What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention, and a need to allocate that attention efficiently among the overabundance of information sources that might consume it. -- Herb Simon
A graphic is never an end in itself; it is a moment in the process of decision making.-- Jacques Bertin
The course is run as a seminar. In addition to class discussions, participants will complete visualization assignments and a group visualization proposal. The ideal group size is three or four students. With approval, larger groups are possible. Your project group must be formed by the beginning of week four and your project or proposal topic must be approved by the end of week four. Project groups will share the results of their effort as both an interactive website and a video presentation.
The seminar meeting each week is devoted to discussing readings, tools and techniques, and your group's developing proposal ideas. In the beginning of the quarter, we will cover selected general background readings and discuss possible research proposal topics. As the quarter progresses, we will focus on readings chosen by groups to provide background information specific to their proposal.
By the end of the course, students will understand key visualization techniques and theory, have gained practical experience developing a visualization proposal, and advanced their skill with modern visualization toolkits.
- The Visual Display of Quantitative Information. Edward Tufte, Graphic Press.
- Envisioning Information. Edward Tufte, Graphic Press.
- Vega-Lite Visualization Notebook Curriculum. Jeffrey Heer, Dominik Moritz, Jake VanderPlas, and Brock Craft.
- Interactive Data Visualization for the Web, 2nd Edition. Scott Murray, "O'Reilly" Press.
Proposals and Implementation Level
All groups will develop an NSF-style research proposal. Developing a proposal will provide group members with useful experience in research collaboration and proposal writing. The level of implementation of visualizations associated with a proposal can very depending on implementation expertise but everyone should demonstrate an increase in their visual toolkit knowledge and skill over the duration of the course.
Schedule & Readings
- REQUIRED Communicating with Interactive Articles, Fred Hohman, Matt Conlen, Jeffrey Heer, Duen Horng (Polo) Chau, Distill, 2020 Journal.
- Optional Human-Centered Interactivity of Visualization Tools: Micro- and Macro-level Considerations, Kamran Sedig, Paul Parsons, Mark Dittmer, and Robert Haworth.
- Optional A Tour Through the Visualization Zoo, Jeffrey Heer, Michael Bostock, and Vadim Ogievetsky.
- Optional Visualizing Algorithms, Mike Bostock
- Optional Chapter 3: The Power of Representation, in Things That Make Us Smart. Don Norman.
- REQUIRED Chapter 1: Information Visualization, in Readings in Information Visualization, Stuart Card, Jock Mackinlay, and Ben Shneiderman, 1999.
- REQUIRED Cognitive Design of Tools of Thought, Barbara Tversky.
- REQUIRED Distribution of Information Processing While Performing Complex Cognitive Activities with Visualization Tools, Paul Parsons and Karran Sedig.
- Opetional Narrative Visualization: Telling Stories with Data, Edward Segel & Jeffrey Heer. InfoVis 2010.
- Optional Storytelling in the Wild: Implications for Data Storytelling, Barbara Tversky.
- Optional Reinventing Explanation. Michael Nielsen, 2014.
- Optional The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations, Ben Shneiderman. Proc. IEEE Conference on Visual Languages, 1996.
- REQUIRED Chapter 1: Graphical Excellence, Chapter 2: Graphical Integrity, and Chapter 3: Sources of Graphical Integrity, in The Visual Display of Qualitative Information, Edward Tufte.
- REQUIRED Notebook: Introduction to Vega-Lite.
- REQUIRED Notebook: Data Types, Graphical Marks, and Visual Encoding Channels.
- REQUIRED Notebook: Scales, Axes, and Legends.
- Optional Design and Redesign in Data Visualization, Martin Wattenberg and Fernanda Viégas. 2015.
- REQUIRED Chapter 4: Data-Ink and Graphical Redesign, Chapter 5: Chartjunk, and Chapter 6 Data-Ink Maximization and Graphical Design in The Visual Display of Qualitative Information, Edward Tufte.
- REQUIRED Multi-View Composition.
- REQUIRED Notebook: Interaction.
- REQUIRED Interactive Dynamics for Visual Analysis Jeffrey Heer & Ben Shneiderman. 2012.
- Optional The Death of Interactive Infographics? Dominikus Baur. 2017.
- Optional In Defense of Interactive Graphics, Gregor Aisch. 2017.
- Optional The PhD Thesis Deconstructed, Stu Card.
- REQUIRED Chapter 8: Data Density and Small Multiples, in The Visual Display of Qualitative Information, Edward Tufte.
- REQUIRED Chapter 2: Macro/Micro Readings, Chapter 4: Small Multiples : Data Density and Small Multiples, in Envisioning Information, Edward Tufte.
