Data & R Script for “Blurred Boundaries: Exploring the Complexity of the Production System at the Luomaqiao Kiln in Yuan-Dynasty Jingdezhen”
Description
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.
Files
Steps to reproduce
1. Download this repository so that your project folder contains: - run_all.R - data/raw/ with Dataset_S1.csv–Dataset_S2.csv - data/supplementary/ Dataset_S3.csv–Dataset_S5.csv 2. Open RStudio or an R console. Make sure you have R ≥ 4.4.0 installed. You do not need to install any packages beforehand—run_all.R will install any that are missing. 3. Set your working directory to the project folder: - In RStudio: Session → Set Working Directory → To Source File Location - In any R console: setwd("C:/path/to/your/project") 4. Run the master script: - In RStudio: open run_all.R and click the Source button (or press Ctrl + Shift + S) - In the R console: type source("run_all.R") and press Enter 5. When the script finishes, all figures (Fig04–Fig13), summary tables (Table1 & Table2), and session_info.txt will be in the results/ folder.
Institutions
- Xiamen University