2018/07/26 by Ulf Toelch, Dirk Ostwald · 1 voice · 3 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Decision Sciences · #Cell Image Analysis Techniques #Research Data Management Practices #Scientific Computing and Data Management
paper · pdf · doi:10.1371/journal.pbio.2006022
openalex publication_date 2018/07/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/23
An important hallmark of science is the transparency and reproducibility of scientific results. Over the last few years, internet-based technologies have emerged that allow for a representation of the scientific process that goes far beyond traditional methods and analysis descriptions. Using these often freely available tools requires a suite of skills that is not necessarily part of a curriculum in the life sciences. However, funders, journals, and policy makers increasingly require researchers to ensure complete reproducibility of their methods and analyses. To close this gap, we designed an introductory course that guides students towards a reproducible science workflow. Here, we outline the course content and possible extensions, report encountered challenges, and discuss how to integrate such a course in existing curricula.