In the two day VLAG course you will be introduced to the basics of starting an R Project in RMarkdown: how to setup a decent file structure, how to import data and how to process them and how to export the results. Some example data will be used but it will also be possible to work on your own data. The course will have many practical assignments.
Goal: to learn basic principles of RMarkdown as a tool for open science. After this course you will be sufficiently equipped to apply RMarkdown to your own research project.
Some basic knowledge about R, e.g. the VLAG course “Introduction to R” by Jos Hageman
What is open science?
Open Science is the movement to make scientific research and data accessible to all. With Open Science decisions in experimental design, data collection, data processing, statistical analysis, and reporting should be transparent and reproducible for everybody. It is basically the old idea that scientific results should be reproducible by everyone and open to criticism.
What is the problem?
Many PhD students and other researchers use tools like Excel or SPSS to collect & store data from their experiments. They even use it for calculations and visualizations. Finally, results are transferred to Word for writing a paper and/or PowerPoint for creating a presentation. What is eventually communicated to the outside world as a final product in the form of a thesis, paper or presentation is hard to unravel for an outsider, let alone to reproduce it. In the process of transferring data, graphs, results of statistical analysis from one software program to another, it is not unlikely that errors will be made and some of them will go unnoticed. The results have become irreproducible and the scientific path has become obscured (even for yourself and your team). Commercial software programs may not be accessible to everyone and therefore results may never be reproducible. This goes against the idea of open science.
RMarkdown is a freely available software program that combines text, statistical analysis, and graphics into one file. Data storage, analysis, and presentation of results (in a paper or presentation) takes places in a single computer program. This has advantages like e.g. changes in a dataset are immediately processed in statistical models, graphs and reports. Workflows in RMarkdown can be considerably more efficient and therefor faster. Multiple RMarkdown files (e.g. each file being a paper) can easily be combined to form a thesis. RMarkdown documents can be converted into:
- Html pages
- Word files
- Presentation slides
The core of RMarkdown is the freely available software program R that runs on every computer platform. In practice, it is most convenient to use RStudio, also freely available. RStudio can be linked to version control systems like GIT and GITHub. In fact, you can use RMarkdown in RStudio just as a word processor without any knowledge of R but its strength is, of course, the combination of text with data processing, statistical analysis, graphing and reporting, so in practice it only makes sense if you master R to some extent.
Jos Hageman (Biometris) & Tiny van Boekel (FQD)
21-22 October 2020, full days on Campus WUR
The study load of this course is 0.6 ECTS credits.
Registration & Costs:
|PhD candidates affiliated with VLAG/WUR *||175 €|
|All other PhD candidates||400 €|
|Postdoc / staff from VLAG||400 €|
|Postdoc / staff not affiliated with VLAG||525 €|
|Professionals / Non academics||800 €|
Costs includes material, tea/coffee and lunches (sandwiches).
* VLAG/EPS/PE&RC/WASS/WIAS/WIMEK PhD candidates with an approved TSP.
You may cancel free of charge up to four weeks before the start of the course. After this date you will be charged the University fee, unless you can find someone to replace you in the course and supply the course coordinator with the name and contact information of your replacement.
For more information please contact Yvonne Smolders