Module 7: Advanced Topics and Skills (Nov 24-Dec 12)

in Modules

We will look at emerging themes in visualization to see where visualization research is providing new solutions. We will look at design and research process in visualization.

Introduction

The last “module” is unusual - I am not making any attempt to have a coherent theme. It’s a bunch of stuff I want you to know. It’s also unusual since it is 3 weeks (including Thanksgiving).

The topics are a bit of a mix… We’ll have a week of core topics that we don’t have enough time to really discuss (interaction and 3D). We’ll have a week of “skills” (presentations and graphic design). And the last week will be filled with a grab bag of topics that you should know about, and we’ll take a little time to tie everything together.

Since there are 3 weeks, there are 3 design exercises. Although, all should be smaller than the ones earlier in the semester.

  • Interaction and Presentations - This design exercise will ask you to think about using interaction for the problems you worked on over the course of the semester. Rather than implement things, you will make a video explaining your idea.
  • Design School - This design exercise will give you a chance to practice your graphic design skills (as we discuss in class).
  • Do-Overs - This design exercise will allow you to “do over” something you did earlier in the semester. Now that you know more, you should be able to improve on something you made.

Summary

What you need to do:

  1. Interaction
    1. You can do the readings after the lecture. The lecture and readings will help you with Design Exercise 7-1: Interaction.
  2. Other “topical” lectures (3D+Scientific, Uncertainty+Ethics) have optional readings.
  3. Presentations
    1. My notes on presentations are optional - but you might want to review them after I present them.
    2. Watch a Hans Rosling video (there will be questions on the survey)
    3. Watch 2 VIS25 conference presentation videos (there will be questions on the survey)
  4. Design School
    1. The readings on design are to reinforce the lecture and to give you more ideas.
    2. The assignment (Design Exercise 7-2: Design School) for the Design School involves some seek and find, and a little design work of your own. You should probably do it after the design school lecture (Dec 3).
  5. Do Overs
    1. Design Exercise 7-3: Do-Overs asks you to redo 2 visualizations you made this semester.

The things to hand in (all due at the end of the module):

Warning: we’ve put the actual due date as late as possible (December 12), but that means we really can’t accept late things because we need to do grading! Monday, December 15 is a hard deadline for all late handins for this module.

Module Learning Outcomes (Goals)

  1. Identify network (graph) data and describe standard visualization approaches for it
  2. Identify high-dimensional (multivariate) data and describe standard visualization approaches for it
  3. Describe standard approaches for visualizing uncertainty in data
  4. Describe standard approaches for visualizing set data
  5. Practice creating and critiquing visualizations

Readings / Watchings

By topic:

  • Interaction (2 Munzner Chapters required, 2 optional readings that go along with lecture) - this material should help with Design Exercise 7-1.
  • 3D and Scientific Data Sets (1 Munzner Chapter Required)
  • Presentations (3 required watchings: Rosling, Munzner, 1 other) - optional reading to help you in the future
  • Graphic Design (readings hidden within the Design Exercise)
  • Uncertainty, Decision making, Ethics, Sensemaking, … - Some recommended readings (and a little snuck in with the required watching above).

Interaction

Interaction is one of those things that is best experienced, rather than read about. The readings will give you a lot of examples, and help to give you a framework for organizing your thinking around interaction. The optional reading is a really useful way to think about the tradeoffs in using interaction, and will be the basis of the lecture.

  • (required) Tamara Munzner. Maniplate View. Chapter 11 from Munzner's Visualization Analysis & Design. (Canvas File) (UW Library)
  • (required) Tamara Munzner. Facet into Multiple Views. Chapter 12 from Munzner's Visualization Analysis & Design. (Canvas File) (UW Library)
  • (optional - but recommended) Heer, J., & Shneiderman, B.. Interactive dynamics for visual analysis. Communications of the ACM, 55(4), 45. (doi) (url)
  • (optional - but recommended) Heidi Lam. A Framework of Interaction Costs in Information Visualization. IEEE Transactions on Visualization and Computer Graphics, 14(6), 1149–1156. (doi) (UW Library)

3D and Traditional Scientific Data Types

Sadly, we don’t really do much of this in class. Read a chapter of Munzner to get some of the big ideas (which we will also go over in Lecture). I have nothing for you to read about 3D (take the graphics class if you want to know about it!)

