Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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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 ; Waard, S.H. de; Musen, Mark A. ; Graybeal, John ; Hettne, Kristina M. ; Jacobsen, Annika ; Pergl, Robert ; Hooft, Rob W.W. ; Staiger, Christine ; Gelder, Celia W.G. van; Knijnenburg, Sebastiaan L. ; Arkel, A.C. van; Meerman, Bert ; Wilkinson, Mark D. ; Sansone, S.A. ; Rocca-Serra, Philippe ; McQuilton, Peter ; Gonzalez-Beltran, Alejandra N. ; Aben, G.J.C. ; Henning, P. ; Menezes Alencar, Maria Simone de; Ribeiro, C. ; Silva, C.R.L. ; Sayao, Luis ; Sales, Luana ; Veiga, Viviane ; Lima, Jefferson ; Dib, Simone ; Xavier dos Santos, Paula dos; 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. ; Miranda Azevedo, Ricardo de; Muhonen, Vesa ; Naald, Mira van der; Smit, N.W. ; Buys, M.J. ; Bruin, Taco F. de; 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
arXiv - 13 p.
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.
Addendum: The FAIR Guiding Principles for scientific data management and stewardship
Wilkinson, Mark D. ; Dumontier, Michel ; Aalbersberg, Ijsbrand Jan ; Appleton, Gabrielle ; Axton, Myles ; Baak, Arie ; Blomberg, Niklas ; Boiten, Jan Willem ; Silva Santos, Luiz Bonino Da; Bourne, Philip E. ; Bouwman, Jildau ; Brookes, Anthony J. ; Clark, Tim ; Crosas, Mercè ; Dillo, Ingrid ; Dumon, Olivier ; Edmunds, Scott ; Evelo, Chris T. ; Finkers, Richard ; Gonzalez-Beltran, Alejandra ; Gray, Alasdair J.G. ; Groth, Paul ; Goble, Carole ; Grethe, Jeffrey S. ; Heringa, Jaap ; Hoen, Peter A.C. 't; Hooft, Rob ; Kuhn, Tobias ; Kok, Ruben ; Kok, Joost ; Lusher, Scott J. ; Martone, Maryann E. ; Mons, Albert ; Packer, Abel L. ; Persson, Bengt ; Rocca-Serra, Philippe ; Roos, Marco ; Schaik, Rene van; Sansone, Susanna Assunta ; Schultes, Erik ; Sengstag, Thierry ; Slater, Ted ; Strawn, George ; Swertz, Morris A. ; Thompson, Mark ; Lei, Johan van der; Mulligen, Erik van; Velterop, Jan ; Waagmeester, Andra ; Wittenburg, Peter ; Wolstencroft, Katherine ; Zhao, Jun ; Mons, Barend - \ 2019
Scientific Data 6 (2019). - ISSN 2052-4463

The FAIR Guiding Principles for scientific data management and stewardship : Comment
Wilkinson, Mark D. ; Dumontier, Michel ; Aalbersberg, Ijsbrand Jan ; Appleton, Gabrielle ; Axton, Myles ; Baak, Arie ; Blomberg, Niklas ; Boiten, Jan Willem ; Silva Santos, Luiz Bonino Da; Bourne, Philip E. ; Bouwman, Jildau ; Brookes, Anthony J. ; Clark, Tim ; Crosas, Mercè ; Dillo, Ingrid ; Dumon, Olivier ; Edmunds, Scott ; Evelo, Chris T. ; Finkers, Richard ; Gonzalez-Beltran, Alejandra ; Gray, Alasdair J.G. ; Groth, Paul ; Goble, Carole ; Grethe, Jeffrey S. ; Heringa, Jaap ; Hoen, Peter A.C. 't; Hooft, Rob ; Kuhn, Tobias ; Kok, Ruben ; Kok, Joost ; Lusher, Scott J. ; Martone, Maryann E. ; Mons, Albert ; Packer, Abel L. ; Persson, Bengt ; Rocca-Serra, Philippe ; Roos, Marco ; Schaik, Rene van; Sansone, Susanna Assunta ; Schultes, Erik ; Sengstag, Thierry ; Slater, Ted ; Strawn, George ; Swertz, Morris A. ; Thompson, Mark ; Lei, Johan van der; Mulligen, Erik van; Velterop, Jan ; Waagmeester, Andra ; Wittenburg, Peter ; Wolstencroft, Katherine ; Zhao, Jun ; Mons, Barend - \ 2016
Scientific Data 3 (2016). - ISSN 2052-4463

There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders-representing academia, industry, funding agencies, and scholarly publishers-have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability 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. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.

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