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

January
11Class 1Course Overview and Introduction
•Read "Visual Analytics: Definition, Process, and Challenges" by Keim et al.
•Read "Illuminating the Path (ItP)" Executive Summary (Pages 1-18)
A1: Environment Setup assigned
A2: Semester Project Proposal assigned
13Class 2Data Ethics and Responsibility
•Read "Fired for Not Manipulating COVID-19 Data" interview by NPR's Rachel Martin
•Read "How Deceptive are Deceptive Visualizations?" by Pandey et al.
•Read "Racial Bias Found in a Major Health Care Risk Algorithm" by Starre Vartan
18Class 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
20Class 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.
25Class 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. Jan. 26th @ 11am (see Team Formation Process)
27Class 6Team Formation and First MeetingsA3: Project Status and Proposal Revision assigned
A4: Semester Project Deliverables and Presentation assigned
February
1Class 7Hands On D3: Part 1
•Read the tutorial Let's Make a Bar Chart.
•Read the tutorial Let's Mark a Bar Chart with SVG.
•Read the tutorial D3 Joins: The Basics.
•Read the tutorial More D3 Joins: Enter, Update, Exit.
A5: D3 Exercise assigned
3Class 8Information Visualization: Visual Encoding
8Class 9Hands On D3: Part 2
•Read about D3 Handling Events.
•Read about D3 Transitions.
A5 due
A6: More D3 assigned
10Class 10Team Design Workshop
15Class 11Data Representation and Transformation: Basic Wrangling
•Read "Research Directions in Data Wrangling" by Kandel et al.
17Class 12Hands On D3: Part 3
•Read about D3 Group and Rollup.
A7: Research Article Choices assigned
22Class 13Data Representation and Transformation: Statistics
•Read Elementary Concepts in Statistics (or as a PDF).
•Read Basic Statistics (or as a PDF).
Note that these texts are based on a publicly available online textbook now owned by TIBCO. Click here for the latest version.
A6 due
24Class 14Hands On Simply Statistics
•Re-Read Simple Statistics web page, focusing on API.
A7 due
A8: Simple Statistics Exercise assigned
March
1Class 15Project Midterms: Present your revised proposal and progress-to-date to the class.
Schedule Research Article Presentations
A3 due
A9: Research Article Presentation assigned
3Class 16Data Representation and Transformation: Dimension Reduction, Classification, Clustering
•Read Dimension Reduction on Wikipedia.
•Read Statistical Classification on Wikipedia.
•Read Cluster Analysis on Wikipedia.
8Class 17User in the Loop: Connecting Analytics and Visualization
10Class 18Guest Lecture: Alison Blaine from Red HatA8 due
15Spring BreakNo Class
17Spring BreakNo Class
22Class 19Analytical Reasoning: Models
•Read "ItP" Chapter 2, pages 33-48
24Class 20Research Article Presentations (Day 1)A9 due (for some)
29Class 21Guest Lecture: Lorin Bruckner from UNC Libraries Digital Research Services
31Class 22Analytical Reasoning: Challenges
•Read "Confirmation Bias" on Wikipedia.
•Read "Groupthink" on Wikipedia.
April
5Class 23Research Article Presentations (Day 2)A9 due (for some)
7Class 24Collaboration and Dissemination
•Read "Storytelling: The Next Step for Visualization" by Kosara and Mackinlay.
12Class 25Research Article Presentations (Day 3)A9 due (for some)
14Wellness DayNo Class
19Class 25Guest Lecture: Sid Thakur from Blaize
21Class 27Final Project PresentationsA4 part 1 (presentation and online demonstration) due (for some)
26Class 28Final Project PresentationsA4 part 1 (presentation and online demonstration) due (for some)
May
3Final Exam PeriodProject Deliverables Due by 8am (Start of Exam Time) A4 part 2 (software prototype) due
A4 part 3 (final report) due
A4 part 4 (team evaluations) due