To understand big data, convert it to sound

To understand big data, convert it to sound

Humans are far better at identifying data pattern changes audibly than they are graphically in two dimensions, researchers exploring a radical concept say. They think that servers full of big data would be far more understandable if the numbers were all moved off the computer screens or hardcopies and sonified, or converted into sound.

That’s because when listening to music, nuances, can jump out at you — a bad note, for example. And researchers at Virginia Tech say the same thing may apply with number crunching. Data-set anomaly spotting, or comprehension overall, could be enhanced.

The team behind a project to prove this is testing the theory with a recently built 129-loudspeaker array installed in a giant immersive cube in Virginia Tech’s performance space/science lab, the school’s Moss Arts Center.

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