Most people know how to read a bar chart and a line chart. But sometimes the data or the message requires a less common and more unfamiliar chart, that people first need to figure out how to read.
Reading a new chart has a high cognitive load, because the complexity of the data and the visualisation can be high (= intrinsic load, see the Reducing the cognitive load module) and the unfamiliarity of the audience means that the germane load is high. As a result, users need to wrestle through a high total cognitive load in order to understand the chart and recognise and retain the message.
So, as a chart author, you need help your readers by lowering the intrinsic load (this means simplifying a a chart, by showing less data for example) and also by lowering the extraneous load, by making the way the data is presented as optimal as possible.
Source: Infographics in the Time of Cholera, propublica.org
The line chart above appeared on the front page of the New York Daily Tribune on 29 September 1849. It shows the total weekly deaths and the weekly deaths attributed to cholera during an outbreak of the disease in New York City.
At that time, data visualisations were very rare in newspapers (and also outside of it), partly due to the technical challenges of analogue printing (printing illustrations and charts like the one above required engraving). It is safe to assume that many Daily Tribune readers had never seen anything like this chart before and still needed to learn how to read it.
The designers of the charts knew this, and made some design decisions to help the reader:
But more importantly, the chart is complemented with a very detailed description of how to read the chart and what to make of it:
“The zig-zag lines, which join the ends of these lines, show, by their upward or downward slopes, whether the deaths during those weeks have increased or decreased, rapidly or slowly.”
One lesson to take away from this chart and the way it was presented and introduced in 1849 is that there is no such thing as an “intuitive chart”. We are not born with the capacity to read line charts: it is a learned skill. If you have good arguments to use more novel, innovative and non-standard charts, you can decide they are worth trying. But just like the journalists of the New York Daily Tribune in 1849, you can’t assume your audience will just understand them.
As Scott Klein, managing editor at the data journalism website ProPublica, writes in the essay that identified the cholera line chart as one of the first data visualisations used in a newspaper, we shouldn’t shy away from using new chart types, as long as we help readers how to make sense of them.
“First, we must always keep our readers in mind. They have the potential to understand our graphics, but we must never assume our graphics are intuitive, without the need for explanations or directions. Visual and narrative clues about how to read them are vital and mandatory.”
“On the other hand, this also means we are not trapped into using simple forms. There is no pure set of visual types that conform to human nature and are thus intrinsically better than the others. We are free to experiment. If we keep our readers in mind, we can pursue new forms that delight them and help shed light on complex subjects in ways that have never been tried before. For the right story, our readers will put in the time necessary to understand even strange new graphical forms — like our line chart must have seemed in 1849 — if we only take the time to help them do so.”
Research has shown that only six out of ten (American) adults managed to interpret a scatterplot correctly.
Source: The art and science of the scatterplot, pewresearch.net