L579: Information Visualization (Spring 2005)

Course Description | Grade | Policies | Course Outline | Resources

Instructor: Katy Börner | Email: katy@indiana.edu | Office: Main Library 019 | Phone: 855-3256
Assistant Instructor: Weimao Ke | Email: wke@indiana.edu

Lecture: Fri 9:30-10:45a LI 001 Lab: Fri 11:00a -12:15p Interdisciplinary Experimental Laboratory, Woodburn Hall 220
Office hours: Wed 4:00p-5:00p, Main Library 019 (Katy) | Mon 10-11am, LI012 (Weimao)

Prerequisites: L401 or permission of instructor.

Majordomo List: katy_l579@indiana.edu
Class Webpage: http://ella.slis.indiana.edu/~katy/L579
Project Handin Webpage: http://ella.slis.indiana.edu/~katy/handin/L579-S05/cgi/handinlogin.cgi

Lecture and lab notes are accessible in my ella directory '~katy/www/L579/*.ppt'
Software is linked from http://iv.slis.indiana.edu/sw

Supplemental Readings (on reserve in the SLIS library):

• Judith R. Brown, Mikael Jern, John Vince (Contributor), Rae A. Earnshaw (Contributor) (1995) Visualization: Using Computer Graphics to Explore Data and Present Information, John Wiley & Sons.
• Scott McCloud (1994) Understanding comics, Kitchen Sink Press.
• Scott McCloud (2000) Reinventing Comics, Paperback, Harperperennial Library.
• Stuart K. Card, Jock D. MacKinlay, Ben Shneiderman (Editors) (1999) Readings in Information Visualization: Using Vision to Think, Morgan Kaufmann Publishers.
• Robert L. Harris (2000) Information Graphics : A Comprehensive Illustrated Reference. Oxford Univ Press.
• Felice Frankel (2002) Envisioning Science: The Design and Craft of the Science Image. The MIT Press. Watch Felice Frankel's presentation.
• Marti Hearst (1999) User Interfaces and Visualization. In Modern Information Retrieval, Ricardo Baeza-Yates & Berthier Ribeiro-Neto, chapter 10, Addison-Wesley. Online version. See http://www.schoenerwissen.com/ for an alternative visualization.
• Ioannis Tollis, Giuseppe Di Battista, Peter Eades (Editor), Roberto Tamassia, Ionnis G. Tollis (1998) Graph Drawing: Algorithms for the Visualization of Graphs, Prentice Hall.
• Edward R. Tufte  (1990) Envisioning Information. Graphics Press.
• Edward R. Tufte  (1992) The Visual Display of Quantitative Information. Graphics Press.
• Edward R. Tufte  (1997) Visual Explanations: Images and Quantities, Evidence and Narrative. Graphics Press.
• Colin Ware (1999) Information Visualization: Perception for Design, Morgan Kaufmann Publishers (now APPRO).
• Colin Ware, Ed H. Chi, & Rich Gossweiler (2000) CHI 2000: Visual Perception and Data Visualization, Tutorial Notes.

• InfoVis Wiki
• Martin Dodge, Atlas of Cyberspace. http://www.cybergeography.org/atlas/atlas.html
• Gallery of Data Visualization http://ricardo.ecn.wfu.edu/SCS/Gallery/
• David Rumsey Map Collection http://www.davidrumsey.com/GIS/
• Science and Engineering Visualization Challenge by National Science Foundation and the journal Science, 2003 and 2004, and 2005.
• Edward Tufte's Ask ET forum
• Inf@Vis. The digital magazine of the InfoVis.net
• VideoArt @ The END
• Information Aesthetics
• HTML into Flowers

Course Description
The visual representation of information requires a deep understanding of human perceptual and cognitive capabilities, computer graphics, interface and interaction design, as well as creativity.

Information - such as log files reporting access of webpages or paper-citation network data - is typically non-spatial or abstract and needs to be mapped into a physical space that will represent relationships contained in the information faithfully and efficiently. If done successfully, visualizations can provide a very intuitive and efficient "interface between two powerful information processing systems - the human mind and the modern computer" [Gershom et al., 1998].

