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GOMMA: a component-based infrastructure for managing and analyzing life science ontologies and their evolution
Toralf Kirsten1, Anika Gross, Michael Hartung
1Interdisciplinary Centre for Bioinformatics, Universität Leipzig, Härtelstraße 16-18, 04107 Leipzig, Germany. tkirsten@izbi.uni-leipzig.de.
Journal of Biomedical Semantics
|September 15, 2011
Summary
GOMMA is a new infrastructure for managing and analyzing life science ontologies and their evolution. It efficiently handles ontology versions and mappings, aiding in the analysis of changes and their impact.
Area of Science:
- Life Sciences
- Bioinformatics
- Ontology Engineering
Background:
- Ontologies are crucial for structuring life science data like genes and proteins.
- Large, frequently updated ontologies require efficient management and analysis systems.
Purpose of the Study:
- To introduce GOMMA, a generic infrastructure for managing and analyzing life science ontologies and their evolution.
- To provide tools for ontology matching and tracking evolutionary changes.
Main Methods:
- Developed a generic repository for uniform management of ontology versions and mappings.
- Integrated components for ontology matching and change detection.
- Utilized analysis tools like the Ontology Evolution Explorer (OnEX).
Main Results:
- GOMMA efficiently manages diverse ontology versions and mappings.
- Identified unstable ontology regions and analyzed evolutionary changes.
- Demonstrated analysis results for life science applications.
Conclusions:
- GOMMA offers a scalable infrastructure for managing and analyzing large life science ontologies.
- Key features include storage of versions/mappings and support for matching/change analysis.
- Facilitates impact assessment of ontology changes on dependent applications.
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