IOSA.it Open Archaeology

The latest issue of “Archeologia e Calcolatori” has an interesting paper by Mike Baxter and Hilary Cool about the statistical analysis of some loomweights from Pompeii (the paper is available from the OAI repository of the journal) Besides being an interesting example of how clever data analysis of

apparently mundane items can provide useful information about the people who made and used them if analysed appropriately

the paper has an extended appendix about the computational details of their study.
They start by stating that

Quote from the last page of the recent article On statistical approaches to the study of ceramic artefacts using geochemical and petrographic data by Baxter MJ, Beardah CC, Papageorgiou I, Cau MA, Day PM, Kilikoglou V appeared on «Archaeometry» 2008 February;50(1):142-157. Available from: http://dx.doi.org/10.1111/j.1475-4754.2007.00359.x .

These pages on the website of prof. Juan A. Barceló deal in detail with some of the hot topics in archaeological computing, like

• Artificial Intelligence and Neural Networks used to analyze archaeological datasets
• Statistical methods
• Spatial Analysis techniques to be performed within GIS
• and more

Content is available both in Catalá and English and can be useful to give students a complete and exhaustive overview of some of the most advanced techniques that can be used to improve and speed up archeological research.

The R environment is very powerful for analysis purposes. Despite the fact it has almost no graphical interface, its capabilities at producing high quality graphical output are probably even more than you will ever need.
Archaeologists willing to deal with quantitative methods for analyzing their data and drawing inferences from samples, will find that R is their best companion if they're going to take the time to learn some of the basics.
Let's start with some galleries that help us understanding what we can achieve with R:

This tutorial covers the basics of the R environment for the Windows platform with figures that help the R newbie. 

This collection of web pages is intended to be a guide to some of the resources for the analysis of spatial data using R, and other associated software. Another useful resource is the CRAN Spatial Task View.It includes packages like spBayes, an R package for hierarchical spatial modelling, rgdal and spgrass6, which are meant to manage spatial information using the most powerful open source tools. There is a mailing list, that of the R-sig-geo.

GGobi is an open source visualization program for exploring high-dimensional data. It provides highly dynamic and interactive graphics such as tours, as well as familiar graphics such as the scatterplot, barchart and parallel coordinates plots. Plots are interactive and linked with brushing and identification. It is based on the previous XGobi, and has a nice GUI developed with GTK. GGobi can:

• Draw dotplots and scatterplots, barcharts, spineplots and histograms, parallel coordinate plots, scatterplot matrices
• Link data points and lines between plots using persistent or transient brushing, and identification
• Pan and zoom
• Rotate data in 3D, and tour high-dimensional data using sequences of 1D, 2D and 2x1D projections augmented by manual control and automatic projection pursuit guidance
• Acts as a high-dimensional drawing tool, by adding, moving, and drawing lines between points.
• Connects with R