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CC BY-NC-ND 4.0 · Methods Inf Med 2022; 61(S 02): e103-e115
DOI: 10.1055/a-1914-1985
Original Article

The Leipzig Health Atlas—An Open Platform to Present, Archive, and Share Biomedical Data, Analyses, and Models Online

Toralf Kirsten   *
1   Department of Medical Data Science, Leipzig University Medical Center, Leipzig, Germany
2   Institute for Medical Informatics, Statistics, and Epidemiology, Leipzig University, Leipzig, Germany
3   Interdisciplinary Centre for Bioinformatics, Leipzig University, Leipzig, Germany
,
Frank A. Meineke   *
2   Institute for Medical Informatics, Statistics, and Epidemiology, Leipzig University, Leipzig, Germany
,
Henry Loeffler-Wirth
4   LIFE Research Centre for Civilization Diseases, Leipzig University, Leipzig, Germany
,
Christoph Beger
2   Institute for Medical Informatics, Statistics, and Epidemiology, Leipzig University, Leipzig, Germany
,
Alexandr Uciteli
2   Institute for Medical Informatics, Statistics, and Epidemiology, Leipzig University, Leipzig, Germany
,
Sebastian Stäubert
2   Institute for Medical Informatics, Statistics, and Epidemiology, Leipzig University, Leipzig, Germany
,
Matthias Löbe
2   Institute for Medical Informatics, Statistics, and Epidemiology, Leipzig University, Leipzig, Germany
3   Interdisciplinary Centre for Bioinformatics, Leipzig University, Leipzig, Germany
,
René Hänsel
2   Institute for Medical Informatics, Statistics, and Epidemiology, Leipzig University, Leipzig, Germany
,
Franziska G. Rauscher
2   Institute for Medical Informatics, Statistics, and Epidemiology, Leipzig University, Leipzig, Germany
3   Interdisciplinary Centre for Bioinformatics, Leipzig University, Leipzig, Germany
,
Judith Schuster
2   Institute for Medical Informatics, Statistics, and Epidemiology, Leipzig University, Leipzig, Germany
,
Thomas Peschel
2   Institute for Medical Informatics, Statistics, and Epidemiology, Leipzig University, Leipzig, Germany
,
Heinrich Herre
2   Institute for Medical Informatics, Statistics, and Epidemiology, Leipzig University, Leipzig, Germany
,
Jonas Wagner
2   Institute for Medical Informatics, Statistics, and Epidemiology, Leipzig University, Leipzig, Germany
3   Interdisciplinary Centre for Bioinformatics, Leipzig University, Leipzig, Germany
,
Silke Zachariae
2   Institute for Medical Informatics, Statistics, and Epidemiology, Leipzig University, Leipzig, Germany
,
Christoph Engel
2   Institute for Medical Informatics, Statistics, and Epidemiology, Leipzig University, Leipzig, Germany
3   Interdisciplinary Centre for Bioinformatics, Leipzig University, Leipzig, Germany
,
Markus Scholz
2   Institute for Medical Informatics, Statistics, and Epidemiology, Leipzig University, Leipzig, Germany
,
Erhard Rahm
5   Department of Computer Sciences, Leipzig University, Leipzig, Germany
,
Hans Binder   §
4   LIFE Research Centre for Civilization Diseases, Leipzig University, Leipzig, Germany
,
Markus Loeffler   §
2   Institute for Medical Informatics, Statistics, and Epidemiology, Leipzig University, Leipzig, Germany
3   Interdisciplinary Centre for Bioinformatics, Leipzig University, Leipzig, Germany
4   LIFE Research Centre for Civilization Diseases, Leipzig University, Leipzig, Germany
,
on behalf of the LHA team › Author Affiliations Funding/Acknowledgments The LHA project was funded by the German Ministry of Education and Research with the reference number 031L0026 within the program i:DSem—Integrative Data Semantics in Systems Medicine. The project further has received funding from the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement No. 853988 including the EU (Horizon 2020)-funded imSAVAR project (to H.L-.W., H.B., and M.L.).
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Abstract

Background Clinical trials, epidemiological studies, clinical registries, and other prospective research projects, together with patient care services, are main sources of data in the medical research domain. They serve often as a basis for secondary research in evidence-based medicine, prediction models for disease, and its progression. This data are often neither sufficiently described nor accessible. Related models are often not accessible as a functional program tool for interested users from the health care and biomedical domains.

Objective The interdisciplinary project Leipzig Health Atlas (LHA) was developed to close this gap. LHA is an online platform that serves as a sustainable archive providing medical data, metadata, models, and novel phenotypes from clinical trials, epidemiological studies, and other medical research projects.

Methods Data, models, and phenotypes are described by semantically rich metadata. The platform prefers to share data and models presented in original publications but is also open for nonpublished data. LHA provides and associates unique permanent identifiers for each dataset and model. Hence, the platform can be used to share prepared, quality-assured datasets and models while they are referenced in publications. All managed data, models, and phenotypes in LHA follow the FAIR principles, with public availability or restricted access for specific user groups.

Results The LHA platform is in productive mode (https://www.health-atlas.de/). It is already used by a variety of clinical trial and research groups and is becoming increasingly popular also in the biomedical community. LHA is an integral part of the forthcoming initiative building a national research data infrastructure for health in Germany.

Keywords

FAIR - data semantics - research data management - metadata - clinical trials - biomathematical models - ontology - risk prediction models - omics data

Ethical Consideration

All personal data provided by the LHA are from studies and projects, for which ethical approval has been obtained, together with informed written consent of all individuals.


* These authors contributed equally.


§ These authors shared senior authorship.


# Further LHA team members in alphabetical order: Anika Groß,5,6 Ying-Chi Lin,5 Katja Rillich,2 Samira Zeynalova,2 Marita Ziepert2.




Publication History

Received: 10 March 2022

Accepted: 11 June 2022

Accepted Manuscript online:
01 August 2022

Article published online:
23 December 2022

© 2022. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)

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