A Framework for Parallelizing OWL Classification in Description Logic Reasoners
This addresses the need for faster ontology classification in description logic reasoners, which is incremental as it builds on existing methods.
The paper tackled the problem of speeding up OWL ontology classification by proposing a parallel framework that can be applied to existing reasoners, resulting in an improvement of wall clock time by one order of magnitude for most real-world ontologies.
In this paper we report on a black-box approach to parallelize existing description logic (DL) reasoners for the Web Ontology Language (OWL). We focus on OWL ontology classification, which is an important inference service and supported by every major OWL/DL reasoner. We propose a flexible parallel framework which can be applied to existing OWL reasoners in order to speed up their classification process. In order to test its performance, we evaluated our framework by parallelizing major OWL reasoners for concept classification. In comparison to the selected black-box reasoner our results demonstrate that the wall clock time of ontology classification can be improved by one order of magnitude for most real-world ontologies.