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USAID case study highlights CIAT’s data-driven agronomy work

An overview of how CIAT is using data analytics to help farmers make better on-farm decisions.
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USAID case study highlights CIAT’s data-driven agronomy work

Aligning needs with solutions: Data-driven agricultural innovation for Vietnam’s farmers

Vietnam's technology innovators and farmers convened at a workshop to gain a deeper appreciation of the challenges in the field on the one hand, and existing technology solutions on the other.
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Aligning needs with solutions: Data-driven agricultural innovation for Vietnam’s farmers

Mapping Maize using UAV Imagery

Remote sensing-based crop mapping in sub-Saharan Africa (SSA) is challenging due to the small field size, intercropping, different crop species...
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Mapping Maize using UAV Imagery

If Mary has a little lamb, who should know about it?

The GDPR and data science for agricultural development are at odds when it comes to delivering personalized products for the public good.
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If Mary has a little lamb, who should know about it?

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.
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Data cleaning, the unsexy but essential aspect of data science

Here’s how to do bean breeding the climate-smart way

'We need to do ‘preemptive breeding’ if we want to sustain bean production under the more erratic climate of the future'
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Here’s how to do bean breeding the climate-smart way

The Global Biodiversity Informatics Outlook: delivering biodiversity knowledge in the information age

The Global Biodiversity Informatics Outlook is a new framework to deliver biodiversity knowledge. Find out more about how it will help gather unprecedented evidence about biodiversity and inform better decisions.
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The Global Biodiversity Informatics Outlook: delivering biodiversity knowledge in the information age

Harmonizing crop trait data: Crop Ontology

Crop Ontology provides scientists and breeders with a common language that describes crop phenotypes and interprets descriptions provided by farmers for the performance of the varieties they prefer.
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Harmonizing crop trait data: Crop Ontology

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Communities of Practice | NEWS

Find out more about CGIAR’s Open Access Policy, ratified in late 2013 by all 15 CGIAR Research Centers.

Join our Communities of Practice

Engage with a range of industry experts & actors to produce new ideas to solve current agriculture development problems.

Meet the 2017 Inspire Challenge Winners

The CGIAR Platform for Big Data in Agriculture awarded five research proposals US$100K each to develop their innovative pilot projects. The five winning teams have 12 months to implement small-scale proof of concept pilots to demonstrate viability. Follow their progress here!

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