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Digital twins: our framework

Descriptive
Visual replica
3D geospatial model
Geolocated data
Multiple visualization options, including Cesium, Unreal Engine, and NVIDIA Omniverse
Informative
Broad source data integration
Ontology and GUID management
Attribute display
Document and multimedia integration
Performance and state visualization
Unified data search and discovery tools
Temporal data management and display
Interactive
Connect data using API microservices
Data modification at an asset level
Updates back to source
Augmented, virtual and mixed reality
Intelligent
AI for automated data acquisition and structuring
AI for data analytics
AI for patterns and warning
AI for automated contextualization of data
AI for federated data learrning
Predictive
Physics–based modeling
Real-time scenario planning
Predictive analysis
Recommended actions

First, identify your ideal twin

The framework allows you to confirm what kind of digital twin is fit for your individual purpose. One challenge may require an Interactive Twin, another a Descriptive Twin.

Despite Hollywood and media hype, most challenges will not require the development of a Predictive Twin. However, each twin category does require the preparatory work undertaken in the category to its left. For example, to create an Intelligent Twin, you first need to prepare to create an Interactive Twin.

Layer and learn over time

This framework encourages a smart start, building your ideal twin by layering data and learning over time. This iterative development creates stronger, more effective digital twins. Our platform user interface and our account license pricing are designed to encourage you take this journey.

Federate different categories

Any category of twin created on the Nextspace platform can be connected to—federated with—any other category of twin regardless of the platform used to create that independent twin.