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
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. Aug. 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
September
1Class 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
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 Data Manipulation.
A7: Research Article Choices assigned
22Class 13Data Representation and Transformation: Statistics
A6 due
24Class 14Hands On Simply Statistics
•Re-Read Simple Statistics web page, focusing on API.
A7 due
A8: Simple Statistics Exercise assigned
29Class 15Project Midterms: Present your revised proposal and progress-to-date to the class.
Schedule Research Article Presentations
A3 due
A9: Research Article Presentation assigned
October
1Class 16Data Representation and Transformation: Dimension Reduction, Classification, Clustering
•Read Dimension Reduction on Wikipedia.
•Read Statistical Classification on Wikipedia.
•Read Cluster Analysis on Wikipedia.
6Class 17User in the Loop: Connecting Analytics and Visualization
8Class 18Guest Lecture: Lorin Bruckner, UNC Libraries
13Class 19Analytical Reasoning: Models
•Read "ItP" Chapter 2, pages 33-48
A8 due
15Class 20Research Article Presentations (Day 1)A9 due (for some)
20Class 21Guest Lecture: Evan Galloway, Sheps Center
22Class 22Analytical Reasoning: Challenges
•Read "Confirmation Bias" on Wikipedia.
•Read "Groupthink" on Wikipedia.
27Class 23Class is cancelled. This class period should be used for team project meetings.
29Class 24Class is cancelled. This class period should be used for team project meetings.
November
3Class 25Research Article Presentations (Day 2)A9 due (for some)
5Class 26Collaboration and Dissemination
•Read "Storytelling: The Next Step for Visualization" by Kosara and Mackinlay.
10Class 27Guest Lecture: Alex Harding, RTI International
12Class 28Final Project PresentationsA4 part 1 (presentation and online demonstration) due (for some)
17Class 29Final Project PresentationsA4 part 1 (presentation and online demonstration) due (for some)
20Final Exam PeriodProject Deliverables Due by 4pm (Start of Exam Time) A4 part 2 (software prototype) due
A4 part 3 (final report) due
A4 part 4 (team evaluations) due