NDAK15017U Interactive Data Exploration (IDE)
MSc Programme in Computer Science
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.
Knowledge
Key principles of visualization
Fundamental visualization and interaction techniques for different data types
Tools and JavaScript libraries for building visualizations
Techniques for parsing/extracting data
- Techniques for building and deploying visualizations on the web
Skills
Systematically analyse and compare visualizations
Design a visualization that effectively supports a particular task
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
Producing cross-platform, shareable, interactive visualizations for the web, particularly of scientific data
Assess the applicability of specific visualization techniques for particular problem domains
- Category
- Hours
- Exam
- 1
- Exercises
- 56
- Lectures
- 24
- Preparation
- 42
- Project work
- 83
- Total
- 206
As
an exchange, guest and credit student - click here!
Continuing Education - click here!
- Credit
- 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% - Exam registration requirements
To qualify for the exam, the student must (1) hand in a report based on their project and (2) have the 4 assignments approved that are given during the course.
- Aid
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
Several internal examiners
- Re-exam
Re-exam same as ordinary exam. If the student is not qualified then qualification can be achieved by hand-in and approval of equivalent assignments and a report for a final project no later than 2 weeks before the re-exam.
Criteria for exam assesment
See Learning Outcome.
Course information
- Language
- English
- Course code
- NDAK15017U
- Credit
- 7,5 ECTS
- Level
- Full Degree Master
- Duration
- 1 block
- Placement
- Block 2
- Schedule
- B
- Course capacity
- No limit
- Continuing and further education
- Study board
- Study Board of Mathematics and Computer Science
Contracting department
- Department of Computer Science
Course Coordinators
- Wouter Krogh Boomsma (2-7a6543676c316e7831676e)