SCHEDULE OVERVIEW

The schedule for this class will weave together four key themes. First, we'll discuss a number of core visual analytics concepts and models. Second, espeically early on in the semester, we'll spend time reviewing the D3.js library, a widely used framework for interactive visualization on the web. Third, we'll review recent examples of research in visual analytics from the scientific literature. And finally, we'll have some special guest speakers address the class both in person and via web conference.

Below you'll find a TENTATIVE schedule for the semester. Please note that all topics/dates/etc. are subject to change at any time. I fully expect to adjust our plans multiple times over the course of the semester.

DETAILED SCHEDULE

August
19	Class 1	Course Overview	A1: Environment Setup assigned A2: Semester Project Proposal assigned
21	Class 2	Introduction to Visual Analytics •Read "Visual Analytics: Definition, Process, and Challenges" by Keim et al. •Read "Illuminating the Path (ItP)" Executive Summary (Pages 1-18)
26	Class 3	Information Visualization Overview Semester Project Orientation •Read "Visualization Analysis and Design (VAD)" Chapter 1 •Read "A Tour Through the Visualization Zoo" by Heer et al.	A1 due
28	Class 4	Select Topics: JavaScript and SVG Introduction to D3 and Simple Statistics •Read web pages for D3 and Simple Statistics. •Bring laptop for in-class exercises.
September
2	Class 5	Proposal Elevator Pitches Team Formation and First Meetings	A2 due A3: Project Status and Proposal Revision assigned A4: Semester Project Deliverables and Presentation assigned
4	Class 6	Information Visualization: Data and Tasks •Read "VAD" Chapter 2 •Read "Chap. 1 Foundations..." by Ware
9	Class 7	Hands On D3: Part 1 •Read the D3 Tutorial "Let's Make a Bar Chart." •Read about D3 Data Joins.	A5: D3 Exercise assigned
11	Class 8	Information Visualization: Visual Enconding •Read "Chap. 4 Visualization Foundations" by Ward et al. •Read "Chap. 6 Patterns" by Ware
16	Class 9	Hands On D3: Part 2 •Read about D3 Animation and Interaction. •Read about D3 Transitions.	A5 due A6: More D3 assigned
18	Class 10	Data Representation and Transformation: Basic Wrangling •Read "Research Directions in Data Wrangling" by Kandel et al.	A7: Research Article Choices assigned
23	Class 11	Hands On D3: Part 3 •Read about D3 Data Manipulation.	A6 due
25	Class 12	Data Representation and Transformation: Statistics •Read Basic Statistics.	A7 Due
30	Class 13	Hands On Simply Statistics •Re-Read Simple Statistics web page, focusing on API.	A8: Simple Statistics Exercise assigned
October
2	Class 14	Project Midterms: Present your proposal and progress-to-date to the class. Schedule Research Article Presentations	A3 due A9: Research Article Presentation assigned
7	Class 15	Data Representation and Transformation: Dimension Reduction, Classification, Clustering •Read Dimension Reduction on Wikipedia. •Read Statistical Classification on Wikipedia. •Read Cluster Analysis on Wikipedia.
9	Class 16	User in the Loop: Connecting Analytics and Visualization •Read "We Need Both Exploratory and Confirmatory" by John Tukey
14	Class 17	Class is cancelled, but A8 is still due today.	A8 due
16	Fall Break	No Class
21	Class 18	Guest Lecture: Nan Cao, IBM
23	Class 19	Analytical Reasoning: Models •Read "ItP" Chapter 2, pages 33-48
28	Class 20	Analytical Reasoning: Challenges •Read "Confirmation Bias" on Wikipedia. •Read "Groupthink" on Wikipedia.
30	Class 21	Research Article Presentations (Day 1)	A9 due (for some)
November
4	Class 22	Guest Lecture: Krist Wongsuphasawat, Twitter
6	Class 23	Research Article Presentations (Day 2)	A9 due (for some)
11	Class 24	Guest Lecture: Annie Chen, SILS
13	Class 25	Guest Lecture: Ketan Mane, RENCI
18	Class 26	Research Article Presentations (Day 3)	A9 due (for some)
20	Class 27	Research Article Presentations (Day 4)	A9 due (for some)
25	Class 28	Collaboration and Dissemination •Read "Storytelling: The Next Step for Visualization" by Kosara and Mackinlay.
27	Thanksgiving	No Class
December
2	Class 29	Final Project Presentations	A4 part 1 (presentation and online demonstration) due
9	Final Exam Period	Project Deliverables Due by Noon on Dec. 9	A4 part 2 (software prototype) due A4 part 3 (final report) due A4 part 4 (team evaluations) due