CPSC 547: Information Visualization, Sep 2026

Remember to reload the page, changes are frequent.

Instructor: Tamara Munzner
First Class: Thu Sep 10 2026
Time: Thu 2-5pm
Location: DMP 201
Office Hours: Thu 5pm in classroom, until all questions are handled. Or zoom by appointment, check my calendar and request a spot by email.
Canvas: 547-26 Canvas
Piazza: 547-26 Piazza (signup link) Please join Piazza, it's a main avenue of communication for this course!

Short Weekly Syllabus

  Week

  Date

  Async Read/Discuss

  Sync: In Class

  Due

1 Sep 10 Logistics, Intro, Nested Model, Ex: Time Series

2 Sep 17 Data, Tasks, DSM Ex: Abstraction

3 Sep 24 Marks & Channels, Layout, Rethinking Ranks Decoding

4 Oct 1 Color, Rules of Thumb, HemoVis Pitches Pitches due Thu Oct 1 noon

5 Oct 8 Interactivity, Multiple Views, Dashboards Ex: Handling Complexity Groups finalized Fri Oct 9 noon

6 Oct 15 Aggregation, Embed, TensorFlow Pre-Proposal Meetings

7 Oct 22 Spatial Data, NecklaceMaps, Myriahedral Ex: Ballotmaps Proposals due Fri Oct 23 noon

8 Oct 29 Networks, Abyss-Explorer, Lineage Post-Proposal Meetings

9 Nov 5 Polaris, D3, Vega-Lite

10 Nov 12 NO CLASS (IEEE VIS)

11 Nov 19 (Project Updates) Project Peer Reviews Updates due Wed Nov 18 noon

12 Nov 26 Post-Update Meetings

13 Dec 3 Research Process

15 Dec 15/17 Final Presentations Tue Dec 15 2pm-TBD Final Papers due Thu Dec 17 noon

Detailed Syllabus

Syllabus tentative, final changes will be made by previous class (for readings). In weeks with required readings/videos, your comments are due by Tue noon and your responses are due by Thu noon.

Required Reading:

All research paper readings available online for free, links posted below. For digital library access from off-campus, use OpenAthens with your CWL login through the UBC library. OpenAthens direct links: IEEE DL, Springer DL, ACM DL, JSTOR
Visualization Analysis and Design, Tamara Munzner (A K Peters Visualization Series, CRC Press, 2014) is the book on which the required videos are based; however, as I'm working on the second edition, the videos have diverged from the content of the book. Nevertheless, if you'd like to see the written version, the UBC library has multiple ebook licenses so you can read it for free: library catalog page, direct link (must be logged in).

Introduction Week 1: Thu Sep 10

Required Reading/Watching: none

Online Discussion: Piazza @8 self-intros

In Class

Exercise: Time Series
Signup Form for in-person attendance
Slides: pdf, pdf 16up, keynote

Further Reading

Ch 1 (Why Do It?) Further Reading
In-Class Exercise Followup Videos & Papers
- Cluster-Calendar paper
- Ocupado video, paper
- ChronoLenses video, paper
- Stack Zooming video, paper
- LiveRAC video, paper

Data, Tasks, Design Study Methodology Week 2: Thu Sep 17

Required Reading/Watching

video Data Abstraction (VAD Ch 2), 27:34.
- Slides: pdf, pdf 16up, keynote.
video Task Abstraction (VAD Ch 3), 14:21.
- Slides: pdf, pdf 16up, keynote.
paper Design Study Methodology: Reflections from the Trenches and the Stacks.
- Michael Sedlmair, Miriah Meyer, and Tamara Munzner. IEEE TVCG 18(12):2431-2440, 2012.
- [type: model (process model)]

Online Discussion: Piazza @8 Data, @9 Tasks, @10 DSM

In Class

Exercise: Abstractions
Slides: pdf, pdf 16up, keynote
Discussion/Linkdump: Horrified, Evaluation example: Perceptual Guidelines for Creating Rectangular Treemaps