This course provides an overview about the state of the art in the emerging field of information visualization. It will highlight the process of producing effective visualizations that take the needs of users into account and illustrate practical visualization procedures. It will cover the

• perceptual basis of information visualization,
• data analysis algorithms that enable extraction of relationships in data,
• major visualization and interaction techniques,
• discussions of systems that drive research and development, and
• future trends and remaining fundamental problems in the field.

The course utilizes a combination of lectures, presentations and discussions, and projects. It also comprises Overview & Discussion sessions that present state of the art tools for the visualization of diverse data sets. There will be in class presentations of public-domain software and you will work with software packages that have been developed for this course. You will be expected to do weekly Readings, to provide a Presentation of specific readings, to participate in class, and to work in teams for projects 2 through 4 improving your social competence.

Class participation:
The quantity and quality of contributions made to class (especially during paper discussions) and electronic discussions counts for 20% of the grade.
All students will be expected to study the assigned readings before each class and to participate in class by asking and answering questions. Readings are assigned for study in preparation for class discussion. Thus, class 2 readings should be completed before attending the second week's class.

Presentation of selected readings:
The 20 minute presentation will address a specific topic/question and will be based on readings from the literature or Internet. Sources will be provided. If you can find more that's great. See Preparation of Presentations for more details.
You are expected to consult the instructor during office hours the week in which you will give the presentation. Prepare your presentation as well as any specific questions you may have in advance.

Projects:
There will be four projects. Except for the first project, you will work on them in teams. Submit links to resulting webpages via the project handin webpage at http://ella.slis.indiana.edu/~katy/handin/L579-S05/cgi/handinlogin.cgi. Projects will be graded according to

• The technical quality, including its reliability, ease-of-use, internal consistency, robustness, and performance, and
• The quality of the content, including the accuracy and completeness of information, the expressiveness and clarity in communication of ideas, and the appropriateness of the attribution(s) for the work of others.

Credits: 3 for L579

1. Class attendance: Please do let me know if you can't make it to a class.
2. Plagiarism: Clearly indicate if you use materials from other sources. Academic and personal misconduct by students in this class are dealt with according to the Student Disciplinary Procedures.
3. Late Handin Policy: Late assignments or incompletes are allowed only because of an unforeseen emergency that is preceded by diligent work, not for a pattern of weak performance. No individual student will be allowed to do extra work to raise the final grade or to make up missing work. All grades become final one week after the material is returned to you. If there is a medical or personal reason requiring you to miss an exam, you must present your excuse in writing, and some physical proof. Course work handed in
• within the first 10 min past due time will receive at most 90% of the possible points.
• between 10 to 60 mins past due time receive at most 50% of the possible points.
• more than one hour too late receive F.
Make sure you submit projects in time and your programs/webpages work ok!

Introduction

Class 1 (01-14-2005) [ivc-class01.ppt, iv-natl-geog.ppt]
Course description & outline, class format, grades, resources.
Information Visualization - Overview, history, relation to other disciplines.
Lab: Examination and discussion of successful information visualizations. Kartoo, InfoZoom, EZChooser, The Brain, Visual Thesaurus, Touchgraph, Marketmap, NetScan, CDS bibliographic service, TextArc, Visible Human Viewer, MapBlast (LineDrive), ClustrMaps, Google Earth
Overview & Discussion: Photographic Contribution of the National Geographic

Project 1: Personal Webpage - Design a personal webpage that tells about your skills, interests, and expectations of the course. Select and discuss three visuals that are important for you and/or helped you understand what words could not explain.
Due 01-20-2005 at 8pm (~ 1 week)

Class 2  (01-21-2005) [ivc-class02.ppt, iv-web-dirs.ppt, iv-searchr.ppt]
Setting the context (Science of data visualization [Ware, 1999] chapter 1).
Reading: Nahum Gershon, Stephen G. Eick and Stuart Card (1998) Information visualization, Interactions March & April, pp 9-15.
Lab: User & task analysis.
Overview & Discussion: Web Topology, Web and File directories

