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Ontology language

In computer science and artificial intelligence, ontology languages are formal languages used to construct ontologies. They allow the encoding of knowledge about specific domains and often include reasoning rules that support the processing of that knowledge. Ontology languages are usually declarative languages, are almost always generalizations of frame languages, and are commonly based on either first-order logic or on description logic. Common Logic - and its dialects CycL DOGMA (Developing Ontology-Grounded Methods and Applications) F-Logic (Frame Logic) FO-dot (First-order logic extended with types, arithmetic, aggregates and inductive definitions) KIF (Knowledge Interchange Format) Ontolingua based on KIF KL-ONE KM programming language LOOM (ontology) OCML (Operational Conceptual Modelling Language) OKBC (Open Knowledge Base Connectivity) PLIB (Parts LIBrary) RACER These languages use a markup scheme to encode knowledge, most commonly with XML. DAML+OIL Ontology Inference Layer (OIL) Web Ontology Language (OWL) Resource Description Framework (RDF) RDF Schema (RDFS) SHOE Attempto Controlled English Executable English Three languages are completely or partially frame-based languages. F-Logic OKBC KM Description logic provides an extension of frame languages, without going so far as to take the leap to first-order logic and support for arbitrary predicates. KL-ONE RACER OWL. Gellish is an example of a combined ontology language and ontology that is description logic based. It distinguishes between the semantic differences among others of: relation types for relations between concepts (classes) relation types for relations between individuals relation types for relations between individuals and classes It also contains constructs to express queries and communicative intent. Several ontology languages support expressions in first-order logic and allow general predicates.

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Frame (artificial intelligence)
Frames are an artificial intelligence data structure used to divide knowledge into substructures by representing "stereotyped situations". They were proposed by Marvin Minsky in his 1974 article "A Framework for Representing Knowledge". Frames are the primary data structure used in artificial intelligence frame languages; they are stored as ontologies of sets. Frames are also an extensive part of knowledge representation and reasoning schemes. They were originally derived from semantic networks and are therefore part of structure-based knowledge representations.
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