Predominance Tag Maps

A predominance map expresses the predominant data category for each geographical entity and colors are used to differentiate a small number of data categories. In tag maps, many data categories are present in the form of different tags, but related tag map approaches do not account for predominance, as tags are either displaced from their respective geographical locations or visual clutter occurs. We propose predominance tag maps, a layout algorithm that accounts for predominance for arbitrary aggregation granularities. The algorithm is able to utilize the font sizes of the tags as visual variable and it is further configurable to implement aggregation strategies beyond visualizing predominance. We introduce various measures to evaluate numerically the qualitative aspects of tag maps regarding local predominance, global features, and layout stability and we comparatively analyze our method to the tag map approach by Thom et al.  [1] on the basis of real world data sets.