Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Slater, Luke T., Gkoutos, Georgios V., Hoehndorf, Robert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
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
_version_ 1783622757956714496
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
work_keys_str_mv AT slaterluket towardssemanticinteroperabilityfindingandrepairinghiddencontradictionsinbiomedicalontologies
AT gkoutosgeorgiosv towardssemanticinteroperabilityfindingandrepairinghiddencontradictionsinbiomedicalontologies
AT hoehndorfrobert towardssemanticinteroperabilityfindingandrepairinghiddencontradictionsinbiomedicalontologies