Digital agriculture platforms: Driving data-enabled agricultural innovation in a world fraught with privacy and security concerns

Digital agriculture is often heralded as the next major wave of innovation in food and agriculture. Driven by big data, the intention is that digital agriculture will transform the entire research and development pipeline across agricultural value chains throughout the developed and developing worlds. Yet, issues concerning data quality, interoperability, intellectual property ownership and data privacy present considerable challenges to this vision. Digital agriculture platforms, which support data sharing, analysis, interoperability, and public and private sector collaboration, are one approach to address this challenge, but as a new research domain, there is a lack of conceptual clarity around what constitutes a digital agriculture platform. Here, we use a bottom up and top down analysis approach to develop a taxonomy of the digital agriculture landscape. Then, we select a set of digital agriculture platforms for in-depth analysis across a set of technical and use requirements. While digital agriculture will remain a constantly evolving landscape with varied technologies and application areas, this presents a first attempt to characterize this landscape and establish a common vocabulary for understanding digital agriculture platforms.

Automated summary

Digital agriculture is seen as the next major innovative wave in the food and agriculture sector, driven by big data to transform research and development processes. However, challenges like data quality, interoperability, intellectual property rights, and data privacy hinder its progress. While digital agriculture platforms aim to address these challenges, there is still a lack of conceptual clarity in this new research domain.