Inference from absence : addressing archaeological negative data through spatial analysis and topographical studies

Abstract

The concepts of hidden landscapes, site formation processes, together with inference from absence will be assessed to understand archaeological negative data i.e. sites which did not yield archaeological discoveries in an area where remains are abundant. Since the introduction of regulated archaeological monitoring in 1997, development-led archaeology has been on an exponential rise. An area which has a considerable number of archaeological discoveries and development-led monitoring cases was selected since such areas presented the most significant data for analysis. For this reason, the Area of Archaeological Importance (AAI) of Rabat, Malta was chosen as the area of study with specific areas within the AAI being selected for the in depth-analysis. Given that Rabat’s uninterrupted human occupation dates back to the Bronze Age, its cultural landscape is mostly hidden. Site formation processes are key to the understanding of the past societies, cultures, and norms. The aim of this study is to derive data from known archaeological sites including discoveries from rescue excavations and undergoing development-driven archaeological monitoring of sites to identify spaces which yielded negative data, i.e., sites where no archaeology was discovered. Various reasons may be attributed to archaeological negative results, including loss from continuous use of the site, war damage, quarrying activities (from ancient times up to the last 30 years) and excavation biases or selected documentation practices. The concept of archaeological negative data derived from archaeological excavations, as discussed by Wallach (2019), will be tested and thoroughly analysed in this research using examples from Rabat. GIS1 will be essential to map out archaeological sites of different typologies and date of discovery, the negative variable and other tools to carry out the analysis. This data, correlated with the topography using GIS to establish a predictive model which will inform on the location and nature of any archaeological discovery. Part of the research will also include analysing the operating parameters whereby heritage managers decide on monitoring the development-led sites and suggesting possible guidelines for this process.