The Genomic Data Infrastructure (GDI) project aims to overcome or lower barriers in clinical diagnostics and treatment by facilitating access to fragmented human genomics data across Europe. The project establishes a federated, secure infrastructure, but faces interoperability challenges on all 6 layers of the refined eHealth European Interoperability Framework due to the diversity of implementations of law and regulations, various organisational setups, data sources and infrastructures. To address this issue, a framework for solving interoperability scenarios is proposed. This framework is able to take on a variety of relevant interoperability building blocks and interoperability scenarios that are listed in this deliverable. Key framework components include shared logical models from which we derive data management systems that serve intrinsically interoperable APIs. These systems are allowed to make different model selections or use different software products while maintaining interoperability. The main drivers for this work are Genome of Europe (GDI T7.1 and 1+MG WG12), Cancer (GDI T7.4 and 1+MG WG9), Infectious diseases (GDI T7.3 and 1+MG WG11), Rare disease (GDI T7.2 and 1+MG WG8), as well as D7.4, MS26, MS27 from WP7. The framework will support the implementation of the T8.2 semantic interoperability package, which develops and harmonizes the minimal models from the WP7 datasets, and we expect it will contribute to achieving WP3 MS7 and MS8, WP8 T8.3, and D4.3, MS11, and MS12 from WP4. Furthermore, multiple standards for data discoverability from the TEHDAS ‘Recommendations to enhance interoperability’ within HealthData@EU have been incorporated in the reference implementation of the framework, such as Beacon, BBMRI MIABIS and DCAT-AP. The upcoming HealthDCAT-AP standard, built on DCAT-AP and designed specifically for the HealthData@EU infrastructure by WP6 of the EHDS2 Pilot, will be implemented when released. HealthDCAT-AP will standardise the descriptions of health-related datasets in GDI to ensure interoperability with the EHDS and meet the needs of its users. A reference implementation of this framework MOLGENIS EMX2 has resulted in a data management solution that acts as a data catalogue and as a ‘local portal’ towards the underlying genomics data. It features Beacon v2, FAIR Data Point, RDF, Life Science AAI, integration and synchronisation to a REMS instance for managing data access requests. The catalogue currently contains datasets like the B1MG Rare Disease Synthetic Dataset. The reference implementation is packaged in a Docker container for easy installation and testing, encouraging collaboration and feedback from all GDI partners.