FAIRsharing is now available for record creation, update, and search at https://beta.fairsharing.org, please visit us there! Replacement of this read-only version of the legacy site with the new version of FAIRsharing is planned for early January 2022.

FAIRsharing is a community-driven resource with a growing number of users, adopters, collaborators and activities, all working to enable the FAIR Principles and to make Standards, Knowledgebases, Repositories and Data Policies FAIR.

How to cite FAIRsharing:

Sansone, McQuilton, Rocca-Serra et al. FAIRsharing as a community approach to standards, repositories and policies. Nat Biotech. 37, 358–367(2019).

A selection of official reports from funders and other organizations that recommend the use of FAIRsharing as a key asset for all stakeholders to enable FAIR data:

“EOSC Strategic Research and Innovation Agenda" 2021
Funder: EU European Open Science Cloud - EOSC
Discipline: All
“Recommendations on certifying services required to enable FAIR within EOSC” 2021
Funder: EU European Open Science Cloud - EOSC
Discipline: All
“FAIR Metrics for EOSC” 2021
Funder: EU European Open Science Cloud - EOSC
Discipline: All
“Six Recommendations for implementation of FAIR practice” 2020
Funder: EU European Open Science Cloud - EOSC
Discipline: All
“Country Sheets Analysis” 2020
Funder: EU European Open Science Cloud - EOSC
Discipline: All
“Horizon 2020 projects working on COVID-19, SARS-CoV-2 and related topics” 2020
Funder: EU H2020
Discipline: Coronavirus research
“Horizon 2020 Annotated Grant Agreement” 2019
Funder: EU H2020
Discipline: All
“Sustainable and FAIR Data Sharing in the Humanities” 2020
Federation: Academies of Sciences and Humanities - ALLEA
Discipline: Humanities
“Open Research Data and Data Management Plans” 2019
Funder: European Research Council - ERC
Discipline: All
“Turning FAIR into Reality” 2018
Funder: EU European Open Science Cloud - EOSC
Discipline: All
“Open Research Data Task Force Case Study” 2018
Governamental: UK Open Research Data Task Force
Discipline: All
“Framework for Discipline-specific Research Data Management” 2018
Funders Association: Science Europe
Discipline: All

Learn more about the FAIRsharing community, and please do not hesitate to contact us if you are interested in working with us.


Lighthouse stakeholders from our user base.


Guidance and tools we lead on or contribute to.


Our international Advisory Board and Team.


Anyone can use FAIRsharing. Adopters, however, use FAIRsharing specifically to:

  1. Educate their users/community on the variety of existing standards, repositories and policies, and actively encourage them to submit/claim records, where relevant;
  2. Create Recommendations by registering their data policy, and then link it to standards and/or databases recommended in the policy; and/or
  3. Create a Collection by pulling together a list of standards and/or databases around a given domain of interest relevant to them.

If you wish to create a new metadata record on FAIRsharing, you can find instructions here.

Adopters are generally representatives of institutions, libraries, journal publishers, infrastructure programmes, societies and other organizations or projects that in turn serve and guide individual researchers or other stakeholders on research data management matters.

Adopters display a FAIRsharing logo on their websites with a link from their website to our homepage.

We cannot list all of our adopters, but we've listed here those publishers that use FAIRsharing to define and refine their data policy.

Global Organisations

Logo Name





FAIRsharing is not just a registry. The team behind FAIRsharing is involved in a number of FAIR-enabling activities, delivering guidance, tools and services with and for a variety of stakeholders. As these activities mature, we will implement or connect them in/to the FAIRsharing resource itself.

Some of these activities are part of funded projects and of national or international consortia, while others are volunteer efforts that fall under a variety of umbrella organisations, such as working groups (WG) and learned societies.

Our activities are classified using the three GO-FAIR pillar structures (change, build, train) and are outlined here.

