Schedule
Subject to change.
Week 1
Lecture 1: Introduction
Wednesday, January 18What is visualization? Why is it important? Who are we? Course overview.
Introduction to Homework 0.
Recommended reading
- A Tour through the Visualization Zoo. Jeffrey Heer, Michael Bostock, Vadim Ogievetsky. Communications of the ACM, 53(6), pp. 59-67, Jun 2010.
- The Value of Visualization.Jarke van Wijk. Proceedings of the IEEE Visualization Conference, pp. 79-86, 2005.
Homework 0, Introduction due.
Friday, January 20, 11:59pm
Technical Foundations
Week 2
Lecture 2: Version Control and HTML.
Monday, January 23Introduction to git. HTML, CSS and the DOM. Selectors, etc.
Introduction to Homework 1.
Mandatory reading
- D3 Book, Chapters 1-3
- VAD Book, Chapter 1
Recommended reading
Lecture 3: JavaScript Basics
Wednesday, January 25An Introduction to JavaScript.
Mandatory reading
- D3 Book, Chapter 3, go over JavaScript parts.
Recommended reading
- MDN JavaScript Guide
- Book: JavaScript - the Good Parts. Get this book for <20$ if you’re interested in learning more about JavaScript.
- Code Academy Javascript Tutorial
Week 3
Lecture 4: JavaScript II, Intro D3
Monday, January 30Manipulating the DOM, first steps in D3.
Mandatory reading
- D3 book, Chapters 4, 5 and 6
Recommended reading
Homework 1 due.
Monday, January 30, 12:00pm (noon)
Lecture 5: Advanced D3 I
Wednesday, February 1More on data, selections, groupings; scales; Axis
Mandatory reading
- D3 book, Chapters 7, 8, 9 and 10
Recommended reading
Week 4
Lecture 6: Advanced D3 II
Monday, February 6Layouts
Mandatory reading
- D3 book, Chapters 11 and 12
Recommended reading
Lecture 7: Advanced D3 III
Wednesday, February 8Maps, Transitions, and Interactions
Homework 2 due.
Wednesday, February 8, 12:00pm (noon)
Week 5
Lecture 8: Perception, Cognition, Color
Monday, February 13
Mandatory reading
- VAD, Chapters 10.2-10.3, Color Theory and Colormaps
Recommended reading
- Perception in Visualization, Christopher G. Healey
- Gestalt principles (part 1). Bang Wong. Nature Methods 7, pp. 863, Nov 2010.
- Gestalt principles (part 2). Bang Wong. Nature Methods 7, pp. 941, Dec 2010.
Lecture 9: Data Abstraction, Data Types.
Wednesday, February 15
Mandatory reading
- VAD, Chapter 2, Data Abstraction
Recommended reading
- On the Theory of Scales of Measurement. S. S. Stevens. Science, 103(2684), pp. 677-680, June 1946.
Homework 3 due.
Wednesday, February 15, 12:00pm (noon)
Week 6
Lecture 10: Public Lecture - Paolo Ciuccarelli
Tuesday, February 21Paolo Ciuccarelli is a Associate Professor at Politecnico di Milano and runs the DensityDesign Research Lab. His research focuses on the visual representation of complex social, organizational and urban phenomena. His research aims to exploit the potential of information visualization and information design and provide innovative and engaging visual artifacts to enable researchers and scholars to build solid arguments. By rearranging numeric data, reinterpreting qualitative information, locating information geographically, and building visual taxonomies, they develop a diagrammatic visualization—a sort of graphic shortcut—to describe and unveil the hidden connections of complex systems. This lecture will *not* be in our normal classroom and time. Instead, it will be at 5:00pm on Tuesday Feb21 in the CFA Building, Room 111
Guest lecturer: Paolo CiuccarelliMandatory reading
- Browse the projects of DensityDesign, which is Paolo’s research lab in the Design Department of the Politecnico di Milano.
Lecture 11: The Visualization Alphabet: Marks and Channels.
