Digital Agriculture Sandbox for Collaborative Research

Digital agriculture is transforming the way we grow food by utilizing technology to make farming more efficient, sustainable, and productive. This modern approach to agriculture generates a wealth of valuable data that could help address global food challenges, but farmers are hesitant to share it due to privacy concerns. This limits the extent to which researchers can learn from this data to inform improvements in farming. This paper presents the Digital Agriculture Sandbox, a secure online platform that solves this problem. The platform enables farmers and researchers to collaborate on analyzing farm data without exposing private information. We employ specialized computer techniques, including federated learning, differential privacy, and data analysis methods, to safeguard the data while maintaining its utility for research purposes. The system works by allowing people to learn from the data and build helpful tools without the sensitive information ever leaving the farmer's computer. This creates a safe space where farmers feel comfortable sharing data, allowing researchers to make important discoveries. Our platform helps bridge the gap between maintaining farm data privacy and utilizing that data to address critical food and farming challenges worldwide.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-10-26
DOI
https://doi.org/10.5281/zenodo.17449791
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
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article

Digital Agriculture Sandbox for Collaborative Research

Zenodo (CERN European Organization for Nuclear Research)
Smart Agriculture and AI
article

Digital Agriculture Sandbox for Collaborative Research

article en

Abstract

Digital agriculture is transforming the way we grow food by utilizing technology to make farming more efficient, sustainable, and productive. This modern approach to agriculture generates a wealth of valuable data that could help address global food challenges, but farmers are hesitant to share it due to privacy concerns. This limits the extent to which researchers can learn from this data to inform improvements in farming. This paper presents the Digital Agriculture Sandbox, a secure online platform that solves this problem. The platform enables farmers and researchers to collaborate on analyzing farm data without exposing private information. We employ specialized computer techniques, including federated learning, differential privacy, and data analysis methods, to safeguard the data while maintaining its utility for research purposes. The system works by allowing people to learn from the data and build helpful tools without the sensitive information ever leaving the farmer's computer. This creates a safe space where farmers feel comfortable sharing data, allowing researchers to make important discoveries. Our platform helps bridge the gap between maintaining farm data privacy and utilizing that data to address critical food and farming challenges worldwide.

Zenodo (CERN European Organization for Nuclear Research)
Georgia Institute of Technology (US), University of Wisconsin–Madison (US), Bilkent University (TR), Case Western Reserve University (US)
Zero hunger
Openalex Percentile: Top 30%
Smart Agriculture and AI
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