This guide, the included recordings, and the included materials that are produced by Lauren Phegley of the University of Pennsylvania are licensed Attribution-NonCommercial 4.0 International (CC BY-NC 4.0).
All's FAIR in Love and Data
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.
Below are a few questions to ask yourself about your data.
If you're creating a data management plan as part of a grant, the specifics of the plan will depend on what your funding agency asks for. Some basics to think about that most agencies will ask for include: