Interconnecting Different Data Sources

This document defines the data workflows needed to interconnect different health data sources within the Dataspace4Health ecosystem. It focuses on two use cases: a diabetes Digital Twin with Clinical AI Decision Support, and an oncology Molecular Tumor Board workflow. For diabetes, the document explains how the Digital Twin could be integrated with the hospital EHR through secure interfaces, using consent verification, role-based access, patient-specific risk prediction, and “what-if” treatment simulations during consultation. It also compares local hospital deployment with national-level deployment and outlines the regulatory path toward clinical use under MDR, IVDR, and the AI Act. For oncology, the document describes how clinical and genomic data can be extracted, standardized, pseudonymized, published as data offerings, accessed through federated DS4H mechanisms, analyzed in secure environments, and returned as actionable insights to support Molecular Tumor Board decisions. Overall, D6.3 shows how DS4H can enable secure, interoperable, and compliant data workflows across healthcare institutions, while preserving data sovereignty and supporting future clinical adoption.