Laboratory of Computer and Information Science > Teaching > T-61.5010 > Exercise work 2006

Exercise work 2006

To pass the course you must pass the examination and complete this exercise work. The work will be graded on the scale rejected, passed and passed with distinction.

To complete the exercise work you may need information that has not been discussed in the lectures. If you have any questions please do not hesitate to contact the assistant or the lecturer for hints, guidance or references.

The exercise work will be graded within a month of the deadline. A passed exercise work will be valid for one year after the original deadline.

General requirements

1. The exercise work should be completed by one person. However, discussing it with others is encouraged.
2. The deadline is 5 May 2006. However, if you want the credits for the course already after the 3rd period, you should return the reports by 13 March.
3. Reports submitted after the final deadline will be rejected. If you have a very good reason that causes you to miss the final deadline you can request an extension. The extension must be requested before the deadline.
4. To pass the exercise work you must fulfill the requirements given in the "specific requirements" section.
5. To pass with distinction you have to do additional work or the specified tasks should be exceptionally well done.
6. Accepted languages for the report are Finnish, Swedish and English.
7. If you submit the exercise work report in time, but don't pass, you will have a chance to supplement your work after the deadline. The supplemented project works will not be eligible for the higher grade, "passed with distinction".
8. Each exercise work report should contain a section that comments on the difficulty of the project and an estimate of the time used for completing it.
9. Documentation should be in a format readable with generally available tools. Preferred formats are Postscript and PDF. However, HTML and plain text are accepted as well.
10. The exercise work reports should be submitted by email (t615010@james.hut.fi). You can either provide a WWW link from which you report can be downloaded or you can attach the report to the email. If email submission is not possible you can use e.g. (internal) mail (Antti Ukkonen, PL 5400, 02015 TKK). The exercise work reports should contain your name, email address and full student number. If you submit your work by email, please include the student number also to the subject line.

Specific requirements

Write 3-5 page summary of one of the papers listed below. All papers are published in
Information Visualization; Houndmills, Summer 2004; Vol.3, Iss.2; Special Issue of selected and extended InfoVis '03 papers
available through the electronic collections of the HUT library.

1. Alistair Morrison, Matthew Chalmers. A pivot-based routine for improved parent-finding in hybrid MDS.
2. Martin Wattenberg, Danyel Fisher. Analyzing perceptual organization in information graphics.
3. Hong Chen. Compound brushing explained.
4. Diane Tang, Chris Stolte, Robert Bosch. Design choices when architecting visualizations.
5. Geraldine E Rosario, Elke A Rundensteiner, David C Brown, Matthew O Ward, Shiping Huang. Mapping nominal values to numbers for effective visualization.

Download one of the data sets given below and visualize some interesting phenomena in the data. Write a short (2-4 pages) report that describes your approach, obtained results and the methods and tools used. The purpose is not to do an analysis that covers the data from all possible angles. Focus on one or two aspects and try to make a clear visualization of them.

Some of the datasets can only be downloaded from the university network.

• Infovis 2004 data
  The data describes research papers related to information visualization. Of every paper is provided the title, authors, abstract, year of publication, keywords and bibliography. You can check the original winners of the 2004 Infovis contest to get an idea what one could do with this data.
• US Census 1990 data (UPDATED Feb. 13!)
  The data consists of a random sample of 24999 individuals, each described by 68 attributes, such as level of education, occupation, country of origin, number of children, etc. More information can be found at the UCI KDD Archive website. Do not try to analyze the complete data. Instead, select some interesting subset of the attributes for inspection. Descriptions of the attributes can be found here. (If the previous link does not work, try this instead.) Note that the continuous variables (eg. age) have been discretized by using this script. For example, the value 5 in the dAge column means the person is 50-65 years old. Check the script for further details. It is written in SQL but should be very easy to interpret for anybody with programming experience.
• Infovis 2006 data
  This alternative is provided for those that seek a challenge. The data is 180MB (zipped) and may require a lot of preprocessing as it is divided to several files.

The use of available visualization tools (e.g. Matlab, R, Graphviz, prefuse, Inkscape etc.) is encouraged. However, implementing your own scripts and small programs for processing the data will be necessary.