Writing about data visualization is like dancing about your PhD thesis (see below). When improperly executed, the jeté between explanatory and interpretative mediums can be jarring.
Fortunately, there is a great wealth of data viz material that effectively matches prose to performance and description to design.
First, several books on the subject are definitely worth your time:
- If William Dean Howells was The Dean of American Letters, then Edward Rolf Tufte is surely The Doyen of American Visualization. Tufte is professor emeritus of political science, statistics, and computer science at Yale University, and his books on information design and data visualization are the closest thing the field has to On the Origin of Species. The Visual Display of Quantitative Information is perhaps his best known book due to its ubiquity in statistics classes, but Envisioning Information and Visual Explanations are widely regarded as his masterworks.
- Colin Ware's Information Visualization frames the subject as an applied science and builds on the study of cognitive perception by psychologists and neuroscientists. His books is heavy reading—and at 500+ pages, heavy lifting—but it's well worth the effort if data visualization is something you intend to pursue professionally.
- Nathan Yau's Visualize This is a great introductory book on the topic. Yau is the author of the popular FlowingData blog about the same topic, and has a Ph.D. in statistics. His writing is clear and concise, and he does a wonderful job of explaining critical nuts-and-bolts concepts like using data to tell stories, matching form to function, and finding the right framework for presentation.
Second, three websites should be on your bookmark list:
- Visual.ly is a community platform for data visualization and infographics. The site functions as both a showcase for the web's best infographics as well as a marketplace and community for publishers, designers, and researchers.
- UK-based designer Andy Kirk's blog, Visualising Data is a huge repository of data viz information, including lists of the most useful web-based visualization tools and more sophisticated software options for collecting and handling data.
- Finally, the Reddit Infographic page ("subreddit" if you insist) is a great spot to find some of the more creative visualizations floating around the web, especially the kooky kind that might get passed over on other sites (e.g. this incredible Gmail hot key cheat sheet.)
Third and finally, you can learn more about visualizations and infographics by simply supporting your neighborhood newsstand. The New York Times and National Geographic are the industry leaders in newspaper and magazine visualizations (respectively), and both do an exceptional job of presenting data with a clarity of context and purpose.
After reading (or intensely skimming) the sources listed above, you should develop a stronger framework for analysis when appraising data visualizations. The next step is to contribute to the design discourse by sharing interesting or even underwhelming graphics on your social channels and articulating why particular compositional choices work well or fall flat.