Constructing and Evaluating Your Design Solution - Data Visualization: A Successful Design Process - page 165

We saw an example of this in the discussion about color in Chapter 4 , Conceiving and
Reasoning Visualization Design Options . Here we saw an initially conceived title format
for an Olympics project that was formed out of thumbnail images of all the historical
event posters; this image is shown here:
When it came to incorporating this title into the final piece, it was clear that it drew
too much attention away from the rest of the visualization. Despite this being
obvious, because of the time and energy spent on making this title image, it was hard
to relinquish. Thankfully, a sensible voice determined that we should drop it and
find a simpler solution. Simple advice? Take the hit and just get over it!
Image from "Pursuit of Faster" ( http://www.visualisingdata.com/index.php/2012/07/new-
visualization-design-project-the-pursuit-of-faster/ ), by Andy Kirk and Andrew Witherley
As we approach the maturing stages of our development work, this idea of getting
input from others becomes more important. It can be quite a tough moment to
convince yourself that something is ready to be judged (in a prelaunch setting) but it
is invaluable to test out people's responses to what you are creating.
You want people who are informed about the context of the work and also about the
challenges involved in creating a visualization. You also need to trust them to give
you constructive and reasonable feedback, otherwise it may prove a wasted effort.
You should be seeking feedback on a number of dimensions of your design in order to
determine if the intention of your solution is consistent with the audience experience:
• What is their instinctive reaction? Positive, negative, intrigue, confusion, or
just a plain "so what?"
• Can they understand how to read the graphic or use the tool? Does it have
clear explanations and intuitive design in terms of visual hierarchy and
structural arrangement?
• Can they derive insight from it? Maybe throw them some test questions to
assess the visualization's ability to effectively inform.
• Does it work functionally? Can they find any errors, mistakes, programmatic
errors, or any other design flaw that undermines the clarity, accuracy, or
performance of the solution?