yDiv Course: Building R packages with Rstudio and GitHub

Date & time: Monday, September 23 - Tuesday, September 24, 2018 (2 full days)

Location: Leipzig, Deutscher Platz, German Centre for Integrative Biodiversity Research (iDiv) - Interim III, Metamorphosis,

Teachers: Alexander Zizka & Steffen Ehrmann, University of Leipzig/German Centre for Integrative Biodiversity Research

Detailed schedule and locations

Day 1 - 9:30 - 18:00

  • 9:30 Introduction
  • 10:00 Lecture “Main components of an R-package”
  • 10:45 Definition of the student projects
  • 11:15 Lecture “How to build an R package – Tools and workflow”
  • 12:00 Lunch
  • 13:00 Demo + Exercise 1 & 2: “Package skeleton and data”
  • 14:30 Demo + Exercise 3: “Functions and Documentation”
  • 16:30 Demo + Exercise 4: “Package building and checking”

Day 2 - 9:30 - 18:00

  • 9:30 Project work
  • 11:14 Lecture: “Package testing”
  • 12:00 Lunch
  • 13:00 Lecture: “Package documentation and release”
  • 14:00 Project work
  • 16:15 Student presentations
  • 17:15 Course evaluation and Wrap up

Before the course


Please do not hesitate to contact us if you have any questions.


After this course, students will be able to

  1. understand the structure of R-packages and their main elements
  2. use up-to-date methodology to provide R code and data as R-package
  3. be familiar with common tools for packaging, including roxygen2, devtools, and GitHub


R is a widely used tool for data analyses in ecology. Part of its success is due to the active community and the wide array of add-on packages contributed by scientists from across disciplines, via the CRAN network. R packages are an excellent and standardize way to distribute code and data to a huge community, and a great tool to ensure reproducible research. The course guides through the process of building and R package starting from conceptualization to testing. The course consists of introductory demonstrations coupled with hands-on exercises on the different stages of package building, plus time to work on a small example.

Project Assignment

During the course you will write a small data package based on your own data with guidance from the teachers.


Grades are pass/fail. Successful participants should participate in all course days and present a project on the last day. A certification will be issued for all participants.


https://r-pkgs.org/, chapters 2, 6-10 and 16.

Course level and requirements

This is a course for graduate students and researchers that routinely use R for analysis and want to learn how to distribute data and code as R package.

Number of students

max. 10

Language of instruction