• Media type: E-Article
  • Title: Data, Economics and Computational Agricultural Science
  • Contributor: Antle, John M.
  • Published: Wiley, 2019
  • Published in: American Journal of Agricultural Economics, 101 (2019) 2, Seite 365-382
  • Language: English
  • DOI: 10.1093/ajae/aay103
  • ISSN: 0002-9092; 1467-8276
  • Origination:
  • Footnote:
  • Description: <jats:title>Abstract</jats:title><jats:p>In this address I discuss the potential for the revolution in data infrastructure, data science and computation to support and accelerate the transformation towards a more productive, healthy and sustainable agricultural systems. A theme that emerges from both the agricultural systems science and economic‐behavioral sciences is that improved acquisition and use of data is a critical constraint on agricultural research and its successful application, both for on‐farm production system management and for technology and policy decision making. This in turn suggests potentially high returns to public investment in the data needed to enable computational agricultural science. I conclude with a prototype private‐public scheme for investment in the data needed to support advanced computational methods and models, and discuss the economic, technical, legal and institutional challenges to its implementation.</jats:p>