These are the Topics discussed in the Course updated along the way.


  • Design of Visualizations: principles, errors, chart junk
  • Models of Information Visualization
  • Data Types and Variables
  • Perception: the eye, contrast, colors, concept and uses of eyetracking, spatial perception, depth cues, Steven's power law
  • Visual Attention
  • Patterns: texture, gabor detector, gestalt laws
  • Cognition: information processing, gist, visual memory, visual search
  • Visual Encoding: semantic depth of field
  • Interactivity: Zooming, Panning, Lenses
  • 3D: basics of 3D visualization, techniques, tasks in 3D space


  • Statistical Graphs: banking, scale, trend line, box plot, scatter plot, stacked plot, pie plot
  • Maps: cartograms, thematic, flowmaps, choropletic, basics of distance over map
  • Graph Visualization
  • Information Landscapes
  • High dimensionality tools: dimensional reduction (PCA, MDS)



  • Computing Online statistics about data
  • Classes
  • Exceptions
  • Using libraries

See JavaScriptNotes

Web Concepts

Web Visualization

High level Visualization

  • IBM ManyEyes
  • Tableau (or optionally Mondrian)
  • Yahoo! Pipes

Map Tools

  • Google Maps and Mashups
  • Google Earth and KML principles