README.md

metadata

title: Cars Knowledge Graph
emoji: 🚗
colorFrom: blue
colorTo: red
sdk: docker
pinned: false

Knowledge Representation Project: Cars Knowledge Graph

1. Introduction & Motivation

This project transforms a flat CSV dataset of Car Specifications (2025) into a semantic Knowledge Graph (RDF/OWL). Domain: Automotive Industry (Cars, Manufacturers, Engines, Performance). Motivation: To enable complex querying of car data that is not possible with simple tabular lookups, such as inferring "High Performance" vehicles or categorizing cars by complex criteria (e.g., specific engine types + price ranges).

2. Ontology Design (Conceptual Model)

The Ontology is designed using RDFLib and conforms to the project requirements (20+ Classes, 7+ Properties).

Core Classes

• Car: The central entity.
  • Subclasses: SportsCar, HyperCar, Sedan, Coupe, ElectricCar, PetrolCar, LuxuryCar.
• Manufacturer: Companies like Ferrari, Tesla, Bugatti.
• Component: Engine, V8Engine, V12Engine.
• defined Classes:
  • SuperCar: Cars with Top Speed > 300 km/h.

Properties

• Object Properties: hasManufacturer, hasEngine, usesFuel, manufactures.
• Datatype Properties: hasPriceValue, hasHorsePowerValue, hasSeatCount, hasTopSpeedKMH.

3. Knowledge Graph Construction

• Source: Cars Datasets 2025.csv
• Output: cars_knowledge_graph.ttl (Turtle Syntax)
• Triples Generated: ~9,842

4. Competency Questions & Validation

The following questions guided the design and were validated via SPARQL:

1. "List all cars manufactured by Ferrari"
   • Verified: Returns models like SF90 STRADALE, ROMA, 812 GTS.
2. "Which cars have > 800 HorsePower?"
   • Verified: Returns Bugatti Chiron, Tesla Roadster 2, etc.
3. "Count of 2-Seater Coupes"
   • Result: 147 vehicles.
4. "What is the average price of all cars?"
   • Result: ~$137,193 USD.

5. How to Run

Prerequisites

• Python 3.x
• Libraries: rdflib, pandas

Steps

1. Install Dependencies:

   pip install rdflib pandas
   

2. Generate Knowledge Graph:

   python src/ontology.py      # Generates Ontology Schema
   python src/convert_data.py  # Generates Graph from CSV
   

3. Run Validation Queries:

   python src/validate.py