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Discovering the time of La Draga

AuthorsBogdanovic, I.; Andreaki, Vasiliki; Barceló-Álvarez, Juan Antonio; Piqué, Raquel ; Terradas-Batlle, Xavier ; Palomo, Antoni; Morera, Núria; López-Bultó, Oriol
KeywordsEarly Neolithic lacustrine
La Draga (Banyoles, Catalonia)
Phreatic zone of the site
Bayesian chronological model
Data of C14
Dendrochronological analysis
Chronometry Database
Chronological Inference Chain
Isotopic events
Archaeological events
Depositional events
Issue Date2019
PublisherJagiellonian University
Citation47th annual CAA. Computer Applications & Quantitative Methods in Archaeology CAA2019: " Check Object Integrity" : 186 (2019)
AbstractThe chronological position of the Early Neolithic lacustrine site La Draga (Banyoles, Catalonia) is defined by a series of C14 dates. The unbroken pattern of calibrated intervals suggests that the village was inhabited continuously from 5361-5223 cal BC to 5000-4796 cal BC. Two phases of the dwelling observed in clear stratigraphic relation in the phreatic zone of the site - where the preservation of the construction wood was excellent - are reflected in the graph without any apparent dividing gap. The extension of the site, its duration and low estimate of population suggest dynamic horizontal displacement of events and constructed spaces, with a certain cyclic tendency. Our aim in this paper is to present Bayesian chronological model of the inner time of La Draga and life cycles of its constructed places. For that purpose the data of C14 and dendrochronological analysis are formalized as required by Chronometry Database, following Chronological Inference Chain. The chain relates events on successive levels, from isotopic event (death of single organism) to archaeological event seen as a palimpsest of depositional events. Formalized correlation of archaeological units in the Harris Matrix enhanced by Allen Algebra and directed graphs provides necessary ordering of the data. The integration of these two methods is central for the interpretation of chronological sequence of events which take a place on the shore of Lake Banyoles, and is expected to advance in a ground data model for Bayesian time modeling.
Appears in Collections:(IMF) Comunicaciones congresos
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