The FAIR Funder pilot programme to make it easy for funders to require and for grantees to produce FAIR Data

Peter Wittenburg, Hana Pergl Sustkova, Annalisa Montesanti, Margreet Bloemers, S.H. de Waard, Mark A. Musen, John Graybeal, Kristina M. Hettne, Annika Jacobsen, Robert Pergl, Rob W.W. Hooft, Christine Staiger, Celia W.G. van Gelder, Sebastiaan L. Knijnenburg, A.C. van Arkel, Bert Meerman, Mark D. Wilkinson, S.A. Sansone, Philippe Rocca-Serra, Peter McQuilton & 40 others Alejandra N. Gonzalez-Beltran, G.J.C. Aben, P. Henning, Maria Simone de Menezes Alencar, C. Ribeiro, C.R.L. Silva, Luis Sayao, Luana Sales, Viviane Veiga, Jefferson Lima, Simone Dib, Paula Xavier dos Santos, R. Murtinho, Jakob Tendel, B.F. Schaap, P.M. Brouwer, A.K. Gavai, Yamine Bouzembrak, Hans J.P. Marvin, Albert Mons, Tobias Kuhn, A.A. Gambardella, Ricardo de Miranda Azevedo, Vesa Muhonen, Mira van der Naald, N.W. Smit, M.J. Buys, Taco F. de Bruin, Fieke Schoots, H.J.E. Goodson, Henry S. Rzepa, Keith G. Jeffery, Hugh P. Shanahan, M. Axton, Veniamin Tkachenko, Anne Deslattes Maya, Natalie Meyers, Michael Conlon, Laurel L. Haak, Erik Schultes

Research output: Working paperAcademic

Abstract

There is a growing acknowledgement in the scientific community of the importance of making experimental data machine findable, accessible, interoperable, and reusable (FAIR). Recognizing that high quality metadata are essential to make datasets FAIR, members of the GO FAIR Initiative and the Research Data Alliance (RDA) have initiated a series of workshops to encourage the creation of Metadata for Machines (M4M), enabling any self-identified stakeholder to define and promote the reuse of standardized, comprehensive machine-actionable metadata. The funders of scientific research recognize that they have an important role to play in ensuring that experimental results are FAIR, and that high quality metadata and careful planning for FAIR data stewardship are central to these goals. We describe the outcome of a recent M4M workshop that has led to a pilot programme involving two national science funders, the Health Research Board of Ireland (HRB) and the Netherlands Organisation for Health Research and Development (ZonMW). These funding organizations will explore new technologies to define at the time that a request for proposals is issued the minimal set of machine-actionable metadata that they would like investigators to use to annotate their datasets, to enable investigators to create such metadata to help make their data FAIR, and to develop data-stewardship plans that ensure that experimental data will be managed appropriately abiding by the FAIR principles. The FAIR Funders design envisions a data-management workflow having seven essential stages, where solution providers are openly invited to participate. The initial pilot programme will launch using existing computer-based tools of those who attended the M4M Workshop.
Original languageEnglish
Number of pages13
Publication statusPublished - 26 Feb 2019

