vc:dependsOn ngm:block-producer ;
vc:dependsOn ngm:cosmos-sdk ;
vc:dependsOn ngm:erc-20-token-standard ;
vc:dependsOn ngm:ethereum-smart-contract-platform ;
vc:dependsOn ngm:evm ;
vc:dependsOn ngm:rollup ;
vc:dependsOn ngm:solana ;
vc:enables ngm:atomic-swap ;
vc:enables ngm:composable-finance ;
vc:enables ngm:financial-inclusion ;
vc:enables ngm:liquidity-provision ;
vc:enables ngm:long-tail-asset-listing ;
vc:enables ngm:permissionless-trading ;
vc:enables ngm:token-swapping ;
vc:enables ngm:yield-farming ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:automated-market-maker ;
vc:hasPart ngm:blockchain-oracle ;
vc:hasPart ngm:concentrated-liquidity ;
vc:hasPart ngm:fee-tier ;
vc:hasPart ngm:liquidity-pool ;
vc:hasPart ngm:liquidity-provider-token ;
vc:hasPart ngm:order-book ;
vc:hasPart ngm:pool-manager ;
vc:hasPart ngm:router-contract ;
vc:hasPart ngm:smart-contract ;
vc:implements ngm:batch-auction-matching ;
vc:implements ngm:coincidence-of-wants ;
vc:implements ngm:concentrated-liquidity ;
vc:implements ngm:constant-product-formula ;
vc:implements ngm:intent-based-execution ;
vc:implements ngm:native-asset-cross-chain-swap ;
vc:qualityScore "0.54"^^xsd:float ;
vc:relatedTo ngm:aggregator ;
vc:relatedTo ngm:flash-loan ;
vc:relatedTo ngm:impermanent-loss ;
vc:relatedTo ngm:liquidity-mining ;
vc:relatedTo ngm:maximal-extractable-value ;
vc:relatedTo ngm:stablecoin ;
vc:relatedTo ngm:vampire-attack ;
vc:relatedTo ngm:yield-farming ;
vc:requires ngm:block-production ;
vc:requires ngm:blockchain-consensus ;
vc:requires ngm:gas-fee-market ;
vc:requires ngm:self-custody ;
vc:requires ngm:smart-contract-platform ;
vc:requires ngm:token-standard ;
vc:slug "decentralized-exchange" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:bc-0482-eu-mica-regulation ;
vc:standardizedBy ngm:curve-stableswap-paper ;
vc:standardizedBy ngm:eip-1153-transient-storage ;
vc:standardizedBy ngm:erc-20-token-standard ;
vc:standardizedBy ngm:erc-2612-permit ;
vc:standardizedBy ngm:mi-ca-regulation ;
vc:standardizedBy ngm:uniswap-v2-whitepaper ;
vc:standardizedBy ngm:uniswap-v3-whitepaper ;
vc:supports ngm:asset-tokenisation ;
vc:supports ngm:composability ;
vc:supports ngm:crypto-aggregation ;
vc:supports ngm:de-fi ;
vc:supports ngm:self-custody ;
vc:supports ngm:token-economy ;
vc:uses ngm:constant-product-formula ;
vc:uses ngm:dutch-auction ;
vc:uses ngm:flash-accounting ;
vc:uses ngm:geometric-mean-invariant ;
vc:uses ngm:hooks-pattern ;
vc:uses ngm:stable-swap-invariant ;
vc:uses ngm:threshold-signature-scheme ;
vc:uses ngm:tick-based-liquidity .
ngm:decentralized-exchange-dex a owl:Class ;
rdfs:comment "Peer-to-peer marketplace enabling direct token swaps and digital asset trading through smart contracts without centralized intermediaries or custodial control."@en ;
rdfs:label "Decentralized Exchange (DEX)"@en ;
rdfs:subClassOf ngm:bc-defi-and-economics ;
rdfs:subClassOf ngm:smart-contract ;
rdfs:subClassOf _:r7357 ;
rdfs:subClassOf _:r7358 ;
rdfs:subClassOf _:r7359 ;
rdfs:subClassOf _:r7360 ;
rdfs:subClassOf _:r7361 ;
rdfs:subClassOf _:r7362 ;
rdfs:subClassOf _:r7363 ;
rdfs:subClassOf _:r7364 ;
skos:broader ngm:bc-defi-and-economics ;
vc:bridgesTo ngm:blockchain ;
vc:dependsOn ngm:blockchain-oracle ;
vc:dependsOn ngm:cryptographic-signature ;
vc:dependsOn ngm:smart-contract ;
vc:enables ngm:decentralized-trading ;
vc:enables ngm:liquidity-provision ;
vc:enables ngm:price-discovery ;
vc:enables ngm:token-swapping ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:automated-market-maker ;
vc:hasPart ngm:liquidity-pool ;
vc:hasPart ngm:price-oracle ;
vc:hasPart ngm:smart-contract ;
vc:hasPart ngm:trading-interface ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:blockchain ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:digital-wallet ;
vc:requires ngm:token-standard ;
vc:slug "decentralized-exchange-dex" ;
vc:sourceDomain "blockchain" .
ngm:decentralized-finance a owl:Class ;
rdfs:comment "Decentralized finance (DeFi) is an ecosystem of financial services built on public blockchains using smart contracts to provide lending, trading, derivatives and asset management without traditional intermediaries. Protocols are composable and permissionless, letting users transact directly from self-custodied wallets. DeFi introduces novel mechanisms such as automated market makers and liquidity pools, along with risks like impermanent loss and smart-contract exploits."@en ;
rdfs:label "Decentralized Finance"@en ;
rdfs:subClassOf ngm:bc-defi-and-economics ;
skos:broader ngm:bc-defi-and-economics ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:decentralized-governance ;
vc:relatedTo ngm:impermanent-loss ;
vc:slug "decentralized-finance" ;
vc:sourceDomain "blockchain" .
ngm:decentralized-finance-de-fi a owl:Class ;
rdfs:comment "Decentralized Finance (DeFi) is an open, permissionless financial ecosystem built on public blockchain networks—principally ereum but increasingly on Layer 2 Networks (Arbitrum, Optimism, Base) and rival Layer 1s (Solana, Avalanche, BNB Chain)—that replicates and extends traditional finan..."@en ;
rdfs:label "Decentralized Finance (DeFi)"@en ;
rdfs:subClassOf ngm:bc-defi-and-economics ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf ngm:cryptographic-protocols ;
rdfs:subClassOf ngm:financial-technology ;
rdfs:subClassOf ngm:smart-contracts ;
rdfs:subClassOf ngm:token-economy ;
rdfs:subClassOf _:r7380 ;
rdfs:subClassOf _:r7381 ;
rdfs:subClassOf _:r7382 ;
rdfs:subClassOf _:r7383 ;
rdfs:subClassOf _:r7384 ;
rdfs:subClassOf _:r7385 ;
rdfs:subClassOf _:r7386 ;
rdfs:subClassOf _:r7387 ;
rdfs:subClassOf _:r7388 ;
rdfs:subClassOf _:r7389 ;
rdfs:subClassOf _:r7390 ;
rdfs:subClassOf _:r7391 ;
rdfs:subClassOf _:r7392 ;
rdfs:subClassOf _:r7393 ;
rdfs:subClassOf _:r7394 ;
rdfs:subClassOf _:r7395 ;
rdfs:subClassOf _:r7396 ;
rdfs:subClassOf _:r7397 ;
rdfs:subClassOf _:r7398 ;
rdfs:subClassOf _:r7399 ;
rdfs:subClassOf _:r7400 ;
skos:broader ngm:bc-defi-and-economics ;
skos:broader ngm:blockchain ;
vc:bridgesTo ngm:cryptographic-protocol ;
vc:contrastsWith ngm:aml-kyc-compliance ;
vc:contrastsWith ngm:cefi ;
vc:contrastsWith ngm:central-bank ;
vc:contrastsWith ngm:traditional-banking ;
vc:contrastsWith ngm:traditional-finance ;
vc:dependsOn ngm:blockchain-oracle ;
vc:dependsOn ngm:cryptographic-proofs ;
vc:dependsOn ngm:ethereum-smart-contract-platform ;
vc:dependsOn ngm:gas-fee-mechanisms ;
vc:dependsOn ngm:layer-2-networks ;
vc:dependsOn ngm:token-standards-erc-20 ;
vc:enables ngm:atomic-composability ;
vc:enables ngm:on-chain-governance ;
vc:enables ngm:permissionless-lending ;
vc:enables ngm:programmable-money ;
vc:enables ngm:tokenised-real-world-assets ;
vc:enables ngm:trustless-trading ;
vc:enables ngm:yield-optimisation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:automated-market-maker ;
vc:hasPart ngm:decentralised-exchange ;
vc:hasPart ngm:decentralized-exchange ;
vc:hasPart ngm:flash-loan ;
vc:hasPart ngm:flash-loans ;
vc:hasPart ngm:governance-token ;
vc:hasPart ngm:lending-protocol ;
vc:hasPart ngm:liquidity-mining ;
vc:hasPart ngm:liquidity-pool ;
vc:hasPart ngm:mev ;
vc:hasPart ngm:oracle ;
vc:hasPart ngm:real-world-asset-tokenisation ;
vc:hasPart ngm:stablecoin ;
vc:hasPart ngm:yield-farming ;
vc:implements ngm:algorithmic-stablecoin ;
vc:implements ngm:automated-market-maker ;
vc:implements ngm:concentrated-liquidity ;
vc:implements ngm:flash-loan-arbitrage ;
vc:implements ngm:liquidity-mining ;
vc:implements ngm:overcollateralised-lending ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:asset-registry ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol-technical-overview ;
vc:relatedTo ngm:blockchain-network ;
vc:relatedTo ngm:btc-layer-3 ;
vc:relatedTo ngm:carbon-neutral-blockchain ;
vc:relatedTo ngm:cbdc-frameworks ;
vc:requires ngm:collateral ;
vc:requires ngm:cryptographic-oracle ;
vc:requires ngm:ethereum-smart-contract-platform ;
vc:requires ngm:gas-fee ;
vc:requires ngm:liquidity-provider ;
vc:requires ngm:public-blockchain ;
vc:requires ngm:smart-contracts ;
vc:slug "decentralized-finance-de-fi" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:bc-0482-eu-mica-regulation ;
vc:standardizedBy ngm:eip-1559 ;
vc:standardizedBy ngm:erc-20-token-standard ;
vc:standardizedBy ngm:fatf-guidance-on-virtual-assets ;
vc:standardizedBy ngm:iosco-defi-report-2023 ;
vc:supports ngm:asset-registry ;
vc:supports ngm:bitcoin-proof-of-work-protocol-as-money ;
vc:supports ngm:blockchain-as-a-service ;
vc:supports ngm:blockchain-interoperability ;
vc:supports ngm:carbon-credit-tracking ;
vc:supports ngm:cbdcs ;
vc:uses ngm:chainlink ;
vc:uses ngm:evm ;
vc:uses ngm:ipfs ;
vc:uses ngm:merkle-tree ;
vc:uses ngm:solidity ;
vc:uses ngm:zero-knowledge-proof .
ngm:decentralized-governance a owl:Class ;
rdfs:comment "Decentralized Governance is a class of collective decision-making systems in which authority, rule-setting, and enforcement mechanisms are distributed across a network of participants rather than concentrated in a single central actor, implemented through formal on-chain voting protocols (token-w..."@en ;
rdfs:label "Decentralized Governance"@en ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
rdfs:subClassOf ngm:collective-action ;
rdfs:subClassOf ngm:common-pool-resources ;
rdfs:subClassOf ngm:distributed-systems ;
rdfs:subClassOf ngm:governance ;
rdfs:subClassOf ngm:institutional-economics ;
rdfs:subClassOf _:r7401 ;
rdfs:subClassOf _:r7402 ;
rdfs:subClassOf _:r7403 ;
rdfs:subClassOf _:r7404 ;
rdfs:subClassOf _:r7405 ;
rdfs:subClassOf _:r7406 ;
rdfs:subClassOf _:r7407 ;
rdfs:subClassOf _:r7408 ;
rdfs:subClassOf _:r7409 ;
rdfs:subClassOf _:r7410 ;
rdfs:subClassOf _:r7411 ;
rdfs:subClassOf _:r7412 ;
rdfs:subClassOf _:r7413 ;
rdfs:subClassOf _:r7414 ;
rdfs:subClassOf _:r7415 ;
rdfs:subClassOf _:r7416 ;
skos:broader ngm:bc-governance-and-regulation ;
vc:contrastsWith ngm:benevolent-dictatorship ;
vc:contrastsWith ngm:centralised-governance ;
vc:contrastsWith ngm:corporate-governance ;
vc:contrastsWith ngm:delegated-proof-of-stake ;
vc:contrastsWith ngm:off-chain-governance ;
vc:dependsOn ngm:blockchain-consensus ;
vc:dependsOn ngm:cryptographic-signatures ;
vc:dependsOn ngm:ethereum-smart-contract-platform ;
vc:dependsOn ngm:mechanism-design ;
vc:dependsOn ngm:smart-contracts ;
vc:dependsOn ngm:token-standards ;
vc:enables ngm:community-ownership ;
vc:enables ngm:dao ;
vc:enables ngm:de-fi ;
vc:enables ngm:parameter-adjustment ;
vc:enables ngm:protocol-upgrades ;
vc:enables ngm:treasury-management ;
vc:enables ngm:trustless-coordination ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:collective-action ;
vc:hasPart ngm:common-pool-resources ;
vc:hasPart ngm:delegation-system ;
vc:hasPart ngm:governance-forum ;
vc:hasPart ngm:institutional-economics ;
vc:hasPart ngm:proposal-system ;
vc:hasPart ngm:quorum-threshold ;
vc:hasPart ngm:snapshot-voting ;
vc:hasPart ngm:timelock-contract ;
vc:hasPart ngm:token-distribution ;
vc:hasPart ngm:voting-mechanism ;
vc:implements ngm:conviction-voting ;
vc:implements ngm:futarchy ;
vc:implements ngm:holographic-consensus ;
vc:implements ngm:liquid-democracy ;
vc:implements ngm:optimistic-governance ;
vc:implements ngm:quadratic-voting ;
vc:implements ngm:token-weighted-voting ;
vc:qualityScore "0.54"^^xsd:float ;
vc:relatedTo ngm:common-pool-resources ;
vc:relatedTo ngm:compound ;
vc:relatedTo ngm:cosmos ;
vc:relatedTo ngm:maker-dao ;
vc:relatedTo ngm:mechanism-design ;
vc:relatedTo ngm:polycentric-governance ;
vc:relatedTo ngm:tezos ;
vc:relatedTo ngm:uniswap ;
vc:requires ngm:blockchain-network ;
vc:requires ngm:cryptographic-proofs ;
vc:requires ngm:identity-systems ;
vc:requires ngm:smart-contracts ;
vc:requires ngm:sybil-resistance ;
vc:requires ngm:token-economics ;
vc:slug "decentralized-governance" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:bip-process ;
vc:standardizedBy ngm:compound-governor-bravo ;
vc:standardizedBy ngm:cosmos-governance-module ;
vc:standardizedBy ngm:eip-process ;
vc:standardizedBy ngm:open-zeppelin-governor ;
vc:standardizedBy ngm:tally ;
vc:supports ngm:community-treasury ;
vc:supports ngm:de-fi-protocol ;
vc:supports ngm:defi-protocols ;
vc:supports ngm:gitcoin-grants ;
vc:supports ngm:open-source-governance ;
vc:supports ngm:protocol-decentralization ;
vc:supports ngm:public-goods-funding ;
vc:uses ngm:discourse-forums ;
vc:uses ngm:erc-20-tokens ;
vc:uses ngm:multisignature-wallets ;
vc:uses ngm:open-zeppelin-governor-contracts ;
vc:uses ngm:snapshot ;
vc:uses ngm:tally ;
vc:uses ngm:timelock ;
vc:uses ngm:timelocks .
ngm:decentralized-identifier a owl:Class ;
rdfs:comment "A Decentralised Identifier (DID) is a globally unique, persistent, cryptographically verifiable identifier that a subject creates and controls without reliance on any centralised registry, authority, or intermediary. Defined by the W3C DID Core specification, a DID is a URI of the form did:method:identifier that resolves to a DID Document containing public keys, authentication mechanisms, and service endpoints. DIDs enable self-sovereign identity by decoupling identifier ownership from third-party identity providers, allowing verifiable credential exchange and privacy-preserving authentication across heterogeneous systems."@en ;
rdfs:label "Decentralized Identifier"@en ;
rdfs:subClassOf ngm:digital-identity ;
rdfs:subClassOf _:r7417 ;
rdfs:subClassOf _:r7418 ;
rdfs:subClassOf _:r7419 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:distributed-ledger-technology ;
vc:bridgesTo ngm:smart-contract ;
vc:contrastsWith ngm:centralized-identity-provider ;
vc:contrastsWith ngm:oauth ;
vc:enables ngm:decentralized-authentication ;
vc:enables ngm:identity-management ;
vc:enables ngm:self-sovereign-identity ;
vc:enables ngm:verifiable-credential-vc ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:uri ;
vc:implements ngm:w3-c-did-core ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:access-control ;
vc:relatedTo ngm:cryptographic-infrastructure ;
vc:relatedTo ngm:verifiable-data-registry ;
vc:requires ngm:did-document ;
vc:requires ngm:did-resolution ;
vc:requires ngm:public-key-cryptography ;
vc:slug "decentralized-identifier" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:w3-c ;
vc:supports ngm:privacy-preserving-authentication ;
vc:supports ngm:zero-knowledge-proof ;
vc:uses ngm:cryptographic-key-pair ;
vc:uses ngm:did-method ;
vc:uses ngm:digital-signature .
ngm:decentralized-identifier-did a skos:Concept ;
rdfs:label "Decentralized Identifier DID"@en .
ngm:decentralized-identifiers a owl:Class ;
rdfs:comment "A W3C-standardised URI scheme (DID Core v1.0 Recommendation 19 July 2022, v1.1 Working Draft progressing through 2024-2025) defining globally unique cryptographically verifiable identifiers of the form did:: controlled directly by their subjects without dependency on c..."@en ;
rdfs:label "Decentralized Identifiers"@en ;
rdfs:subClassOf ngm:bc-token-and-asset ;
rdfs:subClassOf ngm:cryptographic-identifier ;
rdfs:subClassOf ngm:cryptographic-primitive ;
rdfs:subClassOf ngm:identifier ;
rdfs:subClassOf ngm:self-sovereign-identifier ;
rdfs:subClassOf ngm:uri-scheme ;
rdfs:subClassOf _:r7420 ;
rdfs:subClassOf _:r7421 ;
rdfs:subClassOf _:r7422 ;
rdfs:subClassOf _:r7423 ;
rdfs:subClassOf _:r7424 ;
rdfs:subClassOf _:r7425 ;
rdfs:subClassOf _:r7426 ;
rdfs:subClassOf _:r7427 ;
rdfs:subClassOf _:r7428 ;
rdfs:subClassOf _:r7429 ;
rdfs:subClassOf _:r7430 ;
rdfs:subClassOf _:r7431 ;
rdfs:subClassOf _:r7432 ;
skos:broader ngm:bc-token-and-asset ;
vc:bridgesTo ngm:infra-security-and-identity ;
vc:contrastsWith ngm:centralized-identity-provider ;
vc:contrastsWith ngm:keybase ;
vc:contrastsWith ngm:oauth-2-0 ;
vc:contrastsWith ngm:open-id-connect ;
vc:contrastsWith ngm:saml-2-0 ;
vc:contrastsWith ngm:x-509-public-key-infrastructure ;
vc:dependsOn ngm:cryptographic-suites ;
vc:dependsOn ngm:json-ld-contexts ;
vc:dependsOn ngm:multibase-encoding ;
vc:dependsOn ngm:multicodec ;
vc:dependsOn ngm:verifiable-data-registry ;
vc:dependsOn ngm:w-3-c-did-core-1-0 ;
vc:enables ngm:pairwise-pseudonymous-identifiers ;
vc:enables ngm:passwordless-authentication ;
vc:enables ngm:portable-identity ;
vc:enables ngm:selective-disclosure ;
vc:enables ngm:self-sovereign-identity ;
vc:enables ngm:verifiable-credentials ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:did-controller ;
vc:hasPart ngm:did-document ;
vc:hasPart ngm:did-method ;
vc:hasPart ngm:did-resolver ;
vc:hasPart ngm:did-url ;
vc:hasPart ngm:service-endpoint ;
vc:hasPart ngm:verifiable-data-registry ;
vc:hasPart ngm:verification-method ;
vc:implements ngm:did-cheqd ;
vc:implements ngm:did-ethr ;
vc:implements ngm:did-indy ;
vc:implements ngm:did-ion ;
vc:implements ngm:did-jwk ;
vc:implements ngm:did-key ;
vc:implements ngm:did-peer ;
vc:implements ngm:did-plc ;
vc:implements ngm:did-web ;
vc:implements ngm:did-webvh ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:decentralized-identity-foundation ;
vc:relatedTo ngm:digital-identity-wallet ;
vc:relatedTo ngm:ens ;
vc:relatedTo ngm:hyperledger-indy ;
vc:relatedTo ngm:self-sovereign-identity ;
vc:relatedTo ngm:soulbound-tokens ;
vc:relatedTo ngm:sovrin-network ;
vc:relatedTo ngm:trust-over-ip-foundation ;
vc:relatedTo ngm:verifiable-credentials ;
vc:requires ngm:did-resolution ;
vc:requires ngm:json-ld ;
vc:requires ngm:key-management-system ;
vc:requires ngm:public-key-cryptography ;
vc:requires ngm:verifiable-data-registry ;
vc:slug "decentralized-identifiers" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:decentralized-identity-foundation ;
vc:standardizedBy ngm:european-commission ;
vc:standardizedBy ngm:ietf ;
vc:standardizedBy ngm:iso-iec-jtc-1-sc-27 ;
vc:standardizedBy ngm:open-id-foundation ;
vc:standardizedBy ngm:trust-over-ip-foundation ;
vc:standardizedBy ngm:w-3-c-did-working-group ;
vc:standardizedBy ngm:w3-c-verifiable-credentials ;
vc:supports ngm:anon-creds ;
vc:supports ngm:didcomm-v2 ;
vc:supports ngm:digital-identity-wallet ;
vc:supports ngm:ebsi ;
vc:supports ngm:gov-uk-one-login ;
vc:supports ngm:open-id4-vc ;
vc:supports ngm:trust-over-ip-stack ;
vc:uses ngm:bbs-signatures ;
vc:uses ngm:content-addressed-storage ;
vc:uses ngm:ed25519 ;
vc:uses ngm:merkle-logs ;
vc:uses ngm:multihash ;
vc:uses ngm:secp256k1 .
ngm:decentralized-identity a owl:Class ;
rdfs:comment "Decentralized Identity is an approach to digital identity management in which individuals, organisations, and devices hold cryptographic control over their own identifiers and credentials without dependence on any centralised identity provider. Built upon the W3C Decentralized Identifiers (DID) v1.0 Recommendation and the W3C Verifiable Credentials Data Model, it establishes a tripartite trust triangle of issuers, holders, and verifiers where credential authenticity is established through public-key cryptography anchored to a verifiable data registry — such as a distributed ledger or DNS — rather than through a privileged intermediary. This architecture realises self-sovereign identity principles: the subject generates and controls their key material, selectively discloses attributes using mechanisms such as BBS+ signatures or SD-JWT, and satisfies verifiers without exposing credentials to central surveillance or requiring real-time queries to the issuer."@en ;
rdfs:label "Decentralized Identity"@en ;
rdfs:subClassOf ngm:digital-identity ;
rdfs:subClassOf _:r7445 ;
rdfs:subClassOf _:r7446 ;
rdfs:subClassOf _:r7447 ;
rdfs:subClassOf _:r7448 ;
rdfs:subClassOf _:r7449 ;
rdfs:subClassOf _:r7450 ;
rdfs:subClassOf _:r7451 ;
rdfs:subClassOf _:r7452 ;
vc:bridgesTo ngm:iot-device-authentication ;
vc:bridgesTo ngm:smart-contract ;
vc:bridgesTo ngm:web3 ;
vc:contrastsWith ngm:centralized-identity-provider ;
vc:contrastsWith ngm:federated-identity ;
vc:contrastsWith ngm:oauth ;
vc:enables ngm:cross-border-authentication ;
vc:enables ngm:privacy-by-design ;
vc:enables ngm:selective-disclosure ;
vc:enables ngm:self-sovereign-identity ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:credential-verification ;
vc:hasPart ngm:did-document ;
vc:hasPart ngm:didcomm ;
vc:hasPart ngm:digital-identity-wallet ;
vc:hasPart ngm:verifiable-credential-vc ;
vc:implements ngm:w-3-c-verifiable-credentials-data-model ;
vc:implements ngm:w3-c-did-specification ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:access-control ;
vc:relatedTo ngm:data-sovereignty ;
vc:relatedTo ngm:trust-framework ;
vc:requires ngm:cryptographic-signature ;
vc:requires ngm:verifiable-data-registry ;
vc:slug "decentralized-identity" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:decentralized-identity-foundation ;
vc:standardizedBy ngm:open-id-foundation ;
vc:standardizedBy ngm:w3-c ;
vc:uses ngm:blockchain ;
vc:uses ngm:cryptographic-infrastructure ;
vc:uses ngm:cryptographic-keys ;
vc:uses ngm:distributed-ledger-technology ;
vc:uses ngm:zero-knowledge-proof .
ngm:decentralized-identity-did a owl:Class ;
rdfs:comment "A W3C standard for self-sovereign digital identities that are globally unique, cryptographically verifiable, and controlled by the identity subject without requiring centralized authorities."@en ;
rdfs:label "Decentralized Identity (DID)"@en ;
rdfs:subClassOf ngm:infra-security-and-identity ;
rdfs:subClassOf _:r7433 ;
rdfs:subClassOf _:r7434 ;
rdfs:subClassOf _:r7435 ;
rdfs:subClassOf _:r7436 ;
rdfs:subClassOf _:r7437 ;
rdfs:subClassOf _:r7438 ;
rdfs:subClassOf _:r7439 ;
skos:broader ngm:infra-security-and-identity ;
vc:bridgesTo ngm:did-nostr-identity ;
vc:dependsOn ngm:blockchain-technology ;
vc:dependsOn ngm:json-ld ;
vc:dependsOn ngm:w3-c-did-specification ;
vc:enables ngm:cross-domain-identity ;
vc:enables ngm:decentralized-authentication ;
vc:enables ngm:privacy-preserving-identity ;
vc:enables ngm:verifiable-credential-vc ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:did-document ;
vc:hasPart ngm:did-method ;
vc:hasPart ngm:did-resolver ;
vc:hasPart ngm:did-uri ;
vc:hasPart ngm:verifiable-data-registry ;
vc:isPartOf ngm:identity-management-system ;
vc:isPartOf ngm:self-sovereign-identity-ssi ;
vc:qualityScore "0.35"^^xsd:float ;
vc:requires ngm:cryptographic-infrastructure ;
vc:requires ngm:cryptographic-keys ;
vc:requires ngm:distributed-ledger ;
vc:slug "decentralized-identity-did" ;
vc:sourceDomain "infrastructure" .
ngm:decentralized-identity-foundation a owl:Class ;
rdfs:comment "The Decentralized Identity Foundation (DIF) is an open industry consortium founded in 2017 that develops interoperable specifications, protocols, and reference implementations for decentralised digital identity systems. It produces foundational work items including the Presentation Exchange specification, the Decentralized Web Node (DWN) protocol for identity-linked personal data storage, the DIDComm messaging protocol, and the Sidetree protocol family for scalable DID method implementations. DIF operates as a coordination layer complementing W3C standards bodies, bridging specification gaps between DID methods, verifiable credential formats, and identity wallet implementations. Its outputs are adopted in major identity frameworks including the European Union Digital Identity (EUDI) Wallet Architecture Reference Framework."@en ;
rdfs:label "Decentralized Identity Foundation"@en ;
rdfs:subClassOf ngm:standards-body ;
rdfs:subClassOf _:r7440 ;
rdfs:subClassOf _:r7441 ;
rdfs:subClassOf _:r7442 ;
rdfs:subClassOf _:r7443 ;
rdfs:subClassOf _:r7444 ;
vc:bridgesTo ngm:eudi-wallet ;
vc:bridgesTo ngm:identity-verification ;
vc:contrastsWith ngm:centralised-identity ;
vc:contrastsWith ngm:federated-identity ;
vc:enables ngm:decentralized-identifier ;
vc:enables ngm:did-document ;
vc:enables ngm:self-sovereign-identity ;
vc:enables ngm:verifiable-credentials ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:decentralized-web-node ;
vc:hasPart ngm:didcomm ;
vc:hasPart ngm:presentation-exchange ;
vc:hasPart ngm:sidetree-protocol ;
vc:implements ngm:w-3-c-verifiable-credentials-data-model ;
vc:implements ngm:w3-c-did-core ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:blockchain ;
vc:relatedTo ngm:trust-framework ;
vc:relatedTo ngm:zero-knowledge-proof ;
vc:requires ngm:cryptographic-infrastructure ;
vc:requires ngm:cryptographic-key-management ;
vc:slug "decentralized-identity-foundation" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:open-id-foundation ;
vc:standardizedBy ngm:world-wide-web-consortium ;
vc:supports ngm:digital-identity ;
vc:supports ngm:identity ;
vc:supports ngm:privacy-preserving-computation .
ngm:decentralized-key-storage a owl:Class ;
rdfs:comment "Decentralized key storage is the practice of distributing a cryptographic key across multiple independent holders or locations so that no single party ever possesses the whole key, and no single point of compromise or failure can expose or destroy it. Typically realised with Shamir secret sharing or threshold cryptography, the key is split into shares such that a defined quorum reconstructs or jointly uses it while any smaller subset reveals nothing. This is distinct from decentralised data storage — which spreads arbitrary files across a network such as IPFS — because the object being protected is the secret itself and the security goal is quorum-controlled reconstruction rather than content availability."@en ;
rdfs:label "Decentralized Key Storage"@en ;
rdfs:subClassOf ngm:key-management ;
rdfs:subClassOf _:r7453 ;
vc:contrastsWith ngm:decentralized-storage ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:requires ngm:cryptographic-key ;
vc:slug "decentralized-key-storage" ;
vc:sourceDomain "security" ;
vc:uses ngm:shamir-secret-sharing ;
vc:uses ngm:threshold-cryptography .
ngm:decentralized-ownership a skos:Concept ;
rdfs:label "Decentralized Ownership"@en .
ngm:decentralized-storage a owl:Class ;
rdfs:comment "A distributed storage infrastructure that distributes data across peer-to-peer networks rather than centralised data centres, enabling data persistence, redundancy, and access without single points of failure, often incentivised by cryptographic token mechanisms."@en ;
rdfs:label "Decentralized Storage"@en ;
rdfs:subClassOf ngm:data-management ;
rdfs:subClassOf _:r7454 ;
rdfs:subClassOf _:r7455 ;
rdfs:subClassOf _:r7456 ;
rdfs:subClassOf _:r7457 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:metaverse ;
vc:contrastsWith ngm:cloud-storage ;
vc:dependsOn ngm:content-addressing ;
vc:enables ngm:censorship-resistance ;
vc:enables ngm:content-distribution ;
vc:enables ngm:data-availability ;
vc:enables ngm:user-sovereignty ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:data-replication ;
vc:hasPart ngm:node ;
vc:implements ngm:arweave ;
vc:implements ngm:filecoin ;
vc:implements ngm:ipfs ;
vc:isPartOf ngm:peer-to-peer-network ;
vc:isPartOf ngm:web-3-infrastructure ;
vc:qualityScore "0.68"^^xsd:float ;
vc:relatedTo ngm:data-sovereignty ;
vc:relatedTo ngm:storj ;
vc:requires ngm:cryptographic-hash ;
vc:requires ngm:peer-to-peer-network ;
vc:slug "decentralized-storage" ;
vc:sourceDomain "distributed-systems" ;
vc:standardizedBy ngm:ieee ;
vc:supports ngm:nft-metadata ;
vc:supports ngm:persistent-storage ;
vc:uses ngm:blockchain ;
vc:uses ngm:content-addressing ;
vc:uses ngm:token .
ngm:decentralized-swarm-control a owl:Class ;
rdfs:comment "Decentralised swarm control distributes decision-making across all robot agents, where each robot computes commands based solely on local sensor information and direct communication with neighbouring agents."@en ;
rdfs:label "Decentralized Swarm Control"@en ;
rdfs:subClassOf ngm:robo-robot-type ;
rdfs:subClassOf ngm:robotics ;
rdfs:subClassOf ngm:swarm-control ;
rdfs:subClassOf ngm:swarm-robotics ;
rdfs:subClassOf _:r7458 ;
rdfs:subClassOf _:r7459 ;
rdfs:subClassOf _:r7460 ;
rdfs:subClassOf _:r7461 ;
skos:broader ngm:robo-robot-type ;
skos:broader ngm:robotics ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:biologically-inspired-robotics ;
vc:bridgesTo ngm:multi-agent-systems ;
vc:enables ngm:adaptive-behaviour ;
vc:enables ngm:emergent-task-performance ;
vc:enables ngm:fault-tolerance ;
vc:enables ngm:scalability ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:agent-autonomy ;
vc:hasPart ngm:emergent-behavior ;
vc:hasPart ngm:local-decision-logic ;
vc:hasPart ngm:neighbourhood-communication ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:asynchronous-coordination ;
vc:requires ngm:distributed-algorithm ;
vc:requires ngm:inter-agent-communication ;
vc:requires ngm:local-sensing ;
vc:slug "decentralized-swarm-control" ;
vc:sourceDomain "robotics" .
ngm:decentralized-trading a owl:Class ;
rdfs:comment "Decentralized trading is the exchange of crypto-assets directly between parties through smart contracts on a blockchain, without a centralized intermediary holding custody of funds or matching orders. Trades settle peer-to-contract against liquidity pools or order books governed by deterministic on-chain logic, giving traders self-custody and permissionless access. It is the activity layer enabled by decentralized exchanges and automated market makers."@en ;
rdfs:label "Decentralized Trading"@en ;
rdfs:subClassOf ngm:bc-defi-and-economics ;
skos:broader ngm:bc-defi-and-economics ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:automated-market-making ;
vc:relatedTo ngm:decentralized-exchange-dex ;
vc:slug "decentralized-trading" ;
vc:sourceDomain "blockchain" .
ngm:decentralized-web a skos:Concept ;
rdfs:label "Decentralized Web"@en .
ngm:decentralized-web-node a skos:Concept ;
rdfs:label "Decentralized Web Node"@en .
ngm:deceptive-alignment a skos:Concept ;
rdfs:label "Deceptive Alignment"@en .
