A new app turns any New York City subway map into a highly addictive, augmented-reality tour of urban data, including median incomes and rental prices, that’s easier to navigate than the map itself.
The app, called Tunnel Vision NYC, is the work of William Lindmeier, who developed it as part of a master’s thesis at NYU’s Interactive Telecommunications Program. After discovering a wealth of data on NYC Open Data, Lindmeier decided to pull from two sources, the MTA and the U.S. Census Bureau. Taken together, the datasets form a visual portrait of a city where salaries and rents run the gamut but whose residents are connected by a single subway system.
But enough poetry about urban life. The app itself is worthy of a download. Go ahead; it’s free. Then simply point your iPhone at a map (or a PDF version of one on your desktop) to display another layer of subway data, such as where people exit and enter stations and where trains should be along the track, according to their schedules, which probably isn’t an accurate predictor of when they’ll arrive.
The more meaningful data are about the neighborhoods bordering each stop. Move around to see what median household incomes and rents were in 2010 near Chambers Street ($73,438; $1,538) vs. 125th Street in Harlem ($23,957; $805), as well as the percentage of people in those neighborhoods who speak only English at home (42.9 percent around Chambers; 53.9 percent in Harlem). The beauty is in how the information is rendered—in 3D visualizations that pop off the screen and track with your phone’s orientation.
Lindmeier used Vuforia, an image-recognition platform, to build Tunnel Vision. He says the subway map was especially well suited to the project, because it’s recognizable and widely available, and its high-contrast graphics are easy to track with augmented-reality software.
The designer, who presented his thesis last week, says he’s content to let the app “breathe” for a bit before extending it to other cities or adding more datasets. But it should serve as inspiration for the MTA, and similar systems around the world, to invest in wiring their subway platforms and publishing real-time data on subway arrivals. “That would be a win for this kind of data representation,” Lindmeier says, ”because then you could show more granular data for every single train.”