Introducing SourceXplorer, an open-source statistical tool for guided lithic sourcing

Abstract

Archaeologists' access to analytical infrastructure has grown exponentially over the last two decades. This is especially the case for benchtop X-ray fluorescence (XRF) and portable XRF (pXRF) instruments, which are now practically commonplace in archaeological laboratories and provide users with a non-destructive and rapid means to analyze the elemental compositions of archaeological specimens. As XRF has become more accessible, the volume of analytical measurements available in archaeological datasets as well as the number and diversity of researchers participating in data collection have inherently increased. Those researchers, who have various levels of experience with the nuances of lithic sourcing procedures, are also often the ones attempting to interpret the elemental data they produce. While standardized analytical procedures have enabled inexperienced analysts to take accurate and reproducible XRF measurements, interpreting the resulting data is more difficult to convert and standardize with the same degree of user-friendliness. To address this challenge, we have bundled a series of statistical approaches and data exploration tools into an intuitive open-source graphical user interface designed to facilitate reproducible and robust outcomes during lithic sourcing studies. Our application, SourceXplorer, permits easy access to and exploration of numeric baseline data using a map interface while facilitating a guided interpretation of source affiliations for archaeological specimens (e.g., lithics) within any natural context using multivariate statistical analyses. We demonstrate SourceXplorer's functionality in relation to a complex archaeological challenge by examining evidence for the procurement and use of lithic material from previously undocumented toolstone source locations in southwestern British Columbia, Canada. We also provide open access to SourceXplorer, including both a deployed version of the application that can be used with any Internet browser and the packaged script, which can be run locally in the open-source R statistical programming environment.