Motivation

When writing a scientific paper, the process is often that we want to test out a new method using some data. For example, we want to try out a new way of fitting data to a model. This might involve simulation, machine learning, meshing, etc.

Being able to reproduce the results in the paper is essential, and in this guide, we will go through some steps that can help you achieve this.

Reproducibility is important for other researchers that want to build on top of your work. This could a PhD-student that you supervise, a group of masters students at the summer school, an external researcher that just works within the same field of research, or it could be the future you (for example when you get back the first review and the reviewer ask for additional results).

If your code is well documented and easy to set up and use it is more likely that others may use it, and therefore the chances that your paper will get more citations and publicity are higher.

In the next sections, we will cover some important aspects how to structure the data/code corresponding to the paper.

However, there exists a variety of other resources online and you can check out the section on resources for more info.