ArticleJournal of biomedical semantics2015
Completing the is-a structure in light-weight ontologies.
Article in Journal of biomedical semantics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 15 citations in OpenAlex.
- SSIF: Subsumption-based Sub-term Inference Framework to audit Gene Ontology.Bioinformatics (Oxford, England) · 2020Article
- A lexical-based approach for exhaustive detection of missing hierarchical IS-A relations in SNOMED CT.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2020Article
- Experiences from the anatomy track in the ontology alignment evaluation initiative.Journal of biomedical semantics · 2017Review
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3 authors at 2 institutions in 1 country.
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Abstract
backgroundWith the increasing presence of biomedical data sources on the Internet more and more research effort is put into finding possible ways for integrating and searching such often heterogeneous sources. Ontologies are a key technology in this effort. However, developing ontologies is not an easy task and often the resulting ontologies are not complete. In addition to being problematic for the correct modelling of a domain, such incomplete ontologies, when used in semantically-enabled applications, can lead to valid conclusions being missed.
resultsWe consider the problem of repairing missing is-a relations in ontologies. We formalize the problem as a generalized TBox abduction problem. Based on this abduction framework, we present complexity results for the existence, relevance and necessity decision problems for the generalized TBox abduction problem with and without some specific preference relations for ontologies that can be represented using a member of the [Formula: see text] family of description logics. Further, we present algorithms for finding solutions, a system as well as experiments.
conclusionsSemantically-enabled applications need high quality ontologies and one key aspect is their completeness. We have introduced a framework and system that provides an environment for supporting domain experts to complete the is-a structure of ontologies. We have shown the usefulness of the approach in different experiments. For the two Anatomy ontologies from the Ontology Alignment Evaluation Initiative, we repaired 94 and 58 initial given missing is-a relations, respectively, and detected and repaired additionally, 47 and 10 missing is-a relations. In an experiment with BioTop without given missing is-a relations, we detected and repaired 40 new missing is-a relations.
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