Wednesday, February 22
Mandatory reading
- VAD, Chapter 5, Marks and Channels
- VAD, Chapters 6.3-6.6, and 6.9, Rules of Thumb
- VAD, Chapter 10.4, Mapping Other Channels
Recommended reading
- Graphical Perception: Theory, Experimentation and the Application to the Development of Graphical Models. William S. Cleveland, Robert McGill, J. Am. Stat. Assoc. 79:387, pp. 531-554, 1984.
- The Structure of the Information Visualization Design Space. Stuart Card and Jock Mackinlay. Proceedings of InfoVis, 1997.
Week 7
Lecture 12: Design Guidelines; Visualization Tasks
Monday, February 27
Mandatory reading
- VAD, Chapter 6.10, Function First, Form Next
- VAD, Chapter 3, Why: Task Abstraction
Recommended reading
- Design Principles for Visual Communication. Maneesh Agrawala, Wilmot Li, Floraine Berthouzoz. Communications of the ACM, 54(4), pp. 60-69, Apr 2011.
- Design of data figures. Bang Wong. Nature Methods 7, pp. 665, Sept 2010.
- Low-Level Components of Analytic Activity in Information Visualization. Robert Amar, James Eagan, and John Stasko. Proceedings of InfoVis, 2005.
- A Multi-Level Typology of Abstract Visualization Tasks. Matthew Brehmer and Tamara Munzner. IEEE Transactions on Visualization and Computer Graphics (TVCG), 19(12), p. 2376–2385, 2013.
- A Design Space of Visualization Tasks. Hans-Jorg Schulz, Thomas Nocke, Magnus Heitzler, and Heidrun Schumann. IEEE Transactions on Visualization and Computer Graphics (TVCG), 19(12), p. 2376–2385, 2013.
Lecture 13: Interaction
Wednesday, March 1
Mandatory reading
- VAD, Chapter 11, Manipulate View
- VAD, Chapter 6.8, Responsiveness Is Required
Week 8
Lecture 14: Data Science
Monday, March 6Guest Lecture by Nikola Banovic
Guest lecturer: Nikola Banovic
Homework 4 due.
Monday, March 6, 12:00pm (noon)
Lecture 15: No Class! Instead, watch Public Lecture Jeffrey Heer - Predictive Interaction
Wednesday, March 8Guest lecturer: Jeffrey Heer
Week 9
Spring Break!Week 10
Lecture 16: Views; Focus and Context
Monday, March 20
Mandatory reading
- VDA Chapter 12, Facet into Multiple Views
- VDA Chapter 14, Embed: Focus + Context
Lecture 17: Project Proposal Presentations
Wednesday, March 22
Project Proposal due.
Wednesday, March 22, 12:00pm (noon)
Week 11
Lecture 18: Filtering & Aggregation
Monday, March 27
Mandatory reading
- VDA Ch. 13 Reduce Items and Attributes
Lecture 19: How to Lie with Data
Wednesday, March 29Guest Lecture by Nikola Banovic
Guest lecturer: David NewburyWeek 12
Lecture 20: Visualizing Tabular Data
Monday, April 3
Mandatory reading
- VDA Chapter 7, Tables
Lecture 21: Project Feedback Sessions
Wednesday, April 5
Week 13
Lecture 22: Storytelling With Data
Monday, April 10Guest Lecture by Eric Dash
Guest lecturer: Eric DashLecture 23: No Class
Wednesday, April 12
Week 14
Lecture 24: Visualizing Tabular Data, Part 2
Monday, April 17
Mandatory reading
- VDA Chapter 7, Tables
Lecture 25: Project Feedback Sessions
Wednesday, April 19
Project Milestone due.
Wednesday, April 19, 12:00pm (noon)
Week 15
Lecture 26: Visualizing Graphs and Trees
Monday, April 24
Lecture 27: (Tentative Title) Visualizations at Uber
Wednesday, April 26Guest Lecture by Jamie Rasmussen
Guest lecturer: Jamie RasmussenWeek 16
Lecture 28: No Class
Monday, May 1
Lecture 29: In-class Project Presentations
Wednesday, May 3Guest judges (from industry and campus) will choose their favorite projects
Final Project Presentation due.
Wednesday, May 3, 12:00pm (noon)