FAIR guidelines for research data

In 2016 the FAIR Guiding Principles for scientific data management and stewardship in Scientific Data were published. The authors intended to create guidelines to improve the findability, accessibility, interoperability and reuse of digital data. The principles emphasize machine processing/readability (i.e., the ability of computer systems to find, access, interact with, and reuse data with little or no human intervention), as researchers increasingly rely on computer-based data processing due to the growing volume, complexity, and speed of data creation. The guidelines help researchers and data owners to make data discoverable, accessible, interoperable and reusable. This is not only a prerequisite for getting the most out of research data, but is a mandatory requirement for most funding agencies.

In detail FAIR stands for (Wilkinson et al., 2016):

Auffindbarkeit (To be Findable)

F1. (Meta)data are assigned a globally unique and persistent identifier

F2. Data are described with rich metadata (defined by R1 below)

F3. Metadata clearly and explicitly include the identifier of the data it describes

F4. (Meta)data are registered or indexed in a searchable resource

Zugänglichkeit (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

Interoperabilität (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

Wiederverwendbarkeit (To be Reusable)

R1.    (Meta)data are richly described with 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 detailed provenance

R1.3. (Meta)data meet domain-relevant community standards

Further information and references:

FORCE11 (2017): The FAIR Data Principles.

Kraft, A. (2017): Die FAIR Data Prinzipien für Forschungsdaten ( ger. ).

Swiss National Science Foundation (SNF): Explanation of the FAIR Data Principles ( engl. ) .

Wilkinson, Mark D. et al. (2016): The FAIR Guiding Principles for scientific data management and stewardship. In: Scientific Data 3, 160018 EP -. DOI: 10.1038/sdata.2016.18.