Supporting Food Computing with Ontologies and Artificial Intelligence Methods for Sustainability
Abstract
This paper investigates the potential of combining food ontologies and AI in the food sector for enhanced sustainability. We argue that this combination can foster sustainable food systems, underscoring how semantic structures and AI can facilitate precision agriculture, sustainable food choices, personalized diets, and climate change mitigation. Our goal is to discuss how these innovative technologies can be harnessed to better understand, manage, and ultimately transform the food domain for a sustainable future. As a first step towards achieving this goal, we provide an overview of prominent food ontologies and knowledge graphs in the food domain highlighting their structures and focal points, and we illustrate the value of ontological reasoning through practical food domain examples, using SPARQL queries and ontological reasoning for insightful knowledge derivation. We also discuss how to combine AI and ontologies to create new knowledge resources for improved data integration and management.