NDAK15017U Interactive Data Exploration (IDE)

Volume 2017/2018
Education

MSc Programme in Computer Science 

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.

Learning Outcome

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

Students can only take (and get credit for) either this course or the course Visualization (Vis).
Programming skills corresponding to an introductory programming course is expected; experience with computer graphics or JavaScript is an advantage, but is not required.
Mix of lectures and class discussions, tutorials and exercises, and group work on weekly assignments and the project.
  • Category
  • Hours
  • Exam
  • 1
  • Exercises
  • 56
  • Lectures
  • 24
  • Preparation
  • 42
  • Project work
  • 83
  • Total
  • 206
Credit
7,5 ECTS
Type of assessment
Oral examination, 20min
The 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.