TRE for biomedical and clinical data
DATA SPACE
The Alliance Data Space establishes a Trusted Research Environment (TRE) designed to enable secure, governed, and scalable use of biomedical and clinical data across the Alliance Institutions.
The Data Space initiative aims to position the Heidelberg/Mannheim region at the forefront of addressing key challenges in biomedical data access, interoperability, and secure data sharing. It is building the foundation for a long-term sustainable, scalable, and safe data ecosystem, enabling cross-institutional collaboration and ultimately accelerating innovation in diagnostics and therapies.
The Data Space Trusted Research Environment
Sharing and collaborating on biomedical data presents persistent challenges related to data protection, information security, governance, and infrastructure heterogeneity. Direct data transfer or dataset duplication can introduce significant risks to privacy, regulatory compliance, and data integrity. In addition, establishing and maintaining secure analysis environments for sensitive patient-derived data often requires substantial technical expertise and institutional resources.
The Data Space addresses these challenges by developing a secure and legally compliant high-performance environment designed specifically for biomedical patient data. This Trusted Research Environment (TRE) provides a controlled computational framework in which sensitive biomedical and clinical data can be accessed and analyzed without unnecessary data movement.
By implementing this approach, the Data Space enables fast, safe, and impactful research while strengthening collaboration on computational projects between Alliance institutions. At the same time, it preserves institutional autonomy and ensures full compliance with regulatory obligations.
Functionalities
The Data Space Team will develop a legally and technically secure TRE supporting diverse biomedical and clinical research workflows. Researchers will be able to run interactive analysis tools, such as visualization applications, virtual machines, or Jupyter notebooks, as well as automated and scalable workflows, such as pipelines for batch processing and large-scale analyses. This flexibility allows both exploratory research and high-throughput studies to be carried out efficiently within the same secure framework.
The Data Space adopts a hybrid infrastructure model. One part focuses on adapting and extending existing private computing infrastructures at partner institutions, building on established local expertise and resources. In parallel, the project is developing a proof of concept using commercial cloud services. These platforms offer highly scalable, certified, and flexible computing capacity that complements local infrastructures.
Integrating these different resources enables a faster start-up, the ability to scale capacity as demand grows, and broader access for researchers, while remaining fully compliant with legal and data protection requirements. In this way, the Data Space is designed to grow efficiently and serve a wider research and clinical community without being limited by local resource constraints.
Oliver Stegle (Speaker) (DKFZ)
Vincent Heuveline (Co-Speaker)
Jan Korbel (EMBL)
Martin Dugas (Heidelberg University Clinic)
Eva Winkler (Medical Faculty Heidelberg, Heidelberg University)
Johannes Betge (Medical Faculty Mannheim, Mannheim University)
Fabian Siegel (University Hospital Mannheim)
Emanuel Schwarz (Central Institute of Mental Health)
Fruzsina Molnar-Gabor (Heidelberg University)(DKFZ)
How to get involved
Following the initial deployment phase of the Data Space infrastructure, the central development team will reach out to the Alliance Institutions for selecting suitable use cases for a structured pilot phase. During this pilot phase the team will collaborate closely with the pilot users. Insights obtained during the pilot phase will guide platform refinement, ensuring that the Data Space meets the operational and scientific requirements of the research community prior to broader institutional rollout.
Future Perspectives
The Data Space will be designed to be interoperable with national and European data infrastructures, including the MEDI:CUS project by the State of Baden-Württemberg or the European Health Data Space. Particular attention will be given to evolving EU regulatory frameworks governing cross-border data access, secondary use of health data, and secure computational environments.
Alignment with these frameworks will position the Data Space to participate effectively in distributed, data-driven biomedical research across institutional and national boundaries.
Contact
Katharina Deschler
Project Manager
Health + Life Science Alliance Data Space
Tiergartenstrasse 15
69121 Heidelberg
data-space[at]health-life-sciences.de