Someone once accused me of not doing visualizations. Although that is not actually true (I’ve done more than one and so that means there are a lot of people out there with a bad memory) However, I have to admit that it’s not a really my job.
My job, my function in the Visualization department – apart from designing user friendly interfaces, of course– is to make the visualisations of my team more understandable:
Trying to prevent them putting 20 variables in the sae graphic in an attempt to demonstrate that it can be done, just for the sake of it.
Sometimes I managed to do it. Sometimes I didn’t.
That’s the reason why I decided to write this series of blog entries dedicated to analyzing things that are not clear or aspects that could be improved upon, always from the UX point of view.
Taking Tuftte’s work as a base, Fernanda Viegas and Martin Wattenberg wrote a blog entry titled Design & Redesign which suggested that Data Scientists should not only criticize other people’s work but improve on it with suggestions on how to redesign the visualization and I’ll try to analyze them respecting their original style.
First I’ll confess that I chose this representation: Jounals, because I thought, at first glance, that it was appealing and easy to analyze. I also wanted to prove that my point of view coincided with, or at least complemented, the view of experts (my boss basically). And they did.
The first problem we see is that depending of the subject or type of publication we see a different time period (from 2004 to 2013, from 1970 to 2010…)
The question is why not represent the same time period for all graphs to show that they don´t have any data in some years.
A different problem is the time step which is changing throughout the different graphs: every two years, every five years…
After thinking about the color range, in the end, I deduced it was not relevant. The color range selected only tries to differenciate one line from another, but some users could have thought: Does the range (Blue, red, green) mean something? Does the color intensity mean something else? Is the light blue more relevant than the dark one?
And the last and most important design error: Why are some totally different values represented with the same/similar radius?
The basic problem is that for every line they have changed the relative radius. So if you don´t see the values beside two similar circles you might think they are hiding a similar value, but they don’t. One circle could have a value of 20, while a similar circle could have a value of 2. So at first glance, and without any interaction you can’t compare the two graphs (or even two lines) easily.