Improving Ontologies by Automatic Reasoning and Evaluation of Logical Definitions

Overview

Journal BMC Bioinformatics

Publisher Biomed Central

Specialty Biology

Date 2011 Oct 29

PMID 22032770

Citations 19

Authors

Sebastian Kohler

Sebastian Bauer

Chris J Mungall

Gabriele Carletti

Cynthia L Smith

Paul Schofield

Georgios V Gkoutos

Peter N Robinson

Affiliations

Soon will be listed here.

Abstract

Background: Ontologies are widely used to represent knowledge in biomedicine. Systematic approaches for detecting errors and disagreements are needed for large ontologies with hundreds or thousands of terms and semantic relationships. A recent approach of defining terms using logical definitions is now increasingly being adopted as a method for quality control as well as for facilitating interoperability and data integration.

Results: We show how automated reasoning over logical definitions of ontology terms can be used to improve ontology structure. We provide the Java software package GULO (Getting an Understanding of LOgical definitions), which allows fast and easy evaluation for any kind of logically decomposed ontology by generating a composite OWL ontology from appropriate subsets of the referenced ontologies and comparing the inferred relationships with the relationships asserted in the target ontology. As a case study we show how to use GULO to evaluate the logical definitions that have been developed for the Mammalian Phenotype Ontology (MPO).

Conclusions: Logical definitions of terms from biomedical ontologies represent an important resource for error and disagreement detection. GULO gives ontology curators a fast and simple tool for validation of their work.

Citing Articles

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Expansion of the Human Phenotype Ontology (HPO) knowledge base and resources.

Kohler S, Carmody L, Vasilevsky N, Jacobsen J, Danis D, Gourdine J Nucleic Acids Res. 2018; 47(D1):D1018-D1027.

PMID: 30476213 PMC: 6324074. DOI: 10.1093/nar/gky1105.

The Human Phenotype Ontology: Semantic Unification of Common and Rare Disease.

Groza T, Kohler S, Moldenhauer D, Vasilevsky N, Baynam G, Zemojtel T Am J Hum Genet. 2015; 97(1):111-24.

PMID: 26119816 PMC: 4572507. DOI: 10.1016/j.ajhg.2015.05.020.

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