ngm:decidability a skos:Concept ;
rdfs:label "Decidability"@en .
ngm:decidim-platform a skos:Concept ;
rdfs:label "Decidim Platform"@en .
ngm:decision-augmentation a skos:Concept ;
rdfs:label "Decision Augmentation"@en .
ngm:decision-automation a skos:Concept ;
rdfs:label "Decision Automation"@en .
ngm:decision-documentation a skos:Concept ;
rdfs:label "Decision Documentation"@en .
ngm:decision-engine a owl:Class ;
rdfs:comment "A decision engine is a software component that encapsulates decision logic—rules, models, policies, or heuristics—and evaluates inputs against that logic to produce actionable outputs such as approvals, classifications, recommendations, or routing choices. Decision engines decouple business logic from application code, enabling non-developers to modify decision policies without code deployments, and support auditability by providing traceable reasoning paths for each decision. They range from rule-based expert systems to ML model inference services to hybrid architectures combining both. The emergence of large language model reasoning cores has extended the decision engine concept to unstructured input spaces, enabling complex multi-step decisioning with natural language explanation traces."@en ;
rdfs:label "Decision Engine"@en ;
rdfs:subClassOf ngm:automated-reasoning ;
rdfs:subClassOf ngm:decision-intelligence ;
rdfs:subClassOf ngm:expert-systems ;
rdfs:subClassOf ngm:inference-engine ;
rdfs:subClassOf _:r7462 ;
rdfs:subClassOf _:r7463 ;
rdfs:subClassOf _:r7464 ;
rdfs:subClassOf _:r7465 ;
rdfs:subClassOf _:r7466 ;
rdfs:subClassOf _:r7467 ;
rdfs:subClassOf _:r7468 ;
rdfs:subClassOf _:r7469 ;
vc:contrastsWith ngm:automated-reasoning ;
vc:contrastsWith ngm:inference-engine ;
vc:contrastsWith ngm:policy-engine ;
vc:contrastsWith ngm:recommendation-engine ;
vc:dependsOn ngm:event-streaming ;
vc:dependsOn ngm:feature-store ;
vc:dependsOn ngm:human-in-the-loop ;
vc:dependsOn ngm:knowledge-graph ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:mlops ;
vc:dependsOn ngm:model-serving-runtime ;
vc:dependsOn ngm:policy-engine ;
vc:enables ngm:automated-decision-making ;
vc:enables ngm:automated-planning ;
vc:enables ngm:credit-scoring ;
vc:enables ngm:decision-support ;
vc:enables ngm:fraud-detection ;
vc:enables ngm:informed-decision-making ;
vc:enables ngm:risk-scoring ;
vc:enables ngm:workflow-automation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:audit-trail ;
vc:hasPart ngm:business-rules ;
vc:hasPart ngm:decision-model-notation ;
vc:hasPart ngm:explanation-module ;
vc:hasPart ngm:feature-engineering ;
vc:hasPart ngm:feature-engineering-pipeline ;
vc:hasPart ngm:model-scorer ;
vc:hasPart ngm:policy-engine ;
vc:hasPart ngm:rule-evaluator ;
vc:implements ngm:decision-intelligence ;
vc:implements ngm:decision-transparency ;
vc:implements ngm:explainable-ai ;
vc:implements ngm:fairness ;
vc:implements ngm:model-governance ;
vc:implements ngm:regulation ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:adaptive-systems ;
vc:relatedTo ngm:automated-decision-making ;
vc:relatedTo ngm:causal-reasoning ;
vc:relatedTo ngm:decision-transparency ;
vc:relatedTo ngm:deep-learning ;
vc:relatedTo ngm:explainable-ai ;
vc:relatedTo ngm:fairness ;
vc:relatedTo ngm:model-monitoring ;
vc:relatedTo ngm:model-risk-management ;
vc:relatedTo ngm:neuro-symbolic-ai ;
vc:relatedTo ngm:orchestration ;
vc:relatedTo ngm:privacy ;
vc:relatedTo ngm:regulation ;
vc:relatedTo ngm:risk-scoring ;
vc:requires ngm:access-control ;
vc:requires ngm:automated-reasoning ;
vc:requires ngm:data-governance ;
vc:requires ngm:knowledge-representation ;
vc:requires ngm:model-risk-management ;
vc:requires ngm:probabilistic-reasoning ;
vc:slug "decision-engine" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:data-governance ;
vc:standardizedBy ngm:decision-model-notation ;
vc:standardizedBy ngm:first-order-logic ;
vc:standardizedBy ngm:formal-methods ;
vc:standardizedBy ngm:regulation ;
vc:supports ngm:agentic-ai ;
vc:supports ngm:causal-reasoning ;
vc:supports ngm:federated-learning ;
vc:supports ngm:model-calibration ;
vc:supports ngm:natural-language-processing ;
vc:supports ngm:orchestration ;
vc:supports ngm:recommendation-engine ;
vc:supports ngm:robustness ;
vc:uses ngm:api-gateway ;
vc:uses ngm:automated-reasoning ;
vc:uses ngm:bayesian-inference ;
vc:uses ngm:chain-of-thought ;
vc:uses ngm:constraint-satisfaction ;
vc:uses ngm:deep-learning ;
vc:uses ngm:first-order-logic ;
vc:uses ngm:formal-methods ;
vc:uses ngm:knowledge-representation ;
vc:uses ngm:large-language-models ;
vc:uses ngm:neuro-symbolic-ai ;
vc:uses ngm:policy-engine ;
vc:uses ngm:probabilistic-reasoning ;
vc:uses ngm:symbolic-ai .
ngm:decision-framework a skos:Concept ;
rdfs:label "Decision Framework"@en .
ngm:decision-intelligence a skos:Concept ;
rdfs:label "Decision Intelligence"@en .
ngm:decision-logging a skos:Concept ;
rdfs:label "Decision Logging"@en .
ngm:decision-logic a skos:Concept ;
rdfs:label "Decision Logic"@en .
ngm:decision-making a owl:Class ;
rdfs:comment "Decision making is the cognitive and computational process of selecting a course of action from a set of available alternatives by evaluating options against objectives, constraints, and uncertainty. It spans normative models of rational choice (expected utility, Bayesian reasoning), descriptive behavioural accounts that document systematic biases, and computational frameworks such as Markov Decision Processes and reinforcement learning that formalise sequential choice under uncertainty. In artificial intelligence, decision making underpins agent planning, autonomous systems, and large-scale optimisation, bridging probability theory, control theory, and game theory into operational policies."@en ;
rdfs:label "Decision Making"@en ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf ngm:cognitive-science ;
rdfs:subClassOf ngm:decision-theory ;
rdfs:subClassOf ngm:operations-research ;
rdfs:subClassOf _:r7470 ;
rdfs:subClassOf _:r7471 ;
rdfs:subClassOf _:r7472 ;
rdfs:subClassOf _:r7473 ;
rdfs:subClassOf _:r7474 ;
rdfs:subClassOf _:r7475 ;
rdfs:subClassOf _:r7476 ;
rdfs:subClassOf _:r7477 ;
rdfs:subClassOf _:r7478 ;
skos:broader ngm:ai-research-area ;
vc:bridgesTo ngm:risk-management ;
vc:bridgesTo ngm:supply-chain-management ;
vc:contrastsWith ngm:behavioural-economics ;
vc:contrastsWith ngm:bounded-rationality ;
vc:dependsOn ngm:decision-theory ;
vc:dependsOn ngm:game-theory ;
vc:dependsOn ngm:optimisation ;
vc:dependsOn ngm:probability-theory ;
vc:enables ngm:autonomous-agent ;
vc:enables ngm:governance ;
vc:enables ngm:planning ;
vc:enables ngm:policy-optimisation ;
vc:enables ngm:risk-assessment ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:bayesian-inference ;
vc:hasPart ngm:heuristics ;
vc:hasPart ngm:markov-decision-process ;
vc:hasPart ngm:multi-criteria-decision-analysis ;
vc:hasPart ngm:utility-theory ;
vc:hasPart ngm:value-function ;
vc:implements ngm:bayesian-inference ;
vc:implements ngm:decision-theory ;
vc:implements ngm:utility-theory ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:cognitive-science ;
vc:relatedTo ngm:control-theory ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:operations-research ;
vc:relatedTo ngm:spatial-computing ;
vc:relatedTo ngm:transformer-architecture ;
vc:requires ngm:knowledge-representation ;
vc:requires ngm:objective-function ;
vc:requires ngm:probability-theory ;
vc:requires ngm:uncertainty-quantification ;
vc:slug "decision-making" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:iso-31000 ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:ai-ethics ;
vc:supports ngm:ai-safety-research ;
vc:supports ngm:risk-assessment ;
vc:supports ngm:risk-management ;
vc:supports ngm:supply-chain-management ;
vc:uses ngm:deep-learning ;
vc:uses ngm:heuristics ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:neural-network ;
vc:uses ngm:reinforcement-learning .
ngm:decision-management a skos:Concept ;
rdfs:label "Decision Management"@en .
ngm:decision-market a skos:Concept ;
rdfs:label "Decision Market"@en .
ngm:decision-model-notation a skos:Concept ;
rdfs:label "Decision Model Notation"@en .
ngm:decision-path a skos:Concept ;
rdfs:label "Decision Path"@en .
ngm:decision-policy a skos:Concept ;
rdfs:label "Decision Policy"@en .
ngm:decision-recording-system a skos:Concept ;
rdfs:label "Decision Recording System"@en .
ngm:decision-rights a owl:Class ;
rdfs:comment "Decision rights are the formally allocated authorities that determine who may make, approve, or veto a given class of decisions within an organisation or governance system. They specify the mapping between roles or stakeholders and the scope of choices they control, forming the backbone of accountability. Clear decision rights reduce ambiguity, prevent conflicting actions, and enable auditable governance."@en ;
rdfs:label "Decision Rights"@en ;
rdfs:subClassOf ngm:governance ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:governance ;
vc:relatedTo ngm:governance-framework ;
vc:slug "decision-rights" ;
vc:sourceDomain "governance" .
ngm:decision-rules a skos:Concept ;
rdfs:label "Decision Rules"@en .
ngm:decision-science a skos:Concept ;
rdfs:label "Decision Science"@en .
ngm:decision-structure a skos:Concept ;
rdfs:label "Decision Structure"@en .
ngm:decision-support a owl:Class ;
rdfs:comment "Decision Support refers to the class of information systems, analytical frameworks, and AI-augmented tools designed to improve the quality, speed, and consistency of human or automated decision-making by surfacing relevant data, models, and recommendations at the point of choice. Modern decision support systems integrate structured data from enterprise systems with unstructured signals from documents, sensor streams, and language models to present synthesised options with associated confidence levels and risk profiles. They range from simple rule-based dashboards to sophisticated agentic pipelines that autonomously gather evidence, run simulations, and present ranked courses of action. The field spans domains including clinical medicine, financial trading, military command, supply chain management, and public policy."@en ;
rdfs:label "Decision Support"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf _:r7479 ;
rdfs:subClassOf _:r7480 ;
rdfs:subClassOf _:r7481 ;
skos:broader ngm:ai-application ;
skos:broader ngm:artificial-intelligence ;
vc:bridgesTo ngm:financial-risk-management ;
vc:dependsOn ngm:inference ;
vc:dependsOn ngm:real-time-data-pipeline ;
vc:enables ngm:distributed-decision-making ;
vc:enables ngm:evidence-based-policy ;
vc:enables ngm:strategic-planning ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:recommendation-engine ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:clinical-decision-support ;
vc:relatedTo ngm:informed-decision-making ;
vc:relatedTo ngm:predictive-analytics ;
vc:relatedTo ngm:transparent-decision-making ;
vc:requires ngm:data-integration ;
vc:requires ngm:knowledge-representation ;
vc:slug "decision-support" ;
vc:sourceDomain "ai" ;
vc:supports ngm:bounded-rationality ;
vc:supports ngm:decision-transparency ;
vc:supports ngm:human-in-the-loop ;
vc:uses ngm:data-analytics ;
vc:uses ngm:explainable-ai ;
vc:uses ngm:large-language-models ;
vc:uses ngm:retrieval-augmented-generation .
ngm:decision-system a skos:Concept ;
rdfs:label "Decision System"@en .
ngm:decision-table a skos:Concept ;
rdfs:label "Decision Table"@en .
ngm:decision-theory a owl:Class ;
rdfs:comment "Decision theory is the formal study of how a rational agent should choose among actions whose outcomes are uncertain, combining probabilities over states of the world with utilities over outcomes to select actions that maximise expected utility. Its normative branch prescribes optimal choice under axioms of rationality, while its descriptive branch studies how agents actually decide. It provides the foundational framework for rational action in artificial intelligence, economics, and operations research."@en ;
rdfs:label "Decision Theory"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf ngm:decision-making ;
rdfs:subClassOf ngm:operations-research ;
rdfs:subClassOf ngm:probability-theory ;
rdfs:subClassOf _:r7482 ;
rdfs:subClassOf _:r7483 ;
rdfs:subClassOf _:r7484 ;
rdfs:subClassOf _:r7485 ;
rdfs:subClassOf _:r7486 ;
rdfs:subClassOf _:r7487 ;
rdfs:subClassOf _:r7488 ;
rdfs:subClassOf _:r7489 ;
skos:broader ngm:artificial-intelligence ;
vc:bridgesTo ngm:cognitive-science ;
vc:bridgesTo ngm:game-theory ;
vc:bridgesTo ngm:operations-research ;
vc:contrastsWith ngm:behavioural-economics ;
vc:contrastsWith ngm:bounded-rationality ;
vc:contrastsWith ngm:game-theory ;
vc:dependsOn ngm:optimisation ;
vc:dependsOn ngm:probability-theory ;
vc:dependsOn ngm:utility-theory ;
vc:enables ngm:decision-making ;
vc:enables ngm:markov-decision-process ;
vc:enables ngm:planning ;
vc:enables ngm:policy-optimisation ;
vc:enables ngm:rational-agent ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:bayesian-inference ;
vc:hasPart ngm:heuristics ;
vc:hasPart ngm:markov-decision-process ;
vc:hasPart ngm:utility-theory ;
vc:hasPart ngm:value-function ;
vc:implements ngm:bayesian-inference ;
vc:implements ngm:probability-theory ;
vc:implements ngm:utility-theory ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:autonomous-agent ;
vc:relatedTo ngm:bayesian-inference ;
vc:relatedTo ngm:cognitive-science ;
vc:relatedTo ngm:control-theory ;
vc:relatedTo ngm:knowledge-representation ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:operations-research ;
vc:requires ngm:objective-function ;
vc:requires ngm:probability-theory ;
vc:requires ngm:uncertainty-quantification ;
vc:slug "decision-theory" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:savage-expected-utility ;
vc:standardizedBy ngm:von-neumann-morgenstern-axioms ;
vc:supports ngm:ai-ethics ;
vc:supports ngm:ai-safety-research ;
vc:supports ngm:machine-learning-discipline ;
vc:supports ngm:reinforcement-learning ;
vc:supports ngm:risk-management ;
vc:uses ngm:bayesian-inference ;
vc:uses ngm:causal-reasoning ;
vc:uses ngm:heuristics .
ngm:decision-threshold a skos:Concept ;
rdfs:label "Decision Threshold"@en .
ngm:decision-traceability a skos:Concept ;
rdfs:label "Decision Traceability"@en .
ngm:decision-transparency a owl:Class ;
rdfs:comment "Decision transparency is the property of an AI system whereby the basis, logic, and contributing factors of its outputs are made accessible and comprehensible to relevant stakeholders. It requires that decision processes be traceable — from input data through model architecture to final output — and that explanations be appropriate to the audience, whether technical developers, domain experts, or affected individuals. Decision transparency is a foundational prerequisite for meaningful accountability, contestability, and regulatory compliance in AI deployments."@en ;
rdfs:label "Decision Transparency"@en ;
rdfs:subClassOf ngm:ai-ethics ;
rdfs:subClassOf ngm:ai-governance-and-ethics ;
rdfs:subClassOf ngm:responsible-ai ;
rdfs:subClassOf _:r7490 ;
rdfs:subClassOf _:r7491 ;
rdfs:subClassOf _:r7492 ;
rdfs:subClassOf _:r7493 ;
rdfs:subClassOf _:r7494 ;
rdfs:subClassOf _:r7495 ;
rdfs:subClassOf _:r7496 ;
rdfs:subClassOf _:r7497 ;
skos:broader ngm:ai-governance-and-ethics ;
vc:contrastsWith ngm:black-box-ai ;
vc:contrastsWith ngm:deep-learning ;
vc:contrastsWith ngm:opaque-model ;
vc:dependsOn ngm:automated-decision-making ;
vc:dependsOn ngm:decision-tree ;
vc:dependsOn ngm:loss-function ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:neural-network ;
vc:dependsOn ngm:supervised-learning ;
vc:dependsOn ngm:training-data ;
vc:enables ngm:accountability ;
vc:enables ngm:ai-fairness ;
vc:enables ngm:ai-trustworthiness ;
vc:enables ngm:algorithmic-accountability ;
vc:enables ngm:contestability ;
vc:enables ngm:human-oversight ;
vc:enables ngm:regulatory-compliance ;
vc:enables ngm:responsible-ai ;
vc:enables ngm:stakeholder-engagement-in-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:ai-governance-framework ;
vc:implements ngm:algorithmic-accountability ;
vc:implements ngm:ethical-framework ;
vc:implements ngm:regulatory-compliance ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:ai-fairness ;
vc:relatedTo ngm:ai-model-card ;
vc:relatedTo ngm:algorithmic-bias ;
vc:relatedTo ngm:algorithmic-transparency-index ;
vc:relatedTo ngm:automated-decision-making ;
vc:relatedTo ngm:counterfactual-explanation ;
vc:relatedTo ngm:eu-ai-act-regulatory-instrument ;
vc:relatedTo ngm:gdpr ;
vc:relatedTo ngm:gradient-boosted-trees ;
vc:relatedTo ngm:knowledge-graph ;
vc:relatedTo ngm:model-interpretability ;
vc:relatedTo ngm:random-forest ;
vc:relatedTo ngm:responsible-ai ;
vc:relatedTo ngm:right-to-explanation ;
vc:relatedTo ngm:sentiment-analysis ;
vc:relatedTo ngm:stakeholder-engagement-in-ai ;
vc:requires ngm:audit-trail ;
vc:requires ngm:explainable-ai ;
vc:requires ngm:feature-importance ;
vc:requires ngm:interpretability ;
vc:requires ngm:lime ;
vc:requires ngm:model-interpretability ;
vc:requires ngm:post-hoc-explanation ;
vc:requires ngm:shap ;
vc:slug "decision-transparency" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:gdpr ;
vc:standardizedBy ngm:ieee-p2976-xai ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:supports ngm:ai-governance ;
vc:supports ngm:ai-model-card ;
vc:supports ngm:algorithmic-transparency-index ;
vc:supports ngm:data-governance ;
vc:supports ngm:knowledge-graph ;
vc:supports ngm:regulatory-compliance ;
vc:supports ngm:responsible-ai ;
vc:supports ngm:risk-management ;
vc:supports ngm:stakeholder-engagement-in-ai ;
vc:uses ngm:ai-model-card ;
vc:uses ngm:algorithmic-transparency-index ;
vc:uses ngm:confusion-matrix ;
vc:uses ngm:counterfactual-explanation ;
vc:uses ngm:decision-tree ;
vc:uses ngm:feature-importance ;
vc:uses ngm:lime ;
vc:uses ngm:model-evaluation ;
vc:uses ngm:shap .
ngm:decision-tree a owl:Class ;
rdfs:comment "A decision tree is a supervised learning model that predicts an outcome by recursively partitioning the feature space into regions, represented as a tree of decision nodes and leaf nodes. Each internal node tests a feature against a threshold and routes an instance down a branch, while leaves assign a class label or numeric value. Decision trees are valued for their interpretability and form the building blocks of ensemble methods such as random forests and gradient boosting."@en ;
rdfs:label "Decision Tree"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:explainable-ai ;
rdfs:subClassOf ngm:interpretable-model ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf ngm:supervised-learning ;
rdfs:subClassOf _:r7498 ;
rdfs:subClassOf _:r7499 ;
rdfs:subClassOf _:r7500 ;
rdfs:subClassOf _:r7501 ;
rdfs:subClassOf _:r7502 ;
rdfs:subClassOf _:r7503 ;
rdfs:subClassOf _:r7504 ;
rdfs:subClassOf _:r7505 ;
rdfs:subClassOf _:r7506 ;
rdfs:subClassOf _:r7507 ;
skos:broader ngm:ai-technique ;
vc:contrastsWith ngm:deep-learning ;
vc:contrastsWith ngm:k-nearest-neighbours ;
vc:contrastsWith ngm:logistic-regression ;
vc:contrastsWith ngm:naive-bayes ;
vc:contrastsWith ngm:neural-network ;
vc:contrastsWith ngm:support-vector-machine ;
vc:dependsOn ngm:bias-variance-tradeoff ;
vc:dependsOn ngm:gini-coefficient ;
vc:dependsOn ngm:information-gain ;
vc:dependsOn ngm:supervised-learning ;
vc:dependsOn ngm:training-data ;
vc:enables ngm:anomaly-detection ;
vc:enables ngm:decision-transparency ;
vc:enables ngm:ensemble-methods ;
vc:enables ngm:explainable-ai ;
vc:enables ngm:feature-importance ;
vc:enables ngm:gradient-boosted-trees ;
vc:enables ngm:interpretability ;
vc:enables ngm:knowledge-graph ;
vc:enables ngm:random-forest ;
vc:enables ngm:responsible-ai ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:classification ;
vc:hasPart ngm:decision-path ;
vc:hasPart ngm:feature-importance ;
vc:hasPart ngm:gini-coefficient ;
vc:hasPart ngm:information-gain ;
vc:hasPart ngm:pruning ;
vc:hasPart ngm:regression ;
vc:implements ngm:classification ;
vc:implements ngm:interpretability ;
vc:implements ngm:recursive-partitioning ;
vc:implements ngm:regression ;
vc:isPartOf ngm:ensemble-methods ;
vc:isPartOf ngm:supervised-learning ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:ai-fairness ;
vc:relatedTo ngm:algorithmic-accountability ;
vc:relatedTo ngm:algorithmic-bias ;
vc:relatedTo ngm:bagging ;
vc:relatedTo ngm:bias-variance-tradeoff ;
vc:relatedTo ngm:boosting ;
vc:relatedTo ngm:counterfactual-explanation ;
vc:relatedTo ngm:data-science ;
vc:relatedTo ngm:ensemble-methods ;
vc:relatedTo ngm:feature-engineering ;
vc:relatedTo ngm:gradient-boosted-trees ;
vc:relatedTo ngm:hyperparameter-tuning ;
vc:relatedTo ngm:ieee-p2976-xai ;
vc:relatedTo ngm:iso-iec-42001 ;
vc:relatedTo ngm:knowledge-graph ;
vc:relatedTo ngm:overfitting ;
vc:relatedTo ngm:post-hoc-explanation ;
vc:relatedTo ngm:random-forest ;
vc:relatedTo ngm:sentiment-analysis ;
vc:relatedTo ngm:shap ;
vc:relatedTo ngm:text-classification ;
vc:requires ngm:cross-validation ;
vc:requires ngm:evaluation-metric ;
vc:requires ngm:feature-engineering ;
vc:requires ngm:labelled-dataset ;
vc:requires ngm:training-data ;
vc:slug "decision-tree" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:ieee-p2976-xai ;
vc:supports ngm:ai-fairness ;
vc:supports ngm:ai-governance ;
vc:supports ngm:algorithmic-accountability ;
vc:supports ngm:decision-transparency ;
vc:supports ngm:explainability ;
vc:supports ngm:explainable-ai ;
vc:supports ngm:interpretability ;
vc:supports ngm:regulatory-compliance ;
vc:supports ngm:responsible-ai ;
vc:uses ngm:confusion-matrix ;
vc:uses ngm:cross-validation ;
vc:uses ngm:feature-engineering ;
vc:uses ngm:gini-coefficient ;
vc:uses ngm:hyperparameter-tuning ;
vc:uses ngm:information-gain ;
vc:uses ngm:model-evaluation ;
vc:uses ngm:pruning ;
vc:uses ngm:shap .
ngm:decision-tree-approximation a skos:Concept ;
rdfs:label "Decision Tree Approximation"@en .
ngm:declaration-of-conformity a skos:Concept ;
rdfs:label "Declaration Of Conformity"@en .
ngm:declarative-memory a skos:Concept ;
rdfs:label "Declarative Memory"@en .
ngm:declarative-programming a skos:Concept ;
rdfs:label "Declarative Programming"@en .
ngm:declarative-query a skos:Concept ;
rdfs:label "Declarative Query"@en .
ngm:declination a owl:Class ;
rdfs:label "Declination"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:space-reference-systems ;
vc:slug "declination" ;
vc:sourceDomain "space-science-and-systems" .
ngm:decoder a owl:Class ;
rdfs:comment "The component in an encoder-decoder architecture that generates the output sequence autoregressively, using masked self-attention, cross-attention to encoder outputs, and feed-forward layers."@en ;
rdfs:label "Decoder"@en ;
rdfs:subClassOf ngm:ai-model-architecture ;
rdfs:subClassOf _:r7513 ;
rdfs:subClassOf _:r7514 ;
rdfs:subClassOf _:r7515 ;
rdfs:subClassOf _:r7516 ;
rdfs:subClassOf _:r7517 ;
skos:broader ngm:ai-model-architecture ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:time-series-forecasting ;
vc:contrastsWith ngm:encoder ;
vc:enables ngm:machine-translation ;
vc:enables ngm:text-generation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:layer-normalisation ;
vc:hasPart ngm:residual-connection ;
vc:hasPart ngm:self-attention ;
vc:isPartOf ngm:encoder-decoder-architecture ;
vc:isPartOf ngm:transformer ;
vc:qualityScore "0.68"^^xsd:float ;
vc:relatedTo ngm:causal-language-modelling ;
vc:relatedTo ngm:gpt ;
vc:relatedTo ngm:large-language-models ;
vc:relatedTo ngm:speculative-decoding ;
vc:requires ngm:embedding ;
vc:requires ngm:tokenization ;
vc:slug "decoder" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:attention-mechanism ;
vc:uses ngm:cross-attention ;
vc:uses ngm:feed-forward-network ;
vc:uses ngm:positional-encoding ;
vc:uses ngm:self-attention .
ngm:decoder-network a owl:Class ;
rdfs:comment "A decoder network is the component of an encoder-decoder architecture that maps a compact latent representation back to a target output such as a reconstructed input, an image or a sequence of tokens. It learns to invert the compression performed by the encoder, reconstructing high-dimensional structure from low-dimensional codes. Decoders are central to autoencoders, variational autoencoders, sequence-to-sequence models and generative systems."@en ;
rdfs:label "Decoder Network"@en ;
rdfs:subClassOf ngm:encoder-decoder-architecture ;
rdfs:subClassOf ngm:neural-network ;
rdfs:subClassOf _:r7508 ;
rdfs:subClassOf _:r7509 ;
rdfs:subClassOf _:r7510 ;
rdfs:subClassOf _:r7511 ;
rdfs:subClassOf _:r7512 ;
vc:contrastsWith ngm:encoder ;
vc:dependsOn ngm:backpropagation ;
vc:dependsOn ngm:latent-space ;
vc:dependsOn ngm:loss-function ;
vc:enables ngm:audio-synthesis ;
vc:enables ngm:drug-discovery ;
vc:enables ngm:generative-model ;
vc:enables ngm:image-generation ;
vc:enables ngm:image-segmentation ;
vc:enables ngm:machine-translation ;
vc:enables ngm:text-generation ;
vc:enables ngm:video-generation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:attention-mechanism ;
vc:hasPart ngm:loss-function ;
vc:hasPart ngm:skip-connection ;
vc:hasPart ngm:transposed-convolution ;
vc:hasPart ngm:upsampling ;
vc:implements ngm:deep-generative-model ;
vc:implements ngm:generative-model ;
vc:isPartOf ngm:autoencoder ;
vc:isPartOf ngm:encoder-decoder-architecture ;
vc:isPartOf ngm:sequence-to-sequence-model ;
vc:isPartOf ngm:vae ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:autoregressive-model ;
vc:relatedTo ngm:deep-learning ;
vc:relatedTo ngm:diffusion-model ;
vc:relatedTo ngm:foundation-model ;
vc:relatedTo ngm:generative-adversarial-network ;
vc:relatedTo ngm:large-language-model ;
vc:relatedTo ngm:normalising-flow ;
vc:relatedTo ngm:u-net ;
vc:requires ngm:backpropagation ;
vc:requires ngm:latent-space ;
vc:requires ngm:representation-learning ;
vc:slug "decoder-network" ;
vc:sourceDomain "machine-learning" ;
vc:supports ngm:autoregressive-model ;
vc:supports ngm:natural-language-processing ;
vc:supports ngm:vae ;
vc:uses ngm:convolutional-neural-network ;
vc:uses ngm:cross-attention ;
vc:uses ngm:kv-cache ;
vc:uses ngm:pixel-shuffle ;
vc:uses ngm:recurrent-neural-network ;
vc:uses ngm:transformer .
ngm:decoder-only-architecture a skos:Concept ;
rdfs:label "Decoder Only Architecture"@en .
ngm:decoder-stack a skos:Concept ;
rdfs:label "Decoder Stack"@en .
ngm:decoding-algorithm a skos:Concept ;
rdfs:label "Decoding Algorithm"@en .
ngm:decontamination-pipeline a skos:Concept ;
rdfs:label "Decontamination Pipeline"@en .
ngm:decorator-node a skos:Concept ;
rdfs:label "Decorator Node"@en .
ngm:decoy-outputs a skos:Concept ;
rdfs:label "Decoy Outputs"@en .
ngm:deductive-database a skos:Concept ;
rdfs:label "Deductive Database"@en .
ngm:deductive-database-semantics a skos:Concept ;
rdfs:label "Deductive Database Semantics"@en .
ngm:deduplication a owl:Class ;
rdfs:comment "Deduplication is a data-management technique that eliminates redundant copies of identical data by storing a single instance and referencing it wherever the same content recurs. Implementations typically hash data chunks and compare digests, so identical blocks resolve to the same stored object. It reduces storage footprint, backup windows, and network transfer in content-addressed and backup systems."@en ;
rdfs:label "Deduplication"@en ;
rdfs:subClassOf ngm:data-management ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:content-addressing ;
vc:relatedTo ngm:hash-function ;
vc:slug "deduplication" ;
vc:sourceDomain "data" .
ngm:deduplication-filter a skos:Concept ;
rdfs:label "Deduplication Filter"@en .
ngm:deep-dao a owl:Class ;
rdfs:comment "DeepDAO is a leading analytics and data aggregation platform dedicated to tracking and measuring the organisational health, financial activity, governance participation, and membership dynamics of decentralised autonomous organisations across multiple blockchain networks. It provides standardised metrics — total assets under management, number of token holders, proposal counts, voter participation rates, and delegate rankings — that enable comparative analysis of DAO ecosystems and inform investment, research, and governance design decisions."@en ;
rdfs:label "DeepDAO"@en ;
rdfs:subClassOf ngm:dao-analytics ;
vc:enables ngm:dao-governance ;
vc:enables ngm:decentralized-governance ;
vc:enables ngm:decision-transparency ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:dao ;
vc:relatedTo ngm:dao-tooling ;
vc:slug "deep-dao" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:blockchain-analytics ;
vc:uses ngm:governance-token ;
vc:uses ngm:on-chain-governance .
ngm:deep-ensembles a skos:Concept ;
rdfs:label "Deep Ensembles"@en .
ngm:deep-generative-model a owl:Class ;
rdfs:comment "A Deep Generative Model is a class of deep neural network trained to learn and approximate the underlying probability distribution of a dataset so that novel, statistically plausible samples can be drawn from it. The principal families — Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), normalising flows, and diffusion models — differ in how they parameterise and optimise the generative distribution, offering distinct trade-offs among sample fidelity, mode coverage, training stability, and latent-space interpretability. These models underpin modern generative AI capabilities across images, audio, video, text, and structured scientific data such as molecular graphs."@en ;
rdfs:label "Deep Generative Model"@en ;
rdfs:subClassOf ngm:deep-learning ;
rdfs:subClassOf ngm:generative-ai ;
rdfs:subClassOf _:r7518 ;
rdfs:subClassOf _:r7519 ;
rdfs:subClassOf _:r7520 ;
rdfs:subClassOf _:r7521 ;
rdfs:subClassOf _:r7522 ;
rdfs:subClassOf _:r7523 ;
rdfs:subClassOf _:r7524 ;
rdfs:subClassOf _:r7525 ;
rdfs:subClassOf _:r7526 ;
rdfs:subClassOf _:r7527 ;
rdfs:subClassOf _:r7528 ;
rdfs:subClassOf _:r7529 ;
vc:bridgesTo ngm:governance ;
vc:bridgesTo ngm:privacy-preserving-machine-learning ;
vc:bridgesTo ngm:synthetic-media ;
vc:contrastsWith ngm:classifier ;
vc:contrastsWith ngm:discriminative-model ;
vc:dependsOn ngm:backpropagation ;
vc:dependsOn ngm:latent-space ;
vc:dependsOn ngm:training-data ;
vc:enables ngm:audio-synthesis ;
vc:enables ngm:data-augmentation ;
vc:enables ngm:drug-discovery ;
vc:enables ngm:image-generation ;
vc:enables ngm:model-based-reinforcement-learning ;
vc:enables ngm:natural-language-generation ;
vc:enables ngm:synthetic-data ;
vc:enables ngm:text-to-image ;
vc:enables ngm:video-generation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:autoregressive-model ;
vc:hasPart ngm:diffusion-model ;
vc:hasPart ngm:flow-matching ;
vc:hasPart ngm:generative-adversarial-network ;
vc:hasPart ngm:latent-diffusion-model ;
vc:hasPart ngm:normalising-flow ;
vc:hasPart ngm:vae ;
vc:isPartOf ngm:deep-learning ;
vc:isPartOf ngm:generative-ai ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:consistency-distillation ;
vc:relatedTo ngm:density-estimation ;
vc:relatedTo ngm:flow-matching ;
vc:relatedTo ngm:foundation-model ;
vc:relatedTo ngm:large-language-model ;
vc:relatedTo ngm:representation-learning ;
vc:relatedTo ngm:score-matching ;
vc:relatedTo ngm:spatial-computing ;
vc:requires ngm:backpropagation ;
vc:requires ngm:latent-space ;
vc:requires ngm:neural-network ;
vc:requires ngm:neural-network-latent-space ;
vc:requires ngm:probabilistic-inference ;
vc:requires ngm:training-data ;
vc:slug "deep-generative-model" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:governance ;
vc:supports ngm:foundation-model ;
vc:supports ngm:large-language-model ;
vc:supports ngm:spatial-computing ;
vc:uses ngm:attention-mechanism ;
vc:uses ngm:backpropagation ;
vc:uses ngm:decoder-network ;
vc:uses ngm:encoder-decoder-architecture ;
vc:uses ngm:evidence-lower-bound ;
vc:uses ngm:reparameterisation-trick ;
vc:uses ngm:score-matching ;
vc:uses ngm:stochastic-gradient-descent ;
vc:uses ngm:vision-transformer .
