CS4460: Intro to Information Visualization

General Course Info

Instructor: Alex Godwin [alex.godwin (at) gatech.edu]
First Class: Monday, May 11
Time/ Location: Mon/Wed 12pm-1:45pm, ES&T L1175
Office Hours: Mon 2-3 or by appointment, TSRB 342A
TA: Iulian Radu [iulian.radu (at) gatech.edu]
TA Office Hours: By appointment Only
Prerequisites: CS1332 [Data Struct]

Information visualization helps people explore or explain data through interactive software that exploits the capabilities of the human perceptual system. A key challenge in information visualization is designing a useful spatial mapping of a dataset that is not inherently spatial and coupling that mapping to interaction techniques that allow people to intuitively explore the dataset. Information visualization draws on the intellectual history of several traditions, including computer graphics, human-computer interaction, cognitive psychology, semiotics, graphic design, statistical graphics, cartography, and art. The synthesis of relevant ideas from these fields with new methodologies and techniques made possible by interactive computation are critical for helping people keep pace with the torrents of data confronting them.

Academic integrity: Unless explicitly stated otherwise, you are expected to do your assignments and work on your own. Your project will be a collaborative effort among a group of students. For it, you may use libraries and code fragments from sources on the web that you integrate into an overall working system. Your source code should indicate what code is imported and used as is, what code is imported and modified, and what code is original. It is appropriate to discuss your project with others to gain ideas and feedback and help with sticky problems. It is not appropriate to find an existing infovis system, modify it and submit it as your own work. If in doubt, confer with your instructor. All students are expected to adhere to the Georgia Tech Honor Code.

Course Overview

Syllabus tentative, final changes will be made by a week before the class. Readings should be done before the lecture.

Week	Dates	Topic	Topic	Assignments Due
1	May 11, 13	Intro	Data	HW0
2	May 18, 20	Tasks	Validation	HW 1
3	May 25, 27	No class Memorial Day	Marks & Channels	HW 2
4	Jun 1, 3	Pitches & Rules of Thumb	Tables	HW 3, M1, M2
5	Jun 8, 10	Spatial Data	Networks	HW 4
6	Jun 15, 17	Exam Midterm	Color	M3
7	Jun 22, 24	Manipulate	Facet	HW 5
8	Jun 29, Jul 1	Reduce	Embed	HW 6, M4
9	Jul 6, 8	Case Studies	Commercial Tools
10	Jul 13, 15	No class	Presentations	M5
11	Jul 20, 22	Video Review and Discussion	Review Last Day of Class
12	Jul 27, 29	Exam Final Exam		Exam: 11:30am-2:20pm

Detailed Syllabus

Required Textbook

Visualization Analysis and Design (VAD), Tamara Munzner (A K Peters Visualization Series, CRC Press) is the course textbook.

Class Participation

It is expected that students will come to class, be prepared by doing the readings, and will pay attention and participate in discussions. Doing all three regularly will earn full credit. If you want to surf the internet on your laptop in class, take another course.

Any questions regarding general rules and regulations should first be directed to the Georgia Tech Catalog. If you still have questions, please seek out the TA or Instructor during the posted office hours.

Grading

Component	Weight
Class Participation	10%
HW Assignments	25%
Semester Project	35%
Midterm Exam	15%
Final Exam	15%

Homework

Project Milestones

M1 Pitches
M2 Short Project Statement
M3 Project Proposals
M4 Status Updates
M5 Final Presentations & Videos
Full Description

Late Policy

All assignments are due at the time indicated in the schedule. Late work is penalized at one letter grade per day starting with the day of submission. For example, an assignment turned in 10min late on the submission deadline is one day late, turning in 24hours 10min after the deadline is two days, and so on. This policy applies in all cases except medical or family emergencies. Too much other work, gone for the weekend, ran out of paper etc. are not emergencies.

