Representing the movement and other behaviors of large numbers of human inhabitants in a geo-typical fashion within an area of interest provides a way to enhance the realism of a simulation exercise scenario. It also establishes a baseline against which an analyst may make comparisons of behavior to support conclusions of intent, based on departures from the baseline. This capability can be used in simulations in both training and experimental scenarios where close contact with a local noncombatant population is expected. We describe a data model that includes the information needed to characterize a set of signatures attributable to a local population, and that does so in a way that lends itself to discovery using automatic or interactive means. This latter aspect of discoverability is important given the rapidly increasing universe of network-accessible, searchable data, and the broad set of distinguishable population groups that military forces may interact with. The model also includes parameters governing the population's inclination to be forthcoming with information during engagements with military forces within the area of interest. This inclination may be affected positively or negatively by behaviors of the occupying forces, and has implications with respect to the efforts that are required to establish meaningful relations between groups. This allows a unit commander (in a training setting) or an analyst (in an experimental setting) to estimate the return on investment of committing resources to attempt to align a local population more closely with military objectives.