Schedule

The Weekly Rhythm should give you the pattern for each week.

The idea here is to give you a sense of the order of topics. (things are subject to change)

Somehow, when making this schedule, I left off a few key topics: interaction, graphic design, high-dimensional spaces, vis for machine learning (and machine learning for vis), scientific data types, …

Week 1: What is Vis?

Understanding what visualization is will help us understand how to learn about it.

Week 2: Why Vis? And how to learn it (Critique)?

Exploring why we want to make visualizations will help us get a how to make them. We’ll also learn about critique, which will be a key tool for how we can learn about visualization (and other things).

Week 3: How to talk about Vis? (Task and Data Abstractions)

Abstraction will give us the tools to talk about problems (tasks) and data in a general way, so we can understand solutions in a general way.

Week 4: How to describe Visualizations? (Encodings)

We will learn to think of visualization designs as a collection of basic elements (encodings). We will connect this to more traditional way of thinking about visualization by chart types.

Week 5: Science and Engineering

This week, there will be two guest lectures. One real guest lecture (from Karen Schloss) that will get you to think about how psychology can influence visualization. One virtual guest lecture (a recording of an online guest lecture) from Dominik Moritz about implementation (and the engineering aspects).

Week 6: Practical Visualization

We’ll talk more about implementation, with a very practical notion of starting up on the first “mini-project”. We’ll look at some real tools and examples of how students used them in previous years projects.

Week 7: Too Much Stuff - Dealing with Scale

Week 8: Perception 101

The basics of how we see, and what it means for Vis

Week 9: Color

The science of color, and what it means for making visualizations

Week 10: Cognition and Statistical Reasoning (Why Not Vis?)

How we think and interpret visualizations, and why that might create problems?

Week 11: Evaluation: How do we know it’s any good?

How do we evaluate visualizations and use that to improve our designs.

Week 12: Uncertainty

How do we design visualization to show uncertainty and unpredictableness.

Week 13: Graphs

How do we show network data?

Week 14: 3D

How do we show data about our 3D world? How do we use our ability to interpret “real 3D space” in visualization?

Week 15: Presentations and Communication

How should you give a presentation? How can we use design principles more broadly in how we communicate?