2024 Spring GATech CS 4460 Introduction to Information Visualization

CS 4460 Introduction to Information Visualization

Pre-Reading: The Value of Information Visualization

Data is everywhere. It helps us to make informed decisions. However, it is always overwhelming to interpret the “raw” data. Visualizations are tools that translate the raw data into **meaningful graphics**. They take advantage of the **powerful human visual system** to summarize data in a cognitively efficient way, making them popular in **science, analysis, and the media**.

Information visualization is an area of research that helps people analyze and understand data using visualization techniques. The multi-disciplinary area draws from other areas of science, including human-computer interaction, data science, psychology, and art, to develop new visualization methods and understand how (and why) they are effective.

Information visualization methods are applied to data from many different application domains, including:

– Political reporting and forecasting – as seen on TV and in the papers in election season. News reporting – look at the interactive visualizations used by the New York Times, Wall Street Journal, Slate, etc.
– Social science and economics data, such as census and other surveys, and micro and macro economic trends.
– Social networking and web traffic, to understand patterns of communication
– Business intelligence and business dashboards – to forecast sales trends, understand competitive marketplace positions, allocate resources, manage production and logistics.
– Text analysis – to determine trends and relationships for literary analysis and for information retrieval.
– Criminal investigations – to portray the relationships between event, people, places and things.
– Performance analysis of computer networks and systems.
– Software engineering – developing, debugging and maintaining software.
– Bioinformatics, to understand DNA, gene expressions, systems biology.

Time: Tuesday and Thursday  11:00am -12:15PM
Location: Howey Physics L2

Instructor: Cindy Xiong
Office Hours: Thursdays 12:15-1:00 pm or by appointment
Email: cxiong[at]gatech.edu
Office Location:
 TSRB 332 or via ZOOM (link provided upon request)

TAs: (Office hours starting from Week 3)

Claudia Chu (Lab 1 & 2)
Email: claudiachu[at]gatech.edu
Office Hours:
Wednesdays, 9:30-11:30am
Office Location: https://gatech.zoom.us/j/92938756921

Paige Thompson (Lab 5)
Office Hours:
Tuesdays, 5-7pm
Office Location: https://gatech.zoom.us/j/91757890927

Chloe Devre (Homework 4)
Office Hours:
Mondays, 12-2pm
Office Location: https://gatech.zoom.us/j/95469697146

Aparna Arul (Lab 3)
Email: aarul3[at]gatech.edu
Office Hours:
Tuesdays, 1-3pm
Office Location: https://gatech.zoom.us/j/9641100823?pwd=UmJ4Z1NHYVptOTFMSmdHakJhdmlQZz09

Greyson Mullins (Homework 1)
Office Hours:
Wednesdays, 3-5pm
Office Location: https://gatech.zoom.us/j/94562405038?pwd=cTJhT3k2akt4YS95WTVBVzhZUmNmQT09

Justin Blalock (Homework 3)
Office Hours:
Mondays, 2:30-4:30pm
Office Location: https://gatech.zoom.us/j/8264619820?pwd=Y3dVaUN3WnhWNGppL1BjRUR6TTc3dz09

Rishab Mitra (Lab 4)
Office Hours:
Thursdays, 1-3pm
Office Location: TSRB 334

Emily Layton (Homework 2)
Office Hours:
Mondays, 9-11am
Office Location: https://gatech.zoom.us/j/9581669743?pwd=MU9QdnU1NmN0Zk5uaFQzM2hqcEE4dz09



There are no required textbooks for this course. However, a free textbook that may help with learning the principles of web-based visualization development is:

  • Interactive Data Visualization for the Web, Scott Murray, O’Reilly Media, ISBN 9781449339739. While on the GT VPN, you can access this for free at this link. Or visit http://go.oreilly.com/GATech and then search the name of the book.

Course Objectives and Learning Outcome 

  • Learn the principles involved in designing effective information visualizations.
  • Understand the wide variety of information visualizations and know what visualizations are appropriate for various types of data and for different goals.
  • Understand how to design and implement information visualizations.
  • Know how information visualizations use dynamic interaction methods to help users understand data.
  • Learn to apply an understanding of human perceptual and cognitive capabilities to the design of information visualizations.
  • Develop skills in critiquing different visualization techniques in the context of user goals and objectives. Learn how to implement compelling information visualizations.


