TNM048 — Information Visualization, 2019


This course in information visualization is composed of lectures, laboratory assignments and a project assignment. The lectures provide the theoretical framework necessary to work with information visualization. These cover methods for interactive visualization of large complex data sets, common in areas such as: product development, health-care, process control, bioinformatics, etc. The lectures will also cover perception and methods for evaluation. The labs will focus on the implementation of interactive information visualization and here students work in small groups to make practical use of techniques to analyse abstract data sets. In a final project assignment, the student gets the opportunity to specialize in a specific field of information visualization.

Course Aims

After completing the course, the student should be able to:




Laboratory Exercises

The labs should be carried out in pairs. Examination of the laboratory part of the course is performed during the lab session. For questions regarding labs 1 and 2 contact Kahin Akram Hassan or Prithiviraj Muthumanickam. For questions regarding lab 3, contact Camilla Forsell.


The task for the project part of the course is to develop an interactive information visualization application. The application should then be used to analyse a data set containing complex relationships. The choice of techniques used should be supported by literature and should be suitable for the analysis tasks. The application can consists of any number of visual representations and views. The focus should be on having enough representations and interactions techniques in order to efficiently be able to analyse the data set at hand.

The project should be carried out in small groups (2-3 students).

Individual project report
The results of the project are the implementation and a short-paper in English , describing the background, method, results, etc. of the work. The report should be written individually. The report should adhere to the Latex template: Report Template (a preview in pdf can be downloaded here). It is mandatory to use this Latex template. The software TeXnicCenter is installed in the lab rooms. It is not allowed to use Word, etc. For grade 3, it is allowed to use up to 2 pages, for grades 4 and 5 it is allowed to use up to 3 pages.

The projects will be graded U,3,4,5, according to the following criteria:

Grade 3: Well motivated choice of visualization and interaction techniques, given the used data set. A well written and structured report. The maximum length of the report is 2 pages.

Grade 4: The requirements for grade 3 plus a well motivated use of an implemented data mining technique (not K-means) or a performed evaluation with at least 3 participants. The study should be well performed and well documented by using one of the discussed techniques in the course. The evaluation should be done with at least 3 participants (no member of the project group is allowed to participate). The maximum length of the report is 3 pages.

Grade 5: The requirements for grades 3 plus an implemented data mining technique and an evaluation. The maximum length of the report is 3 pages.

Development environment
The project can be implemented in any programming language and can be web-based or a desktop application.

You should write the code by yourself. If you use code from existing sources this should be clearly written in the comments of the code.

Project Presentations
For the project presentations, each group will have 10 minutes to present their project (in English). After this time there will be an additional 5 minutes for questions and changing computer. The main purpose of the presentations is to show and discuss your project results with your peers. Focus the presentation on the data, your results, a demonstration of your application, and some interesting findings.

Project Report
Deadline for submititting the report by e-mail to Jimmy Johansson is March 19, midnight.


Here you can many useful resources needed for the course.

Information Visualization
Data Mining
D3.js, version 4
Data repositories
© 2014 - 2019 Jimmy Johansson. Updated 2019-01-17.