Further Reading

Marks & Channels, Layout, Rethinking Ranks Week 3: Thu Sep 24

Required Reading/Watching

video Marks and Channels I (VAD Ch 5), 34:10
- Slides: pdf, pdf 16up, keynote.
video Marks and Channels II (VAD Ch 5), 16:53.
- Slides: pdf, pdf 16up, keynote.
video Layout/Tables I (VAD Ch 7), 29:57
video Layout/Tables II (VAD Ch 7), 23:54
- Slides: pdf, pdf 16up, keynote.
paper Rethinking the Ranks of Visual Channels.
- Caitlyn M. McColeman, Fumeng Yang, Timothy F. Brady, Steven Franconeri. IEEE TVCG 28(1):707-717, 2022. DOI
- [type: evaluation (quant) ]
Discussion/Linkdump:
- A systematic method for surveying data visualizations and a resulting genomic epidemiology visualization typology: GEViT. Anamaria Crisan , Jennifer L Gardy , Tamara Munzner Bioinformatics, 35(10):1668-1676, 2019.
- Visualizing with Text by Richard Brath, CRC Press, 2020.
- Visual-Motor Recalibration in Geographical Slant Perception. Mukul Bhalla and Dennis R. Proffitt. Journal of Experimental Psychology: Human Perception and Performance 1999, Vol. 25, No. 4,1076-1096

Online Discussion: Piazza @13 Marks & Channels, @14 Layout/Tables, @15 Rethinking Ranks

In Class

Tools guidance
Slides: pdf, pdf 16up, keynote

Further Reading

Color, Rules of Thumb, HemoVis Week 4: Thu Oct 1

Required Reading/Watching

video Color (VAD Ch 10) I, 18:55.
video Color (VAD Ch 10) II, 6:00.
video Color (VAD Ch 10) III, 17:42.
- Slides: pdf, pdf 16up, keynote.
video Rules of Thumb (Ch 6), 31:42.
- Slides: pdf, pdf 16up, keynote.
paper Evaluation of Artery Visualizations for Heart Disease Diagnosis.
- Michelle A. Borkin, Krzysztof Z. Gajos, Amanda Peters, Dimitrios Mitsouras, Simone Melchionna, Frank J. Rybicki, Charles L. Feldman, and Hanspeter Pfister. IEEE TVCG 17(12):2479-2488, 2011. DOI
- [type: empirical / design study]

Online Discussion: Piazza @17 Color, @18 Rules of Thumb, @19 HemoVis

In Class

Project Pitches

Slides: pdf, pdf 16up, keynote
Exercise Color

Further Reading

Ch 10 (Color) Further Reading
Ch 6 (Rules of Thumb) Further Reading
Nadieh Bremer, A sky map of the Hubble Space Telescope's observations (detailed design walkthrough, includes substantial discussion of color palettes)

Interactivity, Multiple Views, Dashboards Week 5: Thu Oct 8

Required Reading/Watching

video Interactive Views (Ch 11), 25:39.
video Multiple Views (Ch 12), 29:28.
- Slides: pdf, pdf 16up, keynote.
paper Dashboard Design Patterns.
- Benjamin Bach, Euan Freeman, Alfie Abdul-Rahman, Cagatay Turkay, Saiful Khan, Yulei Fan, and Min Chen. IEEE TVCG 29(1):342-352, 2023.
- Supplemental materials
Discussion/Linkdump:
- Nullschool Earth another example of motion channel
- Search, Show Context, Expand on Demand paper (van Ham & Perer) as alternative to overview first
- Visual Parameter Space Analysis paper (Sedlmair et al) re considering parameter choices
- Data Navigator: An Accessibility-Centered Data Navigation Toolkit paper (Elavsky et al), but doesn't address accessability support for multiple views

Online Discussion: Piazza @21 Interactive Views, @22 Multiple Views, @23 Dashboard Design Patterns

In Class

Exercise Handling Complexity
Slides: pdf, pdf 16up, keynote

Further Readings

Aggregation, Embed, TensorFlow Week 6: Thu Oct 15

Required Reading/Watching

video Reduce: Aggregation & Filtering (VAD Ch 13), 24:40.
- Slides: pdf, pdf 16up, keynote.
video Embed: Focus+Context (VAD Ch 14), 8:53
- Slides: pdf, pdf 16up, keynote.
paper Visualizing Dataflow Graphs of Deep Learning Models in TensorFlow.
- Kanit Wongsuphasawat, Daniel Smilkov, James Wexler, Jimbo Wilson, Dandelion Mané, Doug Fritz, Dilip Krishnan, Fernanda B. Viégas, and Martin Wattenberg. IEEE TVCG 24(1):1-12, 2018.
- [type: design study]

Online Discussion: Piazza @26 Reduce, @27 Embed, @28 TensorFlow

In Class: Teams do Pre-Proposal Meetings with Tamara

Further Readings

Spatial/Maps, NecklaceMaps, Myriahedral Week 7: Thu Oct 22

Required Reading/Watching

video Geographic Maps (VAD Ch 8) , 38:05.
- Slides: pdf, pdf 16up, keynote.
paper Necklace Maps.
- Bettina Speckmann and Kevin Verbeek. IEEE TVCG 16(6):881-889, 2010.
- [type: algorithm]
paper Unfolding the Earth: Myriahedral Projections.
- Jarke J. van Wijk. The Cartographic Journal, 45(1):32-42, 2008.
- Video
- Demo
- [type: algorithm]

