Setting up a unified railway data ecosystems with the help of Digital Twins
In an interview with Geonatives, railML infrastructure scheme coordinator Christian Rahmig talked about the usages of digital twins in the sector of railway data exchange. Which is a promising trend for the railway since last year was the European Year of the Railway.
Geonatives is, like railML.org, a community that wants to improve the world of transportation. They declare themselves as a think tank that focuses on geodata and its related applications. They want to organize the data flow within transport systems and their mission is to "dry the swamp" of incompatible data flows, data formats, etc. and to make it viable for an efficient collaboration among the interested parties.
Digital twin and the five pillars
A key part of the solution for that problem is a digital twin. But what exactly is a digital twin? In essence a digital twin is a digital representation of something that exists in the real world. Considering a railway line from Dresden to Berlin, a digital map containing all the details of this line, can be understood as its digital twin.
As data drives mobility on all levels of abstraction, this data must be handled in a way that provides scalability and reliability for the user and the developer. The concept of Geonatives consist of five pillars to create such a digital twin. These are: the data lake, data formats, data processing, tooling and stakeholders. With his work on infrastructure data modelling at railML.org Christian contributes to the "data format pillar". Basically, he coordinates the development of a common language between different applications, programs and stakeholders. The main aim is to develop a harmonized and standardized language, which is usable for different kinds of railway applications based on data exchange. In order to be able to create such a united and standardized data exchange format, it must be linked with synchronized data dictionaries, which essentially means that everyone uses the same language and same terms.
The digital twin as the solution
In the end, the digital twin is a way to solve the geodata problem of the railway sector. The problem is that there is not enough geodata, which is practically computerized geographical data or simpler data about a geographical location and how it is build. The digital twin is for solving the shortage of this problem because it can depict the environment in a digital way with all the information needed. The aim is to simplify data usage in the railway domain to implement better and interoperable applications for all the various railway sector stakeholders including passengers, infrastructure owners, railway undertakings, etc. In a way railML.org and Geonatives, both, tackle the problem of geodata and try to solve it from different sides. Every railway or road domain is mapping the same environment but with different approaches, through a digital twin the problem of everyone doing it themselves would be erased. It is hard to find the one and only digital twin which is usable for every application. Sometimes it is better to just share information among domains with a common language. This is where railML.org does its part through generic use case development, which is more community driven and oriented after the user, developer and stakeholder. If the digital twin is designed for just specific use cases, then it can be created faster, and it also reduces its complexity.
How exactly does railML.org help to create a digital twin for a unified railway data ecosystems? By using railML it is possible to create a connection of data models what would also allow to make a "federated digital twin", which means a connected digital twin out of single digital twins. The aim is to find and create a common language between the different applications, programs, stakeholders and data models. Through such a common language it is possible to develop a generic and multi-purpose digital twin of geo-referenced transport infrastructure, which is the key to build for example a more environment friendly transport system. Such a digital twin would provide the railway sector with geodata, what is currently something that is missing. Additionally, it can be used in a large variety of appliances such as digital maps or passenger information. The problem is that the railway sector realized too late the importance of harmonization and standardization of data models. railML.org is aiming to unify the railway data based on digital dictionaries to create the possibility of a functioning data exchange ecosystem which is usable for all the different kinds in the railway sector. The focus is to implement joint user needs but also consider open discussion and standardization. This means to collect the requirements of stakeholders and to translate them into a data format which is standardized. It must be remembered that railML.org is a community-driven initiative, so it is not the aim to develop a complete digital twin of the railway world, but to create what the community wants. If it is required, the railML data model will react and be adjusted accordingly depending in the parameters needed.