Among the great resources at PerceptualEdge, consultant Stephen Few offers some very good discussions of individual data visualization problems, and proposes solutions for each of them. This isn’t a comprehensive treatise, but his commentary on individual cases is highly educational in itself.
Here’s a sample of a poorly done chart. Stephen rightly points out two major issues that make this misleading: a non-zero baseline, and discontinuous time frame on the X axis. I would probably add that the side-by-side column format makes aggregate comparisons of the two data series hard to digest.
Now here is Steve’s redesign of the chart. The problems identified have all been fixed in an elegant and highly functional chart. My only *small* nit with the reworked version is that the years only show up on the bottom-most chart of the three, forcing the viewer to scan down to the bottom of a long graphic in order to understand the time scale of data points at the top.
For numerous additional examples of Stephen’s great work and sound commentary, check out Stephen’s Examples page here.
Since human beings relate to the world spatially, maps are a powerful tool for analysis and sense making.They can also be beautiful works of art in their own right.
Here’s a wonderful resource: Places and Spaces: Mapping Science, a 10-year effort to build a collection of maps to encourage a “cross-disciplinary discussion on how to best track and communicate human activity and scientific progress on a global scale.” The maps are physical artifacts but the online gallery is deep and very well done.
The variety of representation modes in the collection is very broad, ranging from things we would recognize as maps, to Mignard’s “Napoleon’s March to Moscow” chart made famous by Tufte, to some visualizations whose beauty may outstrip their explanatory power such as this one by Ingo Günther.
For a good book on the subject of maps and science, check out Atlas of Science: Visualizing What We Know by Katy Borner (link goes to Amazon).
I just discovered a great blog for data geeks and fans of visual thinking: FlowingData, by Nathan Yau, the author of Visualize This: The FlowingData Guide to Design, Visualization, and Statistics (link to Amazon).
Among other things, Nathan has built a list of Data and Visualization Blogs Worth Following, which is a great resource in its own right.
While Nathan shares a wide variety of serious tools, there’s humor in there too. Check out this one reblogged from Doghouse Diaries: