I was very impressed by the friendship map made by Facebook intern, Paul Butler and I realized that I had access to a similar dataset at Science-Metrix (an old employer I left a while ago). Instead of a database of friendship data, I had access to a database of scientific collaborations. Bibliometric firms use this kind of data to get a (very) approximated view of science, but I thought that for a data visualization, it was good enough
From this database, I extracted and aggregated scientific collaboration between cities all over the world. For example, if a UCLA researcher published a paper with a colleague at the University of Tokyo, this would create an instance of collaboration between Los Angeles and Tokyo. The result of this process is a very long list of city pairs, like Los Angeles-Tokyo, and the number of instances of scientific collaboration between them. Following that, I used the geoname.org database to convert the cities’ names to geographical coordinates.
The next steps were then similar to those of the Facebook friendship map. I used a Mercator projection to project the geographical coordinates onto the map and used the Great Circle algorithm to trace the lines of collaboration between cities. The brightness of the lines is a function of the logarithm of the number of collaborations betweena pair of cities and the logarithm of the distance between those same two cities.
A high resolution map is available here: http://collabo.olihb.com/collabolinks.jpg. Please don’t hotlink.
A zoomable very high resolution map can be consulted there: http://collabo.olihb.com/