Information visualization is essential in making sense out of large data sets. Often, high-dimensional data are visualized as a collection of points in 2-dimensional space through dimensionality reduction techniques. However, these traditional methods often do not capture well the underlying structural information, clustering, and neighborhoods. In this paper, we describe GMap: a practical tool for visualizing relational data with geographic-like maps. We illustrate the effectiveness of this approach with examples from several domains All the maps referenced in this paper can be found in http://www.research.att.com/~yifanhu/GMap

@article{gansner2009drawing, author = {Gansner, Emden R. and Hu, Yifan and Kobourov, Stephen G.}, title = {GMap: Drawing Graphs as Maps}, journal = {cs.CG}, year = {2009}, volume = {arXiv:0907.2585v1}, url = {http://arxiv.org/abs/0907.2585}, keywords = {visualization, graph, gmap, graphviz, social, analysis, graphics, network, sna, citation, drawing}, abstract = {Information visualization is essential in making sense out of large data sets. Often, high-dimensional data are visualized as a collection of points in 2-dimensional space through dimensionality reduction techniques. However, these traditional methods often do not capture well the underlying structural information, clustering, and neighborhoods. In this paper, we describe GMap: a practical tool for visualizing relational data with geographic-like maps. We illustrate the effectiveness of this approach with examples from several domains All the maps referenced in this paper can be found in http://www.research.att.com/~yifanhu/GMap } }

%0 = article %A = Gansner, Emden R. and Hu, Yifan and Kobourov, Stephen G. %D = 2009 %T = GMap: Drawing Graphs as Maps %U = http://arxiv.org/abs/0907.2585