Research into ceramic production and exchange in past societies has led to wide-ranging understanding of social, economic, and political organization in these ancient systems as well as implications for contemporary societies. Much of this work has utilized chemical analysis of ceramics using neutron activation analysis (NAA) and the American Southwest has been one area of intensive research. Existing NAA data represent significant research investment, but the combined power of this investment remains unrealized largely due to two impediments: 1) existing databases require synthesis and standardization; and 2) analytical methods that can systematically compare compositional data at these macroregional scales needs more development. This project produces a standardized, expanded, and broadly accessible database of more than 30,000 ceramic compositional analyses that will allow new big-data approaches (AI and machine learning) to large-scale interactions. The resulting databases are updated and readily available for a broad range of future research. Recent developments in artificial intelligence and machine learning allow exploration of large-scale multivariate data at scales that facilitate the exploration of regional-scale interaction. This project develops new methods for analyzing NAA data using social network analysis (SNA) tools that allow one to evaluate models and expectations derived from social network theory using findings of past networks based on typological si