In this workshop, participants will learn fundamental approaches to creating a research compendium. This is the foundation of transparent and reproducible research. Participants will learn what kinds of documents and materials they should create and preserve; the information the documents should contain; and how they should be formatted and organized. Topics include raw data, analysis data, scripts, metadata, readme files, project organization, and naming conventions. Examples will be provided in R, but this information can be applied to any quantitative programming environment. The are no prerequisites.
This is the first workshop in the series “Reproducible Research Practices: Make Your Research Life Easier.” Other sessions include “Version Control with GitHub,” “Reproducible Analysis and Documentation with R Studio and R Markdown," and "Sharing Your Data for Transparent and Reproducible Research.”
Jennifer Huck
Last updated: Fall 2021.
Slides are available.
Presenter mode slides are also available. Allow pop-ups.
This presentation is for DADA Quantitative Psychology group at UVA, 2021-12-01.
This is mostly a lecture-based workshop. There are no prerequisites.
For this lesson, you will need
- To be able to create and navigate directories (Explorer (Windows), Finder (Mac), or command line)
- A text editor, such as Notepad (default Windows text editor) or TextEdit (default Mac text editor). Notepad++ or BBEdit/TextWrangler, or Sublime Text are also great choices.
- The data file: gapminderDataFiveYear_superDirty.xlsx (also in tab-delimited text .txt)
See Credits and Further References slides for primary credits and further reading.