Daily Schedule

30-45min Lecture
30-45min In-Class Activity
10-15min Ignite Talks
10-15min Open Discussion

Detailed Weekly Schedule

Week 1

Mon, May 11: Intro

Required Reading:
None

Further Reading:

Stuart Card, Jock Mackinlay and Ben Shneiderman. Readings in Information Visualization, Using Visualization to Think, Morgan Kaufmann, 1999, pp. 1-34.
Visualization. Tamara Munzner. Chapter 27, p 675-707, of Fundamentals of Graphics, Third Edition, by Peter Shirley et al. AK Peters, 2009.
A Tour through the Visualization Zoo. Jeffrey Heer, Michael Bostock, Vadim Ogievetsky. Communications of the ACM, 53(6), pp. 59-67, Jun 2010.

Homework:
None

Project Milestones:
None

Wed, May 13: Data

Required Reading:

VAD Ch 1. What's Vis, and Why Do It?
VAD Ch 2. What: Data Abstraction

Further Reading:

Mathematics and the Internet: A Source of Enormous Confusion and Great Potential. Walter Willinger, David Alderson, and John C. Doyle. Notices of the AMS 56(5):586-599, 2009.

Homework:
HW0 Due Friday by 5pm
HW1 Announced

Project Milestones:
None

Week 2

Mon, May 18: Tasks

Required Reading:

VAD Ch 3. Why: Task Abstraction
BallotMaps: Detecting name bias in alphabetically ordered ballot papers. Wood, J., Badawood, D., Dykes, J. & Slingsby, A. (2011). IEEE Transactions on Visualization and Computer Graphics, 17(12), pp. 2384-2391.

Further Reading:
None

Homework:
None

Project Milestones:
None

Wed, May 20: Validation

Required Reading:

VAD Chapter 4. Analysis: Four Levels for Validation
Design Study Methodology: Reflections from the Trenches and the Stacks. Michael Sedlmair, Miriah Meyer, and Tamara Munzner. IEEE Trans. Visualization and Computer Graphics (Proc. InfoVis 2012), 18(12):2431-2440, 2012.

Further Reading:

Storks Deliver Babies (p= 0.008). Robert Matthews. Teaching Statistics 22(2):36-38, 2000. DOI
The Earth is spherical (p < 0.05): alternative methods of statistical inference. Kim J. Vicente and Gerard L. Torenvliet. Theoretical Issues in Ergonomics Science, 1(3):248-271, 2000.
The Prospects for Psychological Science in Human-Computer Interaction. Allen Newell and Stuart K. Card. Journal Human-Computer Interaction 1(3):209-242, 1985.
How to do good research, get it published in SIGKDD and get it cited!, Eamonn Keogh, SIGKDD Tutorial 2009.
False-Positive Psychology: Undisclosed Flexibility in Data Collection and Analysis Allows Presenting Anything as Significant. Joseph P. Simmons, Leif D. Nelson and Uri Simonsohn. Psychological Science 22(11):1359-1366, 2011.
Externalisation - how writing changes thinking.. Alan Dix. Interfaces, Autumn 2008.

Homework:
HW1 Due Wednesday by Class Start
HW2 Announced

Project Milestones:
M1 Announced

Week 3

Mon, May 25: No class Memorial Day

Wed, May 27: Marks and Channels

Required Reading:

VAD Chapter 5. Marks and Channels
Crowdsourcing Graphical Perception: Using Mechanical Turk to Assess Visualization Design. Jeffrey Heer and Michael Bostock. Proc. CHI 2010.

Further 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.
Sizing the Horizon: The Effects of Chart Size and Layering on the Graphical Perception of Time Series Visualizations. Jeffrey Heer, Nicholas Kong, and Maneesh Agrawala. ACM Human Factors in Computing Systems (CHI), 2009. pp. 1303 - 1312.
Automating the Design of Graphical Presentations of Relational Information. Jock Mackinlay, ACM Transaction on Graphics, vol. 5, no. 2, April 1986, pp. 110-141.
Psychophysics: Introduction to Its Perceptual, Neural, and Social Prospects, S. S. Stevens, Wiley 1975.
Semiology of Graphics, Jacques Bertin, Gauthier-Villars 1967, EHESS 1998.
The Grammar of Graphics, Leland Wilkinson, Springer-Verlag 1999.

