Data sharing between digital twins – can we show this in a simple way?
Sarah Hayes, Strategic Engagement Lead for CReDo
It’s great to hear about our digital twin projects because they’re exciting and innovative. Our use cases are different and varied because there are so many problems that digital twins can help us solve. In a recent radio interview[1], Lord Deben, Chair of the Committee on Climate Change suggested that it should be legally required that every single government decision should be made with climate change and sustainability in mind and that each decision should be made quicker than it currently is. We, the DT Hub community, know that connected digital twins are part of the answer to this to enable quicker decisions taking account of more information so that every decision can be made with climate change and sustainability in mind, and it’s part of our duty to communicate this.
But it’s also part of our job to explain well what digital twins are and how we develop them, not just what they can do for us. When I sat and listened to other presentations at the Utility Week conference last May in Birmingham, I started to wonder how others might become confused by the variety of ways we choose to describe our digital twin projects. Each project has a different diagram to represent how the data is brought together, what the controls over the data are and what the governance looks like. If we had a common diagram to describe these areas we could start to properly compare and contrast our approaches and better understand where bespoke approaches trump a common approach and vice versa.
A group of data and digital twin experts have come together since the summer to talk about how our own projects tackle the thorny problems of data integration and access. How do we bring together data from different sources? Where do we put that data? And how do we ensure as much of it is as open as possible and data that needs to be secure stays so? We found that we use different names for the same things but after some discussion we can come to consensus on which names seem most appropriate. It’s not an exact science, but through discussion and working through examples together, we’re all making progress.
We developed the data architecture wheel (with thanks to the Virtual Energy System team at National Grid ESO for sharing the original basis for this diagram) to show how data can be shared. Organisations have digital twins of their assets and may want to share some of their data and almost certainly need data from outside their organisation. We have different ways to share this data. We can share data on a point-to-point basis as below; I email you my file. But that won’t scale as multiple parties send multiple emails to each other (much like today?).
Or we can develop a central database for open or shared data. We’ll need some access, security and quality protocols (the padlocks) to govern the database and we’ll need a way to agree that. And whilst central databases do have their place, one central database cannot become the national digital twin. And many databases will continue to silo our information, causing duplication, inefficiency and friction.
So we can develop a distributed data sharing architecture with agreed common access, security and quality protocols (the padlocks). This allows organisations to retain control over their data and who accesses it and its’ quality.
In reality we know, we’re going to get a bit of each, and can it be represented like this?
We want your feedback, so let us know! Of course, these diagrams will best come to life when presented in the context of real projects, and that’s why we’re presenting them in the context of CReDo and the Virtual Energy System. Stay tuned to the Gemini Call and the CReDo team will be talking more about the distributed architecture being developed on 21 February.
In order to ingest data into particular use cases or digital twin projects, it is necessary to use 1) a high level data structure or model and 2) a more bespoke data structure tailored to the use case. A foundational or top level ontology would lay the foundations for 1) and 2) as is the thinking behind the development of the Information Management Framework.
Without an agreed top level ontology at this stage in our journey, we can still make progress by sharing our common high level data structures at the industry level and sharing our bespoke data structures at the use case and project level (which can be copied and adopted for similar use cases.) But we just need to make sure we’re talking about the same thing and that we can share our learnings as we go.
Using the same diagrams to point out differences of approach can help. I’m talking through these diagrams at the Gemini call today and putting out a call to action to help us improve these diagrams and to join in our discussion. Can you use this diagram to represent your digital twin or data sharing project? It would be fantastic to see others using these diagrams to talk about their projects at the Gemini calls. And can we start to develop shared rules that will enable distributed architectures to work across industries? Join the Data sharing architectures network on the DT Hub and share your feedback Data sharing architectures – DT Hub Community (digitaltwinhub.co.uk). If you’d like to get more involved then please get in touch.
Sarah Hayes is the Strategic Engagement Lead for CReDo, author of Data for the public good.
sarah@digitaltwinnercouk.onmicrosoft.com
Join the Gemini Call Tuesdays at 10:30-11:00 Gemini Call – DT Hub Community (digitaltwinhub.co.uk)
[1] BBC Sounds – Rethink, Rethink Climate, Leadership
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