Data sharing means making your research data available for others to check and reuse — ideally following the FAIR principles: Findable, Accessible, Interoperable, Reusable. Open data lets science verify itself and lets one person’s hard-won dataset power discoveries they never imagined.

For centuries, research data stayed locked in a drawer while only the conclusions were published. That’s changing fast — and for good reason. When data is shared, others can check that the findings hold, and build new work on top without starting from scratch. Sharing turns a private result into a public resource.

The FAIR principles, in plain words

• Findable — described well and given a permanent ID, so people can locate it.
• Accessible — retrievable through an open, standard route (with access rules where needed).
• Interoperable — in common formats other tools and people can read.
• Reusable — documented and clearly licensed, so others know how they may use it.

Open as far as possible, closed as far as necessary

Sharing has limits — you must protect personal or sensitive information. The guiding phrase is “as open as possible, as closed as necessary”: share what you safely can, anonymise or restrict what you can’t, and always respect the people behind the data.

🔗 A friendly free guide: Digital Curation Centre

Whether kept or shared, the most valuable data must survive for the long term — far beyond the project that made it. On to Long-term Preservation.

© FRELIP, released under CC BY 4.0. Linked resources remain under their own licences. Curated by the FRELIP Open Courseware editorial team.