Graphics Reference
In-Depth Information
• The circle area represents the film's budget.
• The circle's color (hue) represents movie genre.
• Users interacting with this web-based design will also discover a text label
displaying the raw values by hovering over one of the bubbles. Text is not
universally treated as a visual variable but it is still worth acknowledging.
If you let your imagination run free and try to conceive as many visible properties
as possible that might be capable of representing series of categorical, ordinal, or
quantitative data, you will realize that there are many potential approaches. In fact,
in a fun recent experiment (
http://blog.visual.ly/45-ways-to-communicate-
two-quantities/
), visualization designer Santiago Ortiz proposed over 40 different
ways to potentially represent just two simple numbers.
Indeed, if you fully release your creative inhibitions, you can take things beyond
the visible or physical, as some of Santiago's suggestions did, and consider how
our other senses might be exploited in order to represent/interpret data through
channels such as sound, smell, touch, and taste. Just imagine how some of the
inherent variable qualities of our other sensory mechanisms could be capable of
distinguishing categories and values of data.
Anyway, back to more practical thoughts, for now, and a brief history lesson.
Once upon a time there was a man called Jacques Bertin. Bertin was a clever chap.
In fact he was a pioneering thought-leader within data visualization. Building on
the earlier studies from the Gestalt School of Psychology—mentioned in
Chapter 1
,
The Context of Data Visualization
—his topic
Semiologie Graphique
(1967) is one of the
subject's founding texts and represents one of the earliest and most comprehensive
attempts to theorize how we perceive and interpret different representations of data
through shape, pattern, and color.
Bertin determined that there were three main aims behind your choice of data
representation, moving from high-to low-level acts of graphical interpretation.
This is still an extremely potent way of organizing our thoughts and reasoning our
selection of the most effective visual variables. These aims are as follows:
• The highest level of Bertin's interpretive acts concerned whether we are
able to visually discriminate between different data marks or data series:
can we actually see and read the data being presented. We must make sure
that the way we visually distinguish different categorical and quantitative
values is legible and is in no way hidden by way of unnecessary clutter,
noise, or distraction.
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