ComR: a combined OWL reasoner for ontology classification

Abstract

Ontology classification, the problem of computing the subsumption hierarchies for classes (atomic concepts), is a core reasoning service provided by Web Ontology Language (OWL) reasoners. Although general-purpose OWL 2 reasoners employ sophisticated optimizations for classification, they are still not efficient owing to the high complexity of tableau algorithms for expressive ontologies. Profile-specific OWL 2 EL reasoners are efficient; however, they become incomplete even if the ontology contains only a small number of axioms that are outside the OWL 2 EL fragment. In this paper, we present a technique that combines an OWL 2 EL reasoner with an OWL 2 reasoner for ontology classification of expressive SROIQ. To optimize the workload, we propose a task decomposition strategy for identifying the minimal non-EL subontology that contains only necessary axioms to ensure completeness. During the ontology classification, the bulk of the workload is delegated to an efficient OWL 2 EL reasoner and only the minimal non-EL subontology is handled by a less efficient OWL 2 reasoner. The proposed approach is implemented in a prototype ComR and experimental results show that our approach offers a substantial speedup in ontology classification. For the well-known ontology NCI, the classification time is reduced by 96.9% (resp. 83.7%) compared against the standard reasoner Pellet (resp. the modular reasoner MORe).