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Visualizing New York’s Transit Data: Grand Central Station



Annually, over 36.5 million passengers travels through the Grand Central Station making it one of the busiest station nationwide. How can harnessing big data allow the MTA to better communicate to it’s internal key members as well as leverage this resource to better serve it’s community?

Effy Zhang, Mike Chen and Nga Nguyen under Rachel Abrams guidance in the SVA IxD winter workshop prototyped an interactive web application to deliver a snapshot of the 42nd Grand Central station. The team was given 3 ½ years of raw data that was analyzed and synthesized into a design language that helps articulate a meaningful story to MTA stakeholders. The visualization provides a visceral tool that speaks to a broad audience. The data allowed the audience to quickly visualize the unique card users, the ebb and flow of traffic and how significant events can impact the MTA network. A big take-away from the Grand Central Station profile is a convincing perception that it is a living, breathing eco system that changes dynamically with the seasons as well with its different users.