WELCOME
The EU LDT Data Modeller is the tool that enables cities to design, structure, and operationalise data models for Local Digital Twins, bridging real-world data and simulation environments.
It provides a flexible and scalable environment to define schemas, connect to existing data sources, and generate synthetic datasets. By combining manual modelling, automated schema generation, and synthetic data capabilities, the tool ensures that data used across the EU LDT Toolbox is structured, interoperable, and simulation-ready.
THE CHALLENGE
Cities face increasing difficulties in preparing data for simulation and digital twin environments:
- Data sources are heterogeneous, unstructured, and not aligned with common models
- Existing databases are complex and difficult to reuse across systems
- Sensitive or missing data limits experimentation and testing
- Creating realistic datasets for simulations is time-consuming and resource-intensive
This makes it difficult to build reliable simulation models, to test scenarios before real-world implementation and ensure interoperability across tools and systems.
The challenge is not only to access data, but to structure it, standardise it, and generate reliable datasets that can power simulations and decision-making across the ecosystem.
HOW IT WORKS
The EU LDT Data Modeller acts as a data modelling and generation layer, transforming raw or existing data structures into interoperable schemas and synthetic datasets:
Create and manage structured data models by defining entities, attributes, and relationships. It supports full schema lifecycles (Draft, Validated, Published) to ensure data lineage and version control.
Connect to external SQL or NoSQL databases to automatically generate initial schema drafts through database introspection, reducing manual configuration time.
Ensure schemas are consistent and compliant with NGSI-LD and JSON Schema standards. Automated checks verify structural integrity and semantic interoperability.
Produce realistic, scalable datasets based on defined schemas. Users can control statistical distributions, correlations, and data volume while ensuring full reproducibility.
INTEGRATION WITHIN THE EU LDT TOOLBOX
The Data Modeller acts as the data modelling layer of the EU LDT Toolbox, ensuring that all tools operate on structured
and interoperable data models.
WHY IT MATTERS
The EU LDT Data Modeller enables cities to move from unstructured or unusable data to simulation-ready, interoperable datasets.
See how cities make better decisions.
KEY CAPABILITIES
Design, edit, and manage structured data models with full control over attributes, relationships, and constraints.
Automatically generate schemas by analysing external database structures.
Generate realistic datasets based on schemas for simulations, testing, and AI workflows.
Ensure data models are consistent, compliant, and stored for reuse across the ecosystem.
Export datasets in multiple formats or inject them directly into external systems and platforms.
Package and publish schemas and generators to the EU LDT Marketplace for reuse across cities.
WHO USES IT
LOOKING FOR DOCUMENTATION?
Access the right resources based on your role and what you need to achieve.
Are you a policy, strategy or innovation lead?
Understand how the EU LDT Toolbox supports strategic planning, policy design and impact measurement.
Explore key concepts, frameworks and real use cases to make informed decisions.
Are you part of a technical or implementation team?
Deploy, integrate and extend the Toolbox in your city environment.
Includes architecture, configuration guides, APIs and source code to support implementation.
New to the Toolbox? Start with the core concepts to understand how everything connects.
STANDARDS AND COMPLIANCE
The tool aligns with key European interoperability standards, providing capability for making what-if scenarios and predicting the impact of a decision on a specific problema. As MIM 2, MIM 7 and MIM 10.
JOIN OUR COMMUNITY
Connect with the EU LDT ecosystem and stay updated on releases, pilots and collaboration opportunities.