Tackling the challenges of matching biomedical ontologies
Abstract Background Biomedical ontologies pose several challenges to ontology matching due both to the complexity of the biomedical domain and to the characteristics of the ontologies themselves. The biomedical tracks in the Ontology Matching Evaluation Initiative (OAEI) have spurred the development...
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| Format: | Article |
| Language: | English |
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BMC
2018-01-01
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| Series: | Journal of Biomedical Semantics |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s13326-017-0170-9 |
| _version_ | 1828791306514595840 |
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| author | Daniel Faria Catia Pesquita Isabela Mott Catarina Martins Francisco M. Couto Isabel F. Cruz |
| author_facet | Daniel Faria Catia Pesquita Isabela Mott Catarina Martins Francisco M. Couto Isabel F. Cruz |
| author_sort | Daniel Faria |
| collection | DOAJ |
| description | Abstract Background Biomedical ontologies pose several challenges to ontology matching due both to the complexity of the biomedical domain and to the characteristics of the ontologies themselves. The biomedical tracks in the Ontology Matching Evaluation Initiative (OAEI) have spurred the development of matching systems able to tackle these challenges, and benchmarked their general performance. In this study, we dissect the strategies employed by matching systems to tackle the challenges of matching biomedical ontologies and gauge the impact of the challenges themselves on matching performance, using the AgreementMakerLight (AML) system as the platform for this study. Results We demonstrate that the linear complexity of the hash-based searching strategy implemented by most state-of-the-art ontology matching systems is essential for matching large biomedical ontologies efficiently. We show that accounting for all lexical annotations (e.g., labels and synonyms) in biomedical ontologies leads to a substantial improvement in F-measure over using only the primary name, and that accounting for the reliability of different types of annotations generally also leads to a marked improvement. Finally, we show that cross-references are a reliable source of information and that, when using biomedical ontologies as background knowledge, it is generally more reliable to use them as mediators than to perform lexical expansion. Conclusions We anticipate that translating traditional matching algorithms to the hash-based searching paradigm will be a critical direction for the future development of the field. Improving the evaluation carried out in the biomedical tracks of the OAEI will also be important, as without proper reference alignments there is only so much that can be ascertained about matching systems or strategies. Nevertheless, it is clear that, to tackle the various challenges posed by biomedical ontologies, ontology matching systems must be able to efficiently combine multiple strategies into a mature matching approach. |
| first_indexed | 2024-12-12T02:48:29Z |
| format | Article |
| id | doaj.art-3289a3274a8a4ae9915b8623c7f154ad |
| institution | Directory Open Access Journal |
| issn | 2041-1480 |
| language | English |
| last_indexed | 2024-12-12T02:48:29Z |
| publishDate | 2018-01-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Biomedical Semantics |
| spelling | doaj.art-3289a3274a8a4ae9915b8623c7f154ad2022-12-22T00:40:56ZengBMCJournal of Biomedical Semantics2041-14802018-01-019111910.1186/s13326-017-0170-9Tackling the challenges of matching biomedical ontologiesDaniel Faria0Catia Pesquita1Isabela Mott2Catarina Martins3Francisco M. Couto4Isabel F. Cruz5Instituto Gulbenkian de CiênciaLASIGE, Faculdade de Ciências, Universidade de LisboaLASIGE, Faculdade de Ciências, Universidade de LisboaSchool of Computer Science, University of ManchesterLASIGE, Faculdade de Ciências, Universidade de LisboaADVIS Lab, Department of Computer Science, University of Illinois at ChicagoAbstract Background Biomedical ontologies pose several challenges to ontology matching due both to the complexity of the biomedical domain and to the characteristics of the ontologies themselves. The biomedical tracks in the Ontology Matching Evaluation Initiative (OAEI) have spurred the development of matching systems able to tackle these challenges, and benchmarked their general performance. In this study, we dissect the strategies employed by matching systems to tackle the challenges of matching biomedical ontologies and gauge the impact of the challenges themselves on matching performance, using the AgreementMakerLight (AML) system as the platform for this study. Results We demonstrate that the linear complexity of the hash-based searching strategy implemented by most state-of-the-art ontology matching systems is essential for matching large biomedical ontologies efficiently. We show that accounting for all lexical annotations (e.g., labels and synonyms) in biomedical ontologies leads to a substantial improvement in F-measure over using only the primary name, and that accounting for the reliability of different types of annotations generally also leads to a marked improvement. Finally, we show that cross-references are a reliable source of information and that, when using biomedical ontologies as background knowledge, it is generally more reliable to use them as mediators than to perform lexical expansion. Conclusions We anticipate that translating traditional matching algorithms to the hash-based searching paradigm will be a critical direction for the future development of the field. Improving the evaluation carried out in the biomedical tracks of the OAEI will also be important, as without proper reference alignments there is only so much that can be ascertained about matching systems or strategies. Nevertheless, it is clear that, to tackle the various challenges posed by biomedical ontologies, ontology matching systems must be able to efficiently combine multiple strategies into a mature matching approach.http://link.springer.com/article/10.1186/s13326-017-0170-9Ontology matchingBiomedical ontologies |
| spellingShingle | Daniel Faria Catia Pesquita Isabela Mott Catarina Martins Francisco M. Couto Isabel F. Cruz Tackling the challenges of matching biomedical ontologies Journal of Biomedical Semantics Ontology matching Biomedical ontologies |
| title | Tackling the challenges of matching biomedical ontologies |
| title_full | Tackling the challenges of matching biomedical ontologies |
| title_fullStr | Tackling the challenges of matching biomedical ontologies |
| title_full_unstemmed | Tackling the challenges of matching biomedical ontologies |
| title_short | Tackling the challenges of matching biomedical ontologies |
| title_sort | tackling the challenges of matching biomedical ontologies |
| topic | Ontology matching Biomedical ontologies |
| url | http://link.springer.com/article/10.1186/s13326-017-0170-9 |
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