Preparing data for use in models and simulations is a process that often consumes a significant amount of resources and has significant schedule impacts during the preparation for events enabled by modeling and simulation (M&S). The processes for data preparation vary widely across organizations and activities, with many individual simulations and federations creating unique processes and semi-automated solutions for database generation. For M&S application, data is typically drawn from multiple sources and integrated to form a common scenario-based data initialization baseline. Database generation is required for many types of data including natural and manmade environments, unit and electronic order of battle, logistics, and command and control information. Effective reuse of data across M&S environments and organizations is severely lacking.

The US Department of Defense (DoD) M&S Steering Committee has established a Rapid Data Generation (RDG) project to reduce the time required to discover, integrate, and correlate M&S data and promote data sharing through common metadata and services. The RDG project is leveraging multiple past and current efforts that address data generation. The RDG project is in its first year of implementation, focusing on establishing a common architecture and demonstrating data reuse across multiple communities. Eventually, RDG will span the full breadth of communities employing M&S including training, planning, testing, analysis, experimentation, intelligence, and acquisition. This paper will describe the background that led to the establishment of the RDG project, the elements of the RDG project, and the concept of operations for an M&S Common Data Production Environment. We will discuss the service oriented architecture-based approach to data discovery and access and the use of common metadata, which will result in a common set of data services to support the M&S user community and the reuse of data across M&S environments.