The Glue for Digital Twins

This blog outlines how to use alphanumeric data as the glue for integrating geometry, geography, and performance information.

The Promise of Digital Twins
Digital Twins in infrastructure offer the potential to replicate the real (physical) world in data, opening up exceptional possibilities. However, these terms don’t point to a single unambiguous solution regarding technology but a combination of various concepts. A common element among these concepts is the use of a description (or information model) of the asset and its dynamic performance. The first concept is a relatively static representation of components, materials, shapes, and sizes, whereas the second concept encompasses a continuous stream of sensor signals, such as temperature, water usage, safety information, light absorption, and the battery level.

Different Data Formats and Protocols Hinder Consistency
The challenge lies in the fact that the data required to mimic the performance of assets is not uniform. Countless formats and protocols are used to express the different types of information involved. Consequently, different types of information are stored in separate databases, following their respective formats and protocols. Siloed and incoherent.

Geometrical shapes, for example, are expressed in numbers and coordinate systems. Geographical positioning is defined using specific coordinates on Earth. On the other hand, sensory data is described in countless ways, often intertwined with the hardware it originates from. Additionally, all sorts of information are described as alphanumeric data, like data from the manufacturer, information about inspecting parts, and characteristics like color and material.

It wasn’t a big issue for industrial automation experts as long as everyone used the same formats and protocols and interfaces presented diagrams. However, for Digital Twins, people expect greater integration with 3D systems, a wider range of automation cases, and different technologies like the use of The Internet for communication.

Figure 1. How the representation in geometry and geography is related to the alphanumeric. (1)

How Do We Tie It All Together?
The principle we follow is to utilize alphanumeric information as the backbone of all other information. Having a central identification and repository for alphanumeric data and a referencing technology called Linked Data, we strive for a more distributed way of working (see Figure 2). Using the Internet protocol, Linked Data allows us to refer to data in other databases elsewhere just as websites refer to each other. (2)

Figure 2. Using Linked Data in a distributed system of databases via the Internet.

This distributed setup still requires agreeing on standards for formats and protocol, but not all kinds of data need to be stored in the same format. For instance, the format in which data about an asset is stored is very different from the format in which signals are stored because both need to be stored in a way optimal for their nature (static versus dynamic).

“The only thing that connects information & provides continuity in our projects is people. Using Laces and Systematic Assurance centralizes our knowledge, enables better knowledge transfer, and avoids the risk of people taking critical project information with them if they leave a project” – Craig Dunningham, Design Manager and Digital Engineer (3)

The backbone describes information from its early inception until the end of the life of an asset, from the stakeholder requirements, up to the final design and from a design decision up to a manufacturer’s model. Such a backbone allows the project and its participants to enrich the asset information as time passes and information accumulates.

Figure 3. Digital Twin of a tunnel in Fundamend software (4)

Want to know more about distributed data? Reach out to James Harvey of Arcadis or Niels Kooiman of Semmtech.


  1. Harvey, J. (2023), Presentation for Transport for New South Wales, Arcadis
  2. Laces White Paper Distributed Data Management
  3. Harvey, J. (2022), Presentation on Model Based Systems Engineering, Arcadis
  4. Fundamend, (2023)