Kierann Healy’s chapter »Looking at Data« is a helpful and profound base which helps to familiarize with the fundamentals of Data Visualization. Especially Healy’s clear structure and classification into 3 categories is an important support to get an overview; from which one can dive deeper into more details and relations.
Healy says a good respectively bad data visualization depends on mainly three factors; Bad Taste, Bad Data and Bad Perception. Most importantly though is, that Healy draws ethical conclusions from these three factors, which the creator of visualizations at least needs to keep in mind.
However I am wondering why Healy, while giving a very broad and important approach towards data visualization in general, is referring only to a very small selection of tools (e.g., ggplot). It feels out of place to mention specific tools in such an general explanation towards an ethical approach to data visualization, as this approach is or should be valid even when creating a visualization with crayons and paper. A tool itself should never set the boundaries of how a visualisation will look eventually.
Furthermore Healy’s classficiations seem quiete technical. What I am missing is a more cultural classification of visual representation, not only limited to technical conditions, for example if a color is readable or if a certain visualization takes advantage of a certain gestalt rule.
Lets take Otto Neurath’s work for example. He did not only invent a new way of visualizing quantities which are easy to decipher, but also started thinking a lot about visual representations of cultural conditions. His pictogrammes of workers looked different from the pictogrammes of elite people. These are also important factors inherent in a visualiation and needs to be mentioned.
Last but not least a lot of sources about Data Visualization mention the stunning work of Minard. I was wondering if the real database of this visualization is gathered somewhere. Tufte only gathered the different sources, but I cant find a database with all the actual figures.