Representing Data - Data Points: Visualization That Means Something - page 104

Perception of Visual Cues
In 1985, William Cleveland and Robert McGill, then statistical scientists at AT&T
Bell Laboratories, published a paper on graphical perception and methods.
The focus of the study was to determine how accurately people read the
visual cues above (excluding shapes), which resulted in a ranked list from most
accurate to least accurate, as shown in Figure 3-12.
F I G U R E 3-12 Visual cues ranked by Cleveland and McGill
A lot of visualization suggestions (and current research) stem from this list,
which places bar charts above pie charts, heat maps at the bottom, and so on.
This is sound advice, and you see more on this in Chapter 5, “Visualizing with
Clarity,” but remember that this list doesn't mean that dot plots are always
better than bubble plots or that pie charts are evil.
Following this list blindly is an oversimplification of what visualization is. As
you saw in the previous chapter, efficiency and exactness are not always the
goal. That said, regardless of what you want to visualize data for, it's good to
know how well people can read your visual cues and what information they can
extract. In other words, use these rankings as a guide rather than a rule topic.
COORDINATE SYSTEMS
When you encode data, you eventually must place the objects somewhere.
There's a structured space and rules that dictate where the shapes and colors
go. This is the coordinate system, which gives meaning to an x-y coordinate
or a latitude and longitude pair. There are several systems, but as shown in
Figure 3-13, there are three that cover most of your bases: Cartesian, polar,
and geographic.