Project 2: User-centered design, discussion and evaluation of a tree visualization
Due 02-10-2005 at 8pm (~ 3 weeks)

Perception for Design

Class 3  (01-28-2005) [ivc-class03.ppt]
General overview (Environment, optics, resolution and display [Ware, 1999] chapter 2; Lightness, brightness, contrast and constancy [Ware, 1999] chapter 3; Color [Ware, 1999] chapter 4).
Reading: Watch Felice Frankel's presentation. Read about Illuminated Diagrams by W. Bradford Paley
Lab: Discussion of different display devices.

Class 4:  (02-04-2004) [ivc-class04.ppt]
Making information visible (Visual attention and information that pops out [Ware, 1999] chapter 5; Static and moving patterns [Ware, 1999] chapter 6; Visual objects and data objects [Ware, 1999] chapter 7).
Reading: Perception in Visualization by Christopher G. Healey.
Lab: Tour with Raymond Burks, Kelley School of Business "Visualizations in marketing and finance".

Class 5:  (02-11-2005) [ivc-class05.ppt]
Perception and interaction. Optical illusions. (Space perception and the display of data in space [Ware, 1999] chapter 8; Images and words [Ware, 1999] chapter 9)
Reading: Joy of Visual Perception by Pete Kaiser & Motion Perception Tutorial by George Mather.
Lab: Exploration and discussion of diverse static and dynamic illusions.

Project 3: Analyzing and Visualizing Time Series Data
Due 03-03-2005 at 8pm (~ 3 weeks)

Class 6:  (02-18-2005) [ivc-class06.ppt]
Data analysis. Salton's Vector space analysis. LSA and Burst detection algorithm.
Reading: Keim, D. Visual Exploration of Large Data Sets. Communications of the ACM, Vol 44, No 8, August 2001.
Presentations:

• Salton, G., Allan, J, Buckley, C., and Sighal, A. (1994) Automatic-Analysis, Theme Generation, and Summary of Machine-Readable Texts. Science 264: (5164),1421-1426. In [Stuart et al., 1999] pp. 413-418. (Jay Askren)
• M.W. Berry, S.T. Dumais, and T.A. Letsche (1995) Computational Methods for Intelligent Information Access. Proceedings of Supercomputing'95, San Diego, CA. & Susan Dumais, John Platt, David Heckerman and Mehran Sahami (1998) Inductive learning algorithms and representations for text categorization. Proceedings of the ACM 7th international conference on Information and knowledge management, Washington, pp 148 - 155. (Heather Roinestad)
• Jon Kleinberg (2002) Bursty and hierarchical structure in streams. Proceedings of the eighth ACM SIGKDD international conference on knowledge discovery and data mining, Edmonton, Alberta, Canada, pp. 91 - 101.  (Roger Stanton)

Class 7:  (02-25-2005) [ivc-class07.ppt]
Clustering techniques.
Reading: How Text Clustering Works &  Douglass Cutting, David Karger, Jan Pedersen, and John W. Tukey. Scatter/Gather: A Cluster-based Approach to Browsing Large Document Collections, Proceedings of the 15th Annual International ACM/SIGIR Conference, Copenhagen, 1992.
Presentation:

• Joe H. Ward (1963). Hierarchical grouping to optimize an objective function. Journal of American Statistical Association, Vol-58, Issue-301 (Mar-1963) 236-244.
• Ulrik Brandes (2001) A Faster Algorithm for Betweenness Centrality. Journal of Mathematical Sociology 25(2):163-177, 2001.  (Aian Aliman)

Lab: Ward clustering and betweeness centrality clustering. Hierarchical Clustering Explorer. Discussion of project 3 plans. 

