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  Improving ontologies by automatic reasoning and evaluation of logical definitions

Kohler, S., Bauer, S., Mungall, C. J., Carletti, G., Smith, C. L., Schofield, P., et al. (2011). Improving ontologies by automatic reasoning and evaluation of logical definitions. BMC Bioinformatics, 12, 418. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/22032770 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3224779/pdf/1471-2105-12-418.pdf?tool=pmcentrez.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-7820-6 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-7821-4
Genre: Journal Article

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 Creators:
Kohler, S., Author
Bauer, S., Author
Mungall, C. J., Author
Carletti, G., Author
Smith, C. L., Author
Schofield, P., Author
Gkoutos, G. V., Author
Robinson, P. N.1, Author              
Affiliations:
1Research Group Development & Disease (Head: Stefan Mundlos), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1433557              

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 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.

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 Dates: 2011
 Publication Status: Published in print
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Title: BMC Bioinformatics
Source Genre: Journal
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Pages: - Volume / Issue: 12 Sequence Number: - Start / End Page: 418 Identifier: ISSN: 1471-2105 (Electronic) 1471-2105 (Linking)