Next Generation 9-1-1 (NG 9-1-1) will revolutionize how the public accesses emergency services and will alter the technological landscape within which existing public safety agencies operate. A lack of systematic methodologies exists for quality control of the required geospatial data layers for NG 9-1-1 systems. The primary objective of this study was to develop and systematize a highly accurate NG 9-1-1 GIS database for Counties of Southern Illinois (CSI). The project goals included mapping relevant geospatial data layers required by and based on NENA standard data formats; conducting data quality control and standardization; and providing standardized spatial datasets for NG 9-1-1 to relevant stakeholders. The approach was developed using a conceptual model for error and uncertainty analysis of the GIS-based NG 9-1-1 system. This included the identification of various sources of input uncertainties often associated with spatial data layers; modeling the accumulation and propagation of errors; analyzing their impact on the quality of the spatial data layers; and correcting the errors. Modeling uncertainty propagation focused on positional errors and was conducted through a simulation procedure. The results showed that the original spatial datasets possessed a large account of uncertainties, especially location errors of railroads and roads. The errors had different sources, including input map errors, the use of different map projection and coordinate systems, a lack of topological structures, etc. In addition, they varied from county to county. From the error propagation simulation, it was also found that the location errors measured as root mean square error (RMSE) fluctuated when the perturbed distance of the ground control points (GCP) was less than 15 m. After that, the RMSE increased as the perturbed distance of GCPs increased. This relationship was significantly linear. In addition, the location errors from railroads were larger than those from roads.