- REQUIRED Notebook: Introduction to D3, Part 1
- REQUIRED Notebook: Introduction to D3, Part 2
- Optional Chapters 2, 4, 5 in Interactive Data Visualization for the Web, 2nd Edition. Scott Murray.
- Optional D3: Data-Driven Documents. Michael Bostock, Vadim Ogievetsky & Jeffrey Heer. InfoVis 2011.
- Optional Vega Lite: A Grammar of Interactive Graphics. K. Wongsuphasawat, D. Moritz, A. Satyanarayan & J. Heer. OpenVis Conf 2017.
M., Carpendale, S., Lee, B., & Tory, M. Pre-design empiricism for information visualization:
Scenarios, methods, and challenges, 2014. In Proceedings of the Fifth Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization (pp. 147-151).
This paper advocates for pre-design empirical work so that visualization researchers can design with a deep understanding of the user, their needs, and their environment. It then provides four examples of pre-design work that illustrate different pre-design methods that provided necessary insights for making sure you have the right design, a design that is appropriate for the given situation.
Koshman, S. (2006). Visualization-based information retrieval on the web. Library & Information Science Research, 28(2), 192-207.
This paper reviews current existing visualization tools that were designed to graphically represent related documents found during web searches. While this isn’t exactly what we are trying to do, it still shows what design features are possible and provides recommendations and critiques.
Lam, H., Bertini, E., Isenberg, P., Plaisant, C., & Carpendale, S. (2011). Seven guiding scenarios for information visualization evaluation. University of Calgary Techreport, 2011-992-04.
This paper should help everyone with writing their proposals. It reviews seven types of evaluations in information visualization: evaluating visual data analysis and reasoning, evaluating user performance, evaluating user experience, evaluating environments and work practices, evaluating communication through visualization, automated evaluation of visualizations, and evaluating collaborative data analysis . They review 800 visualization publications and describe current best practices for each of these purposes, provide advice on what to evaluate for a given project, and provide examples from the literature.
R., Micallef, L., Bach, B., McGee, F., & Lee, B. (2018, June). Information visualization
evaluation using crowdsourcing. In Computer Graphics Forum (Vol. 37, No. 3,
This one is optional, but I included it because people might find it interesting. It is a review of papers from 2006-2017 that used crowdsourcing to evaluate their visualizations. It discusses challenges and opportunities for improvements in conducting crowdsourcing studies for visualization research.
Pohl, M. (2012). Methodologies for the Analysis of Usage Patterns in Information
VIsualization. In Proceedings of the 2012 BELIV Workshop: Beyond Time and Errors-Novel
Evaluation Methods for Visualization (pp. 1-3).
This brief paper describes the benefits and drawbacks of two common usage pattern analysis techniques: log file analysis and thinking aloud.
- Optional Chapters 6, 7, 8 in Interactive Data Visualization for the Web, 2nd Edition. Scott Murray.
- Optional A Nested Model for Visualization Design and Validation. Tamara Munzner. InfoVis 2009
- REQUIRED Neil P. Morris, Bronwen Swinnerton,and Taryn Coop. Lecture recordings to support learning: A contested space between students and teachers, Computers & Education (2019).
- REQUIRED Yang Shi, Chris Bryan, Sridatt Bhamidipati, Ying Zhao, Yaoxue Zhang, and Kwan-Liu Ma. MeetingVis: Visual Narratives to Assist in Recalling Meeting Context and Content, IEEE Transactions on Visualization and Computer Graphics, 2018, 1918-1929.
- REQUIRED Amy Pavel, Dan B Goldman, Björn Hartmann, and Maneesh Agrawala. SceneSkim: Searching and Browsing Movies Using Synchronized Captions, Scripts and Plot Summaries , UIST 2015, 181-190.
- Optional Chapters 9, 10, 11, 12 in Interactive Data Visualization for the Web, 2nd Edition. Scott Murray.
- Optional Design Study Methodology: Reflections from the Trenches and the Stacks. Michael Sedlmair, Miriah Meyer & Tamara Munzner. InfoVis 2012.
Your personal journal and participation in the seminar and discussion group will count for 30% of your final grade. Leadership of discusssion of the readings your group selects and the group's final project showcase will be another 20% of your final grade. Your proposal will count for the remaining 50% of your grade. The proposal grade and project showcase will include your contributions as judged by group members.
This seminar has evolved over the years. It began a couple decades ago following Pat Hanrahan and I co-chairing a DARPA ISAT study group on information visualization. The first version was modeled on a class Pat taught at Stanford. Over the years I have included content from courses offered by Tamara Munzer at UBC and Maneesh Agrawala at Berkeley and Stanford. The current version also incorporates content from Jeff Heer's course at UW, including linking to the excellent Vega-Lite Visualization Notebook Curriculum developed by Jeff, Dominik Moritz, Jake VanderPlas, and Brock Craft.