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Immersive Analytics with Applications in the Life Sciences

Organizational unit: Department of Computer and Information Science
Course type: Hybrid course / Directed Studies

In this course we will study, present and discuss articles concerning foundations, current methods, and tools in the area of Immersive Analytics (IA), taking into account the life sciences as a main area of application. IA is an emerging research thrust investigating how new interaction and display technologies can be used to support analytical reasoning and decision making. The aim is to provide multi-sensory interfaces that support collaboration and allow users to immerse themselves in their data in a way that supports real-world analytics tasks. Immersive Analytics builds on technologies such as large touch surfaces, immersive virtual and augmented reality environments, sensor devices and other, rapidly evolving, natural user interface devices.
Core topics for the discussions are
– Definition of immersive analytics, concepts of immersion, and the impact on data analysis
– The use of stereoscopic 3D for data analysis
– Multisensory representation and interaction
– Support for collaboration
– Integration of computational analytics
– Characterisations of environment designs
– Specific challenges and potential in the application areas, e.g. biology, biochemistry, and biomedicine

Exercises support the understanding of the topic. Hands-on exercises with different technologies (3D projection systems such as MiniCave/Cave and zSpace, 3D monitorwall , HMD AR and VR systems and other technology), where you work on small projects, will complement the theoretical studies.

This course has 4 SWS: 2 SWS directed studies (lectures) and 2 SWS exercises/hands-on studies.

Form of examination: Active participation in the discussions, exercises and hands-on project, oral (20 min) or written (60 min) exam at the end of the course

Course coordinators: Prof. Dr. Falk Schreiber, Dr. Karsten Klein

To receive the credits for this course, you are required to pass an exam at the end of the course. Depending on the number of students, the course coordinators will decide whether the exam will be oral or written. A written exam may be taken at your home university, if your departmental coordinator or a responsible representative of your department agrees to supervise you during the exam and send your exam papers directly to the course coordinators.


This course takes place as a hybrid course / lecture.

Further details on the course will be provided in ILIAS.

Please register in ZEUS and ILIAS for this course.

Practical exercises will take place in our IA lab or at other suitable environments, depending on the Covid-19 situation and the project.

Course Literature will be announced at the start of the lecture. The book “Immersive Analytics”, published in 2018, will mainly be used.

Duration: 13.04. – 20.06. 2022

Prerequisites: – Solid programming skills are required to be able to successfully participate in the exercises. Experience with immersive technologies might be helpful, but is not required.
photo of outer space
Period: 13 April – 20 July, Wednesdays 13 :30 – 15 :00 (seminars)

13 April – 20 July, Wednesdays 15 :15  – 16 :45 (exercises)
Format: Hybrid weekly seminar and exercise, digital participation is possible only for ERUA students.
Number of ERUA Students: 3
Number of ETCS: 6
Language: English
Student Level: Master level, but bachelor students with strong interest in data analysis and immersive technologies plus corresponding knowledge can participate (2nd/3rd year).
Application Deadline: 20.07. 2022