Great Data Visualization Tells a Great Story

Think of all the popular data visualization pieces out there – the ones that you always hear in lectures, read about in blogs, and the ones that popped into your head as you were reading this sentence. What do they all have in common? They probably all told a great story. Maybe the story was to convince us of something, compel us to action, enlighten us with new information, or force us to question our own preconceptions. Whatever it is, truly great data visualization reaches us at a very human level and that is why we remember them.

Let’s face it. Data can be boring if you don’t know what you’re looking for or don’t know that there’s something to look for in the first place. It’s just a mix of numbers and words that mean nothing other than their raw value. The great thing about statistics and data visualization though is that they provide us with the tools to learn that the data are much more than a bucket of numbers. There are stories in that bucket. There’s meaning, truth, and beauty. Sometimes the stories will be simple and other times complex. Some will belong in a textbook; others will come in novel form. It’s up to the statistician, computer scientist, designer, or analyst to make that decision.

Show the Story in the Data

I first got my hands dirty with data visualization when I was at The New York Times for a summer. I had just finished my second year of graduate school and hadn’t made a whole lot of infographics up until then. I had seen plenty of examples and made graphs and such in R for reports, but creating graphics as an intern for the greatest graphics department in the world – that was intimidating.

It was obvious I had a lot to learn right from the start, and during my three months there, I learned more about data visualization than I ever had – design, organization, fact checking, sleuthing, and research. But let me share with you the most important lesson I learned at The Times (that didn’t really click in my head until much after): tell a great story and the data visualization will follow.

Take a look at any New York Times graphic. They present the data clearly, concisely, and ever so nicely. What does that mean though? When you look at a graphic, you get the chance to understand the data. Important points or areas are annotated, symbols and colors are carefully explained in a legend (or with pointers), and the Times makes it easy for readers to see the story in the data. It’s not just a graph. It’s a graphic. It’s why The New York Times graphics department gets so much attention.

Sure you could make a line chart or histogram with default settings straight out of Excel, but where’s the story? Character development? Each and every data point means something (which I learned as I spent a whole day trying to verify a few numbers) – a drowning death because there were too few lifeguards, strict court rulings from a new judge, or whatever it may be.

Humanize the Data

The New York Times is objective. They present the data, give you the facts, and (usually) leave it to you to make your own conclusions. They do an excellent job at that. On the flip side is data visualization that is less about analytics and more about tapping into your emotions or other people’s emotions. Are you thinking of who I’m thinking of?

Jonathan Harris does excellent work with data visualization as story. In fact, as he explains in his TED talk, that’s exactly what he strives to do:

Artist and computer scientist Jonathan Harris makes online art that captures the world’s expression – and gives us a glimpse of the soul of the Internet.

Take a look at Jonathan’s past projects, and it’s not hard to see why his visualization is so often referred to. His projects are stories and let you explore the data and leave the door open for you to connect to each data point. I Want You to Want Me touches on love and hope; The Whale Hunt exudes death and anxiety; and We Feel Fine explores the entire range of human emotion. There is beauty and an emotional aesthetic to these visualizations that traditional statistical visualization doesn’t normally tap into (but should seriously give it some thought). It’s that very human aspect onscreen that we remember.

Compel to Action

S/he who can tell a great story possesses great power, because s/he has the power to move people. Data visualization can show that story for you – or you can show people yourself. Take a look at Gapminder. It’s a relatively basic visualization tool. It’s not really all that pretty and doesn’t follow a whole lot of design principles. In fact, I’ve heard first-hand from designers that Gapminder is just plain ugly.

We all know about it though and were most likely impressed the first time we saw it. Why? Because we saw Hans Rosling give his amazing TED talk with such conviction, especially for someone who was talking about data. Of course, the sword swallowing really drove the point home. Hans told a great story. After I saw that talk, I wanted to use Gapminder, explore the data, and see what Hans was talking about.

I later saw a Gapminder talk that wasn’t as impressive. The speaker, who was not Hans Rosling, talked about the same stuff and pointed out the exact same trends, but the emotion was not there. I did not feel the conviction from the speaker’s voice. The data visualization was just another run-of-the-mill animation. Imagine though, if Hans Rosling’s story were conveyed in the visualization. That would be something to see, right?

When we talk about visualization and maps for advocacy, we should also consider how to achieve that emotional connection. Reverse the title of this post, and the same thing rings true. A great story can make a mediocre data visualization great. Al Gore’s elevator lift also comes to mind. Anyways, you get the idea.

The Lesson: Find the Story

Approach data visualization as if you were telling a story. What kind story are you trying to tell? Is it a report or is it a novel? Do you want to convince people that something is necessary? Think character development. Every data point has a story behind it the same way that every character in a book has a past, present, and future. There are interactions and relationships between those data points. It’s up to you to find them.

Can you think of any other great data visualization that tells a story?

*Photo by wellyg