About

CyberSW is a cyberinfrastructure and collaborative space for conducting interdisciplinary research on and exploring the pre-Hispanic archaeological record of the US Southwest and Northwest Mexico. The goal of cyberSW is to engage not just archaeologists, but scholars from other disciplines, interested parties from federal, state, and tribal entities as well as the general public. CyberSW is a living database that has a fulltime database manager (Joshua Watts) and developer (Andre Takagi), and will be updated, revised, and expanded on a regular basis. The Neo4j graph database platform utilized by cyberSW is very flexible and can accommodate new classes of data and analyses. We encourage users to provide suggestions on what they would like to see.

Figure 1 - CyberSW team research meeting in January 2019.

CyberSW 1.0, the current version, is a powerful tool for reconstructing demography and social networks using ceramic, sourced flaked stone, public architecture, and site size data collected from residential sites, with a focus on the late pre-Hispanic period (1200-1450 C.E.) and, for the Chaco World, back to 800 C.E. CyberSW 1.0 is also a powerful exploratory tool for viewing the distribution of ceramic wares and types, geochemically sourced obsidian, and public architecture across the Southwest. The graph database platform facilitates both network analysis and the ingestion of complex, non-matched archaeological data. The development of cyberSW is funded by a collaborative National Science Foundation grant (Resource Implementations for Data Intensive Research program) between the University of Arizona (PIs Barbara Mills and Sudha Ram), Archaeology Southwest (PI Jeffery Clark), Arizona State University (PI Matthew Peeples), and University of Colorado at Boulder (PI Scott Ortman) (Figure1).

While adding a large amount of new information, CyberSW 1.0 builds upon three previous National Science Foundation grants that focused on reconstructing pre-Hispanic demography and social networks in the Southwest (Coalescent Communities, Southwest Social Networks, Chaco Social Networks). Information on these projects can be found at https://www.southwestsocialnetworks.net/. At this stage much of the CRM and academic literature for the late pre-Hispanic Period and Chaco World have been aggregated and systematized in a single research database. The combined efforts of these projects allow users to explore and analyze over 13.7 million ceramics, 350,000 flaked stone artifacts (including 10,000 sourced obsidian specimens), and 2,000 public architectural features from more than 25,000 settlements with a few keystrokes (Figure 2).

Figure 2 - CyberSW sites and ceramic data compilation by project.
  • Black: Coalescent Communities
  • Blue: Southwest Social Networks
  • Yellow: Chaco Social Networks
  • Red: cyberSW

The current functions of cyberSW 1.0 fall into three general categories: (1) exploration of the distribution of ceramics (ware/type), obsidian (source), and public architecture (type) down to the site level; (2) an exportable record for each site in the database that contains the citation and both the original data and our aggregated data classes for ceramics, obsidian, and public architecture; and (3) an analytical toolkit that includes the Brainerd-Robinson similarity coefficient, Euclidean distance, Morisita’s overlap index, and a Uniform Probability Density analysis chronological tool developed by Ortman. The chronological tool provides a date range for each site as well as the ability to divide ceramic assemblages from multi-component sites into 50-year time intervals.

Ultimately, we plan to ingest all pre-Hispanic archaeological and environmental data into cyberSW with resolution at the scale of individual rooms/features and strata within settlements. We also plan to include data from non-residential sites (e.g., rock art sites). A tool that dates and chronologically groups features and strata across sites is also planned.

Anyone can use the database free of charge after registering and accepting a user agreement. Sensitive site location data is geo-masked to varying degrees based on user level access.