Speaker
Description
The secondary use of health data at national scale requires common services for discovery, access and analysis while preserving the responsibilities of the organisations that hold the data. Spain’s National Health Data Space (Espacio Nacional de Datos de Salud, ENDS) addresses this requirement through a federated governance model and a hybrid technical infrastructure. This paper presents the central ENDS platform and its integration with regional health systems, national public bodies and research organisations. Its architecture combines a national metadata catalogue, federated identity, controlled data ingestion, governed processing with Stratio, elastic analytical services on Google Cloud Platform (GCP), and privacy-preserving federated computation with Acuratio. The three processing layers support complementary workloads: virtualised access, Spark/dbt transformation and governed MLOps in Stratio; serverless SQL, batch/stream processing, managed Spark and machine-learning services in GCP; and distributed statistics plus horizontal or vertical federated learning in Acuratio without moving raw records. Researchers use approved data within Secure Processing Environments, with separate controls for access and release of results. The contribution is an integrated description of governance, data locality and workload placement across central, cloud and compute-to-data execution modes.