Teaching and Educational Methods

Developing R Shiny Web Applications for Extension Education

Matthew S. Elliott(a) and Lisa M. Elliott(a)
(a)South Dakota State University

JEL Codes: A22, A29, Q13
Keywords: Agribusiness, data analytics, extension, R Shiny, R Markdown, web applications

Publish Date: October 8, 2020
Volume 2, Issue 4

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Abstract

The agriculture sector has entered a new era wherein every stage of the supply chain involves gathering an increasing amount of data. Most of these data are generated in real-time and require rapid analysis that can support optimal decision making for agribusinesses to remain competitive. Consequently, extension audiences are demanding more sophisticated, rapid analysis to aid their decision making using the data they have at their disposal. This paper discusses using R Shiny web applications to meet the new demand.

About the Authors: Matthew S. Elliott is an Associate Professor in the Ness School of Management and Economics at South Dakota State University (Corresponding Author: matthew.elliott@sdstate.edu). Lisa M. Elliott is an Associate Professor in the Ness School of Management and Economics at South Dakota State University. Acknowledgements: We gratefully acknowledge the support of this project by the South Dakota Agricultural Experiment Station at South Dakota State University and by Hatch Project accession No. 1006890 and No. 1017800 from the USDA National Institute of Food and Agriculture. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture. This material is based upon work that is supported by the National Institute of Food and Agriculture, U.S. Department of Agriculture, Hatch project under 1017800 and No. 1006890.

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