Efficiently querying RDF(S) ontologies with Answer Set Programming

Ontologies are pervading many areas of knowledge representation and management. To date, most research efforts have been spent on the development of sufficiently expressive languages for the representation and querying of ontologies; however, querying efficiency has received attention only recently, especially for ontologies referring to large amounts of data. In fact, it is still uncertain how reasoning tasks will scale when applied on massive amounts of data. This work is a first step toward this setting: it first shows that Resource Description Framework(Schema) [RDF(S)] ontologies can be expressed, without loss of semantics, into Answer Set Programming (ASP). Then, based on a previous result showing that the SPARQL query language (a candidate W3C recommendation for RDF(S) ontologies) can be mapped to a rule-based language, it shows that efficient querying of big ontologies can be accomplished with a database oriented extension of the well known ASP system DLV, which we recently developed. Results reported in the article show that our proposed framework is promising for the improvement of both scalability and expressiveness of available RDF(S) storage and query systems.