ArticleJournal of biomedical informatics2013
An analysis of FMA using structural self-bisimilarity.
Article in Journal of biomedical informatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Using logical constraints to validate statistical information about disease outbreaks in collaborative knowledge graphs: the case of COVID-19 epidemiology in Wikidata.PeerJ. Computer science · 2022Article
- Automatic Structuring of Ontology Terms Based on Lexical Granularity and Machine Learning: Algorithm Development and Validation.JMIR medical informatics · 2020Article
- Assessing the practice of biomedical ontology evaluation: Gaps and opportunities.Journal of biomedical informatics · 2018Review
- Quality Assurance of UMLS Semantic Type Assignments Using SNOMED CT Hierarchies.Methods of information in medicine · 2016Article
- Biological Model Development as an Opportunity to Provide Content Auditing for the Foundational Model of Anatomy Ontology.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2015Article
- NEO: Systematic Non-Lattice Embedding of Ontologies for Comparing the Subsumption Relationship in SNOMED CT and in FMA Using MapReduce.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2015Article
- MaPLE: A MapReduce Pipeline for Lattice-based Evaluation and Its Application to SNOMED CT.Proceedings : ... IEEE International Conference on Big Data. IEEE International Conference on Big Data · 2014Article
- COHeRE: Cross-Ontology Hierarchical Relation Examination for Ontology Quality Assurance.AMIA ... Annual Symposium proceedings. AMIA SymposiumArticle
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
As ontologies are mostly manually created, they tend to contain errors and inconsistencies. In this paper, we present an automated computational method to audit symmetric concepts in ontologies by leveraging self-bisimilarity and linguistic structure in the concept names. Two concepts A and B are symmetric if concept B can be obtained from concept A by replacing a single modifier such as "left" with its symmetric modifier such as "right." All possible local structural types for symmetric concept pairs are enumerated according to their local subsumption hierarchy, and the pairs are further classified into Non-Matches and Matches. To test the feasibility and validate the benefits of this method, we computed all the symmetric modifier pairs in the Foundational Model of Anatomy (FMA) and selected six of them for experimentation. 9893 Non-Matches and 221 abnormal Matches with potential errors were discovered by our algorithm. Manual evaluation by FMA domain experts on 176 selected Non-Matches and all the 221 abnormal Matches found 102 missing concepts and 40 misaligned concepts. Corrections for them have currently been implemented in the latest version of FMA. Our result demonstrates that self-bisimilarity can be a valuable method for ontology quality assurance, particularly in uncovering missing concepts and misaligned concepts. Our approach is computationally scalable and can be applied to other ontologies that are rich in symmetric concepts.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.