Making your research accessible: Data Visualization and Interactive Graphics

This course aims to enable participants to produce high-quality plots based on raw data and/or model outputs using the R package “ggplot2” (1st day) and to teach principles of interactive data visualization with the R package “shiny” (2nd day). The first day will familiarize participants with the logic of the ggplot package and apply those principles to common use cases. In addition to some generic examples, such as scatterplots with/without regression lines, boxplots, or line charts, these use cases will be largely driven by participants’ needs and requests. Possible topics include grouped plots, faceting (i.e. dividing your data into many categories and plot them individually for comparison), or visualizing regression model output (e.g. through “dot-whisker” plots). Participants will learn through hand-on exercises to build their own plots and learn how to export plots in various formats. The second day will revolve around the main steps involved in creating interactive web applications using R and Shiny Apps. During this day, participants will learn how to prepare data for building interactive graphics, the basic principles for crafting interactive apps and the main alternatives to deploy and share visualizations. After a brief introductory part, this session will be mostly practical. Participants will learn to create generic apps, as well as their own particular visualizations based on participants’ datasets and examples.  

We strongly encourage participants to familiarize themselves with the basic principles of R before the course, as we won't have much time to focus on R basics during the course.