Declan Butler, reporter

September 17, 2008

Some cartograms of US science & technology

Filed under: GIS,Open data,Uncategorized,Venture capital — admin @ 7:38 pm

As anyone who has visited WorldMapper knows, cartograms are an interesting way of visualizing date on geographical areas. I’ve an article in Nature tonight where I’ve generated cartograms for some indicators on US science and technology.
Some excerpts at end below, and also a Picasa slideshow of some of the cartograms — it’s the first time I’ve used the Picasa embed, and its too subliminally speedy. You can press the stop button, and then click back and forward on the below, and there is allso a static version where you can just click through the slides at a normal human pace ;-> — click this link to the Picasa album.

The cartograms reveal the United States distorted in proportion to a variable other than area — such as state spending on R&D. The maps here were made using data from the State Indicators chapter of the 2008 edition of the US National Science Foundation’s (NSF’s) Science and Technology Indicators. For simplicity, the cartograms use a base map of the 48 contiguous mainland states and the District of Columbia.
I haven’t included a detailed description of the indicators – -see the NSF chapter for that.

The Gastner & Newman 2004 PNAS paper introduced an improved algorithm for generating cartograms, which was the one used here. The software implementation is the open-source ScapeToad, released in May by the Chôros Laboratory at the Swiss Federal Institute of Technology (EPFL) in Lausanne, which researches the concept of space in society, from urban planning to territorial development.

Note that per-capita and other cartograms that use normalized data can be confusing, cautions Michael Goodchild, a geographer at the University of California, Santa Barbara – in theory a state with just a few researchers and a tiny research budget, for example, might nonetheless appear huge on such a map. Where possible it might be better to use raw non-normalized data, such as total population to scale state sizes in cartograms, and then layer on data on other related information on top. There are examples of both types of data in the slideshow above.

Declan
PS Nature also has a short editorial on visualization this week, and just last week a fab special on “Big Data.”

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