  Monday Tuesday Wednesday Thursday Friday
Week 1

Jan 8



Jan 9



Jan 10



 Jan 11

InfoVis Overview
(Pre-reading: Here)

Jan 12



Week 2  Jan 15 (Holiday) Jan 16

Visual Encoding and Basic Charts

Jan 17

Jan 18

(Pre-Reading: Here)

Jan 19


Week 3 Jan 22

Jan 23

User Tasks and Sensemaking
(Pre-Reading: Here)

Jan 24

Jan 25

Communication and Storytelling
(Pre-Reading: Here)

Jan 26


Week 4 Jan 29

Jan 30

Multivariate Data Presentations
Coordinates, Line, Axes, Colors

Jan 31

Feb 1 (No Class)

Catch-Up Day (take a breather)

Feb 2

Lab 1 Due (11:59PM)

Week 5 Feb 5

Feb 6 

Unit Charts and Infographic (Pre-Reading: Here)

Feb 7

Feb 8

Design Principles

Feb 9

Lab 2 Due (11:59PM)

Week 6  Feb 12

Feb 13 

User Interaction

Feb 14 Feb 15


Feb 16

Homework 1 Due (11:59PM)
Find it on CANVAS

Week 7

Feb 19

Feb 20


Feb 21

Feb 22

★ Test 1 ★

Feb 23


Week 8 Feb 26

Feb 27

Text Visualization
(Pre-Reading: Here)

Feb 28

Feb 29

Graphs, Networks, Hierarchies, and Trees

Mar 1

Lab 3 Due (11:59PM)

Week 9 Mar 4

Mar 5

Visual Analytics
(Pre-Reading: Here)

Mar 6

Mar 7

Time Series and Temporal Data

Mar 8

Homework 2 Due (11:59PM)
Find it on CANVAS

Week 10 Mar 11

Mar 12

Cognitive Bias in Data Decision-Making

Mar 13

Mar 14

Data Humanism, Bias, and Ethics

Mar 15

Lab 4 Due (11:59PM)

Week 11 Spring Break

Mar 18 (Spring Break)


Mar 19 (Spring Break)


Mar 20 (Spring Break)


Mar 21 (Spring Break)


Mar 22 (Spring Break)


Week 12  Mar 25

Mar 26

Evaluation I

Mar 27

Mar 28

Evaluation II

Mar 29

Homework 3 Due (11:59PM)
Find it on CANVAS

Week 13 Apr 1

Apr 2 (No Class)

Catch-Up Day (take a breather)

Apr 3

Apr 4 

Natural Language Interfaces for Visualization

Apr 5

Homework 4 Due (11:59PM)
Find it on CANVAS

Week 14 Apr 8

Apr 9

Guest Lecture: Geovisualizaton

Apr 10

Apr 11


Apr 12

Lab 5 Due (11:59PM)

Week 15 Apr 15

Apr 16

Final Thoughts

Apr 17

Apr 18 Last Class

★ Test 2 ★

Apr 19
Week 16 Last Week Apr 22 

Apr 23 (No Class)


Apr 24


Apr 25 (No Class)


Apr 26




All assignments are due at 11:59 pm on Fridays.

Late work will receive a 10% per day penalty. After 5 days, a 0% will be given and no submission will be accepted. Too much other work, gone for the weekend, ran out of paper etc. are not emergencies. Advance notification to the instructor and TAs is expected in all but the most severe emergency situations.

However, it is understandable that life events and other reasons come up that may require you to miss a deadline. As such, each student is given 2 “late days” that you can use throughout the semester. If you want to use any of your late days, add a note to the canvas submission at the time you submit. You cannot apply late days to assignments at the end of the semester or days after you submit your assignment. These are intended to be used in a situation where life events happen, not to retroactively apply them at the end of the semester.


There are two primary types of assignments for this course: Homework Assignments and Programming Assignments.

Homework Assignments (HW)

Details on HW assignments are on the Canvas site for this course. Due dates for each assignment can be found on Canvas and on the course Schedule. Grading distributions can be found on the course Syllabus. Submit all HW assignments on Canvas. Unless indicated by the HW instructions, all HWs are to be completed individually.

Programming Assignments (Labs)

These individual assignments will teach you the basic skills for developing web-based visualizations. You are expected to complete these assignments using d3.js.

It is good practice to develop your assignments using some sort of version control. GaTech gives you access to GitHub, which is a good one to use if you haven’t done so already.

D3.js is the Javascript InfoVis toolkit we will use for the programming assignments. Go through the following short tutorial on the fundamentals and set up of D3.

When grading, we will use Google Chrome in Incognito Mode to run your visualizations. Further, when a server is required, we will use a Python server on localhost.

When submitting on Canvas, make sure you submit a .zip containing all your files, and name it Lastname_Firstname.zip (e.g., Yang_Yalong.zip), unless otherwise mentioned in the assignment.

