Data Management

FAIR data is Findable, Accessible, Interoperable, and Reusable. Is your research data FAIR? Appropriate research data management, including the creation of a Data Management Plan (DMP), can help ensure that your data is FAIR and complies with institutional, funding agency, and publisher requirements for making your research data publicly accessible. Conversely, considering the FAIR principles while creating your DMP can also help you craft a DMP that complies with OA requirements. 

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 machine-actionability (i.e., the capacity of computational systems to find, access, interoperate, and reuse data with none or minimal human intervention) because humans increasingly rely on computational support to deal with data as a result of the increase in volume, complexity, and creation speed of data.

Reproduced from GO FAIR, which is licensed under a a Creative Commons Attribution 4.0 License 

FAIR is a set of guiding principles, not a list of requirements. FORCE11 describes this framework as a facilitator of knowledge discovery by assisting humans and machines in their discovery of, access to, integration and analysis of, task-appropriate scientific data and their associate algorithms and workflows.

To be Findable:

F1. (meta)data are assigned a globally unique and eternally persistent identifier.
F2. data are described with rich metadata.
F3. (meta)data are registered or indexed in a searchable resource.
F4. metadata specify the data identifier.

To be Accessible:

A1  (meta)data are retrievable by their identifier using a standardized communications protocol.
A1.1 the protocol is open, free, and universally implementable.
A1.2 the protocol allows for an authentication and authorization procedure, where necessary.
A2 metadata are accessible, even when the data are no longer available.

To be Interoperable:

I1. (meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation.
I2. (meta)data use vocabularies that follow FAIR principles.
I3. (meta)data include qualified references to other (meta)data.

To be Re-Usable:

R1. meta(data) have a plurality of accurate and relevant attributes.
R1.1. (meta)data are released with a clear and accessible data usage license.
R1.2. (meta)data are associated with their provenance.
R1.3. (meta)data meet domain-relevant community standards.

Fair Data Principles Courtesy of FORCE11, The Future of Research Communications and e-Scholarship.