Schedule

Lecture 1: Introduction

Recommended reading

• A Tour through the Visualization Zoo. Jeffrey Heer, Michael Bostock, Vadim Ogievetsky. Communications of the ACM, 53(6), pp. 59-67, Jun 2010.
• The Value of Visualization.Jarke van Wijk. Proceedings of the IEEE Visualization Conference, pp. 79-86, 2005.

Lecture 2: Perception, Cognition, Color

Mandatory reading

• VAD, Chapters 10.2-10.3, Color Theory and Colormaps

Recommended reading

• Perception in Visualization, Christopher G. Healey
• Gestalt principles (part 1). Bang Wong. Nature Methods 7, pp. 863, Nov 2010.
• Gestalt principles (part 2). Bang Wong. Nature Methods 7, pp. 941, Dec 2010.

Lecture 3: Version Control; HTML and SVG.

Mandatory reading

• D3 Book, Chapters 1-3
• VDA Book, Chapter 1

Recommended reading

• Think like a git
• Understanding git conceptually
• Fun and insightful talk on git by Linus Torvalds
• A successful git branching model
• MDN HTML Elements reference
• MDN CSS Reference
• MDN selectors webpage
• Overview of the Chrome developer tools
• MDN SVG tutorial

Lecture 4: Data Abstraction, Data Types.

Mandatory reading

• VAD, Chapter 2, Data Abstraction

Recommended reading

• On the Theory of Scales of Measurement. S. S. Stevens. Science, 103(2684), pp. 677-680, June 1946.

Lecture 5: JavaScript Basics

Mandatory reading

• D3 Book, Chapter 3, go over JavaScript parts.

Recommended reading

• MDN JavaScript Guide
• Code Academy Javascript Tutorial

Lecture 6: The Visualization Alphabet: Marks and Channels.

Mandatory reading

• Crowdsourcing graphical perception: using mechanical turk to assess visualization design. Jeff Heer, Mike Bostock. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 2010.
• VAD, Chapter 5, Marks and Channels
• VAD, Chapter 10.4, Mapping Other Channels

Recommended reading

• Graphical Perception: Theory, Experimentation and the Application to the Development of Graphical Models. William S. Cleveland, Robert McGill, J. Am. Stat. Assoc. 79:387, pp. 531-554, 1984.
• The Structure of the Information Visualization Design Space. Stuart Card and Jock Mackinlay. Proceedings of InfoVis, 1997.

Lecture 7: DOM Manipulation, D3

Mandatory reading

• D3 book, Chapters 4, 5 and 6

Recommended reading

• MDN Document Object documentation
• D3 API

Lecture 8: Design Guidelines

Mandatory reading

• The good, the bad, and the biased: five ways visualizations can mislead (and how to fix them). Danielle Albers Szafir. Interactions. 2018.
• VAD, Chapters 6.3-6.6, and 6.9, Rules of Thumb
• VAD, Chapter 6.10, Function First, Form Next
• VAD, Chapter 3, Why: Task Abstraction

Recommended reading

• Design Principles for Visual Communication. Maneesh Agrawala, Wilmot Li, Floraine Berthouzoz. Communications of the ACM, 54(4), pp. 60-69, Apr 2011.
• Design of data figures. Bang Wong. Nature Methods 7, pp. 665, Sept 2010.
• USA Temperature: can I sucker you?

Lecture 9: D3 Maps

Mandatory reading

• D3 book, Chapters 11 and 12

Recommended reading

• Mike Bostock’s Let’s make a Map

Lecture 10: Interaction

Mandatory reading

• Interactive dynamics for visual analysis, Heer, J., & Shneiderman, B. Communications of the ACM 55(4), 2012.
• VAD, Chapter 11, Manipulate View
• VAD, Chapter 6.8, Responsiveness Is Required

Lecture 11: D3 Layouts

Mandatory reading

• D3 book, Chapters 7, 8, 9 and 10

Recommended reading

• How selections work
• Jerome Cukier’s tutorial on scales
• Let’s make a bar chart

Lecture 12: Views; Focus and Context

Mandatory reading

• VDA Chapter 12, Facet into Multiple Views
• VDA Chapter 14, Embed: Focus + Context

Lecture 13: Advanced JS and D3

Lecture 15: Visualizing Tabular Data (Two Parts)

Mandatory reading

• VDA Chapter 7, Tables

Recommended reading

• Taggle: Scalable Visualization of Tabular Data through Aggregation. Katarina Furmanova, Samuel Gratzl, Holger Stitz, Thomas Zichner, Miroslava Jaresova, Alexander Lex, Marc Streit

