Data governance in smart farming: A systematic review of challenges and gaps

• Governance to address privacy, security, and information sharing challenges. • Gap identification of strong governance structures in smart farming technologies. • Gap in the awareness and technical knowledge of farmers regarding data governance. • Comprehensive taxonomization of smart farming technologies. Smart Farming (SF) has emerged as a transformative approach in modern agriculture, leveraging advanced technologies to meet escalating global food demands. However, the extensive use of digital devices generates vast amounts of data, necessitating robust governance frameworks to ensure secure, ethical, and efficient management. This systematic review evaluates SF data governance literature from 2018 to 2024, analyzing 32 studies that collectively highlight critical challenges and opportunities. Key findings include the absence of standardized governance frameworks, limited exploration of security mechanisms, and insufficient farmer’s awareness regarding data privacy and security. Our novel taxonomy categorizes SF governance into data security, privacy, and sharing frameworks, offering actionable insights for stakeholders. By identifying gaps—such as the need for transparent governance systems and comprehensive regulatory policies—this paper provides a roadmap for advancing ethical and effective data governance in agriculture.

Authors

Publication Details

Journal
Information Processing in Agriculture
Published
2025-12-01
DOI
https://doi.org/10.1016/j.inpa.2025.11.006
Citations
1
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
1.75
Controls
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Data governance in smart farming: A systematic review of challenges and gaps

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article

Data governance in smart farming: A systematic review of challenges and gaps

Hannaneh Barahouei Pasandi, Evelyn Sowells-Boone, Gregory D. Goins, Abdolhossein Sarrafzadeh, Radwan Rouzky
article en
1 citations

Abstract

• Governance to address privacy, security, and information sharing challenges. • Gap identification of strong governance structures in smart farming technologies. • Gap in the awareness and technical knowledge of farmers regarding data governance. • Comprehensive taxonomization of smart farming technologies. Smart Farming (SF) has emerged as a transformative approach in modern agriculture, leveraging advanced technologies to meet escalating global food demands. However, the extensive use of digital devices generates vast amounts of data, necessitating robust governance frameworks to ensure secure, ethical, and efficient management. This systematic review evaluates SF data governance literature from 2018 to 2024, analyzing 32 studies that collectively highlight critical challenges and opportunities. Key findings include the absence of standardized governance frameworks, limited exploration of security mechanisms, and insufficient farmer’s awareness regarding data privacy and security. Our novel taxonomy categorizes SF governance into data security, privacy, and sharing frameworks, offering actionable insights for stakeholders. By identifying gaps—such as the need for transparent governance systems and comprehensive regulatory policies—this paper provides a roadmap for advancing ethical and effective data governance in agriculture.

Information Processing in Agriculture
Openalex Percentile: Top 11%
Smart Agriculture and AI
1.75
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