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 | |||
| 22 | Class 1 | Course Overview | A1: Environment Setup assigned A2: Semester Project Proposal assigned |
| 24 | 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) | |
| 29 | 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 |
| 31 | Class 4 |  Select Topics: JavaScript and SVGIntroduction to D3 and Simple Statistics | |
| September | |||
| 5 | 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. 6th @ 11am (see Team Formation Process) |
| 7 | Class 6 | Team Formation and First Meetings | A3: Project Status and Proposal Revision assigned A4: Semester Project Deliverables and Presentation assigned |
| 12 | 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 |
| 14 | Class 8 | Information Visualization: Visual Encoding •Read "Interactive Data Visualization (IDV)" by Ward et al. Chapter 4 Visualization Foundations •Read "IV" Chapter 6 Patterns | |
| 19 | Class 9 | Hands On D3: Part 2 | A5 due A6: More D3 assigned |
| 21 | Class 10 | Team Design Workshop •Read Sketching with Data Opens the Mind's Eye •Read ""Graphical Perception..." paper" by McGill and Cleveland | |
| 26 | Class 11 | Data Representation and Transformation: Basic Wrangling •Read "Research Directions in Data Wrangling" by Kandel et al. | |
| 28 | Class 12 | Hands On D3: Part 3 •Read about D3 Data Manipulation. | A6 due A7: Research Article Choices assigned |
| October | |||
| 3 | Class 13 | Class is cancelled. This class period should be used for team project meetings. | |
| 5 | Class 14 | Data Representation and Transformation: Statistics •Read Basic Statistics. | A7 due |
| 10 | Class 15 | Hands On Simply Statistics •Re-Read Simple Statistics web page, focusing on API. | A8: Simple Statistics Exercise assigned |
| 12 | Class 16 | Project Midterms: Present your proposal and progress-to-date to the class. Schedule Research Article Presentations | A3 due A9: Research Article Presentation assigned |
| 17 | Class 17 | Data Representation and Transformation: Dimension Reduction, Classification, Clustering •Read Dimension Reduction on Wikipedia. •Read Statistical Classification on Wikipedia. •Read Cluster Analysis on Wikipedia. | |
| 19 | Fall Break | No Class | |
| 24 | Class 18 | User in the Loop: Connecting Analytics and Visualization •Read "We Need Both Exploratory and Confirmatory" by John Tukey | A8 due |
| 26 | Class 19 | Industry Guest Lecture: Evan Galloway, Sheps Center | |
| 31 | Class 20 | Analytical Reasoning: Models •Read "ItP" Chapter 2, pages 33-48 | |
| November | |||
| 2 | Class 21 | Research Article Presentations (Day 1) | A9 due (for some) |
| 7 | Class 22 | Class is cancelled. This class period should be used for team project meetings. | |
| 9 | Class 23 | Industry Guest Lecture: Sidharth Thakur, Intel | |
| 14 | Class 24 | Analytical Reasoning: Challenges | |
| 16 | Class 25 | Research Article Presentations (Day 2) | A9 due (for some) |
| 21 | Class 26 | Collaboration and Dissemination •Read "Storytelling: The Next Step for Visualization" by Kosara and Mackinlay. | |
| 23 | Thanksgiving | No Class | |
| 28 | Class 27 | Industry Guest Lecture: Xan Gregg, SAS | |
| 30 | Class 28 | Final Project Presentations | A4 part 1 (presentation and online demonstration) due (for some) |
| December | |||
| 5 | Class 29 | Final Project Presentations | A4 part 1 (presentation and online demonstration) due (for some) |
| 8 | 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 |