Towards scalable ontology engineering patterns: lessons learned from an experiment based on W3C's part-whole guidelines

Abstract

This paper presents an empirical evaluation of description logic reasoners to support the selection of scalable ontology engineering patterns for TBox reasoning. Our main objective is to define the rationale behind the design decisions required for the generation of large ontologies with XSLT-based tools. We discuss here the outcomes of an experiment focusing on aircraft components and parts for which we have implemented the ontology design guidelines for part-whole relationships published by W3C's Semantic Web best practices working group. We have worked with the following reasoners, being the best state-of-the-art currently available: FaCT++, RACER, Pellet and CEL. We found considerable variation in reasoner performance and have attempted to characterise the factors that distinguish the reasoners to enable a best-practice design style to be successfully applied for the generation of very large ontologies.