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Towards semantic interoperability: finding and repairing hidden contradictions in biomedical ontologies
BACKGROUND: Ontologies are widely used throughout the biomedical domain. These ontologies formally represent the classes and relations assumed to exist within a domain. As scientific domains are deeply interlinked, so too are their representations. While individual ontologies can be tested for consi...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7736131/ https://www.ncbi.nlm.nih.gov/pubmed/33319712 http://dx.doi.org/10.1186/s12911-020-01336-2 |
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author | Slater, Luke T. Gkoutos, Georgios V. Hoehndorf, Robert |
author_facet | Slater, Luke T. Gkoutos, Georgios V. Hoehndorf, Robert |
author_sort | Slater, Luke T. |
collection | PubMed |
description | BACKGROUND: Ontologies are widely used throughout the biomedical domain. These ontologies formally represent the classes and relations assumed to exist within a domain. As scientific domains are deeply interlinked, so too are their representations. While individual ontologies can be tested for consistency and coherency using automated reasoning methods, systematically combining ontologies of multiple domains together may reveal previously hidden contradictions. METHODS: We developed a method that tests for hidden unsatisfiabilities in an ontology that arise when combined with other ontologies. For this purpose, we combined sets of ontologies and use automated reasoning to determine whether unsatisfiable classes are present. In addition, we designed and implemented a novel algorithm that can determine justifications for contradictions across extremely large and complicated ontologies, and use these justifications to semi-automatically repair ontologies by identifying a small set of axioms that, when removed, result in a consistent and coherent set of ontologies. RESULTS: We tested the mutual consistency of the OBO Foundry and the OBO ontologies and find that the combined OBO Foundry gives rise to at least 636 unsatisfiable classes, while the OBO ontologies give rise to more than 300,000 unsatisfiable classes. We also applied our semi-automatic repair algorithm to each combination of OBO ontologies that resulted in unsatisfiable classes, finding that only 117 axioms could be removed to account for all cases of unsatisfiability across all OBO ontologies. CONCLUSIONS: We identified a large set of hidden unsatisfiability across a broad range of biomedical ontologies, and we find that this large set of unsatisfiable classes is the result of a relatively small amount of axiomatic disagreements. Our results show that hidden unsatisfiability is a serious problem in ontology interoperability; however, our results also provide a way towards more consistent ontologies by addressing the issues we identified. |
format | Online Article Text |
id | pubmed-7736131 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-77361312020-12-15 Towards semantic interoperability: finding and repairing hidden contradictions in biomedical ontologies Slater, Luke T. Gkoutos, Georgios V. Hoehndorf, Robert BMC Med Inform Decis Mak Research BACKGROUND: Ontologies are widely used throughout the biomedical domain. These ontologies formally represent the classes and relations assumed to exist within a domain. As scientific domains are deeply interlinked, so too are their representations. While individual ontologies can be tested for consistency and coherency using automated reasoning methods, systematically combining ontologies of multiple domains together may reveal previously hidden contradictions. METHODS: We developed a method that tests for hidden unsatisfiabilities in an ontology that arise when combined with other ontologies. For this purpose, we combined sets of ontologies and use automated reasoning to determine whether unsatisfiable classes are present. In addition, we designed and implemented a novel algorithm that can determine justifications for contradictions across extremely large and complicated ontologies, and use these justifications to semi-automatically repair ontologies by identifying a small set of axioms that, when removed, result in a consistent and coherent set of ontologies. RESULTS: We tested the mutual consistency of the OBO Foundry and the OBO ontologies and find that the combined OBO Foundry gives rise to at least 636 unsatisfiable classes, while the OBO ontologies give rise to more than 300,000 unsatisfiable classes. We also applied our semi-automatic repair algorithm to each combination of OBO ontologies that resulted in unsatisfiable classes, finding that only 117 axioms could be removed to account for all cases of unsatisfiability across all OBO ontologies. CONCLUSIONS: We identified a large set of hidden unsatisfiability across a broad range of biomedical ontologies, and we find that this large set of unsatisfiable classes is the result of a relatively small amount of axiomatic disagreements. Our results show that hidden unsatisfiability is a serious problem in ontology interoperability; however, our results also provide a way towards more consistent ontologies by addressing the issues we identified. BioMed Central 2020-12-15 /pmc/articles/PMC7736131/ /pubmed/33319712 http://dx.doi.org/10.1186/s12911-020-01336-2 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Slater, Luke T. Gkoutos, Georgios V. Hoehndorf, Robert Towards semantic interoperability: finding and repairing hidden contradictions in biomedical ontologies |
title | Towards semantic interoperability: finding and repairing hidden contradictions in biomedical ontologies |
title_full | Towards semantic interoperability: finding and repairing hidden contradictions in biomedical ontologies |
title_fullStr | Towards semantic interoperability: finding and repairing hidden contradictions in biomedical ontologies |
title_full_unstemmed | Towards semantic interoperability: finding and repairing hidden contradictions in biomedical ontologies |
title_short | Towards semantic interoperability: finding and repairing hidden contradictions in biomedical ontologies |
title_sort | towards semantic interoperability: finding and repairing hidden contradictions in biomedical ontologies |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7736131/ https://www.ncbi.nlm.nih.gov/pubmed/33319712 http://dx.doi.org/10.1186/s12911-020-01336-2 |
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