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--- |
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title: Cars Knowledge Graph |
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emoji: 🚗 |
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colorFrom: blue |
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colorTo: red |
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sdk: docker |
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pinned: false |
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--- |
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# Knowledge Representation Project: Cars Knowledge Graph |
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## 1. Introduction & Motivation |
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This project transforms a flat CSV dataset of **Car Specifications (2025)** into a semantic **Knowledge Graph (RDF/OWL)**. |
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**Domain**: Automotive Industry (Cars, Manufacturers, Engines, Performance). |
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**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). |
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## 2. Ontology Design (Conceptual Model) |
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The Ontology is designed using **RDFLib** and conforms to the project requirements (20+ Classes, 7+ Properties). |
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### Core Classes |
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- **Car**: The central entity. |
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- **Subclasses**: `SportsCar`, `HyperCar`, `Sedan`, `Coupe`, `ElectricCar`, `PetrolCar`, `LuxuryCar`. |
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- **Manufacturer**: Companies like Ferrari, Tesla, Bugatti. |
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- **Component**: `Engine`, `V8Engine`, `V12Engine`. |
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- **defined Classes**: |
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- `SuperCar`: Cars with Top Speed > 300 km/h. |
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### Properties |
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- **Object Properties**: `hasManufacturer`, `hasEngine`, `usesFuel`, `manufactures`. |
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- **Datatype Properties**: `hasPriceValue`, `hasHorsePowerValue`, `hasSeatCount`, `hasTopSpeedKMH`. |
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## 3. Knowledge Graph Construction |
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- **Source**: `Cars Datasets 2025.csv` |
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- **Output**: `cars_knowledge_graph.ttl` (Turtle Syntax) |
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- **Triples Generated**: ~9,842 |
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## 4. Competency Questions & Validation |
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The following questions guided the design and were validated via SPARQL: |
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1. **"List all cars manufactured by Ferrari"** |
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- Verified: Returns models like `SF90 STRADALE`, `ROMA`, `812 GTS`. |
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2. **"Which cars have > 800 HorsePower?"** |
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- Verified: Returns `Bugatti Chiron`, `Tesla Roadster 2`, etc. |
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3. **"Count of 2-Seater Coupes"** |
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- Result: 147 vehicles. |
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4. **"What is the average price of all cars?"** |
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- Result: ~$137,193 USD. |
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## 5. How to Run |
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### Prerequisites |
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- Python 3.x |
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- Libraries: `rdflib`, `pandas` |
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### Steps |
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1. **Install Dependencies**: |
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```bash |
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pip install rdflib pandas |
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``` |
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2. **Generate Knowledge Graph**: |
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```bash |
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python src/ontology.py # Generates Ontology Schema |
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python src/convert_data.py # Generates Graph from CSV |
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``` |
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3. **Run Validation Queries**: |
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```bash |
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python src/validate.py |
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``` |
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