ngm:deep-kernel-learning a skos:Concept ;
rdfs:label "Deep Kernel Learning"@en .
ngm:deep-knowledge-tracing a owl:Class ;
rdfs:comment "A machine-learning approach to modelling student knowledge, introduced by Piech et al. in 2015, that feeds a learner's full sequence of exercise interactions into a recurrent neural network which maintains a latent state of mastery and predicts the probability of answering the next item correctly, outperforming Bayesian Knowledge Tracing by learning inter-skill structure and forgetting dynamics directly from data at the cost of interpretability."@en ;
rdfs:label "Deep Knowledge Tracing"@en ;
rdfs:subClassOf ngm:machine-learning-discipline ;
vc:contrastsWith ngm:bayesian-knowledge-tracing ;
vc:enables ngm:adaptive-learning ;
vc:enables ngm:intelligent-tutoring-system ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:deep-learning ;
vc:relatedTo ngm:educational-technology ;
vc:slug "deep-knowledge-tracing" ;
vc:sourceDomain "machine-learning" ;
vc:uses ngm:lstm ;
vc:uses ngm:recurrent-neural-network .
ngm:deep-learning a owl:Class ;
rdfs:comment "Deep Learning is a subset of Machine Learning based on Artificial Neural Networks with multiple layers (depth) that learn hierarchical representations of data through Backpropagation and Gradient Descent."@en ;
rdfs:label "Deep Learning"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf _:r7540 ;
rdfs:subClassOf _:r7541 ;
rdfs:subClassOf _:r7542 ;
rdfs:subClassOf _:r7543 ;
rdfs:subClassOf _:r7544 ;
rdfs:subClassOf _:r7545 ;
rdfs:subClassOf _:r7546 ;
rdfs:subClassOf _:r7547 ;
rdfs:subClassOf _:r7548 ;
rdfs:subClassOf _:r7549 ;
rdfs:subClassOf _:r7550 ;
rdfs:subClassOf _:r7551 ;
rdfs:subClassOf _:r7552 ;
rdfs:subClassOf _:r7553 ;
skos:broader ngm:ai-technique ;
skos:broader ngm:artificial-intelligence ;
vc:bridgesTo ngm:blockchain-validation ;
vc:bridgesTo ngm:decentralized-ai ;
vc:bridgesTo ngm:lightning-network ;
vc:bridgesTo ngm:smart-contract ;
vc:contrastsWith ngm:shallow-machine-learning ;
vc:contrastsWith ngm:symbolic-ai ;
vc:dependsOn ngm:attention-mechanism ;
vc:dependsOn ngm:backpropagation ;
vc:dependsOn ngm:batch-normalisation ;
vc:dependsOn ngm:stochastic-gradient-descent ;
vc:enables ngm:computer-vision ;
vc:enables ngm:image-classification ;
vc:enables ngm:large-language-model ;
vc:enables ngm:natural-language-processing ;
vc:enables ngm:object-detection ;
vc:enables ngm:speech-recognition ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:activation-function ;
vc:hasPart ngm:backpropagation ;
vc:hasPart ngm:hidden-layer ;
vc:hasPart ngm:loss-function ;
vc:hasPart ngm:model-architecture ;
vc:hasPart ngm:neural-network ;
vc:hasPart ngm:optimiser ;
vc:implements ngm:reinforcement-learning ;
vc:implements ngm:self-supervised-learning ;
vc:implements ngm:supervised-learning ;
vc:implements ngm:transfer-learning ;
vc:implements ngm:unsupervised-learning ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:attention-mechanism ;
vc:relatedTo ngm:convolutional-neural-network ;
vc:relatedTo ngm:diffusion-model ;
vc:relatedTo ngm:federated-learning ;
vc:relatedTo ngm:generative-adversarial-network ;
vc:relatedTo ngm:large-language-model ;
vc:relatedTo ngm:recurrent-neural-network ;
vc:relatedTo ngm:transformer-architecture ;
vc:requires ngm:deep-learning-framework ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:gradient-descent ;
vc:requires ngm:hyperparameter-tuning ;
vc:requires ngm:model-architecture ;
vc:requires ngm:training-data ;
vc:slug "deep-learning" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:iso-iec-22989-2022 ;
vc:standardizedBy ngm:nist-ai-standards ;
vc:supports ngm:decentralized-ai ;
vc:supports ngm:federated-learning .
ngm:deep-learning-domain a skos:Concept ;
rdfs:label "Deep Learning Domain"@en .
ngm:deep-learning-framework a owl:Class ;
rdfs:comment "A software library that provides the building blocks for defining, training and deploying deep neural networks, including tensor operations, automatic differentiation and hardware acceleration."@en ;
rdfs:label "Deep Learning Framework"@en ;
rdfs:subClassOf ngm:deep-learning ;
rdfs:subClassOf ngm:deep-learning-domain ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf ngm:machine-learning-software ;
rdfs:subClassOf _:r7530 ;
rdfs:subClassOf _:r7531 ;
rdfs:subClassOf _:r7532 ;
rdfs:subClassOf _:r7533 ;
rdfs:subClassOf _:r7534 ;
rdfs:subClassOf _:r7535 ;
rdfs:subClassOf _:r7536 ;
rdfs:subClassOf _:r7537 ;
rdfs:subClassOf _:r7538 ;
rdfs:subClassOf _:r7539 ;
vc:bridgesTo ngm:edge-inference ;
vc:bridgesTo ngm:model-serving ;
vc:contrastsWith ngm:symbolic-ai ;
vc:dependsOn ngm:gpu-compute ;
vc:dependsOn ngm:gradient-descent ;
vc:enables ngm:backpropagation ;
vc:enables ngm:distributed-training ;
vc:enables ngm:large-language-model ;
vc:enables ngm:model-inference ;
vc:enables ngm:neural-network ;
vc:enables ngm:neural-network-training ;
vc:enables ngm:transfer-learning ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:activation-function ;
vc:hasPart ngm:automatic-differentiation ;
vc:hasPart ngm:computation-graph ;
vc:hasPart ngm:loss-function ;
vc:hasPart ngm:model-architecture ;
vc:hasPart ngm:optimiser ;
vc:hasPart ngm:tensor-operation ;
vc:implements ngm:convolutional-neural-network ;
vc:implements ngm:recurrent-neural-network ;
vc:implements ngm:stochastic-gradient-descent ;
vc:implements ngm:transformer ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:activation-function ;
vc:relatedTo ngm:backpropagation ;
vc:relatedTo ngm:jax ;
vc:relatedTo ngm:loss-function ;
vc:relatedTo ngm:mlx ;
vc:relatedTo ngm:py-torch ;
vc:relatedTo ngm:tensor-flow ;
vc:requires ngm:automatic-differentiation ;
vc:requires ngm:cuda ;
vc:requires ngm:hardware-acceleration ;
vc:requires ngm:python ;
vc:slug "deep-learning-framework" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:ieee ;
vc:supports ngm:distributed-training ;
vc:supports ngm:federated-learning ;
vc:supports ngm:mixed-precision-training ;
vc:uses ngm:computation-graph ;
vc:uses ngm:python .
ngm:deep-learning-pipeline a skos:Concept ;
rdfs:label "Deep Learning Pipeline"@en .
ngm:deep-linking a skos:Concept ;
rdfs:label "Deep Linking"@en .
ngm:deep-metric-learning a skos:Concept ;
rdfs:label "Deep Metric Learning"@en .
ngm:deep-mind a owl:Class ;
rdfs:comment "DeepMind is an artificial intelligence research laboratory owned by Google (Alphabet), headquartered in London, known for pioneering work in reinforcement learning, deep learning, and scientific AI applications including AlphaGo, AlphaFold, Gemini, and Gato."@en ;
rdfs:label "DeepMind"@en ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf _:r7588 ;
rdfs:subClassOf _:r7589 ;
rdfs:subClassOf _:r7590 ;
rdfs:subClassOf _:r7591 ;
rdfs:subClassOf _:r7592 ;
rdfs:subClassOf _:r7593 ;
rdfs:subClassOf _:r7594 ;
rdfs:subClassOf _:r7595 ;
rdfs:subClassOf _:r7596 ;
rdfs:subClassOf _:r7597 ;
skos:broader ngm:ai-research-area ;
skos:broader ngm:artificial-intelligence ;
vc:bridgesTo ngm:ai-energy-optimisation ;
vc:bridgesTo ngm:combinatorial-optimisation ;
vc:bridgesTo ngm:computational-biology ;
vc:bridgesTo ngm:materials-science-ai ;
vc:bridgesTo ngm:nuclear-fusion ;
vc:bridgesTo ngm:weather-prediction ;
vc:contrastsWith ngm:anthropic ;
vc:contrastsWith ngm:meta-ai ;
vc:contrastsWith ngm:microsoft ;
vc:contrastsWith ngm:openai-research-organisation ;
vc:dependsOn ngm:google-ai-technology-corporation ;
vc:dependsOn ngm:gpu-computing ;
vc:dependsOn ngm:large-scale-compute ;
vc:enables ngm:ai-energy-optimisation ;
vc:enables ngm:code-generation ;
vc:enables ngm:drug-discovery ;
vc:enables ngm:game-ai ;
vc:enables ngm:machine-learning-discipline ;
vc:enables ngm:mathematical-reasoning ;
vc:enables ngm:natural-language-processing ;
vc:enables ngm:protein-structure-prediction ;
vc:enables ngm:robotics-control ;
vc:enables ngm:scientific-discovery-acceleration ;
vc:enables ngm:scientific-research ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:alphacode ;
vc:hasPart ngm:alphadev ;
vc:hasPart ngm:alphaevolve ;
vc:hasPart ngm:alphafold ;
vc:hasPart ngm:alphageometry ;
vc:hasPart ngm:alphago ;
vc:hasPart ngm:alphaproof ;
vc:hasPart ngm:alphazero ;
vc:hasPart ngm:flamingo ;
vc:hasPart ngm:gato ;
vc:hasPart ngm:gemini-multimodal-language-model ;
vc:hasPart ngm:gemini-robotics ;
vc:hasPart ngm:graphcast ;
vc:hasPart ngm:sparrow ;
vc:implements ngm:monte-carlo-tree-search ;
vc:implements ngm:neural-network ;
vc:implements ngm:policy-gradient-methods ;
vc:implements ngm:reinforcement-learning-from-human-feedback ;
vc:implements ngm:self-supervised-learning ;
vc:implements ngm:transformer-architecture ;
vc:isPartOf ngm:ai-ecosystem ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:artificial-general-intelligence ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:convolutional-neural-network ;
vc:relatedTo ngm:deep-research ;
vc:relatedTo ngm:drug-discovery ;
vc:relatedTo ngm:foundation-model ;
vc:relatedTo ngm:mathematical-reasoning ;
vc:relatedTo ngm:multi-agent-system ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:protein-structure-prediction ;
vc:relatedTo ngm:reinforcement-learning-from-human-feedback ;
vc:relatedTo ngm:reward-signal ;
vc:relatedTo ngm:scaling-laws ;
vc:relatedTo ngm:self-supervised-learning ;
vc:requires ngm:deep-learning ;
vc:requires ngm:gpu-computing ;
vc:requires ngm:large-language-model ;
vc:requires ngm:large-scale-compute ;
vc:requires ngm:monte-carlo-tree-search ;
vc:requires ngm:neural-network ;
vc:requires ngm:reinforcement-learning ;
vc:requires ngm:transformer-architecture ;
vc:slug "deep-mind" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:uk-ai-opportunities-action-plan-jan-2025 ;
vc:supports ngm:ai-safety ;
vc:supports ngm:artificial-general-intelligence ;
vc:supports ngm:computational-biology ;
vc:supports ngm:materials-science-ai ;
vc:uses ngm:policy-gradient-methods ;
vc:uses ngm:scaling-laws ;
vc:uses ngm:self-supervised-learning ;
vc:uses ngm:value-function .
ngm:deep-neural-network a owl:Class ;
rdfs:comment "A deep neural network is an artificial neural network with multiple hidden layers between its input and output, enabling it to learn hierarchical representations of data. Each layer applies a learnable linear transformation followed by a non-linear activation, and the network is trained by gradient descent with backpropagation to minimise a loss function. Depth lets the model compose simple features into increasingly abstract ones, which underlies modern deep learning across vision, language, and audio."@en ;
rdfs:label "Deep Neural Network"@en ;
rdfs:subClassOf ngm:neural-network ;
rdfs:subClassOf _:r7554 ;
rdfs:subClassOf _:r7555 ;
vc:bridgesTo ngm:transformer ;
vc:contrastsWith ngm:feedforward-neural-network ;
vc:dependsOn ngm:supervised-learning ;
vc:dependsOn ngm:training-data ;
vc:enables ngm:representation-learning ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:activation-function ;
vc:implements ngm:feedforward-neural-network ;
vc:isPartOf ngm:deep-learning ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:convolutional-neural-network ;
vc:relatedTo ngm:embedding ;
vc:relatedTo ngm:overfitting ;
vc:relatedTo ngm:recurrent-neural-network ;
vc:requires ngm:training-data ;
vc:slug "deep-neural-network" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:activation-function ;
vc:uses ngm:backpropagation ;
vc:uses ngm:gradient-descent .
ngm:deep-packet-inspection a skos:Concept ;
rdfs:label "Deep Packet Inspection"@en .
ngm:deep-q-network a skos:Concept ;
rdfs:label "Deep Q Network"@en .
ngm:deep-reinforcement-learning a owl:Class ;
rdfs:comment "Deep Reinforcement Learning (DRL) is a machine learning paradigm that combines deep neural networks with reinforcement learning, enabling agents to learn optimal policies for sequential decision-making tasks by interacting with an environment, receiving scalar reward signals, and updating neural network parameters through gradient-based optimisation. Grounded in the Markov Decision Process framework, DRL applies the Bellman equation recursively to approximate value functions or directly optimise policies using methods such as DQN, PPO, SAC, and MuZero, achieving superhuman performance in games, robotics control, chip design, and language model alignment."@en ;
rdfs:label "Deep Reinforcement Learning"@en ;
rdfs:subClassOf ngm:artificial-intelligence ;
rdfs:subClassOf ngm:deep-learning ;
rdfs:subClassOf ngm:reinforcement-learning ;
rdfs:subClassOf _:r7556 ;
rdfs:subClassOf _:r7557 ;
rdfs:subClassOf _:r7558 ;
rdfs:subClassOf _:r7559 ;
rdfs:subClassOf _:r7560 ;
rdfs:subClassOf _:r7561 ;
rdfs:subClassOf _:r7562 ;
rdfs:subClassOf _:r7563 ;
rdfs:subClassOf _:r7564 ;
rdfs:subClassOf _:r7565 ;
rdfs:subClassOf _:r7566 ;
rdfs:subClassOf _:r7567 ;
skos:broader ngm:artificial-intelligence ;
vc:contrastsWith ngm:imitation-learning ;
vc:contrastsWith ngm:supervised-learning ;
vc:dependsOn ngm:backpropagation ;
vc:dependsOn ngm:bellman-equation ;
vc:dependsOn ngm:gpu-acceleration ;
vc:dependsOn ngm:markov-decision-process ;
vc:dependsOn ngm:simulation-environment ;
vc:enables ngm:agent ;
vc:enables ngm:agentic-ai ;
vc:enables ngm:model-based-reinforcement-learning ;
vc:enables ngm:multi-agent-reinforcement-learning ;
vc:enables ngm:offline-reinforcement-learning ;
vc:enables ngm:reinforcement-learning-from-human-feedback ;
vc:enables ngm:robotics ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:action-space ;
vc:hasPart ngm:bellman-equation ;
vc:hasPart ngm:environment-model ;
vc:hasPart ngm:experience-replay ;
vc:hasPart ngm:exploration-exploitation-tradeoff ;
vc:hasPart ngm:policy-gradient-methods ;
vc:hasPart ngm:reward-signal ;
vc:hasPart ngm:value-function ;
vc:implements ngm:bellman-equation ;
vc:implements ngm:policy-gradient-methods ;
vc:implements ngm:proximal-policy-optimisation ;
vc:implements ngm:q-learning ;
vc:implements ngm:temporal-difference-learning ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:diffusion-policy ;
vc:relatedTo ngm:exploration-exploitation-tradeoff ;
vc:relatedTo ngm:game-theory ;
vc:relatedTo ngm:large-language-model ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:model-based-reinforcement-learning ;
vc:relatedTo ngm:monte-carlo-tree-search ;
vc:relatedTo ngm:multi-agent-reinforcement-learning ;
vc:relatedTo ngm:offline-reinforcement-learning ;
vc:relatedTo ngm:temporal-difference-learning ;
vc:requires ngm:backpropagation ;
vc:requires ngm:experience-replay ;
vc:requires ngm:gpu-acceleration ;
vc:requires ngm:markov-decision-process ;
vc:requires ngm:neural-network ;
vc:requires ngm:simulation-environment ;
vc:slug "deep-reinforcement-learning" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:reinforcement-learning ;
vc:supports ngm:artificial-intelligence ;
vc:supports ngm:diffusion-policy ;
vc:supports ngm:large-language-model ;
vc:supports ngm:safe-ai ;
vc:uses ngm:action-space ;
vc:uses ngm:backpropagation ;
vc:uses ngm:bellman-equation ;
vc:uses ngm:convolutional-neural-network ;
vc:uses ngm:environment-model ;
vc:uses ngm:gpu-acceleration ;
vc:uses ngm:monte-carlo-tree-search ;
vc:uses ngm:neural-network ;
vc:uses ngm:policy-gradient-methods ;
vc:uses ngm:reward-signal ;
vc:uses ngm:value-function .
ngm:deep-research a owl:Class ;
rdfs:comment "Deep research is an agentic AI capability in which a language model autonomously plans and executes multi-step investigations, browsing the web, reading sources, and synthesising a cited report on a topic. The agent decomposes a query into sub-questions, iteratively gathers evidence across many pages, and reconciles findings rather than answering from parametric memory alone. It trades latency for depth, breadth of sources, and verifiable citations."@en ;
rdfs:label "Deep Research"@en ;
rdfs:subClassOf ngm:agentic-workflow ;
rdfs:subClassOf ngm:agents ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf _:r7568 ;
rdfs:subClassOf _:r7569 ;
rdfs:subClassOf _:r7570 ;
rdfs:subClassOf _:r7571 ;
rdfs:subClassOf _:r7572 ;
rdfs:subClassOf _:r7573 ;
rdfs:subClassOf _:r7574 ;
rdfs:subClassOf _:r7575 ;
rdfs:subClassOf _:r7576 ;
rdfs:subClassOf _:r7577 ;
rdfs:subClassOf _:r7578 ;
rdfs:subClassOf _:r7579 ;
rdfs:subClassOf _:r7580 ;
rdfs:subClassOf _:r7581 ;
rdfs:subClassOf _:r7582 ;
rdfs:subClassOf _:r7583 ;
rdfs:subClassOf _:r7584 ;
rdfs:subClassOf _:r7585 ;
rdfs:subClassOf _:r7586 ;
rdfs:subClassOf _:r7587 ;
skos:broader ngm:ai-application ;
vc:contrastsWith ngm:chatbot ;
vc:contrastsWith ngm:retrieval-augmented-generation ;
vc:contrastsWith ngm:static-inference-pipeline ;
vc:dependsOn ngm:embedding-search ;
vc:dependsOn ngm:foundation-model ;
vc:dependsOn ngm:retrieval-augmented-generation ;
vc:enables ngm:competitive-intelligence ;
vc:enables ngm:customer-service-automation ;
vc:enables ngm:drug-discovery ;
vc:enables ngm:due-diligence ;
vc:enables ngm:enterprise-workflow ;
vc:enables ngm:knowledge-graph ;
vc:enables ngm:literature-review-automation ;
vc:enables ngm:personal-assistance ;
vc:enables ngm:scientific-research ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:action-executor ;
vc:hasPart ngm:browser-automation ;
vc:hasPart ngm:chain-of-thought ;
vc:hasPart ngm:embedding-search ;
vc:hasPart ngm:observation-buffer ;
vc:hasPart ngm:planning-module ;
vc:hasPart ngm:reasoning-trace ;
vc:hasPart ngm:reflection-loop ;
vc:hasPart ngm:research-plan ;
vc:hasPart ngm:tool-use ;
vc:hasPart ngm:vector-database ;
vc:hasPart ngm:web-navigation ;
vc:hasPart ngm:web-scraping ;
vc:implements ngm:plan-and-execute ;
vc:implements ngm:re-act ;
vc:implements ngm:reflexion ;
vc:implements ngm:self-consistency ;
vc:implements ngm:tree-of-thoughts ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:agents ;
vc:relatedTo ngm:ai-safety ;
vc:relatedTo ngm:autonomous-task-execution ;
vc:relatedTo ngm:cognitive-architecture ;
vc:relatedTo ngm:computer-use-and-browser-agents ;
vc:relatedTo ngm:hallucination ;
vc:relatedTo ngm:human-oversight ;
vc:relatedTo ngm:multi-agent-orchestration ;
vc:relatedTo ngm:multi-agent-system ;
vc:relatedTo ngm:tool-augmented-llm ;
vc:requires ngm:browser-engine ;
vc:requires ngm:context-window ;
vc:requires ngm:foundation-model ;
vc:requires ngm:function-calling ;
vc:requires ngm:function-schemas ;
vc:requires ngm:inference-compute ;
vc:requires ngm:large-language-model ;
vc:requires ngm:model-context-protocol ;
vc:requires ngm:tool-definition ;
vc:requires ngm:web-scraping ;
vc:slug "deep-research" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:gaia-benchmark ;
vc:standardizedBy ngm:owasp-llm-top-10-2025 ;
vc:standardizedBy ngm:researchrubrics-benchmark ;
vc:supports ngm:ai-augmented-software-engineering ;
vc:supports ngm:knowledge-graph ;
vc:supports ngm:multi-agent-orchestration ;
vc:uses ngm:agent-memory ;
vc:uses ngm:agentic-workflow ;
vc:uses ngm:chain-of-thought ;
vc:uses ngm:function-calling-api ;
vc:uses ngm:function-schemas ;
vc:uses ngm:model-context-protocol ;
vc:uses ngm:reasoning-trace ;
vc:uses ngm:self-consistency ;
vc:uses ngm:vision-language-model .
ngm:deep-sdf a skos:Concept ;
rdfs:label "Deep Sdf"@en .
ngm:deep-sea-robotics a skos:Concept ;
rdfs:label "Deep Sea Robotics"@en .
ngm:deep-speed a owl:Class ;
rdfs:comment "DeepSpeed is an open-source deep learning optimisation library developed by Microsoft Research that enables training and inference of extremely large neural network models through ZeRO (Zero Redundancy Optimizer) memory partitioning, pipeline parallelism, and mixed-precision arithmetic. It reduces the per-device memory footprint of model states by partitioning optimiser states, gradients, and parameters across data-parallel devices."@en ;
rdfs:label "DeepSpeed"@en ;
rdfs:subClassOf ngm:distributed-ai-training ;
rdfs:subClassOf ngm:distributed-computing ;
rdfs:subClassOf ngm:distributed-training ;
rdfs:subClassOf ngm:high-performance-computing ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf _:r7598 ;
rdfs:subClassOf _:r7599 ;
rdfs:subClassOf _:r7600 ;
rdfs:subClassOf _:r7601 ;
rdfs:subClassOf _:r7602 ;
rdfs:subClassOf _:r7603 ;
rdfs:subClassOf _:r7604 ;
rdfs:subClassOf _:r7605 ;
rdfs:subClassOf _:r7606 ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:bridgesTo ngm:infrastructure ;
vc:contrastsWith ngm:fully-sharded-data-parallel ;
vc:contrastsWith ngm:horovod ;
vc:contrastsWith ngm:jax ;
vc:contrastsWith ngm:megatron-lm ;
vc:dependsOn ngm:distributed-computing ;
vc:dependsOn ngm:gpu-cluster ;
vc:dependsOn ngm:message-passing-interface ;
vc:dependsOn ngm:python-pytorch-deep-learning-stack ;
vc:enables ngm:distributed-ai-training ;
vc:enables ngm:distributed-inference ;
vc:enables ngm:high-performance-computing ;
vc:enables ngm:inference ;
vc:enables ngm:large-language-model ;
vc:enables ngm:large-language-model-training ;
vc:enables ngm:model-parallelism ;
vc:enables ngm:model-quantization ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:gradient-checkpointing ;
vc:hasPart ngm:mixed-precision-training ;
vc:hasPart ngm:model-quantization ;
vc:hasPart ngm:pipeline-parallelism ;
vc:hasPart ngm:sparse-attention ;
vc:hasPart ngm:tensor-parallelism ;
vc:hasPart ngm:zero-optimizer ;
vc:implements ngm:data-parallelism ;
vc:implements ngm:mixed-precision-training ;
vc:implements ngm:model-parallelism ;
vc:implements ngm:pipeline-parallelism ;
vc:implements ngm:tensor-parallelism ;
vc:qualityScore "0.73"^^xsd:float ;
vc:relatedTo ngm:backpropagation ;
vc:relatedTo ngm:data-parallelism ;
vc:relatedTo ngm:distributed-inference ;
vc:relatedTo ngm:gradient-descent ;
vc:relatedTo ngm:hugging-face-accelerate ;
vc:relatedTo ngm:large-language-model ;
vc:relatedTo ngm:model-compression ;
vc:relatedTo ngm:model-quantization ;
vc:relatedTo ngm:transformer-architecture ;
vc:requires ngm:cuda ;
vc:requires ngm:gpu-cluster ;
vc:requires ngm:high-performance-computing ;
vc:requires ngm:py-torch ;
vc:slug "deep-speed" ;
vc:sourceDomain "machine-learning" ;
vc:standardizedBy ngm:microsoft ;
vc:supports ngm:azure-machine-learning ;
vc:supports ngm:computer-vision ;
vc:supports ngm:hugging-face ;
vc:supports ngm:natural-language-processing ;
vc:supports ngm:reinforcement-learning ;
vc:uses ngm:cuda ;
vc:uses ngm:gpu-cluster ;
vc:uses ngm:gradient-checkpointing ;
vc:uses ngm:message-passing-interface ;
vc:uses ngm:mixed-precision-training ;
vc:uses ngm:py-torch ;
vc:uses ngm:transformer-architecture .
ngm:deep-think a owl:Class ;
rdfs:comment "An advanced AI model developed by Google, characterized by high performance on reasoning benchmarks and the inclusion of autonomous agents for complex tasks."@en ;
rdfs:label "Deep Think"@en ;
rdfs:subClassOf ngm:model ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:alethea-agent ;
vc:relatedTo ngm:arkg-i2-benchmark ;
vc:relatedTo ngm:model ;
vc:slug "deep-think" ;
vc:sourceDomain "artificial-intelligence" .
ngm:deep-work-protection a skos:Concept ;
rdfs:label "Deep Work Protection"@en .
ngm:deepep a skos:Concept ;
rdfs:label "Deepep"@en .
ngm:deepfacelab a skos:Concept ;
rdfs:label "Deepfacelab"@en .
ngm:deepfake-detection a owl:Class ;
rdfs:comment "Deepfake detection is the application of machine learning and signal processing techniques to identify synthetic or manipulated media—including face-swapped video, voice-cloned audio, and AI-generated images—by analysing artefacts, inconsistencies, and statistical signatures that distinguish fabricated from authentic content. It operates as a countermeasure to generative adversarial networks and related synthesis methods."@en ;
rdfs:label "Deepfake Detection"@en ;
rdfs:subClassOf ngm:computer-vision ;
rdfs:subClassOf ngm:deep-learning ;
rdfs:subClassOf ngm:machine-learning-discipline ;
rdfs:subClassOf ngm:media-forensics ;
rdfs:subClassOf ngm:signal-processing ;
rdfs:subClassOf _:r7607 ;
rdfs:subClassOf _:r7608 ;
rdfs:subClassOf _:r7609 ;
rdfs:subClassOf _:r7610 ;
rdfs:subClassOf _:r7611 ;
rdfs:subClassOf _:r7612 ;
rdfs:subClassOf _:r7613 ;
rdfs:subClassOf _:r7614 ;
rdfs:subClassOf _:r7615 ;
rdfs:subClassOf _:r7616 ;
vc:bridgesTo ngm:ai-regulation ;
vc:bridgesTo ngm:c2-pa ;
vc:contrastsWith ngm:deepfakes ;
vc:contrastsWith ngm:diffusion-model ;
vc:contrastsWith ngm:face-swap ;
vc:contrastsWith ngm:generative-adversarial-network ;
vc:contrastsWith ngm:synthetic-media ;
vc:dependsOn ngm:backpropagation ;
vc:dependsOn ngm:computer-vision ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:generative-ai ;
vc:dependsOn ngm:neural-network ;
vc:dependsOn ngm:signal-processing ;
vc:enables ngm:content-authentication ;
vc:enables ngm:content-authenticity ;
vc:enables ngm:content-provenance ;
vc:enables ngm:media-forensics ;
vc:enables ngm:misinformation-detection ;
vc:enables ngm:trust-and-safety ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:convolutional-neural-network ;
vc:hasPart ngm:face-recognition ;
vc:hasPart ngm:frequency-domain-analysis ;
vc:hasPart ngm:physiological-signal-analysis ;
vc:hasPart ngm:signal-processing ;
vc:hasPart ngm:temporal-analysis ;
vc:hasPart ngm:vision-transformer ;
vc:implements ngm:anomaly-detection ;
vc:implements ngm:classification ;
vc:implements ngm:ensemble-methods ;
vc:implements ngm:multimodal-ai-architecture-learning ;
vc:implements ngm:transfer-learning ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:content-provenance ;
vc:relatedTo ngm:deepfakes-and-fraudulent-content ;
vc:relatedTo ngm:diffusion-model ;
vc:relatedTo ngm:digital-forensics ;
vc:relatedTo ngm:generative-ai ;
vc:relatedTo ngm:misinformation ;
vc:relatedTo ngm:synthid ;
vc:relatedTo ngm:watermarking-service ;
vc:requires ngm:computer-vision-video-analysis ;
vc:requires ngm:face-recognition ;
vc:requires ngm:gpu-cluster ;
vc:requires ngm:labelled-data ;
vc:requires ngm:training-dataset ;
vc:slug "deepfake-detection" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:c2-pa ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:online-safety-act-2023 ;
vc:supports ngm:ai-regulation ;
vc:supports ngm:c2-pa ;
vc:supports ngm:content-provenance ;
vc:supports ngm:election-integrity ;
vc:supports ngm:financial-fraud-prevention ;
vc:supports ngm:identity-verification ;
vc:supports ngm:online-safety ;
vc:supports ngm:trust-and-safety ;
vc:uses ngm:clip ;
vc:uses ngm:convolutional-neural-network ;
vc:uses ngm:deep-learning ;
vc:uses ngm:diffusion-model ;
vc:uses ngm:face-recognition ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:neural-network ;
vc:uses ngm:signal-processing ;
vc:uses ngm:transfer-learning ;
vc:uses ngm:vision-transformer .
ngm:deepfakes a owl:Class ;
rdfs:comment "AI-generated or manipulated synthetic media content that convincingly alters a person's appearance, voice, or actions using deep learning techniques such as GANs, autoencoders, and voice synthesis models."@en ;
rdfs:label "Deepfakes"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:ai-generated-content ;
rdfs:subClassOf ngm:computer-vision-application ;
rdfs:subClassOf ngm:generative-ai ;
rdfs:subClassOf ngm:synthetic-media ;
rdfs:subClassOf _:r7623 ;
rdfs:subClassOf _:r7624 ;
rdfs:subClassOf _:r7625 ;
rdfs:subClassOf _:r7626 ;
rdfs:subClassOf _:r7627 ;
rdfs:subClassOf _:r7628 ;
rdfs:subClassOf _:r7629 ;
rdfs:subClassOf _:r7630 ;
rdfs:subClassOf _:r7631 ;
rdfs:subClassOf _:r7632 ;
rdfs:subClassOf _:r7633 ;
rdfs:subClassOf _:r7634 ;
skos:broader ngm:ai-application ;
vc:bridgesTo ngm:autonomous-robot ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:extended-reality ;
vc:contrastsWith ngm:biometric-verification ;
vc:contrastsWith ngm:c2-pa-standard ;
vc:contrastsWith ngm:content-authentication ;
vc:contrastsWith ngm:deepfake-detection ;
vc:contrastsWith ngm:provenance-watermarking ;
vc:dependsOn ngm:audio-processing ;
vc:dependsOn ngm:backpropagation ;
vc:dependsOn ngm:computer-vision ;
vc:dependsOn ngm:convolutional-neural-network ;
vc:dependsOn ngm:face-recognition ;
vc:dependsOn ngm:machine-learning-discipline-models ;
vc:dependsOn ngm:transformer-architecture ;
vc:enables ngm:content-creation ;
vc:enables ngm:digital-twin ;
vc:enables ngm:entertainment-production ;
vc:enables ngm:identity-deception ;
vc:enables ngm:media-manipulation ;
vc:enables ngm:misinformation ;
vc:enables ngm:personalised-avatar ;
vc:enables ngm:synthetic-video-generation ;
vc:enables ngm:voice-fraud ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:audio-manipulation ;
vc:hasPart ngm:face-swap ;
vc:hasPart ngm:gesture-synthesis ;
vc:hasPart ngm:identity-encoder ;
vc:hasPart ngm:neural-vocoder ;
vc:hasPart ngm:synthetic-video-generation ;
vc:hasPart ngm:talking-head-synthesis ;
vc:hasPart ngm:voice-cloning ;
vc:implements ngm:adversarial-training ;
vc:implements ngm:contrastive-learning ;
vc:implements ngm:identity-transfer ;
vc:implements ngm:latent-space-manipulation ;
vc:implements ngm:neural-rendering ;
vc:isPartOf ngm:ai-generated-content ;
vc:isPartOf ngm:generative-ai ;
vc:isPartOf ngm:synthetic-media ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:ai-ethics ;
vc:relatedTo ngm:biometric-surveillance ;
vc:relatedTo ngm:disinformation ;
vc:relatedTo ngm:electoral-integrity ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:non-consensual-intimate-imagery ;
vc:relatedTo ngm:online-safety ;
vc:relatedTo ngm:privacy ;
vc:requires ngm:autoencoder ;
vc:requires ngm:computational-infrastructure ;
vc:requires ngm:deep-learning ;
vc:requires ngm:diffusion-model ;
vc:requires ngm:generative-adversarial-network ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:neural-network ;
vc:requires ngm:training-dataset ;
vc:slug "deepfakes" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:c2-pa-standard ;
vc:standardizedBy ngm:data-use-and-access-act-2025 ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument ;
vc:standardizedBy ngm:iso-29100 ;
vc:standardizedBy ngm:online-safety-act-2023 ;
vc:supports ngm:accessibility-tools ;
vc:supports ngm:dubbing-and-localisation ;
vc:supports ngm:film-production ;
vc:supports ngm:personalised-media ;
vc:supports ngm:post-production ;
vc:uses ngm:convolutional-neural-network ;
vc:uses ngm:latent-diffusion ;
vc:uses ngm:neural-vocoder ;
vc:uses ngm:optical-flow-estimation ;
vc:uses ngm:stylegan ;
vc:uses ngm:transformer-architecture ;
vc:uses ngm:vae .
