Skip to main content

User account menu

  • Log in
DBS-Logo

Database Group Leipzig

within the department of computer science

ScaDS-Logo Logo of the University of Leipzig

Main navigation

  • Home
  • Study
    • Exams
      • Hinweise zu Klausuren
    • Courses
      • Current
    • Modules
    • LOTS-Training
    • Abschlussarbeiten
    • Masterstudiengang Data Science
    • Oberseminare
    • Problemseminare
    • Top-Studierende
  • Research
    • Projects
      • Benchmark datasets for entity resolution
      • FAMER
      • HyGraph
      • Privacy-Preserving Record Linkage
      • GRADOOP
    • Publications
    • Prototypes
    • Annual reports
    • Cooperations
    • Graduations
    • Colloquia
    • Conferences
  • Team
    • Erhard Rahm
    • Member
    • Former employees
    • Associated members
    • Gallery

GOMMA: A Component-based Infrastructure for managing and analyzing Life Science Ontologies and their Evolution

Breadcrumb

  • Home
  • Research
  • Publications
  • GOMMA: A Component-based Infrastructure for managing and analyzing Life Science Ontologies and their Evolution

Kirsten, T. ; Groß, A. ; Hartung, M. ; Rahm, E.

GOMMA: A Component-based Infrastructure for managing and analyzing Life Science Ontologies and their Evolution

Journal of Biomedical Semantics 2011, 2:6

2011 / 11

Paper

Futher information: http://www.jbiomedsem.com/content/2/1/6

Abstract

Background
Ontologies 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.

Results
We 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 <a href="http://dbs.uni-leipzig.de/GOMMA">http://dbs.uni-leipzig.de/GOMMA</a&gt; .

Conclusions
GOMMA 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.

<h2 id="bibtex_heading">BibTex</h2>
<pre id="bibtex_listing">
@article{kirsten_jbms2011,
title={GOMMA: a component-based infrastructure for managing and analyzing life science ontologies and their evolution},
author={Kirsten, T. and Gross, A. and Hartung, M. and Rahm, E.},
journal={Journal of Biomedical Semantics},
volume={2},
pages={6},
year={2011}
}
</pre>

Recent publications

  • 2025 / 9: Generating Semantically Enriched Mobility Data from Travel Diaries
  • 2025 / 8: Slice it up: Unmasking User Identities in Smartwatch Health Data
  • 2025 / 6: SecUREmatch: Integrating Clerical Review in Privacy-Preserving Record Linkage
  • 2025 / 6: Leveraging foundation models and goal-dependent annotations for automated cell confluence assessment
  • 2025 / 5: Federated Learning With Individualized Privacy Through Client Sampling

Footer menu

  • Directions
  • Contact
  • Impressum