Cascade on Wheels

Cascade on Wheels is a visualization project that intends to express the quantity of cars we live with in big cities nowadays. The data set we worked on is the daily average of cars passing by streets, over a year. In this case, a section of the Madrid city center, during 2006. The averages are grouped down into four categories of car types. Light vehicles, taxis, trucks, and buses.

We made two different visualizations of the same data set. We intended not just to visualize the data in a readable way, but also to express its meaning, with the use of metaphors. In the Walls Map piece, car counts are represented by 3D vertical columns emerging from the streets map, like walls. The Traffic Mixer piece, where noise is the metaphor, is an hybrid of a visualization and a sound toy. The first piece focuses more on showing the data in a readable and functional way, while the latter focuses more on expressing the meaning of the data and immersing the user into these numbers. Both pieces try to complete each other.

Read the interview at we make money not art.

The pieces

Walls Map

Walls Map

Launch the Walls Map video: fullsize quicktime or shrinked flash (on vimeo).

Traffic Mixer

Traffic Mixer

Launch the Traffic Mixer video: fullsize quicktime or shrinked flash (on vimeo).

A few things worth noting

Not all streets in the section are included in the data set, but in the most part the ones with the highest traffic are.

On the Walls Map, busses and trucks categories are represented with 3 times the size of the other categories. This is not rigorous, but it's an approximation that helps in illustrating better the impact of these vehicles.


Medialab Prado

People involved

Cascade on Wheels is a project by Steph Thirion (concept, design, direction, coding), and was initially developed during the 2007 Visualizar workshop at the Medialab Prado in Madrid, with the help of various collaborators:

Thanks to the Medialab Prado team for the help, organization, kindness, and the endless coffee and beer.

And thanks to all the workshop participants for the energy, the ideas and the great time.

Medialab Prado

Software used

Data set

The data set was extracted from Madrid Movilidad.

Special thanks to José Miguel Medrano from the Medialab for finding that treasure.


Steph Thirion: