[MUSIC PLAYING] EDWARD TUFTE (VOICEOVER): In the arrangement of visualization, every single pixel should testify directly to content. As Johnny Ive, the great Apple designer, said, we spend most of our time getting design out of the way. It’s got to get out of the away, because it’s about the relationship with the viewer and how they reason about the content. Style and aesthetics cannot rescue failed content. If the words aren’t truthful, the finest optically letter-spaced typography won’t turn lies into truths. There are enormously beautiful visualizations, but it’s as a byproduct of the truth and the goodness of the information. The big steps in showing information began all with cartography, about 6,000 years ago, when the first map was scratched into a piece of stone. And that has wound up now with the most widely seen visualization in the world, which is Google Maps, where people are using a visualization to actually do something. The next big step was development of real science.
Galileo got his telescope going. He saw things that have never been seen before. He made beautiful drawings of sunspots, and he’d watched the sun for about 40 days, and he did engravings of the sunspots. So he visualized what he saw. And so the history of visualizing data is, very substantially, a history of science. JULIE STEELE (VOICEOVER): Data visualization is not just some airy fairy, creative process, but it’s actually a very linear process of decision making that you can do based on some few basic principles. Three things should inform your design always. One is you, as the designer. What you have to say and what you want to communicate. Two is the reader. That reader is not you, and they’re going to come with their own context, and their own biases, and their own assumptions, and you need to account for that.
And third is the data itself, and what that has to say, and how that informs the truth. There’s a lot of subconscious brain activity happening. We evolved for it to happen that way. We evolved to see things and make snap decisions. Are all those lines in the graph just dried grass, or is that a tiger that’s coming to eat you? [GROWLING] We have to be able to recognize those patterns right away and make snap decisions on them in order to survive. And that can be an advantage as a designer. You can communicate a lot of information very quickly, because we all have brains that are designed to recognize patterns this way. But also, there’s the emotional impact. We react to design, and to art, and to the aesthetics of a piece, just as much as we react to the information contained in it.
And so if you want to change someone’s mind, if you want to change someone’s behavior, sometimes presenting the information in a visual format is the fastest way to get them to engage with that information. JOSH SMITH (VOICEOVER): Truth is one of those ambiguous things that you can’t really define, and probably changes and evolves, the more understanding you have. Data itself is a result of research. So I would say that data is just a clue to the end truth. I think a successful infographic tells a story. It communicates, hopefully, accurate and sometimes complicated data in a way that many people can understand. I think the first step, usually, is always dig really deeply into the data ourselves, and find each key point, and create a hierarchy, and a narrative out of that story.
When you start to merge different pieces of information, and when you start to learn really what it’s all saying, the narrative is clear. The one key fact that everything can revolve around, it’s the hero of the piece. There’s one single piece of data or insight that people respond to and kind of encapsulates the whole vision. And then invite people in to see the nuances and all of the rest of the story around it. When you look at a piece, it’s successful when it translates data from something that’s complicated to something simple. When it communications a message that otherwise would have taken somebody hours to digest and find in an instant. JER THORP (VOICEOVER): My deepest interest lies in the boundary between data and culture. Data are measurements of something. In very many cases, the somethings that we’re talking about are human systems. We’re dealing with data systems that are larger than anything that humans have ever built or experienced before. And these really large systems, things happen within them that are emerging. For example, Gate Change combined shot footage from airports, for pretty much every airport in the world, and then air travel data as well.
So the central idea was to show people that, every time that you’re in an airport, you are standing on the surface of a system that is almost too complex to comprehend. Any given time, there are more than a million people in the air. And so there’s another purpose of data visualization. There’s revelation, which is, show us something that we’ve never seen before. This is, for me, much more exciting. Anybody can visualize data in Excel and see some bar charts. For me, it’s about showing them something in this kind of loose narrative frame that they can interpret.
So we show them some pieces of the picture, and the idea is that they can sort of stand back from that and watch it pass for a little bit, and come out of it with some deeper understanding. Part of it is leaving it open to interpretation, but part of it is also not really knowing. I don’t have some masterful understanding of this system that you don’t. I have some ideas about how these systems might be changing, and how they might be growing, and how they may be important toward culture and society, and I want to share some of those ideas with you.
And maybe you can put together something that I wouldn’t have been able to put together. EDWARD TUFTE (VOICEOVER): I think in general, audiences are a lot smarter than a lot of people think. So it’s not know your audience, it’s respect your audience, and really know your content. That’s what you should be knowing and reasoning about. Look after truth and goodness, and beauty will look after herself. You want to see to learn something, not to confirm something. We usually see to confirm things. It’s very economizing for the brain. How can we see not to confirm, but to see to learn? [MUSIC PLAYING].