Just discovered a great blog post on “data illustration” versus “data visualization” at Information for Humans. AIS argues that data illustration is “for advancing theories” and “for journalism or story-telling.” By contrast data visualization “generate[s] discovery and greater perspective.” I love this distinction, although I’m not sure I like the specific language. Tukey famously argued that data visualization was for developing new theories. Drawing on Tukey, I would use the phrase “exploratory visualization” for techniques that allow us to poke around the data, searching for trends and patterns. Tableau is the great commercial product and Mondrian by Martin Theus is a wonderful freeware application. By contrast, once we have a thesis, we need to convince our audience. That’s “expository data visualization” and it calls for different tools. The R package ggplot2 (http://www.ggplot2.org) is my choice. The terms “expository” versus “exploratory” resonate with freshman comp more that standard data analysis, but that’s the point. After all, this is a DH blog.