Reproducibility in 2023 - An end-to-end template for analysis and manuscript writing Passed
Thursday May 25, 2023 08:30 - 08:45 G2
Lecturer: Jonathan Mang
Track: MIE: Special Topic: Caring is Sharing - exploiting value in data for health and innovation
Reproducibility imposes some special requirements at different stages of each project, including reproducible workflows for the analysis including to follow best practices regarding code style and to make the creation of the manuscript reproducible as well. Available tools therefore include version control systems such as Git and document creation tools such as Quarto or R Markdown. However, a re-usable project template mapping the entire process from performing the data analysis to finally writing the manuscript in a reproducible manner is yet lacking. This work aims to fill this gap by presenting an open source template for conducting reproducible research projects utilizing a containerized framework for both developing and conducting the analysis and summarizing the results in a manuscript. This template can be used instantly without any customization.
Language
English
Seminar type
On site only
Objective of lecture
Tools for implementation
Level of knowledge
Intermediate
Target audience
Technicians/IT/Developers
Researchers
Students
Keyword
Actual examples (good/bad)
Education (verification)
Innovation/research
Documentation
Conference
MIE
Authors
Jonathan Mang, Hans-Ulrich Prokosch, Lorenz Kapsner
Lecturers
Jonathan Mang Lecturer
Researcher / Medical Data Scientist
Friedrich-Alexander University Erlangen-Nürnberg, Germany
Medical engineer and data scientist @ University hospital Erlangen, Germany and @Chair of Medical Informatics, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)