Digital representations of the environment are being used in a wider spectrum of applications. Military units deploy to operational areas with a digital database of that area. This is one example of the many factors that have led the National Geospatial-Intelligence Agency (NGA, formerly NIMA) to adopt a new data production strategy focused on providing digital geospatial data in addition to traditional paper map and chart products. The NGA emphasis on digital geospatial data promises new opportunities for simulation database developers and users. Simulation systems already utilize large-scale, high-fidelity, geo-specific databases to execute joint experiments including urban area operations. Expanded availability of digital source data can only increase this trend; however, the new geospatial data production model, coupled with more rigorous demands and expectations from the operational community, results in continued tension between data quantity and data quality within a crisis-response production environment. Processes developed and refined to produce traditional maps and charts are not sufficient to meet the demands for multi-purpose digital geospatial data. This paper reports on results of research into identifying the data anomalies that may arise in such an environment and describes the development of automated tools that can be applied early in the production process to detect those anomalies.