<![CDATA[Semantic Data Models and Ontologies]]>

<![CDATA[Semantic Data Models and Ontologies]]>A semantic data model describes what data means, not just how it is stored. Resources are linked to shared vocabulary concepts so machines and humans can interpret and query data consistently across systems.

On the web of data, meaning is represented with graph standards:

RDF expresses facts as subject-predicate-object triples.
OWL 2 defines classes, properties, and logical constraints.
SHACL validates whether instance data matches expected structures.

An ontology formally specifies a domain: classes, object properties, datatype properties, and subclass axioms. Reference ontologies like PMD Core ontology anchor project-specific extensions so new terms stay interoperable. MAT-X pipelines (Autoencoder, Agent-TOM) extract or learn candidate classes but ground exports under reference rdfs:subClassOf parents.

Further reading