Data & R Script for “Blurred Boundaries: Exploring the Complexity of the Production System at the Luomaqiao Kiln in Yuan-Dynasty Jingdezhen”

This deposit provides all raw and supplementary geochemical datasets (LA‑ICP‑MS measurements of ceramic paste and glaze) and the master R script (run_all.R) used to reproduce the analyses in Xu et al. (2025), “Blurred Boundaries: Exploring the Complexity of the Production System at the Luomaqiao Kiln in Yuan‑Dynasty Jingdezhen.” Journal of Archaeological Science. https://doi.org/10.1016/j.jas.2025.106328 Contents: data/raw/ Dataset_S1.csv: LA‑ICP‑MS elemental concentrations of ceramic paste Dataset_S2.csv: LA‑ICP‑MS elemental concentrations of ceramic glaze data/supplementary/ Dataset_S3.csv: Catalogue of porcelain samples Dataset_S4.csv: Mahalanobis‑based group membership probabilities for paste samples Dataset_S5.csv: Mean, SD, and RSD of elemental concentrations by claw category run_all.R: Master R script (installs dependencies, processes data, runs HCA/PCA, and generates Figures 4–13 and Tables 1–2) README.md: Project overview, file map, usage instructions, and software environment Reproducibility & Requirements: R ≥ 4.4.0 (download at https://cran.r-project.org/) CRAN packages: here, dplyr, tidyr, ggplot2, dendextend, tibble, factoextra, ggrepel, ggpubr, stringr Running run_all.R will install all required packages, regenerate all manuscript figures and tables, and write a session_info.txt file into results/ for full provenance.本数据集存档包含所有原始与补充地球化学数据集（陶瓷胎料与釉料的激光剥蚀电感耦合等离子体质谱法（LA-ICP-MS）检测数据），以及用于复现Xu等人2025年发表于《考古科学杂志》的论文《模糊的边界：探索元代景德镇落马桥窑生产体系的复杂性》中分析过程的主R脚本run_all.R。论文DOI：https://doi.org/10.1016/j.jas.2025.106328 数据内容： data/raw/ Dataset_S1.csv：陶瓷胎料的LA-ICP-MS元素浓度 Dataset_S2.csv：陶瓷釉料的LA-ICP-MS元素浓度 data/supplementary/ Dataset_S3.csv：瓷器样品目录 Dataset_S4.csv：基于马氏距离的胎料样品组归属概率 Dataset_S5.csv：按爪类划分的元素浓度均值、标准差（SD）与相对标准偏差（RSD） run_all.R：主R脚本（可安装依赖项、处理数据、执行层次聚类分析（Hierarchical Cluster Analysis, HCA）与主成分分析（Principal Component Analysis, PCA），并生成图4至13与表1至2） README.md：项目概述、文件映射、使用说明与软件环境说明 可复现性与依赖要求： R版本≥4.4.0（下载地址：https://cran.r-project.org/） CRAN 依赖包：here、dplyr、tidyr、ggplot2、dendextend、tibble、factoextra、ggrepel、ggpubr、stringr 执行run_all.R即可安装所有所需依赖包，重新生成论文中的全部图表与表格，并将session_info.txt文件写入results/目录以留存完整运行溯源信息。