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Wittenburg, P., Sustkova, H. P., Montesanti, A., Bloemers, M., de Waard, S. H., Musen, M. A., ... Schultes, E. (2019). The FAIR Funder pilot programme to make it easy for funders to require and for grantees to produce FAIR Data.
Wittenburg, Peter ; Sustkova, Hana Pergl ; Montesanti, Annalisa ; Bloemers, Margreet ; de Waard, S.H. ; Musen, Mark A. ; Graybeal, John ; Hettne, Kristina M. ; Jacobsen, Annika ; Pergl, Robert ; Hooft, Rob W.W. ; Staiger, Christine ; van Gelder, Celia W.G. ; Knijnenburg, Sebastiaan L. ; van Arkel, A.C. ; Meerman, Bert ; Wilkinson, Mark D. ; Sansone, S.A. ; Rocca-Serra, Philippe ; McQuilton, Peter ; Gonzalez-Beltran, Alejandra N. ; Aben, G.J.C. ; Henning, P. ; de Menezes Alencar, Maria Simone ; Ribeiro, C. ; Silva, C.R.L. ; Sayao, Luis ; Sales, Luana ; Veiga, Viviane ; Lima, Jefferson ; Dib, Simone ; Xavier dos Santos, Paula ; Murtinho, R. ; Tendel, Jakob ; Schaap, B.F. ; Brouwer, P.M. ; Gavai, A.K. ; Bouzembrak, Yamine ; Marvin, Hans J.P. ; Mons, Albert ; Kuhn, Tobias ; Gambardella, A.A. ; de Miranda Azevedo, Ricardo ; Muhonen, Vesa ; van der Naald, Mira ; Smit, N.W. ; Buys, M.J. ; de Bruin, Taco F. ; Schoots, Fieke ; Goodson, H.J.E. ; Rzepa, Henry S. ; Jeffery, Keith G. ; Shanahan, Hugh P. ; Axton, M. ; Tkachenko, Veniamin ; Deslattes Maya, Anne ; Meyers, Natalie ; Conlon, Michael ; Haak, Laurel L. ; Schultes, Erik. / The FAIR Funder pilot programme to make it easy for funders to require and for grantees to produce FAIR Data. 2019.
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title = "The FAIR Funder pilot programme to make it easy for funders to require and for grantees to produce FAIR Data",
abstract = "There is a growing acknowledgement in the scientific community of the importance of making experimental data machine findable, accessible, interoperable, and reusable (FAIR). Recognizing that high quality metadata are essential to make datasets FAIR, members of the GO FAIR Initiative and the Research Data Alliance (RDA) have initiated a series of workshops to encourage the creation of Metadata for Machines (M4M), enabling any self-identified stakeholder to define and promote the reuse of standardized, comprehensive machine-actionable metadata. The funders of scientific research recognize that they have an important role to play in ensuring that experimental results are FAIR, and that high quality metadata and careful planning for FAIR data stewardship are central to these goals. We describe the outcome of a recent M4M workshop that has led to a pilot programme involving two national science funders, the Health Research Board of Ireland (HRB) and the Netherlands Organisation for Health Research and Development (ZonMW). These funding organizations will explore new technologies to define at the time that a request for proposals is issued the minimal set of machine-actionable metadata that they would like investigators to use to annotate their datasets, to enable investigators to create such metadata to help make their data FAIR, and to develop data-stewardship plans that ensure that experimental data will be managed appropriately abiding by the FAIR principles. The FAIR Funders design envisions a data-management workflow having seven essential stages, where solution providers are openly invited to participate. The initial pilot programme will launch using existing computer-based tools of those who attended the M4M Workshop.",
author = "Peter Wittenburg and Sustkova, {Hana Pergl} and Annalisa Montesanti and Margreet Bloemers and {de Waard}, S.H. and Musen, {Mark A.} and John Graybeal and Hettne, {Kristina M.} and Annika Jacobsen and Robert Pergl and Hooft, {Rob W.W.} and Christine Staiger and {van Gelder}, {Celia W.G.} and Knijnenburg, {Sebastiaan L.} and {van Arkel}, A.C. and Bert Meerman and Wilkinson, {Mark D.} and S.A. Sansone and Philippe Rocca-Serra and Peter McQuilton and Gonzalez-Beltran, {Alejandra N.} and G.J.C. Aben and P. Henning and {de Menezes Alencar}, {Maria Simone} and C. Ribeiro and C.R.L. Silva and Luis Sayao and Luana Sales and Viviane Veiga and Jefferson Lima and Simone Dib and {Xavier dos Santos}, Paula and R. Murtinho and Jakob Tendel and B.F. Schaap and P.M. Brouwer and A.K. Gavai and Yamine Bouzembrak and Marvin, {Hans J.P.} and Albert Mons and Tobias Kuhn and A.A. Gambardella and {de Miranda Azevedo}, Ricardo and Vesa Muhonen and {van der Naald}, Mira and N.W. Smit and M.J. Buys and {de Bruin}, {Taco F.} and Fieke Schoots and H.J.E. Goodson and Rzepa, {Henry S.} and Jeffery, {Keith G.} and Shanahan, {Hugh P.} and M. Axton and Veniamin Tkachenko and {Deslattes Maya}, Anne and Natalie Meyers and Michael Conlon and Haak, {Laurel L.} and Erik Schultes",
year = "2019",
month = "2",
day = "26",
language = "English",
type = "WorkingPaper",

