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Abstract. Digital agriculture technologies have become integrated, to some extent, in almost every type of agricultural operation. These technologies offer innovative solutions that allow producers to solve many of the problems in modern agriculture. The value provided by adoption of these technologies, and the resulting data, can potentially provide short and long-term benefits to farmers. However, often this value is unclear, leading to hesitation in the initiation and/or advancement of farmer‘s investment in digital agriculture technologies. Proper technology selection and implementation varies by farm, level of technological aptitude, and available investment opportunities. In this project, various commercially available technologies were used to document data for a single field, and specifically for a single corn plant. This was done to understand the type and total amount of data being collected; a total of 18.5 Gb of data was collected from 2,476 individual files. These files were then categorized and ranked according to ease of adoption, added value, amount of generated data, and various other categories. Key data layers for the 2017 growing season were found to be as-planted, yield, imagery, seeding prescriptions, and weather data. Post-harvest analyses provided a means to separate data layers or files that provided direct value to the farmer. While impractical in commercial application, this platform served as a means to encourage adoption of these technologies and a determination of the many ways that data can be collected, analyzed, and acted upon in the current state of digital agriculture.