I'm very excited to preview the syllabus of a new dataviz course I've been developing to be launched in Spring 2014. This course is focused on the craft of graph building, and is modeled after the writing workshop. Students will work through multiple drafts of a project while giving and receiving criticism from other students. To my knowledge, this is a one-of-a-kind course so I'm putting up the syllabus and will report on how it goes over in a few months. I hope the format will prove successful and others will offer graph building workshops in the years to come. I'm open to suggestions about the syllabus.
The course is offered as part of the brand-new Certificate in Analytics and Data Visualization at New York University. The announcement of the Certificate is here.
You can sign up for the course here. Please spread the word!
NEW YORK UNIVERSITY
CERTIFICATE IN ANALYTICS AND DATA VISUALIZATION
COURSE TITLE: The Art of Data Visualization (DATA1-CE9002)
FEB/MAR 2014, Saturday mornings
Woolworth Bldg, NYC
Instructor: Kaiser Fung
Data visualization is storytelling in a graphical medium. The format of this course is inspired by the workshops used extensively to train budding writers, in which you gain knowledge by doing and redoing, by offering and receiving critique, and above all, by learning from each another. Present your project while other students offer critique and suggestions for improvement. The course offers immersion into the creative process, the discipline of sketching and revising, and the practical use of tools. You will develop a discriminating eye for good visualizations. Readings on aspects of the craft are assigned throughout the term. For students in the Certificate of Analytics and Data Visualization, the course offers a chance to demonstrate mastery of the integrated approach combining the perspectives of statistical graphics, graphical design, and information visualization.
- Give constructive critique on other people’s data visualization
- Listen and respond to critique from others on one’s own data visualization
- Evaluate alternative visualization of the same data
- Refine and improve drafts of data visualization projects
- Interpret data visualization with an integrated lens combining the perspectives of statistical graphics, graphic design, and information visualization
- Create at least one piece of work that can be included in one’s portfolio
This is not a beginner’s class. You should have prior experience making data graphics for an audience, and feel comfortable offering critique of other’s work. For students in the Certificate of Analytics and Data Visualization, appropriate preparation includes these courses: Introduction to Analytics and Data Visualization, Statistical Foundations of Analytics and Data Visualization, Applied Data Management for Analytics and Data Visualization, and Designing Data: Infographics. Because of these prerequisites, you may execute designs in your preferred set of tools, such as Excel, Adobe Illustrator, R, Processing, Tableau, and JMP.
Edward Tufte. The Visual Display of Quantitative Information (Graphics Press)
Julia Steele and Noah Illinsky (eds.). Beautiful Visualization: Looking at Data Through the Eyes of Experts (O’Reilly, 2010)
Don Norman. The Design of Everyday Things: Revised and Expanded Edition. (Basic Books, 2013)
Required Course Readings:
Kosara, Robert. "Visualization criticism-the missing link between information visualization and art." In Information Visualization, 2007. IV'07. 11th International Conference, pp. 631-636.
Kosara, Robert, “What is Visualization? A Definition”, blog post, July 2008. http://eagereyes.org/criticism/definition-of-visualization
Kirk, Andy, “Walking the tightrope of visualization criticism: the balance, fairness and realism of our visualization criticism must improve”, blog post, July 2012. http://strata.oreilly.com/2012/07/visualization-criticism.html
Kosara, Robert, “A Criticism of Visualization Criticism Criticism”, blog post, July 2012. http://eagereyes.rog/criticism/criticism-visualization-criticism-criticism. The above three references form a dialogue.
Gelman, Andrew, and Antony Unwin, “Infovis and Statistical Graphics: Different Goals, Different Looks”, Journal of Computational and Graphical Statistics 22(1): pp.2-28.
Gelman, Andrew, and Antony Unwin, “Tradeoffs in Information Graphics”, Journal of Computational and Graphical Statistics 22(1), 2013: pp. 45-49. This is a rejoinder to the discussion of the previous article.
Mitchell, Ian. "AUThoRiTy oR CLiChé? the graphic language of information Design." research, education and design experiences (2012).
Rhyne, Theresa-Marie, “Does the Difference Between Information and Scientific Visualization Really Matter?” IEEE Computer Graphics and Applications 23(3): 6-8.
North, Chris, “Toward Measuring Visualization Insight”, IEEE Computer Graphics and Applications, May/June 2006, pp. 6-9.
Heer, Jeffrey, et. al., “A Tour Through the Visualization Zoo”, Communications of the ACM 53(6): June 2010, pp. 59-67.
Optional but recommended:
Other Ed Tufte books
Any book by Howard Wainer (Visual Revelations, Graphic Discovery, etc.)
Van Wijk, Jarke J., “Views on Visualization”, IEEE Transactions on Visualization and Computer Graphics 12(4): July/August 2006, pp. 421-432.
Zangwill, Nick, "Aesthetic Judgment", The Stanford Encyclopedia of Philosophy (Summer 2013 Edition), Edward N. Zalta (ed.). http://plato.stanford.edu/entries/aesthetic-judgment/
Websites: There are a lot of blogs showcasing visualization projects. (List of blogs to be added)
Class attendance: 30%
Ontime submission of drafts: 20%
Ontime submission of written critiques: 20%
Class Participation: 20%
Final Project Grade: 10%
First Two Classes
- Graph building as an artform
- Graph building as story-telling
- Visualization criticism
- The workshop method
Make assignments and schedules
Guest speaker talks about real-world graphics design process
The State of Visualization Criticism: review several blogs
Criticism frameworks, e.g. Junk Charts Trifecta Checkup
Examples of Visualization Criticism
In-class discussion: (based on required reading, may shift to future classes depending on time)
- What is beauty?
- Novelty, and standards
- How should visualization be measured?
- What are insights?
- What works fall under the data visualization label?
- What can graphics designers learn from Norman's approach to product design?
Ground rules for workshop
Final Four Sessions
During the course, each student will hand in two drafts of a graphic, the second of which should take into account prior criticism. The class will be divided into two groups, and projects will be workshopped in alternate weeks. It is crucial that projects are submitted on time so that your classmates have time to prepare considered criticism.
Please leave comments below.
You can sign up for the course here.
Please spread the word!