Data-driven Agronomy


To the Data-Driven Agronomy Community of Practice

Data-driven agronomy refers to an approach or a set of approaches using digital technology to source, analyze and translate data into timely, practical and context-specific information to help farmers make the best choices for their farms.

As a community of practice we aim to collectively strengthen the innovation of technology and big data to tackle an array of agricultural challenges – including the closing of yield gaps – to reduce hunger and poverty and transform global agriculture.

The data-driven agronomy CoP, led by CIAT, builds capacity among farmers, researchers, rural advisory service providers and CGIAR strategic partners. This space can be used as a discussion area, share and request relevant information and contribute towards building the community as a whole.

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Community News

Data cleaning, the unsexy but essential aspect of data science

Data scientists need to be more serious about standardization, to make data interoperable, says Daniel Jimenez.

A vision for the data-driven agronomy community of practice

Daniel Jimenez on how Data-driven agronomy community of practice will advance data-driven agronomy to support the farmers, technicians and researchers committed to meet the Sustainable Development Goals.

Don’t hunt for data unicorns, they don’t exist

Data unicorns are a myth — plain and simple. What any organization needs to do is to build a team of experts whose skills complement each other and work with external specialists if needed so they can make magic to develop real-world solutions.

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