Data visualizations that matter

So I'm toying around with the idea of infographics and data visualization. I was recently inspired by this Mashable article about Jer Thorpe, who is 'Data Artist in Residence at the New York Times' - an awesome title he made up himself. 

Here's one of the key things that struck me about this interview:  

What's your advice for people aspiring to get into design and specifically data visualization?

It's the same thing with almost everything. There are so many people who I hear from who are like, 'I really want to do this, what are some books, what should I read?' You just have to do it. And, the sort of underlying secret about data viz is that it's not that hard. We're doing a very simple act, we're taking (usually) a number, and we're mapping it to something, whether that's mapping it to a color to a size or to a position on the screen. Anybody can take a set of numbers and think about ways you would draw that on a piece of paper. The two things that I always tell people is that: First you need to just get started with it, and admit that the things that your first projects are gonna suck, and that's okay. Y'know, you can't expect to make something beautiful the first time. My first data visualization was terrible.

The second thing I tell my students is to think about something that's close to you, something that's personally relevant to you. If it doesn't resonate with you, you're not gonna do a good job with it. We live in a really cool world right now where there's a lot of data that's accessible to us, whether that's your location data over time, your email transactions.

The reward of data visualization comes from discovery, and if you're not doing something where that discovery is going to feel like a revelation of some kind to you, then you're not gonna get it.

I LOVE THIS. Why? Because it takes the fucking mystery out of it. 

Many years ago when my researcher colleagues and I at Sun Microsystems were interested in getting into competitive intelligence, it felt the same way. CI was this practice shrouded in mystery - none of us could really get at how one did it. We took some courses, we joined SCIP, we read books, but we still seemed stuck when we thought about actually doing it. 

I finally went to a pre-conference workshop at a SCIP conference, and I don't remember a lot of what was taught at that. But the key turned for me at the outset of the workshop. The instructor, Ken Sawka, said simply: "Competitive intelligence is information plus insight."

The light went on. I suddenly felt like the veil had been lifted and it all didn't seem so intimidating any longer. 

I got back and I decided to jump in. I went to one of my long-term clients and I said, 'would you be willing to work with me on a CI project?' He enthusiastically said yes, and so began my competitive intelligence career. 

I've been feeling the same way about data visualizations. Ultra cool, would love to do that. But how? 

Thank you, Jer - for the insight, the removal of the mystery and the permission to create at least a few crappy visualizations. It kind of feels like the birth of punk - you get instruments and you just start playing. It's horrible at first, but sometimes something great emerges. 

So what to visualize? The idea for a first visualization popped into my mind when I was conducting research on chronic conditions in the United States - diabetes, heart disease, hypertension. I came across some information (that I've since lost track of and need to track down again) about how many people in the US - adults and children - are on anti-depressants. It was a striking number, in the millions. IN THE MILLIONS. 

This is data that meant something to me. So I'm going to track it down again and see what I can do with it to make it more visually meaningful. 

In the meantime, I was looking at statistics on suicide in the US. I was struck again by the information I found.

• Since at least 2007, suicide has been the 10th leading cause of death in the US.
• It is the 7th leading cause of death for men in the US.
• It is the 3rd leading cause of death for people ages 15 - 24. 

• Men are four times more likely to successfully commit suicide, but women attempt suicide two to three more times than men. 
• Older Americans are disproportionally more likely to die by suicide, especially white men over the age of 85. 

 These are heartbreaking. But let's look at some other numbers. 

• In 2011, 38,285 people died by suicide in the US - more than twice the number of deaths by homicide. 
• For every death by suicide there are 11 attempts. If we do the math, that means there were 421,135 attempts in 2011. 

So, using these numbers, here's my first visualization - on suicide. 

 

 

Simple graphic. I tried to get the proportions about right.

Maybe not so crappy for a first attempt.

I think it's these kinds of numbers and this kind of information that make visualizations powerful. What could you draw from this? 

• That's a shit ton (I'm pretty sure that's the clinical term) of suicide attempts. 
• There are a shit ton more attempts than successful suicides. 
• These are scary numbers. I think we have an issue on our hands. 

My little visualization won't change the world. But it gives me a different way to grasp the issue. That, to me, is the true power of visualizations. 

Thanks again, Jer. I'm glad you put a guitar in my hands.