}

Wittenburg, P, Sustkova, HP, Montesanti, A, Bloemers, M, de Waard, SH, Musen, MA, Graybeal, J, Hettne, KM, Jacobsen, A, Pergl, R, Hooft, RWW, Staiger, C, van Gelder, CWG, Knijnenburg, SL, van Arkel, AC, Meerman, B, Wilkinson, MD, Sansone, SA, Rocca-Serra, P, McQuilton, P, Gonzalez-Beltran, AN, Aben, GJC, Henning, P, de Menezes Alencar, MS, Ribeiro, C, Silva, CRL, Sayao, L, Sales, L, Veiga, V, Lima, J, Dib, S, Xavier dos Santos, P, Murtinho, R, Tendel, J, Schaap, BF, Brouwer, PM, Gavai, AK, Bouzembrak, Y, Marvin, HJP, Mons, A, Kuhn, T, Gambardella, AA, de Miranda Azevedo, R, Muhonen, V, van der Naald, M, Smit, NW, Buys, MJ, de Bruin, TF, Schoots, F, Goodson, HJE, Rzepa, HS, Jeffery, KG, Shanahan, HP, Axton, M, Tkachenko, V, Deslattes Maya, A, Meyers, N, Conlon, M, Haak, LL & Schultes, E 2019 'The FAIR Funder pilot programme to make it easy for funders to require and for grantees to produce FAIR Data'.

The FAIR Funder pilot programme to make it easy for funders to require and for grantees to produce FAIR Data. / Wittenburg, Peter; Sustkova, Hana Pergl; Montesanti, Annalisa; Bloemers, Margreet; de Waard, S.H.; Musen, Mark A.; Graybeal, John; Hettne, Kristina M.; Jacobsen, Annika; Pergl, Robert; Hooft, Rob W.W.; Staiger, Christine; van Gelder, Celia W.G.; Knijnenburg, Sebastiaan L.; van Arkel, A.C.; Meerman, Bert; Wilkinson, Mark D.; Sansone, S.A.; Rocca-Serra, Philippe; McQuilton, Peter; Gonzalez-Beltran, Alejandra N.; Aben, G.J.C.; Henning, P.; de Menezes Alencar, Maria Simone; Ribeiro, C.; Silva, C.R.L.; Sayao, Luis; Sales, Luana; Veiga, Viviane; Lima, Jefferson; Dib, Simone; Xavier dos Santos, Paula; Murtinho, R.; Tendel, Jakob; Schaap, B.F.; Brouwer, P.M.; Gavai, A.K.; Bouzembrak, Yamine; Marvin, Hans J.P.; Mons, Albert; Kuhn, Tobias; Gambardella, A.A.; de Miranda Azevedo, Ricardo; Muhonen, Vesa; van der Naald, Mira; Smit, N.W.; Buys, M.J.; de Bruin, Taco F.; Schoots, Fieke; Goodson, H.J.E.; Rzepa, Henry S.; Jeffery, Keith G.; Shanahan, Hugh P.; Axton, M.; Tkachenko, Veniamin; Deslattes Maya, Anne; Meyers, Natalie; Conlon, Michael; Haak, Laurel L.; Schultes, Erik.

2019.

Research output: Working paperAcademic

TY - UNPB

T1 - The FAIR Funder pilot programme to make it easy for funders to require and for grantees to produce FAIR Data

AU - Wittenburg, Peter

AU - Sustkova, Hana Pergl

AU - Montesanti, Annalisa

AU - Bloemers, Margreet

AU - de Waard, S.H.

AU - Musen, Mark A.

AU - Graybeal, John

AU - Hettne, Kristina M.

AU - Jacobsen, Annika

AU - Pergl, Robert

AU - Hooft, Rob W.W.

AU - Staiger, Christine

AU - van Gelder, Celia W.G.

AU - Knijnenburg, Sebastiaan L.

AU - van Arkel, A.C.

AU - Meerman, Bert

AU - Wilkinson, Mark D.

AU - Sansone, S.A.

AU - Rocca-Serra, Philippe

AU - McQuilton, Peter

AU - Gonzalez-Beltran, Alejandra N.

AU - Aben, G.J.C.

AU - Henning, P.

AU - de Menezes Alencar, Maria Simone

AU - Ribeiro, C.

