Since reporting on the first issue of Nightingale: The Journal of the Data Visualization Society, something remarkable has occurred: A second edition has been published. That says a lot. But to expand on the story of this much-needed publication, I’ve asked one of its founders, Jason Forrest, to return with an update.
Dataviz is even more important than ever in harvesting information—separating the wheat from the chaff and keeping the … well, you know.
It has been six months since your first issue of Nightingale. How’s it going?
Great! We’ve published a ton of great digital articles, doubled our subscribers (don’t worry, we’re still tiny), and we’re just super excited about the latest issue, which is all about inspiration!
Is data visualization still as open to innovation as it has been over the past 10 years? Or have designs come full circle back to “it looks nice”?
We’ve been talking about this in the dataviz community a lot lately. Data continues to be incredibly important in our lives, but what value does it have if no one pays attention? That’s why the design of dataviz becomes so important. While Nightingale has been promoting dataviz with a design edge, we also emphasize the fundamental importance of being true to the data and the audience it is intended for.
I’d also argue that the design of dataviz isn’t returning to a design sensibility from a decade ago, but rather embodying design concepts that may have been too difficult to achieve technically before now.
What are the stories and themes that you find most engaging for designers and data specialists?
This issue is about inspiration, and our editors started asking questions about how to quantify, track and evaluate it. What is the true value of dataviz if not to inspire others? We want to understand the data of inspiration beyond mere social media metrics.
Have you found the cure yet for misinformation?
I think many of us working in dataviz feel like we’re part of the solution—or at least trying to be! This goes back to always being true to the data and the needs of your audience.
Kids have to be taught data as language (e.g., reading, writing, arithmetic = data). Is that the reason you produce a section for kids?
The fact that we culturally diminish mathematics is just kind of lame. Lots of kids naturally collect or organize their toys and like to think about how to categorize things. At Nightingale, we think that giving kids a new angle into understanding all of the information around them as “data” can empower them to think about math differently. Data science, analytics, visualization—these fields aren’t going anywhere, and we want kids to understand that there are a million—fun—ways to work with data.
Incidentally, do you think dataviz should be taught in elementary school? Get ’em while they’re young, I say!