ArticleJournal of biomedical semantics2011
GOMMA: a component-based infrastructure for managing and analyzing life science ontologies and their evolution.
Article in Journal of biomedical semantics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Tackling the challenges of matching biomedical ontologies.Journal of biomedical semantics · 2018Article
- Experiences from the anatomy track in the ontology alignment evaluation initiative.Journal of biomedical semantics · 2017Review
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- FEDRR: fast, exhaustive detection of redundant hierarchical relations for quality improvement of large biomedical ontologies.BioData mining · 2016Article
- Mining Relation Reversals in the Evolution of SNOMED CT Using MapReduce.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2015Article
- Making species checklists understandable to machines - a shift from relational databases to ontologies.Journal of biomedical semantics · 2014Article
- An effective method of large scale ontology matching.Journal of biomedical semantics · 2014Article
- Article
- Article
- A multi-part matching strategy for mapping LOINC with laboratory terminologies.Journal of the American Medical Informatics Association : JAMIAArticle
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4 authors.
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Abstract
backgroundOntologies are increasingly used to structure and semantically describe entities of domains, such as genes and proteins in life sciences. Their increasing size and the high frequency of updates resulting in a large set of ontology versions necessitates efficient management and analysis of this data.
resultsWe present GOMMA, a generic infrastructure for managing and analyzing life science ontologies and their evolution. GOMMA utilizes a generic repository to uniformly and efficiently manage ontology versions and different kinds of mappings. Furthermore, it provides components for ontology matching, and determining evolutionary ontology changes. These components are used by analysis tools, such as the Ontology Evolution Explorer (OnEX) and the detection of unstable ontology regions. We introduce the component-based infrastructure and show analysis results for selected components and life science applications. GOMMA is available at http://dbs.uni-leipzig.de/GOMMA.
conclusionsGOMMA provides a comprehensive and scalable infrastructure to manage large life science ontologies and analyze their evolution. Key functions include a generic storage of ontology versions and mappings, support for ontology matching and determining ontology changes. The supported features for analyzing ontology changes are helpful to assess their impact on ontology-dependent applications such as for term enrichment. GOMMA complements OnEX by providing functionalities to manage various versions of mappings between two ontologies and allows combining different match approaches.
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