Data privacy has become a critical issue within the agriculture and food industry. The real-time conversion of data to information has been shown to be incredibly valuable to the industry but often requires sharing data with software, platforms, customers, and regulators outside the data owner's control. While much work in this area has focused on legal protections for data privacy, less has been devoted to technical architectures to support different sharing models. This paper defines some "tools in the toolbox" for designing such systems that are accessible to both technical and nontechnical audiences as well as several "sharing design patterns" using the Open Ag Data Alliance (OADA) framework. These tools and patterns are helpful in classifying and understanding both existing and future data flows in agriculture and their privacy implications.

No abstract

No abstract

No abstract

No abstract