"There is a lot of data in the market, especially when it comes to infrastructure and connected trains. There is data for passengers from the operations, maintenance data coming from trains, etc. We can share data via open API and apply data security and safety standards because at the end of the day it’s all about building trust and sharing data. There are also data models in between business models on monetizing different data," explains Stefan Kemper, Senior Strategic Director at Siemens Mobility, and continues with examples of using particular kinds of data:
"The values which we generate are based on use cases, for example, if you look into data that comes out of trains as a temperature, status of doors or let‘s say the occupancy of the train, this data can be reused for passenger operations. For example, this data can be automatically incorporated into the journey plan so that passengers will be able to reach their destinations as quickly as possible, even when disruptions occur. As a result, the operator benefits by being able to offer its customers an improved passenger experience. Or the other way around, if you have data about punctuality you can also use it for maintenance or depo planning, so it’s about sharing data and the data ownership stays with operators or the train manufacturers depending on what data we are talking about. We have to differentiate the set of data," he clarifies.
Regarding obstacles connected with data and the protection of people he has no worries: "We can anonymize data so that we see where travelers are and where they are heading, but without knowing who has sent this data. This ensures that we are fully compliant with GDPR regulations.
Stefan Kemper concludes the interview with the key points for data sharing: "Operators can increase the comfort for passengers and increase punctuality if they make better use out of available data out of the network and from different, former isolated systems via APIs. To optimize the availability of trains, it is also good to know what’s happening on the train and then do the maintenance work order planning, including spare parts logistics upfront in close interaction with the train planning and timetabling systems. So there are a lot of use cases where data plays a major role and can create value for the many stakeholders across the entire railway system".