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Model-driven engineering city spaces via bidirectional model transformations
Ennio Visconti1, Christos Tsigkanos1, Zhenjiang Hu2
1Technische Universität Wien, Vienna, Austria.
Software and Systems Modeling
|December 20, 2021
Summary
This study introduces a method to enrich CityGML data with semantic information for urban cyber-physical systems. Bidirectional transformations ensure synchronized digital twins of cities for robust analysis.
Area of Science:
- Computer Science
- Urban Informatics
- Software Engineering
Background:
- Cyber-physical systems in urban environments require robust software engineering support.
- Current CityGML models lack semantic richness for advanced analysis.
- Bridging the gap between geometric city models and analyzable data is crucial.
Purpose of the Study:
- To develop a technique for deriving analyzable models from CityGML descriptions.
- To ensure consistent bidirectional synchronization between domain and analyzable models.
- To facilitate model-based development for urban digital twins.
Main Methods:
- Leveraging the theory of bidirectional transformations.
- Developing a formal programming technique and technical framework.
- Applying the method to real-world city models.
Main Results:
- Successfully derived analyzable models from CityGML data.
- Achieved automatic and coherent synchronization between domain and analyzable models.
- Demonstrated the practical feasibility of bidirectional transformations for urban data.
Conclusions:
- Bidirectional transformations provide a consistent and well-behaved approach for synchronizing urban models.
- The developed technique enables richer semantic analysis of urban cyber-physical systems.
- This work supports the creation and maintenance of accurate, synchronized digital twins of cities.
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