Warning: There are many existing examples and source code widely available online. While these are great resources for you to learn, note that copying these is considered a breach of the rules from the Office of Student Integrity and will be handled accordingly. Be careful and thoughtful. Many of the assignments will ask you to start from existing source code or examples. In these cases, it is expected that parts of your assignments will resemble the original. You are expected to start with these templates and build your submission to meet the needs of the assignments from there.

The labs start relatively simple and increase in complexity throughout the semester.

The due dates for the labs are listed on the Schedule and on Canvas. The labs can be accessed on the GitHub repo here: https://github.gatech.edu/CS4460/Spring24-Labs-PUBLIC/ 

Notice that in order to access this repo, you must use your Georgia Tech Github account.

Carefully read through the Wiki for each Lab for instructions, submission requirements, etc. Remember, when you clone the labs, please make sure that you do not publicly share your code to avoid inadvertent plagiarism.




Final course grades may be curved (but not always). Grades of individual assignments will not be curved. If a curve is given, it will only be curved up (not down).

Grading distributions for this course are:

Component Weight
HW Assignments 30%
– HW1: Find and Critique a Vis 5%
– HW2: Data Exploration and Analysis 7%
– HW3: Ethical Visualization Design 8%
– HW4: Tableau 10%
Labs 40%
– Lab1 5%
– Lab2 5%
– Lab3 10%
– Lab4 10%
– Lab5 10%
Test 1 15%
Test 2 15%

Attendance/Participation: In some classes, the instructor will randomly call on students to answer questions, and -1% will be applied if the student is not in class (for each class).



Expectations and Academic Integrity

Mutual expectations. At Georgia Tech, we believe that it is important to continually strive for an atmosphere of mutual respect, acknowledgment, and responsibility between faculty members and the student body. See http://www.catalog.gatech.edu/rules/22/ for an articulation of some basic expectations – that you can have of me and that I have of you. In the end, simple respect for knowledge, hard work, and cordial interactions will help build the environment we seek. I encourage you to remain committed to the ideals of Georgia Tech while in this class and always.

Attendance is expected. Institute approved absences will be accommodated, as will absences for interviews, conferences, etc. Notify us by email or direct Canvas messages if you will miss class for one of these two reasons (if you feel some other reason for absence is reasonable, email us, but again, in advance).

Contacting your instructor and TA. For communication with TAs and Instructors, please use Canvas messages. Email will work ok, but it will likely take longer to get a response due to flooded inboxes. If you use email, please include [CS4460] in the subject line.

Collaboration and academic honesty. Georgia Tech aims to cultivate a community based on trust, academic integrity, and honor. Students are expected to act according to the highest ethical standards. For information on Georgia Tech’s Academic Honor Code, please visit http://www.catalog.gatech.edu/policies/honor-code/ or http://www.catalog.gatech.edu/rules/18/.

Any student suspected of cheating or plagiarizing on a test, assignment, or project will be reported to the Office of Student Integrity, who will investigate the incident and, if needed, identify the appropriate penalty for violations.

Unless explicitly stated otherwise, you are expected to do coursework on your own.

In-class use of computers, cell phones, and tablets. Please use your technology appropriately while in class. Using computers. tablets, smartphones, watches, VR headsets, etc. in a way that reinforces the educational context, such as taking notes or visiting a website being discussed, is appropriate. Reading email, playing games, browsing social media, watching Netflix, doing your HW assignments, purchasing football tickets, web browsing, etc. are not appropriate. Not only does this detract from your learning, it unavoidably distracts those sitting near you. Also, incoming emails and alerts are distracting. Even note-taking on your computer may not be such a great idea: studies have shown that note-taking by hand has been shown to be more efficient for learning (also see this news story), as opposed to by computer, but that’s your call. In short, it’s really in your best interest to take the 75 minutes out of your day, disconnect from the internet, and engage in the course.

Also, understand that this course is about data visualization. We will spend significant class time showing slides of visualizations and discussing them. The content of the discussion is not captured in the slides, yet you are expected to take notes, learn, and be tested on it.

Accommodations for students with disabilities. If you are a student with learning needs that require special accommodation, contact the Office of Disability Services (often referred to as ADAPTS) at http://disabilityservices.gatech.edu/, as soon as possible, to make an appointment to discuss your special needs and to obtain an accommodations letter. Please also e-mail your instructor as soon as possible in order to set up a time to discuss your learning needs.

Student Support Services. In your time at Georgia Tech, you may find yourself in need of support. Here you will find some resources to support you both as a student and as a person.

Software. One of the assignments is to analyze data using Tableau. Tableau’s data visualization software is provided through the Tableau for Teaching program.