Interview: Greg and Keith Bentley discuss open source, 4D digital twins and more

Carla Jean Lauter 00:08
Hello, I’m Carla Lauter, and I am the editor of SPAR3D.com. I’m here at the Year in Infrastructure 2019. And I’m joined by Greg Bentley and Keith Bentley and we’re going to talk a little bit about digital twins and itwins today.

Carla Jean Lauter 00:19
How do you think that the ideas and the capability of digital twins has evolved over time?

Greg Bentley 00:25
Well, the capabilities that make a digital twin possible, you know, I think of them as as requiring sort of three characteristics. That digital context is one we’re going to come back to that and the significance of what SPAR 3d covers. But the digital twin needs to be explanatory. It needs to have veracity. We say digital components, you could say the work of infrastructure engineers, it’s been dark in the past, but if we can open it up and have that data be useful throughout the lifecycle, then that’s the second characteristic. Over that life cycle, of course, it’s digital, but it’s only a twin if it is synchronized to the changes that occur in infrastructure project and asset. That’s where the technologies Keith’s helped to guide us to event systems with the distributed hub and imodels and so forth are key. But they go back to it has to be reality. Reality is 3d. I like to say reality over time is 4D.

Greg Bentley 01:21
Not trying trying to rename it to SPAR 4D…

Carla Jean Lauter 01:24
…We could go to SPAR 4D, we could talk about it. [laughs]

Greg Bentley 01:26
When you talk about those technologies evolving, of course our ContextCapture was new a few years ago, that’s where we create the Reality Mesh and overlapping photographs. And at SPAR 3D of course, you’ve been covering laser scanning from the beginning. That’s now a hybrid part of the process where you need and can benefit from laser scans. But again, not to result in point cloud, but an engineering ready digital mesh that is the twin which the digital components can be embedded in their content and so forth.

Greg Bentley 01:59
But the acquisition, we announced here of Orbit GT to bring in and facilitate mobile mapping where, you know, I like to say surveying can be continuous. So I use the term 4D surveying to mean it can be done often with mobile mapping on vehicle mounted LIDAR and cameras and so forth. That really completes the circle when I say evolving for digital twins to have that digital context. And then we say have technologies also that are software technologies for the digital components and the digital chronologies.

Carla Jean Lauter 02:33
And you mentioned a minute ago some dark data, what do you mean by dark data?

Greg Bentley 02:38
Well, everything involved in infrastructure engineering is created with intelligent applications. engineers use our open modeling applications, open simulation agents or those of others. But the result is work deliverables, if you like that are in obscure technical files are inscrutable to analytics or visibility for that matter unless you have the software that creates it.

Greg Bentley 03:05
So we’ve gotten in the habit of assuming that engineering, that information that engineering information isn’t part of what we do with AI and machine learning and analytics generally. So we say, opening up that dark data, if it can describe itself, we can semantically align it, we can manage it, we can, we can make it relevant and useful over time, including analytics that look at things over 4D and so forth. Our reason for saying for 4D digital twins.

Carla Jean Lauter 03:38
So the much discussed McKinsey report and construction about the inefficiencies therein you know, it was eye opening for many about, you know, kind of the scope of that inefficiency and kind of where construction is lagging behind other industries. So, how do you envision that going digital and digital twins will really help to address that problem?

Greg Bentley 03:55
While it can really help to address that problem, and we look at you know, they say there’s a lot of technology investment going into construction. An awful lot of it is just about automating the 2D workflows that exist today and creating, you know, paper on screens and tablets and so forth.

Greg Bentley 04:16
That’s not fundamental. Fundamentally, construction is a 4D process. It’s about the occupancy of space and time and logistics and industrializing processes, with modules and so forth. That’s where the advancement will come in. Nothing less than a digital twin is needed to automate those things and make them work well.

Greg Bentley 04:38
Now constructors, know, they need that, they want that, but a gap is there on the process and people side and that’s the reason that we and Topcon formed a joint venture we’ve announced here called Digital Construction Works to provide services for digital integration, if you’d like. They are a digital accelerator and are putting themselves at the service of constructors and concessions and joint ventures and so forth on major projects to help bring together the technologies of hardware and positioning. The tech, the cloud services that can make a digital twin be persisted across the ecosystem of the construction project and across the project, digital twin so that we can focus on the people in process changes and invent new workflows that will demand and require the construction digital twins.

