Issues of data subjects’ privacy and data security represent a crucial challenge in the biomedical sector more than in other industries. The current IT landscape in this field shows a myriad of isolated, locally hosted patient data repositories, managed by clinical centres and other organisations, which are subject to frequent and massive data breaches. Patients are disenfranchised in this process, and are not able to have a clear understanding of who uses their personal information and for what purposes. This makes it the ideal field to build and test new models of privacy and data protection, and the technologies that encode them. MyHealthMyData (MHMD) aims at changing the existing scenario by introducing a distributed, peer-to-peer architecture, based on Blockchain and Personal Data Accounts. This approach will determine new mechanisms of trust and of direct, value-based relationships between people, hospitals, research centres and businesses, in what will be the first open biomedical information network centred on the connection between organisations and the individual. The system will develop a comprehensive methodology to guide the implementation of data and identity protection systems, specifically defining approaches and tools to profile and classify sensitive data based on their informational and economic value, to assess the most suitable and robust de-identification and encryption technologies needed to secure different types of information, to allow advanced analytics, and to evaluate the overall reliability of a generic multi modular architecture. MHMD will also analyse users’ behavioural patterns alongside ethical and cultural orientations, to identify hidden dynamics in the interactions between humans and complex information services, to improve the design of data-driven platforms and to foster the development of a true information marketplace, in which individuals will be able to exercise full control on their personal data and leverage their value.

euCanSHare will develop the first centralised, secure and sustainable platform for enhanced cross-border data sharing and multi-cohort personalised medicine research in cardiology. At its heart, the platform will contain the most comprehensive cardiovascular data catalogue ever assembled, which will facilitate data discoverability and exploitation in full alignment with the FAIR principles. The project will implement the interoperability of currently fragmented yet mature IT solutions developed by the consortium members for generating a comprehensive multi-functionality platform. It will also integrate major cardiovascular data sources from Europe and Canada, including the renowned MORGAM, BiomarCaRE and CAHHM initiatives. euCanSHare’s legal framework will be built through detailed ethical and legal interoperability analysis, while investigating innovative solutions for promoting responsible Open Science based on the emerging blockchain technology. Initially populated with 35 European and Canadian cohorts (corresponding to about one million records), the platform will provide extensive functionalities, including for data deposition, data harmonisation and quality control, which will support the integration of new cohorts beyond the duration of the project, thus ensuring its scalability. Moreover, sustainability will be targeted by leveraging through our multi-disciplinary partners the most established data infrastructures, namely ELIXIR, EGA, BBMRI and euro-BioImaging in Europe, as well as Maelstrom from Canada. The unique features of the platform will be demonstrated and adjusted through several use cases, including for biomarker validation, knowledge discovery, cardiovascular risk assessment, public health research and industry-driven studies. Furthermore, intensive outreach campaigns and hands-on workshops will be organised to attract a range of stakeholders, data providers and end-users from the academic, public health and industrial sectors.

Foundation models represent a paradigm shift in AI, exhibiting remarkable capabilities across multiple tasks. Their true potential lies in generalizing across diverse domains and modalities, a largely untapped frontier. DVPS advances this frontier by focusing on multimodal foundation models (MMFM), aiming to harness their capabilities across various application domains. DVPS emphasizes three core benefits of MMFM: label efficiency, compute reusability, and engineering efficiency. However, achieving these benefits in multimodal settings presents challenges such as modality-specific architecture and cross-modal alignment. To overcome these, DVPS aims to develop generalizable methods that work across diverse modalities and domains, creating a unified framework for MMFM development and integrating new modalities into existing models. The project focuses on generating foundational knowledge, delivering tested methods, and creating algorithms to expand MMFM capabilities across domains like cardiology, geo-intelligence, and language communication. DVPS also includes two "surprise domains" to drive innovation by challenging initial assumptions. Key objectives include the development of AutoDVPS, a toolkit for automated MMFM design, and the creation of DVPSBench, a benchmarking suite for evaluating MMFM across tasks and domains. DVPS aims to foster a European ecosystem for MMFM research, promoting transparency, fairness, and ethical compliance in line with European values. Through collaboration and open-source contributions, DVPS seeks to standardize and advance MMFM as a scientifically rigorous discipline.

KRAKEN Secure and privacy preserving platform (broKeRage And marKEt platform for persoNal data) aims to bring personal data sharing and trading at a level of maturity that does not yet exist, by leveraging on: i) the emerging paradigm of self-sovereign identity built upon a stack of distributed ledger technologies (multi-ledger) which ensures future compatibility with different specific blockchain implementations for identity management. It will provide a decentralized user-centric approach on personal data sharing and proving that it can incorporate the trust and security assurance levels deriving claims from national identity schemas (eIDAS-compliant); ii) tested data marketplace technologies which support data sharing as well as aggregated data sharing; iii) A set of different data protection techniques based on advanced crypto tools (P/F/HE, FE, MPC, ABE…) coupled with privacy preserving (AI/ML) analytics, featuring management of privacy / utility trade-offs and metadata privacy. iv) The project will provide market-ready tools and services with industrial strength and suitable privacy metrics that will be conveyed to data subjects with high usability. Taking advantages of the emergent models and lessons learned from previous experiences, including existing and mature cloud-based personal data platforms CREDENTIAL and MHMD, as well as Streamr marketplace services, Kraken proposes an unprecedented approach, which creates an alternative to mainstream paradigms while fully granting the privacy and self-sovereignity of the data subject. KRAKEN enables advanced, convenient data sharing control relying on innovative end-to-end encryption and use of sophisticated proxy cryptography schemes grants data subjects with unprecedented control over their data. Furthermore, this ensures that even the cloud provider (data processor) cannot access the data in plain-text and hence protect access to personal data. KRAKEN involves 10 partners and has a duration of 3 years.