Digital twins have revolutionised many industries, and their impact on construction can be even more significant if we take into perspective the long lifecycle of built assets. To be able to take full advantage of the data that is collected and stored in the project, product identification is a very important aspect to consider when developing the digital twin. In this article, we will take a look at the different approaches to product identification – standard-based identifiers, naming conventions and classification systems, and how their use can affect information management throughout the different project stages.
Data Templates and GUIDs
In recent years, the standardisation bodies CEN and ISO have published a set of standards that provide a framework for how digital data should be structured, created, and managed in order to ensure data quality and interoperability. These standards lay the foundation for a common digital language that can be used across the entire construction sector globally. Hence, being able to uniquely identify digital concepts is a key prerequisite, and this is where the so-called Global Unique Identifiers or GUIDs come into play.
What is a GUID?
Global Unique Identifiers (GUID) are language-independent elements that allow machines to operate with the same meaning of information regardless of the difference in semantics. GUIDs are the basis of the International Framework for Dictionaries (IFD – EN ISO 12006-3) which allows concepts to be referenced within a common framework. This framework is fundamental for creating a common digital language.
Now let’s take a look at how such a common digital language is implemented as part of the information exchange between actors.
In the construction industry there is a growing need to present information about physical assets (products, building elements and systems) in a digital manner. These physical assets are referred to as construction objects (e.g., window, wool insulation, structural timber). In a data dictionary developed according to IFD, these are unique dictionary items that are identified through GUID.
Figure 1: Creating a language-independent framework with GUIDs
To allow for interoperability through а language-independent framework, information relevant to a given physical asset (construction object) must be organised in a defined structure. The standard EN ISO 23387 provides this structure in the form of a Data Template.
The Data Template is a collection of properties, quantities, units, enumerated values, and documents relevant to a construction object in a specific context or relevant to a certain purpose. The Data Template, as well as each constituting element are respectively identified through their individual GUID. In other words, the GUIDs that are incorporated into the Data Template structure, ensure clear identification as to the type of construction object and its characteristics.
When a GUID is fetched from a Data Template, it presents the information requirements for a certain construction object thorough a list of machine-readable and expert-reviewed properties. This is how Data Templates enable an employer to set asset information requirements (AIR), a specifier to define value
ranges for specific product characteristics in a digital format, a contractor to compare and select products based on their performance, or a facility manager to identify replacement products. In other words, they enable free flow of digital product data and automation of processes.
Figure 2: Structure of a Data Template
Global Trade Item Number – GTIN
Another important component of this standardised approach to product identification is the Global Trade Item Number. GTIN is a globally used unique number that identifies trade items specific to a given manufacturer (source: www.gs1.com). The GTIN has been widely adopted across multiple industries, and, together with the rest of GS1s standards suite, has been integral part of global commerce.
Within the Data Template, a GTIN is stored as a property of the construction object and allows for reliable identification of the real-world product, be it in the manufacturer’s catalogue or in the built asset.
Naming conventions are another useful way to identify different objects within a digital model, and one of the main benefits is that such type of identification is easily interpreted by humans, i.e., the data is human-readable. Ensuring that each asset type and each individual asset can be uniquely identified is key to secure a good flow of information between the parties involved in the project.
Nevertheless, naming conventions provide either project or company-specific encryption. For example, the asset control panel located inside the telecom room #1 on the first floor, unit 2 of the building number 3 (03_1_02_100T1_T_ACP01) will have no relevance outside of a specific project. In an alternative project/ organisation the same asset may be identified as (B03_Fl1_UNIT02_Tel01_ACPI01). While a manufacturer could refer to it as ACP13455_01. Thus, interoperability outside of the project is hindered.
Figure 3: Naming Conventions vs Unique Identifiers
The GTIN defines a given construction object regardless of the project and facilitates reusability, see figure 3. The GUID and the Data Template on the other hand identify all asset information that can be required and specified and allow for effective mapping.
To create a global interconnected supply chain, there is a need for a global identification system. Such system consists of GUIDs for properties and asset information requirements, represented through the Data Template, and GTINs for products.
The image below illustrates further the differences between GUID, GTIN and Naming conventions, and highlights the benefits of a standardised approach to identification through a combination of GUID and GTIN as part of the logical data model.
Figure 4: Difference between GUID, GTIN and Naming conventions
Classification systems as means of identifying construction objects
Classification systems help us organise information and they are widely used in the construction sector for various purposes. Sometimes classification labels are also used as product identification. Although this approach is not quite as project specific as naming conventions, it still poses limitations to data interoperability because the use of classification systems is often limited to specific countries or regions. In fact, this is where the Data Template can be very useful because it serves as a tool for mapping different classification systems, thus ensuring the labelling systems are interlinked.
How is product identification relevant to the Digital twin?
Coming back to the topic of digital twins, let’s take a look at how Data Templates are used to develop the digital twin. Physical assets in a digital twin are presented by their geometric (3D) model, alphanumeric information, and relevant documentation, see figure 4. The geometrical data presents the assets visually, identifying clashes and facilitating the construction process. The alphanumeric properties of the physical asset are structured in a standardised manner through the format of a Data Template outlined above.
Figure 4: Digital Twins powered by data
This structured information model enables easy identification of construction objects and access to data about their properties. It also allows for the specification of requirements based on the relevant technical documents and construction standards, thus facilitating compliance with project requirements and regulatory procedures.
As standard-based product identification improves data interoperability, it also enables more efficient data management processes throughout all project phases. By developing an asset register based on a language-independent framework, products can be easily searched and compared or maintained and replaced during the long years of operation.
Figure 5: Bew-Richards BIM Maturity Model
Using Data Templates and the product identification components incorporated within their structure is also a step towards BIM Level 3 – from container (files & folders) to database-based information management (figure 5). It is an enabler for advanced analytics in the field of performance, energy efficiency and predictive maintenance.
Finally, the data interoperability, enabled through a global standard-based approach to identifying construction objects and their properties, is essential for further adoption of modern technologies, such as machine learning, internet of things, artificial intelligence, etc. And these technologies are the key to unlock the true potential of the Digital Twin.