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
22Class 1Course OverviewA1: Environment Setup assigned
A2: Semester Project Proposal assigned
24Class 2Introduction to Visual Analytics
•Read "Visual Analytics: Definition, Process, and Challenges" by Keim et al.
•Read "Illuminating the Path (ItP)" Executive Summary (Pages 1-18)
29Class 3Information 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
31Class 4Select 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
5Class 5Information 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)
7Class 6Team Formation and First MeetingsA3: Project Status and Proposal Revision assigned
A4: Semester Project Deliverables and Presentation assigned
12Class 7Hands 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
14Class 8Information Visualization: Visual Encoding
19Class 9Hands On D3: Part 2
•Read about D3 Handling Events.
•Read about D3 Transitions.
A5 due
A6: More D3 assigned
21Class 10Team Design Workshop
26Class 11Data Representation and Transformation: Basic Wrangling
•Read "Research Directions in Data Wrangling" by Kandel et al.
28Class 12Hands On D3: Part 3
•Read about D3 Data Manipulation.
A6 due
A7: Research Article Choices assigned
October
3Class 13Class is cancelled. This class period should be used for team project meetings.
5Class 14Data Representation and Transformation: Statistics
A7 due
10Class 15Hands On Simply Statistics
•Re-Read Simple Statistics web page, focusing on API.
A8: Simple Statistics Exercise assigned
12Class 16Project Midterms: Present your proposal and progress-to-date to the class.
Schedule Research Article Presentations
A3 due
A9: Research Article Presentation assigned
17Class 17Data Representation and Transformation: Dimension Reduction, Classification, Clustering
•Read Dimension Reduction on Wikipedia.
•Read Statistical Classification on Wikipedia.
•Read Cluster Analysis on Wikipedia.
19Fall BreakNo Class
24Class 18User in the Loop: Connecting Analytics and VisualizationA8 due
26Class 19Industry Guest Lecture: Evan Galloway, Sheps Center
31Class 20Analytical Reasoning: Models
•Read "ItP" Chapter 2, pages 33-48
November
2Class 21Research Article Presentations (Day 1)A9 due (for some)
7Class 22Class is cancelled. This class period should be used for team project meetings.
9Class 23Industry Guest Lecture: Sidharth Thakur, Intel
14Class 24Analytical Reasoning: Challenges
•Read "Confirmation Bias" on Wikipedia.
•Read "Groupthink" on Wikipedia.
16Class 25Research Article Presentations (Day 2)A9 due (for some)
21Class 26Collaboration and Dissemination
•Read "Storytelling: The Next Step for Visualization" by Kosara and Mackinlay.
23ThanksgivingNo Class
28Class 27Industry Guest Lecture: Xan Gregg, SAS
30Class 28Final Project PresentationsA4 part 1 (presentation and online demonstration) due (for some)
December
5Class 29Final Project PresentationsA4 part 1 (presentation and online demonstration) due (for some)
8Final Exam PeriodProject Deliverables Due by Noon A4 part 2 (software prototype) due
A4 part 3 (final report) due
A4 part 4 (team evaluations) due