I recently attended the “Summer School in Practical Survey Analysis” hosted by Oxford Unversity’s Department of Sociology. One session was devoted to examples of good data visualization. The example used to demonstrate a good map is shown immediately below and is taken from this page on the Office for National Statistics website.
Many of us felt it would actually serve as an example of poor visualization for reasons that I think are worth mentioning here. Aside from the fact that it is missing a North Arrow and Scale, the map is misleading. The highest category represents areas where between 6.4% to 60.6% of the population are non-white. This range of values grouped together is too large in this context. Additional categories in the data would highlight the exceptional areas and prevent areas with a population of only 7% non-white, for example, ventolin being grouped with areas characterised by a population that is over 60% non-white. In addition the spatial units (Administrative Districts) used to plot the data are too course. The Admin. Districts create an impression that the non-white ethnic groups are fairly evenly spread across Central and Southern England, and, aside from London, not clustered in major urban centres as the associated text suggests (ONS, 2004). Reproducing this map with smaller spatial units (such as Super Output Areas) and a greater number of categories for the data would produce a much more accurate picture of the spatial distribution of the non-white population in the UK today. This example demonstrates the importance of a critical eye when viewing all visualizations, no matter how official the publication may be!