What is a Data Template (DT)?
Advancing the construction industry through standards
In this article, you will find the most important information about the data templates and how they are developed.
Every construction organisation has its own way of structuring data. And this is perfectly fine. But to make it possible to communicate and exchange information with other organisations and systems in a reliable way, a common ground is needed. An agreed approach to structuring and transforming data into an interoperable asset should be implemented across the construction industry. This will enable organisations of all sizes to bring forward their digitisation initiatives and benefit from the numerous technologies available on the market today. More importantly, a common approach to developing data models in construction facilitates data exchange and accelerates the digital transformation of the whole industry.
To address this need, the data template methodology was created and is further developed by standardisation bodies, such as CEN and ISO, to provide the industry with a guideline on common rules and best practices for structuring data for digital use.
Following international standards to define and structure product information in common data templates is paramount to achieving a higher degree of digitalisation across the entire industry.
The data template methodology: International and national standards are among the credible sources that help to define and structure construction product information in common data templates that facilitate digitalisation in the construction world.
Data templates: What are they for people and for machines?
For its user, a data template (DT) is a common data structure describing the characteristics (called ‘properties’) of a construction object, its performance and its physical qualities, according to a credible source of information – be it a standard or regulation.
On the other hand, for any software, the data template structure is a set of concepts that are connected to each other through different relationships. By establishing these connections between concepts through unique pieces of code, a specific logic for machines is set. This allows us to create a common technological language, which helps any software convey meaning consistently regardless of the language used in a particular country.
There are several technical terms that we need to explain further when we talk about the methodology behind data templates. Those are construction objects, properties, attributes and groups of properties.
What is a construction object?
One of the major, and mandatory, prerequisites to define and create a data template is to have a construction object which to associate the data template with.
The construction object identifies the object of interest in a construction process which the data template describes further. This could be a window, exterior door, expanded polystyrene (EPS) insulation, masonry wall and many more.
What is a property, attribute and groups of properties?
One can think of a product property as the smallest building block defining a product for digital use.
Properties are characteristics that describe a construction object. In order to create a property, it is a must to define its attributes. Attributes can be the property’s ‘measure’, ‘value’, ‘unit’, etc. These are the property’s “metadata” that define what physical quantity the property measures and the unit it is expressed in.
Defining unique properties with different attributes is a very important step that enables software to compare values. For instance, to compare the percentage of water absorption of two products.
Last but not least, groups of properties are simply collections that allow users to group properties based on a certain criterion and then easily re-use and re-distribute them.
How do data templates ensure interoperability and transform data into ‘machine-readable’ language?
In different countries and within different organisations the product characteristics (or properties) do not share the same name, spelling or abbreviation. Thus, this information is deemed different by various software programs. The data template methodology takes into account all these differences.
To help machines understand the intended meaning of information there is a need for a common framework of concepts and the relationships between those concepts.
Names and concepts: Machines cannot compare the values if they cannot link it to the same concept
Data templates are built upon a framework, called ‘digital data dictionaries’, that enables the mapping of similar concepts to unique codes so that machines will be able to “read” and “understand” one common meaning, no matter the local differences in semantics. This way, all devices will “know” that “thermal transmittance” for example, is the same as “u-value”.
There is no universal data dictionary available in the construction world. There are many different dictionaries that construction organisations create themselves. However, those dictionaries need to be interconnected. The experts of CEN/TC442/WG4 are aligning the available standards to ensure that any dictionary can store properties and their attributes in a consistent way.
- The process creates a rigorous system of validation of all digital
contents and defines how properties and attributes shall be
established by users and experts in a data dictionary, as well as how
this content shall be mapped to other data dictionaries.
- The objective is to allow quality information exchange between
industry players for multiple uses such as the digital model, also for
international trade and the needs for maintenance.
Standards: The credible sources of data
When we speak about data templates, it is important to say that credible sources of product characteristics (or properties) are international standards, European standards (such as the harmonised standards), regulations, directives, documents and more.
It is also important to underline that there is a specific hierarchy of those credible data sources taken into account in the data template structure. Legal data sources, such as European Harmonised Standards are with greater priority than national standards, and the national standards have greater priority than and user-recognised requirements, like BREEAM and COBie.
This is how Data Templates are created to serve as a common framework to use when managing construction product data.
Credible sources of product characteristics are international standards, European standards, regulations, directives, documents and more. Data templates serve as a common framework to use when managing construction product data.
What standards define the methodology for creating DTs?
The international Standartisation bodies CEN and ISO have published a series of standards to cover the methodology for creating data templates. These standards are developed as part of the CEN technical committee 442 work and were published in 2020:
- EN ISO 23386 Building information modelling and other digital processes used in construction — Methodology to describe, author and maintain properties in interconnected data dictionaries – This standard describes the rules for defining and a methodology for authoring and maintaining the content of a data dictionary. Practically, this adds up to a common governance process for all users, responsible for developing a common data language. Every new entry in a data dictionary is held up to the same scrutiny, all of them are equally well described. That happens by referencing actual relevant sources (ideally standards and regulations) and approval by domain experts, so that the content of the dictionary reflects the actual language used on projects. This framework is very important to ensure interconnectivity between the different data dictionaries in the construction sector, thus enabling one common language for the entire industry.
