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Department of Informatics Interactive Visual Data Analysis Group

Seminar: Visual Analytics (BSc, MSc)

Lecturer Prof. Dr. Jürgen Bernard
Teaching Assistant Madhav Sachdeva
Teaching Language English
Level BSc, MSc
Academic Semester Spring 2023
Time and Location

Kickoff: Monday 20.09.2023: 16:00-17:30 Uhr, BIN-2.A.01

Final Presentations: Friday 15.12.2023 09:00-18:00 Uhr, BIN-2.A.10

Course Material

Research Papers

Link to VV BSc, MSc
Link to OLAT BSc, MSc
Office Hours Madhav Sachdeva: email for appointments, BIN 2.A.24


Course Description

Topic Focus:

Visual Analytics (VA) combines automated analysis techniques with interactive visualizations for an effective understanding, reasoning, and decision-making based on very large and complex datasets. As such, research into VA focuses on the combination of the strengths of humans and computers to address complex data analysis challenges. Solutions typically include interactive visual interfaces, enabling users to participate actively in the data science and machine learning process (human-in-the-loop).

Course Mechanics:

In groups, students will study a paper of interest that dictates the individual seminar topic. Students will compile a structured list of references, prepare a compelling fact sheet about the topic, and present the topic in class. In parallel, students will receive mentoring from the supervisor, give constructive feedback on other student's work, and participate actively in the presentation and Q&A rounds.

Learning Goals:

At the end of the course, students:

  • have gained a deeper and broader understanding and knowledge of VA
  • will be able to identify and discuss research problems and identify relevant related work
  • will be able to write a fact sheet about a specific topic in VA research, present the topic to a student audience, and discuss ideas on the topic.
  • will have learned to accept and give feedback on students’ seminar contributions


  • Fact sheet (25%)
  • References list (10%)
  • Quality of feedback on other students' fact sheets (15%)
  • Presentation slides (15%)
  • Presentation of the topic (15%)
  • Discussion, Q&A (20%)