stat/engl 332

Visualizing Quantitative Information

Fall 2014

Tuesday/Thursday 9:30–10:50. Kildee 0107

Heike Hofmann, hofmann@iastate.edu.
Office hours by arrangement. Snedecor 2413

Syllabus

Course syllabus describing objectives, software used, topics and assessment.

Portfolio

Portfolio page

Lectures and tentative timetable

Date Lecture and Resources Dates and Deadlines
Aug 26 Introduction to the course: what is the visual display of quantitative information? Why and for whom do we display information visually?
Great Examples
Aug 28 Historical and famous examples (1) Reading: Noah Iliinsky, "On Beauty" (1-13)
Sep 2 More historical and famous examples (2) Reading: Matthias Shapiro, "Once upon a Stacked Time Series" (15-36)
Sep 4 Contemporary examples. What makes an effective data display? Thinking about audience and purpose in designing displays. Reading: Jonathan Feinberg, "Wordle" (37-58)
Audience & Purpose
Sep 9 Developing criteria for evaluating data displays. Exam (20 min at start of class) historical and famous examples.
Sep 11 Evaluating displays; group analysis of selected examples Reading: Jessica Hagy, "Visualization: Indexed".
Graphical Conventions
Sep 16 Data display conventions: what do your readers expect? How can you meet those expectations with graphical conventions? Evaluation 1 due (individual, of static graphic)
Reading: Andrew Odewahn, "Visualizing the U.S. Senate Social Graph (1991-2009)" (123-141).
Sep 18 Types of quantitative information: basic data plots. Reading: Robert Kosara, "Turning a Table into a Tree: Growing Parallel Sets into a Purposeful Project" (193-204).
Sep 23 Graphical elements: points, lines, color. Reading: Moritz Stefaner, "The Design of "X" by "Y" (205-225).
Human Cognition
Sep 25 Graphical perception and misperception: testing human cognition. Design 1 due (individual)
Sep 30 Designing experiments to get feedback from users of data displays: from controlled experiments to usability studies.
Interactive Graphics
Oct 2 Interactive graphics: empowering users to manipulate displays. Reading: Todd Holloway, "The Big Picture: Search and Discovery" (143-156).
Oct 7 Interactive graphics continued. Reading: Martin Wattenberg and Fernanda Viegas, "Beautiful History: Visualizing Wikipedia" (175-191).
Ethics
Oct 9 Ethical issues in displaying data: building trust with your readers; practices that can erode that trust. Evaluation 2 due (small group, of interactive graphic)
Tables, Maps & Text
Oct 14 Tables and matrices as display techniques. Reading: Danyel Fisher, "Animation for Visualization: Opportunities and Drawbacks" (329-352).
Oct 16 Temporal visualization; animations Reading: Eddie Jabbour, "Mapping Information: Redesigning the New York City Subway Map" (69-89).
Design 2 due (small group)
Oct 21 Design workshop.
Oct 23 Lab discussion
Oct 28 Text visualizations: from tag clouds to concordances.
Oct 30 Talk aloud Data exploration/visualization Reading: Valdis Krebs, "Your Choices Reveal Who You Are: Mining and Visualizing Social Patterns" (103-122).
Evaluation 3 due (small group, of animation/map)
Networks
Nov 4 Illustrator training, maybe we can use this chart, same chart in AI format
Nov 6 Visualizing networks: social graphs.
Miscellaneous Topics
Nov 11 Graphical inference for comparing designs
Nov 13 Analysis of readings: overview. Design 3 due (small group)
Nov 18 Discussion of software resources One page writeups of ideas for final project are due
Nov 20 Workshop for design 4: discussion of audience and purpose analysis.
Thanksgiving
Nov 25/27 Thanksgiving Week
Dec 2 Workshop: design #4 finishing touches.
Dec 4 Workshop: final prep of the portfolio. Design 4 and portfolio due
Dec 9 Presentations of portfolio.
Dec 11 Presentations of portfolio.
Dec 18 Feedback, back in our regular classroom
The schedule of topics might change, and additional topics might be added.

Software

Excel or JMP will be used to make calculations on data. Photoshop, Canvas, InDesign, Illustrator some similar graphics program will be used to finish graphics.