Advancing U.S. Agricultural Competitiveness with Big Data and Agricultural Economic Market Information, Analysis, and Research
C-FARE recently released a report on 'Big Ag. Data' that examines Big Ag. Data's potential, challenges and opportunities, as well as future research questions and approaches for extension and outreach. See the executive summary of the paper here.View the full report here.
The report was released by a multidisciplinary team of economic and engineering scientists. Authors Keith Coble (Mississippi State University, Department of Agricultural Economics) and Terry Griffin (Kansas State University, Department of Agricultural Economics) released the document at the USDA National Institute of Food and Agriculture (NIFA) Data Science in Agriculture Summit (see @USDA_NIFA #NifaAg.Data). Report co-authors include: Mary Ahearn (retired USDA-ERS), Shannon Ferrell (Oklahoma State University, Department of Agricultural Economics), Jonathan McFadden (USDA-Economic Research Service), Steve Sonka (University of Illinois, Department of Agricultural and Consumer Economics), and John Fulton (Ohio State University, Department of Food Agricultural and Biological Engineering).
New data technology is radically changing the ag sector. Big Ag. Data permit the extraction and use of information to craft insights that were previously unobtainable. This data can be described in terms of volume, velocity, variety, and veracity. Many sources for this information are farmers or input suppliers, and private investment suggests widespread perception of data value. However, this data may be neither statistically valid nor high quality. In contrast, U.S. Department of Agriculture has a long history of collecting and disseminating data to equalize the information available to those in the ag sector. In future, greater complementarity of government and various Big Data sources is feasible with coordination across data sources and investments in data and related research.