Many people track their own data as part of living more healthily, and increasingly health professionals encourage people to participate in self-tracking. The more things we track, the more we come to understand ourselves. There are a hundred different ways to track a hundred different things. I might use a Fitbit to track my exercise, an app to track my diet, and a physical diary to track my weight.

If I want to find the relationship between those things, my data is in three different places, and the only real option I am given to visualize them together is to use a spreadsheet like Microsoft Excel or Apple Numbers. This might be fine if it’s just three points of data, but as the numbers increase even spreadsheeting software is not really designed to make this accessible for everyone, especially those who aren’t used to working with spreadsheets at all.

In this project I explore physical and accessible tools for data visualization. I look at how different types of tokens can be used to visualize any amount or type of data. The final design is DataChest, a personal toolkit that allows users to build a timeline using different types of tokens. Each aspect of the toolkit is designed to represent a different type of data, as well as to make a visualization that is visually readable. The guidebook takes people through how to use the different components and gives some examples of visualizations. DataChest is not only a consumer-friendly design, but also an immediately usable toolkit for exploring data visualization itself.