Adding data to your iTwin

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Why add data to an iTwin?

The infrastructure industry is increasingly adopting digital twins, or as they are called in Bentley’s platform, iTwins. Traditionally, infrastructure projects have involved the use of multiple formats, documents, images, and other data types to collectively represent an asset. This data distribution has caused significant industry challenges and has limited the possibilities of cloud integration. The cloud world has the advantage of organizing this dissimilar data into discrete repositories that can be associated to a project. That’s what the iTwin does, it brings together these data repositories into a single cloud connected entity.

In order to accomplish this, the iTwin Platform connects to cloud repositories through APIs and services. These include APIs for integrating design data, reality data, maps, documents, and other miscellaneous files. The platform also offers an open source library called iTwin.js for developing applications that leverage iTwins. These applications can connect iTwins to IoT sensors, machine learning analytics, and other cloud repositories. This enables the enrichment of infrastructure data beyond traditional desktop limitations.

Diagram 1 − The iTwin Platform uses APIs and services to integrate infrastructure data into a single view of truth.

What data types does the iTwin support?

The iTwin supports many key data types involved in infrastructure. These include:

Design data

Design data is data that comes from traditional CAD applications such as MicroStation, Aveva, AutoCAD, etc. The iTwin Platform supports numerous desktop applications across domains including railways, buildings, roadways, plants, and much more. For a full list of supported applications, see supported formats.

How does the iTwin unify these formats? As mentioned, the iTwin is composed of several data repositories. One such repository is the iModel. The iModel unifies design formats into a common cloud format for collective visualization. This process, of unifying design formats, is called synchronization. Synchronization enables project teams to keep their design files synchronized with the iTwin, ensuring the project digital twin stays up-to-date.

Example 1 - A .dgn file from MicroStation and a .rvt file from Revit synchronized into the same iModel of an iTwin.

Reality data

Another key infrastructure data type is reality data. This is data generated from iTwin Capture by taking imagery of real world objects, which is then converted to 3D meshes or point clouds. The resulting reality data can then be added to a repository for iTwin visualization.

Example 2 − A reality model of the Bentley Systems headquarters visualized within an iTwin.

The iTwin can also provide a holistic representation of an asset by combining design, map, and reality data in the same view.

Example 3 − An iTwin containing design data of a wind farm and reality data of a nearby town, presented on a map.

Additional data

In addition to visual data, projects may include files such as PDFs, images, and documents. To manage important project documents, the iTwin features a dedicated storage that serves as a common file repository for all team members.

Once all project data is consolidated in one place, an iTwin can be further enriched with additional cloud repositories. These include sensor data, enterprise data, machine learning analysis, and any other repository that enhances the asset’s digital twin. Whether they are internal iTwin Platform repositories or external ones, such as maps, the platform is flexible enough to incorporate both.

Geospatial Data

GIS, Maps, Terrains, TINs

Schedule Data

4D Schedule integrated with models

Geotechnical Data

Soil boring logs, Foundations, Compliance

Sensor Data

IOT, IIOT, Other Time Series

Enterprise Data

APM, ERP, EAM, ALIM

Your Data

Open & extensible data sources integration

Expanding your iTwin

As mentioned, the iTwin Platform also offers an open-source library called iTwin.js for developing iTwin applications. This enables deep integration of external repositories with iTwins and supports a wide range of digital twin use cases, making it a versatile tool for addressing industry problems.

Example 4 − An iTwin of a roadway that uses IoT sensors to keep track of the asset’s health.

Example 5 − An iTwin of an office that connects to an HR database for smart seat assignment.

Example 6 – An iTwin of a windfarm (from example 3) connected to time series, ML, and IoT endpoints to track past, present, and future energy production.

These additional repositories may seem cumbersome to manage, especially when referencing them from application code. For this, the iTwin comes with a repositories API to keep a central list of repositories associated with a project. This makes it easy to change repository URIs without causing data distruptions to workflows.

In this manner, the iTwin Platform provides a robust foundation for cloud integration and empowers users to solve infrastructure use cases in innovate ways.