Featured photo: The deleted map displays all deleted elements within the analyzed areas (red). Gray rectangles represent deleted buildings.
This past November, our teams at HeiGIT and GIScience participated in Topi Tjukanov’s Twitter event #30DayMapChallenge, where mappers display their creativity and ingenuity with a set of 30 daily prompts ranging from colors to specific datasets to geometric limitations in any sort of map one can imagine. The challenge runs for the entire month of November and has been active since 2019.
As we eagerly anticipate the next round of mapping, we’re looking back at our contributions to last year’s challenge. In this series, we’ll speak to some of the mappers to gain insight into the colorful, innovative, and downright stunning submissions from last November. You can read part one, which looked at three versions of Germany produced by HeiGIT researcher Jakob Schnell, here.
Next up is our submission to Day 22, NULL. The term describes “No Data” (as opposed to 0 – zero) in many programming languages and therefore offers a wide range of interpretations. Our team’s contribution was to visualize deleted or invisible data from OpenStreetMap (OSM), meaning data that had been NULLed by the mappers. The idea stemmed from a feature request for deleted objects from HeiGIT’s OpenStreetMap History Database (OSHDB) project.
To understand the contribution, one must consider the geographical area around the coordinate (0,0), often referred to as NULL-island. Technically, this location is arbitrary- the Greenwich-meridian (prime meridian or 0-meridian) was chosen for historical rather than geographical reasons. Nevertheless, the location is often used as a “default” or trash-can location. As you can see below, OSM is no exception.
Day 22’s NULL challenge was tackled by Moritz Schott and Rafael Troilo. Moritz Schott is a Research Associate at the GIScience Research Group working on the IDEAL-VGI project, while Rafael Troilo is a Research Associate on HeiGIT’s Big Spatial Data Analytics team with a focus on software development, database and high performance developing/programming, spatial data analysis and visualization.
The two researchers took the prompt significantly further than one map. They created a full workflow that first extracts deleted elements from OSHDB. In a second step, the geo-data in OGR compliant format is transformed to the OSM data format using the ogr2osm tool. Finally, the resulting data is rendered using the recommended setup from switch2osm.