Homework:
HW2 Due Wednesday by Class Start
HW3 Announced

Project Milestones:
None

Week 4

Mon, June 1: Pitches & Rules of Thumb

Required Reading:

VAD Chapter 6. Rules of Thumb
A Layer-Oriented Interface for Visualizing Time-Series Data from Oscilloscopes. Roberto Lopez-Hernandez, David Guilmaine, Michael J. McGuffin, Lee Barford. Proc. PacificVis 2010, p 41-48.

Further Reading:
None

Homework:
None

Project Milestones:
M1 Blurb due Monday by Class Start
M1 due Monday in Class
M2 Announced

Wed, June 3: Tables

Required Reading:

VAD Chapter 7. Arrange Tables
Radial Sets: Interactive Visual Analysis of Large Overlapping Sets. Bilal Alsallakh, Wolfgang Aigner, Silvia Miksch, and Helwig Hauser. IEEE Transactions on Visualization and Computer Graphics (Proc InfoVis 2013), 19(12):2496-2505, 2013.

Further Reading:
None

Homework:
HW3 Due Wednesday by Class Start
HW4 Announced

Project Milestones:
M2 Due Friday by 5pm

Week 5

Mon, June 8: Spatial Data

Required Reading:

VAD Chapter 8. Arrange Spatial Data
Flow Radar Glyphs -- Static Visualization of Unsteady Flow with Uncertainty. Hlawatsch, Leube, Nowak, and Weiskopf. IEEE TVCG 17(12):1949-1958, 2011.

Further Reading:
None

Homework:
None

Project Milestones:
M3 Announced

Wed, June 10: Networks

Required Reading:

VAD Chapter 9. Arrange Networks and Trees
Topological Fisheye Views for Visualizing Large Graphs, Emden Gansner, Yehuda Koren and Stephen North. IEEE TVCG 11(4):457-468, 2005.

Further Reading:
None

Homework:
HW4 Due
HW5 Announced

Project Milestones:
None

Week 6

Mon, June 15: Exam Midterm

Wed, June 17: Color

Required Reading:

VAD Chapter 10. Map Color and Other Channels
Representing Colors as Three Numbers, Maureen Stone, IEEE Computer Graphics and Applications, 25(4), July 2005, pp. 78-85.

Further Reading:

A Field Guide To Digital Color, Maureen Stone, AK Peters 2003. Or, Stone's VIS 2005 Color course notes
Color Vision
Color use guidelines for data representation C. Brewer, 1999.

Brewer Color Use Guidelines figure

How Not to Lie with Visualization, Bernice E. Rogowitz and Lloyd A. Treinish, Computers In Physics 10(3) May/June 1996, pp 268-273.
Face-based Luminance Matching for Perceptual Colormap Generation Gordon Kindlmann, Erik Reinhard, and Sarah Creem Proc. Vis 2002. [Software]
Measuring Spectral Sensitivity, Chapter 8 of The Joy of Visual Perception by Peter Kaiser

Homework:
None

Project Milestones:
M3 Due Friday by 5pm

Week 7

Mon, June 22: Manipulate

Required Reading:

VAD Chapter 11. Manipulate View
Unfolding the Earth: Myriahedral Projections. Jarke J. van Wijk. The Cartographic Journal, Vol. 45, No. 1, pp.32-42, February 2008.

Further Reading:

Topology-Aware Navigation in Large Networks. Tomer Moscovich, Fanny Chevalier, Nathalie Henry, Emmanuel Pietriga, Jean-Daniel Fekete. Proc CHI 2009, p 2319-2328.
Tuning and testing scrolling interfaces that automatically zoom Andy Cockburn, Joshua Savage, Andrew Wallace. Proc CHI 05.
Smooth and Efficient Zooming and Panning. Jack J. van Wijk and Wim A.A. Nuij, Proc. InfoVis 2003, p. 15-22.
Critical Zones in Desert Fog: Aids to Multiscale Navigation, Susanne Jul and George W. Furnas, Proc. UIST 98
Effective View Navigation, George W. Furnas, Proc. SIGCHI 97, pp. 367-374
Selection: 524,288 Ways To Say 'This Is Interesting'. Graham J. Wills. Proc. InfoVis 1996, p 54-61. DOI
Rapid Controlled Movement Through a Virtual 3D Workspace Jock Mackinlay, Stuart Card, and George Robertson. Proc SIGGRAPH '90, pp 171-176.

