- [Instructor] In this video I'm going to talk about the necessity for clear legends, so that users understand what they're looking at in your visualizations. And also the importance of including your sources. These details can make or break an information design or data visualization project. Legends, sometimes called keys, are those explanatory queues that are often found in the bottom right-hand corner of a chart, and so even when you create a chart in Excel it sort of puts them over there on the right-hand side, it helps the viewer understand what they're looking at.
In the most basic form of a chart, like this one here, where everything is labeled, there's really only one thing, I know how many Snoods each one of my Whatchamacallits has, and Whosawhatsits, et cetera, I don't really actually need a legend in this case, it's one of those rare times when I don't, but for the most part, you're going to need legends, especially if you start adding weird shapes or colors, or, more data, more layers of data, in this case I need to know what the Tally Hos are, versus the Hither Tos and the Be Bops. If we don't include a legend, if I can't understand what these different colors mean, then I'm creating art, it's not pretty art, but it is just a picture, there's no knowledge, there's no value here.
But my job is to inform people, not just to create pictures. Better than a legend or a key that's off to the side, by the way, is in-line labeling. If you can include your labels identifying color values, shapes, and the like in this way, you're helping your audience keep their eye on the data, which will always be better than forcing the tennis match watching, back and forth, swivel head behavior a legend requires. Zen Buddhism has a concept called beginner's mind. And the idea is that you should come to everything with an open mind, without any preconceptions.
This can be hard to do when you're doing data visualizations, when you're working on something for a long time, it's very detail-oriented, you know everything about it by the time you're done, and trying to think of it as someone who knows nothing about it can be difficult. But if you can channel a child's mind, or a novice's mind in the topic area that you're discussing, if you can get to a point where you have great user empathy for people who know nothing about what you're showing them, then that will help you understand what's hard for them to understand, which will help you figure out what you should include in the legend.
Sometimes you need more than just a legend, especially in interactive graphics, so this hospital pricing visualization that I shared earlier, there's a lot going on here, there's first of all a ton of data, there's different colors, there are these different-sized bars, there are two different types of bars, if I click into this thing, I get a lot more detail, what do these dots mean, what are these axes, what are these other bars, there's a lot here. And so, no little legend or some labeling on this screen is going to do me justice to understand it. Even if I was fairly knowledgeable about this topic area.
So what I always do, especially for interactive graphics, is I actually create an entire how-to, I'll take a screenshot of the interface, and I'll look at it, again with that beginner's mind, what might I not understand, and I will draw little lines, and I will label everything, I won't leave it up to anyone's imagination, what's going on here, make it very, very clear of what all the details and shapes and colors represent. The other thing that I always include in screens like this, usually at the bottom, are the notes, sources, sometimes it's just about the data, just where the data comes from, oftentimes I'll also include notes on the technology.
One of the most important reasons to provide sources is for credibility, so if you're creating a visualization on a topic, especially if it's a controversial one like politics or climate change, then when you provide your sources, it'll allow your users, whether they're believers or skeptics, to look at the data themselves. And this has two advantages, one, credibility, as I mentioned, in that they can disprove your thesis or confirm your thesis, or at least get the sense that they have the opportunity to judge you based on the merits of the data, and not just have to take you at your word for it.
And the other reason is that a lot of your users, if they're interested in the topic area, might want to dig deeper into the data themselves, so by providing a resource, you're actually being a good citizen and giving them access to the information that they can go play with on their own. If your mission is to inform your audience, which I would argue it should be, if you're in data visualization, then that's great. If not, then you might want to try another calling. Data visualization can be a long and complicated process, and when you're finished, the last thing you want to do is all the busywork, going through the details, like the legends and the sources and the how-tos, but it really is as important as everything else that you're doing, don't rush it, don't neglect it, give it the time and effort that it deserves.
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