Conceiving and Reasoning Visualization Design Options - Data Visualization: A Successful Design Process - page 85

It is unfortunately not as simple as that. If it was, I don't think I would need to
write this topic. As we've seen earlier, we rarely only have just one data variable
to communicate. You will therefore often need multiple visual variables to
communicate multiple data variables.
However, above that, and returning to our section introduction, how accurate
do we really need the interpretations to be? Do we actually need to facilitate the
reading of exact values from every visualization we create?
Alternatively, can we allow ourselves more creative freedom by recognizing that in
some cases just being able to facilitate the relative order of values may be sufficient
for the context and requirements of the design?
If you recall in the first stage of our methodology we discussed the importance
of trying to define, as early as possible, the functional and tonal quality of your
intended design. The tonal judgment, in particular, is the important matter right
now for this is what separated those pieces that matched an analytical and
pragmatic style from those that were more abstract or emotive.
In this image we see a selection of visualization styles and demonstration of the fine
balance being judged between design creativity and interpretive accuracy based on
the contextual requirements. Let's take a closer look at each one at a time:
• The "wind map" on the left-hand side of the image doesn't aim to facilitate
the reading of exact values. The use of pattern density to indicate the
strength of the wind, as shown in the hierarchy table, focuses on delivering
a sense of those areas with strong wind (as well as its direction)and the areas
where there is little wind. The elegance of the resulting design makes for a
compelling visual that draws users to interact and learn about the patterns.