ngm:deepfakes-and-fraudulent-content a owl:Class ;
rdfs:comment "Deepfakes and fraudulent content denote synthetic audio, image, video and text artefacts produced by deep generative models (notably GAN-based face-swap pipelines DeepFaceLab/Faceswap/StyleGAN3, diffusion-based face-conditioning ReActor/Roop/InstantID/PhotoMaker/IP-Adapter-Face, lip-sync video ge..."@en ;
rdfs:label "Deepfakes and fraudulent content"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:ai-safety ;
rdfs:subClassOf ngm:generative-ai-misuse ;
rdfs:subClassOf ngm:identity-fraud ;
rdfs:subClassOf ngm:information-integrity-threat ;
rdfs:subClassOf ngm:online-harm ;
rdfs:subClassOf ngm:synthetic-media ;
rdfs:subClassOf _:r7617 ;
rdfs:subClassOf _:r7618 ;
rdfs:subClassOf _:r7619 ;
rdfs:subClassOf _:r7620 ;
rdfs:subClassOf _:r7621 ;
rdfs:subClassOf _:r7622 ;
skos:broader ngm:ai-application ;
vc:contrastsWith ngm:authentic-ugc ;
vc:contrastsWith ngm:cgi-vfx ;
vc:contrastsWith ngm:consensual-avatar ;
vc:contrastsWith ngm:disclosed-synthetic-media ;
vc:contrastsWith ngm:shallowfake ;
vc:dependsOn ngm:autoencoder ;
vc:dependsOn ngm:diffusion-models ;
vc:dependsOn ngm:face-recognition ;
vc:dependsOn ngm:generative-adversarial-networks ;
vc:dependsOn ngm:speech-synthesis ;
vc:dependsOn ngm:stable-diffusion-image-model ;
vc:dependsOn ngm:text-to-speech ;
vc:dependsOn ngm:wav2lip ;
vc:enables ngm:business-email-compromise ;
vc:enables ngm:election-interference ;
vc:enables ngm:image-based-sexual-abuse ;
vc:enables ngm:kyc-bypass ;
vc:enables ngm:market-manipulation ;
vc:enables ngm:reputation-attack ;
vc:enables ngm:romance-fraud ;
vc:enables ngm:social-engineering ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:face-swap ;
vc:hasPart ngm:lip-sync-generation ;
vc:hasPart ngm:non-consensual-intimate-imagery ;
vc:hasPart ngm:real-time-avatar ;
vc:hasPart ngm:synthetic-disinformation ;
vc:hasPart ngm:synthetic-identity-document ;
vc:hasPart ngm:voice-cloning ;
vc:implements ngm:audiovisual-forgery ;
vc:implements ngm:identity-impersonation ;
vc:implements ngm:real-time-puppetry ;
vc:implements ngm:voice-cloning ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:ai-liability ;
vc:relatedTo ngm:ai-risks ;
vc:relatedTo ngm:algorithmic-bias-and-variance ;
vc:relatedTo ngm:content-authenticity ;
vc:relatedTo ngm:cyber-security-and-cryptography ;
vc:relatedTo ngm:election-integrity ;
vc:relatedTo ngm:media-forensics ;
vc:requires ngm:distribution-platform ;
vc:requires ngm:generative-ai ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:target-identity-reference ;
vc:requires ngm:training-data ;
vc:slug "deepfakes-and-fraudulent-content" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:c2-pa ;
vc:standardizedBy ngm:cai-coalition-for-content-provenance-and-authenticity ;
vc:standardizedBy ngm:china-deep-synthesis-provisions ;
vc:standardizedBy ngm:eu-ai-act-regulatory-instrument-article-50 ;
vc:standardizedBy ngm:iso-22144 ;
vc:standardizedBy ngm:take-it-down-act ;
vc:standardizedBy ngm:uk-online-safety-act ;
vc:supports ngm:disinformation-campaign ;
vc:supports ngm:fraud-ecosystem ;
vc:supports ngm:influence-operation ;
vc:supports ngm:pig-butchering-scam ;
vc:supports ngm:sextortion ;
vc:uses ngm:d-id ;
vc:uses ngm:deepfacelab ;
vc:uses ngm:eleven-labs ;
vc:uses ngm:face-swap ;
vc:uses ngm:heygen ;
vc:uses ngm:instant-id ;
vc:uses ngm:node-based-diffusion-pipeline-interface ;
vc:uses ngm:reactor ;
vc:uses ngm:synthesia ;
vc:uses ngm:wav2lip .
ngm:deeplab a skos:Concept ;
rdfs:label "Deeplab"@en .
ngm:deeplift a skos:Concept ;
rdfs:label "Deeplift"@en .
ngm:deepmind-levels-of-agi-framework a skos:Concept ;
rdfs:label "Deepmind Levels Of Agi Framework"@en .
ngm:deepsdf a skos:Concept ;
rdfs:label "Deepsdf"@en .
ngm:deepseek a skos:Concept ;
rdfs:label "Deepseek"@en .
ngm:deepseek-r1 a skos:Concept ;
rdfs:label "Deepseek R1"@en .
ngm:deepseek-research a skos:Concept ;
rdfs:label "Deepseek Research"@en .
ngm:default-logic a skos:Concept ;
rdfs:label "Default Logic"@en .
ngm:default-management a skos:Concept ;
rdfs:label "Default Management"@en .
ngm:default-prompting a skos:Concept ;
rdfs:label "Default Prompting"@en .
ngm:defect-detection a owl:Class ;
rdfs:comment "Defect Detection is the automated identification of flaws, anomalies, or deviations from specification in products, materials, or processes, typically performed using machine vision and machine-learning models on images or sensor data. It localises and classifies defects such as cracks, scratches, contamination, dimensional errors, or assembly faults, often in real time on a production line. Modern systems combine high-resolution imaging, deep-learning object detection and anomaly detection, and feedback to robotic or process controls. Defect detection underpins quality assurance and industrial inspection, reducing waste and ensuring consistency."@en ;
rdfs:label "Defect Detection"@en ;
rdfs:subClassOf ngm:machine-vision ;
rdfs:subClassOf _:r7635 ;
rdfs:subClassOf _:r7636 ;
rdfs:subClassOf _:r7637 ;
vc:dependsOn ngm:convolutional-neural-network ;
vc:dependsOn ngm:deep-learning ;
vc:enables ngm:predictive-maintenance ;
vc:enables ngm:quality-assurance ;
vc:enables ngm:quality-control ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:computer-vision-system ;
vc:isPartOf ngm:machine-vision ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:automation ;
vc:relatedTo ngm:data-analytics ;
vc:requires ngm:feature-extraction ;
vc:requires ngm:sensor-networks ;
vc:slug "defect-detection" ;
vc:sourceDomain "robotics" ;
vc:supports ngm:industrial-inspection ;
vc:supports ngm:manufacturing-process ;
vc:uses ngm:anomaly-detection ;
vc:uses ngm:computer-vision ;
vc:uses ngm:machine-vision ;
vc:uses ngm:object-detection .
ngm:defect-tracking-system a skos:Concept ;
rdfs:label "Defect Tracking System"@en .
ngm:defence-and-intelligence a skos:Concept ;
rdfs:label "Defence And Intelligence"@en .
ngm:defence-and-security a skos:Concept ;
rdfs:label "Defence And Security"@en .
ngm:defence-and-security-ai a skos:Concept ;
rdfs:label "Defence And Security AI"@en .
ngm:defence-decision-support a skos:Concept ;
rdfs:label "Defence Decision Support"@en .
ngm:defence-in-depth a owl:Class ;
rdfs:comment "Defence in Depth is a cybersecurity strategy that layers multiple independent security controls such that the failure of any single control does not expose the system to compromise. Originating from military doctrine, it applies redundancy and diversity across physical, technical, and administrative security dimensions. The strategy reduces the probability of successful attack by requiring adversaries to defeat multiple independent barriers sequentially."@en ;
rdfs:label "Defence In Depth"@en ;
rdfs:subClassOf ngm:security ;
rdfs:subClassOf _:r7638 ;
rdfs:subClassOf _:r7639 ;
rdfs:subClassOf _:r7640 ;
rdfs:subClassOf _:r7641 ;
rdfs:subClassOf _:r7642 ;
rdfs:subClassOf _:r7643 ;
vc:contrastsWith ngm:perimeter-security ;
vc:enables ngm:incident-response ;
vc:enables ngm:resilience ;
vc:enables ngm:zero-trust-architecture ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:access-control ;
vc:hasPart ngm:encryption ;
vc:hasPart ngm:firewall ;
vc:hasPart ngm:intrusion-detection-system ;
vc:implements ngm:risk-management ;
vc:implements ngm:security-architecture ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:identity-management ;
vc:relatedTo ngm:network-segmentation ;
vc:relatedTo ngm:vulnerability-management ;
vc:requires ngm:security-policy ;
vc:requires ngm:threat-modelling ;
vc:slug "defence-in-depth" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:nist-cybersecurity-framework ;
vc:supports ngm:cloud-security ;
vc:supports ngm:regulatory-compliance .
ngm:defend-forward a skos:Concept ;
rdfs:label "Defend Forward"@en .
ngm:defense-in-depth a owl:Class ;
rdfs:comment "Defense in depth is a security strategy that layers multiple, independent controls across an environment so that the failure or bypass of any single control does not lead to compromise. Adapted from military doctrine, it spans physical, network, host, application, and data layers, combining preventive, detective, and responsive measures to slow attackers, increase the cost of intrusion, and provide redundancy. It assumes no control is infallible and complements modern paradigms such as zero trust by ensuring that defences are distributed rather than concentrated at a single perimeter."@en ;
rdfs:label "Defense In Depth"@en ;
rdfs:subClassOf ngm:security-architecture ;
rdfs:subClassOf _:r7644 ;
rdfs:subClassOf _:r7645 ;
vc:contrastsWith ngm:perimeter-security ;
vc:enables ngm:risk-mitigation ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:risk-mitigation ;
vc:isPartOf ngm:security-architecture ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:access-control ;
vc:relatedTo ngm:cybersecurity ;
vc:relatedTo ngm:network-security ;
vc:requires ngm:intrusion-detection ;
vc:requires ngm:intrusion-detection-system ;
vc:slug "defense-in-depth" ;
vc:sourceDomain "security" ;
vc:supports ngm:endpoint-security ;
vc:supports ngm:network-security ;
vc:uses ngm:access-control ;
vc:uses ngm:encryption ;
vc:uses ngm:firewall .
ngm:defensive-cyber-operations a skos:Concept ;
rdfs:label "Defensive Cyber Operations"@en .
ngm:deferred-net-settlement a skos:Concept ;
rdfs:label "Deferred Net Settlement"@en .
ngm:deferred-rendering a owl:Class ;
rdfs:comment "Deferred rendering is a real-time shading technique that separates geometry processing from lighting by first rasterising scene attributes into a set of screen-space buffers, then computing lighting in a second pass over those buffers. By storing per-pixel position, normal, albedo, and material data in a geometry buffer, lighting cost becomes independent of scene complexity and scales with the number of lights instead. This decoupling makes it efficient to render scenes with many dynamic light sources."@en ;
rdfs:label "Deferred Rendering"@en ;
rdfs:subClassOf ngm:rendering-technique ;
rdfs:subClassOf _:r7646 ;
rdfs:subClassOf _:r7647 ;
vc:contrastsWith ngm:rasterization ;
vc:enables ngm:global-illumination ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:rendering-technique ;
vc:isPartOf ngm:rendering-technique ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:graphics-pipeline ;
vc:relatedTo ngm:rasterization ;
vc:relatedTo ngm:real-time-rendering ;
vc:requires ngm:gpu-rendering ;
vc:requires ngm:graphics-pipeline ;
vc:slug "deferred-rendering" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:real-time-rendering ;
vc:uses ngm:gpu-rendering ;
vc:uses ngm:rasterization ;
vc:uses ngm:shader .
ngm:defi-access a skos:Concept ;
rdfs:label "DeFi Access"@en .
ngm:defi-agent a skos:Concept ;
rdfs:label "DeFi Agent"@en .
ngm:defi-applications a skos:Concept ;
rdfs:label "DeFi Applications"@en .
ngm:defi-composability a skos:Concept ;
rdfs:label "DeFi Composability"@en .
ngm:defi-governance a skos:Concept ;
rdfs:label "DeFi Governance"@en .
ngm:defi-infrastructure a owl:Class ;
rdfs:comment "DeFi infrastructure is the layer of foundational protocols and services — price oracles, stablecoins, bridges, and indexing services — that decentralised finance applications depend on but do not themselves implement. It sits beneath end-user-facing DeFi protocols such as lending markets and exchanges, supplying reliable price feeds and settlement assets like USDC that those protocols compose into their own functionality. Its reliability and decentralisation materially affect the security of everything built on top of it."@en ;
rdfs:label "DeFi Infrastructure"@en ;
rdfs:subClassOf ngm:de-fi ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:de-fi ;
vc:qualityScore "0.6"^^xsd:float ;
vc:slug "defi-infrastructure" ;
vc:sourceDomain "blockchain" .
ngm:defi-protocol a owl:Class ;
rdfs:comment "A DeFi Protocol is a set of immutable or upgradeable smart contracts deployed on a public blockchain that implements a specific financial primitive—such as lending, decentralised exchange, derivatives, or yield aggregation—in a permissionless and non-custodial manner. Protocol logic encodes all rules governing asset custody, interest-rate models, fee distribution, and liquidation mechanics directly in on-chain code that executes deterministically without intermediaries. Most DeFi protocols expose a composable interface through standardised token standards so that outputs (liquidity tokens, receipt tokens, or yield-bearing positions) can be consumed as inputs by other protocols. Governance over protocol parameters is typically delegated to token holders via an on-chain voting system, making protocol evolution itself a decentralised process."@en ;
rdfs:label "DeFi Protocol"@en ;
rdfs:subClassOf ngm:de-fi ;
rdfs:subClassOf _:r7208 ;
rdfs:subClassOf _:r7209 ;
rdfs:subClassOf _:r7210 ;
rdfs:subClassOf _:r7211 ;
rdfs:subClassOf _:r7212 ;
rdfs:subClassOf _:r7213 ;
vc:bridgesTo ngm:cross-chain-bridge ;
vc:bridgesTo ngm:regulatory-compliance ;
vc:contrastsWith ngm:traditional-finance ;
vc:dependsOn ngm:composability ;
vc:enables ngm:flash-loan ;
vc:enables ngm:liquidity-mining ;
vc:enables ngm:yield-farming ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:governance-token ;
vc:hasPart ngm:liquidity-pool ;
vc:hasPart ngm:smart-contract ;
vc:isPartOf ngm:de-fi ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:blockchain-security ;
vc:relatedTo ngm:dao ;
vc:relatedTo ngm:impermanent-loss ;
vc:relatedTo ngm:mev ;
vc:relatedTo ngm:tokenomics ;
vc:requires ngm:blockchain-oracle ;
vc:requires ngm:erc-20-token-standard ;
vc:requires ngm:token-standard ;
vc:slug "defi-protocol" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:automated-market-maker ;
vc:uses ngm:price-oracle ;
vc:uses ngm:stablecoin .
ngm:defi-protocols a skos:Concept ;
rdfs:label "DeFi Protocols"@en .
ngm:defi-risk a skos:Concept ;
rdfs:label "DeFi Risk"@en .
ngm:defi-summer a skos:Concept ;
rdfs:label "DeFi Summer"@en .
ngm:definite-query-answering a skos:Concept ;
rdfs:label "Definite Query Answering"@en .
ngm:definitions-and-frameworks-for-metaverse a owl:Class ;
rdfs:comment "This page surveys competing definitions and analytical frameworks used to characterise the metaverse, drawing from industry reports, academic literature, and standards bodies. It compares platform-centric, social-first, and open-interoperability framings; examines primitives such as persistence, embodiment, real-time 3D graphics, and economic actors; and contextualises failed early attempts (Decentraland, Sandbox) against more enduring platforms (Roblox). The analysis informs design principles for trust, value transfer, and AI-mediated governance in spatial social systems."@en ;
rdfs:label "Definitions and frameworks for Metaverse"@en ;
rdfs:subClassOf ngm:metaverse-ontology ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf _:r7648 ;
rdfs:subClassOf _:r7649 ;
skos:broader ngm:sc-platform-and-environment ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:telecollaboration ;
vc:enables ngm:digital-commerce ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:metaverse ;
vc:hasPart ngm:telecollaboration ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:ai-governance ;
vc:relatedTo ngm:digital-twin ;
vc:slug "definitions-and-frameworks-for-metaverse" ;
vc:sourceDomain "spatial-computing" ;
vc:uses ngm:augmented-reality ;
vc:uses ngm:blockchain .
ngm:deflation a skos:Concept ;
rdfs:label "Deflation"@en .
ngm:deflationary-token a owl:Class ;
rdfs:comment "A Deflationary Token is a cryptocurrency or blockchain token whose total circulating supply decreases over time through one or more programmatic burning mechanisms—such as transaction fee burns, scheduled buyback-and-burn events, or protocol-level token destruction—creating supply-side scarcity intended to exert upward price pressure and incentivise long-term holding."@en ;
rdfs:label "Deflationary Token"@en ;
rdfs:subClassOf ngm:bc-token-and-asset ;
rdfs:subClassOf ngm:blockchain-entity ;
rdfs:subClassOf ngm:economic-mechanism ;
rdfs:subClassOf _:r7650 ;
rdfs:subClassOf _:r7651 ;
skos:broader ngm:bc-token-and-asset ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:de-fi ;
vc:bridgesTo ngm:non-fungible-token ;
vc:bridgesTo ngm:virtual-economy ;
vc:contrastsWith ngm:inflationary-token ;
vc:contrastsWith ngm:native-token ;
vc:contrastsWith ngm:stablecoin ;
vc:dependsOn ngm:distributed-ledger ;
vc:dependsOn ngm:token-standard ;
vc:enables ngm:incentive-mechanism ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:blockchain ;
vc:isPartOf ngm:token-economics ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:blockchain-economics ;
vc:relatedTo ngm:governance-token ;
vc:relatedTo ngm:monetary-policy ;
vc:relatedTo ngm:scarcity ;
vc:relatedTo ngm:store-of-value ;
vc:relatedTo ngm:token-economics ;
vc:relatedTo ngm:tokenomics ;
vc:relatedTo ngm:transaction-fee ;
vc:requires ngm:consensus-mechanism ;
vc:requires ngm:on-chain-governance ;
vc:slug "deflationary-token" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:burning-mechanism ;
vc:uses ngm:proof-of-work ;
vc:uses ngm:smart-contract ;
vc:uses ngm:supply-cap .
ngm:deflection-measurement a skos:Concept ;
rdfs:label "Deflection Measurement"@en .
ngm:deforestation-free-commodities a skos:Concept ;
rdfs:label "Deforestation Free Commodities"@en .
ngm:deforestation-monitoring a owl:Class ;
rdfs:label "Deforestation Monitoring"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:earth-observation-applications ;
vc:slug "deforestation-monitoring" ;
vc:sourceDomain "earth-observation-and-geospatial-sensing" .
ngm:deformable-body-model a skos:Concept ;
rdfs:label "Deformable Body Model"@en .
ngm:deformation-field a skos:Concept ;
rdfs:label "Deformation Field"@en .
ngm:degradation-model a skos:Concept ;
rdfs:label "Degradation Model"@en .
ngm:degradation-prior a skos:Concept ;
rdfs:label "Degradation Prior"@en .
ngm:degrees-of-freedom a skos:Concept ;
rdfs:label "Degrees Of Freedom"@en .
ngm:dei-analytics a skos:Concept ;
rdfs:label "Dei Analytics"@en .
ngm:delaunay-triangulation a skos:Concept ;
rdfs:label "Delaunay Triangulation"@en .
ngm:delaware-statutory-trust a skos:Concept ;
rdfs:label "Delaware Statutory Trust"@en .
ngm:delay-tolerant-space-networking a owl:Class ;
rdfs:label "Delay-tolerant Space Networking"@en ;
vc:bridgesTo ngm:communication-protocol ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:satellite-communication ;
vc:slug "delay-tolerant-space-networking" ;
vc:sourceDomain "space-science-and-systems" ;
vc:uses ngm:store-and-forward-communication .
ngm:delegate a skos:Concept ;
rdfs:label "Delegate"@en .
ngm:delegate-accountability a skos:Concept ;
rdfs:label "Delegate Accountability"@en .
ngm:delegate-democracy a owl:Class ;
rdfs:comment "Delegate Democracy (also known as liquid democracy, delegative democracy, or proxy democracy) is a hybrid political and organisational governance model — formalised in modern computer-mediated form by Bryan Ford in his 2002 paper Delegative Democracy (Yale, later Swiss EPFL) and intellectuall..."@en ;
rdfs:label "Delegate Democracy"@en ;
rdfs:subClassOf ngm:bc-governance-and-regulation ;
rdfs:subClassOf ngm:collective-decision-making ;
rdfs:subClassOf ngm:dao-governance ;
rdfs:subClassOf ngm:governance-model ;
rdfs:subClassOf ngm:hybrid-democracy ;
rdfs:subClassOf ngm:social-choice-mechanism ;
rdfs:subClassOf _:r7652 ;
rdfs:subClassOf _:r7653 ;
rdfs:subClassOf _:r7654 ;
rdfs:subClassOf _:r7655 ;
rdfs:subClassOf _:r7656 ;
rdfs:subClassOf _:r7657 ;
rdfs:subClassOf _:r7658 ;
rdfs:subClassOf _:r7659 ;
skos:broader ngm:bc-governance-and-regulation ;
vc:bridgesTo ngm:collective-decision-making ;
vc:contrastsWith ngm:direct-democracy ;
vc:contrastsWith ngm:futarchy ;
vc:contrastsWith ngm:plutocracy ;
vc:contrastsWith ngm:quadratic-voting ;
vc:contrastsWith ngm:representative-democracy ;
vc:contrastsWith ngm:sortition ;
vc:dependsOn ngm:cryptographic-vote-aggregation ;
vc:dependsOn ngm:identity-system ;
vc:dependsOn ngm:off-chain-or-on-chain-forum ;
vc:dependsOn ngm:proposal-lifecycle-standard ;
vc:dependsOn ngm:sybil-resistance ;
vc:enables ngm:accountability ;
vc:enables ngm:expert-aggregation ;
vc:enables ngm:professional-governance-class ;
vc:enables ngm:reduced-voter-fatigue ;
vc:enables ngm:specialised-governance-domains ;
vc:enables ngm:vote-delegation ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:checkpoints ;
vc:hasPart ngm:delegate ;
vc:hasPart ngm:delegate-discovery ;
vc:hasPart ngm:delegator ;
vc:hasPart ngm:domain-specific-delegation ;
vc:hasPart ngm:revocation-mechanism ;
vc:hasPart ngm:vote-delegation ;
vc:implements ngm:carroll-proportional-representation ;
vc:implements ngm:ford-delegative-theory ;
vc:implements ngm:loar-transitive-delegation-calculus ;
vc:implements ngm:madisonian-republican-filter ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:ai16z-dao ;
vc:relatedTo ngm:aragon ;
vc:relatedTo ngm:better-reykjavik ;
vc:relatedTo ngm:compound-governor-bravo ;
vc:relatedTo ngm:convex-finance ;
vc:relatedTo ngm:curve-wars ;
vc:relatedTo ngm:democracyos ;
vc:relatedTo ngm:ens-dao ;
vc:relatedTo ngm:liquidfeedback ;
vc:relatedTo ngm:olas-autonolas ;
vc:relatedTo ngm:open-rights-group ;
vc:relatedTo ngm:optimism-collective ;
vc:relatedTo ngm:optimism-token-house ;
vc:relatedTo ngm:pirate-party-germany ;
vc:relatedTo ngm:sortition-foundation ;
vc:relatedTo ngm:uniswap-governance ;
vc:requires ngm:membership-cryptographic-identity ;
vc:requires ngm:on-chain-or-verifiable-vote-recording ;
vc:requires ngm:proposal-system ;
vc:requires ngm:quorum-mechanism ;
vc:requires ngm:voting-power-accounting ;
vc:slug "delegate-democracy" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:compound-governor-bravo ;
vc:standardizedBy ngm:erc-20-token-standard ;
vc:standardizedBy ngm:erc-712-typed-structured-data-signing ;
vc:standardizedBy ngm:open-zeppelin-governor-contracts ;
vc:standardizedBy ngm:snapshot ;
vc:supports ngm:citizen-engagement ;
vc:supports ngm:dao ;
vc:supports ngm:polycentric-governance ;
vc:supports ngm:public-goods-funding ;
vc:supports ngm:subsidiarity ;
vc:uses ngm:compound-governor-bravo ;
vc:uses ngm:decidim-platform ;
vc:uses ngm:democracyos-platform ;
vc:uses ngm:erc20-votes-standard ;
vc:uses ngm:karma-delegate-analytics ;
vc:uses ngm:liquidfeedback-platform ;
vc:uses ngm:project-agora ;
vc:uses ngm:snapshot-off-chain-voting ;
vc:uses ngm:tally .
ngm:delegate-discovery a skos:Concept ;
rdfs:label "Delegate Discovery"@en .
ngm:delegate-performance-tracker a skos:Concept ;
rdfs:label "Delegate Performance Tracker"@en .
ngm:delegate-reputation-score a skos:Concept ;
rdfs:label "Delegate Reputation Score"@en .
ngm:delegated-authorisation a owl:Class ;
rdfs:comment "Delegated authorisation is the pattern in which a resource owner grants a third-party application limited access to their resources without sharing their credentials. An authorisation server issues scoped, often time-limited tokens that the application presents to the resource server, so access can be granted, constrained, and revoked independently of the owner's password. OAuth 2.0 is the dominant framework that implements this pattern across web and API ecosystems."@en ;
rdfs:label "Delegated Authorisation"@en ;
rdfs:subClassOf ngm:oauth-2-0 ;
rdfs:subClassOf _:r7660 ;
vc:bridgesTo ngm:identity-provider ;
vc:contrastsWith ngm:authentication ;
vc:dependsOn ngm:authorization ;
vc:dependsOn ngm:identity-provider ;
vc:enables ngm:federated-identity ;
vc:enables ngm:single-sign-on ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:authorization ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:authorization ;
vc:relatedTo ngm:oauth ;
vc:relatedTo ngm:oauth-2-0 ;
vc:relatedTo ngm:token ;
vc:requires ngm:authentication ;
vc:slug "delegated-authorisation" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:standards ;
vc:supports ngm:api ;
vc:uses ngm:token .
ngm:delegated-governance a skos:Concept ;
rdfs:label "Delegated Governance"@en .
ngm:delegated-proof-of-stake a owl:Class ;
rdfs:comment "A Proof-of-Stake variant in which token holders delegate block production rights to a fixed number of elected delegates (witnesses or block producers) via a token-weighted democratic voting mechanism. DPoS achieves high throughput and fast block times by concentrating validation among a small elected set, with delegates subject to removal by voters if they misbehave or underperform."@en ;
rdfs:label "Delegated Proof of Stake"@en ;
rdfs:subClassOf ngm:bc-protocol-and-consensus ;
rdfs:subClassOf ngm:proof-of-stake ;
skos:broader ngm:bc-protocol-and-consensus ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:virtual-economy ;
vc:contrastsWith ngm:nakamoto-consensus ;
vc:contrastsWith ngm:proof-of-work ;
vc:enables ngm:deterministic-finality ;
vc:enables ngm:virtual-economy ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:blockchain-governance ;
vc:relatedTo ngm:consensus-mechanism ;
vc:relatedTo ngm:delegate-democracy ;
vc:relatedTo ngm:liquid-proof-of-stake ;
vc:relatedTo ngm:nominated-proof-of-stake ;
vc:slug "delegated-proof-of-stake" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:epoch ;
vc:uses ngm:governance-token ;
vc:uses ngm:validator-set .
ngm:delegated-representation a skos:Concept ;
rdfs:label "Delegated Representation"@en .
ngm:delegated-treasury-management a skos:Concept ;
rdfs:label "Delegated Treasury Management"@en .
ngm:delegated-voting a skos:Concept ;
rdfs:label "Delegated Voting"@en .
ngm:delegation a owl:Class ;
rdfs:comment "Delegation in blockchain systems is the act of assigning one's stake or voting rights to another participant who acts on one's behalf in consensus or governance, without transferring ownership of the underlying assets. In proof-of-stake networks token holders delegate stake to validators, sharing in rewards and slashing risk while the validator performs block production. In on-chain governance, delegation lets holders entrust their votes to representatives, a pattern formalised as liquid democracy. Delegation lowers the participation barrier for ordinary holders and concentrates operational responsibility with capable operators, while introducing trust and centralisation trade-offs."@en ;
rdfs:label "Delegation"@en ;
rdfs:subClassOf ngm:proof-of-stake ;
rdfs:subClassOf _:r7661 ;
rdfs:subClassOf _:r7662 ;
rdfs:subClassOf _:r7663 ;
rdfs:subClassOf _:r7664 ;
vc:contrastsWith ngm:slashing ;
vc:dependsOn ngm:trust ;
vc:dependsOn ngm:validator ;
vc:enables ngm:liquid-democracy ;
vc:enables ngm:on-chain-governance ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:reward-distribution ;
vc:hasPart ngm:staking ;
vc:implements ngm:delegated-proof-of-stake ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:governance ;
vc:relatedTo ngm:reward-distribution ;
vc:requires ngm:staking ;
vc:requires ngm:validator ;
vc:slug "delegation" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:consensus ;
vc:supports ngm:dao ;
vc:uses ngm:proof-of-stake .
ngm:delegation-graph a skos:Concept ;
rdfs:label "Delegation Graph"@en .
ngm:delegation-protocol a skos:Concept ;
rdfs:label "Delegation Protocol"@en .
ngm:delegation-registry a owl:Class ;
rdfs:comment "A delegation registry is an on-chain contract that records mappings from a token holder's address to a delegate authorised to act or vote on their behalf. In DAO governance it lets holders assign their voting power to a representative without transferring assets, and the registry serves as the canonical source consulted when tallying votes. It enables liquid democracy patterns and separation of custody from voting authority."@en ;
rdfs:label "Delegation Registry"@en ;
rdfs:subClassOf ngm:smart-contract ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:on-chain-voting ;
vc:relatedTo ngm:snapshot-voting ;
vc:slug "delegation-registry" ;
vc:sourceDomain "blockchain" .
ngm:delegation-system a owl:Class ;
rdfs:comment "A delegation system is the governance mechanism by which stakeholders entrust their decision-making or voting power to chosen representatives. In decentralized governance it supports liquid democracy, where delegated authority can be reassigned or revoked at any time, scaling participation without requiring every holder to vote directly. It balances broad legitimacy with the expertise and availability of active delegates."@en ;
rdfs:label "Delegation System"@en ;
rdfs:subClassOf ngm:governance-framework ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:decentralized-governance ;
vc:relatedTo ngm:tokenomics-governance ;
vc:slug "delegation-system" ;
vc:sourceDomain "governance" .
ngm:delegator a skos:Concept ;
rdfs:label "Delegator"@en .
ngm:deletion-request a skos:Concept ;
rdfs:label "Deletion Request"@en .
ngm:deliberate-demonstration a owl:Class ;
rdfs:comment "A paradigm for AI learning where users intentionally teach the system by providing explicit examples, instructions, or demonstrations of desired tasks and behaviors."@en ;
rdfs:label "Deliberate Demonstration"@en ;
rdfs:subClassOf ngm:machine-learning-discipline ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:fine-tuning ;
vc:relatedTo ngm:machine-learning-discipline ;
vc:relatedTo ngm:prompt-engineering ;
vc:slug "deliberate-demonstration" ;
vc:sourceDomain "artificial-intelligence" .
ngm:deliberation a skos:Concept ;
rdfs:label "Deliberation"@en .
ngm:deliberation-agent a skos:Concept ;
rdfs:label "Deliberation Agent"@en .
ngm:deliberation-forum a skos:Concept ;
rdfs:label "Deliberation Forum"@en .
ngm:deliberation-function a skos:Concept ;
rdfs:label "Deliberation Function"@en .
ngm:deliberation-protocol a skos:Concept ;
rdfs:label "Deliberation Protocol"@en .
ngm:deliberative-democracy a skos:Concept ;
rdfs:label "Deliberative Democracy"@en .
ngm:deliberative-reasoning a skos:Concept ;
rdfs:label "Deliberative Reasoning"@en .
ngm:delicate-handling a skos:Concept ;
rdfs:label "Delicate Handling"@en .
ngm:delivery-guarantees a skos:Concept ;
rdfs:label "Delivery Guarantees"@en .
ngm:delivery-robot a skos:Concept ;
rdfs:label "Delivery Robot"@en .
ngm:delivery-versus-payment a owl:Class ;
rdfs:comment "Delivery-Versus-Payment (DvP) is a securities settlement mechanism that links the transfer of a financial instrument to the simultaneous transfer of payment, ensuring that delivery occurs if and only if payment occurs, thereby eliminating principal risk in securities transactions. It is the standard settlement model mandated or strongly encouraged by financial market infrastructures globally."@en ;
rdfs:label "Delivery-Versus-Payment"@en ;
rdfs:subClassOf ngm:payment-system ;
rdfs:subClassOf _:r7665 ;
vc:enables ngm:custody-infrastructure ;
vc:enables ngm:digital-asset-trading ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:digital-asset-market ;
vc:requires ngm:financial-infrastructure ;
vc:slug "delivery-versus-payment" ;
vc:sourceDomain "finance" ;
vc:uses ngm:atomic-swap ;
vc:uses ngm:digital-asset .
ngm:delta-compression a skos:Concept ;
rdfs:label "Delta Compression"@en .
