OraGIS and Loom: Spatial and temporal extensions to the ORA Analysis Platform

Increasingly, data available to network analysts includes not only relationships between actors but measurements of entity attributes and relations through time and space. Integrating this information with existing dynamic network analysis techniques demands new models and tools. This paper introduces two extensions to the ORA dynamic network analysis platform intended to meet this need. The first, OraGIS, provides geospatial visualization and clustering algorithms. The second, Loom, assists in the analysis of agent movements through a discrete state space (such as a set of named locations) over time. We discuss the capabilities of both tools and their integration with the traditional analytics in the ORA platform. This work was supported in part by the National Science Foundation under the IGERT program (DGE9972762) for training and research in CASOS, and the Office of Naval Research under Dynamic Network Analysis program (N00014-02-1-0973, ONR N00014-06-1-0921, ONR N00014-06-1-0104). Additional support was provided by CASOS the Center for Computational Analysis of Social and Organizational Systems at Carnegie Mellon University.