Interactive Data Exploration (IDE)
Course content
The course introduces participants to visualization: use of interactive visual representations to help people understand and analyse data. Visualization is central to data-intensive science, business and intelligence analysis, for exploratory data analysis and for clearly communicating findings in data.
Participants will learn about the foundations of information visualization and techniques for visually representing different types of data and for supporting different tasks. Students will learn through a practical problem-driven approach to analyze, design, and build visualizations. In particular, through weekly exercises, the course will provide hands-on experience with JavaScript visualization libraries such as d3.js to create interactive visualizations on the web.
This course partly overlaps with the Visualization course. The main difference between the courses is that Interactive Data Exploration places greater weight on technical challenges in developing visualizations, with particular focus on building fully functional, interactive visualizations for the web. These aspects will be emphasized in the evaluation of the final project and the oral exam of this course. Students can only take (and get credit for) one of the two courses.
MSc Programme in Computer Science
Knowledge
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Key principles of visualization
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Fundamental visualization and interaction techniques for different data types
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Tools and JavaScript libraries for building visualizations
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Techniques for parsing/extracting data
- Techniques for building and deploying visualizations on the web
Skills
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Systematically analyse and compare visualizations
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Design a visualization that effectively supports a particular task
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Visualize data types such as graphs, trees, matrices, and maps using JavaScript libraries
- Parse and transform data from/to e.g. CSV, JSON, and XML formats using JavaScript libraries
Competences
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Producing cross-platform, shareable, interactive visualizations for the web, particularly of scientific data
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Assess the applicability of specific visualization techniques for particular problem domains
Mix of lectures and class discussions, tutorials and exercises, and group work on weekly assignments and the project.
Programming skills corresponding to an introductory programming course is expected; experience with computer graphics or JavaScript is an advantage, but is not required.
Students can only take (and get credit for) either this course or the course Visualization (Vis).
- ECTS
- 7,5 ECTS
- Type of assessment
-
Oral examination, 20minThe oral exam is without preparation and based on a group project report.
Weight oral exam: 100% - Aid
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
Several internal examiners
Criteria for exam assessment
See Learning Outcome.
Single subject courses (day)
- Category
- Hours
- Lectures
- 24
- Exercises
- 56
- Preparation
- 42
- Project work
- 83
- Exam
- 1
- English
- 206
Kursusinformation
- Language
- English
- Course number
- NDAK15017U
- ECTS
- 7,5 ECTS
- Programme level
- Full Degree Master
- Duration
-
1 block
- Schedulegroup
-
B
- Capacity
- No limit
- Studyboard
- Study Board of Mathematics and Computer Science
- Department of Computer Science
Course Coordinator
- Wouter Krogh Boomsma (2-846f4d71763b78823b7178)
Er du BA- eller KA-studerende?
Kursusinformation for indskrevne studerende