ngm:delta-differential-one-way-ranging a owl:Class ;
rdfs:label "Delta Differential One-way Ranging"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:orbit-determination ;
vc:relatedTo ngm:quasar ;
vc:relatedTo ngm:radiometric-spacecraft-navigation ;
vc:slug "delta-differential-one-way-ranging" ;
vc:sourceDomain "space-science-and-systems" .
ngm:delta-lake a skos:Concept ;
rdfs:label "Delta Lake"@en .
ngm:delta-robot a owl:Class ;
rdfs:comment "Delta robot employs parallel kinematics where three or more kinematic chains connect actuators to an end-effector platform, constraining motion through parallelogram linkages to pure translation."@en ;
rdfs:label "Delta Robot"@en ;
rdfs:subClassOf ngm:industrial-robot ;
rdfs:subClassOf ngm:parallel-robot ;
rdfs:subClassOf ngm:parallel-robots ;
rdfs:subClassOf ngm:robo-robot-type ;
rdfs:subClassOf _:r7666 ;
rdfs:subClassOf _:r7667 ;
rdfs:subClassOf _:r7668 ;
rdfs:subClassOf _:r7669 ;
rdfs:subClassOf _:r7670 ;
rdfs:subClassOf _:r7671 ;
rdfs:subClassOf _:r7672 ;
rdfs:subClassOf _:r7673 ;
skos:broader ngm:robo-robot-type ;
vc:bridgesTo ngm:smart-contract ;
vc:dependsOn ngm:inverse-kinematics-computation ;
vc:dependsOn ngm:trajectory-planning ;
vc:enables ngm:high-speed-picking ;
vc:enables ngm:parallel-processing ;
vc:enables ngm:rapid-sorting ;
vc:enables ngm:ultra-fast-placement ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:actuator ;
vc:hasPart ngm:end-effector ;
vc:hasPart ngm:kinematic-chain ;
vc:hasPart ngm:kinematic-chains ;
vc:hasPart ngm:parallelogram-linkages ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:actuators ;
vc:requires ngm:coordinated-control ;
vc:requires ngm:stiff-support-structure ;
vc:requires ngm:synchronisation ;
vc:slug "delta-robot" ;
vc:sourceDomain "robotics" .
ngm:delta-robots a skos:Concept ;
rdfs:label "Delta Robots"@en .
ngm:delta-state a skos:Concept ;
rdfs:label "Delta State"@en .
ngm:delta-v a owl:Class ;
rdfs:label "Delta-v"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:orbital-dynamics ;
vc:slug "delta-v" ;
vc:sourceDomain "space-science-and-systems" .
ngm:demand-chain a skos:Concept ;
rdfs:label "Demand Chain"@en .
ngm:demand-elasticity a skos:Concept ;
rdfs:label "Demand Elasticity"@en .
ngm:demand-forecasting a owl:Class ;
rdfs:comment "Demand forecasting is the analytical process of estimating future customer demand for products or services over a specified time horizon using historical sales data, statistical models, and increasingly machine learning algorithms. Accurate demand forecasts drive inventory replenishment, capacity planning, production scheduling, and financial budgeting decisions across retail, manufacturing, logistics, and energy sectors."@en ;
rdfs:label "Demand Forecasting"@en ;
rdfs:subClassOf ngm:predictive-analytics ;
rdfs:subClassOf _:r7674 ;
rdfs:subClassOf _:r7675 ;
rdfs:subClassOf _:r7676 ;
rdfs:subClassOf _:r7677 ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:reinforcement-learning ;
vc:enables ngm:capacity-planning ;
vc:enables ngm:demand-planning ;
vc:enables ngm:supply-chain-management ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:forecast-horizon ;
vc:hasPart ngm:probabilistic-forecasting ;
vc:hasPart ngm:time-series-analysis ;
vc:isPartOf ngm:supply-chain-planning ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:logistics-optimisation ;
vc:relatedTo ngm:supply-chain ;
vc:requires ngm:feature-engineering ;
vc:slug "demand-forecasting" ;
vc:sourceDomain "supply-chain" ;
vc:uses ngm:arima ;
vc:uses ngm:exponential-smoothing ;
vc:uses ngm:gradient-boosted-trees ;
vc:uses ngm:machine-learning-discipline ;
vc:uses ngm:recurrent-neural-network .
ngm:demand-planning a owl:Class ;
rdfs:comment "Demand planning is the supply-chain process of estimating future customer demand and aligning inventory, production, and procurement to meet it efficiently. It consolidates statistical forecasts, market intelligence, and business constraints into an actionable plan that minimises stockouts and excess holding. Modern demand planning increasingly relies on time-series forecasting and machine-learning models fed by historical sales and external signals."@en ;
rdfs:label "Demand Planning"@en ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
skos:broader ngm:sc-platform-and-environment ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:demand-forecasting ;
vc:relatedTo ngm:time-series-forecasting ;
vc:slug "demand-planning" ;
vc:sourceDomain "supply-chain" .
ngm:demand-response a owl:Class ;
rdfs:comment "Demand response is the deliberate modification of electricity consumption patterns by end users in response to signals from grid operators, energy markets, or automated control systems, with the aim of balancing supply and demand in real time. It enables consumers—from large industrial facilities to domestic smart appliances—to reduce or shift load during peak periods or grid stress events in exchange for financial incentives or reduced tariffs. Demand response programmes are a cornerstone of smart grid operation, deferring or avoiding costly investment in peak generation capacity. Increasingly, AI-driven automation and IoT sensor networks enable fine-grained, real-time demand response at residential scale without requiring manual intervention from end users."@en ;
rdfs:label "Demand Response"@en ;
rdfs:subClassOf ngm:smart-grid ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:distributed-systems ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:contrastsWith ngm:peaking-power-plant ;
vc:dependsOn ngm:energy-aggregator ;
vc:dependsOn ngm:smart-grid ;
vc:enables ngm:grid-stability ;
vc:enables ngm:power-efficient-ai ;
vc:enables ngm:renewable-energy-certificates ;
vc:enables ngm:vehicle-to-grid ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:electricity-market ;
vc:relatedTo ngm:energy-and-power ;
vc:relatedTo ngm:industrial-io-t ;
vc:relatedTo ngm:load-balancing ;
vc:relatedTo ngm:peak-load-management ;
vc:relatedTo ngm:power-management ;
vc:relatedTo ngm:virtual-power-plant ;
vc:requires ngm:grid-communication-protocol ;
vc:requires ngm:smart-meter ;
vc:slug "demand-response" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:carbon-emissions-reduction ;
vc:supports ngm:machine-to-machine-payments ;
vc:supports ngm:renewable-energy-integration ;
vc:uses ngm:advanced-metering-infrastructure ;
vc:uses ngm:io-t-ai-integration ;
vc:uses ngm:io-t-sensor-network ;
vc:uses ngm:real-time-pricing ;
vc:uses ngm:reinforcement-learning .
ngm:demand-response-mining a owl:Class ;
rdfs:comment "Demand response mining is the practice of operating cryptocurrency miners as a flexible, interruptible electrical load that ramps up or down in response to grid conditions and price signals. Miners absorb surplus or stranded generation and shut off during peak demand, helping balance the grid while monetising otherwise curtailed energy. It is studied as both a grid-stabilisation tool and a mitigation for the environmental criticism of proof-of-work mining."@en ;
rdfs:label "Demand Response Mining"@en ;
rdfs:subClassOf ngm:sustainability ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:bitcoin-proof-of-work-protocol-environmental-issues ;
vc:relatedTo ngm:stranded-energy-monetisation ;
vc:slug "demand-response-mining" ;
vc:sourceDomain "blockchain" .
ngm:demand-side-response a owl:Class ;
rdfs:comment "Demand-side response is the adjustment of electricity consumption by end users in reaction to grid signals, time-of-use tariffs, or scarcity events, rather than altering generation. Smart-home and building automation systems shift or curtail loads such as heating, EV charging, and appliances to flatten peaks and exploit cheap or low-carbon periods. It improves grid reliability and lets consumers reduce energy cost and carbon footprint."@en ;
rdfs:label "Demand-Side Response"@en ;
rdfs:subClassOf ngm:sustainability ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:home-assistant ;
vc:slug "demand-side-response" ;
vc:sourceDomain "infrastructure" .
ngm:dematerialised-book-entry a skos:Concept ;
rdfs:label "Dematerialised Book Entry"@en .
ngm:dementia-engagement a skos:Concept ;
rdfs:label "Dementia Engagement"@en .
ngm:democracyos a skos:Concept ;
rdfs:label "Democracyos"@en .
ngm:democracyos-platform a skos:Concept ;
rdfs:label "Democracyos Platform"@en .
ngm:democratic-deliberation a skos:Concept ;
rdfs:label "Democratic Deliberation"@en .
ngm:democratic-engagement a owl:Class ;
rdfs:comment "Democratic Engagement refers to the mechanisms, platforms, and practices through which citizens and communities participate in governance decisions, policy formation, and collective sense-making, including via digital and virtual channels. In metaverse and telecollaboration contexts, democratic engagement encompasses online deliberation tools, DAO-based governance, participatory spatial environments, and AI-assisted facilititation of broad-based civic participation."@en ;
rdfs:label "Democratic Engagement"@en ;
rdfs:subClassOf ngm:metaverse-and-telecollaboration ;
rdfs:subClassOf ngm:sc-governance-and-safety ;
skos:broader ngm:sc-governance-and-safety ;
vc:bridgesTo ngm:telecollaboration ;
vc:enables ngm:democratic-governance ;
vc:enables ngm:democratic-participation ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:platform-governance ;
vc:slug "democratic-engagement" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:ai-governance ;
vc:supports ngm:democratic-values ;
vc:uses ngm:digital-platform ;
vc:uses ngm:telecollaboration .
ngm:democratic-governance a owl:Class ;
rdfs:comment "The exercise of collective decision-making through participatory, accountable, and transparent processes in which stakeholders deliberate and vote on rules and resource allocation; in digital and blockchain contexts it encompasses DAO voting, token-weighted and one-person-one-vote mechanisms, and community oversight of platforms and protocols."@en ;
rdfs:label "Democratic Governance"@en ;
rdfs:subClassOf ngm:infra-legal-and-regulatory ;
rdfs:subClassOf _:r7678 ;
rdfs:subClassOf _:r7679 ;
skos:broader ngm:infra-legal-and-regulatory ;
vc:bridgesTo ngm:blockchain ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:regulatory-framework ;
vc:hasPart ngm:voting-mechanism ;
vc:qualityScore "0.35"^^xsd:float ;
vc:relatedTo ngm:dao-governance ;
vc:relatedTo ngm:decentralized-governance ;
vc:slug "democratic-governance" ;
vc:sourceDomain "infrastructure" .
ngm:democratic-participation a owl:Class ;
rdfs:comment "The mechanisms and systems enabling citizens to engage in collective decision-making processes within virtual environments, digital governance platforms, and metaverse communities, encompassing voting, deliberation, and civic engagement through immersive technologies and decentralized governance ..."@en ;
rdfs:label "Democratic Participation"@en ;
rdfs:subClassOf ngm:digital-governance ;
rdfs:subClassOf ngm:sc-governance-and-safety ;
rdfs:subClassOf _:r7680 ;
rdfs:subClassOf _:r7681 ;
rdfs:subClassOf _:r7682 ;
skos:broader ngm:sc-governance-and-safety ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:digital-governance ;
vc:enables ngm:civic-participation ;
vc:enables ngm:community-decision-making ;
vc:enables ngm:virtual-voting ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:governance-framework ;
vc:requires ngm:identity-verification ;
vc:requires ngm:voting-systems ;
vc:slug "democratic-participation" ;
vc:sourceDomain "spatial-computing" .
ngm:democratic-resilience a skos:Concept ;
rdfs:label "Democratic Resilience"@en .
ngm:democratic-resource-allocation a skos:Concept ;
rdfs:label "Democratic Resource Allocation"@en .
ngm:democratic-values a owl:Class ;
rdfs:comment "Principles and practices of democratic governance—including pluralism, participatory decision-making, transparent governance, electoral integrity, free formation of political will, and protection of civic space—which AI systems and digital platforms should respect and strengthen rather than undermine. As codified in the OECD AI Principles 2024 and the EU AI Act, these values impose specific constraints on AI deployment in electoral, civic, and public-interest contexts."@en ;
rdfs:label "Democratic Values"@en ;
rdfs:subClassOf ngm:infra-legal-and-regulatory ;
rdfs:subClassOf ngm:policy-enforcement ;
skos:broader ngm:infra-legal-and-regulatory ;
vc:contrastsWith ngm:attack-vector ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:democratic-governance ;
vc:relatedTo ngm:eu-ai-act-regulatory-instrument ;
vc:relatedTo ngm:privacy ;
vc:slug "democratic-values" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:accountability ;
vc:supports ngm:governance ;
vc:supports ngm:transparency .
ngm:democratised-deep-learning a skos:Concept ;
rdfs:label "Democratised Deep Learning"@en .
ngm:democratised-ml-development a skos:Concept ;
rdfs:label "Democratised ML Development"@en .
ngm:democratized-investment a skos:Concept ;
rdfs:label "Democratized Investment"@en .
ngm:demographic-parity a owl:Class ;
rdfs:comment "Demographic parity is a group-fairness criterion requiring that a model's positive prediction rate be equal across protected groups, independent of the true label. Also called statistical parity, it is satisfied when the probability of a favourable decision does not depend on membership of a protected attribute such as gender or ethnicity. It is one of several formal, often mutually incompatible, definitions of algorithmic fairness."@en ;
rdfs:label "Demographic Parity"@en ;
rdfs:subClassOf ngm:algorithmic-fairness ;
rdfs:subClassOf _:r7683 ;
rdfs:subClassOf _:r7684 ;
vc:bridgesTo ngm:disparate-impact ;
vc:contrastsWith ngm:accuracy ;
vc:dependsOn ngm:classification ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:classification ;
vc:implements ngm:algorithmic-fairness ;
vc:isPartOf ngm:fairness ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:bias ;
vc:relatedTo ngm:disparate-impact ;
vc:relatedTo ngm:responsible-ai ;
vc:relatedTo ngm:transparency ;
vc:requires ngm:model-evaluation ;
vc:slug "demographic-parity" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:fairness ;
vc:uses ngm:model-evaluation .
ngm:demographic-performance-analysis a skos:Concept ;
rdfs:label "Demographic Performance Analysis"@en .
ngm:demonstration-content-curation-tag a owl:Class ;
rdfs:comment "A placeholder tagging concept used within the knowledge graph to label pages or artefacts intended for demonstration purposes. It serves as a lightweight organisational marker allowing authors to filter, surface, or present selected graph nodes during product demonstrations or stakeholder presentations without altering the underlying ontological structure."@en ;
rdfs:label "Demonstration Content Curation Tag"@en ;
rdfs:subClassOf ngm:software-engineering ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.7"^^xsd:float ;
vc:relatedTo ngm:generative-ai ;
vc:relatedTo ngm:knowledge-graph ;
vc:relatedTo ngm:large-language-models ;
vc:slug "demonstration-content-curation-tag" ;
vc:sourceDomain "infrastructure" ;
vc:uses ngm:software-engineering .
ngm:demonstration-data a skos:Concept ;
rdfs:label "Demonstration Data"@en .
ngm:demonstration-selection a skos:Concept ;
rdfs:label "Demonstration Selection"@en .
ngm:demonstrator a skos:Concept ;
rdfs:label "Demonstrator"@en .
ngm:demosaicing a skos:Concept ;
rdfs:label "Demosaicing"@en .
ngm:denavit-hartenberg-parameters a owl:Class ;
rdfs:comment "Denavit-Hartenberg (DH) parameters are a standardised four-parameter convention for describing the relative geometry between consecutive links of a robotic manipulator. Each joint is characterised by link length, link twist, link offset, and joint angle, yielding a homogeneous transformation matrix per joint. Chaining these matrices gives a compact, systematic model of the arm's kinematics."@en ;
rdfs:label "Denavit-Hartenberg Parameters"@en ;
rdfs:subClassOf ngm:control-theory ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:forward-kinematics ;
vc:relatedTo ngm:kinematics-model ;
vc:slug "denavit-hartenberg-parameters" ;
vc:sourceDomain "robotics" .
ngm:deniable-authentication a skos:Concept ;
rdfs:label "Deniable Authentication"@en .
ngm:denial-of-service a skos:Concept ;
rdfs:label "Denial Of Service"@en .
ngm:denial-of-service-protection a skos:Concept ;
rdfs:label "Denial Of Service Protection"@en .
ngm:deno a skos:Concept ;
rdfs:label "Deno"@en .
ngm:denoiser a skos:Concept ;
rdfs:label "Denoiser"@en .
ngm:denoising a skos:Concept ;
rdfs:label "Denoising"@en .
ngm:denoising-diffusion-probabilistic-models a skos:Concept ;
rdfs:label "Denoising Diffusion Probabilistic Models"@en .
ngm:denoising-network a skos:Concept ;
rdfs:label "Denoising Network"@en .
ngm:denoising-objective a skos:Concept ;
rdfs:label "Denoising Objective"@en .
ngm:denoising-score-matching a owl:Class ;
rdfs:comment "Denoising score matching is a training objective for learning the score function, the gradient of the log probability density, of a data distribution. Rather than estimating the score directly, it perturbs data with known Gaussian noise and trains a model to predict the noise, which is equivalent to estimating the score of the noise-perturbed distribution. This objective avoids the intractable normalising constant of energy-based models and underpins score-based generative models and diffusion models, where the learned score guides iterative sampling from noise back to data."@en ;
rdfs:label "Denoising Score Matching"@en ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:generative-model ;
rdfs:subClassOf _:r7685 ;
rdfs:subClassOf _:r7686 ;
rdfs:subClassOf _:r7687 ;
skos:broader ngm:ai-technique ;
vc:bridgesTo ngm:deep-learning ;
vc:contrastsWith ngm:vae ;
vc:dependsOn ngm:stochastic-differential-equation ;
vc:enables ngm:diffusion-model ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:sampling ;
vc:implements ngm:generative-model ;
vc:isPartOf ngm:diffusion-model ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:diffusion-model ;
vc:relatedTo ngm:markov-chain ;
vc:relatedTo ngm:probabilistic-model ;
vc:requires ngm:probability-distribution ;
vc:requires ngm:stochastic-process ;
vc:slug "denoising-score-matching" ;
vc:sourceDomain "artificial-intelligence" ;
vc:supports ngm:deep-learning ;
vc:uses ngm:gradient-descent ;
vc:uses ngm:neural-network .
ngm:dense-3d-reconstruction a skos:Concept ;
rdfs:label "Dense 3d Reconstruction"@en .
ngm:dense-inference a skos:Concept ;
rdfs:label "Dense Inference"@en .
ngm:dense-model-training a skos:Concept ;
rdfs:label "Dense Model Training"@en .
ngm:dense-passage-retrieval a owl:Class ;
rdfs:comment "Dense Passage Retrieval (DPR) is an information retrieval approach in which both queries and document passages are encoded into dense continuous vector representations using dual-encoder neural networks, enabling similarity search via dot-product or cosine distance rather than sparse lexical matching. It substantially outperforms traditional BM25 retrieval on semantic matching tasks and forms the retriever component of open-domain question-answering and retrieval-augmented generation systems."@en ;
rdfs:label "Dense Passage Retrieval"@en ;
rdfs:subClassOf ngm:ance ;
rdfs:subClassOf ngm:bge-m3 ;
rdfs:subClassOf ngm:bi-encoder-retrieval ;
rdfs:subClassOf ngm:colbert ;
rdfs:subClassOf ngm:drqa ;
rdfs:subClassOf ngm:e5-embedding ;
rdfs:subClassOf ngm:hybrid-retrieval ;
rdfs:subClassOf ngm:information-retrieval ;
rdfs:subClassOf ngm:neural-information-retrieval ;
rdfs:subClassOf ngm:orqa ;
rdfs:subClassOf ngm:realm ;
rdfs:subClassOf ngm:semantic-search ;
rdfs:subClassOf ngm:splade ;
rdfs:subClassOf _:r7688 ;
rdfs:subClassOf _:r7689 ;
rdfs:subClassOf _:r7690 ;
rdfs:subClassOf _:r7691 ;
rdfs:subClassOf _:r7692 ;
rdfs:subClassOf _:r7693 ;
rdfs:subClassOf _:r7694 ;
rdfs:subClassOf _:r7695 ;
rdfs:subClassOf _:r7696 ;
vc:contrastsWith ngm:bm25 ;
vc:contrastsWith ngm:closed-book-generation ;
vc:contrastsWith ngm:colbert ;
vc:contrastsWith ngm:cross-encoder ;
vc:contrastsWith ngm:sparse-retrieval ;
vc:contrastsWith ngm:splade ;
vc:contrastsWith ngm:tf-idf ;
vc:dependsOn ngm:backpropagation ;
vc:dependsOn ngm:bert ;
vc:dependsOn ngm:contrastive-learning ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:embedding-space ;
vc:dependsOn ngm:gpu-compute ;
vc:dependsOn ngm:natural-language-processing ;
vc:enables ngm:document-retrieval ;
vc:enables ngm:fact-checking ;
vc:enables ngm:hallucination-reduction ;
vc:enables ngm:knowledge-intensive-nlp ;
vc:enables ngm:open-domain-qa ;
vc:enables ngm:question-answering ;
vc:enables ngm:retrieval-augmented-generation ;
vc:enables ngm:semantic-search ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:contrastive-training ;
vc:hasPart ngm:faiss-index ;
vc:hasPart ngm:hard-negative-mining ;
vc:hasPart ngm:in-batch-negative-sampling ;
vc:hasPart ngm:offline-indexing-pipeline ;
vc:hasPart ngm:online-retrieval-service ;
vc:hasPart ngm:passage-encoder ;
vc:hasPart ngm:query-encoder ;
vc:implements ngm:bi-encoder-architecture ;
vc:implements ngm:contrastive-learning ;
vc:implements ngm:in-batch-negative-training ;
vc:implements ngm:maximum-inner-product-search ;
vc:implements ngm:offline-index-online-serve-pattern ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:atlas ;
vc:relatedTo ngm:embedding-layer ;
vc:relatedTo ngm:embedding-search ;
vc:relatedTo ngm:fusionindecoder ;
vc:relatedTo ngm:knowledge-graph ;
vc:relatedTo ngm:language-model ;
vc:relatedTo ngm:question-answering ;
vc:relatedTo ngm:retrieval-augmented-generation ;
vc:relatedTo ngm:semantic-segmentation ;
vc:relatedTo ngm:semantic-web-linked-data-standard ;
vc:relatedTo ngm:transformer-architecture ;
vc:relatedTo ngm:vector-database ;
vc:requires ngm:bert ;
vc:requires ngm:contrastive-learning ;
vc:requires ngm:embedding-model ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:nearest-neighbor-search ;
vc:requires ngm:training-dataset ;
vc:requires ngm:transformer-architecture ;
vc:requires ngm:vector-database ;
vc:slug "dense-passage-retrieval" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:beir-benchmark ;
vc:standardizedBy ngm:kilt-benchmark ;
vc:standardizedBy ngm:ms-marco ;
vc:standardizedBy ngm:natural-questions ;
vc:standardizedBy ngm:trec-deep-learning-track ;
vc:supports ngm:clinical-decision-support ;
vc:supports ngm:code-search ;
vc:supports ngm:dialogue-systems ;
vc:supports ngm:knowledge-management ;
vc:supports ngm:legal-research ;
vc:supports ngm:open-domain-question-answering ;
vc:supports ngm:retrieval-augmented-generation ;
vc:uses ngm:bm25 ;
vc:uses ngm:cross-encoder-reranking ;
vc:uses ngm:dot-product-similarity ;
vc:uses ngm:embedding ;
vc:uses ngm:faiss ;
vc:uses ngm:hnsw-index ;
vc:uses ngm:ivf-index ;
vc:uses ngm:natural-language-processing ;
vc:uses ngm:transformer ;
vc:uses ngm:vector-database .
ngm:dense-prediction a skos:Concept ;
rdfs:label "Dense Prediction"@en .
ngm:dense-retrieval a owl:Class ;
rdfs:comment "Dense retrieval is an information-retrieval method that encodes queries and documents into dense vector embeddings and ranks results by vector similarity rather than lexical term overlap. A learned bi-encoder maps text into a shared semantic space so that conceptually related items are close even without shared keywords. It underpins semantic search and retrieval-augmented generation, often paired with approximate nearest-neighbour indexes for scale."@en ;
rdfs:label "Dense Retrieval"@en ;
rdfs:subClassOf ngm:embedding-search ;
rdfs:subClassOf ngm:information-retrieval ;
rdfs:subClassOf ngm:neural-information-retrieval ;
rdfs:subClassOf ngm:semantic-search ;
rdfs:subClassOf _:r7697 ;
rdfs:subClassOf _:r7698 ;
rdfs:subClassOf _:r7699 ;
rdfs:subClassOf _:r7700 ;
rdfs:subClassOf _:r7701 ;
rdfs:subClassOf _:r7702 ;
rdfs:subClassOf _:r7703 ;
rdfs:subClassOf _:r7704 ;
rdfs:subClassOf _:r7705 ;
rdfs:subClassOf _:r7706 ;
rdfs:subClassOf _:r7707 ;
vc:contrastsWith ngm:bm25 ;
vc:contrastsWith ngm:inverted-index ;
vc:contrastsWith ngm:keyword-search ;
vc:contrastsWith ngm:sparse-retrieval ;
vc:contrastsWith ngm:tf-idf ;
vc:dependsOn ngm:contrastive-learning ;
vc:dependsOn ngm:embedding-model ;
vc:dependsOn ngm:hnsw-index ;
vc:dependsOn ngm:transformer-architecture ;
vc:dependsOn ngm:vector-database ;
vc:enables ngm:agentic-rag ;
vc:enables ngm:cross-modal-retrieval ;
vc:enables ngm:document-retrieval ;
vc:enables ngm:hybrid-retrieval ;
vc:enables ngm:knowledge-retrieval ;
vc:enables ngm:question-answering ;
vc:enables ngm:retrieval-augmented-generation ;
vc:enables ngm:semantic-search ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:bi-encoder ;
vc:hasPart ngm:contrastive-learning ;
vc:hasPart ngm:embedding-model ;
vc:hasPart ngm:hard-negative-mining ;
vc:hasPart ngm:hnsw-index ;
vc:hasPart ngm:nearest-neighbor-search ;
vc:hasPart ngm:vector-database ;
vc:implements ngm:contrastive-learning ;
vc:implements ngm:embedding-search ;
vc:implements ngm:nearest-neighbor-search ;
vc:implements ngm:semantic-search ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:agentic-rag ;
vc:relatedTo ngm:bm25 ;
vc:relatedTo ngm:colbert ;
vc:relatedTo ngm:contrastive-learning ;
vc:relatedTo ngm:cross-encoder-reranking ;
vc:relatedTo ngm:dense-passage-retrieval ;
vc:relatedTo ngm:document-retrieval ;
vc:relatedTo ngm:embedding-model ;
vc:relatedTo ngm:embedding-search ;
vc:relatedTo ngm:hnsw-index ;
vc:relatedTo ngm:hybrid-retrieval ;
vc:relatedTo ngm:question-answering ;
vc:relatedTo ngm:retrieval-augmented-generation ;
vc:relatedTo ngm:semantic-search ;
vc:relatedTo ngm:splade ;
vc:relatedTo ngm:vector-database ;
vc:requires ngm:contrastive-learning ;
vc:requires ngm:gpu-compute ;
vc:requires ngm:nearest-neighbor-search ;
vc:requires ngm:training-data ;
vc:requires ngm:transformer-architecture ;
vc:requires ngm:vector-database ;
vc:slug "dense-retrieval" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:beir-benchmark ;
vc:standardizedBy ngm:ms-marco ;
vc:standardizedBy ngm:mteb-leaderboard ;
vc:standardizedBy ngm:trec-deep-learning-track ;
vc:supports ngm:agentic-rag ;
vc:supports ngm:cross-encoder-reranking ;
vc:supports ngm:hybrid-retrieval ;
vc:supports ngm:large-language-models ;
vc:supports ngm:question-answering ;
vc:supports ngm:retrieval-augmented-generation ;
vc:uses ngm:contrastive-learning ;
vc:uses ngm:embedding-model ;
vc:uses ngm:hnsw-index ;
vc:uses ngm:nearest-neighbor-search ;
vc:uses ngm:transformer-architecture ;
vc:uses ngm:vector-database .
ngm:density-based-clustering a skos:Concept ;
rdfs:label "Density Based Clustering"@en .
ngm:density-estimation a owl:Class ;
rdfs:comment "Density estimation is the statistical problem of inferring the underlying probability density function of a random variable from a finite set of observed samples. Parametric approaches assume a fixed functional form whose parameters are fitted by maximum likelihood, while non-parametric approaches such as kernel density estimation and histograms make minimal distributional assumptions. Modern deep density estimation uses normalizing flows, autoregressive models, and variational methods to model complex high-dimensional distributions, making it foundational to generative modelling, anomaly detection, and unsupervised learning."@en ;
rdfs:label "Density Estimation"@en ;
rdfs:subClassOf ngm:statistics ;
rdfs:subClassOf _:r7708 ;
vc:contrastsWith ngm:supervised-learning ;
vc:enables ngm:anomaly-detection ;
vc:enables ngm:generative-model ;
vc:enables ngm:outlier-detection ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:kernel-density-estimation ;
vc:hasPart ngm:maximum-likelihood-estimation ;
vc:implements ngm:gaussian-mixture-model ;
vc:implements ngm:normalising-flow ;
vc:isPartOf ngm:unsupervised-learning ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:entropy ;
vc:relatedTo ngm:information-theory ;
vc:relatedTo ngm:vae ;
vc:slug "density-estimation" ;
vc:sourceDomain "machine-learning" ;
vc:uses ngm:maximum-likelihood-estimation ;
vc:uses ngm:probability-distribution ;
vc:uses ngm:sampling .
ngm:density-weighted-methods a skos:Concept ;
rdfs:label "Density Weighted Methods"@en .
ngm:deontic-modality a skos:Concept ;
rdfs:label "Deontic Modality"@en .
ngm:deorbiting a owl:Class ;
rdfs:label "Deorbiting"@en ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:orbital-dynamics ;
vc:slug "deorbiting" ;
vc:sourceDomain "space-science-and-systems" .
ngm:depalletising a skos:Concept ;
rdfs:label "Depalletising"@en .
ngm:department-for-science-innovation-and-technology a skos:Concept ;
rdfs:label "Department For Science Innovation And Technology"@en .
ngm:department-of-computing a skos:Concept ;
rdfs:label "Department Of Computing"@en .
ngm:department-of-health-and-human-services a skos:Concept ;
rdfs:label "Department Of Health And Human Services"@en .
ngm:department-of-industry-science-and-resources a skos:Concept ;
rdfs:label "Department Of Industry Science And Resources"@en .
ngm:department-of-informatics a skos:Concept ;
rdfs:label "Department Of Informatics"@en .
ngm:dependency-graph a owl:Class ;
rdfs:comment "A dependency graph is a directed graph in which nodes represent build artefacts, assets or tasks and edges represent a requires-before relationship between them. Traversing the graph in topological order determines a valid build or execution sequence and reveals cycles that would otherwise deadlock a pipeline. Asset and content pipelines rely on dependency graphs to determine what must be rebuilt when a source file changes."@en ;
rdfs:label "Dependency Graph"@en ;
rdfs:subClassOf ngm:graph-theory ;
vc:enables ngm:asset-pipeline ;
vc:enables ngm:content-pipeline ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:graph-theory ;
vc:qualityScore "0.55"^^xsd:float ;
vc:slug "dependency-graph" ;
vc:sourceDomain "data" .
ngm:dependency-injection a skos:Concept ;
rdfs:label "Dependency Injection"@en .
ngm:dependency-parsing a skos:Concept ;
rdfs:label "Dependency Parsing"@en .
ngm:depin a skos:Concept ;
rdfs:label "Depin"@en .
ngm:deployer a owl:Class ;
rdfs:comment "A Deployer, as defined in EU AI Act Article 3(4), is a natural or legal person, public authority, agency, or other body that uses an AI system under its authority in a professional context. Deployers bear obligations for human oversight, input data monitoring, logging, and fundamental rights impact assessments for high-risk AI systems. They are distinct from providers (who develop or place AI systems on the market) and incur provider-level obligations if they substantially modify an AI system."@en ;
rdfs:label "Deployer"@en ;
rdfs:subClassOf ngm:digital-infrastructure ;
rdfs:subClassOf ngm:software-engineering ;
vc:dependsOn ngm:ai-governance ;
vc:dependsOn ngm:digital-infrastructure ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:ai-governance-and-ethics ;
vc:slug "deployer" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:ai-regulation ;
vc:uses ngm:ai-agent-system ;
vc:uses ngm:autonomous-robot .
ngm:deployment-artifact a skos:Concept ;
rdfs:label "Deployment Artifact"@en .
ngm:deployment-context a skos:Concept ;
rdfs:label "Deployment Context"@en .
ngm:deployment-decision-making a skos:Concept ;
rdfs:label "Deployment Decision Making"@en .
ngm:deployment-diagram a skos:Concept ;
rdfs:label "Deployment Diagram"@en .
ngm:deployment-flexibility a skos:Concept ;
rdfs:label "Deployment Flexibility"@en .
ngm:deployment-infrastructure a skos:Concept ;
rdfs:label "Deployment Infrastructure"@en .
ngm:deployment-policy a skos:Concept ;
rdfs:label "Deployment Policy"@en .
ngm:deployment-scripting a skos:Concept ;
rdfs:label "Deployment Scripting"@en .
ngm:deployment-unit a skos:Concept ;
rdfs:label "Deployment Unit"@en .
ngm:deposit-insurance a skos:Concept ;
rdfs:label "Deposit Insurance"@en .
ngm:deposit-return-scheme a owl:Class ;
rdfs:comment "A deposit return scheme is a circular-economy mechanism in which consumers pay a small refundable deposit on a beverage container at purchase and reclaim it on returning the empty for recycling or reuse. The financial incentive drives high collection rates and clean material streams, reducing litter and supporting closed-loop recycling. It is a recognised instrument of reverse logistics and extended producer responsibility."@en ;
rdfs:label "Deposit Return Scheme"@en ;
rdfs:subClassOf ngm:sustainability ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:circular-economy ;
vc:relatedTo ngm:reverse-logistics ;
vc:slug "deposit-return-scheme" ;
vc:sourceDomain "supply-chain" .
ngm:deprecation a skos:Concept ;
rdfs:label "Deprecation"@en .
ngm:depth-anything a skos:Concept ;
rdfs:label "Depth Anything"@en .
