One Data Artist Combined Visuals And Music To Bring Attention To Income Inequality In New York City

The song is pretty catchy.

Income inequality is difficult to understand when multiple factors are involved, but one data visualization artist used a simple medium to sum it all up: music.

Brian Foo, a data artist at the American Museum of Natural History, created Two Trains – Sonifcation of Income Inequality on the NYC Subway, a video that combines visuals and music to convey the income inequality among each stop of New York City's No. 2 train line that runs through Brooklyn, Manhattan, and The Bronx. With each passing stop on the 2 train line, the sounds correspond to the stop's median household income.

In order to create this, Foo turned to data sonification, a system where data can be translated into sound values. He took a data set and used Python, a type of programming language, to process it and then turned to Chuck, a music programming language, to distribute sounds to values.

"The data set itself is the composition, or the thing that drives the sound," he said to Mic. "I kind of just define the rules in which the data gets mapped in sound. I don't manipulate the data.

In keeping his commitment to not manipulate the data, Foo made sure that this song didn't assign particular notes or tones to income levels or neighborhoods, and created a scale that focuses more on the song's volume and the variety of instruments used throughout the piece.

"That's kind of the gray area between being a data scientist and being an artist," he said. "A data scientist shouldn't bias the audience whereas an artist, they kind of want to do that. I want to be faithful to the data, but the medium of music is kind of inherently emotive."

This isn't the first time Foo has combined music with data. In subsequent videos after his income inequality piece, he's worked on a soundtrack for diversity in film, the global refugee movement throughout four decades, and more.


Watch and listen Foo's song below:

(H/T: HelloGiggles)


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