Governing agricultural data: Challenges and recommendations

The biomedical domain has shown that in silico analyses over vast data pools enhances the speed and scale of scientific innovation. This can hold true in agricultural research and guide similar multi-stakeholder action in service of global food security as well (Streich et al. Curr Opin Biotechnol 6...

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Main Authors: Devare, Medha, Arnaud, Elizabeth, Antezana, Erick, King, Brian
Format: Book Chapter
Language:Inglés
Published: Springer 2023
Subjects:
Online Access:https://hdl.handle.net/10568/125916
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author Devare, Medha
Arnaud, Elizabeth
Antezana, Erick
King, Brian
author_browse Antezana, Erick
Arnaud, Elizabeth
Devare, Medha
King, Brian
author_facet Devare, Medha
Arnaud, Elizabeth
Antezana, Erick
King, Brian
author_sort Devare, Medha
collection Repository of Agricultural Research Outputs (CGSpace)
description The biomedical domain has shown that in silico analyses over vast data pools enhances the speed and scale of scientific innovation. This can hold true in agricultural research and guide similar multi-stakeholder action in service of global food security as well (Streich et al. Curr Opin Biotechnol 61:217–225. Retrieved from https://doi.org/10.1016/j.copbio.2020.01.010, 2020). However, entrenched research culture and data and standards governance issues to enable data interoperability and ease of reuse continue to be roadblocks in the agricultural research for development sector. Effective operationalization of the FAIR Data Principles towards Findable, Accessible, Interoperable, and Reusable data requires that agricultural researchers accept that their responsibilities in a digital age include the stewardship of data assets to assure long-term preservation, access and reuse. The development and adoption of common agricultural data standards are key to assuring good stewardship, but face several challenges, including limited awareness about standards compliance; lagging data science capacity; emphasis on data collection rather than reuse; and limited fund allocation for data and standards management. Community-based hurdles around the development and governance of standards and fostering their adoption also abound. This chapter discusses challenges and possible solutions to making FAIR agricultural data assets the norm rather than the exception to catalyze a much-needed revolution towards “translational agriculture”.
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spelling CGSpace1259162025-11-06T03:58:17Z Governing agricultural data: Challenges and recommendations Devare, Medha Arnaud, Elizabeth Antezana, Erick King, Brian governance agriculture data standards interoperability data management gobernanza agricultura normas datos The biomedical domain has shown that in silico analyses over vast data pools enhances the speed and scale of scientific innovation. This can hold true in agricultural research and guide similar multi-stakeholder action in service of global food security as well (Streich et al. Curr Opin Biotechnol 61:217–225. Retrieved from https://doi.org/10.1016/j.copbio.2020.01.010, 2020). However, entrenched research culture and data and standards governance issues to enable data interoperability and ease of reuse continue to be roadblocks in the agricultural research for development sector. Effective operationalization of the FAIR Data Principles towards Findable, Accessible, Interoperable, and Reusable data requires that agricultural researchers accept that their responsibilities in a digital age include the stewardship of data assets to assure long-term preservation, access and reuse. The development and adoption of common agricultural data standards are key to assuring good stewardship, but face several challenges, including limited awareness about standards compliance; lagging data science capacity; emphasis on data collection rather than reuse; and limited fund allocation for data and standards management. Community-based hurdles around the development and governance of standards and fostering their adoption also abound. This chapter discusses challenges and possible solutions to making FAIR agricultural data assets the norm rather than the exception to catalyze a much-needed revolution towards “translational agriculture”. 2023 2022-12-13T14:23:39Z 2022-12-13T14:23:39Z Book Chapter https://hdl.handle.net/10568/125916 en Open Access application/pdf Springer Devare, M.; Arnaud, E.; Antezana, E.; King, B. (2022) Governing agricultural data: Challenges and recommendations. In: Williamson, H.F.; Leonelli, S. (eds) Towards responsible plant data linkage: Data challenges for agricultural research and development. Cham (Switzerland): Springer. 22 p. Online first (27 October 2022). ISBN: 978-3-031-13276-6
spellingShingle governance
agriculture
data
standards
interoperability
data management
gobernanza
agricultura
normas
datos
Devare, Medha
Arnaud, Elizabeth
Antezana, Erick
King, Brian
Governing agricultural data: Challenges and recommendations
title Governing agricultural data: Challenges and recommendations
title_full Governing agricultural data: Challenges and recommendations
title_fullStr Governing agricultural data: Challenges and recommendations
title_full_unstemmed Governing agricultural data: Challenges and recommendations
title_short Governing agricultural data: Challenges and recommendations
title_sort governing agricultural data challenges and recommendations
topic governance
agriculture
data
standards
interoperability
data management
gobernanza
agricultura
normas
datos
url https://hdl.handle.net/10568/125916
work_keys_str_mv AT devaremedha governingagriculturaldatachallengesandrecommendations
AT arnaudelizabeth governingagriculturaldatachallengesandrecommendations
AT antezanaerick governingagriculturaldatachallengesandrecommendations
AT kingbrian governingagriculturaldatachallengesandrecommendations