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This story features in Unearthed: The Age Of Data

We asked five experts “what do they see in their data crystal ball?”

Trevor O’Shannessy,
Principal Geotechnical Engineer, Golder Associates

Integration and compatibility
“We deal with a large amount of data that describes the ground and its engineering behaviour, both current and archival (e.g. borehole logs, lab testing, in-situ testing, proof loads, etc). In modern society there are increasing time constraints in distilling and processing ground data to a point where it provides a timely answer of useable output for our clients.

“In the next two to five years I’d like to think we’ll become increasingly smarter about storage and recall of archival data so it can be quickly acquired and integrated seamlessly with current project data collected and transferred electronically in the field.

“At the back end of this process is data portability and having the flexibility to ‘pump’ the models created in a package such as Leapfrog directly into other platforms. As an example, I often now tell people that the 3D model is not the software; it’s management of the ‘bucket’ of data. A software platform is just one specific tool with which to manipulate it.

“Some platforms are easier to work with than others and the model may pass through a number of software platforms and tools before it’s in a form that conveys the desired outcome. Examples of this are interpretation of the geological layer (geological model), or the way groundwater flows (hydrogeological model), or its relationship to ground support and predicted ground strain (geotechnical engineering model).

“I’d like to think the age-old problem of user and software incompatibility and how software packages speak to each other will finally disappear. I think the market is forcing this compatibility in order to make the transitioning of data smoother and faster, by competitiveness, and by project tools and technologies like BIM.”

Pat McLarin,
Product Manager, Civil and Environmental, Seequent

Community and collaboration “We have a fantastic and passionate user group willing to provide feedback on the problems they are trying to solve and the product features they want us to deliver. We are aiming to make it easier for our users to do that because better data on what they need and how they interact with our products enables us to create better solutions. Enabling a user community that can see what feedback others are providing and say ‘hey, I have that exact same problem’ provides a voice for the silent majority as to what is valuable, or painful, in our current workflows. That collaboration is incredibly important to us.

“My dream is that digital data can make civil projects go completely 3D. After all we live in 3D, we model in 3D, we design in 3D, we build in 3D. 2D plans and sections are really artefacts of the limitations we had in the past – an inability to handle 3D on a static piece of paper, or the lack of processing power required to handle calculations in three dimensions. So, a shift to where we do everything in 3D would be my vision.”

Graham Irvine,
Senior Engineering Geologist South Queensland, GHD

Virtual site visits “The common thread of compatibility between software tools is always there. The ability to export or import any number of file formats is important to create a smooth workflow. Limitations on compatibility of data between packages only reduces how fluid the exchange of data should be. I hope that we can move towards physical interaction with data to create a more immersive experience and understanding of the information we use. The ability to do a virtual site visit with multiple users interacting in real time with data and collaborating on solutions and ideas seems to be the next natural evolution of data utilisation.

“Also, the more I work with compiling archival data to build 3D representations of ground conditions in Leapfrog, the more I realise that the final model is only one part of the puzzle. Many of our projects have archival data from as far back as the 1940s. Clients typically have difficulties in compiling and understanding the relationships between all this old data and how it relates to new information. Having a 3D representation or library of existing information and being able to layer new data on top of it has proven indispensable. It provides a powerful way to easily digest the special relationships to data that may have been collected decades ago and compare it with a borehole drilled yesterday. “With this in mind, I wonder how data we capture today will be used decades from now?”

Jason McIntosh,
Product Owner, Seequent

Machine learning “There is a wealth of information out there that has been collected and produced for historic earth modelling projects. This data has often had humans applying their knowledge to it in order to extract meaningful outputs – but it can be hard and time consuming. As Craig Fenton suggests elsewhere, I would love it if machine learning could automate the more basic decisions that humans made for similar historic projects. Also if one day we could see the design and construction phases drawn closer together as a result of two-way data exchange.”

Ian Besford,
Projects Director, Mott MacDonald

Fresh interpretation “People are often heard referring to data as the new oil. The key difference is that data is reusable. Our ability to obtain, process and interpret data is increasing exponentially and we are continually identifying opportunities to digitise and interpret old data in different ways. This ability to reuse and add value from data we have that couldn’t have been anticipated at the time of capture is invaluable. It means we are able to work with our partners to identify opportunities to improve safety, reduce cost, manage risk and optimize our solutions more quickly and more cost-effectively than ever before. Within a five-year horizon this will shift from being the preserve of technical specialists towards being commonplace. Smarter data and smarter ways of processing it will democratize data analytics in the same way the PC did computing.”

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