Formal system for Ontology based knowledge extraction


In philosophy, ontology is the study of the kinds of things that exist. It is often said that ontologies “carve the world at its joints.” In AI, the term ontology has largely come to mean one of two related things. Research on ontology is becoming increasingly widespread in the computer science community, and its importance is being recognized in a multiplicity of research fields and application areas, including knowledge engineering, database design and integration, information retrieval and extraction. Ontologies are becoming a recognized vehicle for knowledge reuse, knowledge sharing, and modeling. Ontology Based Knowledge Access (OBKA) has drawn considerable attention from the OWL and RDF communities. In OBKA, instance knowledge is accessed by means of mappings, which state the relationship between the knowledge in a data source (e.g., an RDBMSs) and the vocabulary of an ontology. In this project we present a new system for OBKA focused on fast and efficient reasoning with large ontologies and large volumes of data. System provides SPARQL query answering with OWL 2 QL/RDFS entailments and can function as a traditional OWL reasoner/triple store, or as a mediator, located on-top of a legacy data source linked to the ontology by means of mappings.