Research Data Management

The FAIR Principles, originally developed for management of scientific data (see Wilkinson et al. 2016), are broadly applicable to data in all disciplines. FAIR offers a framework for making data more Findable, Accessible, Interoperable and Reusable.

The principles emphasize machine-actionability (the ability for machines to find and use data with minimal human intervention). 

Detailed information can be found at the link above, but here are a few easy ways for you to make your data FAIR:

• Organize your data with logical file structures and consistent file naming conventions.
• Use open and standard file formats for your data where possible.
• Describe and document your data with appropriate metadata. 
• Assign a Creative Commons or other standard licence to your data.
• Deposit your data into a recognized repository that assigns your dataset a persistent identifier for enhanced discoverability and citability. See the Store and Share section of this guide for help choosing a repository.