Transforming Legacy Spatial Data into Testable Hypotheses about Socioeconomic Organization. Issue 1 (February 2020)

• Record Type: Journal Article
• Authors: Quinn, Colin P.; Fivenson, Daniel
• Is Part Of: Advances in archaeological practice. Volume 8:Issue 1(2020)
• Page Start: 65
• Page End: 77
• Publication Date: 2020-02
• Subjects: archaeological survey, -- Bronze Age, -- GIS, -- institutionalized inequality, -- least-cost path analysis, -- legacy data, -- network analysis, -- settlement systems, -- Transylvania; prospección arqueológica, -- Edad del Bronce, -- SIG, -- desigualdades, -- análisis de rutas óptimas, -- datos heredados, -- análisis de redes, -- sistemas regionales de asentamiento, -- Transilvania; Archaeology -- Methodology -- Periodicals; Archaeology -- Technological innovations -- Periodicals; Archaeology -- Periodicals; Electronic journals; Periodicals; 930.1028
• DOI: 10.1017/aap.2019.37
• Languages: English
• ISSNs: 2326-3768

Abstract

ABSTRACT: As archaeologists expand the accessibility of legacy data, they have an opportunity to use these datasets to design future research. We argue that legacy data can be a critical resource to help predict characteristics of sites and socioeconomic systems. In this article, we present a combined geographic information system (GIS) and network analysis methodology that turns site location data into testable hypotheses about site characteristics and the organization of regional settlement systems. We demonstrate the utility of this approach with a case study: Bronze Age (2700–1100 BC) settlement patterns in the mining region of Hunedoara in southwest Transylvania, Romania. We leverage unsystematically collected site location information in legacy datasets to develop testable predictions about sites, regional networks, and socioeconomic systems that can be evaluated through future systematic surveys and large-scale excavations. Such testable hypotheses can inform archaeological research design by providing a quantitative basis for determining where to focus research efforts and can also help secure funding and fieldwork permits. The method developed here can be applied in diverse archaeological contexts to reinvigorate legacy data as part of future archaeological research design.