The Translational Data Catalog - discoverable biomedical datasets

Area of Science:

• Biomedical research
• Data science
• Information management

Background:

• Dataset discoverability in translational and biomedical research is often sporadic.
• Pre-competitive project datasets face challenges due to data-sharing agreements and differing sector priorities.

Purpose of the Study:

• To present the creation, content, value, and adoption of the Translational Data Catalog.
• To establish a single discovery point for European Commission-funded research projects and datasets.
• To ensure datasets are machine-findable and accessible.

Main Methods:

• Building the Data Catalog on FAIR-enabling community standards.
• Integrating projects from major European private-public partnership research programs.
• Focusing on machine accessibility and findability.

Main Results:

• The Translational Data Catalog provides a centralized discovery point for diverse datasets.
• It addresses challenges in data sharing for pre-competitive research.
• The catalog is built on FAIR principles, enhancing data accessibility.

Conclusions:

• The Translational Data Catalog is a valuable resource for improving biomedical data discoverability.
• Its foundation on FAIR principles ensures machine accessibility.
• Sustainability within the ELIXIR ecosystem is a key next step.