We at the VAP have been working more intensively on the topic of data ecosystems for some time. In 2022, we initiated the development of a data platform at the Coordination Unit for Sustainable Mobility (KOMO) and are pushing ahead with the further development of the Mobility Data Infrastructure (MODI). With this blog post, we would like to continue the dialogue and show why data ecosystems should be part of the vision of all freight railway actors.
Here’s why:
- Complexity sets the bar high
- Small steps to the big vision
- Exploiting the inexhaustible potential of data
- We should stay in the conversation
Complexity sets the bar high
Data ecosystems are highly complex and encompass diverse subject areas (see Figure 1). If they are to be made usable and economically viable, we must take into account all the wishes and needs of the actors as well as any restrictions.
On the occasion of our Freight 2023 Forum, Dr Matthias Prandtstetter, Senior Scientist and Thematic Coordinator at the AIT Austrian Institute of Technology AIT, and Monika Zosso Lundsgaard-Hansen, Co-Section Head Directorate Operations at the BAV, provided insights on the current status of initiatives and considerations. The experts agree: progress in the rail sector will be a long and difficult affair.
In small steps to the big vision
The target image of an intelligent and possibly self-deciding data ecosystem could be realised through the following development phases as examples (not exhaustive):
1. provide basic data (e.g. with MODI)
- Guaranteed quality
- “Uniqueness” of the data set (i.e. clear definitions)
- Accessibility/transparency for all those involved
- Market-based development of apps and extended functionalities possible
2. activate hub for exchange of data (e.g. DX Intermodal by Hupac)
- Exchange between 2 or more companies operating on the hub
- Additional data sets (with or without restrictions for individual actors/companies)
- Booking possibilities for individual or entire relations
3. create data ecosystem
- Ensure access to historical data for initial analysis possibilities
- Connect databases (basic data and/or data sets available with restrictions)
4. use blockchain technology
- Data and data sets are optimally networked
- Absolute cost and price transparency
- Increased security in data exchange
- More efficient overall development and processing
5. realise the vision of a physical internet
- Open global system based on physical, digital and operational interconnectivity
- Applies protocols, interfaces and modularisation
- Certain decisions are made by the ecosystem – not by individual players
Currently, the rail sector is in phase 1 and 2, even if only selectively. With the Federal Act on Mobility Data Infrastructure (MODIG), the FOT is addressing all relevant topics. DX Intermodal is already operational in combined transport (CT) and takes up points from phase 2. An overall benefit for rail freight logistics can only be achieved if all forms of freight transport production and the entire transport chain (“door-to-door”) are taken into account. To this end, elements of artificial intelligence must be integrated.
Exploiting the inexhaustible potential of data
Big Data has transformed from hype to megatrend; the potential of collected data is almost infinite. This enables disruptive, innovative, digital business models and better predictions for correct business decisions. However, this only applies to data that is available in the right quality and granularity. In addition, the actors must be able to extract the right information and thus the desired knowledge from the data and to interpret and use it correctly. This poses a number of challenges for the ecosystem partners:
System benefit vs. self-benefit
Some companies already have in-house data systems. They collect data from devices on locomotives and wagons and use it for optimisation or pass it on to third parties. This gives them a competitive advantage and additional sources of revenue. Why should such companies participate in data ecosystems? Because optimising their own system does not necessarily serve the system as a whole or the end customer. If, for example, various individual players sell the same data to third parties for a fee, the system becomes more expensive because money flows for each data transfer. In addition, individual actors can combine their data sets within the framework of a data ecosystem and thus promote the efficiency of the entire system, for example the estimated time of departure or arrival. In this context, questions of data sovereignty need to be clarified.
Obligation vs. voluntariness
The state is and remains the biggest financial backer of the rail system. It should have an interest in relieving its own coffers and thus the taxpayers. The provision of non-profit data can improve efficiency. Again, questions remain: Should ecosystem partners be obliged to provide datasets? Should it be possible in a data ecosystem to offset previous, individual investments or to contrast subsidies received? Or should participation in a data ecosystem remain voluntary, with the risk that too few participants feed the platform with data?
Data vs. data
Not every data element is equal for a data ecosystem. Thus, it must be clearly defined from the beginning with which goal and overall benefit an actor should deposit its data elements on a data platform. In addition, a distinction must be made between operational, technical and commercial data in order to avoid emotional discussions. Finally, the quality ensured by the data owner or a newly created quality body determines the credibility and sustainability of a data ecosystem.
We should stay in the conversation
We at the VAP want to make the potential of data ecosystems available to the entire rail sector and increase its competitiveness. That is why we are committed to various initiatives, research projects and established products in this context, namely the following:
- Further development of the mobility data infrastructure MODI, together with the BAV.
- Common European Mobility Data Space (EMDS), an EU initiative
- Logistics Working Group (AKL), in which we have taken over the leadership
If you too would like to help shape the digital future of the rail sector, Jürgen Maier looks forward to hearing from you.