DatalogDL:: Datalog rules parameterized by description logics

Combining ontologies with rules has become a central topic in the Semantic Web. Bridging the discrepancy between these two knowledge representations, this paper introduces Datalog(DL) as a family of hybrid languages, where Datalog rules are parameterized by various DL (description logic) languages ranging from A L C to S H I Q. Making Datalog(DL) a decidable system with complexity of EXPTIME, we propose independent properties in the DL body as the restriction to hybrid rules, and weaken the safeness condition to balance the trade-off between expressivity and reasoning power. Building on existing well-developed techniques, we present a principled approach to enrich (RuleML) rules with information from (OWL) ontologies, and develop a prototype system integrating a rule engine (OO jDREW) with a DL reasoner (RACER).