Kursussøgning, efter- og videreuddannelse – Københavns Universitet

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Kursussøgning, efter- og videreuddannelse

Interactive Data Exploration (IDE)

Practical information
Study year 2016/2017
Block 2
Programme level Full Degree Master
Course responsible
  • Wouter Krogh Boomsma (2-7c6745696e33707a336970)
  • Department of Computer Science
Course number: NDAK15017U

Course content

Visualizing scientific data is important, not only for presenting results and conclusions in a convincing and appealing manner, but also as tools for exploration and generating hypotheses. Interaction networks between molecules, social relationships between friends, or road networks can all be represented as graphs and visualized using force-directed graph layouts (http://getspringy.com). Large treestructures can be visualized and explored using sunbursts (http://mbostock.github.io/protovis/ex/sunburst.html) or collapsible trees (http://bl.ocks.org/tchaymore/1249394). Finally, displaying, navigating and animating three-dimensional scenes is essential to most disciplines that involve some form of physical simulation. While static visualizations can be created with tools like matplotlib, animated or interactive visualizations that are easily shared across any modern platform (webpage, tablet app, phone app, conference video-presentation) have much wider uses.

This course will introduce interactive visualization techniques that are particularly relevant in science, and teach the student to implement these. A set of techniques, representing a wide range of scientific visualizations, will be demonstrated during lectures and projects, and students will be trained in reading, transforming and reducing a dataset to a representation that fits a certain visualization need. There is some flexibility to adapt projects to the students background but likely topics that will be covered include, interactive scatter+bar plots, force-directed graph drawing, decision trees, geographical maps, scene visualization, 3D volume visualization, and 3D streamlines/streaklines/pathlines.

There will be weekly programming exercises, mainly creating and using JavaScript libraries, where students get hands-on experience with the curriculum.

Learning outcome


  • Familiarity with a wide set of techniques used for interactive visualization

  • Experience with 4-6 key interactive visualization techniques

  • Familiarity with at least two large JavaScript libraries that will enable students to easily build or adapt visualizations in their future research careers.



  • Visualizing graphs, trees, matrices, maps, and 3D-scenes using JavaScript libraries

  • Parsing, representing and transforming data from/to e.g. CSV, JSON, and XML formats using JavaScript libraries


  • Producing cross-platform, sharable, interactive visualizations of scientific data

  • Producing high-quality, publication ready, customized figures for scientific publications

Recommended prerequisites

Students are expected to have programming experience corresponding to either ‘Introduktion til Programmering’ or ‘Python Programming’.

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Study Board of Mathematics and Computer Science

Course type

Single subject courses (day)


1 block


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Teaching and learning methods

Mix of lectures and group work on weekly projects.


No limit




The following books are expected to be used:

  • Interactive Data Visualization for the Web, Scott Murray

  • Learning Three.js


Category Hours
Lectures 28
Preparation 42
Exercises 60
Project work 75
Exam 1
English 206


Type of assessment

Continuous assessment
Oral defence, 15min
Final grade is an overall evaluation of
- the 5 individual weekly projects
- final group project
- oral defense of final project (no preparation)

Marking scale

7-point grading scale

Criteria for exam assessment

To get the grade 12, a student should 

  • Have accomplished the learning objectives of the course
  • Be able to present and discuss both final project and topics taught during the course

Censorship form

No external censorship
Several internal examiners


Oral exam, 30 minutes, with no preparation. To qualify 4 of the 5 individual weekly projects must be passed, no later than two weeks before the re-exam.

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