Data Visualization Workshop
- Sessions 1 & 2: None
- Session 3: Basic skills in programming with R
- Session 4: Experience in programming with R and in particular the package ggplot2
Graphics are an essential part of any publication. Good graphics can improve the understanding, credibility and make an impact. In these workshops, we will discuss the importance of data visualizations, key considerations for their construction, and possibilities for animated and interactive graphics.
The program consists of a series of 2 seminar talks and 2 exercise classes.
- Session 1: The communicative power of eloquent data visualization (150 min)
Data visualization allows us to represent and understand information in a fast and intuitive manner. What makes great charts great? and what makes bad charts bad, or even sometimes misleading? It is easy to view charts as factual and impartial, but every chart tells a story and highlights different aspects of the underlying data. Through a series of real-life examples, we will discuss the importance of clear and deliberate data visualization, which ingredients we need to combine to create clear and precise visualizations, and learn how communicate as clearly through our charts as in our writing.
- Session 2: Interactive Graphics (45 min)
Classical graphics, such as those found in publications, are static. While a good chart is insightful, clarity dictates a necessary restriction of scope and prohibits the presentation of all data. So, the readers are bound to the story line of the authors. Enabling interested readers to modify the graphic and change this focus allows them to learn more than is possible from a classical chart. In this talk we explain advantages and features of interactive graphic by introducing simple interactive 2D graphics (plotly), simple 3D graphics (rgl), animated plots (gganimate) and tools for interactive displaying of data (shiny). This is an introductory overview session where NO prior knowledge of either statistics or programming is necessary.
- Session 3: A taster for creating shiny apps (90 min)
Shiny is a powerful tool providing more than just static graphics or tables to readers. It enables us to directly combine R code/outputs with the writing of interactive html pages. The user can modify all kinds of features, for example selecting specific groups, adding further covariates, or simply playing around to discover more features step-by-step. In this session we combine some short introduction on how shiny works with hands-on exercises. Therefore, we require some knowledge of programming in R, such as would be obtained through our “Introduction to R” course. Knowledge in ggplot2 would also be beneficial.
- Session 4: A taster for creating animated figures (90 min)
Following on from the introductory session Interactive Graphics, we provide a more detailed insight into to the animation of graphics. Static graphics often become too crowded, when we try to show all features at once. In an animated graphic we can guide the reader through different aspects by showing these in sequence. One option for building such “videos” in an easy way is the R-package gganimate. In this session we combine some short explanations of the R-package gganimate with exercises focused on how to animate graphics. For this course some programming knowledge is required. We rely on knowledge in R in general and the package ggplot2 in particular.
- Sessions 1 & 2 are intended to give an overview on different aspects of data visualization. The participants are invited to bring their own graphs, or graphs from the literature to discuss them during the class.
- Sessions 3 & 4 are exercise classes with a mix of explanations on the coding aspects and hands-on exercise sessions.
- Duration: 2 half days split into 4 sessions of different length
- Language: English
- This course will be offered either on campus (in person), or online.
- For online courses we use the software Zoom.
- Material for the workshop will be published in the Campus Management System
Dates and Application:
- Workshops provided for Helmholtz Munich:
* Links marked with * are only available for Helmholtz Munich staff.