Agri-Food Supply Chain Traceability Supported by a Formal Ontology: A Grain Elevator to Processor Use Case

Abstract

Abstract Traceability of food products to their sources is critical for quick responses to food emergencies. However, having the complete and consistent information needed to quickly investigate sources and identify affected material has proven difficult. Food trace-ability is challenging for a variety of reasons including diversity and heterogenicity of participants, complexity of the supply chain and its processes and lack of a common understanding of steps in a supply chain, and incompleteness of data, and unwillingness of actors to expose information of their internal operations. The objective of this work is to address the traceability challenge by developing a formal ontology that can provide a shared and common understanding of the traceability model across all stakeholders in a food supply chain. In previous research, an ontological approach was adopted to address the traceability problem in the context of a use case related to harvest to on-farm storage activities. This work extends the Supply Chain Traceability ontology by introducing additional critical tracking events including transform event, sampling event, observation event, custody change event, and ownership change event in the context of a scenario involving shipments of commodity grain from a primary grain elevator to a processor of grain such as a feed manufacturer. A knowledge graph is generated based on a simulated dataset and the ontology is validated through query, reasoning, and visualization conducted in the RDFox environment.