Data Visualization Foundation

1 - About

Data visualization is the process of mapping quantitative data to visuals (shapes, color, position, etc). See Data Vizualization - Encoding / Decoding

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 Tess Flanders

The Purpose of computing is insight, not numbers. Richard Hamming (1962)

See (Image|Picture)

Giving shapes to data !

2 - Data Type

2.1 - Characters

2.2 - Numeric

Graphical methods class:

  • diagram techniques,
  • chart techniques,
  • plot techniques,

3 - Choosing

3.1 - Software

3.1.1 - Real-time

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.

3.1.2 - 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, …

4 - Foundation Vis Papers and Books

5 - Documentation / Reference

data/viz/viz.txt · Last modified: 2017/10/01 20:17 by gerardnico