Session: #723

Session, made up of a combination of papers, max. 15 minutes each

Buzzwords like Big Data and modelling, derived from the so-called 'third science revolution in archaeology', currently transform the theory and practice of archaeological research into something more abstract and subjective to the researcher. However, the mere presence of a large amount of data and the collection alone is not a scientific result, whereas digital data and methods are one answer to the question of how transparency can be achieved. This is the point at which quantitative methods come into play. Research environments such as R, Python and other structured open source evaluation methods offer the possibility to recreate processes by documentation to enable Reproducible Research and Open Science. Our session is intended to provide a forum for contributions dealing with methods for managing the increasing flood of data and their transparent transfer into an archaeological interpretation. We would like to encourage potential presenters to demonstrate their individual case studies, methodological approaches and especially Reproducible Research and its application all across the different archaeologies and its many adjacent disciplines. The talk should also reflect on the difficulties their approach presents while using the tools of the ‘Third Science Revolution’. Presentations concerning practical solutions such as software are particularly welcome - whether they are finished products, beta stages or conceptual designs.

QuantitativeMethods; BigData; DataManagement; Interpretation

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M.A. Nicole Grunert (Germany) ^1,2,3

PhD Student Archaeology Clara Filet (France) ^4,3
Carolin Tietze (Germany) ⁵