774410 Data Visualization for communication and exploration (in Eng.)
This page is available under these URLs:
- Lecture and exercise
- Semester hours
- Lecturer (assistant)
- Böhmdorfer, Stefan
- Offered in
- Wintersemester 2023/24
- Languages of instruction
This course gives an introduction to the creation of graphs for effective communication and data exploration. Participants will be able to design graphs according to the desired function while considering the conflicting aims of design (effectiveness/expressiveness, legibility/depth, …). Practical application of the theoretical knowledge – preferably with own data – is an integral part of the course.
•Components of a graph
•Visual variables (length, area, colour, …) and their effectiveness
•Functions of graphs
•Graph types and their effectiveness
•Conflicting design goals
•The physiology of vision
•Data mining, critical assessment of data sources
•Properties of data
•Data reduction and transformation
•Exploratory data analysis
•File types for graphics
•Creation of an A3 infographic, using own or external data
•Constant refining of the infographic and its graphs by implementing new knowledge
•Rules of thumb for scientific posters and slides
•Peer feedback, critical assessment of alterations to the graphic/graph
•Free-hand drawing for quick sketching
•Vector and pixel based drawing software
- Previous knowledge expected
Basic skills in Excel
- Objective (expected results of study and acquired competences)
After completing the course, participants will be able to:
-Create a functional graph.
-Define the purpose of a graph.
-Select a graph that fulfils this purpose effectively.
-Understand the pros and cons of different graph types.
-Select visual parameters according to the requirements of the graphing task.
-Explain the properties of visual parameters.
-Resolve the contradictory requirements of a graph.
-Understand colours, colour spaces, and the physiological and technological limitations of colour usage.
-Make use of contrast.
-Understand the physiological processes of vision and their effects on the perception of graphs.
-Communicate a process graphically.
-Find data sources and judge their trustworthiness.
-Prepare their data for exploratory data analysis.
-Purposefully pre-process their data.
-Answer simple statistical questions visually.
-Sketch their visual ideas.
-Realize their ideas in publication quality with software tools.
-Understand copyright licenses.
You can find more details like the schedule or information about exams on the course-page in BOKUonline.