ArcheoFOSS 2022
Linking stratigraphy, context and interpretation: a starting proposal

Panel: Archaeological stratigraphy data.

In the graph theory, a graph is a structure consisting in «a set of points called vertices or nodes and a set of lines called edges such that each edge is attached to a vertex at each end». Graphs are powerful tools used for numerous purposes. Specifically, in archaeology, the most widely known application is undoubtedly the Harris’ Matrix, a relatively simple method to organise stratigraphy by relative chronology. Other less common applications include, for instance, network graphs, mainly used to represent exchange routes through different settlements, and directed graphs, that can be applied in order to analyse directions and connections through different spaces inside buildings. All these domains of use have been strongly influenced by other disciplines, among which the social network analysis (SNA), originally developed for sociological studies, plays the most prominent role.

The Extended Matrix is so far the most recent attempt to overcome the limits of the standard stratigraphical representation: the concept of the stratigraphical virtual unit, constituting a standardized interpretation of an archeological record, follows precise conceptual rules. As previously happened to the social network analysis with other kinds of graphs in archaeology, it is possible to go further and take inspiration from the landscape graphs developed in ecology, hence adding further layers to the Extended Matrix so as to link stratigraphy, context and interpretation. The present work aims to account for the basic theory underlying this approach and suggest a possible solution to the problem of linking stratigraphical data and interpretation using the Extended Matrix graph. An example will be also provided to highlight the steps involving the integration of sources, archaeological data and hypothesis making in the general workflow.

License

Texts and image are released under CC BY-ND 4.0 International license. Copyright: Alessio Paonessa, 2022