  • (required) Tamara Munzner. Arrange Spatial Data. Chapter 8 from Munzner's Visualization Analysis & Design. (Canvas File) (UW Library)

Presentations

Normally, I ask students to read my notes on presentation before I present them in class. Instead, I will make the reading optional - but I am going to require you to watch (at least) 3 presentation videos: 1 by Hans Rosling and 2 from this year’s VIS conference (one by Tamara Munzner, and another of your choice). The content survey will ask you about what you watched.

My annual rant about presentations is an unusual event. When I first did it, it happened by accident. But so many students have responded positively to it, that I keep doing it. Each year it ends up a little different. Over time, it has stopped being a random ramble (The first time I did it was spontaneous. I just started talking - and by the end of the 75 minutes there was a list on the blackboard, that became the outline for future things). But it’s usually highly interactive.

My real goal is to get you to think about what might make for a good presentation, and to form your own strong opinions – even if they are different than mine.

In recent years, I’ve asked students to read my notes first. This year, I am making the notes optional. After you see the presentation, you might want to go back to look over the notes. You might want to refer to it after you see the presentation (or read it before, to get an idea of what to expect).

Mike’s Notes On Presentations

Before reading my notes, here are some caveats (note: this is taken from the 2012 class):

  • The goals and standard for presentation really vary across venue/discipline. What we value in computer science (in particular the areas I work in) are quite different than in other disciplines. It’s hard for me to discuss this without value judgement (since I am bred to believe in the “CS way”), but I also plead ignorance to the practices in other areas. I’d like to use this as a chance to learn about others.
  • I don’t consider myself to be a great presenter. Do as I say, not as I do. The upside of this is that it means I think about how to be better at it.
  • A lecture is not the same as a talk, so what you see in class is quite different than what you would see in one of my talks.
  • Even within a particular style/venue/type of talk, there is a wide range of opinions on what is good talk, what the goals should be, …
  • The “right answer” depends not only on the situation, but on the person. But that will be one of the biggest lessons I hope you get. I may not speak to your specific case, but hopefully, you can see how the general lessons apply.
  • As you might guess, I have strong opinions. But you don’t have to guess at what they are, since I’ve written them down.
  • (optional) Michael Gleicher. Advice on Presentations. CS777 Course Web from 2011. (url) Yes, it’s from a 2011 class – but I think if I were updating it, it wouldn’t be much different.

Hans Rosling

Hans Rosling was a famous presenter – talking about social issues around the world in venues like TED, etc. He was famous for presenting data in a compelling way to make his points for a broad audience. His influence is significant (both on presenting data and on the world in general).

If you haven’t seen a Rosling talk, you need to experience one. If you have seen one, you probably won’t mind watching another. These are getting a bit dated, but the lessons on how to present with data still apply.

You can watch any video of one of his presentation. Pay attention to how he interacts with his visuals and uses animation and presentation techniques to direct attention and tell a story.

Some example videos:

  • (alternate) Hans Rosling. The best stats you've ever seen. Hans Rosling Example Video 1. TED2006. (video)
  • (alternate) Hans Rosling. New insights on poverty. Hans Rosling Example Video 2. TED2007. (video)
  • (alternate) Hans Rosling. Let my dataset change your mindset. TED2009. (video)
  • (alternate) Hans Rosling. The good news of the decade? We're winning the war against child mortality. TEDxChange • September 2010. (video)
  • (alternate) Hans Rosling. Hans Rosling's 200 Countries, 200 Years, 4 Minutes - The Joy of Stats - BBC. BBC, The Joy of Stats, 2010. (video) - This one is short, and uses fancy video overlays.

Vis 2025 Talks

The talks at this year’s VIS conference (2025) were recorded. Unfortunately, you only get to see the slides and hear the audio - but in most cases, this is all the audience got (the speaker was generally behind a podium). A recording of a talk is not as good as a talk (even a bit of the presenter’s expression is helpful).

