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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

Profile image for Jonathan Mang

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)