Filling the Gaps—Computational Approaches to Incomplete Archaeological Networks

Abstract

Networks are increasingly used to describe and analyse complex archaeological data in terms of nodes (archaeological sites or places) and edges (representing relationships or connections between each pair of nodes). Network analysis can then be applied to express local and global properties of the system, including structure (e.g. modularity) or connectivity. However, the usually high amount of missing data in archaeology and the uncertainty they cause make it difficult to obtain meaningful and robust results from the statistical methods utilised in the field of network analysis. Hence, we present in this paper manual and computational methods to (1) fill gaps in the settlement record and (2) reconstruct an ancient route system to retrieve a network that is as complete as possible. Our study focuses on the sites and routes, so-called hollow ways, in the Khabur Valley, Mesopotamia, during the Bronze and Iron Age as one of the most intensively surveyed areas worldwide. We were able to predict additional sites that were missing from the record as well as develop an innovative hybrid approach to complement the partly preserved hollow way system by integrating a manual and computational procedure. The set of methods we used can be adapted to significantly enhance the description of many other cases, and with appropriate extensions successfully tackle almost any archaeological region.