Data management

This course is offered within the context of the IMPRS BeSmart Summerschool.

Objectives

Effective data management is crucial for organizing, storing, and accessing research data seamlessly. Data management also helps saving time and ensuring the reproducibility and integrity of our research.

Topics

1. Introduction.
   • Data lifecycle.
   • Research integrity.
   • Data sharing.
   • Storage.
   • Reproducibility, replicability.
2. Literate programming.
   • Reproducible research.
   • Definition and concept.
   • Goals and Benefits.
   • Structure.
   • Tools and Languages.
   • Workflow.
   • Examples.
3. Version control with git.
   • Motivation.
   • Repositories.
   • Commits.
   • Branches.
   • Basic Workflow.
   • Collaboration with git.
   • Examples.

Handout

Software

Students should have the following software installed:

• R, in particular with packages knitr, tikzDevice, xtable, tidyverse, car, Ecdat.
• RStudio
• LaTeX (e.g. TeX Live, MiKTeX, or MacTeX)
• git