Using AberOWL for fast and scalable reasoning over BioPortal ontologies.

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

doi:10.1186/s13326-016-0090-0

Abstract

BackgroundReasoning 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.MethodsWe 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 conclusionsWe 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.

Highlights

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
We demonstrate that the AberOWL framework makes it possible to provide, at least, light-weight description logic reasoning over most of the freely accessible ontologies contained in BioPortal, with a relatively low memory footprint and high scalability with respect to the number of queries executed in parallel, using only a single medium-sized server as hardware to provide these services
We have demonstrated that it is feasible to reason over most of the ontologies available in BioPortal in real time, and that queries over these ontologies can be answered quickly, in real-time, and using only standard server hardware

Summary

Introduction

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. 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 Major ontology repositories such as BioPortal [1], OntoBee [2], or the Ontology Lookup Service [3], have existed for a number of years, and currently contain several hundred ontologies. Currently missing from the major ontology repositories, is the ability to provide online access to reasoning services simultaneously over many ontologies Such a feature would enable the use of semantics and deductive inference when processing data characterized by the ontologies these repositories contain [4].

Methods

Results

Conclusion