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Data Carpentry for Agriculture: Computer Science Basics for Illinois Farmers, Agronomists, and CCAs

Project Team

  • Dr. Lindsay Clark, Research Specialist, Dept. of Crop Sciences
  • Dena Strong, Senior Information Design Specialist, CITES & Technology Services
  • Dr. Carolyn Butts-Wilmsmeyer, Research Assistant Professor, Dept. of Crop Sciences
  • Dr. Neal Davis, Teaching Assistant Professor, Dept. of Computer Science

Abstract

Now more than ever, agriculture is an intensely data-rich and data-dependent business, with dozens of variables of information behind every crop. But many farmers, agronomists, and certified crop advisors (CCAs) haven’t had the opportunity to learn the types of data science that can support and enhance their work; all-hands-needed busy seasons make traditional semester-long classes difficult and expensive, and many institutions require minimal exposure to “big data” analyses as part of their agriculture curriculum requirements.

Software and Data Carpentry are internationally-collaborative, open-source educational workshops developed to provide “just enough computer science” to people whose primary field of interest is something else—biology, genomics, ecology, and more. With the support of local infrastructure, the Software Carpentry team at the University of Illinois can offer two full days of training at a cost of $40 per student: affordable, time-efficient, and focused on the students’ specific field of interest.

With a grant from the Center for Digital Agriculture, researchers at ACES and certified Software Carpentry instructors could develop a branch of Data Carpentry specifically designed to serve the needs of rural agronomists, CCAs, and farmers who need “just enough” computer science to be of particular benefit to them, without the commitment of semester-long coursework and hundreds or thousands of dollars in expenses. We could contribute to an international body of knowledge and make these lessons available to production agriculturists and scientists around the world.

We can also research the most effective method of delivery and analyze the costs and benefits between in-person training and online training of the same subject: Will participants find the convenience of remote lessons outweigh the interpersonal benefits of sharing the same classroom? Will the network infrastructure that reaches rural areas support streaming video lessons adequately? Or would in-person workshops allow more focus on the lesson with fewer distractions from technical difficulties?

By teaching basic computer science and data analysis concepts that are specifically relevant to agriculture, we can enable agronomists, CCAs, and farmers to better understand the data they collect, to analyze these data independently, and to mine their data for additional results leading to an increased understanding of the physical ecosystem of their or their client’s farm.