This repository contains the data and code for our paper:
Eduardo Paixão, Antonella Pedergnana, Joao Marreiros, Laure Debreuil, Marion Prévost, Yossi Zaidner, Geoff Carver, Walter Gneisinger, (2021). Using mechanical experiments to study Ground Stone Tool use: exploring the formation of percussive and grinding wear traces on limestone tools. Journal of Archaeological Science: Reports https://doi.org/10.1016/j.jasrep.2021.102971
Our pre-print is online here:
Eduardo Paixão, Antonella Pedergnana, Joao Marreiros, Laure Debreuil, Marion Prévost, Yossi Zaidner, Geoff Carver, Walter Gneisinger, (2021). Using mechanical experiments to study Ground Stone Tool use: exploring the formation of percussive and grinding wear traces on limestone tools. Name of journal/book, Accessed 26 May 2021. Online at https://10.31219/osf.io/kdfu5
Please cite this compendium as:
Eduardo Paixão, Antonella Pedergnana, Joao Marreiros, Laure Debreuil, Marion Prévost, Yossi Zaidner, Geoff Carver, Walter Gneisinger, (2021). Compendium of R code and data for Using mechanical experiments to study Ground Stone Tool use: exploring the formation of percussive and grinding wear traces on limestone tools. Accessed 26 May 2021. Online at https://doi.org/xxx/xxx
The analysis directory contains:
- 📁 scripts: R Markdown source
document for manuscript. Includes code to reproduce the figures and
tables generated by the analysis. It also has a rendered version,
paper.docx, suitable for reading (the code is replaced by figures and tables in this file) - 📁 raw_data: Raw data used in the analysis.
- 📁 derived_data: Derived data generated from the analysis.
- 📁 plots: Plots and other illustrations
This research compendium has been developed using the statistical programming language R. To work with the compendium, you will need installed on your computer the R software itself and optionally RStudio Desktop.
The simplest way to explore the text, code and data is to click on binder to open an instance of RStudio in your browser, which will have the compendium files ready to work with. Binder uses rocker-project.org Docker images to ensure a consistent and reproducible computational environment. These Docker images can also be used locally.
You can download the compendium as a zip from from this URL:
master.zip. After unzipping: - open the .Rproj
file in RStudio - run devtools::install() to ensure you have the
packages this analysis depends on (also listed in the
DESCRIPTION file). - finally, open
analysis/paper/paper.Rmd and knit to produce the paper.docx, or run
rmarkdown::render("analysis/paper/paper.Rmd") in the R console
Text and figures : CC-BY-4.0
Code : See the DESCRIPTION file
Data : CC-0 attribution requested in reuse
We welcome contributions from everyone. Before you get started, please see our contributor guidelines. Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.