FOOD ONTOLOGY FOR ALLERGY DETECTION 

Project Description

This project involves the development of a food ontology specifically designed to detect allergens in four major food categories: meat, nuts, dairy, and gluten. Using the Web Ontology Language (OWL) and guided by the NeOn Methodology, the ontology will model relationships between food items, allergenic compounds, symptoms, and related dietary restrictions. The aim is to improve allergy detection, enable personalized dietary management, and support food labeling and healthcare applications. The project builds the ontology from scratch, integrating data from existing allergen databases and validating its structure through reasoning tools and expert input.