Using AberOWL for fast and scalable reasoning over BioPortal ontologies. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Slater, Luke; Gkoutos, Georgios; Schofield, Paul; Hoehndorf, Robert
• Is Part Of: Journal of biomedical semantics. Volume 7:Issue 1(2016)
• Page Start: 1
• Page End: 6
• Publication Date: 2016-12
• Subjects: Ontology -- Reasoning -- Scalable reasoning -- Description logics -- OWL -- AberOWL; Semantics -- Periodicals; Medicine -- Research -- Periodicals; Biology -- Research -- Periodicals; Computer systems -- Periodicals; Bioinformatics -- Periodicals; 570.285
• DOI: 10.1186/s13326-016-0090-0
• Languages: English
• ISSNs: 2041-1480

Abstract

Abstract Background Reasoning over biomedical ontologies using their OWL semantics has traditionally been a challenging task due to the high theoretical complexity of OWL-based automated reasoning. As a consequence, ontology repositories, as well as most other tools utilizing ontologies, either provide access to ontologies without use of automated reasoning, or limit the number of ontologies for which automated reasoning-based access is provided. Methods We apply the AberOWL infrastructure to provide automated reasoning-based access to all accessible and consistent ontologies in BioPortal (368 ontologies). We perform an extensive performance evaluation to determine query times, both for queries of different complexity and for queries that are performed in parallel over the ontologies. Results and conclusions We demonstrate that, with the exception of a few ontologies, even complex and parallel queries can now be answered in milliseconds, therefore allowing automated reasoning to be used on a large scale, to run in parallel, and with rapid response times.