IT for signalling is a niche industry because it is closely tied to national markets.  

Customising software is expensive when each IM has his own model, e.g. PlanPro, IMSpoor, SDEF, Gaia. Software developers rarely have both rail and IT know-how so the language, jargon and culture remain barriers to developing pan-European software packages.

EULYNX DP is designed to help data break out of the national silo.

Firstly, to make data accessible to "one-size-fits-all" software packages, we must map national datasets to EULYNX DP. Tools that handle EULYNX DP data are easier to customise for different IM’s.

This mapping activity is already underway as part of the EULYNX DP validation process. By absorbing data that originate from national models we show EULYNX DP can represent these data and simultaneously we write the transformation rules.


Model once - run everywhere

The EULYNX DP model is a Platform Independent Model. A PIM isn’t tied to a computer language or the hard-/software platform. A PIM is easily transformed into a Platform Specific Model, PSM, such as XSD or object-oriented languages such as Java, C# and Python.  Developers can create a PSM from the EULYNX DP PIM and add functionality whilst being assured that the underlying data is compatible and that their software is easily portable across borders.

Enriching the model

The EULYNX DP information model can be extended to unleash its full potential.  EULYNX DP is developed using tried-and-tested methods from Model Based Software/Systems Engineering. Models in MBSE are meant to be extended and enriched.  In below, hypothetical, figure, a developer added methods that search the data for neighbouring signals and another method that checks that the signal is correctly placed according to a set of prolog rules that he created from a set national rules and regulations. The EULYNX DP model natively provides information about the type and position of the signal. The developer can leverage graph-algorithms to do complex rule checking.

This is one example how a software developer can make objects smart by adding methods implementing algorithms that are appropriate to his use case. Transforming and enriching an MBSE model is a tried and tested approach.

Finally, configuration data can be combined with methods to create live digital twin. Objects are aware of their position in the network. This would exploit graph information that is included in the EULYNX model because it is based on the RailTopoModel. This allows objects to be queried using graph walking algorithms. When combining network knowledge with OPC-UA, an industrial IoT protocol that is used by EULYNX SCI interfaces, one can effectively create a digital twin of the railway network. This opens many possibilities for new use cases ranging from event-driven simulation to finely tuned maintenance scenarios.