CS 6730 Data Visualization: Principles & Applications
Pre-Reading: The Value of Information Visualization This course is an ntroductory course on design principles and applications of data visualization. This course teaches best practices for visualizing datasets from diverse domains intended to help people make sense of data. Data visualization is a rich research area that focuses on the design, development, and use of visual representations and interaction techniques to help people understand, explore, and analyze data. In this course, students will
- Learn fundamental principles of effective data visualization.
- Understand the wide variety of data visualization techniques and know what visualizations are appropriate for various types of data and for different goals.
- Understand how to design and implement data visualizations using commercial and open-source software tools.
- Know how data visualization uses dynamic interaction methods to help users explore, analyze, and make sense of data.
- Gain an understanding of human perceptual and cognitive capabilities to the design of effective data visualizations.
- Develop skills in critiquing different data visualization techniques in the context of user goals and objectives.
Students from a variety of disciplines are invited to take the class, as no prior experience with computer programming is expected. The course will involve using data visualization systems as opposed to coding visualizations from scratch. Students from business, science, engineering, and the arts are all welcome.
Time: Tuesday and Thursday 2:00pm -3:15PM
Location: J. Erskine Love Manufacturing | Room 185
Instructor: Cindy Xiong Bearfield
Office Hours: Thursdays 3:15-4:00 pm or by appointment
Email: cxiong[at]gatech[dot]edu
Office Location: TSRB 332 or via ZOOM (link provided upon request)
TAs: (Office hours starting from Week 2)
Yixuan Li
Email:yixuanli[at]gatech[dot]edu
Office Hours: Wednesday 10-11am
Office Location: TSRB 334
Ajay Bhat
Email:abhat319[at]gatech[dot]edu
Office Hours: Friday 11 am – 12 pm
Office Location: See CANVAS for ZOOM LINK
Atharva Ujwal Gulhane
Email: agulhane3[at]gatech[dot]edu
Office Hours: Monday 1-2pm (zoom or in-person)
Office Location: TSRB 334 or ZOOM LINK ON CANVAS
Textbooks
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.
| Monday | Tuesday | Wednesday | Thursday | Friday | |
|---|---|---|---|---|---|
| Week 1 | Jan 6 | Jan 7 Introduction | Jan 8 | Jan 9 InfoVis Overview (Pre-reading: Here) | Jan 10 |
| Week 2 | Jan 13 | Jan 14 Visual Encoding and Basic Charts | Jan 15 | Jan 16 Perception (Pre-Reading: Here) | Jan 17 |
| Week 3 | Jan 20 (Holiday) | Jan 21 User Tasks and Sensemaking (Pre-Reading: Here) | Jan 22 | Jan 23 Communication and Storytelling (Pre-Reading: Here) | Jan 24 Homework 1 Due (11:59PM) Find it on CANVAS |
| Week 4 | Jan 27 | Jan 28 Multivariate Data Presentations Coordinates, Line, Axes, Colors | Jan 29 | Jan 30 Unit Charts and Infographic (Pre-Reading: Here) | Jan 31 Design Project: Team formation Due (11:59PM) |
| Week 5 | Feb 3 | Feb 4 Design Principles & Web Tools | Feb 5 | Feb 6 User Interaction | Feb 7 Homework 2 Due (11:59PM) Find it on CANVAS |
| Week 6 | Feb 10 | Feb 11 Uncertainty |
Feb 12 |
Feb 13 Tableau Workshop | Feb 14 Design Project: Initial project description Due (11:59PM) |
| Week 7 | Feb 17 | Feb 18 ★ Test 1 ★ | Feb 19 | Feb 20 Cognitive Bias in Data Decision-Making | Feb 21 Homework 3 Due (11:59PM) Find it on CANVAS |
| Week 8 | Feb 24 | Feb 25 Graphs, Networks, Hierarchies, and Trees | Feb 26 | Feb 27 Visual Analytics, Text, Time Series, and Temporal Data (Pre-Reading: Here) | Feb 28 Homework 4 Due (11:59PM) Find it on CANVAS |
| Week 9 | Mar 3 | Mar 4 Data Humanism, Bias, and Ethics | Mar 5 | Mar 6 Natural Language Interfaces for Visualization | Mar 7 Design Project: Midterm Project Review |
| Week 10 | Mar 10 | Mar 11 Project Midterm Meetings | Mar 12 | Mar 13 (No Class) Catch-Up Day Work on your project! |
Mar 14 |
| Week 11 Spring Break | Mar 17 (Spring Break) | Mar 18 (Spring Break) | Mar 19 (Spring Break) | Mar 20 (Spring Break) | Mar 21 (Spring Break) |
| Week 12 | Mar 24 | Mar 25 Evaluation I | Mar 26 | Mar 27 Evaluation II | Mar 28 Design Project: Project materials |
| Week 13 | Mar 31 | Apr 1 (No Class) Catch-Up Day Work on your project! |
Apr 2 | Apr 3 Explainability | Apr 4 Homework 5 Due (11:59PM) Find it on CANVAS |
| Week 14 | Apr 7 | Apr 8 ★ Test 2 ★ | Apr 9 | Apr 10 Trust and Visualizations | Apr 11 Design Project: System Video |
| Week 15 | Apr 14 | Apr 15 Design Project: Project presentation/demonstration | Apr 16 | Apr 17 Last Class Design Project: Project presentation/demonstration | Apr 18 Design Project: Peer Review Due |
| Week 16 Last Week | Apr 21 | Apr 22 (No Class) | Apr 23 | Apr 24 (No Class) | Apr 25 |
Grading
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 | 40% |
| – HW1: Analytic Tasks & Queries | 5% |
| – HW2: Visualization Tools | 8% |
| – HW3: Tableau | 12% |
| – HW4: Infographic Design | 10% |
| – HW5: Network Vis | 5% |
| Design Project | 40% |
| – Team Formation | 1% |
| – Initial Project Description | 4% |
| – Midterm Project Review | 5% |
| – Project materials | 6% |
| – System Video | 7% |
| – Presentation & Overall Assessment | 12% |
| – Peer Review | 5% |
| Test 1 | 10% |
| Test 2 | 10% |
Attendance/Participation: It is expected that students will attend class, be prepared by doing the readings, and will pay attention and participate in discussions. We will have a number of interactive exercises during classes where students will turn in their work.
Homework Assignments: Each HW will be graded out of 10 points. Weights toward the final grade are listed above. For each calendar day late, that is 24 hours after the regular due date/time, 10% of the total grade (i.e., one point) will be deducted from an assignment’s score. A HW can be turned in up to a week late unless otherwise notified. All the HW assignment details can be found in Canvas.
Capstone Design Project: You can find the project information here.
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.