Lecturer: Jonas Schöley (jschoeley@health.sdu.dk)
"Visualizing Data" is a four day course where participants are introduced to the theory and practice of data visualization. Visualization will be taught as a design process: In order to produce effective visualization one needs to have a clear communication purpose in mind, know the audience and the medium, understand visual perception and be able to use the tools of the trade. This broad range of skills requires the integration of theory and practice. Each lecture starts with an introduction to relevant theory followed by a guided ggplot2 practical.
Please install the current versions of
- R (https://cran.r-project.org/),
- Rstudio (https://www.rstudio.com/products/rstudio/download/), and
- Inkscape (https://inkscape.org/en/).
In R install some necessary libraries by executing install.packages('tidyverse').
- Lecture Slides
- Rost, Lisa C. (2017). Why Do We Visualise Data?
- Emery, Ann K. (2014). The dataviz design process.
- Chapter 2 of Wickham, H. (2016). ggplot2. Elegant Graphics for Data Analysis (2nd ed.) for getting started with
ggplot2.
- Lecture Slides
- ggplot heatmap examples
- Brilliant color advice from NASA
- Chapter 5 of Visualization Analysis and Design for an introduction to marks, channels and visual perception.
- 500 pages on perception in data viz: Ware, C. (2013). Information Visualization. Perception for Design.
- ggplot heatmap examples
- Chapters 9, 10, 11 of Wickham, H. (2016). ggplot2. Elegant Graphics for Data Analysis (2nd ed.) for learning how to use ggplot and other tidy tools for exploratory data analysis.