Online Discussion: Piazza @30 Geographic Maps, @31 Necklace Maps, @32 Myriahedral

In Class

Exercise: BallotMaps
Slides: pdf, pdf 16up, keynote

Followup reading: BallotMaps: Detecting name bias in alphabetically ordered ballot papers. Wood, J., Badawood, D., Dykes, J. & Slingsby, A. (2011). IEEE Transactions on Visualization and Computer Graphics, 17(12), pp. 2384-2391.

Further Readings

Ch 8 (Spatial Data) Further Reading

Networks, Abyss-Explorer, Lineage Week 8: Thu Oct 29

Required Reading/Watching

video Networks (VAD Ch 9) I, 38:08. Slides: pdf, pdf 16up, keynote.
paper ABySS-Explorer: visualizing genome sequence assemblies..
- Cydney B. Nielsen, Shaun D. Jackman, Inanc Birol, Steven J.M. Jones. TVCG 15(6):881-8, 2009.
- [type: design study]
paper Lineage: Visualizing Multivariate Clinical Data in Genealogy Graphs.
- Carolina Nobre, Nils Gehlenborg, Hilary Coon, Alexander Lex. IEEE TVCG 25(3): 1543-1558, 2019.
- Video
- [type: technique]

Online Discussion: Piazza @33 Networks, @34 AbySS-Explorer, @35 Lineage

In Class: Teams do Post-Proposal Meetings with Tamara

Further Reading

Ch 9 (Network Data) Further Reading

Polaris, D3, Vega-Lite Week 9: Thu Nov 5

Required Reading/Watching

paper Polaris: A System for Query, Analysis and Visualization of Multi-dimensional Relational Databases.
- Chris Stolte and Pat Hanrahan. Proc. InfoVis 2000.
- [type: system]
paper D3: Data-Driven Documents.
- Michael Bostock, Vadim Ogievetsky, Jeffrey Heer. IEEE TVCG 17(12):2301-2309, 2011.
- [type: system]
paper Vega-Lite: A Grammar of Interactive Graphics.
- Arvind Satyanarayan, Dominik Moritz, Kanit Wongsuphasawat, and Jeffrey Heer. IEEE TVCG 23(1):341-350, 2017.
- [type: system]

Online Discussion: Piazza @36 Polaris, @37 D3, @38 Vega-Lite

Further Reading

paper A layered grammar of graphics. Hadley Wickham. Journal of Computational and Graphical Statistics 19(1):3-28, 2010. [type: system/model] (R/tidyverse)
D3
- D3.js A powerful JavaScript library for manipulating documents based on data
- Interactive Data Visualization for the Web - An Introduction to Designing with D3 by Scott Murray (2nd edition, D3 v4)
- Technology fundamentals for D3.js (Slides by K. Wongsuphasawat, J. Hoffswell, D. Moritz)
- Intro to D3
- See the resource page for a longer discussion of readings for D3 (and a few other tools as well).

Week 10: Thu Nov 12

Required Reading/Watching: none

In Class: NO CLASS (IEEE VIS Conference week)

Project Reviews Week 11: Thu Nov 19

In Class: Project Peer Reviews

Post-Update Meetings Week 12: Thu Nov 26

In Class: Teams do 1on1 Post-Update Meetings with Tamara

Paper Writing and Research Process Week 13: Thu Dec 3

In Class

Lecture

Evals

Final Project Presentations Tue Dec 15 2pm-TBD, DMP 201

Final Papers Due Thu Dec 17 noon

About

Visualization is a crucial cornerstone of data science and a skill that is increasingly required in many other areas in science, engineering, business, and journalism. The scale and complexity of data that people must understand and reason about has exploded in nearly every field, so many students want to learn how to present data visually and gain fluency in visual data analysis. Visualization is suitable when there is a need to augment human capabilities rather than simply replace people with computational decision-making methods. Computer-based visualization systems provide visual representations of datasets designed to help people carry out tasks more effectively. In this course, you will learn about how to design and critique visualization systems through reading research papers and textbook chapters, working through deep-dive active learning exercises in small groups in class, and creating a substantial final project.

