An efficient workflow in the R programming language for replicable lithic quantitative analysis

Abstract

Stone tools dominate the prehistoric archaeological record and are pivotal to understanding cultural evolution as their production relies heavily on learned behaviors. Lithics are frequently described using attribute analysis, which is a powerful method for conducting intra- and inter-site comparisons as it builds upon a set of discrete and metric traits that can be statistically treated. Despite recent attempts to tune recording systems and increase interobserver reliability, lithic analysis is seldom replicable because of the infrequent sharing of datasets and workflows for data recording and statistical analysis. The latter do in fact frequently rely on proprietary software that does not permit sharing all coding steps conducted for reaching a certain conclusion. The software environment of R, which is the most used programming language in archaeology, can be a powerful ally to make lithic analysis open and fully replicable. In this talk, we will present an ongoing discussion surrounding the use of R in lithic quantitative analysis that aims at increasing transparency and interoperability by developing a system for data manipulation, visualization, and statistical treatment using several packages available in CRAN. Furthermore, we will show how R Markdown and Quarto are ideal for fostering data replicability by allowing embedding codes alongside observations and visual outputs. We will quantify differences between the MIS3 assemblage from Pinnacle Point 5–6 in South Africa and the Italian Protoaurignacian as an example of efficient and smooth inter-site comparison. Overall, we hope to generate a crucial discussion and stimulate new collaborative projects to foster research replicability and data reuse with the final goal of facilitating cross-regional studies of human cultural evolution.

Armando Falcucci

Postdoctoral Researcher

My research focuses on the earliest stages of the Upper Paleolithic. I am currently analyzing several Aurignacian sites in Italy to better frame the chrono-cultural development of this technocomplex and investigate the role of climate change in the evolution of stone tool technologies.