Aber-OWL: a framework for ontology-based data access in biology

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

Research output: Contribution to journalArticlepeer-review

60 Scopus citations

Abstract

Background: Many ontologies have been developed in biology and these ontologies increasingly contain large volumes of formalized knowledge commonly expressed in the Web Ontology Language (OWL). Computational access to the knowledge contained within these ontologies relies on the use of automated reasoning. Results: We have developed the Aber-OWL infrastructure that provides reasoning services for bio-ontologies. Aber-OWL consists of an ontology repository, a set of web services and web interfaces that enable ontology-based semantic access to biological data and literature. Aber-OWL is freely available at http://aber-owl.net. Conclusions: Aber-OWL provides a framework for automatically accessing information that is annotated with ontologies or contains terms used to label classes in ontologies. When using Aber-OWL, access to ontologies and data annotated with them is not merely based on class names or identifiers but rather on the knowledge the ontologies contain and the inferences that can be drawn from it.
Original languageEnglish (US)
JournalBMC Bioinformatics
Volume16
Issue number1
DOIs
StatePublished - Jan 28 2015

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01

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