How do graphic objects in data visualisation facilitate ease of interpretation?

Question

Background: I vaguely remember reading in a book (I think it may have been Nudge - Thaler and Sunstein) about the advantages of using graphics for visualising data, such as a smiley face, or traffic lights, to communicate a message in an easily interpreted, visual language.

• To what extent do graphics such as smiley faces and traffic lights in visualisations facilitate ease of interpretation?
• What is the cause of this ease of interpretation?
• What research has studied this phenomena?

Initial thoughts: I imagine that the ease of interpretation is due to these items being purely visual that we quickly recognise them, and they can make complicated, unfamiliar information (for instance health results) that much easier to comprehend. Is that an accurate summary?

If it's any further help I'm looking into this specifically for use in the communication of health results. So for example if you have a 20% risk of developing a disease, a good way to illustrate this could be 100 smiley faces - of which 20 are :( and 80 are :)

Answer 1

This is a great question. I'm not a cognitive psychologist by training, but I can offer a usability perspective on this from a person who is a trained cognitive psychologist. Jakob Nielsen recommends using icons when users don't have to guess what they represent. If the icon is vague, there's no additional benefit to including an icon with your label. It might actually confuse people. People aren't going to understand the meaning of your icon as well as you probably assume. This is because you have an expert bias in choosing your icon.

It doesn't sound like you're creating an interface. You say you'd like to visualize data using graphics like smiley faces. Emoticons (smiley faces) are the one exception to this icon rule. People immediately recognize emotions and faces. Our brains are hardwired to turn anything into a face. Every car has a face and an emotion, for example. The first thing you recognize when you look at a picture subconsciously will be the expression on everybody's face. In eyetracking studies, the first thing people notice in pictures is faces.

This is getting really deep, but on the subject of smiley faces, the more simplified the face, the more we project ourselves into the character. The character can be drawn very realistically, and it looks like a photographic picture. In this case, you are an observer looking at the character. Or the character can be less detailed. In this case, you become the cartoon character. This is why cartoons are so universal and permeate our culture.

Your representation of a face in your mind is like a cartoon. You don't see yourself wearing a photographic picture of your face. When you're smiling to someone, you see yourself with an upturned mouth. You see yourself wearing a very simplified smiley face. That's the abstract idea of your appearance in your mind. It's like looking at a bike. You don't see two wheels, a frame, and so on. In your mind, you see the abstract concept of "bike."

The more simplified the cartoon, the more we identify with it. This is demonstrated well in japanese comics. When the artist wants a character to seem otherly or distant from the reader, he draws them very detailed.

So if you want people to feel a certain way about your data, they will automatically empathize with the emotion of the cartoon characters you draw. Hope all this explanation answered your question and was relevant. ;)

Edward Tufte

If you want to dive deep into data visualization, buy any book by Edward Tufte. Envisioning Information was awakening for me. The Quantitative Display of Information might be a better place for you to start. The graphics aren't as colorful and pretty, but it really gets into data visualization. Tufte's books are seminal.

Answer 2

As you mentioned, data visualization and visual stimulation in general, trigger a primitive brain response, which results in an easier comprehension and engagement/rejection process - a process more trivial than sensing and comprehending symbols. Thus, numerical information such as percentages, distributions, and relativistic data in general, immediately get infused into the cognitive realm, provided the visual field is not excessively cluttered. Too much visual stimulus in a presentation results in a more laborious attempt at comprehension, and hence may lose favor.

When it comes to non-numerical / non-quantitative data, visualizations serve as a promoter of cognitive engagement. Traffic lights to draw attention, smiley faces may be used to encourage the receiver, boxes and other demarcations to engrave specific items of information in memory, the list goes on.

I think the effectiveness of the visual presentation largely depends on the creativity and imagination of the presenter to resonate with the target audience, in terms of the mood, awareness, humor (mood?), social values and other variables which maybe of interest, of the target audience.

Again, if the visual field is excessively populated, the labor involved in the comprehension process may impede the effectiveness of the presentation.

Also, the ease at which visual information is processed also depends on how distinct the objects that are communicating information in the visual are. In your example, smiley faces to depict percentages maybe less effective compared to, say a colored pie chart, or something to that effect, because smiley faces are not easy to distinguish by themselves - even if they are ordered into separate regions. And in the possible event of conveying grim news , grim graphics may not received in the highest of spirits :P.

Cheers!