Data-driven Agronomy

Welcome

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.

Email | Work Plan

Events

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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