Exploratory Network Reconstruction with Sparse Archaeological Data and XTENT

Abstract

This contribution discusses methods for reconstructing the links of past physical networks, based on archaeological site locations and mathematical models of few parameters. Networks are ubiquitous features of human culture. They structure the geographical patterning of the archaeological record strongly. But while material evidence of networked social interaction is abundant (e.g. similarities in artefact types and technologies), preserved physical remains of the networks (such as roads) are much rarer, making it difficult, if not impossible, to understand the spatial structure of cultural exchange and diffusion. This raises the intractably complex problem of optimal physical network reconstruction, based solely on the known locations of archaeological finds or sites. We address the tractable subproblem of plausible reconstruction of network links. Using a small sample set of Late Bronze Age settlement sites in and around the Mediterranean, we explore model-based network reconstruction from sparse and legacy archaeological data. A hierarchical model is provided by a network-adapted version of Renfrew and Level’s (1979) classic XTENT formula. We show that a GIS-based implementation, that utilises cost surfaces, offers significantly increased realism and analytical advantages. Our approach represents an alternative (with its specific strengths and weaknesses) to more data-intense and computationally complex approaches, such as agent-based models and simulations. The network reconstruction software used in this study (v.net.models) is available under an open source license.

Bronze Age communication and trade networks from Mediterranean Ivory records

“…We employ computational modelling and Least Cost Path (LCP) analysis to understand supraregional dissemination patterns of ivory across the Bronze Age Mediterranean Basin. Furthermore, we use the recently developed network v.net.model algorithm by Ducke and Suchowska (2022) that is implemented in GRASS GIS 7 (Geographic Resources Analysis Support System, GRASS Development Team 2017) to simulate land-based and sea-based distribution graphs. Together with the site database, we present a fully replicable computational model (Marwick 2017) that adds environmental conditions into the network of material distribution to explain potential movement and transportation corridors as well as predict potential site locations across Northern Africa, the Iberian Peninsula, and Italy.…”