Lecture 16: Visualizing Tabular Data (Two Parts)

Mandatory reading

• VDA Chapter 7, Tables

Recommended reading

• Taggle: Scalable Visualization of Tabular Data through Aggregation. Katarina Furmanova, Samuel Gratzl, Holger Stitz, Thomas Zichner, Miroslava Jaresova, Alexander Lex, Marc Streit

Lecture 19: Project Peer Feedback in Groups

Lecture 20: Storytelling with Visualization

Mandatory reading

• E. Segel and J. Heer, “Narrative Visualization: Telling Stories with Data,” IEEE Transactions on Visualization and Computer Graphics, vol. 16, no. 6, pp. 1139–1148, Nov. 2010.

Lecture 21: Visualizing Networks and Trees

Mandatory reading

• VDA Chapter 9, Arrange Networks and Trees

Recommended reading

• S. Kieffer, T. Dwyer, K. Marriott, and M. Wybrow, “HOLA: Human-like Orthogonal Network Layout,” IEEE Transactions on Visualization and Computer Graphics, vol. 22, no. 1, pp. 349–358, Jan. 2016.

Lecture 22: Visualizing Multivariate Networks

Recommended reading

• C. Nobre, M. Meyer, M. Streit, and A. Lex, “The State of the Art in Visualizing Multivariate Networks,” Computer Graphics Forum (EuroVis 2019), vol. 38, no. 3, pp. 807–832, 2019.
• MVNV Companion Website

Project Feedback with Instructors

Lecture 23: Tasks Analysis, Designing and Evaluating Visualizations

Mandatory reading

• A nested model for visualization design and validation. Tamara Munzner. IEEE Transactions on Visualization and Computer Graphics 15(6), 2009.
• VAD, Chapter 4, Analysis: Four Levels for Validation
• S. Carpendale, “Evaluating Information Visualizations,” in Information Visualization: Human-Centered Issues and Perspectives, Springer Berlin Heidelberg, 2008, pp. 19–45.

Recommended reading

• H. Lam, E. Bertini, P. Isenberg, C. Plaisant, and S. Carpendale, “Empirical Studies in Information Visualization: Seven Scenarios,” IEEE Transactions on Visualization and Computer Graphics, vol. 18, no. 9, pp. 1520–1536, 2012.
• Design Activity Framework for Visualization Design (Section 4-4.3). Sean McKenna, Dominika Mazur, James Agutter, Miriah Meyer. IEEE Transactions on Visualization and Computer Graphics (InfoVis ’14), 20(12), pp. 2191-2200, 2014.
• Parallel Prototyping Leads to Better Design Results, More Divergence, and Increased Self-Efficacy. Dow, Steven P., et al. Design Thinking Research. Springer Berlin Heidelberg, 2012. 127-153.
• Sketching Designs Using the Five Design-Sheet Methodology. Roberts, Jonathan C., Chris Headleand, and Panagiotis D. Ritsos. IEEE Transactions on Visualization and Computer Graphics 22.1 (2016): 419-428.
• VizItCards: A Card-Based Toolkit for Infovis Design Education. He, Shiqing, and Eytan Adar. IEEE Transactions on Visualization and Computer Graphics (2016).

Lecture 24: Maps

Lecture 25: Text Visualization

Mandatory reading

Recommended reading

• “Text visualization techniques. Taxonomy, visual survey, and community insights”, Kostiantyn Kucher, Andreas Kerren, IEEE Pacific Visualization Symposium, 2015

Lecture 26: Filtering & Aggregation

Mandatory reading

• VDA Ch. 13 Reduce Items and Attributes

Lecture 27: Set Visualization

Mandatory reading

• A. Lex and N. Gehlenborg, “Points of view: Sets and intersections,” Nat Meth, vol. 11, no. 8, pp. 779–779, Aug. 2014.

Recommended reading

• B. Alsallakh, L. Micallef, W. Aigner, H. Hauser, S. Miksch, and P. Rodgers, “The State-of-the-Art of Set Visualization,” in Computer Graphics Forum, 2016, vol. 35, pp. 234–260.
• A. Lex, N. Gehlenborg, H. Strobelt, R. Vuillemot, and H. Pfister, “UpSet: Visualization of Intersecting Sets,” IEEE Transactions on Visualization and Computer Graphics (InfoVis ’14), vol. 20, no. 12, pp. 1983–1992, 2014.

Lecture 28: Best Project Presentations, Wrap-Up