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"I Want to Teach About Digital Twins...so what do I do?"

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09-05-2023 10:40 AM
BrianBaldwin
Esri Regular Contributor
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At the Education Summit this year, @MichaelGould and I hosted a session titled ‘Demystifying Digital Twins’. The goal of the session was to discuss what digital twins are from a geospatial perspective, hear what the interests from the community have been, and to discuss the availability of resources for teaching about digital twins.

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Some of the hottest topics of conversation at the session were: “What the heck is a digital twin?”, “What makes it different from a model?”, “Does it include real-time data?”, “Is it just a buzzword?”

For some great articles that start to dive into this discussion/definition – please see:

From the ASU meeting listed above, the participants found little disagreement with the following definition:

A digital twin is a virtual representation of the real world, including physical objects, processes, relationships, and behaviors (Esri)

As was also the case at the ASU workshop, a big part of the discussion at the Education Summit was simply that a digital twin could be a lot of different things. A digital twin for Syracuse NY will differ a great deal from one for Singapore. The question for us was: For any city or location… what is the technology that students can learn about that supports the vision for building a digital twin?

The goal of this post is not to dive into the definition of a digital twin – but to help those that are interested in teaching about digital twins – understand where they can get started.

Not to replicate work that has already been done – here is a great summary of the technology that can be used to support various aspects of a digital twin:

The aim of the following resources is to provide a list of lessons, training, and labs. All of this content is broken down into a digital twin framework and linked to in the appropriate ‘bucket’.

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  • Data Capture: the creation of an accurate geospatial model or foundation
  • Integration: combining information from multiple data sources and sensor networks
  • Real time & Visualization: presenting information visually
  • Analysis & prediction: using traditional statistics, spatial statistics, and GeoAI to interrogate the data
  • Sharing & collaboration: building applications and tools to operationalize the resulting information

Data Capture

Integration

Real time & Visualization

Analysis & prediction

Sharing & collaboration

Conclusion

I am sure I missed a lot. If there are additional lessons or resources that you are using to teach about digital twins, please let us know! Please provide additional resources in the comments below.

About the Author
Brian works as a Lead Engineer at Esri to support customers in Education. Brian has worked as a lecturer in GIS, supported non-profits through his community planning work, and honestly just loves working with users to help solve their geospatial quandaries!