notes/docs/lectures/infovis/02_value_of_visualisation.md

The Value of Visualisation

Why create a Visualisation?

• Answer questions (or discover them)
• Make decisions
• See data in context
• Expand memory
• Support graphical calculation
• Find patterns and trends
• Present arguments or tell a story

A picture is worth a 1000 words

Record information

• Blueprints, photographs, seismographs

Communicate information to others

• Share and persuade
  • Think of Florence Nightingale using a graph to show that infection was the leading cause of death in hospitals
• Collaborate and revise
  • Think of the London tube map: before it was geographically accurate, now it is only topologically accurate

Analyse data to support reasoning

• Find patterns
  • Think of the London Cholera map, how John Snow found out where the infection was coming from
• Discover errors in data
• Expand memory
  • Imagine doing a sum like 34\times 52 mentally versus with a pen and paper
  • Visualising the sum (column multiplication) can expand your memory
• Develop and assess hypotheses

Different Stages of Visualisation

• Data transformation
  • Create a structural model, schema, mapping raw data into data tables
• Visual Mapping
  • Create a visual spatial model, transforming data tables into visual structures
• View Transformations
  • Create views of the Visual Structures by specifying graphical parameters such as position, scaling and clipping.

Acquire

• Obtain the data, whether from a file on a disk or network

Parse

• Provide some structure for the data’s meaning, and order it into categories

Filter

• Remove all but interesting data

Mine

• Apply methods from statistics or data mining as a way to discern patterns or place the data in mathematical context
  • Work out mean, standard deviation etc

Represent

• Choose a visual model
  • Bar chart, graph, pie chart etc

Refine

• Improve the basic representation to make it clearer and more engaging

Interact

• Add methods for manipulating the data or controlling what features are visible

Interaction is Vital for Exploration

• Engage in a dialogue with your data
• Employ interaction in a more fundamental manner to strengthen the power of visualisation