Ontological Modelling and Execution of Phenotypic Queries in the Leipzig Health Atlas.

Biomedical Ontologies Domain-specific Language Information Storage and Retrieval Metadata Phenotype Selection Criteria Web Archive

Journal

Studies in health technology and informatics
ISSN: 1879-8365
Titre abrégé: Stud Health Technol Inform
Pays: Netherlands
ID NLM: 9214582

Informations de publication

Date de publication:
24 May 2021
Historique:
entrez: 27 5 2021
pubmed: 28 5 2021
medline: 1 6 2021
Statut: ppublish

Résumé

Sharing data is of great importance for research in medical sciences. It is the basis for reproducibility and reuse of already generated outcomes in new projects and in new contexts. FAIR data principles are the basics for sharing data. The Leipzig Health Atlas (LHA) platform follows these principles and provides data, describing metadata, and models that have been implemented in novel software tools and are available as demonstrators. LHA reuses and extends three different major components that have been previously developed by other projects. The SEEK management platform is the foundation providing a repository for archiving, presenting and secure sharing a wide range of publication results, such as published reports, (bio)medical data as well as interactive models and tools. The LHA Data Portal manages study metadata and data allowing to search for data of interest. Finally, PhenoMan is an ontological framework for phenotype modelling. This paper describes the interrelation of these three components. In particular, we use the PhenoMan to, firstly, model and represent phenotypes within the LHA platform. Then, secondly, the ontological phenotype representation can be used to generate search queries that are executed by the LHA Data Portal. The PhenoMan generates the queries in a novel domain specific query language (SDQL), which is specific for data management systems based on CDISC ODM standard, such as the LHA Data Portal. Our approach was successfully applied to represent phenotypes in the Leipzig Health Atlas with the possibility to execute corresponding queries within the LHA Data Portal.

Identifiants

pubmed: 34042877
pii: SHTI210052
doi: 10.3233/SHTI210052
doi:

Types de publication

Journal Article

Langues

eng

Pagination

66-74

Auteurs

Alexandr Uciteli (A)

Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Germany.

Christoph Beger (C)

Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Germany.
Growth Network CrescNet, University of Leipzig, Germany.

Jonas Wagner (J)

Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Germany.
LIFE Research Centre for Civilization Diseases, University of Leipzig, Germany.

Alexander Kiel (A)

LIFE Research Centre for Civilization Diseases, University of Leipzig, Germany.

Frank A Meineke (FA)

Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Germany.

Sebastian Stäubert (S)

Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Germany.

Matthias Löbe (M)

Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Germany.

René Hänsel (R)

Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Germany.

Judith Schuster (J)

Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Germany.

Toralf Kirsten (T)

LIFE Research Centre for Civilization Diseases, University of Leipzig, Germany.
Faculty Applied Computer and Biological Sciences, University of Applied Sciences Mittweida, Germany.

Heinrich Herre (H)

Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Germany.

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