Introduction to Information Visualization (CS 4460)

Class Times: Tuesday, Thursday 2-3:15 on WebEx
Recitation: Thursday 5-6:15 on BlueJeans

Instructor: Clio Andris
Contact: [clio] at gatech and https://clioandris.youcanbook.me/

TAs: Subhajit Das [das], Arpit Mathur [arpit.mathur], Hayeong Song [hayeong.song], Yu Fu [fuyu]

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

  1. Learn the principles of designing effective information visualizations.
  2. Understand the wide variety of information visualizations and know what visualizations are appropriate for various types of data and for different goals.
  3. Understand how to design and implement information visualizations.
  4. Know how information visualizations use dynamic interaction methods to help users understand data.
  5. Learn to apply an understanding of human perceptual and cognitive capabilities to the design of information visualizations.
  6. Develop skills in critiquing different visualization techniques in the context of user goals and objectives.
  7. 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.

Schedule

DateTopicRecitationReading 1Reading 2Due
Tu 8-18Introduction and Intro to InfoVisCMS – Info VisToptal – Best Practices 
Th 8-20Multivariate Data & Tables, Graphs & ChartsNone. Sign up for your pod.Info Vis ZooData-to-Viz 
Tu 8-25Data Sources, Integrity, Cleaning, Structuring Canvas: Data ClassificationChartio – HygieneHW 1 (analog) 
Th 8-27Visualization Design PrinciplesMeet with your POD 1.1Canvas: Tufte FolderNumbers 
Tu 9-1Multivariate Visual Reps 1 LineupLineup – WebHW 2 (no vis)
Th 9-3Multivariate Visual Reps 2, HTML and CSS, SVGHTML, CSS, SVG help Murray (Ch 1) POD 1.1 Discussion 
Tu 9-8User Interaction 1 (Dr. John Stasko)Yi-InteractionJigsaw 
Th 9-10User Interaction 2, JavaScript and Intro to D3Meet with your POD 1.2Murray (Ch 3)  
Tu 9-15InfoVis Systems & Toolkits, OperationsCanvas: Munzer Ch 3BrehmerHW 3 (multivariate)
Th 9-17Visual PerceptionNoneCanvas: Visual Perception FolderMediumPOD 1.2 Discussion 
Tu 9-22Graphs & Networks   HW 4 (tableau)
Th 9-24Graphs & Networks, Hierarchies & TreesMeet with your POD 1.3Canvas: NetworksJohnson-Treemaps 
Tu 9-29Geovisualization 1TBD HW 5 (graphs)
Th 10-1Geovisualization 2,  Setting up D3: Intro, Chart Types, AxesSetting up D3 helpMurray (Ch 2)POD 1.3 Discussion 
Tu 10-6POD Review 1! None   
Th 10-8MIDTERM    
Tu 10-13Meet with your POD 2.1    
Th 10-15Evaluation, WW2 VisP1 helpBeliv  
Tu 10-20Times Series DataTexTonic – Video P1 (simple charts) 
Th 10-22Text & Documents P2 helpHarmful Word Clouds POD 2.1 Discussion 
Tu 10-27ColorCanvas: Munzer Ch 10Choosing Colors
Th 10-29Election Vis, D3 Project Boost: Enter, Update, & ExitMeet with your POD 2.2Murray (Ch 9) P2 (static)  
Tu 11-3Vis in Marketing, Persuasion, Affect (Cary Anderson)Canvas: CaryAndersonPaper (link to a paper)VisValue
Th 11-5StorytellingP4 helpCanvas: Storytelling  POD 2.2 Discussion
Tu 11-10Visual AnalyticsNone P3 (filtering + animation) 
Th 11-12D3 Project Boost: LayoutsMeet with your POD 2.3Murray (Ch 10)  
Tu 11-17Cutting Edge VIS and VIS Research    P4 (linking + brushing) 
Th 11-19QUIZProject help  POD 2.3 Discussion 
Tu 11-24Thanksgiving break    
Th 11-26Thanksgiving break    
Tu 12- 1Course Wrap Up, POD 2 Review!   P5 (Project) Final Due Dec 6 – Midnight
Th 12- 3NO FINAL EXAMProject help