Graphics Reference
In-Depth Information
Sometimes subjects are fundamentally simple and the portrayal of the data is
straightforward and intuitive. This in turn means the reader's task of interpreting the
data should be relatively easy.
On other occasions, a data framework might be more complex. Your challenge will
be to respect the complexity and avoid simplifying, diluting, or reducing the essence
of this subject. This might mean something is not immediately easy to interpret.
Some visualizations will require effort to be put in, forcing the reader to undertake
a certain amount of experiential practice in order for the eye and mind to essentially
become trained in reading the display.
Think of it being like muscle memory, but for the eye and the brain. We are so
used to reading bar charts and line charts that they have become entrenched and
programmed into our interpretative toolkit. But when we are faced with something
new, something different or seemingly complex, its not always immediately clear
how we are supposed to handle it.
In the following example, we see a demonstration of what is quite a complex data
framework. This is an image of a legend that was used to explain how to read an
innovative visualization to portray three separate indicators of a movie's success.
On the left-hand side of the image is the aggregate reviews (the higher the value,
the better) and on the right-hand side of the image are both the budget and gross
takings (the bigger the gap, the better):
Image from "Spotlight on Profitability" (
http://www.szucskrisztina.hu
),
created by KrisztinaSzucs
It is an unusual representation of data, not something as preprogrammed as the
bar or line chart, and so it takes a short while to learn how to read and interpret the
resulting shapes formed by the movie data shown across piece. This is absolutely
legitimate as an effective approach to visualizing this data so long as the efforts that
go into learning how to read it eventually leads the user to understand it.
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