AU - Silva, C.R.L.

AU - Sayao, Luis

AU - Sales, Luana

AU - Veiga, Viviane

AU - Lima, Jefferson

AU - Dib, Simone

AU - Xavier dos Santos, Paula

AU - Murtinho, R.

AU - Tendel, Jakob

AU - Schaap, B.F.

AU - Brouwer, P.M.

AU - Gavai, A.K.

AU - Bouzembrak, Yamine

AU - Marvin, Hans J.P.

AU - Mons, Albert

AU - Kuhn, Tobias

AU - Gambardella, A.A.

AU - de Miranda Azevedo, Ricardo

AU - Muhonen, Vesa

AU - van der Naald, Mira

AU - Smit, N.W.

AU - Buys, M.J.

AU - de Bruin, Taco F.

AU - Schoots, Fieke

AU - Goodson, H.J.E.

AU - Rzepa, Henry S.

AU - Jeffery, Keith G.

AU - Shanahan, Hugh P.

AU - Axton, M.

AU - Tkachenko, Veniamin

AU - Deslattes Maya, Anne

AU - Meyers, Natalie

AU - Conlon, Michael

AU - Haak, Laurel L.

AU - Schultes, Erik

PY - 2019/2/26

Y1 - 2019/2/26

N2 - There is a growing acknowledgement in the scientific community of the importance of making experimental data machine findable, accessible, interoperable, and reusable (FAIR). Recognizing that high quality metadata are essential to make datasets FAIR, members of the GO FAIR Initiative and the Research Data Alliance (RDA) have initiated a series of workshops to encourage the creation of Metadata for Machines (M4M), enabling any self-identified stakeholder to define and promote the reuse of standardized, comprehensive machine-actionable metadata. The funders of scientific research recognize that they have an important role to play in ensuring that experimental results are FAIR, and that high quality metadata and careful planning for FAIR data stewardship are central to these goals. We describe the outcome of a recent M4M workshop that has led to a pilot programme involving two national science funders, the Health Research Board of Ireland (HRB) and the Netherlands Organisation for Health Research and Development (ZonMW). These funding organizations will explore new technologies to define at the time that a request for proposals is issued the minimal set of machine-actionable metadata that they would like investigators to use to annotate their datasets, to enable investigators to create such metadata to help make their data FAIR, and to develop data-stewardship plans that ensure that experimental data will be managed appropriately abiding by the FAIR principles. The FAIR Funders design envisions a data-management workflow having seven essential stages, where solution providers are openly invited to participate. The initial pilot programme will launch using existing computer-based tools of those who attended the M4M Workshop.

AB - There is a growing acknowledgement in the scientific community of the importance of making experimental data machine findable, accessible, interoperable, and reusable (FAIR). Recognizing that high quality metadata are essential to make datasets FAIR, members of the GO FAIR Initiative and the Research Data Alliance (RDA) have initiated a series of workshops to encourage the creation of Metadata for Machines (M4M), enabling any self-identified stakeholder to define and promote the reuse of standardized, comprehensive machine-actionable metadata. The funders of scientific research recognize that they have an important role to play in ensuring that experimental results are FAIR, and that high quality metadata and careful planning for FAIR data stewardship are central to these goals. We describe the outcome of a recent M4M workshop that has led to a pilot programme involving two national science funders, the Health Research Board of Ireland (HRB) and the Netherlands Organisation for Health Research and Development (ZonMW). These funding organizations will explore new technologies to define at the time that a request for proposals is issued the minimal set of machine-actionable metadata that they would like investigators to use to annotate their datasets, to enable investigators to create such metadata to help make their data FAIR, and to develop data-stewardship plans that ensure that experimental data will be managed appropriately abiding by the FAIR principles. The FAIR Funders design envisions a data-management workflow having seven essential stages, where solution providers are openly invited to participate. The initial pilot programme will launch using existing computer-based tools of those who attended the M4M Workshop.

M3 - Working paper

BT - The FAIR Funder pilot programme to make it easy for funders to require and for grantees to produce FAIR Data

ER -

Wittenburg P, Sustkova HP, Montesanti A, Bloemers M, de Waard SH, Musen MA et al. The FAIR Funder pilot programme to make it easy for funders to require and for grantees to produce FAIR Data. 2019 Feb 26.