Distributed Resolution for Expressive Ontology Networks

Abstract

The Semantic Web is commonly perceived as a web of partially interlinked machine readable data. This data is inherently distributed and resembles the structure of the web in terms of resources being provided by different parties at different physical locations. A number of infrastructures for storing and querying distributed semantic web data, primarily encoded in RDF have been developed but almost all the work on description logic reasoning as a basis for implementing inference in the Web Ontology Language OWL still assumes a centralized approach where the complete terminology has to be present on a single system and all inference steps are carried out on this system. We propose a distributed reasoning method that preserves soundness and completeness of reasoning under the original OWL import semantics. The method is based on resolution methods for $\mathcal{ALCHIQ}$ ontologies that we modify to work in a distributed setting. Results show a promising runtime decrease compared to centralized reasoning and indicate that benefits from parallel computation trade off the overhead caused by communication between the local reasoners.