Food Ontology and Semantic Web

Overview
Background
Key Concepts
Implementation
References
Notes

Overview

Food ontologies provide formal, machine-readable representations of food-related knowledge, enabling semantic interoperability between nutrition databases, recipe systems, dietary applications, and scientific research platforms. This research explores the landscape of food ontologies, their design patterns using OWL and RDF, integration with linked data ecosystems, and practical applications in nutrition informatics and food traceability systems.

Background

The food domain presents unique ontological challenges due to its inherent complexity: foods exist as biological entities, cultural artifacts, commercial products, and nutritional compositions simultaneously. Early efforts to standardize food data focused on hierarchical classification systems like USDA food codes, but these lacked the expressivity needed for modern applications requiring inference, cross-database mapping, and multilingual support.

The semantic web movement provided the technological foundation for food ontologies through RDF (Resource Description Framework), OWL (Web Ontology Language), and SPARQL query capabilities. Projects like FoodOn emerged from the need to unify disparate food vocabularies across agriculture, nutrition science, food safety, and consumer applications.

Key Concepts

Core Food Ontologies

FoodOn

The Food Ontology (FoodOn) provides a comprehensive vocabulary for food description:

@prefix foodon: <http://purl.obolibrary.org/obo/FOODON_> .
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .

foodon:00001002 a owl:Class ;
    rdfs:label "apple (whole, raw)" ;
    rdfs:subClassOf foodon:00001714 ;  # pome fruit
    foodon:has_food_substance_analog foodon:03301710 .

Open Food Facts

Community-driven product database with structured nutritional data:

Barcode-indexed products
Nutritional composition
Ingredients parsing
Nutri-Score calculations

USDA FoodData Central

Authoritative nutritional composition database:

Foundation Foods
SR Legacy
Branded Foods
Survey Foods (FNDDS)

Ontology Design Patterns

Food Product Hierarchy

@prefix : <http://example.org/food#> .
@prefix owl: <http://www.w3.org/2002/07/owl#> .
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .

:Food a owl:Class .

:PlantFood a owl:Class ;
    rdfs:subClassOf :Food .

:Fruit a owl:Class ;
    rdfs:subClassOf :PlantFood .

:Apple a owl:Class ;
    rdfs:subClassOf :Fruit ;
    :hasNutrient :Fiber, :VitaminC ;
    :typicalServingSize "182"^^xsd:decimal ;
    :servingUnit "gram" .

Nutritional Composition

:NutrientContent a owl:Class .

:AppleNutrition a :NutrientContent ;
    :food :Apple ;
    :nutrient :Calories ;
    :amount "95"^^xsd:decimal ;
    :unit "kcal" ;
    :per "182g serving" .

:Macronutrient a owl:Class .
:Micronutrient a owl:Class .

:Fiber a :Macronutrient ;
    rdfs:label "Dietary Fiber" ;
    :dailyValue "28"^^xsd:decimal ;
    :unit "gram" .

Recipe Modeling

:Recipe a owl:Class .

:ApplePie a :Recipe ;
    :hasIngredient [
        :food :Apple ;
        :quantity "6"^^xsd:integer ;
        :preparation "sliced"
    ] ;
    :hasIngredient [
        :food :Sugar ;
        :quantity "150"^^xsd:decimal ;
        :unit "gram"
    ] ;
    :cookingMethod :Baking ;
    :cookingTime "PT45M"^^xsd:duration .

Linked Data Integration

Food ontologies connect to broader knowledge graphs:

DBpedia: General encyclopedic knowledge
Wikidata: Structured Wikipedia data
schema.org: Web-scale structured data (Recipe, NutritionInformation)
AGROVOC: FAO agricultural vocabulary

Implementation

SPARQL Queries

# Find foods high in vitamin C
PREFIX food: <http://example.org/food#>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>

SELECT ?food ?vitaminC
WHERE {
  ?food a food:Food ;
        food:hasNutrientContent ?content .
  ?content food:nutrient food:VitaminC ;
           food:amount ?vitaminC .
  FILTER (?vitaminC > 50)
}
ORDER BY DESC(?vitaminC)

Schema.org Integration

{
  "@context": "https://schema.org",
  "@type": "Recipe",
  "name": "Apple Pie",
  "nutrition": {
    "@type": "NutritionInformation",
    "calories": "320 calories",
    "carbohydrateContent": "45 g",
    "fiberContent": "3 g"
  },
  "recipeIngredient": [
    "6 medium apples",
    "3/4 cup sugar"
  ]
}

Python Implementation with RDFLib

from rdflib import Graph, Namespace, Literal, URIRef
from rdflib.namespace import RDF, RDFS, XSD

FOOD = Namespace("http://example.org/food#")

g = Graph()
g.bind("food", FOOD)

# Add food item
apple = URIRef(FOOD.Apple)
g.add((apple, RDF.type, FOOD.Fruit))
g.add((apple, RDFS.label, Literal("Apple")))
g.add((apple, FOOD.calories, Literal(95, datatype=XSD.integer)))

# Query
for s, p, o in g.triples((None, FOOD.calories, None)):
    print(f"{s} has {o} calories")

References

FoodOn - Food Ontology
Open Food Facts
USDA FoodData Central
OWL 2 Web Ontology Language
Schema.org Recipe
OBO Foundry - Biomedical ontology standards

Notes

Food identity is context-dependent (biological vs. culinary vs. commercial)
Multilingual support is essential for global food vocabularies
Provenance and traceability require supply chain ontology integration
Allergen and dietary restriction modeling needs careful attention
Consider cultural and regional food naming variations
Integration with agricultural ontologies enables farm-to-fork tracking