Ontology Modeling

Coverage

Formalize domain meaning into classes, properties, constraints, and axioms. Covers class hierarchy, object/data properties, domain/range, cardinality constraints, equivalence, disjointness, identity, controlled vocabularies, validation shapes, and interop-oriented JSON-LD/RDF projection. The output may be an actual ontology file or a precise ontology sketch before implementation.

Philosophy

Ontology modeling is only worth its cost when ambiguity, interoperability, validation, or reasoning matter. Most teams do not need OWL. They need clear conceptual models and controlled vocabularies. Escalate to ontology when another consumer must compute over the semantics, validate instances against constraints, or align meaning across systems.

The ontology must preserve business meaning while stating which inferences are allowed. A vague ontology is worse than no ontology because it gives false confidence to downstream tools.

Method