Competition 2018: Nominated in the category Journalistic
StreetscapesZEIT ONLINE, 2018
Streets and squares are an archive of both language and history. We suspected that their names would reveal patterns, and we wanted to make them visible. Doing such a thing is impossible using conventional map tools because none of them will show you all of the streets and squares of the same name at the same time.
That is why ZEIT ONLINE programmed a searchable database including all German streets and squares. By doing so, we discovered some fascinating patterns in the distribution of the 450,000 street names. They tell the story of almost forgotten artists and historical events, they shed light on obsolete economic structures and trade routes, on dialects and on idioms imported from abroad. Additionally, we identified groups of streets with thematically linked terms like the names of poets or types of animals. Beyond that, for example, we searched for all the possible endings to a street name, like Limes Road, Limes Way, Limes Alley or Limes Lane for discernible name components like -limes. All streets with the same root name were then tested to see if there were linked groups of streets on a local level. This enabled us to uncover other patterns.
The foundation of our tool is OpenStreetMap, a map wiki where volunteers collect information on all streets around the world. Using the Overpass_API via http://overpass-turbo.eu/ we could see first pattern, i.e. that streetnames with (Paul von) Hindenburg are only left in Germanys western parts. Using that information, the Karlsruhe-based service provider Geofabrik created a dataset for us including all streets and squares in Germany (current as of Oct. 10, 2017). It includes the respective street names, the postal codes and communities through which the streets lead, and the precise geometry of the route taken by the street. Geofabrik also combined multiple data points from OpenStreetMap to create a single, coherent data object accurately reflecting the street's geometry. You can download the data here in GeoJSON format: http://interactive.zeit.de/2017/strassennamen/datensatz_deutsche_strassennamen.zip