FAIR Principles
The acronym FAIR is used to describe qualities that research data can have which maximises how beneficial it can be. They describes how research outputs should be organised so they can be findable, accessible, interoperable and reusable. Major international and national funding bodies, including the ARC and NHMRC, promote FAIR data to maximise the integrity and impact of their research investment.
The FAIR principles are designed to support knowledge discovery and innovation both by humans and machines. Making your research data FAIR can increase visibility and impact of yourself and your work, maximise potential from your data assets, and improve the reproducibility of your research. Following the FAIR guiding principles will also strengthen your research data management strategy. Even if you don’t intend to share your data with anyone yet, you will most likely reuse your own data.
8 steps to make your data more FAIR
Can Sensitive Data be FAIR?
Sensitive data can be FAIR without being open. The FAIRness is made by a clear description on how access to the data can be granted e.g. for research purposes.
A lot of research is based on sensitive personal data, data protected by IPR (Intellectual Property Rights) agreements or confidential data. This means that access to the data must be managed and restricted.
D.B. Deutz, M.C.H. Buss, J. S. Hansen, K. K. Hansen, K.G. Kjelmann, A.V. Larsen, E. Vlachos, K.F. Holmstrand (2020). How to FAIR: a Danish website to guide researchers on making research data more FAIR. https://doi.org/10.5281/zenodo.3712065
Is your data FAIR to publish?
You can assess whether your data is fair (Findable, Accessible, Interoperable, Reusable) to publish by using
ARDC FAIR data self-assessment tool |
In the tool, you will answer questions related to the principles underpinning Findable, Accessible, Interoperable and Reusable (FAIR).
Once you’ve answered all the questions in each section, you’ll be given a ‘green bar’ indicator based on your answers in that section. When all sections are completed, it provides you with an overall ‘FAIRness’ indicator.