The fifth INDICATE training session brought together participants from across the consortium to understand the role of metadata in supporting interoperability, data discovery, and federated research across institutions.

Led by María González-Lopez and Paloma Bravo del Cid from the Computational Health Informatics Group at Virgen del Rocío University Hospital, the training focused on metadata standards, cataloguing workflows, and best practices within the INDICATE framework.

A key message throughout the training was that metadata is what makes health data discoverable, understandable and reusable across institutions. Participants explored how researchers often encounter datasets from multiple hospitals without knowing how the data were collected, whether they can be combined or even if they are allowed to access them. 

Metadata provides the answers to these questions by describing what a dataset contains, how it was created, under which conditions it can be used and how it can be accessed. Rather than being administrative overhead, metadata forms the foundation of the INDICATE federated catalogue and enables hospitals and researchers to collaborate without sharing patient-level data.

The session concluded with interactive breakout rooms, where participants took on the role of the local INDICATE data provider team for a fictional university hospital. Working with a realistic case study, they assessed whether the hospital’s existing OMOP database, ETL process and ICU data were ready to support a federated study on early organ failure in patients with suspected sepsis. 

By reviewing governance, metadata, data quality and technical readiness, each group determined whether the hospital was ready to participate or which improvements were still needed. The exercise highlighted that successful federated research requires more than available data. It depends on well-documented metadata, robust data quality and close collaboration between clinical, technical and governance experts.