Activities Brief description and links Umbrella organisation Related funded projects
CHANGE - focusing on priorities, policies and incentives for implementing FAIR
1. FAIR maturity indicators, metrics and models A core set of 14 universal machine-actionable measurable FAIR Metrics covering the FAIR principles, a questionnaire for manual assessment, and a template form to create new metrics. Publication on these metrics and the FAIRsharing Collection of metrics . GO-FAIR OPEDAS IN; GO-FAIR StRePo; FAIR Metrics WG
Discussion forum to improve the interoperability of existing and emerging FAIR assessment methodologies. RDA FAIR Maturity Model WG bringing together other RDA groups, including the RDA FAIRsharing WG.
2. Cross-publishers common criteria for repository selection Through a collaboration with Datacite, we are working with a number of journal publishers (PLOS, Springer Nature, F1000, Hindawi, Wiley, Taylor and Francis, Elsevier, EMBO Press, eLife, GigaScience and Cambridge University Press) to identify a common set of criteria for selecting and recommending data repositories (and associated standards) that will be implemented in FAIRsharing. Read our pre-print providing a summary of the work.

In addition, please see the following blogs that discuss this work:

Your feedback on these criteria is welcomed. Please use the following form no later than January 31st January 2020.

FAIRsharing team and Datacite   Memorandum of Understanding
3. Journal data policies and the TOP guidelines We are working with Jisc and the Center for Open Science (COS) to disseminate information about open science policies (including preprints & open data journal/funder policies) and to standardize classification of these policies in the hope of encouraging change. FAIRsharing team, COS   Memorandum of Understanding
4. Standardized templates for journal data policies Working within the RDA community and collaborating with a number of journal publishers to help define common frameworks for publisher data policies and increase adoption of (standardized) research data policies by all stakeholders and in particular journal publishers. RDA Standardisation and Implementation IG and RDA FAIRsharing WG
5. UK Reproducibility Network The UK Reproducibility Network (UKRN) is a peer-led consortium that aims to ensure the UK retains its place as a centre for world-leading research. This will be done by investigating the factors that contribute to robust research, promoting training activities, and disseminating best practice, and working with stakeholders to ensure coordination of efforts across the sector. UKRN works across disciplines, ranging from the arts and humanities to the physical sciences, with a particular focus on the biomedical sciences. FAIRsharing is a key stakeholder of UKRN and Reproducible Research Oxford (RROx), the Oxford local network of UKRN UKRN and RROx
BUILD - focussing on the technology needed to enable FAIR
6. Research graphs We are working with OpenAIRE to interconnect information on repositories and standards with other data to provide greater knowledge to researchers and other stakeholders. FAIRsharing team and OpenAIRE Memorandum of Understanding
7. Domain and subject terminologies for data classification We have developed and maintain two terminologies: the Subject Resource Application Ontology (SRAO) describing subject areas / academic disciplines and the Domain Resource Application Ontology (DRAO) describing cross-discipline research domains. These are used by the FAIRsharing curators and the users to describe and classify standards, repositories and polices. FAIRsharing team Wellcome Trust
8. Future-proofing the FAIRsharing technical architecture To adapt and improve the FAIRsharing data model to accurate reflect and respond to community requirements. To update and refactor FAIRsharing code to facilitate improved data visualisation and access and to respond to user requirements. FAIRsharing team and International Advisory Board Wellcome Trust
9. FAIR assessment tools FAIRshake: a prototype software to assess the FAIRness of bioinformatics tools, analyses, and biological datasets against a variety of different metrics that can be uploaded in the tool. FAIRsharing is a core element of this work. FAIRsharing team and the NIH Data Commons teams NIH FAIR Data Commons Consortium
FAIR Evaluator: a software to register and execute tests of compliance with the published FAIR Metrics. FAIRsharing is a core element of this work. Pre-print of this work. GO-FAIR OPEDAS IN; GO-FAIR StRePo IN; FAIR Metrics WG
10. Connecting FAIRsharing to data stewardship and data management plans tools We have a MoU with the Data Stewardship Wizardto provide metadata information on databases, standards and data policies to inform and drive instances of the Data Stewardship Wizard. GO-FAIR Build; GO-FAIR StRePo IN
11. Data FAIRification We are developing a FAIR Cookbook, a process with examples of methods and tools needed to increase the level of FAIRness of biomedical datasets, as part of a public-private consortium under the Innovative Medicine Initiative (IMI) programme. Details of this work and participants here. FAIRsharing team IMI FAIRplus
12. Metadata standards for machines We are investigating how to maximize the ‘computability’ of these data/metadata standards , which are essential to measure the level of compliance of a given dataset (or other digital object) against the relevant metadata descriptors. These machine-readable standards will provide the necessary quantitative and verifiable measures of the degree by which a digital object meet these reporting guidelines. Our work will also feed into a larger GO-FAIR driven effort, as described in this preprint. FAIRsharing team, GO-FAIR StRePo IN; GO-FAIR OPEDAS IN (partly) NIH Data Commons
TRAIN - focussing on FAIR awareness and skills development
13. Guidance to stakeholders We are developing FAIRassist, a tool to navigate and select standards, repositories and other digital objects to guide researchers, data managers and other data producers and consumers to improve the FAIRness of their data. FAIRsharing team EU INFRA EOSC-Life
14. FAIR competencies and curricula Working with the community, including GO-FAIR, CODATA, the RDA and others, we are building infrastructure in training and teaching to enable both a competency or skills framework and a generic teaching curriculum. GO-FAIR Training; GO-FAIR StRePo IN; CODATA, FAIRsFAIR; terms4FAIRskills

