A visualization published last week places viewers inside a New York City taxi, tracking the car as it picks up and drops off fares across the city’s boroughs. The visualization, created by Socrata Data Solutions Architect Chris Whong, is based on data that became available openly for the first time after Whong obtained it from the city’s Taxi and Limousine Commission through a freedom of information law request. Each iteration of the visualization follows a random taxi drawn from the data set for 24 hours in 2013. The visualization shows well-known facts about the city’s taxi activity, such as how the number of riders spikes sharply during rush hours, as well as less obvious information, like how cab drivers often go a long time without a fare after heading to the city’s airports or how people in the wealthy Upper East Side and Upper West Side neighborhoods often take cabs for distances as short as a few blocks.
Travis Korte is a research analyst at the Center for Data Innovation specializing in data science applications and open data. He has a background in journalism, computer science and statistics. Prior to joining the Center for Data Innovation, he launched the Science vertical of The Huffington Post and served as its Associate Editor, covering a wide range of science and technology topics. He has worked on data science projects with HuffPost and other organizations. Before this, he graduated with highest honors from the University of California, Berkeley, having studied critical theory and completed coursework in computer science and economics. His research interests are in computational social science and using data to engage with complex social systems. You can follow him on Twitter @traviskorte.