Abstract
| Original language | English |
|---|---|
| Number of pages | 13 |
| Publication status | Published - 26 Feb 2019 |
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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 paper › Academic
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 -