We live in a data-driven era with the inevitable emergence of interdisciplinary, geographically dispersed data repositories. The fact that these repositories do not necessarily adhere to existing interdisciplinary data representation standards, nor do they belong to any data federation initiative, renders them unusable and difficult for researchers to access.  Moreover, maintaining integrity, privacy and security in the interactions of diverse data repositories is typically very challenging or impossible to sustain.

The “Trust & Privacy Preserving Computing Platform For Cross-Border Federation Of Data” project – in TRUSTEE for short - aims to solve this issue by delivering a green, open-source, scalable, efficient, secure, trustworthy and privacy-aware framework that brings together various interdisciplinary data repositories, such as from Healthcare, Education, Energy, Space, Automotive, Cross-border domains, and also from the European data federation spaces and transnational initiatives (e.g., Gaia-X and EOSC).

To achieve its goals, TRUSTEE focuses on three main pillars of innovation:

  • Fostering collaboration between data consumers and providers, who until now used to work in silos.
  • Building trusted data solutions by reflecting the trustworthiness of data through the use of quality indicators such as endorsements and deprecations.
  • Automating testing and monitoring, not only of the infrastructure but also of the quality of the data itself, while keeping every stakeholder informed about changes in a distributed manner.

The project is partly funded by the European Commission’s “Horizon Europe” Framework Programme for Research and Innovation (2021-2027) and will run for 42 months (July 2022 – December 2025), bringing together 22 partners with recognised expertise in their respective domains.

University of Vienna is privileged to participate in this project by providing legal and ethical expertise in the domain of data protection, new technologies and cybersecurity.

For more information about the project, please visit:

Experts of the Department working on this project: