Advancing Bayesian Methods for Typo-Chronologically Dated Archaeological Datasets

BTChron aims to advance chronological methods in archaeology by developing innovative Bayesian approaches to the analysis of typo-chronologically dated datasets, where temporal attributes are typically reported as time spans. Failure to formally integrate these time spans into statistical analyses can potentially lead to biases in interpretation. The proposed research addresses the critical limitations of current methods, which are inadequate for dealing with chronological uncertainty.Applicable to any temporal analysis of large archaeological datasets, the proposal will make a substantial contribution to the field of quantitative archaeology by providing robust statistical tools for chronological analysis, ensuring the integration of legacy data into new, scientifically rigorous frameworks. The proposal is interdisciplinary, combining data science approaches with archaeological/historical methods and zooarchaeology. BTChron will select open access datasets to model temporal changes in three metrics commonly used in zooarchaeological analysis: LSI (Log-Size-Index), NISP (Number of Identified Specimens) and age-at-death. By focusing on faunal assemblages from Western Europe during the Roman period, BTChron will also provide a more accurate understanding of agricultural changes driven by Romanisation. The results will improve archaeological interpretations and contribute to open science through reproducible methods and accessible data.The proposed research will be conducted at the McDonald Institute for Archaeological Research in Cambridge under the supervision of Dr Enrico Crema, a leading expert in applications of Bayesian approaches to archaeological data problems.This fellowship will allow the Researcher to develop their expertise in data science approaches, which is essential for their future ambitions in the field of quantitative archaeology.