I believe that data has a shape — an internal characteristic that can be extracted and exposed thought data visualization techniques and combining them with generative design systems.

I’ll be talking about the shape of data in the context of algorithmic skin, a concept describing the layer of algorithms that nowadays live between our bodies and the interactions with the real world. I’m interested in the quantified-self movement myself and I find it fascinating to be able to constantly learn more about ourselves through personal data.

Couple of years ago I had a pleasure to work with Nike on a project involving Nike FuelBand. FuelBand is now discontinued but it was a device that instead of just tracking your steps it gives you fuel points for any kind of movement: walking, running, dancing, hand waving, you name it.

Nike Fuel Band. Photo: Nike

In this project we looked at the data of 7 female runners preparing for a race. We wanted to create “a digital award” to celebrate their efforts.

If you think about 24h day as a cycle you can represent it as a circle. We then put the fuel points you have collected on that circle next to the time of the activity (video). This looks quite cool but I was more interested the total amount of points that you collected that day.

What I did is as you collect more and more points I extrude the line higher and higher. As it grows it starts to resemble a branch of a growing tree.

When we then combine 7 of them, one for each day of the week for me they started to look like a muscle.

Next step was to look at the data of all the 7 runners together. Here we see a fuel graph for the each day of the week. Red colors represents no activity and green spikes are the times when the person was physically active. Additionally some of the days are highlighted in red as for them the minute to minute data was missing (lost FuelBand, forgot to sync etc.)