Information Visualization

Class 8:  (03-04-2005) [ivc-class08.ppt]
Display techniques: Temporal, tabular, and multidimensional data displays.
Reading: Chi, E.H., Riedel, J., Barry, Ph., & Konstan, J. (1998) Principles for Information Visualization Spreadsheets. In IEEE Computer Graphics and Applications (Special Issue on Visualization), IEEE CS Press. p. 30 - 38.
Presentation:

• Eick, Steffen, Summer: SeeSoft-A tool for visualizing line oriented software statistics, IEEE Transactions on Software Engineering 18 (1992), pp. 957-968. See also [Stuart et al., 1999]  pp 419-430. (Joseph Cottam)

Lab: TimeSearcher & GRIDL. Infozoom, Tableau Software & BlogPulse

Project 4: Design an Interactive Visualization of Dataset
Due 04-21-2005 at 8pm (~ 6 weeks)

Class 9: (03-11-2005) [ivc-class09.ppt]
Display techniques: Trees & networks
Reading: Treemaps & Treemap publications. To Draw a Tree by Pat Hanrahan.
Presentations:

• Ka-Ping Yee, Danyel Fisher, Rachna Dhamija, Marti Hearst: Animated Exploration of Graphs with Radial Layout. Proceedings of the IEEE Symposium on Information Visualization 2001 (Infovis 2001), October 2001. (Jue Mei)
• Tamara Munzner, Francois Guimbretiere, Serdar Tasiran, Li Zhang, and Yunhong Zhou. TreeJuxtaposer: Scalable Tree Comparison using Focus+Context with Guaranteed Visibility. SIGGRAPH 2003, published as ACM Transactions on Graphics 22(3), pp. 453-462. (Chad Armstrong)

Lab: Hyperbolic Trees, Radial Trees, Treemaps, Force Directed Layout and Pathfinder Network Scaling. Simple graph match, ABSURDIST & Similarity Flooding.
Overview & Discussion: Trees

Class 10: (03-18-2005) Have a nice Spring Break!

Class 11: (03-25-2005) [ivc-class11.ppt, iv-kdvis.ppt]
Display techniques: Text data and semantic data landscapes.
Reading: Katy Börner, Chaomei Chen, & Kevin Boyack. Visualizing Knowledge Domains. In Blaise Cronin (Ed.), Annual Review of Information Science & Technology, Volume 37, Medford, NJ: Information Today, Inc./American Society for Information Science and Technology, chapter 5, pp. 179-255, 2003.
Presentations:

• Chen, C., & Carr, L. (1999) Trailblazing the literature of hypertext: Author co-citation analysis (1989-1998). Proceedings of the 10th ACM Conference on Hypertext, pp. 51-60.
• Chen, C. (2004) Searching for intellectual turning points: Progressive Knowledge Domain Visualization. Proceedings of the National Academy of Sciences of the United States of America (PNAS), 101 (Suppl. 1), 5303-5310. Demo CiteSpace. (Cuau Vital)

Overview & Discussion: Visualization of Knowledge Domains
Lab: Discussion of final project plans.

Class 12: (04-01-2005) [ivc-class12.ppt, iv-activity-patterns.ppt]
Display techniques: Geographic data landscapes and activity patterns.
Reading: Börner, Katy and Penumarthy, Shashikant. (2003). Social Diffusion Patterns in Three-Dimensional Virtual Worlds. Information Visualization, 2(3):182-198.
Presentation:

• Andre Skupin (2000) From Metaphor to Method: Cartographic Perspectives on Information Visualization. In: Roth, S.F. and Keim, D.A. (Eds.) Proceedings IEEE Symposium on Information Visualization, Salt Lake City, Utah. Los Alamitos: IEEE Computer Society, pp. 91-97.
• Andre Skupin (2002) A Cartographic Approach to Visualizing Conference Abstracts. IEEE Computer Graphics and Applications. 22 (1): 50-58.

Overview & Discussion: Visualization of Activity Patterns & Dynamics.
Lab: CAIDA tools, WiGLE, and the Active World Toolkit.

