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DH2322 Interactive Data Visualization 7.5 credits

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Information per course offering

Termin

Information for Spring 2027 Start 12 Jan 2027 programme students

Course location

KTH Campus

Duration
12 Jan 2027 - 12 Mar 2027
Periods

Spring 2027: p3 (7.5 hp)

Pace of study

50%

Application code

10425

Form of study

Normal Daytime

Language of instruction

English

Course memo
Course memo is not published
Number of places

Min: 1

Target group
Open for all students from year 3 and for students admitted to a master's programme as long as it can be included in your programme.
Planned modular schedule
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Schedule
Schedule is not published

Contact

Examiner
No information inserted
Course coordinator
No information inserted
Teachers
No information inserted

Course syllabus as PDF

Please note: all information from the Course syllabus is available on this page in an accessible format.

Course syllabus DH2322 (Autumn 2026–)
Headings with content from the Course syllabus DH2322 (Autumn 2026–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

The course covers the basic concepts of data visualization including visualization pipeline, data types, data transformations, data models, visual mappings, visual structures, view transformations, and evaluation techniques. Students develop projects using web-based visualization tools.

The course is project-based and students create and work both individually and in groups. The projects range from, for example, visualizing medical data to visualizing the environmental impacts of global trade. Group projects include actual data from open sources or from partners who provide the data.

Intended learning outcomes

After passing the course, the student should be able to

  • develop interactive visualizations through interactive data transformations, visual mappings and view transformations 
  • motivate design choices based on domain knowledge
  • analyse and criticize information visualization systems
  • demonstrate and explain own data visualizations for a broad audience
  • evaluate their own data visualizations 

in order to achieve the ability to read and create interactive data visualizations. Knowledge of visualization enables clear communication in our data-rich world.

Literature and preparations

Specific prerequisites

Knowledge and skills in programming, 6 credits, equivalent to completed course DD1337/DD1310-DD1319/DD1321/DD1331/DD1333/DD100N/ID1018/ID1022.

Literature

You can find information about course literature either in the course memo for the course offering or in the course room in Canvas.

Examination and completion

Grading scale

A, B, C, D, E, FX, F

Examination

  • PROA - Individual Project, 2.0 credits, grading scale: A, B, C, D, E, FX, F
  • PROB - Group Project, 4.5 credits, grading scale: A, B, C, D, E, FX, F
  • INL1 - Home Assignments, 1.0 credits, grading scale: P, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability. The examiner may apply another examination format when re-examining individual students. If the course is discontinued, students may request to be examined during the following two academic years.

Examiner

No information inserted

Ethical approach

  • All members of a group are responsible for the group's work.
  • In any assessment, every student shall honestly disclose any help received and sources used.
  • In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Further information

Course room in Canvas

Registered students find further information about the implementation of the course in the course room in Canvas. A link to the course room can be found under the tab Studies in the Personal menu at the start of the course.

Offered by

EECS/Human Centered Technology

Main field of study

Computer Science and Engineering

Education cycle

Second cycle