Taphonomic Analysis with Multisite Big Data in the Central Mesa Verde Region

Summary

This is an abstract from the "Interdisciplinary Approaches in Zooarchaeology: Addressing Big Questions with Ancient Animals" session, at the 89th annual meeting of the Society for American Archaeology.

Understanding taphonomic patterns across large spatial scales can greatly enhance archaeological interpretation. However, standardized data curation across many sites is a significant challenge. Thus, opportunities for taphonomic analyses that employ big multisite datasets are rare. Data curation practices in archaeology are often different from those in other data rich sciences—such as software engineering and bioinformatics—where documentation with open source software and the programmatic integration of basic tasks are commonplace. In addition, archaeology may have restrictions in data sharing related to culturally sensitive information. With improved curation, data analytics approaches enable archaeologists to tackle large challenges, such as multisite taphonomic analyses in rapid, efficient, and powerful ways. Crow Canyon Archaeological Center has systematically curated data from projects in a universal database for decades. In the 1990s, this information was incorporated into a relational database, which is currently managed using PostgresSQL and networked for real time analyses with R. Faunal analysis protocols were also explicitly designed with data quality standards during database construction. Faunal and taphonomic data from approximately 130,000 specimens across 50 archaeological sites are curated. We showcase how these data aid the interpretation of region-wide taphonomic patterns bolstered by data science practices.

Cite this Record

Taphonomic Analysis with Multisite Big Data in the Central Mesa Verde Region. Steve Wolverton, Jonathan Dombrosky, Lisa Nagaoka, Susan Ryan. Presented at The 89th Annual Meeting of the Society for American Archaeology. 2024 ( tDAR id: 497517)

Spatial Coverage

min long: -124.365; min lat: 25.958 ; max long: -93.428; max lat: 41.902 ;

Record Identifiers

Abstract Id(s): 38015.0