Beautiful Data: The Stories Behind Elegant Data Solutions

We want something in between the textbook and novel when we visualize personal data.

Most of the time we are not after the numbers themselves; we are interested in what the numbers mean.

When the user scrolls over a trip on the PEIR map, that trip is highlighted, while all other trips are made less prominent and blend in with the background without completely disappearing. To be more specific, transparency of the trip of interest is decreased while the other trips are blurred by a factor of five.

It did not seem right to break emotions down into graphs and numbers, so a sorted tag cloud is used instead. It somehow feels more organic. Emotions of higher frequency are larger than those that occur rarely.

There are perhaps few types of data that are so immediately understandable as one's place in physical space. Therefore, we use maps as the visualization anchor point and work from there.

I like to think of data visualization as a story. The main character is the user, and we can go two ways. A story of charts and graphs might read a lot like a textbook; however, a story with context, relationships, interactions, patterns, and explanations reads like a novel.

People seemed more interested in patterns over time than overall distributions.