How to make your data FAIR
The FAIR data principles are guiding principles on how to make data Findable, Accessible, Interoperable and Reusable, formulated by Force11. On this website, the principles are explained and translated into practical information for Utrecht University researchers.
Science, at its core, is a discipline that builds upon the discoveries of its antecedents. The amount of progress we can make as an academic community is therefore intrinsically connected to the amount of information that we make available and reusable to others. As science entered into the digital age, the amount of data produced began to reach astronomical sizes.
Thankfully, the same digital movement brought along digital platforms where the data could be stored and relayed. But how to use these digital platforms in an organised manner? The FAIR principles (Findable, Accessible, Interoperable, Reusable) are a useful framework for thinking about sharing data in a way that will enable maximum use and reuse.
Benefits for research(ers)
Making research data more FAIR will provide a range of benefits to researchers, research communities, research infrastructure facilities and research organisations alike, including:
- Achieving maximum impact from research.
- Increasing the visibility and citations of research.
- Improving the reproducibility and reliability of research.
- Attracting new partnerships with researchers, business, policy and broader communities.
- Enabling new research questions to be answered.
When making data FAIR, metadata plays an important role. Why and how is explained here:
How to make your research data FAIR?
There are different levels of making your data FAIR. Note that you may not always be able to adhere to all. But applying some of the principles to your data will add to the findability, accessibility, interoperability and reusability of your research data.