Instructor: Tamara Munzner
First Class: Wed Sep 8 2021
Last Class: Wed Dec 1 2021
Time/Location: Wed 3-6pm, SWNG 207 FSC 2330
Office Hours: Wed 6-7pm in classroom. Or by appointment, in person (X661) or zoom - check my calendar and request a spot by email.
UBC Cal Page: CPSC 547
Canvas Page: 547 Canvas Page
Piazza Page: 547 Piazza (signup link) Please join Piazza, it's a main avenue of communication for this course!

Visualization Analysis and Design, Tamara Munzner (A K Peters Visualization Series, CRC Press, 2014) is the course textbook.

The UBC library has multiple ebook licenses so you can read it for free: library catalog page, EZProxy direct link.

To buy your own copy online, it's currently around US$77 new (with shipping) from amazon.com, on sale for US$72 directly from CRC Press, and CD$104 from amazon.ca. If you buy the hardcover book, you'll get the ebook version for free; you can also buy an ebook-only for less, or rent the ebook for even less.

All additional readings are research papers available online for free, links posted below. For digital library access from off-campus, use EZproxy with your CWL login through the UBC library.
EZproxy direct links: IEEE DL, Springer DL, ACM DL, JSTOR

• VAD Chapter 1. What's Vis, and Why Do It?
• Course Logistics
  • main/syllabus (this page!)
  • course structure
  • project structure

Slides: pdf, pdf 16up, keynote

Online Discussion: see Piazza posts @7 self-intros, @8 reading list, @9 Ch 1 comments

In Class Exercise: Time Series
Signup sheet: Signup

Further Reading

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

• VAD Chapter 2. What: Data Abstraction
• VAD Chapter 3. Why: Task Abstraction
• paper A Nested Model for Visualization Design and Validation. Tamara Munzner. IEEE TVCG (Proc. InfoVis 2009) 15(6):921-928, 2009.
[type: model]

Slides: pdf, pdf 16up, keynote

In Class Exercise: Abstractions (source: Bertini)

Further Reading

• Ch 2 (Data Abstraction) Further Reading
• Ch 3 (Task Abstraction) Further Reading

• VAD Chapter 5. Marks and Channels
• VAD Chapter 6. Rules of Thumb
• paper Design Study Methodology: Reflections from the Trenches and the Stacks. Michael Sedlmair, Miriah Meyer, and Tamara Munzner. IEEE Trans. Visualization and Computer Graphics (Proc. InfoVis 2012), 18(12):2431-2440, 2012. [type: model]

Slides: pdf, pdf 16up, keynote

In Class Exercise: Decoding (source: Bertini)
Signup sheet: Signup

Discussion Pointers

• motion coding example (animal migration)
• Principles of traditional animation applied to 3D computer animation Lasseter paper: Disney->Pixar principles. hand-drawn animation carefully designed so you're looking at only one thing at a time!
• Value of Visualization, van Wijk paper about what "good enough" might mean
• Outside In video, complex 3D shape where animation is helpful
• Structuring information interfaces for procedural learning. Zacks and Tversky paper with example of saxophone assembly, small multiples vs animation

Further Reading

• Ch 5 (Marks & Channels) Further Reading
• Ch 6 (Rules of Thumb) Further Reading
• pointers to many design studies

• VAD Chapter 7. Arrange Tables
• paper LineUp: Visual Analysis of Multi-Attribute Rankings. Samuel Gratzl, Alexander Lex, Nils Gehlenborg, Hanspeter Pfister, Marc Streit. IEEE Trans. Visualization and Computer Graphics (Proc. InfoVis 2013), 19(12):2277-2286, 2013. [type: technique]
• paper Revisiting Bertin Matrices: New Interactions for Crafting Tabular Visualizations. Charles Perin, Pierre Dragicevic, Jean-Daniel Fekete. IEEE Trans. Visualization and Computer Graphics (Proc. InfoVis 2014), 20(12):2082-2091, 2014. [type: technique]

Slides: pdf, pdf 16up, keynote

In Class: Project Pitches

Further Reading

• Ch 7 (Table Data) Further Reading

• VAD Chapter 10. Map Color and Other Channels
• 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 (Proc. InfoVis 2011), 17(12):2479-2488, 2011. [type: empirical / design study]
• paper Rainbows Revisited: Modeling Effective Colormap Design for Graphical Inference. Khairi Reda and Danielle Albers Szafir. IEEE TVCG (Proc. InfoVis 2020). [type: empirical]

In Class Exercise: 2Nums; Color (source: Pfister/Lex/Ortiz; Rheingans)

Slides: pdf, pdf 16up, keynote

Further Reading

• Ch 10 (Color) Further Reading
• Santiago Ortiz, 45 Ways to Communicate Two Quantities
• Nadieh Bremer, A sky map of the Hubble Space Telescope's observations (detailed design walkthrough, includes substantial discussion of color palettes)

• Tools guidance
• VAD Chapter 9. Arrange Networks
• 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 (Proc. InfoVis 2009). [type: design study]
• paper Interactive Visualization of Genealogical Graphs. Michael J. McGuffin, Ravin Balakrishnan. Proc. InfoVis 2005, pp 17-24. [type: technique]
  • video

