@article{gansner2009drawing,
  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 },
  author = {Gansner, Emden R. and Hu, Yifan and Kobourov, Stephen G.},
  interhash = {881280a1a2aa34d84322d3781f62ca90},
  intrahash = {3f9e522da9443c0a07c39009918a4a77},
  journal = {cs.CG},
  month = jul,
  title = {{GMap}: Drawing Graphs as Maps},
  url = {http://arxiv.org/abs/0907.2585},
  volume = {arXiv:0907.2585v1},
  year = 2009
}