MSAN 622: Data Visualization

This course introduces common data visualization techniques and design principles using python with the seaborn, bokeh, plotly, and networkx packages. Students design and implement interactive, multivariate, text, hierarchical, network, and temporal data visualizations. Restriction: Restricted to Graduate level; Restricted to Analytics Majors

Course Schedule

Tuesday, March 20 - Introduction to Data Visualization

Steven Johnson, How the Ghost Map Helped End a Killer Disease at TedSalon2006, 2006.
Matejka, Justin, and George Fitzmaurice. Same stats, different graphs: generating datasets with varied appearance and identical statistics through simulated annealing. Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. ACM, 2017.
Hans Rosling, Let my Dataset Change your Mindset at TED@State, 2009.
Hans Rosling, The best stats you've ever seen, 2006.
Laramee, Robert S, How to read a visualization research paper: Extracting the essentials. Computer Graphics and Applications, IEEE 31.3 (2011): 78-82.
Segel, Edward, and Jeffrey Heer. Narrative visualization: Telling stories with data." IEEE transactions on visualization and computer graphics 16.6 (2010): 1139-1148.

Thursday, March 22 - Perception & Color

David Borland and Russell M. Taylor II, Rainbow Color Map (Still) Considered Harmful, CG & A, March/April 2007 (vol. 27 no. 2), pp. 14-17
Maureen Stone, Representing Colors as Three Numbers, Computer Graphics and Applications, 25(4), July 2005, pp. 78-85.
Cynthia Brewer, ColorBewer: Color Advice for Maps

Tuesday, March 27 and Thursday, March 29 - Multivariate Data Visualization Techniques

YH Fua, MO Ward, and IA Rundensteiner (1999), Hierarchical Parallel Coordinates for Exploration of Large Datasets, Proceedings of IEEE Visualization '99, pp. 43-50.
Stolte, C., Tang, D., and Hanrahan, P., Polaris: a system for query, analysis, and visualization of multidimensional databases, Commun. ACM 51, 11 (Nov. 2008), 75-84.
Mark A. Livingston, Jonathan W. Decker, Evaluation of Trend Localization with Multi-Variate Visualizations. IEEE Trans. Vis. Comput. Graph. 17(12): 2053-2062 (2011)

Tuesday, April 3rd - Interactivity

Andy Cockburn, Amy Karlson, and Benjamin B. Bederson. A review of overview+detail, zooming, and focus+context interfaces. ACM Computing Surveys 41(1), pp. , 2008.
Jack J. van Wijk and Wim A.A. Nuij,Smooth and Efficient Zooming and Panning, Proc. InfoVis 2003, p. 15-22
Beth Yost and Chris North (2006), The Perceptual Scalability of Visualization, IEEE Transactions on Visualization and Computer Graphics, vol. 12, no. 5, pp. 837-844.
Jonathan C. Roberts. On Encouraging Multiple Views for Visualization. In IEEE Information Visualization, pages 8-14, July 1998.

Thursday, April 5 - Temporal Data

Tuesday, April 10 - Evaluation

Robert Kosara, Christopher G. Healey, Victoria Interrante, David H. Laidlaw, and Colin Ware. User Studies: Why, How, and When?. IEEE Comput. Graph. Appl. 23, 4 (July 2003), 20-25.
Ben Shneiderman, Catherine Plaisant, Strategies for evaluating information visualization tools: multi-dimensional in-depth long-term case studies, BELIV '06 Proceedings of the 2006 AVI workshop on BEyond time and errors: novel evaluation methods for information visualization.
Tory, M., Moeller T. Evaluating Visualizations: Do Expert Reviews Work? IEEE Computer Graphics and Applications, 25(5), 2005, 8-11.
Heidi Lam, Enrico Bertini, Petra Isenberg, Catherine Plaisant, Sheelagh Carpendale, Empirical Studies in Information Visualization: Seven Scenarios, TVCG, December 2011

Thursday, April 12 - Geospatial Data & Projections

Tuesday, April 17 - Trees & Hierarchical Data

Ben Shneiderman. Tree visualization with tree-maps: 2-d space-filling approach. ACM Trans. Graph. 11, 1 (January 1992), 92-99.
Alfred Kobsa. User Experiments with Tree Visualization Systems. In Proceedings of the IEEE Symposium on Information Visualization (INFOVIS '04). IEEE Computer Society, Washington, DC, USA, 9-16.
Bruls, M., Huizing, K., Van Wijk, J. J. (2000). Squarified treemaps. In Data visualization 2000 (pp. 33-42). Springer, Vienna.
Balzer, Michael, Oliver Deussen, and Claus Lewerentz. Voronoi treemaps for the visualization of software metrics. In Proceedings of the 2005 ACM symposium on Software visualization, pp. 165-172. ACM, 2005.
Gortler, Jochen, Christoph Schulz, Daniel Weiskopf, and Oliver Deussen. Bubble Treemaps for Uncertainty Visualization. IEEE transactions on visualization and computer graphics 24, no. 1 (2018): 719-728.

Thursday, April 19 - Alpha Presentations (Final Project)

Thursday, April 24 - Graphs & Networks - Alpha Presentations (Final Project)

Chapter 9 from the Visualization Analysis and Design book by Tamara Munzner
Ghoniem, Mohammad, J-D. Fekete, and Philippe Castagliola. A comparison of the readability of graphs using node-link and matrix-based representations." Information Visualization, 2004. INFOVIS 2004. IEEE Symposium on. Ieee, 2004.
Interactive d3 demo showing both node-link and matrix-representations for the same graph.
Henry, Nathalie, Jean-Daniel Fekete, and Michael J. McGuffin. "NodeTrix: a hybrid visualization of social networks." IEEE transactions on visualization and computer graphics 13.6 (2007): 1302-1309.

Thursday, April 26 - Beta presentations (Final Project)

Tuesday, May 1 - Textual Structures

Thursday, May 3 - Communicating Uncertainty

Kay, Matthew, Tara Kola, Jessica R. Hullman, and Sean A. Munson. "When (ish) is my bus?: User-centered visualizations of uncertainty in everyday, mobile predictive systems." In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, pp. 5092-5103. ACM, 2016.
Wood, Jo, Petra Isenberg, Tobias Isenberg, Jason Dykes, Nadia Boukhelifa, and Aidan Slingsby. "Sketchy rendering for information visualization." IEEE Transactions on Visualization and Computer Graphics 18, no. 12 (2012): 2749-2758.