In 2016, the ‘FAIR Guiding Principles for scientific data management and Stewardship’ were published in Scientific Data. The authors intended to provide guidelines to improve the Findability, Accessibility, Interoperability, and Reuse of digital assets. The principles emphasize the use of IT systems to access data because of the increasing volume and complexity of data.
The following section gives an in-depth explanation of the FAIR principles:
Findable
The first step in (re)using data is to find them. Metadata and data should be easy to find for both humans and computers. Machine-readable metadata are essential for automatically discovering datasets and services, which is a critical component in the FAIRification process.
2. Accessible
Once the user finds the required data, she/he/they need to know how they can be accessed, possibly including authentication and authorization.
3. Interoperable
The data usually need to be integrated with other data. In addition, the data need to interoperate with applications or workflows for analysis, storage, and processing.
4. Reusable
The ultimate goal of FAIR is to optimize the reuse of data. To achieve this, metadata and data should be well-described so that they can be replicated and/or combined in different settings.
These principles refer to three types of entities: data (or any digital object), metadata (information about that digital object), and infrastructure.
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