CRediTas

The goal of CRediTas is to facilitate the tedious job of creating CRediT authors statements for scientific publications. Normally, the first author of a scientific paper organizes a table in a spreadsheet where all the authors self-state their contributions. Often too, it is the first author responsibility to state the contributions of all co-authors. However, at the end, the information has to be translated to the CRediT statement format of “Author 1: roles Authors 2: roles …” which is prone to errors and tedious, especially if there are many co-authors. The CRediTas package aims to make this easier by providing a template to be filled in form of a table (csv) and then converting this table to CRediT statement format.

Installation

You can install the development version of CRediTas from r-universe with:

install.packages("CRediTas", repos = "https://ropensci.r-universe.dev")

Example

The workflow is meant to work with three basic functions. First, we create a template table. It can be created as a data.frame and being populated in R. Or as a csv file and being populated in your preferred csv editor.

library(CRediTas)

template_create(authors = c("Alexander Humboldt", "Carl Ritter"), file = tempfile())

cras_table <- template_create(authors = c("Friedrich Ratzel", 
                                          "Pau Vidal de la Blache", 
                                          "Pau Vila",
                                          "Élisée Reclus"))
knitr::kable(cras_table)

As you can see, the table is empty. So you must provide the information of who did what. You can use the fix function to fill the template directly in R:

fix(cras_table)

If you wrote the template to a file, then you can read it back to R as follows:

cras_table <- template_read(path_to_your_csv_file)

Once the cras_table is populated, for instance:

A text file can be generated following the CRediT author statement format. Since drop = TRUE by default, the authors without contribution are removed from the statement, Pau Vila in this case.

textfile <- tempfile()

cras_write(cras_table, textfile, markdown = TRUE, quiet = TRUE)

If you open the text file, you will find this:

Friedrich Ratzel: Conceptualization, Formal Analysis, Investigation, Writing - original draft, Visualization, Project administration Pau Vidal de la Blache: Conceptualization, Software, Investigation, Project administration, Funding acquisition Élisée Reclus: Software, Validation, Resources, Writing - original draft, Writing - review & editing, Supervision, Project administration, Funding acquisition

Related packages

• tenzing: Tenzing, an easy-to-use web-based app, allows researchers to generate reports about the contribution of each team member on a project using CRediT, for insertion into their manuscripts and for publishers to potentially incorporate into article metadata.
• contribution: The goal of contribution is to generate contribution table for credit assignment in a project. This is inspired by Nick Steinmetz (see twitter https://twitter.com/SteinmetzNeuro/status/1147241138291527681).