Carla Jean Lauter 05:39
So what do you see kind of beyond that as the construction industry is next steps like what what is the where is the going digital? Where are we at in the process of doing digital what needs to come next?

Greg Bentley 05:50
Well, sometimes you will hear that someday they’ll be robotics, you know, to the extent of automation, even robotics on construction sites, and you see the odd example of that, and so forth. The thing is with something we call “constructioneering” where you consider the engineering aspect of construction and engineering itself is construction-driven.

Greg Bentley 06:12
You can wind up for instance, in a heavy civil site. The first autonomous vehicles on the roadway are the machine controlled graders. But with a digital twin in a cloud service, they can be providing the “as operated” conditions, and then routinely re-survey and so forth.

Greg Bentley 06:32
In other words, we should think, in no lesser terms than automating things to that level of robotics. It’s already doable. We just need to increase the ambition.

Greg Bentley 06:41
And you’re right, therefore, it is necessary to increase the ambition on the construction side. But the fact that construction is fundamentally a 4D exercise gives me hope that when we focus on the for the aspect, we will make that happen.

Greg Bentley 06:41
We appreciate SPAR helping with that, you know, by all I’ve always thought of SPAR’s, constituencies and opportunities, sort of… you could say 3D… but I like to say existing conditions and conditions capture and that can be over a lifecycle that includes operations and maintenance of infrastructure, not only capital projects, and the importance of the construction stage is the work of the engineers in design is going to be lost if the 3D model and construction starts from scratch, because that’s how we do construction these days with 3D models. But if you don’t start with the BIM model and advance it to a digital twin than the intelligence work of the engineers can never be the digital DNA and operations that it can be with a digital twin approach.

Carla Jean Lauter 07:42
So I want to talk with Keith about some of the back end and how this is being accomplished. So for those who are not familiar, can you talk about what imodel’s role is in relation to a digital twin and kind of how that’s managed?

Keith Bentley 07:54
So Greg mentioned that a lot of the information that we create during the process of designing, turns out not to get used for anything other than its original purpose, therefore, refer to that as “dark” not that it isn’t valuable, it’s just not used.

Keith Bentley 08:11
The idea of an imodel is if we can take that information and transform it in certain regards, so that it can be understood later on, hold that data and put it in a form with that is accessible and is trusted, used for many other purposes. So imodel’s role is to be that container to bring you information that previously was only accessed through specific tools and make it generally accessible.

Carla Jean Lauter 08:40
Yeah, and I think, you know, having the right people have access to the right information is very key.

Keith Bentley 08:44
Yeah, and only if the data can be trusted. Right.

Carla Jean Lauter 08:47
Right.

Greg Bentley 08:49
The points we’re realizing here is once your data is no longer dark, you can see its quality, right?

Carla Jean Lauter 08:54
And maybe it’s not as good as you thought.

Greg Bentley 08:57
So improving the quality is also something machine learning can help with and so forth. We sort of showed that with our AssetWise twin services, the OpenUtilities example, in that case.

Carla Jean Lauter 09:08
And what was behind the decision to make like imodel.js open source? Who benefits from that?

Keith Bentley 09:13
Well, so the concept of digital twin was not conceived like that is not our idea. But the concept is generally recognized as being hugely valuable.

Keith Bentley 09:26
Nobody debates whether or not a digital twin is a good idea. So it’s how to make a digital twin. And when we talk to people about what they wish for in their digital twin, what we discover is everybody wants something different. Always there is requirements to connect a digital twin to other information systems.

Keith Bentley 09:43
So who’s going to be the vendor for the digital twin? No, I don’t think there’s going to be just one vendor for digital twins, so what sort of necessary is there be a platform upon which we can build interoperable tools that will connect information that belongs visible through digital twin to the consumers.

