Interactive maps show the accessibility and quality of public transportation for each house in Germany. Computer scientists at the University of Konstanz developed the maps to enable data-driven simulations for discussing political issues – or just checking the situation in one's own neighbourhood.
How good is the public transportation from your home address? For an objective perspective, you can check the
interactive "Mobility Maps" for Germany that are freely available online. The maps show the accessibility and quality of public transportation for each house in Germany. For example, they can be used to check the situation around a current home or at various potential locations for a new one. In addition to this, the maps provide a valuable tool for data-driven simulations and political decisions, e.g. about the effects of transportation planning activities and potential structural reforms in Germany.
The interactive maps are based entirely on publicly accessible data. The mapping system was created under the leadership of Daniel Keim and Maximilian Fischer in the Data Analysis and Visualization (DBVIS) research team at the University of Konstanz and funded in the context of the Cluster of Excellence “Collective Behaviour”.
35 million houses at a glance
Where in Germany can people expect to walk long distances to reach public transportation stops? Where is the quality of public transportation not good enough for people to reach important everyday destinations like grocery stores, doctors' offices or schools? The Mobility Maps answer these questions for more than 35 million houses, each publicly listed building in Germany. The simple colour coding makes it easy to spot where the transportation situation is good and where there is room for improvement.
The maps factor in the walking distance to the next stop as well as the connection quality, i.e. travel times, service frequency and, most importantly, the key destinations these connections serve. For each house, the system checks the individual connections to schools and kindergartens, shopping centres, doctors' offices, cultural facilities and much more. The system's developers based their analysis on typical daily scenarios, such as: How well can I manage my everyday activities using public transportation? How long does it take to travel to a physician or go shopping?
The interactive maps also allow users to get answers to their own specific questions. For example, they can use the slider to set a certain maximum acceptable walking distance to the next stop or state a desired connection quality. They can also zoom seamlessly from showing all of Germany down to just one individual home.
Mapping transportation reality in Germany
"In many areas of Germany, the walking distance to the nearest stop is relatively reasonable", Maximilian Fischer says. "When you look at connection quality, however, the major cities have a high frequency of services, while the situation is problematic in many individual locations in Germany. Some of these results are surprising when you compare them with the broader region or even parts of individual city quarters." On the one hand, the maps show a "belt" of well-developed transportation services across central Germany, from Trier to Erfurt and on to Rostock in the north. On the other hand, transportation connections are less strong in areas along the country's northern and southern borders and in its mountainous regions.
The system is a valuable tool for identifying and closing gaps like these. "We see great potential for addressing policy matters in a way that is data driven and very precise – down to the household level", says Daniel Keim. "We want to give policymakers and local residents a solid, data-driven basis for discussing mobility issues."
For example, the maps could be used to estimate the effects of economic restructuring by simulating precisely for which households connections would change if, say, local hospitals merged or a grocery store closed. The maps would also show, for example, which positive or negative effects moving a bus stop would have.
An interactive "expert system"
The Mobility Maps are an example of an interactive "expert system" developed by the Data Analysis and Visualization research team led by Daniel Keim. The motivation behind such a "visual analytics" application is to create analysis systems that assist policymakers and the public with finding data-driven answers to important social issues ("human-AI teaming").
The interactive maps are freely available online, and can even be viewed using a mobile device, although a more powerful computer is recommended for more detailed research. The
OPTIMAP dataset, developed specifically for the Mobility Maps and on which the system is based, has also been published open access. Pre-rendered analyses for all of the administrative districts in Germany are also posted on the
Mobility Maps website.
Click on the green button "start interactive map" to get started. At the top right of the map, click on "Scenarios" to customize the interactive settings. The "walking" maps show the distance to the next stop, while the "quality" maps show the quality of public transportation connections, including travel times, service frequency and ability to reach key destinations.
Key facts:
- Publication of the dataset: Fischer, M. T., Fürst, D., Metz, Y., Schmidt, M., Rauscher, J., & Keim, D. A. (2025). OPTIMAP: A Dataset for Open Public Transport Infrastructure and Mobility Accessibility Profiles [Data set]. Zenodo. doi: 10.5281/zenodo.14772647
Link: https://zenodo.org/records/14772647
- Publication focusing on the methodology: Metz, Y., Ackermann, D., Keim, D. A., Fischer, M. T. (2024). Interactive Public Transport Infrastructure Analysis through Mobility Profiles: Making the Mobility Transition Transparent. IEEE Visualization in Data Science (VDS), St. Pete, FL, USA. doi: 10.1109/VDS63897.2024.00006.
Link: https://ieeexplore.ieee.org/document/10747691
- The Mobility Maps were developed by the Data Analysis and Visualization (DBVIS) research team at the University of Konstanz in collaboration with the Steinbeis Competence Center Interactive Data Analysis and Visualization at the University of Konstanz. The research project was funded by the Cluster of Excellence Collective Behaviour.
- Professor Daniel Keim leads the Data Analysis and Visualization research team at the University of Konstanz. He is a principle investigator in the Cluster of Excellence Collective Behaviour and a member of the directorate of the Centre for Human | Data | Society (CHDS) at the University of Konstanz. His main areas of research include data mining in addition to data visualization and analysis.
- Dr Maximilian T. Fischer is a postdoctoral researcher in the Data Analysis and Visualization research team led by Daniel Keim. His research focuses on the interactive visualization and analysis of communication using machine learning as well as the analysis of infrastructure networks in the energy and transportation sectors.
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