2026-10-29 –, LUMC04
Messy, inconsistent metadata is one of the biggest blockers to data interoperability— and it usually happens because metadata is an afterthought, often added long after the data was created. In this session, you'll see how PID4NFDI, TS4NFDI, and the RSpace research data management platform establish a practical interoperability layer that puts interoperable metadata right at the point of data creation. Using embedded terminology widgets and cross-schema mappings, researchers can capture DataCite-aligned metadata without ever leaving their lab notebook. The result: cleaner data, less manual clean-up, a reusable model that can extend to other tools and services, and ultimately data and PIDs with metadata that can easily be transformed into other formats.
Do you find yourself cleaning up inconsistent metadata long after the research is done, wishing your data had been labelled properly from the start? Or are you struggling making data interoperable with your tool or service? In this session, you'll see how PID4NFDI, TS4NFDI, and the ResearchSpace have collaborated on an actionable solution so that structured, interoperable metadata becomes a natural part of your (researchers') daily lab workflow — not something you bolt on later.
You'll get a look at a solution where DataCite metadata vocabularies are embedded directly into RSpace via TS4NFDI terminology widgets, letting you and your team efficiently tag data and curate metadata with standardised terms at the moment of creation, that ultimately enable efficient data interoperability through established crosswalks between different metadata standards.
After this session, you'll walk away with:
- A practical picture of how terminology services and tools in the active research phase can work together on a reusable interoperability layer for your institution or consortium.
- An understanding of how cross-schema mappings (DataCite ↔ schema.org / DCAT) can act as a robust interoperability layer — versioned, transparent, and ready to reuse.
- Inspiration for how this integration pattern can extend to other research and research data management tools.
