Combining Declarative and Procedural Knowledge to Automate and Represent Ontology Mapping

Ontologies on the Semantic Web are by nature decentralized. From the body of ontology mapping approaches, we can draw a conclusion that an effective approach to automate ontology mapping requires both data and metadata in application domains. Most existing approaches usually represent data and metadata by ad-hoc data structures, which lack formalisms to capture the underlying semantics. Furthermore, to approach semantic interoperability, there is a need to represent mappings between ontologies with well-defined semantics that guarantee accurate exchange of information. To address these problems, we propose that domain ontologies attached with extraction procedures are capable of representing knowledge required to find direct and indirect matches between ontologies. And mapping ontologies attached with query procedures not only support equivalent inferences and computations on equivalent concepts and relations but also improve query performance by applying query procedures to derive target-specific views. We conclude that a combination of declarative and procedural representation based on ontologies favors the analysis and implementation for ontology mapping that promises accurate and efficient semantic interoperability.