Geospatial data visualizations make it possible to quickly recognize regional characteristics. A great added value in the information visualizations results from the comparison between different data sets. Conventional map visualizations such as choroplethic maps, however, can usually only show a single value within a map; comparability is lost.

As part of my bachelor thesis, I investigated how the informative value of statistics can be increased by a multidimensional visualization of geospatial data. Several studies have been developed, which aim to make different data sets comparable within a single graph.

One approach to combine several data sets into one graph was to extend the two-dimensional representation by one axis and thus bring the data as points into the three-dimensional space. The exciting thing about this is that the abstract data is used to create an object that can be explored and experienced just like a landscape in real world.

A second approach was to combine two design parameters in one place, so that the relation of the two data sets can be directly recognized and analyzed. The result is a geospatial regression analysis.

Connections can also be used to display quantitative data at a specific location. The quantitative relationships were visualized by the thickness of the compounds. The local origins of the connections were then linked to the nationwide cumulative total value. Thus, weightings of a certain region can be identified and compared.

The result is seven interactive studies that show in two and three dimensions how the information content of the data sets can be increased through a newly gained comparability of statistical, geospatial data. Equally exciting was the visual exploration with geo-referenced data points and the aesthetic experiments, some of which allow new perspectives on the data.