This is the course web for the Fall 2022 offering of CS765, Data Visualization.

You might want to start with Getting Started. Announcements of new things here will be made via the Course Canvas.

The Week in Vis: Week 11 (Nov 14-18): Design, ATUS Handins

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This week was supposed to be color week. We’ll put that off so we can do things that are timely and relevant to the Design Exercise / Projects: we’ll talk about design, and you’ll read about uncertainty. And in class, we’ll do some brainstorming about projects and help people find partners and choose topics.

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Atus Class Questions

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For Design Exercise 9: Visualization Hand-Ins one of your “stories” must be built from a “class question”. Here are the “class questions” - in that they are for the entire class. Note that for each question, there is a basic question, but then suggestions for more richness/detail/nuance to be layered into an answer/story. You must pick one of these four for the set of visualizations you create for DE9. Note that several of these require doing data joins of the samples with the population/household data set. Read more…

The Week in Vis: Week 10 (Nov 7-Nov 11): Perception

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This week we’ll dig into human perception as an important foundation for visualization. We’ll also continue the Time Usage Survey Design Exercise.

This will be a non-standard week because of the Design Exercise: the Tuesday deadline to turn in drafts is strict, and the normal Friday activities will be replaced by doing critiques.

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The Week in Vis: Week 08 - Why Vis Works (and doesn't)

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This week is a bit of a grab bag of topics. We’ll try to take a step back and ask the question “why does Vis work?” We’ll look at it from the perspective of perception and cognition (going back to the readings that we did not do as part of “Why Vis” in week 2). These will set the stage for our upcoming discussions of perception. We’ll also talk about some statistical issues, which will be relevant as we do exploratory data analysis in Design Exercise 7: Exploratory Data Analysis with the ATUS data.

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The Week in Vis: Week 07 (Oct 17-21)

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This week, we’ll look at a different part of scale: scaling in the number of dimensions. The lecture will look at different ways to do this (some of the more traditional ways), and the In Class Exercise will cover a different kind of way to deal with dimensions (glyphs).

We’ll have the final handins for the Aid Data exercise, and move on to some other design exercises.

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The Week in Vis: Week 06 (Oct 10-14)

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This week, we’ll explicitly talk about scale: what do we do when the data gets big. This problem is pervasive: we’ve been dealing with it all along, and will continue to deal with it with everything else we talk about. This week, we’ll try to get some vocabulary to talk about the problems and their solutions.

We’ll also be wrapping up the Aid Data Design Exercise. This week you’ll provide feedback to your classmates (and receive feedback), so you can improve your final designs.

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The Week in Vis: Week 05

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This week we’ll talk about implementation… how do we make visualizations. In general, we won’t spend too much time on the topic, but I want everyone to see some of the basic strategies. The Readings 05: Implementation will tell you more about the plan (and give you “readings”).

Part of this week is a video - it doesn’t take the place of a lecture, but it serves in the place of a reading. We’ll use class time to look at the design exercise and to look ahead at some tools you might use to make visualizations.

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The Week in Vis: Week 04 (Sep 26-30)

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This week, we’ll learn about encodings the way we map data to things we see. Encodings give the basics building blocks that we build visualizations from. The key idea is that rather than thinking about chart types, we think about them in terms of building blocks. That way we don’t need to learn zillions of chart types… we learn a few basic building blocks that we can assemble into charts as needed. An advantage to this approach: it lets us reason about why we might make certain choices.

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Tableau

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For the design exercises (and possibly other things), you must at least try Tableau.

Tableau is a commercial data analysis and visualization tool. The company generously provides it for use in classes through the Tableau for Teaching Program.

Here, we will give you a brief guide on how to get started with it, and pointers to some resources. We expect students to figure out how to work with Tableau enough for class.

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