https://github.com/joseruiz01/ontology
N-ary relationship and Ontology modeling by identifying and analyzing real-world scenarios
https://github.com/joseruiz01/ontology
Last synced: 2 months ago
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N-ary relationship and Ontology modeling by identifying and analyzing real-world scenarios
- Host: GitHub
- URL: https://github.com/joseruiz01/ontology
- Owner: JoseRuiz01
- Created: 2025-03-05T22:36:06.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2025-03-05T22:39:46.000Z (4 months ago)
- Last Synced: 2025-03-05T23:28:00.736Z (4 months ago)
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- Stars: 0
- Watchers: 1
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- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Part 1: Modeling N-ary Relationship Patterns
This project explores N-ary relationship modeling by identifying and analyzing real-world scenarios that require N-ary relations. The focus areas include urban planning, building construction, and language teaching, where complex interactions between multiple entities must be captured accurately.
### Urban Planning
#### 1. Public Transportation System Design
- **Example:** Spain's Madrid-Levante high-speed rail line connecting Madrid with Valencia, Alicante, and Murcia.
- **Classification:** Transportation System Development Pattern
- **Key Entities:** Country, rail line, cities, regions
- **Modeling Purpose:** Captures how the infrastructure enhances regional connectivity.
### Building Construction
#### 2. Stadium Renovation
- **Example:** Renovation of Santiago Bernabéu Stadium in Madrid, incorporating a retractable roof and 360-degree scoreboard.
- **Classification:** Renovation Pattern
- **Key Entities:** Stadium, new features, events
- **Modeling Purpose:** Demonstrates how renovations influence the usability of the structure for different types of events.
#### 3. Museum Construction
- **Example:** The Guggenheim Museum in Bilbao, designed by Frank Gehry, boosting tourism and cultural value.
- **Classification:** Cultural Construction Pattern
- **Key Entities:** Architect, museum, exhibitions, tourism
- **Modeling Purpose:** Highlights the interconnection between architecture, cultural exhibitions, and urban impact.
### Language Teaching
#### 4. Language Proficiency Testing
- **Example:** TOEFL exam evaluating listening, speaking, reading, and writing skills.
- **Classification:** Language Assessment Pattern
- **Key Entities:** Test sections, scores, overall proficiency
- **Modeling Purpose:** Demonstrates how different test components contribute to an individual’s language proficiency level.
# Part 2: Urban Planning Ontology
To better represent knowledge structures in urban planning, an ontology was developed using various knowledge sources and established ontological standards.
### Knowledge Sources
Key Wikipedia pages were used for reference, including:
- Urban Planning
- Sustainable City
- Transit-oriented Development
- Mixed-use Development
### Ontology Reuse Strategy
The project integrates:
- **SOSA/SSN Ontology:** For representing organizational structures and urban monitoring.
- **GeoSPARQL:** For spatial data representation and GIS system integration.
- **Time Ontology:** For modeling temporal aspects in urban planning.
### Design and Implementation
- **Core Principles:** Modular structure with zones, facilities, and regulations for maintainability and extensibility.
- **Class Hierarchy:** Abstract, domain-specific, and implementation-level classes for detailed categorization.
- **Property Design:** Object and data properties capture relationships such as connectivity, temporal aspects, and administrative dependencies.
- **Environmental Considerations:** Integrated tracking for sustainability and impact assessments.
### Integration and Future Extensibility
- **External Compatibility:** Supports GIS integration, urban planning software, and municipal databases.
- **Scalability:** Designed to handle complex queries and large datasets with efficient property chains.
- **Future Enhancements:** Expansion to smart city concepts, additional sustainability metrics, and accessibility measures.