Class 13: (04-08-2005) [ivc-class13.ppt]
Interaction techniques (Interacting with visualizations [Ware, 1999] chapter 10).
Reading: Christopher Ahlberg, Christopher Williamson and Ben Shneiderman (1992) Dynamic queries for information exploration: An implementation and evaluation. Conference Proceedings on Human Factors in Computing Systems, pp. 619 - 626. Magic Lens Demo, TaskGallery Video

Class 14: (04-15-2005) [ivc-class14.ppt]
Distortion techniques.
Reading: Leung, Y. and Apperley, M. (1994) A Review and Taxonomy of Distortion-Oriented Presentation Techniques, ACM ToCHI, 1 (2), pp. 126-160.
Presentation:

• George W. Furnas and Benjamin B. Bederson (1995)  Space-scale diagrams: Understanding multiscale interfaces. Conference Proceedings on Human Factors in Computing Systems, pp. 234 - 241.
• Emden R. Gansner, Yehuda Koren and Stephen North (2004) Topological Fisheye Views for Visualizing Large Graphs. Proceedings of the IEEE Symposium on Information Visualization (INFOVIS'04), IEEE Press, pp. 175 - 182 (Mark Meiss)

Lab:  FishEye table, bifocal displays & zoom. Piccolo Toolkit and GeoZui3D

Student generated test questions
Write five test questions and exemplary answers that test main course topics. This will give you the opportunity to evaluate course topics, reflect on what you understood, and what are good test items for the upcoming final exam. Submit result via email to katy@indiana.edu by Tuesday 4-19-05.

Class 15:  (04-22-2005) [ivc-class15.ppt]
Current trends in information visualization & remaining fundamental problems in the field. Scalability and complexity issues.
Readings:  Browse position papers for the Information Visualization Software Infrastructures workshop, Free Code Graphing Project and TeraGrid.
Presentations:

• Stephen G. Eick & Alan F. Karr: Visual Scalability. IEEE Transactions on Visualization and Computer Graphics, 6(1), pp. 44-58, 2000. (Matt Liggett)
• What users/researchers truly want: Major visualization code libraries/tools available via sourceforge.net. (Weimao Ke)

Lab: Discussion of test questions as preparation for final exam.

Class 16: (04-29-2004)
Final Project Demo

Final Exam on Monday 05-02-2004, 12:30-1:30 pm, LI 001

It will be open book - you can use all your notes etc. You will not be able to use a computer.

• Information Visualization projects page
• CyberStacks(sm)
• Olive - On-line Library of Information Visualization Environments
• Information Visualization Resources
• Software for Visualization
• Information Visualization Benchmarks Repository

• B573/P573: Scientific Computing and B673: Advanced Scientific Computing by Randy Bramley
• B581: Advanced Computer Graphics by Andrew J. Hanson
• B689: Mathematical Modeling for Scientific Visualization by Andrew J. Hanson
• CSCI 552 Scientific Visualization by Shiaofen Fang, IUPUI

• Information Visualization by Ben Shneiderman, HCIL, University of Maryland
• Information Visualization by Ben Bederson, HCIL, University of Maryland
• Information Visualization and Presentation, Marti Hearst, University of California
• Information Visualization by George Furnas, University of Michigan
• Information Visualization by John Stasko, Georgia Institute of Technology
• Interactive Data Visualization by Colin Ware, University of New Hampshire
• Interaction Design: A Perceptual Approach, W. Bradford Paley, Columbia University.
• Geographies of Cyberspace by Martin Dodge, University College London
• Social Visualization by Judith Donath, MIT
• Information Visualization as Artistic Practice, Golan Levin, Carnegie-Mellon University
• Mapping Cyberspace by Sara Fabrikant, UCSB
• Interaction Design: A Perceptual Approach by W. Bradford Paley, Columbia University
• Visualizations in Learning by David Akers, Stanford University

Katy Börner L579
http://ella.slis.indiana.edu/~katy/L579
Last modified: 01/25/2005