I.9 In Terms of Geography
André Skupin’s research interests focus on geographic visualization, cartographic generalization, data mining, and information visualization. This map was computed from more than 22,000 abstracts submitted to the annual meetings of the Association of American Geographers during a ten-year period from 1993 to 2002. The methodology is centered around the representation of each document as an n-dimensional vector of terms. These vectors are used to construct a neural network model of the geographic knowledge domain using a Self-Organizing Map (SOM). The neural network model is then transformed into two types of information: (1) a landscape in which elevation indicates the degree to which a single, focused topic is addressed; and (2) multilevel text labels associated with regions in the visualization. The final rendering was executed in standard geographic information systems (GIS) software.
Skupin, André. 2004. “The World of Geography: Visualizing a Knowledge Domain with Cartographic Means.” PNAS 101 (Suppl. 1): 5274-5278.
Skupin, André. 2005. In Terms of Geography. Courtesy of André Skupin, San Diego State University, San Diego, CA. In “1st Iteration (2005): The Power of Maps,” Places & Spaces: Mapping Science, edited by Katy Börner and Deborah MacPherson. http://scimaps.org.
Acknowledgements: This exhibit is supported by the National Science Foundation under Grant No. IIS-0238261, CHE-0524661, IIS-0534909 and IIS-0715303, the James S. McDonnell Foundation; Thomson Reuters; the Cyberinfrastructure for Network Science Center, University Information Technology Services, and the School of Library and Information Science, all three at Indiana University. Some of the data used to generate the science maps is from the Web of Science by Thomson Reuters and Scopus by Elsevier. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.