ngm:depth-buffer a owl:Class ;
rdfs:comment "A depth buffer (also called a z-buffer) is a per-pixel array maintained during rasterised rendering that stores the depth of the nearest surface drawn at each screen position. As fragments are generated, their interpolated depth is compared against the stored value, and only fragments closer to the camera overwrite the colour and depth, resolving visibility automatically. The depth buffer is the standard hidden-surface-removal mechanism in real-time graphics pipelines."@en ;
rdfs:label "Depth Buffer"@en ;
rdfs:subClassOf ngm:rendering-pipeline ;
rdfs:subClassOf _:r7709 ;
rdfs:subClassOf _:r7710 ;
rdfs:subClassOf _:r7711 ;
vc:contrastsWith ngm:ray-tracing ;
vc:enables ngm:occlusion-culling ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:texture-mapping ;
vc:isPartOf ngm:graphics-pipeline ;
vc:isPartOf ngm:rendering-pipeline ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:gpu ;
vc:relatedTo ngm:spatial-computing ;
vc:relatedTo ngm:texture-mapping ;
vc:requires ngm:gpu ;
vc:requires ngm:rasterization ;
vc:slug "depth-buffer" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:computer-graphics ;
vc:uses ngm:gpu-acceleration .
ngm:depth-camera a owl:Class ;
rdfs:comment "A depth camera is a sensor that captures, for each pixel, the distance from the camera to objects in the scene, producing a depth map or 3D point cloud rather than only colour intensity. Common operating principles include structured light, time-of-flight, and stereo disparity, often combined with a colour stream to yield RGB-D data. Depth cameras are foundational sensors for spatial perception, enabling reconstruction, mapping, and interaction with three-dimensional environments."@en ;
rdfs:label "Depth Camera"@en ;
rdfs:subClassOf ngm:camera ;
rdfs:subClassOf _:r7712 ;
vc:bridgesTo ngm:computer-vision ;
vc:contrastsWith ngm:lidar ;
vc:enables ngm:depth-sensing ;
vc:enables ngm:point-cloud ;
vc:enables ngm:spatial-mapping ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:sensor ;
vc:isPartOf ngm:perception ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:mapping ;
vc:relatedTo ngm:object-detection ;
vc:relatedTo ngm:photogrammetry ;
vc:requires ngm:calibration ;
vc:slug "depth-camera" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:augmented-reality ;
vc:supports ngm:gesture-recognition ;
vc:supports ngm:slam ;
vc:uses ngm:stereo-vision ;
vc:uses ngm:structured-light .
ngm:depth-completion a skos:Concept ;
rdfs:label "Depth Completion"@en .
ngm:depth-controlled-synthesis a skos:Concept ;
rdfs:label "Depth Controlled Synthesis"@en .
ngm:depth-estimation a owl:Class ;
rdfs:comment "Depth Estimation is the computer vision task of recovering per-pixel distance from a camera (or a virtual viewpoint) to the surfaces of a 3D scene, producing a depth map D(u,v) ∈ ℝ⁺ aligned to an image I(u,v) that encodes scene geometry needed for 3D reconstruction, robotic perception, augmented-..."@en ;
rdfs:label "Depth Estimation"@en ;
rdfs:subClassOf ngm:3-d-perception ;
rdfs:subClassOf ngm:ai-technique ;
rdfs:subClassOf ngm:computer-vision ;
rdfs:subClassOf ngm:dense-prediction ;
rdfs:subClassOf ngm:geometric-vision ;
rdfs:subClassOf ngm:scene-understanding ;
rdfs:subClassOf _:r7713 ;
rdfs:subClassOf _:r7714 ;
rdfs:subClassOf _:r7715 ;
rdfs:subClassOf _:r7716 ;
rdfs:subClassOf _:r7717 ;
rdfs:subClassOf _:r7718 ;
rdfs:subClassOf _:r7719 ;
rdfs:subClassOf _:r7720 ;
rdfs:subClassOf _:r7721 ;
rdfs:subClassOf _:r7722 ;
rdfs:subClassOf _:r7723 ;
rdfs:subClassOf _:r7724 ;
rdfs:subClassOf _:r7725 ;
skos:broader ngm:ai-technique ;
vc:contrastsWith ngm:3-d-reconstruction ;
vc:contrastsWith ngm:optical-flow ;
vc:contrastsWith ngm:pose-estimation ;
vc:contrastsWith ngm:semantic-segmentation ;
vc:contrastsWith ngm:surface-normal-estimation ;
vc:dependsOn ngm:bundle-adjustment ;
vc:dependsOn ngm:convolutional-neural-network ;
vc:dependsOn ngm:diffusion-models ;
vc:dependsOn ngm:epipolar-geometry ;
vc:dependsOn ngm:photometric-consistency ;
vc:dependsOn ngm:vision-transformers ;
vc:enables ngm:3-d-reconstruction ;
vc:enables ngm:ar-occlusion ;
vc:enables ngm:bokeh-rendering ;
vc:enables ngm:free-space-estimation ;
vc:enables ngm:grasp-planning ;
vc:enables ngm:novel-view-synthesis ;
vc:enables ngm:obstacle-avoidance ;
vc:enables ngm:visual-slam ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:camera-extrinsics ;
vc:hasPart ngm:camera-intrinsics ;
vc:hasPart ngm:cost-volume ;
vc:hasPart ngm:depth-map ;
vc:hasPart ngm:disparity-map ;
vc:hasPart ngm:epipolar-geometry ;
vc:hasPart ngm:loss-function ;
vc:hasPart ngm:point-cloud ;
vc:implements ngm:block-matching ;
vc:implements ngm:depth-anything ;
vc:implements ngm:dpt ;
vc:implements ngm:marigold ;
vc:implements ngm:midas ;
vc:implements ngm:monodepth ;
vc:implements ngm:multi-view-stereo ;
vc:implements ngm:psmnet ;
vc:implements ngm:semi-global-matching ;
vc:implements ngm:stereo-vision ;
vc:implements ngm:structure-from-motion ;
vc:implements ngm:zoedepth ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:3-d-gaussian-splatting ;
vc:relatedTo ngm:depth-completion ;
vc:relatedTo ngm:ne-rf ;
vc:relatedTo ngm:object-detection ;
vc:relatedTo ngm:photogrammetry ;
vc:relatedTo ngm:visual-slam ;
vc:requires ngm:camera-calibration ;
vc:requires ngm:feature-matching ;
vc:requires ngm:image-pair ;
vc:requires ngm:loss-function ;
vc:requires ngm:optimisation ;
vc:requires ngm:training-data ;
vc:slug "depth-estimation" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:da-2k ;
vc:standardizedBy ngm:eth3d ;
vc:standardizedBy ngm:kitti-benchmark ;
vc:standardizedBy ngm:nyu-depth-v2 ;
vc:standardizedBy ngm:scannet ;
vc:standardizedBy ngm:sintel ;
vc:standardizedBy ngm:stereo-vision ;
vc:supports ngm:arcore ;
vc:supports ngm:arkit ;
vc:supports ngm:autonomous-driving ;
vc:supports ngm:digital-twin ;
vc:supports ngm:robotic-manipulation ;
vc:supports ngm:slam ;
vc:supports ngm:telepresence ;
vc:supports ngm:visual-odometry ;
vc:uses ngm:kinect ;
vc:uses ngm:lidar ;
vc:uses ngm:realsense ;
vc:uses ngm:rgb-d-camera ;
vc:uses ngm:stereo-camera ;
vc:uses ngm:structured-light ;
vc:uses ngm:time-of-flight-sensor .
ngm:depth-first-search a owl:Class ;
rdfs:comment "Depth-first search (DFS) is a graph and tree traversal algorithm that explores as far as possible along each branch before backtracking, following one path to its end before considering alternatives. It is naturally expressed through recursion or an explicit last-in-first-out stack and runs in time linear in the number of vertices and edges. DFS underpins many algorithms including topological sorting, cycle detection, finding connected components and solving maze and constraint problems through systematic backtracking."@en ;
rdfs:label "Depth-First Search"@en ;
rdfs:subClassOf ngm:algorithm ;
rdfs:subClassOf ngm:graph-algorithms ;
rdfs:subClassOf ngm:graph-search ;
rdfs:subClassOf ngm:search-algorithm ;
rdfs:subClassOf _:r7735 ;
rdfs:subClassOf _:r7736 ;
rdfs:subClassOf _:r7737 ;
vc:contrastsWith ngm:a-star-algorithm ;
vc:contrastsWith ngm:breadth-first-search ;
vc:contrastsWith ngm:dijkstra-algorithm ;
vc:contrastsWith ngm:search-algorithm ;
vc:contrastsWith ngm:uniform-cost-search ;
vc:dependsOn ngm:algorithm ;
vc:dependsOn ngm:graph-representation ;
vc:dependsOn ngm:graph-theory ;
vc:dependsOn ngm:stack-data-structure ;
vc:enables ngm:articulation-point-detection ;
vc:enables ngm:biconnected-components ;
vc:enables ngm:constraint-satisfaction ;
vc:enables ngm:cycle-detection ;
vc:enables ngm:formal-verification ;
vc:enables ngm:pathfinding ;
vc:enables ngm:sat-solving ;
vc:enables ngm:strongly-connected-components ;
vc:enables ngm:topological-sort ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:backtracking ;
vc:hasPart ngm:dfs-tree ;
vc:hasPart ngm:edge-classification ;
vc:hasPart ngm:recursion ;
vc:hasPart ngm:stack-data-structure ;
vc:hasPart ngm:visited-set ;
vc:implements ngm:backtracking ;
vc:implements ngm:graph-search ;
vc:implements ngm:search-algorithm ;
vc:implements ngm:spanning-tree-construction ;
vc:isPartOf ngm:graph-algorithms ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:a-star-algorithm ;
vc:relatedTo ngm:ai-search ;
vc:relatedTo ngm:backtracking ;
vc:relatedTo ngm:breadth-first-search ;
vc:relatedTo ngm:computer-science ;
vc:relatedTo ngm:constraint-satisfaction ;
vc:relatedTo ngm:dijkstra-algorithm ;
vc:relatedTo ngm:graph-theory ;
vc:relatedTo ngm:ida-star ;
vc:relatedTo ngm:kosaraju-algorithm ;
vc:relatedTo ngm:search-algorithms ;
vc:relatedTo ngm:strongly-connected-components ;
vc:relatedTo ngm:tarjan-algorithm ;
vc:relatedTo ngm:topological-sort ;
vc:requires ngm:data-structure ;
vc:requires ngm:graph-representation ;
vc:requires ngm:graph-theory ;
vc:requires ngm:stack-data-structure ;
vc:requires ngm:visited-set ;
vc:slug "depth-first-search" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:acm-computing-classification-system ;
vc:standardizedBy ngm:clrs-introduction-to-algorithms ;
vc:supports ngm:ai-search ;
vc:supports ngm:compiler-optimisation ;
vc:supports ngm:constraint-satisfaction ;
vc:supports ngm:formal-verification ;
vc:supports ngm:game-ai ;
vc:supports ngm:knowledge-graph ;
vc:supports ngm:pathfinding ;
vc:supports ngm:topological-sort ;
vc:uses ngm:algorithm ;
vc:uses ngm:backtracking ;
vc:uses ngm:graph-theory ;
vc:uses ngm:recursion ;
vc:uses ngm:stack-data-structure .
ngm:depth-map a owl:Class ;
rdfs:comment "A depth map is a per-pixel image in which each value encodes the distance from the camera to the corresponding point in the scene rather than its colour. It provides the 2.5D geometric structure needed to reconstruct surfaces, segment foreground from background and place virtual content in spatial computing. Depth maps are produced by stereo matching, structured light, time-of-flight sensing or learned monocular estimation."@en ;
rdfs:label "Depth Map"@en ;
rdfs:subClassOf ngm:computer-vision ;
rdfs:subClassOf _:r7726 ;
rdfs:subClassOf _:r7727 ;
vc:bridgesTo ngm:computer-graphics ;
vc:enables ngm:point-cloud ;
vc:enables ngm:volumetric-video ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:point-cloud ;
vc:isPartOf ngm:computer-vision ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:computer-vision ;
vc:relatedTo ngm:stereo-vision ;
vc:relatedTo ngm:volumetric-video ;
vc:requires ngm:depth-sensing ;
vc:slug "depth-map" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:spatial-computing ;
vc:uses ngm:lidar ;
vc:uses ngm:stereo-vision ;
vc:uses ngm:structured-light .
ngm:depth-of-field a skos:Concept ;
rdfs:label "Depth Of Field"@en .
ngm:depth-of-market a skos:Concept ;
rdfs:label "Depth Of Market"@en .
ngm:depth-sensing a owl:Class ;
rdfs:comment "Depth Sensing is the acquisition and processing of per-pixel or per-point distance information from a sensor to surfaces in a scene, yielding depth maps, range images, or 3D point clouds. Hardware modalities include structured light projection, time-of-flight (ToF) imaging, passive and active stereo vision, LiDAR scanning, and monocular depth estimation via machine learning. Depth sensing is a foundational enabling technology for spatial computing, robotic navigation, autonomous vehicles, augmented and mixed reality occlusion, gesture recognition, and 3D scene reconstruction, providing the geometric substrate upon which higher-level understanding is built."@en ;
rdfs:label "Depth Sensing"@en ;
rdfs:subClassOf ngm:sensor-fusion ;
rdfs:subClassOf _:r7728 ;
rdfs:subClassOf _:r7729 ;
rdfs:subClassOf _:r7730 ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:bridgesTo ngm:neural-radiance-field ;
vc:contrastsWith ngm:monocular-depth-estimation ;
vc:enables ngm:3-d-reconstruction ;
vc:enables ngm:augmented-reality ;
vc:enables ngm:gesture-recognition ;
vc:enables ngm:object-detection ;
vc:enables ngm:point-cloud ;
vc:enables ngm:slam ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:computer-vision ;
vc:relatedTo ngm:depth-estimation ;
vc:relatedTo ngm:scene-understanding ;
vc:relatedTo ngm:semantic-segmentation ;
vc:requires ngm:camera-calibration ;
vc:requires ngm:sensor-input ;
vc:requires ngm:signal-processing ;
vc:slug "depth-sensing" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:autonomous-navigation ;
vc:supports ngm:mixed-reality ;
vc:supports ngm:robotics ;
vc:uses ngm:infrared-sensor ;
vc:uses ngm:lidar ;
vc:uses ngm:stereo-camera ;
vc:uses ngm:structured-light ;
vc:uses ngm:time-of-flight-sensor .
ngm:depth-sensor a owl:Class ;
rdfs:comment "A Depth Sensor is a hardware device or sensor modality that measures the distance between the sensor and objects in a scene, producing per-pixel or per-point depth information as its primary output. Operating principles include structured light projection, time-of-flight measurement, stereo vision correlation, and LiDAR pulse ranging. Depth sensors are fundamental components in robotics, augmented and mixed reality, autonomous vehicles, and industrial inspection, providing the three-dimensional scene understanding that colour cameras alone cannot supply. The output is typically represented as a depth map, disparity map, or three-dimensional [[Point Cloud]], forming the input to downstream perception and scene reconstruction pipelines."@en ;
rdfs:label "Depth Sensor"@en ;
rdfs:subClassOf ngm:exteroceptive-sensor ;
rdfs:subClassOf _:r7731 ;
rdfs:subClassOf _:r7732 ;
rdfs:subClassOf _:r7733 ;
rdfs:subClassOf _:r7734 ;
vc:bridgesTo ngm:augmented-reality ;
vc:bridgesTo ngm:spatial-computing ;
vc:contrastsWith ngm:radar-sensor ;
vc:dependsOn ngm:structured-light ;
vc:dependsOn ngm:time-of-flight ;
vc:enables ngm:3-d-reconstruction ;
vc:enables ngm:object-detection ;
vc:enables ngm:obstacle-avoidance ;
vc:enables ngm:simultaneous-localisation-and-mapping ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:image-sensor ;
vc:hasPart ngm:infrared-light-source ;
vc:isPartOf ngm:perception-system ;
vc:isPartOf ngm:sensor-suite ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:depth-estimation ;
vc:relatedTo ngm:depth-map ;
vc:relatedTo ngm:depth-sensing ;
vc:relatedTo ngm:point-cloud ;
vc:relatedTo ngm:scene-understanding ;
vc:requires ngm:camera-calibration ;
vc:requires ngm:sensor-fusion ;
vc:slug "depth-sensor" ;
vc:sourceDomain "robotics" ;
vc:supports ngm:autonomous-robot ;
vc:supports ngm:autonomous-vehicle ;
vc:uses ngm:camera ;
vc:uses ngm:lidar ;
vc:uses ngm:stereo-vision .
ngm:depth-sensor-pose a skos:Concept ;
rdfs:label "Depth Sensor Pose"@en .
ngm:depth-sorting a skos:Concept ;
rdfs:label "Depth Sorting"@en .
ngm:der-encoding a skos:Concept ;
rdfs:label "Der Encoding"@en .
ngm:derandomisation a skos:Concept ;
rdfs:label "Derandomisation"@en .
ngm:deregulation a owl:Class ;
rdfs:comment "Deregulation is the process of removing, reducing, or simplifying government rules and controls that constrain how firms operate in a market, typically to increase competition, lower barriers to entry, and improve economic efficiency. It is the deliberate counterpart to regulation and is often pursued in sectors such as telecommunications, finance, energy, and transport. Deregulation does not mean the absence of oversight but rather a shift toward lighter-touch or market-based governance."@en ;
rdfs:label "Deregulation"@en ;
rdfs:subClassOf ngm:governance ;
vc:bridgesTo ngm:internet-governance ;
vc:contrastsWith ngm:regulation ;
vc:contrastsWith ngm:regulatory-compliance ;
vc:dependsOn ngm:policy ;
vc:enables ngm:telecommunications ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:governance ;
vc:isPartOf ngm:regulation ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:digital-governance ;
vc:relatedTo ngm:digital-regulation ;
vc:relatedTo ngm:financial-regulation ;
vc:relatedTo ngm:governance-framework ;
vc:relatedTo ngm:net-neutrality ;
vc:slug "deregulation" ;
vc:sourceDomain "governance" ;
vc:supports ngm:compliance .
ngm:derivation-chains a skos:Concept ;
rdfs:label "Derivation Chains"@en .
ngm:derivative-control a owl:Class ;
rdfs:comment "Derivative control responds to the rate of change of system error, providing damping that opposes oscillations and improves transient response."@en ;
rdfs:label "Derivative Control"@en ;
rdfs:subClassOf ngm:control-actions ;
rdfs:subClassOf ngm:feedback-control ;
rdfs:subClassOf ngm:pid-control-component ;
rdfs:subClassOf ngm:robo-actuation-and-control ;
rdfs:subClassOf _:r7738 ;
rdfs:subClassOf _:r7739 ;
skos:broader ngm:robo-actuation-and-control ;
vc:bridgesTo ngm:ai-agent-system ;
vc:enables ngm:faster-convergence ;
vc:enables ngm:oscillation-damping ;
vc:enables ngm:reduced-overshoot ;
vc:enables ngm:stability-improvement ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:damping-action ;
vc:hasPart ngm:derivative-gain ;
vc:hasPart ngm:error-rate-measurement ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:error-signal ;
vc:requires ngm:gain-tuning ;
vc:requires ngm:low-pass-filtering ;
vc:requires ngm:time-derivative ;
vc:slug "derivative-control" ;
vc:sourceDomain "robotics" .
ngm:derivative-gain a skos:Concept ;
rdfs:label "Derivative Gain"@en .
ngm:derivatives a skos:Concept ;
rdfs:label "Derivatives"@en .
ngm:derivatives-trading a owl:Class ;
rdfs:comment "Derivatives trading is the buying and selling of financial contracts whose value is derived from an underlying asset, index or rate, such as futures, options, swaps and perpetual contracts. Traders use these instruments to hedge exposure, gain leveraged directional exposure or speculate on price movements without holding the underlying. In decentralised finance, derivatives are implemented through smart contracts that handle margin, settlement and liquidation on-chain."@en ;
rdfs:label "Derivatives Trading"@en ;
rdfs:subClassOf ngm:digital-asset-trading ;
rdfs:subClassOf _:r7740 ;
rdfs:subClassOf _:r7741 ;
rdfs:subClassOf _:r7742 ;
vc:bridgesTo ngm:automated-market-maker ;
vc:bridgesTo ngm:de-fi ;
vc:dependsOn ngm:settlement ;
vc:enables ngm:digital-asset-trading ;
vc:enables ngm:risk-management ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:order-book ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:blockchain ;
vc:relatedTo ngm:digital-asset-trading ;
vc:requires ngm:liquidity-pool ;
vc:requires ngm:settlement ;
vc:slug "derivatives-trading" ;
vc:sourceDomain "blockchain" ;
vc:supports ngm:risk-management ;
vc:uses ngm:order-book ;
vc:uses ngm:smart-contract .
ngm:descript a skos:Concept ;
rdfs:label "Descript"@en .
ngm:description-logic a owl:Class ;
rdfs:comment "A family of formal knowledge representation languages used to describe concepts, roles, and individuals with well-defined model-theoretic semantics, providing decidable fragments of first-order logic tailored to structured knowledge representation and automated reasoning."@en ;
rdfs:label "Description Logic"@en ;
rdfs:subClassOf ngm:ai-research-area ;
rdfs:subClassOf ngm:first-order-logic ;
rdfs:subClassOf ngm:formal-logic ;
rdfs:subClassOf ngm:knowledge-representation ;
rdfs:subClassOf ngm:modal-logic ;
rdfs:subClassOf _:r7743 ;
rdfs:subClassOf _:r7744 ;
rdfs:subClassOf _:r7745 ;
skos:broader ngm:ai-research-area ;
vc:bridgesTo ngm:digital-twin ;
vc:bridgesTo ngm:internet-of-things ;
vc:bridgesTo ngm:large-language-model ;
vc:bridgesTo ngm:linked-data ;
vc:bridgesTo ngm:natural-language-processing ;
vc:bridgesTo ngm:neuro-symbolic-ai ;
vc:contrastsWith ngm:closed-world-assumption ;
vc:contrastsWith ngm:frame-based-representation ;
vc:contrastsWith ngm:horn-logic ;
vc:contrastsWith ngm:probabilistic-logic ;
vc:contrastsWith ngm:relational-database-schema ;
vc:contrastsWith ngm:rule-based-reasoning ;
vc:contrastsWith ngm:semantic-network ;
vc:dependsOn ngm:first-order-logic ;
vc:dependsOn ngm:formal-semantics ;
vc:dependsOn ngm:model-theory ;
vc:dependsOn ngm:set-theory ;
vc:enables ngm:automated-reasoning ;
vc:enables ngm:classification ;
vc:enables ngm:conjunctive-query-answering ;
vc:enables ngm:consistency-checking ;
vc:enables ngm:instance-recognition ;
vc:enables ngm:knowledge-graph ;
vc:enables ngm:ontology-alignment ;
vc:enables ngm:owl ;
vc:enables ngm:semantic-interoperability ;
vc:enables ngm:subsumption-reasoning ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:abox ;
vc:hasPart ngm:alc ;
vc:hasPart ngm:alc-with-transitivity ;
vc:hasPart ngm:concept-constructor ;
vc:hasPart ngm:concrete-domain ;
vc:hasPart ngm:consequence-based-algorithm ;
vc:hasPart ngm:dl-lite ;
vc:hasPart ngm:el ;
vc:hasPart ngm:general-concept-inclusion ;
vc:hasPart ngm:nominals ;
vc:hasPart ngm:number-restriction ;
vc:hasPart ngm:owl-2-el-profile ;
vc:hasPart ngm:owl-2-ql-profile ;
vc:hasPart ngm:owl-2-rl-profile ;
vc:hasPart ngm:role-constructor ;
vc:hasPart ngm:role-hierarchy ;
vc:hasPart ngm:shiq ;
vc:hasPart ngm:sroiq ;
vc:hasPart ngm:subsumption-axiom ;
vc:hasPart ngm:tableau-algorithm ;
vc:hasPart ngm:tbox ;
vc:implements ngm:knowledge-base ;
vc:implements ngm:model-theoretic-semantics ;
vc:implements ngm:ontology ;
vc:implements ngm:open-world-assumption ;
vc:isPartOf ngm:knowledge-representation ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:computational-complexity-theory ;
vc:relatedTo ngm:concept-language ;
vc:relatedTo ngm:description-logic-handbook ;
vc:relatedTo ngm:knowledge-representation-and-reasoning ;
vc:relatedTo ngm:linked-data ;
vc:relatedTo ngm:modal-logic ;
vc:relatedTo ngm:natural-language-processing ;
vc:relatedTo ngm:open-world-assumption ;
vc:relatedTo ngm:rdf ;
vc:relatedTo ngm:sparql ;
vc:relatedTo ngm:tableau-method ;
vc:relatedTo ngm:terminological-logic ;
vc:requires ngm:computational-complexity-theory ;
vc:requires ngm:first-order-logic ;
vc:requires ngm:formal-semantics ;
vc:requires ngm:model-theoretic-semantics ;
vc:requires ngm:model-theory ;
vc:requires ngm:set-theory ;
vc:slug "description-logic" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:iso-iec-jtc1-sc42 ;
vc:standardizedBy ngm:w3-c ;
vc:supports ngm:biomedical-ontology ;
vc:supports ngm:clinical-terminology ;
vc:supports ngm:enterprise-knowledge-graph ;
vc:supports ngm:gene-ontology ;
vc:supports ngm:neuro-symbolic-ai ;
vc:supports ngm:ontology-engineering ;
vc:supports ngm:semantic-web-linked-data-standard ;
vc:supports ngm:snomed-ct ;
vc:uses ngm:elk-reasoner ;
vc:uses ngm:fact-reasoner ;
vc:uses ngm:hermit-reasoner ;
vc:uses ngm:pellet-reasoner ;
vc:uses ngm:prot-g ;
vc:uses ngm:rdf ;
vc:uses ngm:sparql ;
vc:uses ngm:tableau-algorithm ;
vc:uses ngm:whelk-reasoner .
ngm:description-logic-handbook a skos:Concept ;
rdfs:label "Description Logic Handbook"@en .
ngm:descriptive-analytics a skos:Concept ;
rdfs:label "Descriptive Analytics"@en .
ngm:descriptive-complexity a skos:Concept ;
rdfs:label "Descriptive Complexity"@en .
ngm:descriptor-set a skos:Concept ;
rdfs:label "Descriptor Set"@en .
ngm:deserialisation a owl:Class ;
rdfs:comment "The process of reconstructing in-memory data structures or objects from a serialised byte stream or textual encoding such as JSON, XML, or Protocol Buffers, reversing serialisation so that transmitted or persisted state can be used by a running program. Deserialisation must validate structure, types, and bounds of untrusted input, since naive object reconstruction is a well-known source of remote-code-execution vulnerabilities."@en ;
rdfs:label "Deserialisation"@en ;
rdfs:subClassOf ngm:data-format-standard ;
vc:contrastsWith ngm:serialisation ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:data-exchange ;
vc:qualityScore "0.8"^^xsd:float ;
vc:slug "deserialisation" ;
vc:sourceDomain "data" ;
vc:uses ngm:json-data-interchange-format ;
vc:uses ngm:protobuf .
ngm:design a skos:Concept ;
rdfs:label "Design"@en .
ngm:design-collaboration a skos:Concept ;
rdfs:label "Design Collaboration"@en .
ngm:design-data a skos:Concept ;
rdfs:label "Design Data"@en .
ngm:design-database a skos:Concept ;
rdfs:label "Design Database"@en .
ngm:design-operations a skos:Concept ;
rdfs:label "Design Operations"@en .
ngm:design-optimization a skos:Concept ;
rdfs:label "Design Optimization"@en .
ngm:design-optimizer a skos:Concept ;
rdfs:label "Design Optimizer"@en .
ngm:design-pattern a owl:Class ;
rdfs:comment "A named, reusable solution template for a recurring design problem in software, describing the participating roles, their collaborations, and the trade-offs of applying the solution in a given context. Catalogued most famously by the Gang of Four as creational, structural, and behavioural patterns, design patterns form a shared vocabulary that lets engineers communicate architecture concisely, guide refactoring towards proven structures, and evaluate components against well-understood alternatives."@en ;
rdfs:label "Design Pattern"@en ;
rdfs:subClassOf ngm:software-engineering ;
vc:enables ngm:refactoring ;
vc:hasMaturity ngmi:maturity-draft ;
vc:isPartOf ngm:software-architecture ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:component ;
vc:relatedTo ngm:reference-architecture ;
vc:slug "design-pattern" ;
vc:sourceDomain "infrastructure" .
ngm:design-recommendation a skos:Concept ;
rdfs:label "Design Recommendation"@en .
ngm:design-research a skos:Concept ;
rdfs:label "Design Research"@en .
ngm:design-review a skos:Concept ;
rdfs:label "Design Review"@en .
ngm:design-software a owl:Class ;
rdfs:comment "Design software comprises applications used to create, edit, visualise, and publish visual, spatial, or interactive artefacts across disciplines including graphic design, user interface and user experience design, 3D modelling, architectural drafting, motion graphics, and industrial product design. These tools span 2D vector and raster editors, parametric and direct-modelling CAD environments, sculpting and procedural-generation suites, prototyping platforms, and real-time 3D authoring environments that feed directly into game engines and extended reality runtimes. Modern design software increasingly integrates generative AI assistance for layout suggestion, texture synthesis, mesh generation, and design-variant exploration. The category sits at the intersection of creative practice, software engineering, and spatial computing infrastructure, making it a foundational enabler of digital content pipelines across entertainment, architecture, manufacturing, and immersive media."@en ;
rdfs:label "Design Software"@en ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
rdfs:subClassOf _:r7746 ;
rdfs:subClassOf _:r7747 ;
rdfs:subClassOf _:r7748 ;
rdfs:subClassOf _:r7749 ;
rdfs:subClassOf _:r7750 ;
skos:broader ngm:sc-platform-and-environment ;
vc:bridgesTo ngm:bim-virtual-model ;
vc:bridgesTo ngm:machine-learning-discipline ;
vc:contrastsWith ngm:game-engine ;
vc:enables ngm:3-d-content-generation ;
vc:enables ngm:digital-twin ;
vc:enables ngm:film-production ;
vc:enables ngm:user-interface-design ;
vc:enables ngm:virtual-production-workflow ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:3d-modelling ;
vc:hasPart ngm:animation-software ;
vc:hasPart ngm:cad-software ;
vc:hasPart ngm:vector-graphics-editor ;
vc:isPartOf ngm:content-pipeline ;
vc:isPartOf ngm:technology-stack ;
vc:qualityScore "0.0"^^xsd:float ;
vc:relatedTo ngm:colour-management ;
vc:relatedTo ngm:digital-asset-management ;
vc:relatedTo ngm:rendering-pipeline ;
vc:requires ngm:file-format-standard ;
vc:requires ngm:graphics-processing-unit ;
vc:slug "design-software" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:extended-reality ;
vc:supports ngm:metaverse ;
vc:supports ngm:spatial-computing ;
vc:uses ngm:3-d-rendering-engine ;
vc:uses ngm:computer-vision ;
vc:uses ngm:generative-ai ;
vc:uses ngm:procedural-generation ;
vc:uses ngm:rasterization .
ngm:design-space-exploration a skos:Concept ;
rdfs:label "Design Space Exploration"@en .
ngm:design-sprint a skos:Concept ;
rdfs:label "Design Sprint"@en .
ngm:design-sprints a skos:Concept ;
rdfs:label "Design Sprints"@en .
ngm:design-systems a owl:Class ;
rdfs:comment "A design system is a single source of truth that combines reusable UI components, design tokens, patterns, and documentation governing how a product looks and behaves. It unifies designers and engineers around a shared component library and usage guidelines, ensuring consistency and accelerating delivery across teams and platforms. It encompasses both the visual language and the coded implementation that enforces it."@en ;
rdfs:label "Design Systems"@en ;
rdfs:subClassOf ngm:software-development ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:human-computer-interaction ;
vc:relatedTo ngm:product-design ;
vc:slug "design-systems" ;
vc:sourceDomain "infrastructure" .
ngm:design-thinking a owl:Class ;
rdfs:comment "Design Thinking is a human-centred, iterative problem-solving methodology that prioritises deep empathy with end users, rapid ideation, and prototype-driven experimentation to arrive at innovative solutions. Originating in industrial design and formalised at Stanford's d.school, it proceeds through five non-linear phases: empathise, define, ideate, prototype, and test. The approach deliberately suspends assumptions and defers judgement during divergent thinking stages, producing a rich solution space before converging on testable prototypes. Design Thinking is now applied widely in product development, service design, organisational strategy, and technology innovation contexts."@en ;
rdfs:label "Design Thinking"@en ;
rdfs:subClassOf ngm:knowledge-representation ;
vc:enables ngm:generative-design-tool ;
vc:enables ngm:product-design ;
vc:enables ngm:user-experience ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:accessible-design ;
vc:relatedTo ngm:etsi-domain-human-interface-ux ;
vc:relatedTo ngm:human-computer-interaction ;
vc:relatedTo ngm:information-architecture ;
vc:slug "design-thinking" ;
vc:sourceDomain "governance" ;
vc:uses ngm:collaborative-systems-modality-design ;
vc:uses ngm:design-software ;
vc:uses ngm:user-research .
ngm:design-tokens a skos:Concept ;
rdfs:label "Design Tokens"@en .
ngm:design-tools a skos:Concept ;
rdfs:label "Design Tools"@en .
ngm:design-visualization a skos:Concept ;
rdfs:label "Design Visualization"@en .
ngm:designops a skos:Concept ;
rdfs:label "Designops"@en .
ngm:desire-set a skos:Concept ;
rdfs:label "Desire Set"@en .
ngm:desktop-clients a skos:Concept ;
rdfs:label "Desktop Clients"@en .
ngm:desktop-computing a skos:Concept ;
rdfs:label "Desktop Computing"@en .
ngm:destination-chain-execution a owl:Class ;
rdfs:comment "Destination chain execution is the phase of a cross-chain operation in which a message or transaction validated from a source chain is finally executed on the target blockchain. After relayers and verification prove the source event, the destination chain mints, releases, or calls a contract to complete the bridged action. Correct execution requires replay protection, message ordering guarantees, and trust in the verification layer."@en ;
rdfs:label "Destination Chain Execution"@en ;
rdfs:subClassOf ngm:cross-chain-bridge ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:blockchain-interoperability ;
vc:relatedTo ngm:cross-chain-bridge ;
vc:slug "destination-chain-execution" ;
vc:sourceDomain "blockchain" .
