Continuous growth in the transport sector means that today’s transport infrastructures, such as terminals and routes, are highly frequented and heavily utilized. In order to maximize the efficiency of available transport facilities and resources, comprehensive and real-time data is required at every step of the transport chain. Such communication requires two key components: technical possibility and willingness of participants to share their data. The technical possibility is provided by electronic data interchange (EDI) and the inclusion of logistics platforms. For readiness, it is necessary to leave each partner sovereignty over their data, allowing them to determine the scope and nature of the use of their data.

International Data Spaces (IDS) represent a suitable solution for establishing this sovereignty. The IDS enables a direct exchange of data via standardized and certified interfaces. This means that participants regain autonomy and control over their data. The goal is the long-term use and dissemination of the standard, which will also gain further importance on a European level in the future as part of the GAIA-X project.

As part of the “DataNetPort” project, IDS will be used in port-related transport chains to improve the organization and cooperation of partners in the transport chain. This project is in cooperation with Fraunhofer Institute for Material Flow and Logistics, thyssenkrupp Steel Europe and Rail-Flow and implements IDS in the context of transport chain use cases.

The project focus for Rail-Flow is the transmission of wagon provisioning times and locations, which shippers and ports communicate to rail transport companies via the IDS. The aim is to transfer this data automatically to a transport management system. In this way, the availability of up-to-date information can be ensured, which is used for the calculation of transport plans. Conversely, rail transport companies have the possibility to share the estimated time of arrival (ETA) with unloaders and ports. With the help of IDS, additional influencing information such as weather data can be used to provide a more accurate forecast and predict arrival times more reliably.

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