Data sharing is essential for Global Crop Improvement Network to address crop challenges

“Combined with socioeconomic and cropping systems research, a Global Crop Improvement Network could revolutionize the ability to understand and model crop responses to environments globally and accelerate adoption of vital technologies,” write the article authors.

Addressing transnational crop challenges will require refinement of research infrastructure and better leverage of global expertise and technologies. Drawing on lessons learned from international collaboration in wheat, we outline how such a model could evolve into a Global Crop Improvement Network (GCIN) encompassing most staple food crops, providing access to well-controlled “field laboratories,” while harmonizing research practices and sharing data.

Recently established crosscutting CGIAR platforms, including one to harness big data and another for modernization of breeding methods within CGIAR centers, would also contribute to a GCIN’s goals.

Data integration

Crop models have been used to estimate impacts of climate change on crop performance, yet many breeding and agronomy data sets do not fulfill core needs to drive models. Research institutions and funding bodies could facilitate more timely data sharing by prioritizing publication of results linked to open-access data.

Data sharing will drive standardization toward more precise descriptions of environments and experimental treatments, and more “searchable” databases. Although intellectual property (IP) rights are necessary incentives for private investment, greater access to data benefits all sectors.

It would be mutually beneficial to carefully define “precompetitive” research so that private entities are encouraged to share nonsensitive data more routinely in precompetitive mode and when engaged in public-private partnerships (PPPs).

Some transforming technologies could be made more accessible through non-exclusive licenses while ensuring that industry received returns on investments.

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May 3, 2018

M. P. Reynolds et al.

This article’s original version is posted on Science.