Keith Bentley 10:03
So we said, look, we’re gonna have to write a lot of that stuff as Bentley Systems, we have a pretty good idea of how we would like for it to work. But obviously, for it to be a platform, it has to be something that would work brought more broadly than that.

Keith Bentley 10:18
You know, the concern about open sourcing things is well, are we going to give our technology competitors? And yes, I think it’s possible and probable that some people will use our open source technology to beat Bentley Systems. But by and large, we just think that the industry needs a digital twin. The only way it’s going to happen is if a lot of people agree on sort of the basic premise of a digital twin and we have offered what we’ve done as a starting point.

Keith Bentley 10:18
So the idea of open source is validated. We use a lot of we consume a lot of open source stuff, we see a lot of value by being able to make contributions to open source projects so we said, let’s do do that with our stuff. And so the imodel, the technology that you use to access an imodel, visualize an imodel to create and synchronize data with an imodel. All of the source that we wrote to do that is now on GitHub. Anybody anywhere can use it, you can download it and modify it if you’d like. We kind of expect that people who will start with what we had and use it for other purposes.

Carla Jean Lauter 11:28
How does the imodel.js of connect people in various roles across a project?

Keith Bentley 11:33
Right. So, the basic premise of digital twin is it must be accessible anywhere by anybody, right. So, except that is why digital twin versus simply just a information dystem disconnected. You have to say well, you need to be able to make it so that it can run anywhere, right so that it can be used by different types of systems running on personal computers, on mobile devices.

Keith Bentley 12:05
And so what we’ve tried to do is make it so that you can use imodel.js and customize it so that it connects with systems created by other back end data sources in the user experience looks like a seamless, single view of a data point. But at this point, it really will be a collection of many data sources.

Carla Jean Lauter 12:30
And for those who haven’t worked with digital twins before, what’s the learning curve like?

Keith Bentley 12:34
Well, one of the one of the biggest learning curves just has to do with embracing the concept of a distributed world, you know, information isn’t stored, where it’s contained in a in a box, file on disk.

Keith Bentley 12:50
So those people who are used to writing software and interacting with systems where you have a local copy of something and then it’s disconnected.

Keith Bentley 12:58
A connected world takes a different approach a different mindset for learning. But it isn’t unique to the infrastructure ranks certainly not unique to the Bentley Systems. So what we’re discovering is a lot of the people that see our source code and use the tools that we’ve created, find it very natural, because it’s very similar to other systems.

Carla Jean Lauter 13:21
It’s more of a mindset shift?

Keith Bentley 13:22
So we’re hoping to minimize that learning curve. It’s not a trivial thing.

Greg Bentley 13:26
And Carla, you’re asking about a learning curve from a technical side to work with the open source environment and so forth. To work with digital twins, when they are a cloud service that is available with immersive visualization is the most intuitive thing there is it’s much more so intuitive. And I’d like to say it’s going to solve the data quality problem because when you can actually find engineering information, because you can navigate intuitively and immersively like with the HoloLens2 here and so forth, and other immersive technologies of which that’s just the beginning. Then It’ll be used, and it will be kept up to date.

Greg Bentley 14:02
It really is a terrific opportunity for 3D and 4D, where deliverables. We go back to surveying, I think surveying as a tremendous, but different future because surveying won’t be done for a particular purpose, rarely with specialized deliverables, it will be done continuously or I like to even pose the challenge can it be 4d, can there be 4D surveying?

Greg Bentley 14:29
The mobile mapping is an example it’s so easy to remap the city by driving it or the vehicle-mounted units will be on autonomous vehicles, of course, they’re already capturing that data, we’re on the trains and metros and so forth. And then the the learning curve to use that information. When it’s in the form of a digital twin, that is a Reality Mesh, and the 3D we actually experienced that’s why it’s a twin. There’s no learning curve at all. for that. We think it’s gone. To increase the demand for with that information again securely at the right time and right place.

Carla Jean Lauter 15:05
Absolutely. Well, I want to thank you both Keith and Greg for taking the time to talk to SPAR 3D today and looking forward to following everything that’s going on in future.

Carla Jean Lauter 15:13

Greg Bentley 15:13
SPAR 4D!