Lecture 08 Design principles & visualisation

Question 1

Four Data Visualization Heuristics to Facilitate Reflection in Personal Informatics

Answer 1

1. Make Data Interpretable at a Glance
2. Enable Exploration of Patterns in Time Series Data
3. Enable Discovery of Trends in Multiple Data Streams
4. Turn Key Metrics into Affordances for Action

Question 2

Goals of visualisation

Answer 2

1. Presentation
   * Starting point: facts to be presented are fixed a priori
   * Process: choice of appropriate presentation techniques
   * Result: high-quality visualization of the data to present facts
2. Confirmatory Analysis
   * Starting point: hypotheses about the data
   * Process: goal-oriented examination of the hypotheses
   * Result: visualization of data to confirm or reject the hypotheses
3. Exploratory Analysis
   * Starting point: no hypotheses about the data
   * Process: interactive, usually undirected search for structures, trends
   * Result: visualization of data to lead to hypotheses about the data

Question 3

color guidelines

Answer 3

• Take color deficiency into account
• Consider mental model of users (e.g. red = high values, blue = low values)
• Use diverging colormap if meaningful midpoint exist (e.g. to indicate coastline on a map)
• Sufficient space is needed to encode color
• Consider different tasks
• Consider the separability of used visual variables
• Use contrast effect compensation

Question 4

Perceptual properties

Answer 4

1. Selective perception
2. Associative perception
3. Ordered perception
4. Quantitative perception

Question 5

Expressiveness

Answer 5

Visualization presents all the information and only the information.

Expressiveness = (information displayed / information desired to display)
< 1 means we are not displaying enough
> 1 we are displaying more than intended (noise that could lead to confusion)

Visualization is effective when it can be interpreted accurately and quickly and when it can be rendered in a cost-effective manner.