- EN ISO 23387 Building information modelling (BIM) — Data templates for construction objects used in the life cycle of built assets — Concepts and principles – This is the document that enables the common structuring of data for construction sector through the so-called data templates. The data templates are structured representation of construction objects and their features. It leverages both above standards to provide data structures, based on the common language from a data dictionary, subjected to a rigorous governance process according to EN ISO 23386. That makes data templates digital human-understandable, machine-readable, interoperable representations of the very standards and regulations they were derived from.
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What is a data sheet?
When a manufacturer completes a data template the created output is called a Data Sheet (DS). A Data Sheet summarises the performance and the technical characteristics of a specific product, material or component according to a specific regulation or market requirement that has been incorporated into the Data Template.
In other words, a DS is like a product’s passport – it is traceable to the manufacturer and unique for the construction product. Data Sheets allow all actors that participate in a construction process to benefit from trusted, accurate, up-to-date manufacturers’ data.
Moreover, manufacturers can integrate the repository that stores their digital product information with their PIM, DAM or ERP systems. This way they can ensure that the data held in the Data Sheets is always up-to-date. These Data Sheets can serve as a single source of truth (SSoT) and the information that they contain can be automatically updated into any third-party systems.
Data Sheets can be populated with construction product data by other actors besides the manufacturer. Such DSs are often referred to as ‘project-specific’, because their author can verify the accuracy of the data held in the DS at the specific point in time when the Data Sheet is created.
What are the DTs used for and what benefits do they bring?
After having described what the Data Template methodology is, we will have a look at the advantages that it brings and how structured data can lead construction to the next level of digitalisation.
Essentially, the purpose of data templates is to make sure that product data requesters (e.g. asset owners, architects, specifiers, contractors, facility managers) and product data providers (manufacturers, distributors) exchange products information based on the same structures and using the same digital language.
Any actor involved in the construction project can use DTs to set data requirements, populate them with actual data and verify input data against requirements. The implementation of Data Templates is the missing puzzle piece that connects Manufacturers’ product information to Clients’ requirements and needs.
Apart from making the exchange of product information a much more efficient process, data templates also serve as a link to smart technologies that the construction industry can leverage.
Only after building a stable backbone of digital data through data templates, we will be able to create and benefit from digital representations of physical assets (Digital twins), maintain a network of internet-enabled devices (Internet of Things), enable them to learn from external stimuli (Artificial Intelligence), and even to evolve to a common digital marketplace within the construction industry.
How is a DT useful to manufacturers?
Data Templates are especially useful for manufacturers who can populate them with the most up-to-date and accurate information about the products, materials, systems and components that they produce. Among the most important benefits of the DTs for manufacturers are:
- Better quality of the data: A single source of information for all departments and subsidiaries, no more guesswork in tendering, clients gain trust in data that they can access on the fly.
- Adaptability to emerging business models: By applying the latest standards for structuring data, manufacturers ensure that their high-quality data can enter any existing or emerging digital channel.
- Cost savings now – By introducing Data Templates, the average manufacturer can substantially reduce data management costs by minimising data entry and manual maintenance of various internal and external databases.
What can DTs do for Clients and Building Owners?
The client’s main goals are to bring his project and program to success, to stay compliant with regulations, to operate effectively and, finally, to grow. To achieve this, he needs to ensure co-operation and co-ordination with other stakeholders. Among the benefits that the standard-based DTs bring for Clients are:
- The smart way to achieve project objectives: Improved management of Information Requirements and enhanced decision-making on costs, performance, environmental impact, etc.
- Automated information exchange and delivery to all stakeholders in the supply chain
- High–quality data across the whole life cycle: predictive maintenance, integration with FM systems, access to historical data – all possible with structured data.
What benefits do DTs bring to Contractors?
The contractor can benefit from the same opportunities as the client in terms of efficiency and increased competitiveness in the bidding process. As the contractor has many responsibilities regarding the safety of incorporated materials and works, as well as compliance with requirements, the automated validation and verification of data for the constructed asset are crucial. Some of the benefits include:
- Improve collaboration with all stakeholders by implementing a common digital language.
- Minimising the risk of errors by verifying that requirements and regulations are met by the whole supply chain.
- Reduce project costs and take advantage of eruptive digital transformation (LCA, cost estimation, digital twins, historical analysis).
How can DTs help the Design Team?
Construction is a complex process. As part of the iterative specification process, multiple actors need to provide different data describing the performance of various construction products or elements to be installed. This is done at different project stages and at different levels of information. Here are some of the benefits of working with well-structured, standardised information are:
- Easily identify the product data needed in all phases of the information value chain.
- Improve collaboration and reduce the risk of errors through clearly defined information requirements per role, stage, purpose and level of information.
- Create/reuse specifications, based on best practices and search for matching products.