I found Card and Mackinlay's taxonomy of information visualization to be rather dry. The article struck me more as a retrospective summary than an informative exploration. To be frank, keeping my eyes up with the text required determined effort.
I found Tufte’s exploration in the first chapter considerably more elucidating. In particular, I enjoyed the historical evolution of data representation documented—the study encouraged me to reevaluate the common visualizations I take for granted today, and also made my mind percolate with ideas for newer innovative visualization techniques.
My favorite section of the reading was the third chapter of Tufte’s text. While the second chapter on integrity was certainly entertaining, the lessons presented were for the most part common sense. But what was striking to me was that that article of common sense—that data representation often obscures or exaggerates relationships within data—had become so common that I had as a reader accepted it. Until I came upon the third chapter, there had never been a time when I questioned why data integrity was so poor in publications, or when I expected better. The brief but concise examination of causes behind data integrity issues caused me to look introspectively for a moment, in particular at my first assignment.
My first assignment strived to be easy on the eyes and minimalist; I wanted to emphasize certain patterns, and was willing to leave out labels and frills that did not contribute toward that end. But while I am confident that I avoided skewing my visualization via any inconsistency, Tufte makes a good point about respecting the reader’s intellect. I personally found some of the examples Tufte illustrates in the first chapter overly busy from a visual perspective. As a technically-minded (and reasonably intelligent) computer scientist, I wonder if there is an artist inside me, one that prefers visual representations to be a simple and incremental instead of dense and spatially economic.