ArticleSemantic web2017
A Systematic Analysis of Term Reuse and Term Overlap across Biomedical Ontologies.
Article in Semantic web, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Mondo: integrating disease terminology across communities.Genetics · 2026Article
- Enhancing diagnostic precision for rare diseases using case-based reasoning.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Analyzing Llama 3-based Approach for Axiom Translation from Ontologies.CEUR workshop proceedings · 2024Article
- Evaluating FAIR Digital Object and Linked Data as distributed object systems.PeerJ. Computer science · 2024Article
- CMAT: ClinVar Mapping and Annotation Toolkit.Bioinformatics advances · 2024Article
- Comprehensive Ontology of Fibroproliferative Diseases: Protocol for a Semantic Technology Study.JMIR research protocols · 2023Article
- Performance assessment of ontology matching systems for FAIR data.Journal of biomedical semantics · 2022Article
- An empirical meta-analysis of the life sciences linked open data on the web.Scientific data · 2021Article
- Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project.Nature reviews. Nephrology · 2020Review
- Ontologies relevant to behaviour change interventions: a method for their development.Wellcome open research · 2020Article
- Enabling Web-scale data integration in biomedicine through Linked Open Data.NPJ digital medicine · 2019Review
- Assessing the practice of biomedical ontology evaluation: Gaps and opportunities.Journal of biomedical informatics · 2018Review
- Analyzing user interactions with biomedical ontologies: A visual perspective.Web semantics (Online) · 2018Article
- Review
- BiOnIC: A Catalog of User Interactions with Biomedical Ontologies.The semantic Web--ISWC ... : ... International Semantic Web Conference ... proceedings. International Semantic Web Conference · 2017Article
- Secondary Use of Patient Data: Review of the Literature Published in 2016.Yearbook of medical informatics · 2017Review
- An empirical analysis of ontology reuse in BioPortal.Journal of biomedical informatics · 2017Article
- NCBO Ontology Recommender 2.0: an enhanced approach for biomedical ontology recommendation.Journal of biomedical semantics · 2017Article
- Consumers' Use of UMLS Concepts on Social Media: Diabetes-Related Textual Data Analysis in Blog and Social Q&A Sites.JMIR medical informatics · 2016Article
- A unified software framework for deriving, visualizing, and exploring abstraction networks for ontologies.Journal of biomedical informatics · 2016Article
Corrections and comments
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Authors and funding
3 authors.
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Abstract
Reusing ontologies and their terms is a principle and best practice that most ontology development methodologies strongly encourage. Reuse comes with the promise to support the semantic interoperability and to reduce engineering costs. In this paper, we present a descriptive study of the current extent of term reuse and overlap among biomedical ontologies. We use the corpus of biomedical ontologies stored in the BioPortal repository, and analyze different types of reuse and overlap constructs. While we find an approximate term overlap between 25-31%, the term reuse is only <9%, with most ontologies reusing fewer than 5% of their terms from a small set of popular ontologies. Clustering analysis shows that the terms reused by a common set of ontologies have >90% semantic similarity, hinting that ontology developers tend to reuse terms that are sibling or parent-child nodes. We validate this finding by analysing the logs generated from a Protégé plugin that enables developers to reuse terms from BioPortal. We find most reuse constructs were 2-level subtrees on the higher levels of the class hierarchy. We developed a Web application that visualizes reuse dependencies and overlap among ontologies, and that proposes similar terms from BioPortal for a term of interest. We also identified a set of error patterns that indicate that ontology developers did intend to reuse terms from other ontologies, but that they were using different and sometimes incorrect representations. Our results stipulate the need for semi-automated tools that augment term reuse in the ontology engineering process through personalized recommendations.
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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.