TRUSTEE

In a world driven by data, it is natural for interdisciplinary and geographically distributed data repositories to arise. These repositories do not necessarily adhere to established interdisciplinary data representation standards or participate in any data federation initiatives. Thus, researchers have limited access to data. Additionally, preserving integrity, privacy and security in such exchanges is extremely challenging or even impossible. The EU-funded TRUSTEE project will deliver a green, secure, trustworthy and privacy-aware framework that aggregates multiple interdisciplinary data repositories (healthcare, education, energy, space, automotive, cross-border) and also takes into account other European data federation spaces and transnational initiatives (Gaia-X and the EOSC). The project will deliver a completely encrypted solution that enables researchers to search for and utilise encrypted data.

As we live in a data-driven era, the emergence of interdisciplinary, geographically dispersed, data repositories, is inevitable. The fact that these repositories do not necessarily abide with existing interdisciplinary data representation standards, nor do they necessarily belong to any data federation initiative, renders them unusable, since researchers cannot easily access this data. Moreover, most of the times, integrity, privacy, and security in such interactions is either very difficult, or impossible to maintain. Towards this end, TRUSTEE aims to bring a green, secure, trustworthy, and privacy-aware framework that will aggregate various interdisciplinary data repositories, such as Healthcare, Education, Energy, Space, Automotive, Cross-border etc. and also consider other European data federation spaces and trans-national initiatives, such as Gaia-X and EOSC. TRUSTEE will offer a secure-by-design framework, wherein stored data is homomorphically encrypted, thus offering researchers i) ability to search and use data in the encrypted domain, ii) a unified and meaningful FAIR representation of data, in an open and fair manner, iii) complex and context-aware queries through advanced ontologies, iv) data processing and analysis through transparent trustworthy ML workflows, over an intuitive AI playground, which will promote AI eXplainability, interoperability, and re-usability, by utilizing state of the art methods and paradigms, v) compliance with European privacy and ethical frameworks, e.g. GDPR, PIA, etc., vi) enforce privacy by applying a Homomorphic encryption layer, through which all data interaction will take place, vii) a blockchain-based transaction recorder to ensure accountability. TRUSTEE's fully encrypted solution will be validated through six different use cases supporting GAIA-X, EOSC, EGI, etc. demonstrating a multi-disciplinary, Pan-European federated FAIR and private data ecosystem.