Data science is changing the way policymakers, agricultural professionals and farmers, make decisions. Cutting-edge technologies have made it possible to collect data about soil, water, and other farm data; store data in centralized systems; then share and exchange data at various levels and for multiple uses.  Farm data can be augmented by integrated data from external sources such as satellites, weather stations and localized ground data to create large datasets for analysis. Data analytics can be used to extract insights that help farmers optimize their farming and build smart agriculture systems to digitally operate their farms.  With data at core of agriculture systems, farmers and policymakers can engage in data-driven decisions relating to planning, planting, harvesting, processing, marketing, consumption as well as agricultural trade. From data acquisition and data analytics to building smart systems, internet of Things (IoT), Artificial Intelligence (AI) and Machine Learning are integral parts of data science and data use. The overall goal of the event is to shed some light on the increasing scope of data science and its use in agriculture. Increasing access to data and professional skills to use data ensures the establishment of a mindset for trustworthy data science to drive human progress for all. The session will provide an account of the need for data science in agriculture, the opportunities it creates, and the risks it might pose. The impacts of data-driven agriculture will be highlighted followed by conclusion.

09:00 – 09:05

09:05- 09:10

09:10-09:25

Keynote speech:
Data science and data use in science and innovation for agrifood systems

GUO Huadong
Director General, International Research Center of Big Data for Sustainable Development Goals (CBAS)
Chinese Academy of Sciences (CAS)

09:25 – 10:20

10:20 – 10:40

10:40-10:45

Closing
Summary of key messages and recommendations

Anne Mullen, Nature Food