Q&A with Nathan Yau
Today, we're kicking off our new feature: the Visualizing Q&A, where we'll introduce you to some of the designers behind the work you see at Visualizing.org. Got questions for them? Comment on this article!
We're happy to feature Nathan Yau this week - a visualizer that frankly needs no introduction. He's the mastermind behind Flowing Data and a current UCLA PhD candidate in statistics with a focus on data visualization. We asked him a few questions to get his take on what's new, what's cool, and what's in store for the world of data viz.
A sample of Nathan's work:growth of Walmart is a good one. At the time I made it, I was just trying to learn Flash and Actionscript. It's really simple (and I can think of a number of ways to improve it now), just showing a new dot for each new store, but it seems to have resonated with a lot of people, and it's been fun to see the response. V: What’s the most exciting development that’s happened in the field in the past year? NY: Visualization-wise, the most exciting thing for me has been the improving browser technologies that let visualization run native in the browser. It makes development easier and faster, and visuals can be dynamically generated. What's more exciting though is the growing availability of data. There's simply more to visualize, and we can ask (and answer) more questions now. V: Where do you see data visualization heading in the next couple of years? NY: Visualization is going to be more interactive, adapting to the type of data that's available. Although there will still be a place for static graphics. My hope is that designers will become more data literate and that data-centric people will become more in tune with aesthetics and design. There are a handful of people who have all of the above, but for the most part, it seems disjoint. This is why we have so many graphics that tell us very little but are nice to look at and graphics that could potentially tell a lot, but the ideas are communicated poorly. As a result, those who can design and provide thoughtful analysis really stand out. From the consumer-side, people will learn to see data better and learn what to look for. Now I'm not saying everyone's going to be an expert in statistics, but they will (I hope) at least know what's good visualization and what's just a bunch of smoke and mirrors. V: What's one visualization or data set you’ve always wanted to tackle but haven’t yet had the time? NY:There's been a surge in health data recently, and I think it has the potential to help a lot of people. It's kind of sparse and not super manageable though, so it'll take some serious data munging before you can do something useful with it.