In Class: Project Groups Meet with Tamara

Further Reading

• Ch 9 (Network Data) Further Reading

• VAD Chapter 8. Arrange Spatial Data
• paper Necklace Maps. Bettina Speckmann and Kevin Verbeek. IEEE TVCG (Proc. InfoVis 2010) 16(6):881-889. [type: algorithm]
• paper Unfolding the Earth: Myriahedral Projections. Jarke J. van Wijk. The Cartographic Journal, 45(1):32-42, 2008. [type: algorithm]
  • Video
  • Demo

Slides: pdf, pdf 16up, keynote

In Class Exercise: Ex: Ballotmaps
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

Pointers from Discussion

• Online Dynamic Graph Drawing from Frishman and Tal. providing spatial stability for streaming data, avoiding non-determinism
• Simple Algorithms for Network Visualization: A Tutorial from McGuffin, on matrix re-ordering (and also 1D case of node reordering)
• Seriation and Matrix Reordering Methods: An Historical Overview from Liiv, matrix re-ordering survey
• The State of the Art in Multilayer Network Visualization from McGee et al, survey on multi-level graphs
• Topological Fisheye Views for Visualizing Large Graphs from Gansner, Koren, and North. coarsening multi-level graphs according to both topological and geometric info
• Graphical Inference for Infovis from Wickham, Cook, Hofmann, and Buja. interesting exploitation of randomness

• paper Polaris: A System for Query, Analysis and Visualization of Multi-dimensional Relational Databases. Chris Stolte and Pat Hanrahan. Proc. InfoVis 2000. [type: system]

In Class: NO SYNC CLASS attend virtual IEEE VIS Conference (any two 90-minute sessions, post 1 comment per session)

• main conference site: http://ieeevis.org/
• free registration for students: direct link to registration
• virtual conference site with full program (register to access): https://virtual.ieeevis.org/
• serendipitous paper browser is cool to find interesting content!
• only exclusion: my full-day tutorial Sunday does not count
• best to attend full session in realtime with both prerecorded talks and live Q&A. but it's also acceptable to just watch a session's worth of pre-recorded paper talks (there are 6 paper talks in each session)
• I said in class full-day Observable tutorial on Monday could be useful if you want to learn D3, but now I see it's not so much about basic D3 and more about how to use D3 in Observable if you already know it. So, never mind!

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
  • paper D3: Data-Driven Documents. Michael Bostock, Vadim Ogievetsky, Jeffrey Heer. IEEE Trans. Visualization & Comp. Graphics (Proc. InfoVis), 2011. [type: system]
  • 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).

• VAD Chapter 11. Manipulate View
• VAD Chapter 12. Facet into Multiple Views
• paper Pattern-Driven Navigation in 2D Multiscale Visualizations with Scalable Insets. Fritz Lekschas, Michael Behrisch, Benjamin Bach, Peter Kerpedjiev, Nils Gehlenborg, and Hanspeter Pfister. TVCG 26(1):611-621, 2020 (Proc InfoVis 2019). [type: technique]
  • Videos

Slides: pdf, pdf 16up, keynote

In Class Exercise Ex: Handling Complexity
Followup reading:
Animation vs traces vs small multiples: Effectiveness of Animation in Trend Visualization. Robertson, Fernandez, Fisher, Lee, and Stasko. TVCG/InfoVis 2008.
EdgeMaps: Visualizing Explicit and Implicit Relations of Complex Information Spaces. Dörk, Carpendale, Williamson. Information Visualization 2012.

Further Readings

• Ch 11 (Manipulate) Further Reading
• Ch 12 (Multiple Views) Further Reading

Slides: pdf, pdf 16up, keynote

In Class: Peer Review

Pointers from Discussion

• Wind Map: example of motion coding to show attributes
• Progressive Data Analysis and Visualization: example of handling big data incrementally/progressively
• TreeJuxtaposer: example of guaranteed frame rate rendering
• Buckets: example of manageable number of multiple views
• Histogram binning revisited with a focus on human perception: checking automatic binning against what people actually notice

Further Readings

• Ch 13 (Reduce) Further Reading

• VAD Chapter 14. Embed: Focus+Context
• 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 (Proc. VAST 2017) 24(1):1-12, 2018. [type: design study]

In Class: Post-Update Groups Meet with Tamara

Further Readings

• Ch 14 (Embed) Further Reading

Slides: pdf, pdf 16up, keynote

In Class: Lecture, Evals

• Information Visualization, Fall 2020
• Information Visualization, Fall 2019
• Information Visualization, Fall 2017
• Information Visualization, Spring 2017
• Information Visualization, Fall 2015
• Information Visualization, Fall 2014
• Information Visualization, Fall 2011
• Information Visualization, Fall 2009
• Information Visualization, Fall 2007
• Information Visualization, Fall 2006
• Information Visualization, Fall 2005
• Information Visualization, Fall 2004
• Information Visualization, Spring 2004
• Information Visualization, Spring 2003