After successful completion of the course, students are able to...
... distinguish between the different functions of visualisation in scientific work
... select suitable visualisation methods for different questions and types of data sets
... understand and apply basic properties of visual perception in the context of visualisation methods
... use common tools (R/ggplot2, Gephi) for the pre-processing of data sets and their visualisations
... read existing visualisations critically
Visual perception and the functioning, possibilities, goals, application scenarios of visualisation.
History, positive and negative examples of the use of visualisation in STEM fields
Critical interpretation of visualisation
"Scientific visualisation" vs. data or information visualisation
The visualisation pipeline and its different stages
Types of data sets, data types, data properties and matching visualisation methods, visual variables
Selected software tools (R/ggplot2, Gephi) for visualisation and pre-processing of different data sets
Lecture with slides on theoretical and practical aspects of visualisation.
Practical exercises with the presented tools
Exercises, presentations and discussion in the Data Visualisation Space (DAVIS) in the TU Vienna library
Mini-Project with own or provided data
Multiple-choice test
Examination immanent
20% Analysis of a freely chosen existing visualisation according to the Munzner Framework
40% Realisation of a Mini-Project - Visualisation(s) of a provided or freely chosen dataset, Report of 2000 words (without references, code, ...)
40% Multiple Choice Test