ngm:destination-marketing a owl:Class ;
rdfs:comment "The strategic promotion of physical or virtual locations using immersive technologies, AR/VR experiences, and digital twin representations to attract visitors, investors, and residents by showcasing destinations through interactive 3D visualizations and metaverse presence."@en ;
rdfs:label "Destination Marketing"@en ;
rdfs:subClassOf ngm:digital-marketing ;
rdfs:subClassOf ngm:sc-content-and-assets ;
rdfs:subClassOf _:r7751 ;
rdfs:subClassOf _:r7752 ;
rdfs:subClassOf _:r7753 ;
skos:broader ngm:sc-content-and-assets ;
vc:bridgesTo ngm:digital-marketing ;
vc:enables ngm:advertising ;
vc:enables ngm:location-promotion ;
vc:enables ngm:virtual-tourism ;
vc:hasMaturity ngmi:maturity-draft ;
vc:qualityScore "0.5"^^xsd:float ;
vc:requires ngm:3-d-content-creation ;
vc:requires ngm:digital-twin ;
vc:requires ngm:vr-experiences ;
vc:slug "destination-marketing" ;
vc:sourceDomain "spatial-computing" .
ngm:detailed-balance a owl:Class ;
rdfs:comment "Detailed balance is a condition on a Markov chain stating that, in equilibrium, the probability flux between any two states is equal in both directions. When a transition kernel satisfies detailed balance with respect to a target distribution, that distribution is a stationary distribution of the chain. It is the central design principle behind most Markov chain Monte Carlo samplers, including Metropolis-Hastings."@en ;
rdfs:label "Detailed Balance"@en ;
rdfs:subClassOf ngm:equilibrium-condition ;
rdfs:subClassOf ngm:markov-chain-monte-carlo ;
rdfs:subClassOf ngm:markov-chain-property ;
rdfs:subClassOf ngm:reversibility-condition ;
rdfs:subClassOf ngm:stochastic-process-condition ;
rdfs:subClassOf _:r7754 ;
rdfs:subClassOf _:r7755 ;
rdfs:subClassOf _:r7756 ;
rdfs:subClassOf _:r7757 ;
rdfs:subClassOf _:r7758 ;
vc:bridgesTo ngm:active-matter-physics ;
vc:bridgesTo ngm:computational-biology ;
vc:bridgesTo ngm:lattice-qcd ;
vc:bridgesTo ngm:non-equilibrium-thermodynamics ;
vc:bridgesTo ngm:quantum-thermodynamics ;
vc:bridgesTo ngm:statistical-physics ;
vc:contrastsWith ngm:bouncy-particle-sampler ;
vc:contrastsWith ngm:event-chain-monte-carlo ;
vc:contrastsWith ngm:global-balance ;
vc:contrastsWith ngm:irreversible-markov-chain ;
vc:contrastsWith ngm:non-reversible-markov-chain-monte-carlo ;
vc:contrastsWith ngm:piecewise-deterministic-markov-process ;
vc:contrastsWith ngm:stochastic-process ;
vc:contrastsWith ngm:zig-zag-sampler ;
vc:dependsOn ngm:markov-chain ;
vc:dependsOn ngm:measure-theory ;
vc:dependsOn ngm:probability-theory ;
vc:dependsOn ngm:stochastic-process ;
vc:enables ngm:ergodic-convergence ;
vc:enables ngm:gibbs-sampling ;
vc:enables ngm:hamiltonian-monte-carlo ;
vc:enables ngm:markov-chain-monte-carlo ;
vc:enables ngm:metropolis-hastings ;
vc:enables ngm:no-u-turn-sampler ;
vc:enables ngm:sampling ;
vc:enables ngm:slice-sampling ;
vc:enables ngm:stationary-distribution ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:acceptance-probability ;
vc:hasPart ngm:acceptance-ratio ;
vc:hasPart ngm:barker-acceptance-function ;
vc:hasPart ngm:gibbs-conditional-updates ;
vc:hasPart ngm:hastings-ratio ;
vc:hasPart ngm:langevin-monte-carlo-detailed-balance ;
vc:hasPart ngm:metropolis-hastings-acceptance-rule ;
vc:hasPart ngm:microscopic-reversibility ;
vc:hasPart ngm:probability-flux ;
vc:hasPart ngm:stationary-distribution ;
vc:hasPart ngm:transition-kernel ;
vc:implements ngm:markov-chain ;
vc:implements ngm:microscopic-reversibility ;
vc:implements ngm:reversible-markov-chain ;
vc:implements ngm:time-reversal-symmetry ;
vc:isPartOf ngm:markov-chain-monte-carlo ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:boltzmann-distribution ;
vc:relatedTo ngm:convergence ;
vc:relatedTo ngm:ergodicity ;
vc:relatedTo ngm:integrated-autocorrelation-time ;
vc:relatedTo ngm:mixing-time ;
vc:relatedTo ngm:monte-carlo-methods ;
vc:relatedTo ngm:posterior-distribution ;
vc:relatedTo ngm:probabilistic-model ;
vc:relatedTo ngm:quantum-detailed-balance ;
vc:relatedTo ngm:sampling ;
vc:relatedTo ngm:spectral-gap ;
vc:relatedTo ngm:statistical-mechanics ;
vc:requires ngm:ergodicity ;
vc:requires ngm:markov-chain ;
vc:requires ngm:probability-distribution ;
vc:requires ngm:probability-theory ;
vc:requires ngm:stochastic-process ;
vc:requires ngm:transition-kernel ;
vc:slug "detailed-balance" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:no-formal-standard-community-best-practice-via-stan-documentation ;
vc:supports ngm:bayesian-inference ;
vc:supports ngm:energy-based-model ;
vc:supports ngm:ising-model-simulation ;
vc:supports ngm:posterior-inference ;
vc:supports ngm:probabilistic-programming ;
vc:supports ngm:statistical-physics ;
vc:supports ngm:uncertainty-quantification ;
vc:uses ngm:acceptance-probability ;
vc:uses ngm:boltzmann-distribution ;
vc:uses ngm:hastings-ratio ;
vc:uses ngm:probability-distribution ;
vc:uses ngm:stochastic-process ;
vc:uses ngm:transition-kernel .
ngm:detective-control a skos:Concept ;
rdfs:label "Detective Control"@en .
ngm:determinism a owl:Class ;
rdfs:comment "Determinism, in computing and distributed systems, is the property by which a computational process produces identical outputs given identical inputs and initial state, regardless of when, where, or how many times it is executed. Deterministic systems are essential for reproducibility of scientific experiments, predictability of embedded and safety-critical control systems, and correctness of distributed consensus protocols where all participating nodes must reach the same conclusion from the same inputs. In the context of blockchain and smart contracts, determinism is a hard requirement because non-deterministic execution would cause different nodes to compute different state transitions, breaking consensus."@en ;
rdfs:label "Determinism"@en ;
rdfs:subClassOf ngm:consensus-mechanism ;
vc:contrastsWith ngm:probabilistic-model ;
vc:contrastsWith ngm:stochastic-process ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:consensus-algorithm ;
vc:relatedTo ngm:formal-verification ;
vc:relatedTo ngm:random-number-generation ;
vc:relatedTo ngm:state-machine-replication ;
vc:slug "determinism" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:automated-reasoning ;
vc:supports ngm:blockchain ;
vc:supports ngm:cyber-physical-systems .
ngm:deterministic-algorithms a skos:Concept ;
rdfs:label "Deterministic Algorithms"@en .
ngm:deterministic-bitcoin-commitment a skos:Concept ;
rdfs:label "Deterministic Bitcoin Commitment"@en .
ngm:deterministic-chaos a skos:Concept ;
rdfs:label "Deterministic Chaos"@en .
ngm:deterministic-commitment-scheme a skos:Concept ;
rdfs:label "Deterministic Commitment Scheme"@en .
ngm:deterministic-computation a skos:Concept ;
rdfs:label "Deterministic Computation"@en .
ngm:deterministic-control a skos:Concept ;
rdfs:label "Deterministic Control"@en .
ngm:deterministic-dag-pipeline a skos:Concept ;
rdfs:label "Deterministic Dag Pipeline"@en .
ngm:deterministic-dynamical-system a skos:Concept ;
rdfs:label "Deterministic Dynamical System"@en .
ngm:deterministic-encoding a skos:Concept ;
rdfs:label "Deterministic Encoding"@en .
ngm:deterministic-execution a owl:Class ;
rdfs:comment "Deterministic Execution guarantees that a computation produces identical outputs and state transitions whenever it is run on the same inputs in the same order, irrespective of host, timing, or scheduling. It is a prerequisite for state machine replication and blockchain smart contracts, where independent nodes must reach byte-identical results to agree on shared state. Achieving it demands eliminating sources of nondeterminism such as wall-clock time, unordered concurrency, and floating-point divergence."@en ;
rdfs:label "Deterministic Execution"@en ;
rdfs:subClassOf ngm:state-machine-replication ;
rdfs:subClassOf _:r7759 ;
rdfs:subClassOf _:r7760 ;
vc:bridgesTo ngm:smart-contract ;
vc:contrastsWith ngm:concurrency ;
vc:enables ngm:byzantine-fault-tolerance ;
vc:enables ngm:consensus-mechanism ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:idempotency ;
vc:isPartOf ngm:infrastructure ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:blockchain ;
vc:relatedTo ngm:fault-tolerance ;
vc:relatedTo ngm:reproducibility ;
vc:requires ngm:reproducibility ;
vc:requires ngm:state-machine-replication ;
vc:slug "deterministic-execution" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:replication ;
vc:supports ngm:smart-contract ;
vc:uses ngm:virtual-machine .
ngm:deterministic-finality a owl:Class ;
rdfs:comment "Transaction finality achieved through explicit protocol mechanisms in BFT-based consensus systems, providing absolute mathematical guarantee that finalized blocks cannot be reverted once a supermajority of validators has committed to them."@en ;
rdfs:label "Deterministic Finality"@en ;
rdfs:subClassOf ngm:blockchain ;
rdfs:subClassOf ngm:transaction-finality ;
rdfs:subClassOf _:r7761 ;
rdfs:subClassOf _:r7762 ;
rdfs:subClassOf _:r7763 ;
skos:broader ngm:blockchain ;
vc:bridgesTo ngm:ai-agent-system ;
vc:bridgesTo ngm:de-fi ;
vc:bridgesTo ngm:virtual-economy ;
vc:contrastsWith ngm:longest-chain-rule ;
vc:contrastsWith ngm:nakamoto-consensus ;
vc:contrastsWith ngm:probabilistic-finality ;
vc:enables ngm:cross-chain-bridge ;
vc:enables ngm:transaction-finality ;
vc:hasMaturity ngmi:maturity-draft ;
vc:implements ngm:casper-ffg ;
vc:implements ngm:tendermint ;
vc:isPartOf ngm:blockchain ;
vc:isPartOf ngm:consensus-mechanism ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:economic-finality ;
vc:relatedTo ngm:validator ;
vc:requires ngm:byzantine-fault-tolerance ;
vc:requires ngm:proof-of-stake ;
vc:requires ngm:validator-set ;
vc:slug "deterministic-finality" ;
vc:sourceDomain "blockchain" ;
vc:uses ngm:bls-signature ;
vc:uses ngm:byzantine-fault-tolerance ;
vc:uses ngm:slashing ;
vc:uses ngm:two-phase-commit .
ngm:deterministic-integration a skos:Concept ;
rdfs:label "Deterministic Integration"@en .
ngm:deterministic-jvm a skos:Concept ;
rdfs:label "Deterministic Jvm"@en .
ngm:deterministic-key-generation a skos:Concept ;
rdfs:label "Deterministic Key Generation"@en .
ngm:deterministic-level-design a skos:Concept ;
rdfs:label "Deterministic Level Design"@en .
ngm:deterministic-model a skos:Concept ;
rdfs:label "Deterministic Model"@en .
ngm:deterministic-network a skos:Concept ;
rdfs:label "Deterministic Network"@en .
ngm:deterministic-networking a owl:Class ;
rdfs:comment "Deterministic networking is a class of networking techniques that provide bounded latency, low jitter and negligible packet loss for time-critical traffic over shared packet-switched infrastructure, typically through reserved bandwidth, scheduled transmission windows and time synchronisation across network nodes. It underpins standards such as IEEE Time-Sensitive Networking and IETF DetNet, which extend best-effort Ethernet and IP networks with guarantees suitable for industrial control, robotics and audio-video applications. Deterministic behaviour is achieved by combining traffic shaping, redundancy and precise clock synchronisation rather than relying on statistical over-provisioning alone."@en ;
rdfs:label "Deterministic Networking"@en ;
rdfs:subClassOf ngm:network-protocol ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:network-protocol ;
vc:qualityScore "0.55"^^xsd:float ;
vc:relatedTo ngm:profinet ;
vc:relatedTo ngm:time-sensitive-networking ;
vc:slug "deterministic-networking" ;
vc:sourceDomain "infrastructure" .
ngm:deterministic-observer a skos:Concept ;
rdfs:label "Deterministic Observer"@en .
ngm:deterministic-replay a skos:Concept ;
rdfs:label "Deterministic Replay"@en .
ngm:deterministic-scheduling a owl:Class ;
rdfs:comment "Deterministic scheduling is a task-scheduling approach in which the order and timing of task execution are fully predictable given the same inputs, so that worst-case latency and execution order can be guaranteed in advance. It is a defining requirement of real-time computing and real-time operating systems, which must bound task response times to meet hard or soft deadlines. Deterministic scheduling contrasts with best-effort scheduling, which optimises average throughput without timing guarantees."@en ;
rdfs:label "Deterministic Scheduling"@en ;
rdfs:subClassOf ngm:real-time-computing ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.0"^^xsd:float ;
vc:slug "deterministic-scheduling" ;
vc:sourceDomain "infrastructure" .
ngm:deterministic-serialisation a owl:Class ;
rdfs:comment "Deterministic serialisation is the encoding of structured data into bytes such that semantically identical inputs always yield exactly the same byte sequence. It fixes ambiguities like map-key ordering, number formatting, and whitespace so that the output is canonical and reproducible. This property is essential for hashing, digital signatures, and content addressing, where any byte difference changes the resulting digest."@en ;
rdfs:label "Deterministic Serialisation"@en ;
rdfs:subClassOf ngm:data-management ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:content-addressing ;
vc:relatedTo ngm:uri-canonicaliser ;
vc:slug "deterministic-serialisation" ;
vc:sourceDomain "data" .
ngm:deterministic-signing a skos:Concept ;
rdfs:label "Deterministic Signing"@en .
ngm:deterministicsecrets a skos:Concept ;
rdfs:label "Deterministicsecrets"@en .
ngm:deterrence-of-harm a skos:Concept ;
rdfs:label "Deterrence Of Harm"@en .
ngm:detr a skos:Concept ;
rdfs:label "Detr"@en .
ngm:dev-sec-ops a owl:Class ;
rdfs:comment "DevSecOps is a software engineering practice that integrates security controls, testing, and policy enforcement directly into the continuous integration and delivery pipeline, making security a shared responsibility across development, operations, and security teams. It applies the principle of shift-left security, automating vulnerability scanning, dependency auditing, and policy-as-code checks at every stage from code commit through production deployment."@en ;
rdfs:label "DevSecOps"@en ;
rdfs:subClassOf ngm:agile-software-development ;
rdfs:subClassOf ngm:continuous-delivery ;
rdfs:subClassOf ngm:cybersecurity ;
rdfs:subClassOf ngm:software-engineering ;
rdfs:subClassOf _:r7772 ;
rdfs:subClassOf _:r7773 ;
rdfs:subClassOf _:r7774 ;
rdfs:subClassOf _:r7775 ;
rdfs:subClassOf _:r7776 ;
rdfs:subClassOf _:r7777 ;
rdfs:subClassOf _:r7778 ;
rdfs:subClassOf _:r7779 ;
rdfs:subClassOf _:r7780 ;
rdfs:subClassOf _:r7781 ;
rdfs:subClassOf _:r7782 ;
rdfs:subClassOf _:r7783 ;
rdfs:subClassOf _:r7784 ;
rdfs:subClassOf _:r7785 ;
rdfs:subClassOf _:r7786 ;
vc:contrastsWith ngm:manual-security-audit ;
vc:contrastsWith ngm:perimeter-security ;
vc:contrastsWith ngm:periodic-penetration-testing ;
vc:contrastsWith ngm:waterfall-security-model ;
vc:dependsOn ngm:agile-software-development ;
vc:dependsOn ngm:ci-cd-automation ;
vc:dependsOn ngm:cloud-security ;
vc:dependsOn ngm:container-security ;
vc:dependsOn ngm:continuous-integration ;
vc:dependsOn ngm:infrastructure-as-code ;
vc:dependsOn ngm:source-control ;
vc:enables ngm:ai-security ;
vc:enables ngm:continuous-monitoring ;
vc:enables ngm:mlsecops ;
vc:enables ngm:regulatory-compliance ;
vc:enables ngm:secure-software-development-lifecycle ;
vc:enables ngm:software-bill-of-materials ;
vc:enables ngm:supply-chain-security ;
vc:enables ngm:vulnerability-management ;
vc:enables ngm:zero-trust-architecture ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:cloud-security ;
vc:hasPart ngm:container-security ;
vc:hasPart ngm:continuous-monitoring ;
vc:hasPart ngm:infrastructure-as-code ;
vc:hasPart ngm:penetration-testing ;
vc:hasPart ngm:policy-as-code ;
vc:hasPart ngm:security-testing ;
vc:hasPart ngm:software-bill-of-materials ;
vc:hasPart ngm:vulnerability-scanner ;
vc:implements ngm:nist-ai-rmf ;
vc:implements ngm:nist-cybersecurity-framework ;
vc:implements ngm:policy-as-code ;
vc:implements ngm:secure-software-development-lifecycle ;
vc:implements ngm:shift-left-security ;
vc:implements ngm:slsa-framework ;
vc:implements ngm:zero-trust-architecture ;
vc:qualityScore "0.95"^^xsd:float ;
vc:relatedTo ngm:ai-security ;
vc:relatedTo ngm:ai-trust-risk-and-security-management ;
vc:relatedTo ngm:api-security ;
vc:relatedTo ngm:cloud-security ;
vc:relatedTo ngm:continuous-integration ;
vc:relatedTo ngm:continuous-training ;
vc:relatedTo ngm:cyber-security-and-cryptography ;
vc:relatedTo ngm:cybersecurity-policy ;
vc:relatedTo ngm:cybersecurity-risk-management ;
vc:relatedTo ngm:cybersecurity-standard ;
vc:relatedTo ngm:data-security ;
vc:relatedTo ngm:mlsecops ;
vc:relatedTo ngm:nist-ai-standards ;
vc:relatedTo ngm:nist-cybersecurity-framework ;
vc:relatedTo ngm:vulnerability-management ;
vc:requires ngm:ci-cd-automation ;
vc:requires ngm:cloud-security ;
vc:requires ngm:continuous-deployment ;
vc:requires ngm:continuous-integration ;
vc:requires ngm:cybersecurity-framework ;
vc:requires ngm:infrastructure-as-code ;
vc:requires ngm:source-control ;
vc:requires ngm:vulnerability-scanner ;
vc:slug "dev-sec-ops" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:cybersecurity-standard ;
vc:standardizedBy ngm:ncsc-cybersecurity-framework ;
vc:standardizedBy ngm:nist-ai-rmf ;
vc:standardizedBy ngm:nist-cybersecurity-framework ;
vc:standardizedBy ngm:slsa-framework ;
vc:supports ngm:api-security ;
vc:supports ngm:continuous-delivery ;
vc:supports ngm:cyber-security-and-cryptography ;
vc:supports ngm:cybersecurity-policy ;
vc:supports ngm:data-security ;
vc:supports ngm:platform-engineering ;
vc:supports ngm:regulatory-compliance ;
vc:uses ngm:continuous-monitoring ;
vc:uses ngm:cryptographic-security ;
vc:uses ngm:open-policy-agent ;
vc:uses ngm:penetration-testing ;
vc:uses ngm:security-testing ;
vc:uses ngm:sigstore ;
vc:uses ngm:software-bill-of-materials ;
vc:uses ngm:vulnerability-scanner .
ngm:developer-ai a skos:Concept ;
rdfs:label "Developer AI"@en .
ngm:developer-centralisation a skos:Concept ;
rdfs:label "Developer Centralisation"@en .
ngm:developer-ecosystem a skos:Concept ;
rdfs:label "Developer Ecosystem"@en .
ngm:developer-experience a skos:Concept ;
rdfs:label "Developer Experience"@en .
ngm:developer-onboarding a skos:Concept ;
rdfs:label "Developer Onboarding"@en .
ngm:developer-portal a skos:Concept ;
rdfs:label "Developer Portal"@en .
ngm:developer-productivity a skos:Concept ;
rdfs:label "Developer Productivity"@en .
ngm:developer-toolchain a skos:Concept ;
rdfs:label "Developer Toolchain"@en .
ngm:development-economics a skos:Concept ;
rdfs:label "Development Economics"@en .
ngm:development-finance a skos:Concept ;
rdfs:label "Development Finance"@en .
ngm:development-platform a owl:Class ;
rdfs:comment "A Development Platform is an integrated suite of tools, APIs, runtimes, and infrastructure services that enables engineers and creators to build, test, and deploy applications. In spatial computing contexts, development platforms provide SDKs for XR hardware, scene-graph editors, physics engines, and asset pipelines supporting OpenXR and Universal Scene Description (USD). They abstract hardware heterogeneity and supply governance tooling for collaborative multi-stakeholder development."@en ;
rdfs:label "Development Platform"@en ;
rdfs:subClassOf ngm:sc-platform-and-environment ;
skos:broader ngm:sc-platform-and-environment ;
vc:dependsOn ngm:digital-infrastructure ;
vc:enables ngm:digital-twin ;
vc:enables ngm:spatial-computing ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:qualityScore "0.0"^^xsd:float ;
vc:slug "development-platform" ;
vc:sourceDomain "spatial-computing" ;
vc:supports ngm:collaboration ;
vc:supports ngm:digital-fabrication ;
vc:uses ngm:computer-vision ;
vc:uses ngm:open-xr .
ngm:development-rights a skos:Concept ;
rdfs:label "Development Rights"@en .
ngm:development-workflow a skos:Concept ;
rdfs:label "Development Workflow"@en .
ngm:developmental-cognition a skos:Concept ;
rdfs:label "Developmental Cognition"@en .
ngm:developmental-robotics a skos:Concept ;
rdfs:label "Developmental Robotics"@en .
ngm:device-alignment a skos:Concept ;
rdfs:label "Device Alignment"@en .
ngm:device-attestation a skos:Concept ;
rdfs:label "Device Attestation"@en .
ngm:device-commissioning a skos:Concept ;
rdfs:label "Device Commissioning"@en .
ngm:device-drivers a owl:Class ;
rdfs:comment "A device driver is a software component that mediates between an operating system and a specific hardware device, translating generic OS calls into the device's command and register protocol. Drivers expose a uniform interface so applications can use peripherals without knowing their internal details, and they handle interrupts, buffering, and power state. They are the foundation of the hardware abstraction layer that makes hardware portable to software."@en ;
rdfs:label "Device Drivers"@en ;
rdfs:subClassOf ngm:software-engineering ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:hardware-abstraction-layer-hal ;
vc:relatedTo ngm:human-interface-device ;
vc:slug "device-drivers" ;
vc:sourceDomain "infrastructure" .
ngm:device-fleet-management a skos:Concept ;
rdfs:label "Device Fleet Management"@en .
ngm:device-functionality a skos:Concept ;
rdfs:label "Device Functionality"@en .
ngm:device-hardening a skos:Concept ;
rdfs:label "Device Hardening"@en .
ngm:device-identity a owl:Class ;
rdfs:comment "Device identity is a unique, verifiable credential bound to a physical device that allows it to authenticate itself to a network, service, or other devices independently of any human user. It is typically established through a hardware root of trust, such as a TPM or secure element, that stores a cryptographic key pair generated or provisioned at manufacture. In IoT and sensor network deployments, device identity is foundational to zero-trust access control, allowing gateways and platforms to verify which physical device is sending data before admitting it to the network. Without it, spoofed or cloned devices can inject false data or gain unauthorised network access."@en ;
rdfs:label "Device Identity"@en ;
rdfs:subClassOf ngm:digital-identity ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.0"^^xsd:float ;
vc:slug "device-identity" ;
vc:sourceDomain "security" .
ngm:device-management a skos:Concept ;
rdfs:label "Device Management"@en .
ngm:device-portability a skos:Concept ;
rdfs:label "Device Portability"@en .
ngm:device-sensors a skos:Concept ;
rdfs:label "Device Sensors"@en .
ngm:devin a skos:Concept ;
rdfs:label "Devin"@en .
ngm:devolution a skos:Concept ;
rdfs:label "Devolution"@en .
ngm:devops a owl:Class ;
rdfs:comment "DevOps is a sociotechnical discipline that unifies software development (Dev) and IT operations (Ops) through cultural practices, shared toolchains, and automation pipelines to shorten the system development lifecycle and deliver high-quality software continuously. It operationalises collaboration between development and operations teams by eliminating organisational silos, embracing infrastructure as code, and instrumenting every stage of delivery with feedback loops spanning continuous integration, continuous delivery, monitoring, and incident response. The discipline extends Agile principles beyond code authorship to encompass deployment, reliability engineering, and production observability as first-class engineering concerns."@en ;
rdfs:label "DevOps"@en ;
rdfs:subClassOf ngm:software-engineering ;
rdfs:subClassOf _:r7764 ;
rdfs:subClassOf _:r7765 ;
rdfs:subClassOf _:r7766 ;
rdfs:subClassOf _:r7767 ;
rdfs:subClassOf _:r7768 ;
rdfs:subClassOf _:r7769 ;
rdfs:subClassOf _:r7770 ;
rdfs:subClassOf _:r7771 ;
vc:bridgesTo ngm:dev-sec-ops ;
vc:bridgesTo ngm:mlops ;
vc:contrastsWith ngm:siloed-operations ;
vc:contrastsWith ngm:waterfall-development ;
vc:dependsOn ngm:cloud-computing ;
vc:dependsOn ngm:containerisation ;
vc:dependsOn ngm:microservices ;
vc:enables ngm:mlops ;
vc:enables ngm:platform-engineering ;
vc:enables ngm:site-reliability-engineering ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:continuous-delivery ;
vc:hasPart ngm:continuous-deployment ;
vc:hasPart ngm:continuous-integration ;
vc:hasPart ngm:incident-response ;
vc:hasPart ngm:infrastructure-as-code ;
vc:hasPart ngm:monitoring-system ;
vc:implements ngm:agile-software-development ;
vc:implements ngm:lean-software-development ;
vc:implements ngm:shift-left-testing ;
vc:isPartOf ngm:software-delivery-lifecycle ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:feature-flags ;
vc:relatedTo ngm:observability ;
vc:requires ngm:automated-testing ;
vc:requires ngm:build-automation ;
vc:requires ngm:version-control ;
vc:slug "devops" ;
vc:sourceDomain "infrastructure" ;
vc:supports ngm:cloud-platform ;
vc:supports ngm:security-scanning ;
vc:supports ngm:software-development ;
vc:uses ngm:docker-containerisation-platform ;
vc:uses ngm:git-hub-actions ;
vc:uses ngm:kubernetes ;
vc:uses ngm:terraform .
ngm:devops-practices a skos:Concept ;
rdfs:label "Devops Practices"@en .
ngm:devp2p a skos:Concept ;
rdfs:label "Devp2p"@en .
ngm:dex a owl:Class ;
rdfs:comment "The common abbreviation for a decentralised exchange, a smart-contract trading venue where users swap assets without surrendering custody to a central operator."@en ;
rdfs:label "DEX"@en ;
rdfs:subClassOf ngm:decentralised-exchange ;
rdfs:subClassOf _:r6663 ;
rdfs:subClassOf _:r6664 ;
vc:bridgesTo ngm:automated-market-maker ;
vc:bridgesTo ngm:order-book ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.6"^^xsd:float ;
vc:requires ngm:liquidity-pool ;
vc:requires ngm:smart-contract ;
vc:slug "dex" ;
vc:sourceDomain "blockchain" .
ngm:dexterity a skos:Concept ;
rdfs:label "Dexterity"@en .
ngm:dexterous-grasping a owl:Class ;
rdfs:comment "Dexterous grasping is the capability of a robotic hand with multiple independently actuated fingers to acquire and reposition objects using coordinated, in-hand manipulation rather than a simple two-jaw pinch. It requires fine control over contact forces and finger placement, often informed by tactile sensing to detect slip and adjust grip in real time without relying solely on vision. Reinforcement learning has become a dominant approach for training dexterous grasping policies, since the high dimensionality of multi-fingered hand kinematics and contact dynamics is difficult to model and plan for analytically. It is a prerequisite for robots handling irregular, deformable, or fragile objects that a rigid parallel gripper cannot reliably grip."@en ;
rdfs:label "Dexterous Grasping"@en ;
rdfs:subClassOf ngm:robotic-grasping ;
vc:hasMaturity ngmi:maturity-established ;
vc:qualityScore "0.0"^^xsd:float ;
vc:slug "dexterous-grasping" ;
vc:sourceDomain "robotics" .
ngm:dexterous-manipulation a owl:Class ;
rdfs:comment "Dexterous manipulation is the capability of robotic systems to grasp, reorient, assemble, and interact with objects using multi-fingered hands or compliant end-effectors in ways that require fine motor control, contact-rich reasoning, and real-time adaptation to object geometry and physical properties. It encompasses grasp planning, in-hand manipulation, and tactile feedback integration to replicate or exceed human-hand dexterity in unstructured environments."@en ;
rdfs:label "Dexterous Manipulation"@en ;
rdfs:subClassOf ngm:manipulation ;
rdfs:subClassOf _:r7787 ;
rdfs:subClassOf _:r7788 ;
rdfs:subClassOf _:r7789 ;
rdfs:subClassOf _:r7790 ;
rdfs:subClassOf _:r7791 ;
rdfs:subClassOf _:r7792 ;
vc:bridgesTo ngm:computer-vision ;
vc:bridgesTo ngm:foundation-model ;
vc:contrastsWith ngm:pick-and-place ;
vc:dependsOn ngm:contact-mechanics ;
vc:dependsOn ngm:motion-planning ;
vc:enables ngm:humanoid-robot ;
vc:enables ngm:robot-learning ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:grasp-planning ;
vc:hasPart ngm:in-hand-manipulation ;
vc:isPartOf ngm:robot-manipulation ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:sim-to-real-transfer ;
vc:relatedTo ngm:soft-robotics ;
vc:relatedTo ngm:teleoperation ;
vc:requires ngm:end-effector ;
vc:requires ngm:force-torque-sensor ;
vc:requires ngm:kinematics ;
vc:requires ngm:tactile-sensing ;
vc:slug "dexterous-manipulation" ;
vc:sourceDomain "robotics" ;
vc:uses ngm:domain-randomisation ;
vc:uses ngm:haptic-feedback ;
vc:uses ngm:imitation-learning ;
vc:uses ngm:physics-simulation ;
vc:uses ngm:reinforcement-learning .
ngm:dfdc-benchmark a skos:Concept ;
rdfs:label "Dfdc Benchmark"@en .
ngm:dfe-generative-ai-guidance a skos:Concept ;
rdfs:label "Dfe Generative AI Guidance"@en .
ngm:dfs-tree a skos:Concept ;
rdfs:label "Dfs Tree"@en .
ngm:dgx-h100 a skos:Concept ;
rdfs:label "Dgx H100"@en .
ngm:dh-convention a skos:Concept ;
rdfs:label "Dh Convention"@en .
ngm:dhl-supply-chain a skos:Concept ;
rdfs:label "Dhl Supply Chain"@en .
ngm:di-lo-co a owl:Class ;
rdfs:comment "DiLoCo (Distributed Low-Communication training) is a method for training large language models across loosely connected, geographically distributed compute clusters with minimal inter-node communication. Workers perform many local optimisation steps before periodically synchronising via an outer optimiser, drastically reducing the bandwidth and latency demands of conventional data-parallel training. It enables collaborative model training over the public internet rather than within a single tightly coupled datacentre."@en ;
rdfs:label "DiLoCo"@en ;
rdfs:subClassOf ngm:distributed-ai-training ;
rdfs:subClassOf ngm:distributed-computing ;
rdfs:subClassOf ngm:distributed-training ;
rdfs:subClassOf ngm:federated-learning ;
rdfs:subClassOf _:r7793 ;
rdfs:subClassOf _:r7794 ;
rdfs:subClassOf _:r7795 ;
rdfs:subClassOf _:r7796 ;
rdfs:subClassOf _:r7797 ;
rdfs:subClassOf _:r7798 ;
rdfs:subClassOf _:r7799 ;
rdfs:subClassOf _:r7800 ;
rdfs:subClassOf _:r7801 ;
rdfs:subClassOf _:r7802 ;
vc:contrastsWith ngm:centralised-training ;
vc:contrastsWith ngm:pipeline-parallelism ;
vc:contrastsWith ngm:synchronous-data-parallelism ;
vc:contrastsWith ngm:tensor-parallelism ;
vc:contrastsWith ngm:zero-sharding ;
vc:dependsOn ngm:adam-optimiser ;
vc:dependsOn ngm:asynchronous-communication ;
vc:dependsOn ngm:collective-communication ;
vc:dependsOn ngm:communication-protocol ;
vc:dependsOn ngm:distributed-computing ;
vc:dependsOn ngm:gradient-descent ;
vc:dependsOn ngm:large-language-models ;
vc:enables ngm:collaborative-model-ownership ;
vc:enables ngm:compute-democratisation ;
vc:enables ngm:decentralised-ai ;
vc:enables ngm:decentralised-science ;
vc:enables ngm:federated-edge-learning ;
vc:enables ngm:internet-scale-training ;
vc:enables ngm:model-training ;
vc:hasMaturity ngmi:maturity-draft ;
vc:hasPart ngm:checkpoint-recovery ;
vc:hasPart ngm:collective-communication ;
vc:hasPart ngm:global-model-broadcast ;
vc:hasPart ngm:gradient-compression ;
vc:hasPart ngm:local-sgd ;
vc:hasPart ngm:pseudo-gradient-aggregation ;
vc:hasPart ngm:synchronisation-barrier ;
vc:implements ngm:data-parallelism ;
vc:implements ngm:federated-learning ;
vc:implements ngm:gradient-descent ;
vc:implements ngm:local-sgd ;
vc:implements ngm:nesterov-momentum ;
vc:qualityScore "0.95"^^xsd:float ;
vc:relatedTo ngm:adam-optimiser ;
vc:relatedTo ngm:ai-energy-optimisation ;
vc:relatedTo ngm:ai-energy-scarcity ;
vc:relatedTo ngm:asynchronous-communication ;
vc:relatedTo ngm:asynchronous-rl ;
vc:relatedTo ngm:bandwidth-optimization ;
vc:relatedTo ngm:bittensor ;
vc:relatedTo ngm:collective-communication ;
vc:relatedTo ngm:communication-protocol ;
vc:relatedTo ngm:decentralised-ai ;
vc:relatedTo ngm:distributed-ai-training ;
vc:relatedTo ngm:distributed-training ;
vc:relatedTo ngm:federated-edge-learning ;
vc:relatedTo ngm:federated-learning ;
vc:relatedTo ngm:gradient-compression ;
vc:relatedTo ngm:prime-intellect ;
vc:requires ngm:adam-optimiser ;
vc:requires ngm:bandwidth-optimization ;
vc:requires ngm:checkpoint-recovery ;
vc:requires ngm:collective-communication ;
vc:requires ngm:distributed-computing ;
vc:requires ngm:gradient-descent ;
vc:requires ngm:large-language-models ;
vc:requires ngm:nesterov-momentum ;
vc:slug "di-lo-co" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:apache-license-2-0 ;
vc:standardizedBy ngm:arxiv-preprint-standards ;
vc:supports ngm:bittensor ;
vc:supports ngm:collaborative-systems-modality ;
vc:supports ngm:compute-exchange ;
vc:supports ngm:decentralised-science ;
vc:supports ngm:federated-edge-learning ;
vc:supports ngm:model-training ;
vc:supports ngm:prime-intellect ;
vc:uses ngm:adam-optimiser ;
vc:uses ngm:asynchronous-communication ;
vc:uses ngm:bandwidth-optimization ;
vc:uses ngm:checkpoint-recovery ;
vc:uses ngm:collective-communication ;
vc:uses ngm:communication-protocol ;
vc:uses ngm:gradient-compression ;
vc:uses ngm:nesterov-momentum .
