COMP4048  Information Visualisation   2008 Semester 2 Thursday 3-5pm, SIT Lab 117 Unit coordinator: Dr. SeokHee Hong ( shhong  "at"  it. usyd. edu. au)

Information Visualisation and Graph Drawing aim to make good pictures of abstract information, such as stock prices, family trees, and software design diagrams.
Well designed pictures can convey this information rapidly and effectively.
The research challenge for Information Visualisation and Graph Drawing is to design and implement new algorithms that produce such pictures.
Applications include visualisation of bioinformatics, social network, software visualisation and network visualisation.
This unit will provide basic concepts, techniques and fundamental algorithms to achieve good visualisation of  abstract information.
Further, it will also provide opportunities for academic research and developing new methods for information visualisation.

Assumed Knowledge

It is assumed that students will have basic knowledge of data structures, algorithms  and programming skills.

USYD SIT Policy

You are required to visit the URL and carefully read the policies on Academic Honesty, Special Consideration due to illness and misadventure, and Late Submissions.

• Week 5-7: Student Presentation 1 (15%)
• Week 10-12: Student Presentation 2 (15%)
• Choice of Survey Paper or Programming Assignment (with Report 1 and 2)
• Week 7: Report 1 (10%)
• Week 13: Report 2 and Final Presentation or Demo (50%)
• In class participation: 10%

• Visualisation of Social Networks
• Visualisation of Biological Data/Networks
• Visualisation of Large and Complex Networks
• Visual Analytics
• Visual Complexity
• Visualisation of Multi-dimensional/Multi-relational/Temporal/Dynamic/Evolution Networks
• Evaluation in Information Visualisation
• Information Visualisation and Graph Drawing Systems/Tools

• Giuseppe Di Battista, Peter Eades, Roberto Tamassia, Ioannis G. Tollis, Graph Drawing: Algorithms for the Visualization of Graphs, Prentice-Hall, 1999.
• Michael Kaufmann, Dorothea Wagner eds., Drawing Graphs - Methods and Models, Springer, Lecture Notes in Computer Science, vol. 2025, 2001.
• Stuart Card, Jock Mackinlay, and Ben Shneiderman, Readings in Information Visualization: Using Vision to Think, Morgan Kaufmann, 1999.
• Colin Ware, Information Visualization: Perception for Design, Morgan Kaufmann, 2000.
• Robert Spence, Information Visualization, Pearson Addison Wesley, 2000
• Annual Conference Proceedings: Graph Drawing, IEEE InfoVis, EuroVis (VisSym), PacificVis (APVIS), IV, ACM CHI.

• Chapter 10, Giuseppe Di Battista, Peter Eades, Roberto Tamassia, Ioannis G. Tollis, Graph Drawing: Algorithms for the Visualization of Graphs, Prentice-Hall, 1999.
• Ulrik Brandes, Drawing on Physical Analogies, Michael Kaufmann and Dorothea Wagner (Eds.), Drawing Graphs: Methods and Models, LNCS Tutorial 2025, pp. 71-86, Springer-Verlag, 2001.
• P. Eades, A Heuristic for Graph Drawing, Congressus Numerantium, vol. 42, pp. 149-160, 1984.
• T. Kamada and S. Kawai, An Algorithm for Drawing General Undirected Graphs, Information Processing Letters, vol. 31, pp. 7-15, 1989.
• T. Fruchterman and E. Reingold, Graph Drawing by Force-Directed Placement, Software-Practice and Experience, vol. 21, no. 11, pp. 1129-1164, 1991.
• Arne Frick, Andreas Ludwig, Heiko Mehldau, A Fast Adaptive Layout Algorithm for Undirected Graphs, Proceedings of GD 1994, 388-403
• Kozo Sugiyama, Kazuo Misue, A Simple and Unified Method for Drawing Graphs: Magnetic-Spring Algorithm, Proceedings of GD 1994, 364-375

• Send your preference list (ranking 1-6) to the lecturer.
• 1. Chris Walshaw: A Multilevel Algorithm for Force-Directed Graph Drawing, Proceeding of Graph Drawing 2000, pp. 171-182, LNCS 1984, Springer 2001.
• 2. David Harel, Yehuda Koren: A Fast Multi-scale Method for Drawing Large Graphs, Proceeding of Graph Drawing 2000, pp. 183-196, LNCS 1984, Springer 2001.
• 3. Pawel Gajer, Michael T. Goodrich, Stephen G. Kobourov: A Multi-dimensional Approach to Force-Directed Layouts of Large Graphs, Proceeding of Graph Drawing 2000, pp. 211-221, LNCS 1984, Springer 2001.
• 4. David Harel, Yehuda Koren: Graph Drawing by High-Dimensional Embedding, Proceeding of Graph Drawing 2002, pp. 207-219, LNCS 2528, Springer 2002.
• 5. Yehuda Koren, Liran Carmel, David Harel: ACE: A Fast Multiscale Eigenvectors Computation for Drawing Huge Graphs, Proceedings of IEEE INFOVIS 2002, pp. 137-144.
• 6. Yehuda Koren, David Harel: Axis-by-Axis Stress Minimization, Proceeding of Graph Drawing 2003, pp. 450-459.

• Web of Science : It is possible to download complete descriptions of selected works (with references) - up to 500 at once.
• See also, WoS Pajek .

• Information on Paper Presentation: (1). Explain your paper: problem definition, previous/related work, main methods/techniques/approaches, obtained/experimental results and discussion. (2). Evaluate the paper: what are the advantages (good features) and disadvantages (bad features) of their approaches, and how to improve the results (follow up).
• Report 1 (programming): should include your understanding/processing of the data set, related/previous work, your approach and main idea, implementation plan and references.
• Report 1 (survey): should include your understanding of the topic, related/previous work, your approach for categorization and comparison, future plans and references.
• Report 1 marking scheme: originality (20%), understanding and approaches (20%), literature review (20%), planning (20%) and presentation (20%).
• Report 1: at least 5 up to 10 pages with single column text in 11-point font size.
• Report 1 presentation: 10 minutes for each team.

• Topics and time table is subject to change.