FAIR stands for ‘Findable, Accessible, Interoperable, and Reusable‘. The FAIR data principles act as an international guideline for the result of high-quality data management.
With the increase in volume, complexity and creation speed of data, humans are more and more relying on computational support for dealing with data. The principles were defined with the focus on machine-actionability, i.e. the capacity of computational systems to find, access, interoperate and reuse data with none or minimal human intervention.
By using correct metadata to describe the data, it will be findable. By using a persistent identifier the data can be found by computer systems automatically.
The data should be accessible for the long term. Even when underlying data is not accessible, the describing metadata should remain available.
The data can be used and combined with other datasets. To achieve this, the data should be stored in generic file types, not in software specific file types.
The options for reuse should be stated clearly in a licence. Without a licence there is no certainty about the options for reuse and creator rights are implicit.