Managing data models: Excel and beyond

Modified on June 3, 2020

Digital transformation is all about data, and construction is finally set to take a huge leap forward in its digital journey. The two standards developed by CEN/TC 442 – EN ISO 23386 and FprEN ISO 23387 (to be published in a few months) – provide the industry with the much-needed framework for managing data through properties and data templates**. Yet, there is another important consideration that many actors are facing at the moment – how to go about it? What is the most efficient way for managing properties and data templates? Let’s take a look and compare the two main options available – the good old Excel vs. tools specifically designed to facilitate the implementation of the above-mentioned standards, such as Cobuilder Define.

Excel is a very convenient format. In fact, at Cobuilder we often rely on it to perform our Consultancy services – exchanging information with clients, be it to communicate needs for implementing data requirements on projects or to help us map data between the clients’ systems and our platform. But how useful is it when it comes to managing your data models?

Properties and data templates

The newly published standard EN ISO 23386 introduces the term ‘property’ – although not as in real estate. A product property is a characteristic that defines a product for digital use, and EN ISO 23386 describes how these properties should be managed to ensure fully machine-readable and connected information exchange. The upcoming FprEN ISO 23387 builds further upon this concept by defining the data structure, called data template, that allows properties to be grouped into meaningful sets of information to meet specific needs.

digital twin

Managing properties within data templates

The property is the essential building block to describe a product for digital use. This is why, it contains some very important metadata. To ensure machine-readability and quality of the data exchange, each property is defined by a set of attributes, such as commonly agreed naming and definition, translations and connections to other concept types such as ‘unit’, ‘value’, and many more. While creating the standard-based contents of a data template in Excel is possible, the creation of properties might prove to be quite a challenge.

While creating the standard-based contents of a data template in Excel is possible, the creation of properties might prove to be quite a challenge.

Fundamentally, the structure of Excel is quite simple. This is what makes it so versatile. However, trying to introduce complexity to the data structure would require a significant effort, first to develop and later to maintain. This is why, creating data templates in an Excel spreadsheet, with the necessary web of links and attributes that define each property, might be a difficult task to accomplish. Regardless of the effort spent in developing a sophisticated solution in Excel, it will not be a very user-friendly one.

A solution specifically developed for managing properties and data templates, such as Cobuilder Define, provides an easy to navigate authoring process and enables the users to create a digital dictionary of data concepts (template, group of properties, property) to define construction objects.

In addition, it notifies users automatically when changes are made and enables strict versioning control, leaving a clear record and providing traceability. While Excel files are а good option for capturing data at a specific moment in time, for example to export a data template, they are not so useful when it comes to tracking updates. Using an API will allow you to distribute the latest versions of your data models in real time.  This way both you and all stakeholders can always be sure that they are using the most up-to-date information – an important factor when it comes to building trust in the data that is exchanged throughout the entire supply chain.

Using an API will allow you to distribute the latest versions of your data models in real time.  This way both you and all stakeholders can always be sure that they are using the most up-to-date information – an important factor when it comes to building trust in the data that is exchanged throughout the entire supply chain.

Ensuring data quality is essential

To ensure data quality, the newly published standard EN ISO 23386 establishes a standardised process for creating properties. All proposed properties are subject to formal approval by domain experts.

Cobuilder Define enables you to implement the data governance process described in EN ISO 23386

Excel does not facilitate the implementation of the prescribed data governance process. Ultimately, this might result in poor data quality. The spreadsheet may become full of repetitions and unnecessary data fields over time, not to mention inconsistencies.

Moreover, some product properties have certain restrictions on data type and format, e.g. integer, float, string, enumerations. While Excel allows for creating data validation rules, these can be easily overwritten by accident, e.g. with a single copy/paste action in the wrong cell. Here the best-case scenario is for the resulting data template to be incompatible and cause a validation error. The worst case is for the template to be copied repeatedly along the supply chain into the project documentation, with no chance of traceability or correction.

A solution specifically designed for managing properties and data templates, such as Cobuilder Define, can be very useful to implement a rigorous data governance process and safeguard the quality of your data.

Managing data models: Excel and beyond

As we already mentioned, Excel is a very versatile and convenient format.  It can be used by anyone and allows us to exchange information as a good start even today. But that’s just it – it is not specifically designed to meet the needs of the construction sector, nor to implement its standards for data management.

A solution specifically developed for this purpose will help you to manage your data in a more efficient way. Thanks to the efforts of the experts maintaining it, you won’t need to manually update your data models according to the latest changes in regulations or to worry about adapting them to each of your target markets. A specialised solution, such as Cobuilder Define, allows for automated translations and localisation of the data aligning it to all relevant local standards. It offers an embedded process for data governance to help you ensure quality and trust in your data.

Finally, if your supply chain insists on working with Excel exports, this need can also be supported. However, the future of automated processes lies with machine-readable data directly exchanged between various systems through APIs.  We are ready for this future. Are you?