When it comes to data visualization, Keats put it best: “Beauty is truth, truth beauty.” Sure, he wrote that line 200 years ago in Ode on a Grecian Urn, but the sentiment captures an essential reality that computer scientists understand: There’s beauty in truth. In data.
Anna’s six years old and I teach her piano lessons in Austin, where I live. She had just tried a new music notation I invented with a friend. And she understood it—no; she loved it. Her mom came into the room to see how Anna was doing.
“Look,” Anna said, pointing at the paper, “these, this is full! And empty! And this one is long!” She began explaining it all back to her mom. The whole system, after a thirty-minute lesson. I was amazed.
Learning to play an instrument is hard, but sheet music makes it even harder. I’ve taught dozens of students, ages 4 to 60, and traditional music notation never comes easily. It can often take months (or longer) to pick up. Worse yet, those frustrations often lead to thoughts like, “I’m bad at music.” It’s tough to hear; as their teacher, I know that’s not true. The sheet music just isn’t intuitive. And that shouldn’t be the hard part—when you read a great book, you think about the *meaning*, not which letter is which.
Last year, I set out to fix it. I recruited my old college roommate, Mike Sall, who works in data visualization, and together we started hacking ideas. Over the past year, we’ve tried everything —colors and shapes, lines and squiggles, flipping and squashing—putting it all in front of my students as we went. We ended up with Hummingbird, a new music notation.