All's FAIR in Love and Data
You may have seen the acronym FAIR used in reference to research data, but what does the acronym mean?
And why should you care about FAIR?
FAIR stands for Findable, Accessible, Interoperable, Reusable and came from the 2016 article "The Fair Guiding Principles for Scientific Data Management and Stewardship," which called for more specific guidance to researchers who wanted to be good stewards of their data. The goal of FAIR is to provide actionable measures for data stewardship through the research lifecycle.
Why should you embrace FAIR? There are several benefits to you as a researcher. First, you are more likely to get appropriate credit for the data, metadata, and other products you create. Because FAIR promotes the use of persistent identifiers, those who use your data will know how to cite your work accurately. Second, FAIR promotes well-documented, accessible, and interoperable documentation, meaning that your data will be more reusable well into the future. Finally, research funders are asking that research projects be consistent with FAIR principles. In short, using the FAIR principles for your data, metadata, and workflows will ensure a long and loving relationship with your data.
Questions to Ask Yourself
Below are a few questions to ask yourself about your data.
Findable:
Accessible:
Interoperable:
Reusable:
Action Steps for a Future with Your Data:
