Case Study

Agency for Roads and Traffic

Agency for Roads and Traffic case study

The Agency for Roads and Traffic migrates and improves data for road works

There are all kinds of ‘assets’ on and along the Flemish motorways and regional roads: from cameras and noise barriers to manhole covers and trees. Making data about those assets accessible allows integrated and digital collaboration on infrastructure works in BIM projects. To make this possible, the Agency for Roads and Traffic (AWV) had to migrate a large volume of asset data to new databases, in accordance with a new data standard, the Object Type Library, or OTL for short. The manager of the Flemish motorways and regional roads called on Nordend, an expert in FME and OTL.

Until recently, all information about assets for road works, for example asphalt layers, traffic lights and cables was stored and managed by the Agency for Roads and Traffic in various databases, including the Akela and roads database. But the data standard used at the time did not allow the agency to optimally manage the assets. Moreover, the data wasn’t reusable for BIM projects, in which construction partners realise projects in a digitally integrated way.

‘That is why the Flemish Government experts established a new data standard to use: an OTL or Object Type Library, to build a new database about the assets,’ explains Natasha Blommaert, AIM-BIM Programme Manager at the Agency for Roads and Traffic. ‘With this standard we capture the right asset data at the right time, so we obtain the right information for optimal asset management. At the same time, the OTL allows us to work with new methodologies such as BIM (Building Information Modelling).’

‘Nordend’s extensive expertise in FME was a crucial reason for us to collaborate with them. We realised that we could intelligently transfer and improve our data with this technology.’

Natasha Blommaert, Innovation & Data Advisor and AIM-BIM Programme Manager at the Agency for Roads and Traffic

Robust data migration

Today, contractors for works on the Flemish motorways and regional roads are already delivering information on their assets in OTL format, via a new data platform from the Agency for Roads and Traffic. Thus, the agency has OTL-compliant data. But in addition, there was a lot of data that was in the old format in the Akela and roads database.

‘We wanted to migrate that data to the new OTL-compliant database Infra DB and visualise it in our new asset management application, called ELISA Infra in the OTL data standard,’ continues Isabelle Piette, AIM manager, IT Specialist and manager of the data migration team. ‘The idea was to maximise the industry’s use of the data,’ Natasha adds, ‘and to become more efficient ourselves, with our employees no longer working in different databases, but growing in maturity based on optimally available asset data.’

In addition, the agency wanted to immediately migrate the data on camera installations from the EMinfra database, as well as the data from the road database on manhole covers, street gullies, ditches, noise barriers, road surfacing (asphalt/concrete) and roadside trees. From now on, all that information would be located in the new system, in accordance with the OTL data standard.

Not only migrate, but also improve

‘A first, crucial, question was whether the OTL data standard defined all the types of data we needed to migrate,’ Isabelle Piette continues. ‘To answer that, we first performed data mapping. Based on this, we could then convert the processes through the FME tool to migrate the data.’

For that entire process, including the actual data migration, the Agency for Roads and Traffic counted on Nordend’s expertise. In 2021, both partners first realised the smaller migration of data regarding camera installations. Then it was time for the Akela database itself, accounting for a migration of 500,000 objects and their interrelationships. The final migration then started from October 2022, after which the road database also followed.

‘The intention was certainly not to simply migrate data from model A to model B,’ Natasha Blommaert continues. ‘We aimed to improve data quality by using a balanced set of criteria and a similar framework. After all, the old databases contained information that we could not transfer one-to-one. It involved data that the OTL standard did not always consider, because it was created primarily to best meet asset management needs.’

When data could not be accommodated in the new OTL standard, the agency took one of two paths. ‘Either we adapted the OTL standard to still recover the data, with maximum recovery as our goal, or, in the case of data we no longer needed, we did not transfer it. But we never decided to do this unthinkingly’, Isabelle added.

‘We had to be able to continue to inquire in the Akela database which cables and pipes were in the ground at locations where road works were in progress,’ explains Isabelle Piette. ‘Thus, up to the point that the actual data migration began, new data was still being added in Akela.’ And even today, requesting that information is still done through the Akela database. Natasha Blommaert explains: ‘The migrated data therefore had to be backward compatible with the old data model. That was certainly one of the challenges, but the biggest advantage is that the contractors now only have to supply data according to one more model, instead of two, and we have ensured the derivation takes place automatically.’

‘Nordend’s familiarity with the content definitely added value because it allowed us to more smoothly work out the processes for data migration, together with the business.’

Isabelle Piette, AIM manager, ICT Specialist and manager of the data migration team at the Agency for Roads and Traffic

Relying on expertise

Throughout the entire process, both for the data migration and the improvement of data quality, the Agency for Roads and Traffic worked intensively with Nordend. ‘Nordend strengthened the whole process with their thorough expertise and know-how,’ says Natasha Blommaert, ‘both about the data itself, and about FME and how it could help us improve migrations and data quality.’

In fact, Nordend’s extensive expertise in FME was a crucial reason for the agency to partner with the company. We realised that we could intelligently transfer and improve our data with this technology. Especially if we involved an expert like Nordend, who knows FME inside out and would be able to transfer that knowledge to our internal employees. Nordend also had experience with the data mapping and migration of exactly the types of data that we wanted to migrate. In other words, they were also immediately familiar with the content.’

‘That familiarity definitely added value, because it allowed us to more smoothly work out the processes for data migration, together with the business,’ continues Isabelle Piette. ‘In fact,’ Natasha Blommaert notes, ‘it is precisely this familiarity with the content that made the biggest difference, because that way Nordend also took a lot of work off our hands, instead of having to ask us questions us all the time.’

The results

Once migrated, the Infra DB database and therefore ELISA Infra contain more than ever all the necessary data for road works, in the OTL data standard and in optimal quality. Data that moreover described both the assets themselves, and the relationships between them: not stored in a relational database, but in a graph database. Nordend has a lot of experience with this and also provides the tools to automate the creation of relationships between assets.

‘Thanks to the successful data migration, we are another step closer to our goal,’ Isabelle Piette concludes. ‘We want to grow into an asset-driven organisation, with a fully developed asset management system. We can only do that by migrating all the data into the new data standard and representing it in relation to each other.’ It also ensures that contractors can now enter data more easily and deliver BIM projects together.

Challenges

Converting data in outdated Akela application to the new OTL model
Additional migration of camera installations and Road database to the same new application and database in accordance with the OTL
Taking over specific types of assets (additional classification)
Avoiding duplication and data quality improvement actions
Creating specific models, e.g. cable and pipe models