3.31 Perception: Acceptability principles

  • “Understanding Charts and Graphs” (Kosslyn 1989): Contains lessons on how to think about your audience/perception/decoding17

    • ‘acceptability principles’ are derived from facts about human visual information processing and from an analysis of the nature of symbols
    • Visual information processing: Perceptual image (1) → Short-term memory (2) → Long-term memory (3) (Kosslyn 1989, 190–91)
        1. Discriminability, distortions, priority, organized18
        1. Capacity limit
        1. Knowledge
      • “an effective display must be easily encoded and comprehended by the visual information-processing system” (Kosslyn 1989, 192)19

  • (1), (2) and (3) are linked to the audience you have (this includes yourself!)

  • Kosslyn (1989) goes into more detail, however, for us the here mentioned concepts are useful enough

  • Q: Knowing these concepts what questions would you ask yourself when you see a graph and evaluate it?

    • e.g., Is the viewer able to discriminate the different categories in the graph?

References

Kosslyn, Stephen M. 1989. “Understanding Charts and Graphs.” Appl. Cogn. Psychol. 3 (3): 185–225.

  1. “This article develops a way of analysing the information in charts and graphs that reveals the design flaws in the display” (Kosslyn 1989).↩

  2. Adequate discriminability: Variations in marks must be great enough to be easily noted. This principle has two aspects (Kosslyn 1989, 195); Perceptual distortion: Marks should be used that are perceived veridically (Kosslyn 1989, 195); Priority: Some aspects of a stimulus are given priority over others ; we pay attention first to abrupt changes of any sort (e.g. heavier marks, brighter colours) (Kosslyn 1989, 191). Partly because only a limited amount of information can be held in short-term memory at once, some marks will be given priority over others. The information conveyed by these marks should be central to the display’s message (Kosslyn 1989, 196); Organized: Stimuli are organized into coherent groups and units by the time we become aware of them. Much of this organization is ‘automatic’ , not under voluntary control, and is determined by reasonably well-understood properties of stimuli (e.g. proximity of elements). The grouping imposed by these automatic_processes must be respected if a chart or graph is to be seen the way a designer intends (Kosslyn 1989, 191).↩

  3. Kosslyn (1989) also discusses Goodman (1976)’s theory of symbols but to me it seems less useful to the applied data scientists.↩