FAIR principles

The FAIR Data Principles are a set of guiding principles for the management and stewardship of research data. FAIR stands for Findable, Accessible, Interoperable, and Reusable. These principles are designed to facilitate the sharing and reuse of research data (FAIRification process), particularly in the context of scientific research and data-driven disciplines. By adhering to these principles, researchers can maximize the value of their data, as well as increase visibility, and enhance reproducibility of their work.

To be findable:
The first step in (re)using data is to find them. Data and Metadata should be easy to find for both humans and computers. To achieve this, data should be assigned a unique identifier, and metadata describing the data should be rich, clear, standardized and indexed in a searchable resource.

To be accessible:
Data should be easily accessible to both humans and computers, possibly including authentication and authorization, where necessary. This means that data should be stored in a repository or data centre that provides secure and reliable access. Metadata must be accessible, even when data are no longer available. Data should be made accessible using a standardized communications protocol. The protocol is open, free, and universally implementable.

To be interoperable:
Data should be structured and described in a way that allow them to be integrated with other data and systems. This principle emphasizes the importance of using a formal, accessible, shared and broadly applicable language for knowledge representation.

To be reusable:
Data should be designed for reuse and should be well-documented. This includes providing comprehensive metadata, clear and accessible licensing information, and guidance on how to properly cite the data. Additionally, data should be in a format that can be easily used and analysed by other researchers.