Data Visualization Foundation


Data visualization is the process of mapping quantitative data to visuals (shapes, color, position, etc) to create a graph made of geometric object.

Information visualization:

  • is defined as “visual representations of abstract data to amplify cognition”.
  • is not useful when the information is specific (for a single instance)

The greatest value of a picture is when it forces us to notice what we never expected to see.

John Tukey, 1977

A picture is worth a thousand words

The Purpose of computing is insight, not numbers.

Richard Hamming (1962)

See (Image|Picture)

Giving shapes to data !

Document structure

A scene graph is generally the document containing all graphic information.

Data Type



Graphical methods class:

  • diagram techniques,
  • chart techniques,
  • plot techniques,
Type Description
Data Visualization - Map Geographical data
Data Visualisation - Voronoi Map
Data Visualisation - Heat Map For a lot of data
Data Visualisation - Scatterplot For a lot of data
Tree - Treemap Chart hierarchy data
Data Visualization - Stream graph
Data Visualisation - Histogram (Frequency distribution) distribution
Data Visualization - Box Plot summary of distribution
Data Visualization - Bar Chart ranking, comparison
Data Visualization - Line Chart deviation, trend
Data Visualisation - Area Chart ratio
Table Table
Ring Charts hierarchy data
Flow Charts Data or Business Processing




In realtime chart, you try to repaint only a part of the chart and not to repaint it completely.

Generally updating completely once per second is fine, but updating multiple times per second results in high CPU load.

Best practices / Fact

  • Use common scales to be able to compare across the graphs
  • Proportions are difficult to interpret
  • Avoid pie charts – Angular and curvature comparisons are hard to interpret.
  • Let it simple. Do not use 3-D charts, shading. Limit border, …


Foundation Vis Papers and Books

Documentation / Reference

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