The class can be divided (roughly) in to 4 parts:
- Foundations:
- What is Visualization?
- Why do we do it? (and Why bother doing it well?)
- What does it mean to do it effectively?
- How do we think about it in the abstract? (so we can learn once and apply a lot)
- Key Topics: Types of visualization, goals of visualization, audiences and stakeholders, evaluation of visualization, critique skills, task abstraction, data abstraction
- Principles:
- What are the basic building blocks of visualizations?
- How do we put those together to make effective visualizations?
- How does human perception work, and how can this inform our design?
- What principles of visual design can help us?
- Key Topics: Encodings, Layout, Graphic Design, Human Perception, Color Theory
- Applying those Principles:
- How do we use the principles to solve harder problems?
- How do we use interaction and multiple views?
- How do we use standard designs – and when do we need to invent new ones?
- How do we deal with common challenges (like networks and high dimensions)?
- Key Topics: standard (and non-standard) designs, combining encodings, interaction and multi-view, graphs, networks, high-dimensions, dealing with scale, 3D objects
- Specific Challenges:
- How have people addressed common, but challenging cases? (e.g., volumes and flows)
- How are researchers addressing emerging problems? (e.g., uncertainty, statistical models)
- Key Topics: Scientific Visualization (volumes, flows, tensors), Uncertainty Visualization, Statistical Model Visualization, …
Mixed throughout is the idea that the best way to learn about visualizations is to look at examples (and critique them) and to try making some (either from scratch, or re-designing existing ones). Which means we’ll get some small tastes of what comes later at the beginning, and those concepts from the beginning will permeate throughout the class.