From CS294-10 Visualization Fa07
 Good Visualization.
Source: page 116 of the September 2007 issue of Scientific American magazine
This visualization shows the agricultural and seafood imports to the United States in 2006. The article in which it appears is about policy recommendations that were made in response to the recent alarming incidents of contaminated goods to the U.S.
This visualization uses a statistical data model to show the origin and division of the $78,475M USD-worth of agricultural and seafood goods imported to the U.S. from fourteen geographical locations in 2006. Both direction (N) and quantity (Q) are clear from the image; the former implicit by the definition of 'import,' and the latter nicely encoded by line width and marked with a consistent currency. From my quick measurements, these line widths scale proportionally with their quantity and do not appear to constitute graphic distortion. Also, geographical information such as rough import distances (Q) can be gleaned by nature of the visualization being a map, as longitude (Y-axis, Q) and latitude (X-axis, Q) are both encoded in the image. There appears to be no uninformative elements.
 Bad Visualization. Very, VERY Bad.
Source: page 30 of the September 2007 issue of Popular Science magazine
This advertisement uses a visualization of the human body to highlight the areas that are nutritionally benefited by beef consumption.
To the left is a list of five beef-abundant nutrients that seem wrongly mapped to the body part it supposedly affects. For example, Niacin (which, from the description, helps to promote energy) is oddly mapped to the hip area.
This visualization uses a relational data model, where the tuples represent nutrients (N) and the attributes represent health benefits (N). The image shows mapping by connecting a dotted-line from each nutrient to a color-encoded bodily area.
uninformative elements include pretty much all of them; in fact, not only is the entire visualization uninformative, it's arguably misleading. Aside from confusion, I don't think this visualization adds anything to the message of the advertisement.
Visualizing qualitative data is a lot less approachable for me than quantitative data. Because a single nutrient can have many health benefits, I felt it was impractical for me visualize each and every benefit with a proper image. Instead, I chose to list on the left all the beef-abundant nutrients (using hue to encode unordered data) and on the right list all the beef-induced health benefits. A nutrient-benefit mapping is shown with a solid line connecting the two, in the unique color of the nutrient. To further clarify this mapping (the connecting lines are very thin and may not be easily discernable), vertical stripes in the color of the mapped nutrient is added to the left side of the mapped benefit.
From an observer's standpoint, it's easy to glean all the nutrients rich in beef, all the health benefits from beef consumption, which nutrient is responsible for which benefit as well as which benefit is supported by duplicate nutrients.