“Raumdatenpool” and Other Fancy Data Sources
August 31st, 2026 | by Marius Dupuis
(5 min read)
In the spring of 2026, we had the pleasure of joining the SUMO conference in Berlin, presenting our first-ever GEONATIVE poster, and talking with our peers about traffic simulation and geodata.
One of the discussions centered around the general practice of measuring the same areas again and again instead of sharing once-measured data and just updating them as necessary. This led to an interest in knowing whether some stakeholders got it right and followed what we have always postulated: spend money on creating larger data pools instead of creating a landscape of redundant smaller ones.
Here’s what we found:
“Raumdatenpool” Kanton Luzern
This collection of information with spatial correlation to the municipality and district of Lucerne, Switzerland is quite comprehensive, up-to-date and standardized.
It is comprehensive, because it contains cadastral data, usage and development data, utilities data etc.
It is up to date, because it is just that. And the platform also promises that any data uploaded until noon on one day will be available on the next working day. Each data set is also clearly marked with its release date.
It is standardized, because it defines data models and publishes the respective descriptions. The term “standardized” though, may suggest that data comply with commonly accepted standards. Here, it’s more the type of de-facto standardization for the given purpose.
Another key feature is the transparency with which the platform talks about itself and its roadmap and strategy.
The drawback, though, is that some data are only available to communities, the canton, utility companies, associations etc. The “ordinary” user would need to go to these entities and ask for information. In an age of increased security demand, this seems a viable solution but still raises the bar considerably for the interested public (like us here at GEONATIVES).
Nevertheless, creating a consistent, up-to-data database that can be shared among official stakeholders sets a great example for other entities. The clear highlight is the speed when it comes to updating data in the pool by giving the promise to act usually within 24 hours (on work days). Just browse through the datasets mentioned on the page about data updates, and you will hardly find anything that is more than a week old.
Also for figuring out the extent of data available, it is definitely worth digging deeper. Try it yourself. Just select any community from the “Geoportal” prompt on the landing page of the “Raumdatenpool” and you will end up at the respective community’s own geo information page, offering maps, a 3d model, information on usage of areas, cadastral data, aerial images and information about water, energy and other networks. Exploring the Geoportal Luzern further you will also find data on climate and energy etc.
An interesting discovery were the data on punctuality of bus and rail services – especially if you compare them to experience in your home country (here: Germany).
It seems a bit odd, though, that there are hardly links to other cantons’ information systems. Is each canton an island? Does a country of less than 10 million people really have parallel geoinformation infrastructure, especially when the need for making geoinformation available is based on a federal law in Switzerland?
Indeed, you find information from other cantons, e.g. Zug, Wallis, Graubünden, with different user interfaces and extent of data, but you also get the federal top-down view on the Geoportal Switzerland homepage. Overall, the data situation looks more than just promising.
Looking at Germany
A frontrunner in terms of making geodata available is Hamburg. Its geoportal looks like a regular map and doesn’t seem to offer a lot of information when you open it. But once you browse through the filter options, you enter an almost endless choice of additional layers. Interested in the number of unmarried people or in the roof areas and their fitness for solar energy? All this information is right there. In total, you find roughly 500 data sets via this portal.
Hamburg is not only adding data to the portal and keeps them up to date, the city is also involved in the development of the underlying software Masterportal. With more than 50 development partners and approximately 200 installations, the software has significant weight. Five German states and the federal government use it as their central geoportal. (BTW: don’t expect Bavaria – except for some “rebels” in Munich and Regensburg – to use something that has not been invented there. This is the reason why you find most data in and about Bavaria in the BayernAtlas.)
On the other side of the Atlantic
In our discussions at the SUMO conference, data about Salt Lake City were named as a good example where authorities made information available to the general public. Especially the data on transportation is worth mentioning – and worth exploring. Go, for example, to the transportation counter page. But, of course, you also find the “typical” GIS data provided by the state of Utah.
You can repeat similar queries across the US by accessing, for example, the data websites of New York City, San Francisco etc.
Elsewhere
Comparing smaller entities like Singapore with larger ones like Delhi, it becomes clear that size matters – as long as it remains small. Where we see well-curate up-to-date data in the former repository, the latter one seems to be stuck in beta state and was last updated two years ago. Going to the IT hub in India, Bengaluru, the situation looks slightly better but still far away from generally usable data.
Conclusion
A small conversation at the 2026 SUMO Conference led to a slightly deeper dive into publicly available sources for geoinformation, traffic data, cadastral data etc. Our survey is far from complete; it merely scratches the surface. But what we could find out is that many communities, municipalities, and governments pay a lot of attention to making data openly available and to curating their data. Whether they all follow our rule of thumb – measure once and share your data – cannot be confirmed. But the data we found in Switzerland seem to set a good example.
We’ll certainly keep exploring the continuously growing offerings of open data.
About The Author
