Agricultural Data Sharing

Until the 1980s, farming practices relied heavily on shared knowledge, experience, and intuition. The introduction of precision agriculture – the use of technology and automation to make farming more efficient – both transformed farming practices and introduced a number of agriculture data challenges. Today, data-driven digital agriculture is expected to play a crucial role in producing 60 percent more food to feed the projected global population by 2050 (Yu et al. 2025). The agriculture sector now relies on interconnected data ecosystems to inform decision-making. Precision agriculture merges a wide variety of technology, including sensor networks, Internet-connected devices (also known as Internet-of-Things or IoT), and Artificial Intelligence (AI)-enabled farm machinery. Tools ranging from basic soil moisture sensors to advanced drones, satellite imagery, auto-steering farm equipment, and cloud-based databases comprise the precision agriculture data ecosystem. These devices and sensors are capable of collecting an averaged half a million raw agricultural data points per day per farm – projected to reach 4 million data points by 2036 – and sending this data to third parties for data transformation and processing (Yu et al. 2025).