We provide a sneak preview under the hood of Telekom mobility data analytics R&D, which is currently implemented in the real lab of the Hamburger Hochbahn for the National Platform Future of Mobility in Hamburg (link), specifically the use of the International Data Spaces standards (IDS, DIN Spec 27070) for the new European GAIA-X hypercloud. The problem: There are billion-dollar opportunities in mobility, yet the big hurdle is data. Think Uber, which benefits from reusing existing assets, like other people’s cars even drivers. Uber’s capital is not tied up in cars like Car2Go/ShareNow. Instead, it is investing in data to orchestrate a service offering. A gigantic opportunity lurks in urban transport where empty seats dramatically exceed occupied ones - most commuters drive alone; many buses remain empty for long periods of the day. Derived from this, the question arises how to fill the empty seats? The solution is simple in theory: Use data to match demand with supply, like Uber … or how Google is auctioning off ad spaces. In practice it is a lot more complicated. In a nutshell: Often data doesn’t speak the right language, is not using the same metrics (think Celsius versus Fahrenheit) … and some parties don’t even talk to each other like competitors to protect the customer connection. We will briefly illustrate how there is value in intermodal mobility and how it can be released using data.