Reproducibility is an essential Open Science practice and consequently a cornerstone of computational research. Publishing the code and the data underlying the results in the paper allows reviewers to verify the results, readers to understand the finding in more detail, and other researchers to build upon the work. Nevertheless, for several cultural and technical reasons, publishing open and reproducible results is challenging to realize.
This presentation introduces basic concepts and issues around reproducibility. It will then provide an overview of existing tools that help researchers publish open reproducible research and which aspects users should consider when selecting the right tool for the own work.
