CONJ 610: Fundamentals of Data Visualization

Synopsis

Data visualization is very interesting and nifty. The simple act of attending this class is guaranteed to enhance your evolutionary fitness.

More seriously, this course is designed to give students a foundation in the principles of data visualization, particularly as applied to scientific and technical data. In large part, the specific details that we cover will be determined by the interests and backgrounds of the students.

As this is a "nano-course", grading will be based on class participation and on turning in completed assignments. There will also be a final group project.

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Instructors

CONJ 610's instructors are Jackie Wirz and Steven Bedrick.

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Textbook

We will be drawing material from a wide variety of sources for this course; as such, there is no single, required text book per se. However, we will frequently refer to Nathan Yau's Data Points, and highly recommend that anybody taking this class have a copy.

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Schedule

Date	Topic
Oct. 2	Introduction: Why visualize? | data/ink ratio | different types of graphs, etc. [pdf]
Oct. 9	Visual Perception: neurology[part 1] [part 2]
Oct. 16	Color, HW discussion [pdf]
Oct. 23	Graphs [part 1][part 2]
Oct. 30	Tables [part 1][part 2]
Nov. 6	Networks & Trees [part 1][part 2]
Nov. 13	(Cancelled due to Snow)
Nov. 20	Maps! [pdf]
Nov. 27	Thanksgiving (no class)
Dec. 4	Multidimensional Data: heat maps, topography, 3D
Dec. 11	Ethics
Dec. 18	Visualization Tools

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Resources

Useful books

• William Cleveland, The Elements of Graphing Data
• Colin Ware, Information Visualization: Perception for Design
• Stephen Kosslyn, Graph Design for Eye and Mind
• Nathan Yau
  • Data Points
  • Visualize This
• Stephen Few, Now You See It: Simple Visualization Techniques for Quantitative Analysis
• Alberto Cairo, The Functional Art: An Introduction to Information Graphics and Visualization
• Katy Börner, Visual Insights: A Practical Guide to Making Sense of Data
• Joel Katz, Designing Information: Human Factors and Common Sense in Information Design
• Manuel Lima
  • Visual Complexity: Mapping Patterns of Information
  • The Book of Trees: Visualizing Branches of Knowledge
• Edward Tufte
  • The Visual Display of Quantitative Information
  • Envisioning Information
  • Visual Explanations
  • Beautiful Evidence
• Rudolf Arnheim, Visual Thinking
• Scott McCloud, Understanding Comics: The Invisible Art

Websites of note

• Visualising Data's "Resources" index'
• OHSU Communications Office (Graphic Design services, etc.)
• A useful tutorial on using the Seaborn Python library for visualizing distributions.
• Blogs:
  • FlowingData
  • The Why Axis
  • eagereyes
  • Visua.ly's blog
  • Junk Charts
• Resources:
  • ColorBrewer
  • Adobe Kuler
• Are we missing a favorite of yours? Let us know!

Additional Readings

• Dörk M, Feng P, Collins C, Carpendale S. Critical InfoVis: exploring the politics of visualization. Proc. 'CHI 2013.
• Shneiderman B. Research agenda: Visual overviews for exploratory search. Information Seeking Support Systems. 2008;11:4.
• The Why Axis's "Mind the Gap: An Economic Chart Remake", by Jon Schwabish
• Borland D, Taylor MR. Rainbow color map (still) considered harmful. IEEE computer graphics and applications. 2007 Mar;27(2):14–7.

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Student Access Statement

Our program is committed to all students achieving their potential. If you have a disability or think you may have a disability (physical, learning, hearing, vision, psychological) which may need a reasonable accommodation please contact Student Access at (503) 494-0082 or e-mail studentaccess@ohsu.edu to discuss your needs. You can also find more information at www.ohsu.edu/student-access. Because accommodations can take time to implement, it is important to have this discussion as soon as possible. All information regarding a student’s disability is kept in accordance with relevant state and federal laws.