What is it about?
In this study we developed a machine-learning based model for the classification of prehistoric mineral objects of personal adornment in the Iberian Peninsula. Using the compositional data obtained by XRF, which is a portable and easy to use technique, the model can infer the mineral in each sample, providing crucial information for the study of this type of material.
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Photo by USGS on Unsplash
Why is it important?
This model facilitates the collection of empirical data for the study of the dynamics of production, circulation and consumption of these objects, reducing analysis times, bureaucratic processes and insurance costs related to the loan of archaeological material. All resources and data are free and open access, allowing interested parties to contribute to improve the model or develop their own in an open science and collective knowledge building approach.
Perspectives
I hope that this study will contribute to building a workflow that integrates computational approaches into archaeological research related to personal adornments. The acquisition of new data will allow us to move towards developing new questions about the emergence of social complexity in the past, and hopefully help us to envision new strategies to meet the challenges of the present.
Daniel Sanchez-Gomez
Universidade de Lisboa
Read the Original
This page is a summary of: A supervised multiclass framework for mineral classification of Iberian beads, PLoS ONE, July 2024, PLOS,
DOI: 10.1371/journal.pone.0302563.
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