ngm:diagnostic-analytics a skos:Concept ;
rdfs:label "Diagnostic Analytics"@en .
ngm:diagnostic-coverage a skos:Concept ;
rdfs:label "Diagnostic Coverage"@en .
ngm:diagnostic-feedback a skos:Concept ;
rdfs:label "Diagnostic Feedback"@en .
ngm:diagnostic-imaging a skos:Concept ;
rdfs:label "Diagnostic Imaging"@en .
ngm:diagnostic-interface a skos:Concept ;
rdfs:label "Diagnostic Interface"@en .
ngm:diagonalisation a skos:Concept ;
rdfs:label "Diagonalisation"@en .
ngm:diagram-driven-development a skos:Concept ;
rdfs:label "Diagram Driven Development"@en .
ngm:diagram-grammar a skos:Concept ;
rdfs:label "Diagram Grammar"@en .
ngm:diagram-grammar-compiler a skos:Concept ;
rdfs:label "Diagram Grammar Compiler"@en .
ngm:diagram-specification-language a skos:Concept ;
rdfs:label "Diagram Specification Language"@en .
ngm:diagrams-as-code a owl:Class ;
rdfs:comment "Diagrams as Code (DaC) is a software-engineering discipline and tooling category in which technical diagrams (architecture, sequence, state, deployment, entity-relationship, Gantt, wireframe, timing, dataflow) are authored as plain-text source artefacts in a constrained, machine-readable grammar ..."@en ;
rdfs:label "Diagrams as Code"@en ;
rdfs:subClassOf ngm:declarative-specification ;
rdfs:subClassOf ngm:documentation-as-code ;
rdfs:subClassOf ngm:domain-specific-language ;
rdfs:subClassOf ngm:software-engineering ;
rdfs:subClassOf ngm:text-based-authoring ;
rdfs:subClassOf ngm:version-controlled-artefact ;
rdfs:subClassOf _:r7803 ;
rdfs:subClassOf _:r7804 ;
rdfs:subClassOf _:r7805 ;
rdfs:subClassOf _:r7806 ;
rdfs:subClassOf _:r7807 ;
vc:contrastsWith ngm:generative-models ;
vc:contrastsWith ngm:lucidchart-drag-drop ;
vc:contrastsWith ngm:microsoft-visio ;
vc:contrastsWith ngm:whiteboard-photographs ;
vc:contrastsWith ngm:wysiwyg-editor ;
vc:dependsOn ngm:eclipse-layout-kernel ;
vc:dependsOn ngm:force-directed-layout ;
vc:dependsOn ngm:markdown ;
vc:dependsOn ngm:sugiyama-algorithm ;
vc:dependsOn ngm:svg ;
vc:dependsOn ngm:unicode ;
vc:enables ngm:architectural-decision-records ;
vc:enables ngm:c4-model ;
vc:enables ngm:code-review ;
vc:enables ngm:continuous-integration ;
vc:enables ngm:living-documentation ;
vc:enables ngm:refactor-time-consistency ;
vc:enables ngm:runbook ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:build-pipeline ;
vc:hasPart ngm:diagram-grammar ;
vc:hasPart ngm:icon-library ;
vc:hasPart ngm:layout-engine ;
vc:hasPart ngm:preview-plugin ;
vc:hasPart ngm:renderer ;
vc:hasPart ngm:source-file ;
vc:hasPart ngm:theme ;
vc:implements ngm:d2 ;
vc:implements ngm:graphviz-dot ;
vc:implements ngm:markdown-diagramming-as-code-tool ;
vc:implements ngm:penrose ;
vc:implements ngm:pikchr ;
vc:implements ngm:plantuml ;
vc:implements ngm:structurizr-dsl ;
vc:implements ngm:tikz ;
vc:implements ngm:vega-lite ;
vc:implements ngm:wavedrom ;
vc:qualityScore "0.52"^^xsd:float ;
vc:relatedTo ngm:adr ;
vc:relatedTo ngm:ai-diagram-tools ;
vc:relatedTo ngm:c4-model ;
vc:relatedTo ngm:diagrams-py ;
vc:relatedTo ngm:documentation-as-code ;
vc:relatedTo ngm:excalidraw ;
vc:relatedTo ngm:kroki ;
vc:relatedTo ngm:logseq ;
vc:relatedTo ngm:notion ;
vc:relatedTo ngm:static-site-generator ;
vc:requires ngm:layout-algorithm ;
vc:requires ngm:markdown ;
vc:requires ngm:render-toolchain ;
vc:requires ngm:text-editor ;
vc:requires ngm:version-control ;
vc:slug "diagrams-as-code" ;
vc:sourceDomain "infrastructure" ;
vc:standardizedBy ngm:ieee ;
vc:standardizedBy ngm:markdown-diagramming-as-code-tool ;
vc:standardizedBy ngm:object-management-group ;
vc:standardizedBy ngm:omg ;
vc:standardizedBy ngm:thoughtworks-tech-radar ;
vc:standardizedBy ngm:w3-c ;
vc:supports ngm:class-diagram ;
vc:supports ngm:deployment-diagram ;
vc:supports ngm:entity-relationship-diagram ;
vc:supports ngm:flowchart ;
vc:supports ngm:gantt-chart ;
vc:supports ngm:mind-map ;
vc:supports ngm:sequence-diagram ;
vc:supports ngm:state-diagram ;
vc:supports ngm:timing-diagram ;
vc:uses ngm:json-data-interchange-format-schema ;
vc:uses ngm:markdown-code-fence ;
vc:uses ngm:open-api-specification ;
vc:uses ngm:web-components ;
vc:uses ngm:yaml-frontmatter .
ngm:diagrams-py a skos:Concept ;
rdfs:label "Diagrams Py"@en .
ngm:dialogue-act-recognition a skos:Concept ;
rdfs:label "Dialogue Act Recognition"@en .
ngm:dialogue-history a skos:Concept ;
rdfs:label "Dialogue History"@en .
ngm:dialogue-management a owl:Class ;
rdfs:comment "Dialogue management is the component of a conversational system that tracks the evolving state of an interaction and decides the system's next action at each turn. It maintains context across utterances, integrates recognised user intents and slots, and selects responses or operations that move the conversation toward the user's goal. It is the control layer that connects language understanding to language generation in a dialogue agent."@en ;
rdfs:label "Dialogue Management"@en ;
rdfs:subClassOf ngm:conversational-ai ;
rdfs:subClassOf _:r7808 ;
rdfs:subClassOf _:r7809 ;
rdfs:subClassOf _:r7810 ;
vc:bridgesTo ngm:natural-language-understanding ;
vc:dependsOn ngm:natural-language-understanding ;
vc:enables ngm:chatbot ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:context-management ;
vc:hasPart ngm:state-tracking ;
vc:implements ngm:conversational-ai ;
vc:qualityScore "0.62"^^xsd:float ;
vc:relatedTo ngm:chatbot ;
vc:relatedTo ngm:context-management ;
vc:requires ngm:intent-recognition ;
vc:requires ngm:slot-filling ;
vc:slug "dialogue-management" ;
vc:sourceDomain "ai" ;
vc:supports ngm:natural-language-processing ;
vc:uses ngm:reinforcement-learning .
ngm:dialogue-policy a skos:Concept ;
rdfs:label "Dialogue Policy"@en .
ngm:dialogue-state-tracking a owl:Class ;
rdfs:comment "A component of conversational systems that maintains a structured representation of the user's goals and the context of a conversation across turns. It updates the dialogue state as new utterances are processed."@en ;
rdfs:label "Dialogue State Tracking"@en ;
rdfs:subClassOf ngm:conversational-ai ;
rdfs:subClassOf ngm:dialogue-system ;
rdfs:subClassOf ngm:dialogue-systems ;
rdfs:subClassOf ngm:natural-language-processing ;
rdfs:subClassOf ngm:task-oriented-dialogue-systems ;
rdfs:subClassOf _:r7811 ;
rdfs:subClassOf _:r7812 ;
rdfs:subClassOf _:r7813 ;
rdfs:subClassOf _:r7814 ;
rdfs:subClassOf _:r7815 ;
rdfs:subClassOf _:r7816 ;
rdfs:subClassOf _:r7817 ;
rdfs:subClassOf _:r7818 ;
rdfs:subClassOf _:r7819 ;
vc:contrastsWith ngm:chit-chat-systems ;
vc:contrastsWith ngm:eliza ;
vc:contrastsWith ngm:information-retrieval ;
vc:contrastsWith ngm:open-domain-dialogue ;
vc:contrastsWith ngm:retrieval-based-dialogue ;
vc:dependsOn ngm:attention-mechanism ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:intent-classification ;
vc:dependsOn ngm:large-language-models ;
vc:dependsOn ngm:named-entity-recognition ;
vc:dependsOn ngm:pre-trained-language-model ;
vc:dependsOn ngm:transformer-architecture ;
vc:enables ngm:conversational-ai ;
vc:enables ngm:customer-support-automation ;
vc:enables ngm:database-query ;
vc:enables ngm:dialogue-policy ;
vc:enables ngm:healthcare-triage ;
vc:enables ngm:intelligent-tutoring-system ;
vc:enables ngm:natural-language-generation ;
vc:enables ngm:spoken-dialogue-systems ;
vc:enables ngm:task-completion ;
vc:enables ngm:virtual-assistant ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:belief-state ;
vc:hasPart ngm:coreference-resolution ;
vc:hasPart ngm:dialogue-history ;
vc:hasPart ngm:domain-classification ;
vc:hasPart ngm:intent-recognition ;
vc:hasPart ngm:named-entity-recognition ;
vc:hasPart ngm:slot-filling ;
vc:hasPart ngm:utterance-encoding ;
vc:implements ngm:belief-state-update ;
vc:implements ngm:carry-over-mechanism ;
vc:implements ngm:context-accumulation ;
vc:implements ngm:domain-classification ;
vc:implements ngm:intent-classification ;
vc:implements ngm:slot-filling ;
vc:qualityScore "0.6"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:dialogue-policy ;
vc:relatedTo ngm:dialogue-systems ;
vc:relatedTo ngm:information-extraction ;
vc:relatedTo ngm:knowledge-graph ;
vc:relatedTo ngm:natural-language-generation ;
vc:relatedTo ngm:question-answering ;
vc:relatedTo ngm:sentiment-analysis ;
vc:relatedTo ngm:tool-augmented-reasoning ;
vc:requires ngm:data-annotation ;
vc:requires ngm:dialogue-history ;
vc:requires ngm:natural-language-processing ;
vc:requires ngm:natural-language-understanding ;
vc:requires ngm:ontology ;
vc:requires ngm:training-data ;
vc:requires ngm:utterance-encoding ;
vc:slug "dialogue-state-tracking" ;
vc:sourceDomain "ai" ;
vc:standardizedBy ngm:dstc-challenge-series ;
vc:standardizedBy ngm:multiwoz-benchmark ;
vc:standardizedBy ngm:schema-guided-dialogue ;
vc:supports ngm:customer-support-automation ;
vc:supports ngm:human-robot-interaction ;
vc:supports ngm:intelligent-tutoring-system ;
vc:supports ngm:spoken-dialogue-systems ;
vc:supports ngm:task-oriented-dialogue-systems ;
vc:supports ngm:voice-assistant ;
vc:uses ngm:attention-mechanism ;
vc:uses ngm:bert ;
vc:uses ngm:function-calling ;
vc:uses ngm:in-context-learning ;
vc:uses ngm:multiwoz ;
vc:uses ngm:retrieval-augmented-generation ;
vc:uses ngm:schema-guided-dialogue ;
vc:uses ngm:sequence-to-sequence-model .
ngm:dialogue-system a owl:Class ;
rdfs:comment "A Dialogue System (conversational AI system) is an AI application that engages in natural language conversations with users through text or speech, managing multi-turn interactions, maintaining conversational context, and executing task-oriented or open-domain dialogues. Modern dialogue systems employ transformer-based language models, dialogue state tracking, and reinforcement learning to power virtual assistants, customer service chatbots, and conversational interfaces."@en ;
rdfs:label "Dialogue System"@en ;
rdfs:subClassOf ngm:ai-application ;
rdfs:subClassOf ngm:natural-language-processing ;
rdfs:subClassOf _:r7820 ;
rdfs:subClassOf _:r7821 ;
rdfs:subClassOf _:r7822 ;
rdfs:subClassOf _:r7823 ;
rdfs:subClassOf _:r7824 ;
rdfs:subClassOf _:r7825 ;
rdfs:subClassOf _:r7826 ;
skos:broader ngm:ai-application ;
vc:bridgesTo ngm:human-computer-interaction ;
vc:bridgesTo ngm:spatial-computing ;
vc:bridgesTo ngm:telecollaboration ;
vc:contrastsWith ngm:rule-based-systems ;
vc:contrastsWith ngm:search-engine ;
vc:dependsOn ngm:large-language-model ;
vc:dependsOn ngm:reinforcement-learning ;
vc:enables ngm:conversational-ai ;
vc:enables ngm:customer-service-automation ;
vc:enables ngm:question-answering ;
vc:enables ngm:virtual-assistant ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:hasPart ngm:dialogue-state-tracking ;
vc:hasPart ngm:natural-language-generation ;
vc:hasPart ngm:natural-language-understanding ;
vc:implements ngm:context-management ;
vc:implements ngm:turn-taking ;
vc:qualityScore "0.68"^^xsd:float ;
vc:relatedTo ngm:chatbots ;
vc:relatedTo ngm:multimodal-ai-architecture-ai ;
vc:relatedTo ngm:sentiment-analysis ;
vc:requires ngm:intent-recognition ;
vc:requires ngm:natural-language-understanding ;
vc:requires ngm:speech-recognition ;
vc:requires ngm:transformer ;
vc:slug "dialogue-system" ;
vc:sourceDomain "artificial-intelligence" ;
vc:uses ngm:knowledge-graph ;
vc:uses ngm:slot-filling .
ngm:dialogue-systems a owl:Class ;
rdfs:comment "Dialogue systems are software systems that converse with users in natural language across one or more turns. They include task-oriented assistants, slot-filling pipelines, and open-domain conversational agents, managing intent recognition, dialogue state tracking, response selection and natural language generation."@en ;
rdfs:label "Dialogue Systems"@en ;
rdfs:subClassOf ngm:conversational-ai ;
rdfs:subClassOf ngm:human-computer-interaction ;
rdfs:subClassOf ngm:natural-language-processing ;
rdfs:subClassOf _:r7827 ;
rdfs:subClassOf _:r7828 ;
rdfs:subClassOf _:r7829 ;
rdfs:subClassOf _:r7830 ;
rdfs:subClassOf _:r7831 ;
rdfs:subClassOf _:r7832 ;
rdfs:subClassOf _:r7833 ;
rdfs:subClassOf _:r7834 ;
rdfs:subClassOf _:r7835 ;
rdfs:subClassOf _:r7836 ;
rdfs:subClassOf _:r7837 ;
rdfs:subClassOf _:r7838 ;
rdfs:subClassOf _:r7839 ;
rdfs:subClassOf _:r7840 ;
rdfs:subClassOf _:r7841 ;
vc:bridgesTo ngm:human-computer-interaction ;
vc:bridgesTo ngm:robotics ;
vc:contrastsWith ngm:batch-processing ;
vc:contrastsWith ngm:form-based-interface ;
vc:contrastsWith ngm:information-retrieval ;
vc:contrastsWith ngm:rule-based-systems ;
vc:contrastsWith ngm:scripted-chatbot ;
vc:dependsOn ngm:context-management ;
vc:dependsOn ngm:deep-learning ;
vc:dependsOn ngm:knowledge-representation ;
vc:dependsOn ngm:large-language-models ;
vc:dependsOn ngm:machine-learning-discipline ;
vc:dependsOn ngm:pre-trained-language-model ;
vc:dependsOn ngm:transformer-architecture ;
vc:enables ngm:agentic-ai-workflow ;
vc:enables ngm:chatbot ;
vc:enables ngm:customer-support-automation ;
vc:enables ngm:healthcare-triage ;
vc:enables ngm:human-robot-interaction ;
vc:enables ngm:intelligent-tutoring-system ;
vc:enables ngm:question-answering ;
vc:enables ngm:virtual-assistant ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:context-management ;
vc:hasPart ngm:dialogue-policy ;
vc:hasPart ngm:dialogue-state-tracking ;
vc:hasPart ngm:intent-recognition ;
vc:hasPart ngm:natural-language-generation ;
vc:hasPart ngm:natural-language-understanding ;
vc:hasPart ngm:response-selection ;
vc:hasPart ngm:slot-filling ;
vc:hasPart ngm:speech-recognition ;
vc:hasPart ngm:text-to-speech ;
vc:implements ngm:dialogue-policy ;
vc:implements ngm:dialogue-state-tracking ;
vc:implements ngm:intent-classification ;
vc:implements ngm:named-entity-recognition ;
vc:implements ngm:response-generation ;
vc:implements ngm:slot-filling ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:agentic-ai ;
vc:relatedTo ngm:conversational-ai ;
vc:relatedTo ngm:knowledge-graph ;
vc:relatedTo ngm:multimodal-ai-architecture-ai ;
vc:relatedTo ngm:question-answering ;
vc:relatedTo ngm:reinforcement-learning-from-human-feedback ;
vc:relatedTo ngm:sentiment-analysis ;
vc:requires ngm:context-management ;
vc:requires ngm:knowledge-base ;
vc:requires ngm:language-modeling ;
vc:requires ngm:natural-language-processing ;
vc:requires ngm:natural-language-understanding ;
vc:requires ngm:speech-recognition ;
vc:requires ngm:training-data ;
vc:slug "dialogue-systems" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:iso-iec-jtc1-sc42 ;
vc:standardizedBy ngm:multiwoz-benchmark ;
vc:standardizedBy ngm:schema-guided-dialogue ;
vc:standardizedBy ngm:w3-c ;
vc:supports ngm:accessibility ;
vc:supports ngm:autonomous-robot ;
vc:supports ngm:customer-support-automation ;
vc:supports ngm:digital-twin ;
vc:supports ngm:human-robot-interaction ;
vc:supports ngm:multimodal-ai-architecture-ai ;
vc:uses ngm:attention-mechanism ;
vc:uses ngm:in-context-learning ;
vc:uses ngm:large-language-models ;
vc:uses ngm:reinforcement-learning-from-human-feedback ;
vc:uses ngm:retrieval-augmented-generation ;
vc:uses ngm:tool-augmented-reasoning .
ngm:diba-inc a skos:Concept ;
rdfs:label "Diba Inc"@en .
ngm:dice-coefficient a skos:Concept ;
rdfs:label "Dice Coefficient"@en .
ngm:dicom a owl:Class ;
rdfs:comment "DICOM (Digital Imaging and Communications in Medicine) is the international standard for storing, transmitting, and managing medical images and associated metadata. It defines both a file format that binds pixel data to rich patient, study, and acquisition attributes, and network services for exchanging images between modalities, archives, and viewing workstations. DICOM enables interoperability across radiology, cardiology, and other imaging-intensive specialities, and serves as the canonical data substrate for medical imaging artificial intelligence."@en ;
rdfs:label "DICOM"@en ;
rdfs:subClassOf ngm:healthcare-data-standard ;
rdfs:subClassOf ngm:interoperability-standard ;
rdfs:subClassOf _:r6665 ;
rdfs:subClassOf _:r6666 ;
rdfs:subClassOf _:r6667 ;
rdfs:subClassOf _:r6668 ;
vc:bridgesTo ngm:electronic-health-record ;
vc:bridgesTo ngm:hl7-fhir ;
vc:bridgesTo ngm:interoperability-framework ;
vc:contrastsWith ngm:hl7-fhir ;
vc:contrastsWith ngm:nifti-format ;
vc:contrastsWith ngm:proprietary-imaging-format ;
vc:dependsOn ngm:picture-archiving-and-communication-system ;
vc:dependsOn ngm:standards-body ;
vc:enables ngm:clinical-decision-support ;
vc:enables ngm:data-annotation ;
vc:enables ngm:drug-discovery ;
vc:enables ngm:federated-learning ;
vc:enables ngm:image-segmentation ;
vc:enables ngm:medical-imaging ;
vc:enables ngm:medical-imaging-ai ;
vc:enables ngm:telehealth ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:dicom-data-dictionary ;
vc:hasPart ngm:dicom-file-format ;
vc:hasPart ngm:dicom-network-services ;
vc:hasPart ngm:dicom-rt-plan ;
vc:hasPart ngm:dicom-segmentation-iod ;
vc:hasPart ngm:dicom-sop-classes ;
vc:hasPart ngm:dicom-structured-reporting ;
vc:hasPart ngm:dicomweb ;
vc:implements ngm:data-governance ;
vc:implements ngm:semantic-interoperability ;
vc:isPartOf ngm:interoperability-standard ;
vc:qualityScore "0.9"^^xsd:float ;
vc:relatedTo ngm:artificial-intelligence ;
vc:relatedTo ngm:computer-vision ;
vc:relatedTo ngm:data-governance ;
vc:relatedTo ngm:digital-health ;
vc:relatedTo ngm:drug-discovery ;
vc:relatedTo ngm:electronic-health-record ;
vc:relatedTo ngm:medical-imaging ;
vc:relatedTo ngm:natural-language-processing ;
vc:requires ngm:data-protection ;
vc:requires ngm:interoperability ;
vc:requires ngm:picture-archiving-and-communication-system ;
vc:requires ngm:privacy ;
vc:requires ngm:security ;
vc:slug "dicom" ;
vc:sourceDomain "artificial-intelligence" ;
vc:standardizedBy ngm:standards-body ;
vc:supports ngm:computer-vision ;
vc:supports ngm:convolutional-neural-network ;
vc:supports ngm:dataset ;
vc:supports ngm:deep-learning ;
vc:supports ngm:healthcare-ai ;
vc:supports ngm:image-segmentation ;
vc:supports ngm:neural-network ;
vc:supports ngm:transfer-learning ;
vc:uses ngm:rest-api ;
vc:uses ngm:semantic-interoperability ;
vc:uses ngm:snomed-ct .
ngm:dicom-data-dictionary a skos:Concept ;
rdfs:label "Dicom Data Dictionary"@en .
ngm:dicom-file-format a skos:Concept ;
rdfs:label "Dicom File Format"@en .
ngm:dicom-network-services a skos:Concept ;
rdfs:label "Dicom Network Services"@en .
ngm:dicom-rt-plan a skos:Concept ;
rdfs:label "Dicom Rt Plan"@en .
ngm:dicom-segmentation-iod a skos:Concept ;
rdfs:label "Dicom Segmentation Iod"@en .
ngm:dicom-sop-classes a skos:Concept ;
rdfs:label "Dicom Sop Classes"@en .
ngm:dicom-structured-reporting a skos:Concept ;
rdfs:label "Dicom Structured Reporting"@en .
ngm:dicomweb a skos:Concept ;
rdfs:label "Dicomweb"@en .
ngm:dictionary-based-translation a skos:Concept ;
rdfs:label "Dictionary Based Translation"@en .
ngm:did a owl:Class ;
rdfs:comment "A decentralised identifier, a type of globally unique identifier that enables verifiable, self-sovereign digital identity without reliance on a central registry."@en ;
rdfs:label "DID"@en ;
rdfs:subClassOf ngm:self-sovereign-identity ;
rdfs:subClassOf _:r6698 ;
rdfs:subClassOf _:r6699 ;
rdfs:subClassOf _:r6700 ;
rdfs:subClassOf _:r6701 ;
vc:bridgesTo ngm:blockchain ;
vc:bridgesTo ngm:decentralized-identifiers ;
vc:bridgesTo ngm:distributed-collaboration ;
vc:contrastsWith ngm:centralized-identity-provider ;
vc:contrastsWith ngm:federated-identity ;
vc:enables ngm:authentication ;
vc:enables ngm:decentralized-identity ;
vc:enables ngm:key-agreement ;
vc:enables ngm:self-sovereign-identity ;
vc:enables ngm:verifiable-credentials ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:did-method ;
vc:implements ngm:w3-c-did-core ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:service-endpoint ;
vc:relatedTo ngm:trust-registry ;
vc:relatedTo ngm:wallet ;
vc:requires ngm:cryptography ;
vc:requires ngm:did-document ;
vc:requires ngm:did-resolver ;
vc:requires ngm:public-key ;
vc:slug "did" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:w3-c ;
vc:supports ngm:privacy-preserving-authentication ;
vc:supports ngm:selective-disclosure ;
vc:supports ngm:zero-knowledge-proof ;
vc:uses ngm:cryptographic-infrastructure ;
vc:uses ngm:digital-signature ;
vc:uses ngm:json-ld .
ngm:did-cheqd a skos:Concept ;
rdfs:label "DID Cheqd"@en .
ngm:did-controller a owl:Class ;
rdfs:comment "The entity—person, organisation, or autonomous system—authorised to make changes to a DID document, as defined by the W3C DID Core specification. The DID controller proves its authority by controlling the cryptographic keys or verification methods designated in the DID document, and may be the DID subject itself (self-sovereign control), a guardian acting for a subject such as a child or an IoT device, or a set of parties sharing control. It is unrelated to the PID controller of control engineering, with which it shares only a surface string."@en ;
rdfs:label "DID Controller"@en ;
rdfs:subClassOf ngm:entity ;
rdfs:subClassOf _:r6669 ;
rdfs:subClassOf _:r6670 ;
vc:hasMaturity ngmi:maturity-established ;
vc:isPartOf ngm:decentralized-identifiers ;
vc:qualityScore "0.8"^^xsd:float ;
vc:relatedTo ngm:decentralised-identity ;
vc:relatedTo ngm:did-document ;
vc:relatedTo ngm:digital-identity ;
vc:requires ngm:cryptographic-key ;
vc:requires ngm:key-management ;
vc:slug "did-controller" ;
vc:sourceDomain "security" .
ngm:did-document a owl:Class ;
rdfs:comment "A DID Document is a JSON-LD resource resolved from a Decentralised Identifier (DID) that expresses the DID subject's cryptographic public keys, authentication methods, assertion methods, key agreement protocols, capability delegation mechanisms, and service endpoints. Defined by the W3C DID Core specification, a DID Document is the machine-readable artefact that enables any verifier to discover how to authenticate with or communicate securely to a DID subject without relying on a centralised identity authority. DID Documents are anchored to a Verifiable Data Registry — such as a distributed ledger, blockchain, or peer-to-peer network — via a DID method-specific read operation, making them a foundational component of self-sovereign identity and verifiable credential ecosystems."@en ;
rdfs:label "DID Document"@en ;
rdfs:subClassOf ngm:decentralised-identifier ;
rdfs:subClassOf _:r6671 ;
rdfs:subClassOf _:r6672 ;
rdfs:subClassOf _:r6673 ;
rdfs:subClassOf _:r6674 ;
rdfs:subClassOf _:r6675 ;
vc:bridgesTo ngm:agent-identity ;
vc:bridgesTo ngm:zero-knowledge-proof ;
vc:contrastsWith ngm:centralized-identity-provider ;
vc:contrastsWith ngm:x-509-certificate ;
vc:enables ngm:decentralised-authentication ;
vc:enables ngm:key-agreement-protocol ;
vc:enables ngm:verifiable-credentials ;
vc:hasMaturity ngmi:maturity-established ;
vc:hasPart ngm:service-endpoint ;
vc:hasPart ngm:verification-method ;
vc:hasPart ngm:verification-relationship ;
vc:isPartOf ngm:decentralised-identifier ;
vc:isPartOf ngm:self-sovereign-identity ;
vc:qualityScore "0.72"^^xsd:float ;
vc:relatedTo ngm:did-resolution ;
vc:relatedTo ngm:did-url ;
vc:relatedTo ngm:digital-identity ;
vc:relatedTo ngm:identity-verification ;
vc:requires ngm:did-method ;
vc:requires ngm:did-resolver ;
vc:requires ngm:verifiable-data-registry ;
vc:slug "did-document" ;
vc:sourceDomain "blockchain" ;
vc:standardizedBy ngm:w3-c ;
vc:standardizedBy ngm:w3-c-did-core ;
vc:uses ngm:digital-signature ;
vc:uses ngm:json-ld ;
vc:uses ngm:linked-data ;
vc:uses ngm:public-key-cryptography .
ngm:did-document-metadata a skos:Concept ;
rdfs:label "DID Document Metadata"@en .
ngm:did-ethr a skos:Concept ;
rdfs:label "DID Ethr"@en .
ngm:did-indy a skos:Concept ;
rdfs:label "DID Indy"@en .
ngm:did-ion a skos:Concept ;
rdfs:label "DID Ion"@en .
ngm:did-jwk a skos:Concept ;
rdfs:label "DID Jwk"@en .
ngm:did-key a skos:Concept ;
rdfs:label "DID Key"@en .
ngm:did-method a owl:Class ;
rdfs:comment "A DID Method is a specification that defines how a particular type of Decentralised Identifier (DID) is created, resolved, updated, and deactivated, encoding the syntax rules and CRUD semantics for identifiers anchored to a specific verifiable data registry, ledger, or peer-to-peer network. Each method is identified by a unique method name embedded in the DID string (e.g. did:web, did:key, did:ion), and must provide a compliant DID Resolver that retrieves the corresponding DID Document containing public keys and service endpoints. DID Methods are standardised through the W3C DID Core specification and registered in the DIF DID Method Registry, enabling interoperable self-sovereign identity across heterogeneous systems. The diversity of methods reflects trade-offs between decentralisation guarantees, key management complexity, ledger dependency, and resolver performance."@en ;
rdfs:label "DID Method"@en ;
rdfs:subClassOf ngm:decentralized-identity ;
rdfs:subClassOf _:r6676 ;
rdfs:subClassOf _:r6677 ;
rdfs:subClassOf _:r6678 ;
rdfs:subClassOf _:r6679 ;
rdfs:subClassOf _:r6680 ;
vc:bridgesTo ngm:ipfs ;
vc:bridgesTo ngm:smart-contract ;
vc:contrastsWith ngm:centralized-identity-provider ;
vc:contrastsWith ngm:oauth ;
vc:contrastsWith ngm:x-509-certificate ;
vc:enables ngm:decentralised-authentication ;
vc:enables ngm:digital-identity ;
vc:enables ngm:self-sovereign-identity ;
vc:enables ngm:verifiable-credentials ;
vc:hasMaturity ngmi:maturity-established ;
vc:implements ngm:did-resolution ;
vc:implements ngm:w3-c-did-core ;
vc:qualityScore "0.75"^^xsd:float ;
vc:relatedTo ngm:decentralized-identity ;
vc:relatedTo ngm:did-resolver ;
vc:relatedTo ngm:digital-identity-wallet ;
vc:relatedTo ngm:zero-knowledge-proof ;
vc:requires ngm:cryptographic-infrastructure ;
vc:requires ngm:decentralised-identifier ;
vc:requires ngm:decentralized-identifier ;
vc:requires ngm:did-document ;
vc:requires ngm:verifiable-data-registry ;
vc:slug "did-method" ;
vc:sourceDomain "security" ;
vc:standardizedBy ngm:decentralized-identity-foundation ;
vc:standardizedBy ngm:w3-c ;
vc:uses ngm:content-addressing ;
vc:uses ngm:cryptographic-key-pair ;
vc:uses ngm:distributed-ledger-technology .
ngm:did-nostr a owl:Class ;
rdfs:comment "did:nostr is a W3C DID Core-conformant decentralised identifier method that represents a Nostr public key as a universally resolvable DID of the form did:nostr:{pubkey}, where {pubkey} is the 64-character hex secp256k1 key already used by the Nostr protocol. Because the identifier is the key, no registration, server, or fee is required: anyone with a Nostr keypair already has a DID. Resolution degrades gracefully across three layers — HTTP fetch of a .well-known/did/nostr/{pubkey}.json document, relay-enhanced resolution from Nostr kind 0 (metadata) and kind 10002 (relay list) events, and an offline fallback that derives a minimal valid DID document from the key alone. Keys are expressed in W3C Multikey/Multibase form (secp256k1 multicodec), letting Nostr identities authenticate to any DID-aware system, including Solid login, SSO, and verifiable-credential flows."@en ;
rdfs:label "did:nostr"@en ;
rdfs:subClassOf ngm:did-method ;
vc:bridgesTo ngm:block-trails ;
vc:bridgesTo ngm:javascript-solid-server ;
vc:bridgesTo ngm:solid ;
vc:bridgesTo ngm:webid-decentralised-identity-uri ;
vc:contrastsWith ngm:did-web ;
vc:dependsOn ngm:did-resolution ;
vc:enables ngm:self-sovereign-identity ;
vc:enables ngm:single-sign-on ;
vc:enables ngm:solid-oidc ;
vc:enables ngm:w3-c-verifiable-credentials ;
vc:hasMaturity ngmi:maturity-emerging ;
vc:implements ngm:decentralised-identifier ;
vc:implements ngm:w3-c-did-core ;
vc:qualityScore "0.74"^^xsd:float ;
vc:relatedTo ngm:decentralised-identity ;
vc:relatedTo ngm:web-authn ;
vc:relatedTo ngm:web-contracts ;
vc:slug "did-nostr" ;
vc:sourceDomain "security" ;
vc:uses ngm:multibase ;
vc:uses ngm:nostr ;
vc:uses ngm:schnorr-signature ;
vc:uses ngm:secp256k1 .
ngm:did-nostr-identity a owl:Class ;
rdfs:comment "A W3C DID Core|W3C Decentralised Identifier (did:nostr: