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Agricultural data management and sharing: Best practices and case study

Agricultural data are crucial to many aspects of production, commerce, and research involved in feeding the global community. However, in most agricultural research disciplines standard best practices for data management and publication do not exist. Here we propose a set of best practices in the ar...

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Published in:Agronomy journal 2022-09, Vol.114 (5), p.2624-2634
Main Authors: Moore, Eli K., Kriesberg, Adam, Schroeder, Steven, Geil, Kerrie, Haugen, Inga, Barford, Carol, Johns, Erica M., Arthur, Dan, Sheffield, Megan, Ritchie, Stephanie M., Jackson, Carolyn, Parr, Cynthia
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cited_by cdi_FETCH-LOGICAL-c3099-24d2a2a3d9e1d976f5cb9dde56f998aedc62ff70651e951f0b9114fb436cb2753
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container_end_page 2634
container_issue 5
container_start_page 2624
container_title Agronomy journal
container_volume 114
creator Moore, Eli K.
Kriesberg, Adam
Schroeder, Steven
Geil, Kerrie
Haugen, Inga
Barford, Carol
Johns, Erica M.
Arthur, Dan
Sheffield, Megan
Ritchie, Stephanie M.
Jackson, Carolyn
Parr, Cynthia
description Agricultural data are crucial to many aspects of production, commerce, and research involved in feeding the global community. However, in most agricultural research disciplines standard best practices for data management and publication do not exist. Here we propose a set of best practices in the areas of peer review, minimal dataset development, data repositories, citizen science initiatives, and support for best data management. We illustrate some of these best practices with a case study in dairy agroecosystems research. While many common, and increasingly disparate data management and publication practices are entrenched in agricultural disciplines, opportunities are readily available for promoting and adopting best practices that better enable and enhance data‐intensive agricultural research and production. Core Ideas Peer review can be important for ensuring that the value of agricultural data is maintained. Minimal data sets can foster re‐use for innovation beyond initial data collection. Data repositories should be used and should promote best practices and data transparency. Engaging citizens in agricultural research can enhance data and adoption of research results. Funders, journals, institutions, librarians, and researchers all support good data management.
doi_str_mv 10.1002/agj2.20639
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