Estimating temporal likelihood of archaeological sites in prehistoric Denmark combining typochronological and radiocarbon data

This repository contains the necessary instructions to carry out the analyses described in the paper titled:

Estimating temporal likelihood of archaeological sites combining typochronological and radiocarbon data

Author

Giacomo Bilotti ([e-mail])

Kiel University, Institute of Pre- and Protohistoric Archaeology

Abstract

The surge in data availability and methodological advancements over the last decades has enabled archaeologists to develop more robust data-driven models, which are essential for reconstructing ancient human history. However, despite their potential, these datasets pose significant challenges due to their heterogeneity and inherent uncertainties. A common limitation is the low chronological resolution of many datasets, which often compels archaeologists to rely on proxies such as radiocarbon date frequency distributions to study variations in occupation intensity. While this approach is widely used, it necessitates a large number of radiocarbon samples to construct probability curves, leading to a considerable loss of spatial resolution. Moreover, the method itself is not without criticism. To address these challenges, I propose a novel method that combines typochronological and radiocarbon datasets, preserving both temporal and spatial resolution while accounting for uncertainty. Each relatively dated site is assigned a simulated calendar date within its chronological span, based on the cumulative probability distribution of locally available radiocarbon data. The results are grouped into uniform time windows, with each site assigned a likelihood of belonging to each time period, bridging temporal and spatial data. The efficacy and functionality of the method are demonstrated using toy data, with the results compared to outputs from alternative methods. Finally, the method is applied to four case studies from prehistoric Denmark (4000-500 BC), showcasing its potential in addressing long-standing challenges in archaeological modelling.

Structure of the repository

The repository folder is structured as follows:

Readme.md: This file (repository overview).

scripts/: Contains all R scripts for data preparation, analysis, and visualisation.

00_required_packages.R: Installs and loads required packages.

01_data_preparation.R: Processes raw data into analysis-ready format.

03_paper_figures_6-9.R: Generates figures 6 to 9 for the paper.

(other scripts): Each named by function or purpose for clarity.

data/: Raw and derived geospatial data in GeoPackage (.gpkg) format.

raw_data: Contains raw input files.

derived_data: Contains processed or derived datasets.

SI/: Contains 7 supplementary figures for additional analyses and a PDF file with information about Danish prehistory.

figures/: Stores 11 figures used in the main paper.

All the scripts are also available in GitLab (https://gitlab.com/bilottigiacomo/chronological-modelling)