Welcome to the SwissRN seminar series on Computational Reproducibility!

In today’s world, computational research has become an essential tool for advancing scientific knowledge and discovery. However, the increasing complexity of computational models and the abundance of data available for analysis can make it challenging to reproduce research results. Computational reproducibility is the ability to independently verify the results of a computational study using the same data and methods. It is a critical aspect of scientific research as it ensures the transparency and credibility of scientific findings. Computational reproducibility allows researchers to build upon the work of others, helping to accelerate scientific progress.

Relevance
The importance of computational reproducibility is particularly evident in fields such as medicine, psychology, environmental science, and economics, where scientific findings can have a direct impact on people’s lives. Inaccurate or non-reproducible results can have severe consequences, ranging from wasted resources to public health risks.

Scope
In this seminar series, we will explore the challenges and opportunities of achieving computational reproducibility in research. We will discuss best practices for data management, code sharing, and documentation, as well as tools and techniques for achieving reproducible results. Join us as we delve into this important topic and work towards enhancing the reproducibility and transparency of scientific research.

Instalments
First seminar: Wednesday, 2023-04-19, 17:00-18:00 https://ethz.zoom.us/j/65832714361 (fixed link for Seminar Series)