Why Computational Reproducibility?
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.
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.
Who we are and how we work
We are researchers and service providers working with tools and technologies facilitating our everyday processing of data. While some of us are good in one aspect of making computational methods more reproducible, others might have improved other ways of achieving this. Together, we aim to learn from each other and find the best ways to ensure reproducibility of our research, our services, and our work.
We are still a very young working group, trying to find a suitable mode of operation. Feel free to join us and defining the best way forward in achieving our goals … oh yeah, and help us define goals!
If you feel up to the challenge, please contact Daniel Stekhoven, to join the group.
Join us every third Wednesday of the month at 5 pm (CET) exploring ways to become computationally more reproducible. 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.
The seminar is free to attend and no registration is required. Join us on Zoom.
If you want to give a talk as part of this series, please contact Daniel Stekhoven.
|2023-10-18||Singularity Containers in Bioinformatics||Vipin Sreedharan, ETH Zurich|
|2023-11-15||MaRDI TA2: Research Data and Reproducibility in Scientific Computing||Jens Saak, MPI for Dynamics of Complex Technical Systems|
|2023-12-13||Sustainable data science with the Renku platform||Rok Roškar, Swiss Data Science Center|
|2024-01-17||The Reproducible Research Platform – Towards FAIR and reproducible sharing of data, code and computational environments||Henry Lütcke, ETH Zurich|
|2024-02-21||Reproducibility and beyond with Snakemake and Datavzrd||Johannes Köster, Uni Duisburg Essen|
If available recording of the seminars can be found here.
|2023-06-21||Sustainable tool benchmarking and workflow development in Computational Biology||Kim Philipp Jablonski, Google||slides, recording|
|2023-05-17||Replicability, Reproducibility, and Reusability in Computer-based Experiments||Jan Heiland, MPI for Dynamics of Complex Technical Systems||slides|
|2023-04-19||LabKey Server for Reproducible Biomedical Research||Natalia Chicherova, ETH Zurich||slides, recording|