A Cornell University Project Partners Researchers, Librarians and AI to Fight Hunger
Ceres2030, a global effort led by International Programs in the College of Agriculture and Life Sciences (IP-CALS), the International Food Policy Research Institute and the International Institute of Sustainable Development, is employing machine learning, librarian expertise and cutting-edge research analysis to use existing knowledge to help solve these and other challenges – all aimed at eliminating hunger by 2030.
“In this world of information overload, it’s important for researchers in all fields to understand that literature reviews that will inform decision-making must be performed in a methodical fashion,” said Kate Ghezzi-Kopel, health sciences and evidence synthesis librarian at Cornell University Library and a member of the climate-resilient crops team.
Librarians said the syntheses will evaluate how interventions that are successful in one geographic location will work elsewhere, too.
“Agriculture has geographic specificity – it isn’t the same all over the world or sometimes even 50 miles down the road,” said Mary Ochs ’79, director of Mann Library. “So you can’t just assume that one solution is going to work everywhere. But by pulling together all of the solutions through comprehensive systematic reviews, you can identify the approaches that have worked and consider whether they’re likely to work elsewhere.”
About Gary Price
Gary Price (firstname.lastname@example.org) is a librarian, writer, consultant, and frequent conference speaker based in the Washington D.C. metro area. He earned his MLIS degree from Wayne State University in Detroit. Price has won several awards including the SLA Innovations in Technology Award and Alumnus of the Year from the Wayne St. University Library and Information Science Program. From 2006-2009 he was Director of Online Information Services at Ask.com. Gary is also the co-founder of infoDJ an innovation research consultancy supporting corporate product and business model teams with just-in-time fact and insight finding.