PURDUE University researchers are leading an effort to develop a nationwide, unified system for storing and making publicly available the abundance of research data that could help the agriculture industry and policy-makers.
Agronomy professor Sylvie Brouder and five other Purdue agricultural and library science faculty and staff members organized an Oct. 10-11 meeting in Potomac, Md., to identify concrete steps in developing an online system for open-access agricultural data.
The "Smarter Agriculture" workshop was held in the Washington, D.C., suburb in part to involve federal agencies, Purdue said. The Obama Administration has mandated that the direct results of federally funded scientific research be made available to the public digitally. That would promote greater and easier access to data that could be used to help drive innovative breakthroughs in areas such as health, energy, the environment, national security and agriculture.
The workshop attracted scientists, librarians, modelers, educators, publishers, leaders of professional societies and partners from the private sector. However, program managers of the U.S. Department of Agriculture's National Institute of Food & Agriculture, which provided a grant that funded the conference, were unable to attend because of the government shutdown.
"The workshop format was designed to brainstorm, identify and foster beneficial linkages toward the broad goal of developing a functional data infrastructure for agriculture," Brouder said. "We want to make research data useful to the agricultural community and policy-makers. This infrastructure is critically necessary."
Open access to agricultural data also could be used in education to help graduate students better interpret and present data, Brouder said.
There are many issues to resolve, such as determining ownership of the information and where it would be stored — with so much data to preserve, multiple sites most likely would be needed — and developing a "common language" for data.
Brouder noted that even a seemingly simple term such as "yield" would need a precise definition so the data could be analyzed correctly. For instance, she explained that farmers typically refer to corn yield with the grain having a 15.5% moisture content, while modelers predicting global yields perform their calculations presuming that the grain contains no moisture.
A statement is being composed on the challenges and opportunities from the perspectives of the workshop participants. It will help with the development of data infrastructure for the Purdue College of Agriculture's plant sciences initiative, announced in September, as well as ongoing initiatives nationwide.