The course has a mostly flipped format, and is taught in a 3-hour block once a week. In the first 10 weeks students read textbook chapters and research papers and contribute to the asynchronous discussion about them before class. Students must post about each of three readings early in the week, and then respond to at least one post from another student within two more days. During class, I follow up the async discussion with additional commentary by answering selected topics in more depth through mini-lectures. Six of the class sessions are used for deep-dive active learning exercises in small groups, interleaved with reportbacks framed by critique and response from the instructor. No tooling is taught in the course; students are free to use whatever tools best match their strengths and interests.

The final project, conducted over the last 9 weeks, is typically done in small self-chosen student teams, with solo projects allowed by permission of instructor for well-justified requests. Four class sessions are devoted to project work, including a pitch session before teams are formed, pre-proposal meetings each team and me, pairwise peer reviews between teams, and post-update meetings with each team and me. Project work concludes with final presentations, then teams have a few more days in which to finish their final reports.

Audience

There are no enforced prerequisites. Grad students from other departments are very welcome. It is possible to for students in other disciplines to take this course without a programming background, by picking an analysis or survey project.

My past experience in teaching this course shows that students need strength in at least 1 and preferably 2 of these 3 skills to succeed: programming, English, HCI.

Strong English communication skills are important for success in this course: there are substantial reading, writing, discussion, and presentation components in the required work.
Many of the project types require programming, so that skill will give you the broadest possible set of options. However, there are no enforced prerequisites, and grad students from other departments are very welcome. It's possible to for students in disciplines outside of CS to take this course without a programming background, by picking an analysis or survey project.
HCI (human-computer interaction) is helpful but not required; it's useful to take CPSC 544 (fine to do so simultaneously this term), or have taken an equivalent methods course elsewhere.
Many other skills are useful, including computer graphics, cognitive psychology, machine learning, statistics, or algorithms. Also useful is expertise in a particular application domain if you intend to do your project in it (bioinformatics, computer systems, etc).
I have found that students with weak backgrounds in all three of these areas have often not succeeded in previous years: weak programming skills, weak English (for example, if English is your second language and you struggle with fluency), and no HCI background is not a recipe for success.

This graduate course does not teach visualization libraries: most students will pick up D3 (Javascript), ggplot (R), or python-based visualization tooling on their own.

For most undergrads, the 4th year undergrad visualization course, next offered in January 2026, is probably a better match; D3 will be explicitly taught and a programming background is required. If you nevertheless feel strongly that this course is the right one for you, email me and we'll discuss whether your background is a good fit.

Although the class is typically officially full at the start of term and often there's a waitlist, don't worry if you can't register: do show up anyway. In grad CS classes there is typically substantial churn in the first few weeks as people shop around, so it's extremely likely that you'll be able to get in. The waitlist has always been cleared in the past. I will give priority to people who have been attending all along and are caught up.

I'm open to unofficial auditors, there are usually a few each year. You'll get out what you put in: please do the reading for that session, so that you can participate in the in-class exercises and discussions. It's OK to come for the first several weeks and then stop if you get too busy with other things.

Previous Versions

Permanent URL of this page is http://www.cs.ubc.ca/~tmm/courses/547-26/

Tamara Munzner

Last modified: Wed Nov 4 22:36:19 MST 2026

Week	Date	Async Read/Discuss	Sync: In Class	Due
1	Sep 10		Logistics, Intro, Nested Model, Ex: Time Series
2	Sep 17	Data, Tasks, DSM	Ex: Abstraction
3	Sep 24	Marks & Channels, Layout, Rethinking Ranks	Decoding
4	Oct 1	Color, Rules of Thumb, HemoVis	Pitches	Pitches due Thu Oct 1 noon
5	Oct 8	Interactivity, Multiple Views, Dashboards	Ex: Handling Complexity	Groups finalized Fri Oct 9 noon
6	Oct 15	Aggregation, Embed, TensorFlow	Pre-Proposal Meetings
7	Oct 22	Spatial Data, NecklaceMaps, Myriahedral	Ex: Ballotmaps	Proposals due Fri Oct 23 noon
8	Oct 29	Networks, Abyss-Explorer, Lineage	Post-Proposal Meetings
9	Nov 5	Polaris, D3, Vega-Lite
10	Nov 12		NO CLASS (IEEE VIS)
11	Nov 19	(Project Updates)	Project Peer Reviews	Updates due Wed Nov 18 noon
12	Nov 26		Post-Update Meetings
13	Dec 3		Research Process
15	Dec 15/17		Final Presentations Tue Dec 15 2pm-TBD	Final Papers due Thu Dec 17 noon