Using Aber-OWL for fast and scalable reasoning over BioPortal ontologies

Luke Slater*, Georgios V. Gkoutos, Paul N. Schofield, Robert Hoehndorf

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

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. We apply the Aber-OWL 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 as well as for queries that are performed in parallel over the ontologies. 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.

Original languageEnglish (US)
JournalCEUR Workshop Proceedings
Volume1515
StatePublished - 2015

ASJC Scopus subject areas

  • Computer Science(all)

Fingerprint Dive into the research topics of 'Using Aber-OWL for fast and scalable reasoning over BioPortal ontologies'. Together they form a unique fingerprint.

Cite this