Description logic programs

TLDR

The paper demonstrates how to semantically and inferentially interoperate between rule-based systems and ontologies by analyzing their expressive intersection. The authors introduce Description Logic Programs (DLP) and the related Description Horn Logic (DHL) as an intermediate representation, and describe a bidirectional translation (fusion) that maps premises and inferences between DL and LP fragments. DLP offers expressiveness beyond RDF‑Schema, and its fusion technique enables rules to be built atop ontologies and vice versa, allowing efficient LP inference over large DL ontologies.

Abstract

We show how to interoperate, semantically and inferentially, between the leading Semantic Web approaches to rules (RuleML Logic Programs) and ontologies (OWL/DAML+OIL Description Logic) via analyzing their expressive intersection. To do so, we define a new intermediate knowledge representation (KR) contained within this intersection: Description Logic Programs (DLP), and the closely related Description Horn Logic (DHL) which is an expressive fragment of first-order logic (FOL). DLP provides a significant degree of expressiveness, substantially greater than the RDF-Schema fragment of Description Logic. We show how to perform DLP-fusion: the bidirectional translation of premises and inferences (including typical kinds of queries) from the DLP fragment of DL to LP, and vice versa from the DLP fragment of LP to DL. In particular, this translation enables one to "build rules on top of ontologies": it enables the rule KR to have access to DL ontological definitions for vocabulary primitives (e.g., predicates and individual constants) used by the rules. Conversely, the DLP-fusion technique likewise enables one to "build ontologies on top of rules": it enables ontological definitions to be supplemented by rules, or imported into DL from rules. It also enables available efficient LP inferencing algorithms/implementations to be exploited for reasoning over large-scale DL ontologies.