Managing Global Resources for a Secure Future

2017 Annual Meeting | Oct. 22-25 | Tampa, FL

241-1 The Ggp Package: Tools for the Retrieval / Visualization / Analysis / Mining of Syngenta's Good Growth Plan Data.

See more from this Division: ASA Section: Global Agronomy
See more from this Session: Global Agronomy General Oral

Tuesday, October 24, 2017: 1:05 PM
Marriott Tampa Waterside, Room 4

Paul Kowalczyk, Syngenta, Research Triangle Park, NC, Hannah Wickenden, Data Collaborations, Syngenta, Berkshire GR42 6EY, United Kingdom, Marcin Skorupka, Data Science Service, Syngenta, Stein, Switzerland, Graham Mullier, Data Science Service, Syngenta, Berkshire RG42 6EY, United Kingdom and Elisabeth Fischer, Public Policy and Sustainability, Syngenta, Greensboro, NC
Abstract:
Syngenta’s Good Growth Plan (http://www4.syngenta.com/what-we-do/the-good-growth-plan) is a company mission to improve the sustainability of agriculture through six commitments: make crops more efficient; rescue more farmland; help biodiversity flourish; empower smallholders; help people stay safe; and look after every worker. Working with growers, governments, NGOs and others, Syngenta has collected data over the past three years (2014-2016) to track progress associated with each of these challenges. The data is independently verified, and is published using various Creative Commons licenses. We introduce the GGP R package, a collection of tools allowing one to query, download, visualize, analyze, and mine these data in an automated and reproducible manner. The GGP package is designed to allow researchers the opportunity to access Syngenta’s Good Growth Plan data in a format prepared for exploration. Demonstrations of workflows (e.g., exploratory data analysis, year-over-year comparisons, site-by-site comparisons) will be presented. The GGP package is a contribution to the open source ecosystem dedicated to reproducible research in computational agronomic science.

See more from this Division: ASA Section: Global Agronomy
See more from this Session: Global Agronomy General Oral

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