Research compendium for 'Evaluating Cultural Transmission in Bronze Age burial rites of Central, Northern and North-western Europe using radiocarbon data'
http://dx.doi.org/10.17605/OSF.IO/B6NP2
The files at the URL above will generate the results as found in the publication. The files hosted at https://github.com/nevrome/cultrans.bronzeageburials.article2019 are the development versions and may have changed since the paper was published
Schmid, C. (2019). Evaluating Cultural Transmission in Bronze Age burial rites of Central, Northern and Northwestern Europe using radiocarbon data. Adaptive Behavior. https://doi.org/10.1177/1059712319860842
A preprint is available here: https://nevrome.de/lt/schmid2019a.pdf
European Bronze Age archaeology traditionally focusses on two major dimensions to categorise burials -- although there is an immense variability of attendant phenomena within this spectrum -- flat graves versus burial mounds and cremation versus inhumation. These traits are an indispensable ingredient for common archaeological narratives of sociocultural interaction and cultural evolution. This paper presents a quantitative reconstruction of the general trends in the distribution of Bronze Age burial traditions based on bulk radiocarbon data and employs the resulting time series for the estimation of macro-regional cultural distance. Despite the relatively small amount of input data the trend reconstruction fits to established archaeological observations for prehistoric Europe. The comparison of cultural and spatial distance leads to the remarkable result of no significant permanent correlation, which indicates that the spread of the relevant aspects of burial traditions can not be explained with simple diffusion models. Instead a more complex process of cultural transmission has to be considered.
Bronze Age, Burial Traditions, Cultural Transmission, Radiocarbon Dating
This repository contains text, code and data for the paper. The analysis directory contains code and data to reproduce the preparations, calculations and figure renderings. The article directory contains the text for the paper in .Rmd format.
As the data and code in this repository are complete and self-contained, it can be reproduced with any R environment (> version 3.5.0). The necessary package dependencies are documented in the DESCRIPTION file and can be installed manually or automatically with devtools::install(). If it's not possible any more to construct a working environment with these methods due to technological progress, one can use the Docker image.
A Docker image is a lightweight GNU/Linux virtual computer that can be run as a piece of software on Windows, Linux, and OSX. To capture the complete computational environment used for this project, I added a Dockerfile that specifies how to make a compatible Docker image and subsequently created this image. It includes all of the software dependencies needed to run the code, including the data and code itself.
To launch the image, first, install Docker on your computer and start the Docker daemon. Linux users should take a look at the post-installation steps. Then download all the image .tar.part_* files from the relevant repository (see Compendium DOI). At the command prompt you have to merge these .tar.part_* files to one coherent .tar archive:
cat cultransbronze19_docker_image.tar.part_* > cultransbronze19_docker_image.tar
This image archive then has to be loaded into Docker:
docker load -i cultransbronze19_docker_image.tar
With the image loaded you can run it as a container:
docker run -e PASSWORD=cultransbronze19 -dp 8787:8787 --name cultransbronze19 cultransbronze19
This will start a server instance of RStudio. You can now open your web browser at localhost:8787 or run docker-machine ip default in the shell to find the correct IP address, and log in.
username: rstudio
password: cultransbronze19
Once logged in, use the Files pane (bottom right) to navigate to the script files in the analysis folder.
More information about using RStudio in Docker is available at the Rocker wiki pages.
I developed and tested the package on this Docker container, so this is the only platform that I'm confident it works on. It was built and stored with:
docker build -t cultransbronze19 .
docker save -o cultransbronze19_docker_image.tar cultransbronze19
split -d -b 100M cultransbronze19_docker_image.tar "cultransbronze19_docker_image.tar.part_"
Code: MIT http://opensource.org/licenses/MIT year: 2019, copyright holder: Clemens Schmid
Data: Please see the license agreements of Radon-B and Natural Earth data
Text: Please see the license agreements of the Adaptive Behavior journal