IAT 814 Introduction to Visual Analytics

1. IAT 814 Introduction to Visual Analytics Symbols vs Perceptual Science IAT 814

2. Visualization based on science • Visualization based on science – • not recognition of arbitrary symbols • Semiotics of graphics: Bertin, Saussure • The craft of designing visual languages? • The perceptual system has built-in capabilities • Understanding of perceptual mechanisms is fundamental to a science of visualization • Experimental semiotics (Ware) IAT 814

3. Sensory vs arbitrary symbols • Sensory: • You can see and understand without training. • Match the way our brains are wired • Object shape, color, texture • Arbitrary: • Must be learned • Having no perceptual basis • The word “dog” IAT 814

4. Arbitrary representations • Strengths • Formally powerful • Capable of rapid change • May already be learned • Visually concise • Weaknesses • Can be hard to learn • Can be easy to forget • Same symbol, different meaning • Different symbol, same meaning IAT 814

5. Sensory representations • Strengths • Can be understood without training • Resistant to instructional bias • Processed very quickly, and in parallel • Valid across cultures • Weaknesses • Poor mappings can be misunderstood, quickly and without effort, even with instruction and training. • Can’t be unlearned IAT 814

6. Sensory symbols • “Symbols and aspects of visualizations that derive their expressive power from their ability to use the perceptual power of the brain without learning”. • Empirically testable (ha!) IAT 814

7. Building a Visualization: Steps • Collect the data (lab work, simulation, archives, ……) • Transform the data into • a format readable and manipulable by the visualization software • the form most likely to reveal information • Visualization algorithms and computational treatments run on graphics hardware or software renderers • Human views and interacts with the visualization • Changes parameters, techniques, view options • User studies to evaluate effectiveness • ideally! IAT 814

8. What’s a good visualization? • Make a model that captures the essence of a information system • Model = abstraction with • The important things in • The unimportant things out • Different visualizations provide different levels of detail, • Show and hide different things • Support different abstractions • Useful to aid understanding, not just realistic representations (what color is a carbon atom?) • Map the important part of the tasks onto techniques that show the relevant characteristics best Acts of rhetoric! IAT 814