Big Data and Early Archives (Big-DEA). Measuring Settlement Dynamics and Environmental Exploitation in the Ebla Region during the 3rd Millennium BC: Archaeological Record, Cuneiform Texts, and Remote Sensing

The Big-DEA project aims at developing a comprehensive multi-level explanatory model for the development of an archaic State during the 3rd mill. BC in the Near East. The project focuses on the reconstruction of the archaic state of Ebla through an integrated analysis of archaeological and epigraphic data. A multidisciplinary approach is adopted in order to build a multi-tier explanatory model for the territory under the control of Ebla around the mid-3rd mill. BC, taking into account anthropic and environmental data deriving from previously conducted excavations and surveys and from newly analyzed textual sources. The way to managing and study such a large Big Data repository, encompassing different datasets, is in itself one of the main challenges of the project: the creation of a relational database management system (RDBMS) functional to the implementation of the available GIS platform and the development of an appropriate simulation framework. The extraordinary source of information from the State Archives of Tell Mardikh/Ebla, the large amount of archaeological and environmental data (Big Data) available from its surrounding territory make Ebla a unique case to test the rise and the collapse of a vast kingdom of the Early Bronze Age. The Big-DEA project is therefore based on a quantitative approach, where all the information from each Research Unit will be stored in appropriate geodatabases and then analyzed in order to create clusters of distribution and statistical patterns. The work capitalizes on the results of the ERC-funded Ebla Chora Project (2010-2014), which made possible a first assessment of the archaeological landscape of Early Syrian Ebla. On the one hand, the updated chronological seriation of the sites in the territory around Ebla will provide a clear picture of the settlement patterns coeval to the State Archives (2350-2300 BC). The spatial analyses carried out on the archaeological landscape will result in a better defined human-environment interaction, with a specific attention to the exploitation of resources and land use according to the ecological features shaping this region (basalt, limestone, water depression, foothills, marshes, and semi-arid steppe). On the other hand, all information concerning products and goods and available in the cuneiform documents will be quantified in the RDBMS. Each entry will be considered according to its provenience and its amount. The Big-DEA project is based on the close interaction between four Research Units (RUs): Milan (PI), for archaeology; Bologna for information science application and remote sensing; Florence and Rome for epigraphy. During the first phase the methodological framework is designed and the relational database management system (RDBMS) for the data entry is developed together with the implementation of the GIS platform and development of the statistical-computational framework for managing Big Data (RU Bologna). Data entry into the RDBMS of the archaeological (RU Milan) and textual (RUs Florence and Rome) record from the site of Ebla, especially the Royal Palace G, as well as Remote Sensing analysis, thematic classification, multivariate, geostatistical and spatial analyses on the EB settlement patterns of the Ebla territory (RUs Milan and Bologna) will be performed. Integration of the datasets from the single RUs into the simulation framework in order to test a general model for the Eblaite socio-economic structures and their quantitative impact on the political center and its territory will represent the final stage (all RUs), focusing on spatial organization and diachronic variables from local to regional scales. Big-DEA represents the first systematic and integrated attempt at creating a simulation framework aimed at reconstructing the economic landscape of an ancient Near Eastern capital and its region in the 3rd mill. BC. Regular project meetings will evaluate the advances of the RUs engaged into the project and their appropriate inter