With current infrastructure communication processes failing to meet market requirements, information exchange through digital rail system interfaces has become a necessity in the rail sector. Using defined standards in these exchanges will enable improvements in speed and efficiency of data transfer. As part of the TTR – Smart Capacity Management project, railML.org and RNE are collaborating to develop an interface to facilitate digital data transfer for infrastructure.

Who is RNE?

RailNetEurope (RNE) is an association of European Rail Infrastructure Managers. It serves as an umbrella organisation that helps coordinate its members’ international processes in the areas of Capacity Management, Traffic Management, Corridor Management, IT and Sales & Legal Matters.

What will the interface achieve?

The interface will enable machine-to-machine (M2M) communication between infrastructure systems and other rail applications providing infrastructure managers (IMs) with a more user-friendly solution. The interface is underpinned by a newly created database in the railML format of the following RNE infrastructure* data:

• TAF/TAP TSI Primary Locations and Subsidiary Locations ( can be found as code list Registers )
• Connections between locations (Segments)
• Tracks belonging to Primary Locations and Segments
• Line Properties
• Service Facilities

*This collaboration is limited to the railML infrastructure scheme; RNE uses TAF/TAP for the exchange of data.

Next steps and outcomes

In this collaborative effort between RNE and railML.org, the upcoming railML interface is poised to significantly improve communication within the railway sector. This development promises increased efficiency by reducing manual labour and the potential for human error, marking a significant step towards digitalisation in the railway sector.

Upon its completion and implementation, RNE will use the interface to bridge RNE infrastructure systems with the railDAX (railML 2.5) infrastructure subschema. Case studies on its implementation will be shared on the railML website, ensuring accessibility for the entire industry.