What is Ontology?
An ontology is a formal, explicit specification of a shared conceptualization within a knowledge domain. It defines the types of entities that exist, their properties, the relationships between entities, and the rules or constraints that govern the domain. Ontologies provide a structured vocabulary and logical framework for representing knowledge in a way that both humans and machines can understand and reason about.
Ontologies go beyond simple taxonomies or knowledge graphs by including formal definitions, axioms, and inference rules. They specify not just what entities and relationships exist, but also what properties entities must or can have, what constraints apply to relationships, and what logical inferences can be drawn from the knowledge. For example, an ontology might specify that "Person" and "Organization" are distinct types, a person can work for at most one organization, and if person A works for organization B and B is a subsidiary of C, then A is indirectly associated with C.
In AI systems, ontologies serve multiple purposes: they provide standardized vocabularies for knowledge representation, enable logical reasoning and inference over knowledge bases, support data integration from multiple sources by providing common semantics, and facilitate knowledge sharing between systems. Technologies like OWL (Web Ontology Language) and RDF Schema provide standards for defining ontologies. While building comprehensive ontologies requires significant effort, they enable sophisticated reasoning capabilities and semantic interoperability that simpler knowledge representations cannot support.