Data Viz for Research
First created in December 2020, for the Amsterdam UMC, for the personal development of the Psychotrauma Team across two of their weekly meetings. Across these two session, alongside the provision of additional teaching resources, it was aimed to provide a research focused approach to data visualisation in R. Given the broad spectrum of experience within this team, it was decided to provide a structured multi-level approach similar to those sessions developed for the Office for National Statistics, with a strong focus upon practical skills within data visualisation without extensive prior knowledge in this area.
Due to the larger time allowance of this session, two sessions of 90 minutes, this would aim to cover a wider range of practical aspects of data visualisation.
For this site, the contents of both sessions will be combined, however if you wish to complete everything in the order of the sessions, please download the sessions directly from Github
Session 1: A Data Driven Hope (Practical Exercises 1-10)
- To be introduced to the R Universe, in particular the tidyverse and ggplot2.
- To understand the benefits of using different plotting methods (ggplot2 vs plot).
- To begin to generate simple visualisations from novel (research based) data.
- To utilize good coding and data visualisation practices.
- To begin to think constructively about the application of these visualisation techniques
- Basic introduction to the use of R and the tidyverse.
- Basic visualisation techniques using ggplot2.
- Understanding data visualisation techniques and good practice.
- Exploratory Data Analysis using visualisation.
- Creative Problem solving and debugging.
Session 2: Revenge of the Data (Practical Exercises 11-20)
- To embed good practice, through creating replicatable graphics
- To be able to effectively combine complex plots retaining good practice
- To be able to generate publishable plots, in line with common requirements
- Use of replication driven techniques for graph production
- Use of effective layering techniques in ggplot
- Understanding techniques to make effective publishable plots in line with common standards.