Published Versions 2 Vol 2 (1) : 171–180 2019
The FAIR Funding Model: Providing a Framework for Research Funders to Drive the Transition toward FAIR Data Management and Stewardship Practices
76 1 0
Abstract & Keywords
Abstract: A growing number of research funding organizations (RFOs) are taking responsibility to increase the scientific and social impact of research output. Also reusable research data are recognized as relevant output for gaining impact. RFOs are therefore promoting FAIR research data management and stewardship (RDM) in their research funding cycle. However, the implementation of FAIR RDM still faces important obstacles and challenges. To solve these, stakeholders work together to develop innovative tools and practices. Here we elaborate on the role of RFOs in developing a FAIR funding model to support the FAIR RDM in the funding cycle, integrated with research community specific guidance, criteria, metadata, and enabling automatic assessments of progress and output from RDM. The model facilitates to create research data with a high level of FAIRness that are meaningful for a research community. To fully benefit from the model, RFOs, research institutions and service providers need to implement machine actionability in their FAIR RDM tools and procedures. As many stakeholders still need to get familiar with “human actionable” FAIR data practices, the introduction of the model will be stepwise, with an active role of the RFOs in driving FAIR RDM processes as effectively as possible.
Keywords: FAIR funder; Data stewardship; Data management plan (DMP); Policy; Tools
We thank Mira Staphorst of the Dutch Heart Foundation and her colleagues of the Association of Dutch Health Foundations, Jeremy Geelen of the Canadian Institutes of Health Research, and Kate Holmes of the Stroke Association for their input to the article.
M.D. Wilkinson, M. Dumontier, I.J. Aalbersberg, G. Appleton, M. Axton, A. Baak, … & B. Mons. The FAIR guiding principles for scientific data management and stewardship. Scientific Data 3(2016), Article No.160018. doi: 10.1038/sdata.2016.18.
GLOPID-R: Roadmap for data sharing in public health emergencies (2019). Available at:
ZonMw: Strengthening Impact in The Netherlands. The case of ZonMw (2018). Available at:
S. Hodson. Teaching FAIR. Data Intelligence. Special issue on Emerging FAIR practices. (In press). DI-2019-0023.
P. Ayris, A.L. de San Román, K. Maes, & I. Labastida. Open science and its role in universities: A roadmap for cultural change. League of European Research Universitie (LERU). Advice paper 24 (2018). Available at:
M. Ball, M. Bloemers, D. Carr, V. Cavalli, M. Haglund, V. Kalaitzi, … & Karen Vandevelde. A vision for open science. In: The workshop "Research Institutions and Libraries and the role of Funders in the European Open Science Cloud" held at the LIBER 2018 Conference in Lille, France on 4 Juy 2018. doi: 10.5281/zenodo.1491303.
European Commission: Turning Fair into reality. Final report and action plan from the European Commission expert group on FAIR data (2018). doi: 10.2777/1524.
A. Landi, M. Thompson, V. Giannuzzi, F. Bonifazi, I. Labastida, L.O.B. da Silva Santos, & M. Roos. The “A” of FAIR - As open as possible, as closed as necessary. Data Intelligence. Special issue on Emerging FAIR practices. (In press). DI-2019-0005.
A. Jacobsen. FAIR principles: explanation and implementation considerations. Special issue on Emerging FAIR practices. (In press). Paper #1
S. Scholtens, P. Anbeek, J. Böhmer, M. Brullemans, M. van der Geest, M. Jetten, ... & C. van Gelder. Towards a community-endorsed data steward profession description for life science research (2019). doi: 10.5281/zenodo.2554974.
A. Jacobsen. A generic workflow for the data FAIRification process. Special issue on Emerging FAIR practices. (In press). DI-2019-0027.
Science Europe: Practical guide to the international alignment of research data management D/2018/13.324/4 (2018). Available at:
R. Pergl. Data Management Planning: how requirements and solutions are beginning to converge. Special issue on Emerging FAIR practices. (In press). DI-2019-0018.
M. Thompson. Making FAIR easy with FAIR tools: from creolization to convergence. Special issue on Emerging FAIR practices. (In press). DI-2019-0008
P. Wittenburg, H.P. Sustkova, A. Montesanti, S.M. Bloemers, S.H. de Waard, M.A. Musen, ... & E.A. Schultes. The FAIR Funder pilot programme to make it easy for funders to require and for grantees to produce FAIR data. arXiv preprint. arXiv: 1902.11162, 2019.
H. van Vlijmen, &A. Mons. The need for industry to Go FAIR. Special issue on Emerging FAIR practices. (In press). DI-2019-0022.
Article and author information
Cite As
M. Bloemers & A. Montesanti. The FAIR funding model: Providing a framework for research funders to drive the transition toward FAIR data management and stewardship practices. Data Intelligence 2(2020), 171–180. doi: 10.1162/dint_a_00039
Margreet Bloemers
M. Bloemers ( and A. Montesanti ( conceived and presented the idea relevant to the FAIR funders model and the Dutch and Irish perspectives, respectively. M. Bloemers is the main author of the manuscript.
Margreet Bloemers is project leader for FAIR data & data management at the Netherlands Organization for Health Research and Development (ZonMw). Margreet promotes creating and reusing FAIR data in several contexts: she develops innovative approaches and coordinates procedures for data management in ZonMw’s research programs; at the National Platform Open Science, she is one of the project leaders for introducing open science in academia in the Netherlands. In the field of antimicrobial resistance, she is work package leader for Research Infrastructures at the Joint Programming Initiative Antimicrobial Resistance. Also, she participates in the international consortium VALUE-Dx for innovative diagnostic strategies for more personalized antibiotic therapy in community care settings. Finally, Margreet advises about the implementation of research findings from ZonMw funded projects into policy and practice. Margreet is trained as a biologist, and got her PhD in developmental biology at the Hubrecht Institute in Utrecht, the Netherlands.
Annalisa Montesanti
M. Bloemers ( and A. Montesanti ( conceived and presented the idea relevant to the FAIR funders model and the Dutch and Irish perspectives, respectively.
Annalisa Montesanti is the Program Manager at the Health Research Board (HRB). She is responsible for developing and managing a portfolio for health research careers in order to develop a coordinated approach to building capacity in health research in Ireland. She has developed a framework promoting the training, support and career development of academic researchers and health practitioners with the long-term goal of training individuals as collaborative researcher in order to generate ideas and undertake research, drive the integration of research and evidence into policy and practice, thus improving decision-making and, ultimately, health outcomes and creating a wider impact in society. Annalisa is also deeply involved in promoting open science, FAIR data and research data stewardship through several international collaborations. Annalisa had many years of experience in scientific research in in Italy, England and Ireland. She has a BSc from Palermo University in Italy and a PhD in cancer biology from the Institute of Molecular Medicine in Oxford, UK.
Publication records
Published: None (Versions2
Data Intelligence