I had a lot of positive feedback last year when I designed my map of scientific collaborations. I think that there were two main reasons for this interest. First of all, the map was visually striking; it was abstract but it could still convey useful information about the world. Secondly, I think that the interest that people have in maps is mainly egocentric. In other words, the first thing that we look for when looking at a map, is to see where and how our house, state, country, etc. are represented on that map.
This time I wanted to design a much more detailed map, one that could help to make decisions or help understand scientific collaborations. The USA is a very interesting country because they fund science in such a massive way. Also, the United States is a land of contrasts where no two states are alike and this makes for interesting comparisons. Continue reading “Scientific collaborations by Metropolitan Statistical Areas”
This summer I was contacted by Goodby, Silverstein & Partners, a Californian Ad Agency in San Francisco working with Adobe Systems. GS&P hired me to design an interactive visualization for their Museum of Digital Media to illustrate how people contribute to Wikipedia and how these contributors form communities.
This was a challenge I could not refuse.
Continue reading “Contributing Communities on Wikipedia”
Less visually striking than my last project, this visualization shows the voting patterns of Canadian Members of Parliament. It uses a Principal Component Analysis (or PCA) transformation to convert the multidimensional voting record of each MP to a 2D (or Cartesian) form.
Each point on the chart represents an MP. The color of every MP follows their party affiliation. They are tightly clustered because of party discipline : in Canada, MPs normally vote in accordance to directions given by the Prime Minister.
Continue reading “Legislative Explorer | Multidimensional Vote Explorer”