Compositional Data Analysis

Provenance studies rely on the identification of probable sources, such that the variability between two sources is greater than the internal variability of a single source (the so-called, provenance postulate). This assumes that a unique signature can be identified for each source on the basis of several criteria.

This application is designed for chemical fingerprinting and source tracking of ancient materials. It provides provides tools for the exploration, visualization and analysis of compositional data in the framework of Aitchison (1986). If you are unfamiliar with the concepts and challenges of compositional data analysis, the following publications are a good place to start:

  • Egozcue, J. J., Gozzi, C., Buccianti, A. & Pawlowsky-Glahn, V. (2024). Exploring Geochemical Data Using Compositional Techniques: A Practical Guide. Journal of Geochemical Exploration, 258: 107385. DOI: 10.1016/j.gexplo.2024.107385.
  • Greenacre, M. & Wood, J. R. (2024). A Comprehensive Workflow for Compositional Data Analysis in Archaeometry, with Code in R. Archaeological and Anthropological Science, 16: 171. DOI: 10.1007/s12520-024-02070-w
  • Grunsky, E., Greenacre, M. & Kjarsgaard, B. (2024). GeoCoDA: Recognizing and Validating Structural Processes in Geochemical Data. A Workflow on Compositional Data Analysis in Lithogeochemistry. Applied Computing and Geosciences, 22: 100149. DOI: 10.1016/j.acags.2023.100149.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY.

If you use this application in your research, you must report and cite it properly to ensure transparency of your results. Moreover, authors and maintainers of this project are more likely to continue their work if they see that it's being used and valued by the research community.

To cite in your publications, please use:

Frerebeau N (2024). “The tesselle Project: a Collection of R Packages for Research and Teaching in Archaeology.” Advances in Archaeological Practice. doi:10.1017/aap.2024.10 https://doi.org/10.1017/aap.2024.10.

Frerebeau N, Philippe A (2025). nexus: Sourcing Archaeological Materials by Chemical Composition. Université Bordeaux Montaigne, Pessac, France. doi:10.5281/zenodo.10225630 https://doi.org/10.5281/zenodo.10225630, R package version 0.4.0, https://packages.tesselle.org/nexus/.

You can save the state of the application and get a URL which will restore the application with that state. You can then copy the URL and save it for later, or share it with others so they can visit the application in the bookmarked state.

This is not intended for long-term storage. There is no guarantee as to how long your bookmark will last.

Bookmarking is currently disabled.

Dimensions

Sparsity

Missing values

Export your data for futur use. Download
Multivariate statistics
Barplot
Visualize your data in the ternary space. Click and drag to select an area, then double-click to zoom in. Double-click again to reset the zoom.
Ternary plot
Density
Density
Density
Density
Click and drag to select an area, then double-click to zoom in. Double-click again to reset the zoom.
Individuals factor map
Variables factor map
Screeplot
Dendrogram