Ontology translation by ontology merging and automated reasoning

Ontologies are a crucial tool for formally specifying the vocabulary and relationship of concepts used on the Semantic Web. In order to share information, web-based agents that use different vocabularies must be able to translate data from one ontological framework to another, both syntactically and semantically. This dissertation describes ontology translation in three categories: dataset translation, ontology extension generation, and querying through different ontologies. The approach that has been proposed in this work is: ontology translation by ontology merging and automated reasoning. Ontology translation can be thought of in terms of formal inference. The merge of two related ontologies is obtained by taking the union of the concepts and the axioms defining them, and then adding bridging axioms that relate their concepts. The resulting merged ontology serves as an inferential medium for ontology translation. Web-PDDL, a strongly typed first-order logic language for the Semantic Web, can work as the internal representation for ontology merging and ontology translation. The syntactic translation can be done by an automatic syntax translator between Web-PDDL and other web agent languages. The semantic translation can be implemented by an inference engine, OntoEngine, a first order theorem prover with equality substitutions, running in both forward and backward chaining ways. The approach has also been extended to handle conditional fact translation, axiom derivation, ontology composition and data integration for web-based databases.

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