This two-day workshop enables life scientists to effectively create figures based on quantitative data that add impact to their publications and presentations. The workshop is divided into two one-day modules: Principles and Applications.
On the first day, the Principles module focuses on understanding the purpose of a figure, choosing the most appropriate plot type, and the science of perception. The first day is primarily concerned with the art of visual communicaiton and integrates participants’ own examples into the teaching process.
On the second day, the Applications module focuses on the practical implementation of the data visualisation principles discussed on the first day. This is done using the R statistical programming environ- ment with the participants’ own data.
On the second day of the workshop, students are expected to bring their own computers and data for practical work. The following cross-platform software pre-installed.
ggplot2, 3.1 or later – RColorBrewer, 1.1 or later.Hmisc, 4.1 or later.RColorBrewer and Hmisc should be installed as a dependency of ggplot2.
Participants are expected to have proficiency in R prior to the workshop. Previously, students proficient in MatLab, Perl and/or Python, but with little experience in R, have also benefited from the workshop. However, if you are not comfortable with any programming or scripting language, you may find the second day difficult.
If you can at least follow R code, you are in good shape. Students often comment that I place too much emphasis on previous R knowledge, but I’d rather be overly cautious than not give any warning at all.
The workshop’s first day will focus on principles of data visualisation, with a focus on design principles and plotting quantitative data (i.e. statistical graphs). This will involve an interactive discussion of your own examples of data visualisation.
For this purpose, you can submit either one of your own plots of quantitative data, or a figure from a published research article. In either case, please include a couple of sentences describing the data/plot (very useful for understanding what is going on) and why you find it to be a particularly good or bad example of Data Visualisation. Your input will help to develop relevant examples for the workshop.
Please bring in 4 print-outs of your example and if possible e-mail to me vefore the workshop: office@scavetta.academy. . We’ll use this for an in-class exercises at the beginning of the first day.
Finally, you should also prepare some of your own data to work with so that you can make figures on the second day.