The course participants will acquire the knowledge and skills necessary to visualize a wide range of data for analysis, exploration, and information purposes. The participants will learn the fundamentals of human perception, design and interaction principles as well as elemental visualization techniques necessary to create visualizations suitable for the given type of data and the intended use case. The participants will also know the requirements that different data types and levels of complexity impose on the visualization as well as how to evaluate the quality of information visualizations. Much of the data covered in the course is abstract, i.e., the data has no spatial reference and thus cannot be mapped trivially to geometric visuals. Examples of abstract data include survey results, database contents, or genome information. The participants will be challenged with data from many more applications in industry, business, science and everyday life.
The lecture will cover the following topics:
- Perceptual psychology and cognitive basics
- Design and interaction principles
- Interactive information visualization techniques for multivariate data, relational data, time-dependent data, geographic data, and network data
- Techniques for managing large amounts of information: Multiple views, focus and context techniques, Visual Analytics
- Development environments and toolkits for information visualization
- Evaluation of information visualization solutions
The course is in English.
The modality of the final exam depends on the number of participants. In case of ~10 or fewer participants, the exam will be oral; otherwise, the exam will be in writing.