In the early aughts, Kim Rees loaded a single website and had a life-changing experience. It was IBM’s Glass Engine, an interactive visualization of composer Philip Glass’s work. The software featured some amazing capabilities, like rearranging over 60 of his compositions with a few clicks of a mouse. Since graduating from NYU with a computer science degree in hand, she’d worked on interactive installations, Flash games, and more traditional web design with partner Dino Citraro. But the Glass Engine was different. It was information she could actually hear and feel.
“I remember how excited Kim was when she found it,” Citraro writes, “and looking back on it now, it was an epiphany moment for us both.”
“It was such a profound change in my way of thinking, we decided to focus just on data visualization,” Rees tells me. “So we formed a data visualization company.”
There was just one problem. This was 2004. Nobody knew what the heck data visualization was yet.
Today, alongside Citraro, Rees runs Periscopic, a “socially conscious information visualization” company that promises to “do good with data.” Their clients have included Google, GE, and the Bill & Melinda Gates Foundation. She’s also an advisor to the U.S. Congressional Budget Office. So roughly once a month, Rees looks over Congress’s own reports to ensure they’re as clear and unbiased as possible.
But back to the year 2004. Blogs were a novel idea. Myspace had just launched. Touch-screen smartphones didn’t exist. Storage, however, was just getting cheap, with consumer hard drives reaching into the GBs and a new SATA standard making them fast to boot.
“We were seeing more interest in large databases, but there was a lag in the sense-making part of it,” Rees says. “If you store a lot of data it does you no good unless you can understand it.”
Ten years later, this is still the core problem driving data visualization. Our ability to sense and record information has vastly outpaced our capacity to understand it. From GPS to Facebook likes, we’re likely talking about trillions of new data points recorded, somewhere, every day. So the issue remains—these 1s and 0s are useless to us unless we can begin to synthesize them into actionable policy.
“It was really a tough sell in the beginning. People didn’t understand it,” Rees says. “It wasn’t until we’d developed one or two projects that we could show people, then it was like a lightbulb. It allowed them to realize that there’s a power in delivering that raw stuff they didn’t know what to do with or how to explain to people.”
Periscopic caught a break when EcoTrust brought them 70 pages of dry, scientific data, intended for a broader audience capable of shaping policy. Periscopic shamelessly over delivered by creating a tool featuring a multitude of filterable visualizations, from geotagged population densities to radial species extinction trends. They were left with a showcase piece to land more clients, as well as a philosophy that would ground their work.
“Our goal is to communicate what the data is saying and allow people to have their own ownership of that data,” Rees explains, “so as they’re looking through it, they can say, ‘I see what they’re saying! And I can confirm it!’ We allow the visualization to be almost a fact-checking tool for the end user.”
It’s a dialogue with the user based upon information transparency. And ultimately, that dialogue is a vital grounding component of socially conscious work. In a recent project, Periscopic visualized the years of life lost to shooting victims. If you haven’t seen it, I urge you to take a look now.
Their gimmick was to show you every single lifeline cut short by a shooting. In other words, their only stunt was to deploy a heavy dose of objectivity–every scrap of data they had on gun violence, presented at once. The result is a chest-tightening, tear-jerking portrait of the cost of life due to handguns–and it’s so much more overwhelming than the power stats, like that 80% of all gun deaths occur in the U.S.
“If I just told that person a statistic, maybe they would believe it or not believe it,” Rees says. “But if I gave them all the data, then they can see that for themselves.”
“We don’t think guns are good … [but] we don’t want to turn people away, which is part of the problem we get into when we become less objective. The other side of persuasion is propaganda. The further you get into that direction, you alienate people, you start preaching to your choir, and that’s a problem.”
The more I hear this info-heavy view of data visualization, the more I realize how wrong some of my own conclusions have been. I’ve always thought of data viz–of all these infographics–as a pretty pre-chew of data. Information is simplified so, at a glance, we can understand it.
But that’s not Periscopic’s purpose, not at all.
“I don’t think the goal of vizualization should be that precog understanding, giving you something so quickly that you don’t have to think about it; I think the goal should be that you do have to think about it,” she says. “I want people to have a brain, to have a say. I think it’s becoming only more important as we tackle more nuanced information. I don’t want the computer or the creator to tell me what to believe. I want an opening to say, ‘let me look into that machine.'”
“We are trying to encourage people to take an objective look at what’s actually going on, and then draw a conclusion,” Citraro tells me later. “To us, that means trusting that people will be open to embracing the complexity of the information, without the need to simplify.”
Because of this philosophy, Periscopic refuses to round their creations down to the lowest cognitive bidder. They can be downright tough to understand at first glance, challenging your intellect by requiring some level of decoding. In fact, Rees tells me that in their own research, testers have often drawn correct conclusions regarding the information, but been a bit unsure of their own read.
And that’s OK, Rees says, because it beats the alternative.
“I’m looking into kindergartens for my oldest boy right now, and one of the things we’ve heard is, ‘we teach to the top, and we support the bottom.’ I would like to think of us as doing the same thing,” Rees says, “that we’re presenting information to be clear, concise, and comprehensible, but also sophisticated, elegant, and attractive.
“We’re not going to dumb it down because we don’t want to teach to the lowest common denominator. We don’t want to take everyone back down to bargraphs!”
Indeed. The horror.