Authors:
Stephen Batiuk
1
;
Tim Harrison
1
;
Lynn Welton
2
;
Darren Joblonkay
1
and
Lemonia Ragia
3
Affiliations:
1
University of Toronto, Canada
;
2
University of Chicago, United States
;
3
The University of Chicago, Switzerland
Keyword(s):
Data Mining, Archaeological Database, Data Analysis, Spatial Analysis, Information Retrieval, Simulation Modelling.
Abstract:
Archaeology has emerged as one of the most dynamic and innovative disciplines in the humanities and social
sciences, employing a truly interdisciplinary, collaborative approach and a continually expanding array of
analytical research tools. Computer aided analysis of archaeological data is remarkably challenging given the
heterogeneous nature of the material. Archaeologists generally aim to discover patterns, spatial relationships
and other associations between different traits of the archaeological record. However, given the idiosyncratic
and highly personal nature in which archaeological data is collected and analyzed, identifying these patterns
and relationships offers many challenges. The Computational Research on the Ancient Near East (CRANE)
initiative seeks to build an international multidisciplinary research collaboration, comprised of archaeologists,
computer scientists, and paleo-environmental specialists, with the capacity to leverage a burgeoning corpus
of data f
rom a number of archaeological sites and fundamentally transform our knowledge of the civilizations
of the ancient Middle East. The CRANE initiative is developing a sustainable, scalable, user-driven vehicle
for large-scale data management and cross-project data integration, to harness the full evidentiary range
produced by this uniquely rich cultural legacy. At the same time we are developing tools for data mining
techniques, and to analyze simulate ancient societies using agent-based models of behavior.
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