A structured specification defining metadata elements, their semantics, syntax, and relationships for describing and managing information resources. Metadata schemas establish standardised vocabularies and constraints that enable interoperability, discovery, and governance across data ecosystems through predefined sets of descriptive attributes tailored for specific domains or resource types.
Semantic Classification
Content
Definition
A Metadata Schema is a formal specification that defines the structure, semantics, and constraints for metadata elements used to describe information resources. It establishes standardised vocabularies enabling consistent documentation of data assets across systems and organisations.
Core Components
Schema Elements
-
Element Name: Unique identifier for the metadata attribute
-
Semantics: Formal meaning and interpretation rules
-
Syntax: Data type, format, and encoding constraints
-
Cardinality: Required, optional, or repeatable designations
-
Controlled Vocabularies: Permitted value sets or taxonomies
Schema Types
- Descriptive Schemas: Resource discovery and identification (Dublin Core)
- Structural Schemas: Data organisation and relationships (XML Schema)
- Administrative Schemas: Management and provenance tracking
- Technical Schemas: Format, encoding, and processing specifications
Standards and Frameworks
Core Standards
-
Dublin Core Metadata Initiative: 15 core elements for resource description
-
Schema.org: Web content structured data vocabulary
-
Data Documentation Initiative (DDI): Survey and observational data
-
ISO 19115: Geographic information metadata
Semantic Web Standards
-
RDF Schema (RDFS): Vocabulary definition framework
-
Web Ontology Language (OWL): Complex ontology specification
-
SHACL: Validation constraints and data quality rules
-
JSON-LD: Semantic contexts for linked data
Applications
Data Governance
-
Asset inventory and cataloguing
-
Lineage and provenance tracking
-
Quality assessment and compliance
-
Access control and classification
Knowledge Management
-
Semantic search and discovery
-
Cross-system interoperability
-
Knowledge graph construction
-
Automated metadata generation
References