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
21	Class 1	Course Overview	A1: Environment Setup assigned A2: Semester Project Proposal assigned
23	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)
28	Class 3	Information Visualization Overview Semester Project Orientation •Read "Visualization Analysis and Design (VAD)" Chapter 1 ('What's Vis, and Why Do It?') •Read "A Tour Through the Visualization Zoo" by Heer et al.	A1 due
30	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
4	Class 5	Information Visualization: Data and Tasks •Read "VAD" Chapter 2 ('What: Data Abstraction') •Read "Information Visualization (IV)" by Colin Ware, portions of Chapter 1 on Types of Data/Metadata	A2 due Problem preferences due Wed. Sept. 5th @ 11am (see Team Formation Process)
6	Class 6	Team Formation and First Meetings	A3: Project Status and Proposal Revision assigned A4: Semester Project Deliverables and Presentation assigned
11	Class 7	Hands On D3: Part 1 •Read the tutorial "Let's Make a Bar Chart." •Read about D3 Data Joins. •Read the tutorial "Data Joins in D3.js."	A5: D3 Exercise assigned
13	Hurricane Florence Class 8	No class due to the hurricane. Material shifted to Class 10 Information Visualization: Visual Encoding •Read "Interactive Data Visualization (IDV)" by Ward et al. Chapter 4 Visualization Foundations •Read "IV" Chapter 6 Patterns
18	Class 9	Hands On D3: Part 2 •Read about D3 Handling Events. •Read about D3 Transitions.	A5 due A6: More D3 assigned
20	Class 10 (was Class 8)	Information Visualization: Visual Encoding •Read "Interactive Data Visualization (IDV)" by Ward et al. Chapter 4 Visualization Foundations •Read "IV" Chapter 6 Patterns
20	Omitted due to hurricane. Class 10	Team Design Workshop You should still complete the readings. •Read Sketching with Data Opens the Mind's Eye •Read "Graphical Perception..." paper by McGill and Cleveland
25	Class 11	Data Representation and Transformation: Basic Wrangling •Read "Research Directions in Data Wrangling" by Kandel et al.
27	Class 12	Hands On D3: Part 3 •Read about D3 Data Manipulation.	A6 due A7: Research Article Choices assigned
October
2	Class 13	Data Representation and Transformation: Statistics •Read Basic Statistics.	A7 due
4	Class 14	Hands On Simply Statistics •Re-Read Simple Statistics web page, focusing on API.	A8: Simple Statistics Exercise assigned
9	Class 15	Project Midterms: Present your proposal and progress-to-date to the class. Schedule Research Article Presentations	A3 due A9: Research Article Presentation assigned
11	Class 16	Data Representation and Transformation: Dimension Reduction, Classification, Clustering •Read Dimension Reduction on Wikipedia. •Read Statistical Classification on Wikipedia. •Read Cluster Analysis on Wikipedia.
16	Class 17	User in the Loop: Connecting Analytics and Visualization •Read "We Need Both Exploratory and Confirmatory" by John Tukey
18	Fall Break	No Class
23	Class 18	Class is cancelled. This class period should be used for team project meetings.	A8 due
25	Class 19	Guest Lecture: Evan Galloway, Sheps Center
30	Class 20	Analytical Reasoning: Models •Read "ItP" Chapter 2, pages 33-48
November
1	Class 21	Research Article Presentations (Day 1)	A9 due (for some)
6	Class 22	Class is cancelled. This class period should be used for team project meetings.
8	Class 23	Guest Lecture: Xan Gregg, SAS
13	Class 24	Analytical Reasoning: Challenges •Read "Confirmation Bias" on Wikipedia. •Read "Groupthink" on Wikipedia.
15	Class 25	Research Article Presentations (Day 2)	A9 due (for some)
20	Class 26	Collaboration and Dissemination •Read "Storytelling: The Next Step for Visualization" by Kosara and Mackinlay.
22	Thanksgiving	No Class
27	Class 27	Guest Lecture: Angela Zoss, Duke University Libraries
29	Class 28	Final Project Presentations	A4 part 1 (presentation and online demonstration) due (for some)
December
4	Class 29	Final Project Presentations	A4 part 1 (presentation and online demonstration) due (for some)
11	Final Exam Period	Project Deliverables Due by Noon	A4 part 2 (software prototype) due A4 part 3 (final report) due A4 part 4 (team evaluations) due