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.

Keywords:
Computer science Description logic Fragment (logic) Programming language Semantic Web Knowledge representation and reasoning RDF Theoretical computer science Artificial intelligence

Metrics

13
Cited By
0.38
FWCI (Field Weighted Citation Impact)
0
Refs
0.75
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Semantic Web and Ontologies
Physical Sciences →  Computer Science →  Artificial Intelligence
Natural Language Processing Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
Service-Oriented Architecture and Web Services
Physical Sciences →  Computer Science →  Information Systems

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