Accurate data on the location and size of agricultural fields is important for almost all kinds of agricultural analysis. Through the new partnership, CGIAR and Linux Foundation will unify data standards and standard operating procedures to support the sharing and use of field boundary data at scale. The project will support the responsible use of agricultural field data, strengthening analytics for global farming.
Commenting on the initiative, Sumer Johal, Executive Director of The AgStack Project  at the Linux Foundation, said: “CGIAR and the Linux Foundation are natural partners. Both are trusted intermediaries with global partner networks, facilitating pre-competitive collaboration and products for the public good. Together we can help remove the blockages around working with field data in a community-driven way.”
The Linux Foundation is the world’s largest open-source collaboration. Its AgStack Project is building the open-source digital infrastructure to power tomorrow’s agriculture needs.
Digitalization is paving the way for extensive transformation in the agricultural sector, but the adoption and use of data-enabled applications is still fragmented and crop specific. Through its new Digital Innovation and Transformation Initiative (DI/DX) , CGIAR is supporting the development of cost-effective digital innovations in the sector. Agricultural field data is central to this work.
“Global agriculture is increasingly driven by data. The sharing and exchange of well-described, reusable agricultural data can help develop solutions to some of the global food system’s most pressing challenges,” said Jawoo Koo, Lead of the DI/DX Initiative at CGIAR. “Despite growing demand, poor adoption of standards and fragmentation in the digital agriculture sector have hindered access to the data needed to drive innovation. Our new partnership with the Linux Foundation aims to change this and serve a new generation of digital agri-food services with the speed and scale to revolutionize food, land and water systems.”
Accurate data on the location and size of agricultural fields can be used to calculate yields and guide efficient use of agricultural inputs such as fertilizer and seeds, or by financial services providers to develop and tailor innovative digital finance products, including loans and insurance, to meet the needs of smallholder farmers. On a larger scale, these data can be used to help researchers predict shifts in the suitability of crop growing zones and prepare food systems for a changing climate.