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Title: – a vision for increasing usability of sensor data in grassland agriculture

item REUTER, RYAN - Oklahoma State University
item Moffet, Corey
item MANNA, ALEJANDRO - Oklahoma State University

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 11/7/2017
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: A collection of software tools is actively being developed to improve access to and usefulness of data relevant to managing grassland agriculture. The tools are available at and are in continuous development. Modern R software packages (open-source; tidyverse, Shiny, RMarkdown, flexdashboard) and publicly available data (e.g., the University of Idaho’s Gridded Surface Meteorological [GridMET] data or the USDA-NRCS’s SSURGO soil data) have been used where possible to remove barriers to adoption related to licensing, costs, user interface, mobile formatting, etc. The common vision in these software tools is to eventually allow a user to identify the management unit they are interested in (i.e. a parcel of land, and/or a herd of animals) and have the software gather, analyze, and format available data that is relevant to that management unit. This approach stands in contrast to the apparent vision of many current data products in which the users are expected to realize what data is relevant to them, know where to go to find that data, and filter out irrelevant data. An example of our vision is our precipitation comparison tool in which a user simply clicks a map for a location (continental US) of interest, and the tool retrieves cumulative YTD precipitation for that location from the GridMET database. Further, the user can indicate the number of years they wish to compare the current precipitation to, and a publication-ready plot of that data is generated. A second example is the SmartFeed dashboard in which data from precision supplement feeders (SmartFeed Pro, C-Lock Inc., Rapid City, SD) is downloaded, summarized and formatted automatically to allow ready visualization of data from this high-throughput phenotyping equipment. These and similar tools will be continuously developed to explore models for making data available and useful to researchers and grassland agriculture managers.