Universität Wien FIND

Return to Vienna for the summer semester of 2022. We are planning to hold courses mainly on site to enable the personal exchange between you, your teachers and fellow students. We have labelled digital and mixed courses in u:find accordingly.

Due to COVID-19, there might be changes at short notice (e.g. individual classes in a digital format). Obtain information about the current status on u:find and check your e-mails regularly.

Please read the information on https://studieren.univie.ac.at/en/info.

136014 UE Data Visualization in the Digital Humanities (2021W)

Continuous assessment of course work


Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).


max. 25 participants
Language: English


Classes (iCal) - next class is marked with N

The course will be held online.

Course dates:

15.10.2021, 14:00-19:00
19.11.2021, 14:00-19:00
17.12.2021, 14:00-19:00
21.01.2022, 14:00-19:00

Friday 15.10. 14:00 - 19:00 Digital
Friday 19.11. 14:00 - 19:00 Digital
Friday 17.12. 14:00 - 19:00 Digital
Friday 21.01. 14:00 - 19:00 Digital


Aims, contents and method of the course

Be it in academia or in everyday contexts, we are surrounded by all kinds of graphs, charts, and other visualizations of data. But what makes a good visualization and how can we create such visualizations ourselves?

This course gives an introduction to data visualization techniques in the digital humanities.

Students will be made familiar with:
• basic principles of human visual perception and processing.
• basic theoretical concepts of how to design informative and reader-friendly visualizations.
• various types of static and interactive visualizations, such as bar charts, point, line and violin plots, heat maps, word clouds, maps, networks, trees, or timelines.
• the programming language R and relevant R packages for data visualization.

Students will do plenty of hands-on exercises in R, in which they will practice creating different types of data visualizations.

Assessment and permitted materials

• Regular homework assignments: 4 x 20 points
• In-class participation: 20 points

Minimum requirements and assessment criteria

In this course, we will work with the programming language R, which is a versatile tool for data visualization and analysis. No preliminary knowledge of R is required, but having some experience in any programming language will certainly be beneficial.

The grading scale for the course will be:

90-100 points: sehr gut
80-89 points: gut
70-79 points: befriedigend
60-69 points: genügend
0-59 points: nicht genügend

Examination topics

Completion of in-class assignments and homework assignments, active contribution to discussions in class.

Reading list

To be announced in class.

Association in the course directory

S-DH (Cluster III: Theater, Film und Medien)

Last modified: Fr 24.09.2021 14:28