<p>FAIR data is central to open data practices, and stands for making data <b>F</b>indable, <b>A</b>ccessible, <b>I</b>nteroperable, and <b>R</b>eusable.</p>
We’ll be exploring steps needed to share data effectively later in the guide, but some helpful FAIR data resources include:
The full FAIR principles and guidelines
A FAIRy tale for a simple breakdown of each principle
GO FAIR materials and workshops
Data should be deposited in a repository
This location should be given a DOI or PID
You should use metadata to give a detailed description of your data, helping it to be more easily findable by computers (and humans!)
Your chosen repository must use a standard protocol like http://
The repository must continue to provide a landing page and metadata even if the dataset is removed
The metadata used to describe the data should be based on the standard subject vocabularies and should be machine-readable
The metadata should be extensive, accurate, and relevant, to the point that others could replicate or apply the data from the information
An explicit license must be applied to the data, explaining what others can and cannot do.