At the Aristotle University of Thessaloniki (AUTH), researchers have been working on the development of the INCISIVE project involving the collection and curation of high-quality datasets covering breast, thyroid, and brain cancer, bringing together rich clinical information and imaging data for research, education, and AI development.
Yet, despite their scientific value, these datasets faced a challenge common to many research initiatives. While they enabled important discoveries within individual projects, their broader potential remained isolated. By joining EUCAIM, AUTH found an opportunity to move beyond the project’s borders. Rather than supporting a single project or research question, the university became part of a federated European ecosystem designed to enable the secure reuse of cancer imaging data for multiple clinical and research applications.
The opportunity to move from individual research projects towards a more sustainable ecosystem was not the only benefit facilitated by EUCAIM. By becoming Data Holders through the platform, the AUTH team gained a better understanding and practical experience of challenges related to data quality, legal and regulatory aspects of medical data sharing, data standardisation, and FAIR data principles. This experience helped them better understand the challenges faced by data collectors and shape the requirements of the data quality tool. In parallel, working within the EUCAIM ecosystem allowed the team to better understand AI needs and the broader landscape of cancer imaging and trustworthy AI.
Moreover, participation in EUCAIM, as a continuation of the INCISIVE project, gave the AUTH team the opportunity to build on its previous experience and adopt a dual role as both data holder and data user.
Finally, the experience and collaborations established through the project have created a strong basis for continued scientific collaboration, new joint research activities, and future funding opportunities. AUTH has successfully collected and made available three datasets covering breast, thyroid, and brain cancer through its federated node, representing three dedicated data-holder use cases. The data are hosted within a Tier 3 federated node, supporting the EUCAIM Common Data Model (CDM) and federated learning capabilities.
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