Class Times: Mon, Wed 2-3:15 in Paper Tricentennial Building
Instructor: Clio Andris
Contact: [clio] at gatech.edu
Introduction
Information visualization goes beyond presenting information as static charts, graphs and maps by leveraging the power of computer interaction to help people analyze, understand and make decisions from data. Dozens of companies – including Google, Microsoft, IBM, Oracle and SAP – offer Information Visualization tools. Thousands of companies and governments use the tools for daily operations and for longer-term strategic planning.
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.
Course Objectives
- Learn the principles of 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.
Software
We will use D3 in this class and related software needs to be installed on your computer. One of the assignments is to analyze data using Tableau. Tableau’s data visualization software is provided through the Tableau for Teaching program.
DOWNLOAD SYLLABUS FOR FALL 2022
Schedule
| Date | Topic | Recitation | Reading 1 | Reading 2 | Due |
| Tu 8-18 | Introduction and Intro to InfoVis | CMS – Info Vis | Toptal – Best Practices | ||
| Th 8-20 | Multivariate Data & Tables, Graphs & Charts | None. Sign up for your pod. | Info Vis Zoo | Data-to-Viz | |
| Tu 8-25 | Data Sources, Integrity, Cleaning, Structuring | Canvas: Data Classification | Chartio – Hygiene | HW 1 (analog) | |
| Th 8-27 | Visualization Design Principles | Meet with your POD 1.1 | Canvas: Tufte Folder | Numbers | |
| Tu 9-1 | Multivariate Visual Reps 1 | Lineup | Lineup – Web | HW 2 (no vis) | |
| Th 9-3 | Multivariate Visual Reps 2, HTML and CSS, SVG | HTML, CSS, SVG help | Murray (Ch 1) | POD 1.1 Discussion | |
| Tu 9-8 | User Interaction 1 (Dr. John Stasko) | Yi-Interaction | Jigsaw | ||
| Th 9-10 | User Interaction 2, JavaScript and Intro to D3 | Meet with your POD 1.2 | Murray (Ch 3) | ||
| Tu 9-15 | InfoVis Systems & Toolkits, Operations | Canvas: Munzer Ch 3 | Brehmer | HW 3 (multivariate) | |
| Th 9-17 | Visual Perception | None | Canvas: Visual Perception Folder | Medium | POD 1.2 Discussion |
| Tu 9-22 | Graphs & Networks | HW 4 (tableau) | |||
| Th 9-24 | Graphs & Networks, Hierarchies & Trees | Meet with your POD 1.3 | Canvas: Networks | Johnson-Treemaps | |
| Tu 9-29 | Geovisualization 1 | TBD | HW 5 (graphs) | ||
| Th 10-1 | Geovisualization 2, Setting up D3: Intro, Chart Types, Axes | Setting up D3 help | Murray (Ch 2) | POD 1.3 Discussion | |
| Tu 10-6 | POD Review 1! | None | |||
| Th 10-8 | MIDTERM | ||||
| Tu 10-13 | Meet with your POD 2.1 | ||||
| Th 10-15 | Evaluation, WW2 Vis | P1 help | Beliv | ||
| Tu 10-20 | Times Series Data | TexTonic – Video | P1 (simple charts) | ||
| Th 10-22 | Text & Documents | P2 help | Harmful Word Clouds | POD 2.1 Discussion | |
| Tu 10-27 | Color | Canvas: Munzer Ch 10 | Choosing Colors | ||
| Th 10-29 | Election Vis, D3 Project Boost: Enter, Update, & Exit | Meet with your POD 2.2 | Murray (Ch 9) | P2 (static) | |
| Tu 11-3 | Vis in Marketing, Persuasion, Affect (Cary Anderson) | Canvas: CaryAndersonPaper (link to a paper) | VisValue | ||
| Th 11-5 | Storytelling | P4 help | Canvas: Storytelling | POD 2.2 Discussion | |
| Tu 11-10 | Visual Analytics | None | P3 (filtering + animation) | ||
| Th 11-12 | D3 Project Boost: Layouts | Meet with your POD 2.3 | Murray (Ch 10) | ||
| Tu 11-17 | Cutting Edge VIS and VIS Research | P4 (linking + brushing) | |||
| Th 11-19 | QUIZ | Project help | POD 2.3 Discussion | ||
| Tu 11-24 | Thanksgiving break | ||||
| Th 11-26 | Thanksgiving break | ||||
| Tu 12- 1 | Course Wrap Up, POD 2 Review! | P5 (Project) Final Due Dec 6 – Midnight | |||
| Th 12- 3 | NO FINAL EXAM | Project help |