Chapter 1 Preface
A repository to house materials for a open and reproducible workflows in the public service workshop.
The goal of this workshop is to introduce participants to concepts of
Reproducible research is the idea that data analyses, and more generally, scientific claims, are published with their data and software code so that others may verify the findings and build upon them.
This workshop focuses on the concepts and tools behind reporting modern data analyses in a reproducible manner. As part of this, we introduce tools that enable publishing data analyses in a single document that allows others to easily execute the same analysis to obtain the same results.
Additionally, as part of this workshop, we briefly introduce working with
R and Rstudio to create a Rmarkdown document. R is a popular statistical computing language, commonly used in many scientific disciplines for statistical analysis, generating production-quality graphics, and automating data workflow tasks.
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1.1 Learning goals
By the end of this workshop, EW2 participants will learn be able to:
- Define reproducible research and open workflows - Discuss current issues surrounding reproducibility - Discuss solutions and important components of reproducibility - Identify tools that are used for reproducible and open research
In the demonstration part of the workshop, we will:
- Write basic markdown documents
- Use knitr, rmarkdown and bookdown R packages to build various document types (e.g. PDF, HTML and DOCX)
- Create reproducible rmarkdown documents leveraging .Rproj and .RData
- Create presentations from Rmarkdown documents that include R code
- Work with git version control tools
- Create reproducible and “backed up” analysis via remote repositories (e.g github)