standards > reporting guideline > DOI:10.25504/FAIRsharing.WWI10U

ready The FAIR Principles

Abbreviation: FAIR

General Information
One of the grand challenges of data-intensive science is to facilitate knowledge discovery by assisting humans and machines in their discovery of, access to, integration and analysis of, task-appropriate scientific data and their associated algorithms and workflows. The term "FAIR" was launched at a Lorentz workshop in 2014, attended by a wide range of academic, corporate, and governmental stakeholders. The resulting draft FAIR Principles were initially made available for public comment via the websites of peer-initiatives such as, for example, Force11. Based on this feedback, the final Principles were published in 2016 ( FAIR is a set of guiding principles to make data Findable, Accessible, Interoperable, and Re-usable. These guidelines provide advice for those wishing to enhance the (re)usability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals.

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How to cite this record FAIR; The FAIR Principles; DOI:; Last edited: Oct. 24, 2019, 2:56 p.m.; Last accessed: May 06 2021 11:32 a.m.

This record is maintained by MarkWilkinson  ORCID

Record added: March 16, 2018, 10:45 a.m.
Record updated: Oct. 24, 2019, 1:08 p.m. by The FAIRsharing Team.

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The FAIR Guiding Principles for scientific data management and stewardship.

Wilkinson MD,Dumontier M,Aalbersberg IJ,Appleton G,Axton M,Baak A,Blomberg N,Boiten JW,da Silva Santos LB,Bourne PE,Bouwman J,Brookes AJ,Clark T,Crosas M,Dillo I,Dumon O,Edmunds S,Evelo CT,Finkers R,Gonzalez-Beltran A,Gray AJ,Groth P,Goble C,Grethe JS,Heringa J,'t Hoen PA,Hooft R,Kuhn T,Kok R,Kok J,Lusher SJ,Martone ME,Mons A,Packer AL,Persson B,Rocca-Serra P,Roos M,van Schaik R,Sansone SA,Schultes E,Sengstag T,Slater T,Strawn G,Swertz MA,Thompson M,van der Lei J,van Mulligen E,Velterop J,Waagmeester A,Wittenburg P,Wolstencroft K,Zhao J,Mons B
Sci Data 2016

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Related Databases (6)
FAIRsharing is a FAIR-supporting resource that provides an informative and educational registry on data standards, databases, repositories and policy, alongside search and visualization tools and services that interoperate with other FAIR-enabling resources. FAIRsharing guides consumers to discover, select and use standards, databases, repositories and policy with confidence, and producers to make their resources more discoverable, more widely adopted and cited. Each record in FAIRsharing is curated in collaboration with the maintainers of the resource themselves, ensuring that the metadata in the FAIRsharing registry is accurate and timely. Every record is manually reviewed at least once a year. Records can be collated into collections, based on a project, society or organisation, or Recommendations, where they are collated around a policy, such as a journal or funder data policy.

4TU.ResearchData is an international data repository for science, engineering and design, open to anyone in the world to upload and download data. Its services include curation, sharing, long-term access and preservation of research datasets. These services are available to anyone around the world. In addition, 4TU.ResearchData also offers training and resources to researchers to support them in making research data findable, accessible, interoperable and reproducible (FAIR).

The Tromsø Repository of Language and Linguistics
The Tromsø Repository of Language and Linguistics (TROLLing) is a repository of data, code, and other related materials used in linguistic research. The repository is open access, which means that all information is available to everyone. All postings are accompanied by searchable metadata that identify the researchers, the languages and linguistic phenomena involved, the statistical methods applied, and scholarly publications based on the data (where relevant). DataverseNO is aligned with the FAIR Guiding Principles for scientific data management and stewardship. Being part of DataverseNO, TROLLing is CoreTrustSeal certified.

DataverseNO ( is a national, generic repository for open research data, owned and operated by UiT The Arctic University of Norway. DataverseNO is aligned with the FAIR Guiding Principles for scientific data management and stewardship. The technical infrastructure of the repository is based on the open source application Dataverse, which is developed by an international developer and user community led by Harvard University. DataverseNO is CoreTrustSeal certified.

Metabolic Atlas
Metabolic Atlas integrates open source genome-scale metabolic models (GEMs) of human and yeast for easy browsing and analysis. It also contains many more GEMs constructed by our organization. Detailed biochemical information is provided for individual model components, such as reactions, metabolites, and genes. These components are also associated with standard identifiers, facilitating integration with external databases, such as the Human Protein Atlas.

CORA. Repositori de dades de Recerca
The CORA. Repositori de dades de Recerca is a repository of open, curated and FAIR data that covers all academic disciplines. CORA. Repositori de dades de Recerca is a shared service provided by participating Catalan institutions (Universities and CERCA Research Centers). The repository is managed by the CSUC and technical infrastructure is based on the Dataverse application, developed by international developers and users led by Harvard University (

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