Presently the railway is the most used means of transport, and as such there is a need to digitalize and automate rail planning and operation. The automation of rail operations requires large amounts of data, but most industry stakeholders are reluctant to share data. Moreover, sensor data is being collected, although the processing and exploitation of these data are faced with legal, economic, or technical setbacks. This has necessitated the development of decentralized data ecosystems such as “data spaces” which provide a solution for trusted data sharing through dedicated connectors that enables reliable and secure data hub. Accordingly, this article discusses how the Federated Rail Data Space (RDS) implemented as part of Europe's Rail FP1 MOTIONAL project is leveraged for developing digital twin data representation of rail operations. Furthermore, RDS incorporates trusted data exchange, ensuring transparency and accountability among stakeholders, e.g., manufacturers, suppliers, assets and infrastructure managers. The findings present an architectural concept that shows how data space connectors support reliable and secure data sharing for digital twins of rail assets. Overall, the RDS enables the development of digital twin models that use data in real time for rail planning and operations. The RDS offers technological building blocks for the rail twin transition.
Anthony Jnr. Bokolo (Mon,) studied this question.
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