I want you to watch two of them. One by Tamara Munzner is important for the content, as well as to see how a senior person in the field presents. You can pick any other talk you like - I mainly want you to pay attention to the presentation. I’ve tried to pick examples that I remember as being reasonable/memorable presentations (and accessible enough topics).

You do not need to read the paper (you are welcome to, but it is optional). Watch the videos and try to be aware of the presentation.

  • (required) Charles Berret and Tamara Munzner. Iceberg Sensemaking: A Process Model for Critical Data Analysis. IEEE Transactions on Visualization and Computer Graphics (Volume: 31, Issue: 9, September 2025). (doi) (web pdf) (url) (video) - Tamara Munzner giving a talk that relates to the ethical issues in data analysis. It has a good (brief) review of the sensemaking literature (that we didn’t get to discuss in class).
  • (alternate) Chase Stokes, Anjana Arunkumar, Marti A. Hearst, Lace Padilla. An Analysis of Text Functions in Information Visualization. IEEE VIs (Short Papers), November 2025. (web pdf) (url) (video) - A short paper with a good presentation (and an interesting message).
  • (alternate) Arjun Srinivasan; Joanna Purich; Michael Correll; Leilani Battle; Vidya Setlur; Anamaria Crisan. From Dashboard Zoo to Census: A Case Study with Tableau Public. IEEE Transactions on Visualization and Computer Graphics (Volume: 31, Issue: 9, September 2025). (doi) (web pdf) (url) (video)
  • (alternate) Sungbok Shin, Sanghyun Hong, Niklas Elmqvist. Visualizationary: Automating Design Feedback for Visualization Designers Using LLMs. IEEE Transactions on Visualization and Computer Graphics (Volume: 31, Issue: 10, October 2025). (doi) (web pdf) (url) (video)
  • (alternate) Camelia D. Brumar; Sam Molnar; Gabriel Appleby; Kristi Potter; Remco Chang. A Typology of Decision-Making Tasks for Visualization. IEEE Transactions on Visualization and Computer Graphics (Volume: 31, Issue: 10, October 2025). (doi) (web pdf) (url) (video)

Graphic Design

The readings for Graphic Design are part of Design Exercise 7-2: Design School.

Uncertainty, Decision Making, Sensemaking, Ethics, …

I have no idea where to begin with this array of topics - all of which are really important. I’ve snuck some in with the other readings and watchings. For this year, everything is optional. I do recommend reading at least one of the uncertainty readings (one is a more formal version of the other).

  • (optional - but recommended) Jessica Hullman. How to get better at Embracing Unknowns. Scientific American, Volume 29, Special Issue. (url) (video)
  • (optional) Padilla, L., Kay, M. and Hullman, J.. Uncertainty Visualization. Chapter 22 of Computational Statistics in Data Science. (web pdf) (url)
  • (optional - but recommended) Michael Correll. Ethical Dimensions of Visualization Research. CHI '19: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, Paper No.: 188, Pages 1 - 13. (doi) (web pdf) (url) - This is mainly targeted to what researchers should think about, but it is thought provoking.

Lecture Plan

  • Monday 1 (Nov 24) - Interaction
  • Wednesday 1 (Nov 26) - 3D and Traditional Scientific Data Types
  • Monday 2 (Dec 1) - Presentations
  • Wednesday 2 (Dec 3) - Design School
  • Monday 3 (Dec 8) - Uncertainty and Decision Making
  • Wednesday 3 (Dec 10) - Summary

The Content Survey

Here are the questions for the Content Survey. I recommend writing things down as you do the work over the course of the module so you can upload the answers all at once.

  • Which Hans Rosling video did you watch?
  • Give a few takeaways from Tamara Munzner’s Iceberg talk
  • What thoughts do you have on the presentation (not the content)?
  • Which other vis talk did you watch?
  • Give a few takeaways from this presentation.
  • What thoughts do you have on the presentation (not the content)?
  • I put Munzner Chapter 12 as part of “interaction” for a reason: multiple views are (often) connected with interaction. Give an example of how interaction connects can address the challenges of multiple views.