FAIRification of Structural Biology Experimental Metadata
The FAIRification of Structural Biology Experimental Metadata project sets out a practical framework to make metadata from techniques such as X‑ray crystallography, cryo‑EM, NMR, and SAXS more Findable, Accessible, Interoperable, and Reusable. It addresses a common gap in the research lifecycle: rich experimental context is generated across instruments and facilities but is often captured inconsistently or lost before deposition. By standardising how metadata are described and shared—from initial capture in the lab through to submission to public archives—the framework helps ensure that structural data can be reliably discovered, interpreted, and reused.
At its core, the framework provides a minimal‑but‑extensible metadata model, checklists and templates aligned to community standards, and guidance on using controlled vocabularies and ontologies for consistent terminology. It emphasises persistent identifiers (for people, samples, instruments, and projects), clear provenance (who did what, where, when, and how), and machine‑actionable formats to enable automation. Complementary tools and examples show how to map existing lab records to standard schemas, validate and transform metadata, and integrate with institutional data management systems and public repositories, lowering the barrier for facilities and research groups to adopt FAIR practices.
The result is higher‑quality submissions, better cross‑linking between experiments and derived structures, and improved discoverability across modalities. By making metadata consistent and computable, the project supports reproducibility, long‑term stewardship, and downstream reuse—including AI/ML workflows that depend on well‑annotated data. The article invites structural biology labs and facilities to adopt the templates and guidance, contribute feedback to evolve the standards, and work with the community to extend FAIRification across additional techniques and use cases.