Advisory Board

Executive Advisors

  • Varsha Khodiyar, Springer Nature, UK
  • David Carr, The Wellcome Trust and Wellcome Open Research, UK
  • Chris Graf, Wiley, UK
  • Marta Teperek, Data Stewardship Coordinator, TUDelft, The Netherlands
  • Robert Hanisch, Director of the Office of Data and Informatics, National Institute of Standards and Technology (NIST), USA
  • Peter McQuilton, GSK, UK.

Stakeholder Advisors

  • Emma Ganley, Director of Strategic Initiatives, Protocols.io, UK
  • Michael Ball, Biotechnology and Biological Sciences Research Council (BBSRC), UK
  • Theo Bloom, British Medical Journal (BMJ), UK
  • Nick Everitt and Matthew Cannon, Taylor and Francis
  • Wei-Mun Chan, eLife, UK
  • Geraldine Clement-Stoneham, Head of Knowledge Management and Scholarly Communication, Medical Research Council, UK
  • Helena Cousijn, DataCite
  • Scott Edmunds, GigaScience, Oxford University Press
  • Dominic Fripp, JISC, UK
  • Simon Hodson, CODATA
  • Iain Hrynaszkiewicz, PLoS
  • Mike Huerta, Coordinator of Data & and Open Science Initiative, Associate Director for Programme Development at the NIH National Library of Medicine, USA
  • Amye Kenall, VP of Publishing and Product, Research Square, UK
  • Adam Leary, Oxford University Press
  • Thomas Lemberger, EMBO Press
  • Luiz Olavo Bonino, GO-FAIR
  • Kiera McNiece, Cambridge University Press
  • Dagmar Meyer, European Research Council (ERC), Executive Agency, Belgium
  • Marina Soares E Silva, Ilaria Carnevale and Sarah Callaghan, Elsevier
  • Imma Subirats, Information Management Officer, FAO of the United Nations, Italy
  • Molly Cranston and Guillaume Wright, F1000Research
  • Kathryn Sharples, Wiley
  • Catriona MacCallum, Hindawi
  • Sowmya Swaminathan, Springer Nature

Meet The Team

Operating since 2011, and born from an early community-driven portal we launched in 2008 (MIBBI), FAIRsharing has become a sustainable service, hosted at the University of Oxford, and run by the Data Readiness Group funded from a portfolio of infrastructure grants (to Prof. Sansone, a permanent faculty member) that will ensure ongoing management and curation of this invaluable resource.

We also make you aware of the FAIRsharing RDA and Force11 WG webpages. DOI generation for each record is kindly provided through a collaboration with the Bodleian Library at the University of Oxford.

Principal Investigator and Founder
Technical Coordinator
Content and Community Coordinator
Research Software Engineer
Research Software & Knowledge Engineer
Research Software & Knowledge Engineer
Research Software & Web Developer
Curator (Contract)