Homework:
HW 5 Due
HW 6 Announced

Project Milestones:
None

Wed, June 24: Facet

Required Reading:

VAD Chapter 12. Facet into Multiple Views
Exploring High-D Spaces with Multiform Matrices and Small Multiples Alan MacEachren, Xiping Dai, Frank Hardisty, Diansheng Guo, and Gene Lengerich. Proc InfoVis 2003, p 31-38.

Further Reading:

Exploring the Design Space of Composite Visualizations Javed and Elmqvist, PacificVis 2012, p 1-8.

Homework:
None

Project Milestones:
None

Week 8

Mon, June 29: Reduce

Required Reading:

VAD Chapter 13. Reduce Items and Attributes
Glimmer: Multilevel MDS on the GPU. Stephen Ingram, Tamara Munzner and Marc Olano. IEEE TVCG, 15(2):249-261, Mar/Apr 2009.

Further Reading:
None

Homework:
HW 6 Due

Project Milestones:
M4 Announced

Wed, July 1: Embed

Required Reading:

VAD Chapter 14. Embed: Focus+Context
A Fisheye follow-up: further reflections on focus+context. George W. Furnas, CHI 2006, p 999-1008.

Further Reading:
None

Homework:
None

Project Milestones:
M4 Due Friday by 5pm

Week 9

Mon, July 6: Case Studies

Required Reading:

VAD Chapter 15. Analysis Case Studies
D3: Data-Driven Documents. Michael Bostock, Vadim Ogievetsky, Jeffrey Heer. IEEE Trans. Visualization & Comp. Graphics (Proc. InfoVis), 2011.

Further Reading:

Graph-Theoretic Scagnostics Leland Wilkinson, Anushka Anand, and Robert Grossman. Proc InfoVis 05.

Homework:
None

Project Milestones:
None

Wed, July 8: Commercial Tools

Required Reading:
None

Further Reading:
None

Homework:
None

Project Milestones:
None

Week 10

Mon, July 13: No class

Required Reading:
None

Further Reading:
None

Homework:
None

Project Milestones:
None

Wed, July 15: Presentations

Required Reading:
None

Further Reading:
None

Homework:
None

Project Milestones:
None

Week 11

Mon, July 20: Videos

Required Reading:
None

Further Reading:
None

Homework:
None

Project Milestones:
None

Wed, July 22: Review Last Day of Class

Required Reading:
None

Further Reading:
None

Homework:
None

Project Milestones:
None

Week 12

Mon, July 27: Exam Final Exam

Introduction to Information Visualization [CS 4460 - Summer 2015]

General Course Info

Course Overview

Detailed Syllabus

Required Textbook

Class Participation

Grading

Homework

Project Milestones

Late Policy

Daily Schedule

Detailed Weekly Schedule

Week 1

Mon, May 11: Intro

Wed, May 13: Data

Week 2

Mon, May 18: Tasks

Wed, May 20: Validation

Week 3

Mon, May 25: No class Memorial Day

Wed, May 27: Marks and Channels

Week 4

Mon, June 1: Pitches & Rules of Thumb

Wed, June 3: Tables

Week 5

Mon, June 8: Spatial Data

Wed, June 10: Networks

Week 6

Mon, June 15: Exam Midterm

Wed, June 17: Color

Week 7

Mon, June 22: Manipulate

Wed, June 24: Facet

Week 8

Mon, June 29: Reduce

Wed, July 1: Embed

Week 9

Mon, July 6: Case Studies

Wed, July 8: Commercial Tools

Week 10

Mon, July 13: No class

Wed, July 15: Presentations

Week 11

Mon, July 20: Videos

Wed, July 22: Review Last Day of Class

Week 12

Mon, July 27: Exam Final Exam

Introduction to Information Visualization
[CS 4460 - Summer 2015]