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Combining big data and thick data: scalar issues when integrating neutron activation and petrographic data as illustrated through a ceramic study from the southern US Southwest
Combining big data and thick data: scalar issues when integrating neutron activation and petrographic data as illustrated through a ceramic study from the southern US Southwest
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Combining big data and thick data: scalar issues when integrating neutron activation and petrographic data as illustrated through a ceramic study from the southern US Southwest
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Combining big data and thick data: scalar issues when integrating neutron activation and petrographic data as illustrated through a ceramic study from the southern US Southwest
Combining big data and thick data: scalar issues when integrating neutron activation and petrographic data as illustrated through a ceramic study from the southern US Southwest

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Combining big data and thick data: scalar issues when integrating neutron activation and petrographic data as illustrated through a ceramic study from the southern US Southwest
Combining big data and thick data: scalar issues when integrating neutron activation and petrographic data as illustrated through a ceramic study from the southern US Southwest
Journal Article

Combining big data and thick data: scalar issues when integrating neutron activation and petrographic data as illustrated through a ceramic study from the southern US Southwest

2022
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Overview
Recent theoretical approaches in archaeology have focused on “big data” that is the production of large and varied datasets reflective of advances in scientific methods and data science. While such data are now more common, the need for “thick data”, qualitative and contextual information, has also become significant. Particularly for ceramic research where big data from neutron activation analysis is combined with thick data from petrography, the juxtaposition has revealed issues of interpretation. Through a regional case study of painted ware and unpainted utility ware from AD 1200 to 1450 settlements in southern Arizona and southwestern New Mexico, three areas of concern were identified. These centered around issues of scale: (1) number of samples (sometimes in the thousands); (2) geographic area (often necessarily extensive); and (3) organization of production (potters can be centralized and/or dispersed on the landscape). Interestingly, only the combined datasets reveal these issues, which highlights why they work well together and are necessary for more accurate explanations. Once the specifics of the disjunction between compositional “big data” interpretations and those arrived at through petrographic thick data are accounted for, a more contextual approach can be taken in reconstructing past behavior.