Reproducible research through reusable code

Introduction

Reproducibility of quantitative research is essential for robust research findings. But did you ever wonder if your analysis can be re-run by someone else?

This workshop helps you make your quantitative research reproducible by sharing your analysis code. Analysis code is the code that you generate when you execute your data processing and analysis steps (for example, in a programming language like R or Python). This code indicates in detail how you processed and analysed your data.

This workshop will teach you the skills to make your code reusable by others. This workshop is organized together with the Netherlands eScience Center and co-led by one of their research software trainers. You will practice skills needed for reproducible research by directly applying them to your own project. Inevitably, this will make your research more reproducible.

Next to this workshop you can attend the Code-check your research workshop, in which you will learn how to evaluate the level of reproducibility of someone else’s code.
 

Course information 

ECTS: 1.5
Number of sessions: 1 
Hours per session: 7.5 

 

Working method and preparation

You will practice with your own code project. You will learn how to share your code with others using GitHub, writing documentation such as a good README file, how to deal with software dependencies, and how to apply code conventions and modular coding. By practising on your own project, you will make your code more readable and reusable. There will be ample opportunity to ask questions to the instructors, who are experts in research software engineering and reproducibility.z
 

Relevance

The workshop is relevant for people who do statistical research with script-based programs like R and Python.
 

Entry level

You should be able to write basic code in a programming language like R or Python. This can be a few simple line of code to process your data and to run your analysis, it is not necessarily expected that participants are able to write a full software package. Please contact the lecturer in case you have any questions about whether you have the required code skills.