The greatest dataviz, that nobody has seen…
By: Luuk Van Der Meer
Tags: Dataviz, Fintech, Data Visualization, Design

One step back.

“Remove to improve” — it’s an expression used in countless professions and can, crazily enough, also be applied to data visualizations. Edward R. Tufte introduced the concept of data-ink ratio in his classic “The Visual Display of Quantitative information” in 1983. The concept talks about removing most of the non-data ink/pixels to improve the data to tell its story. Most people who are serious about data visualization will or have probably come to know this concept. The data-ink ratio can easily be applied to dashboards and other visualizations where you expect the audience to already be interested. But what if you need to convert people and get them engaged towards your story? By applying the data-ink ratio and holding onto it too much, we could lose our users within the onboarding process, because maybe we’ve removed an easy to digest piece of context.

I think there are several reasons why designers should consider onboarding, but I want to highlight three of my main reasons: ambiguity, irreversible growth of data and conversion.

Ambiguous figures

One of the reasons why we should consider onboarding is because of the ambiguity of data visualization. Most data visualizations are telling multiple stories at once. Now you might think; how is that possible, it’s only one figure, right? It has everything to do with the “curse” of knowledge and Steven Franconeri pointed it out during the Openvis Conference 2018: “Knowledge and expertise can literally change what you see.” When I create a more complex visualization about a certain topic, experts about this topic are likely to see this visualization differently than I do. The visualization tells them a more detailed story. It’s like an “Ambiguous Wally” figure: whenever you spot Wally in a “Where’s Wally” figure, the figure looks different because you’re now cursed with the knowledge of Wally’s location.

Onboarding can help a lot by making data visualization less ambiguous.

Ambiguous Wally

Growth of data

Besides us humans being responsible for the growing amount of plastic into our oceans, we’re also responsible for the ongoing growth of data. Data is growing, but with help of intelligent software we can unfold these big piles of data and discover the relations within. But we still have to tell the story of the unfolded, complicated data. Most graphs, for example line graphs, bar charts or scatterplots, are well known to most people. Main reason for this is that we have been taught the function of these graphs at primary/high school. The only problem with these kind of graphs is that they’re not always able to tell highly complicated stories efficiently. Maarten Lambrechts (2018) suggests that we should all start acting like William Playfair (great inventor of the bar chart and line graph but also the pie chart 😢). By creating more custom and perhaps weird visualizations we could solve this problem.

Within these custom visualizations we can combine multiple dimensions at once, which provide the possibility for getting better insights out of complex data. But these custom visualizations need some kind of onboarding to reveal their true power.

Conversion

For this it’s maybe nice to have a look at Reif’s Larssens Fairly Unscientific Graph of an Infogasm. As mentioned, it’s unscientific, but it shows Reif’s process of processing information when he looks at an infographic. First, Reif is really excited about all the information he instantly understands…..then he realises he doesn’t…….and then he gradually starts to unfold the infographic like reading a paragraph.

From a conversion point of view, it’s important to realise that people need to understand quickly and easily how the data visualization works and what it could mean to them. According to research conducted by Lindgaard, Fernandes, Dudek, & Brown (2006), people make up their mind about a website in the blink of an eye. I don’t know to what extent this conclusion applies to data visualization, but it tells us something about their attention span. We might grab their attention by gradually telling people a story.