of Maryland as well as through direct broadcast, provides critical information to manage emergency response to emerging and evolving fire threats.

It is clear that, for these classes of operational users, real-time, or near-real-time, processing is a critical factor in the utility of environmental satellite data. There is value in reducing system latency until, as a goal, a pixel of information appears on a user’s display as the corresponding detector is read out on orbit. As a philosophy, no system should be designed or implemented that unnecessarily adds latency into the end-to-end data stream. Here, the system level includes sensor tasking, processing, exploitation, and dissemination, including the time taken to command the acquisition of needed data, delays within sensor and satellite, buffering and delays in the satellite-to-ground downlink, delays in collection of all satellite and ancillary data at the processing centrals, the wall-clock time required to produce the end products, and the time required to notify the end users and deliver the valid products to their workstations.

Reduction of latency is an area ripe for exploitation in data system management. Current POES systems typically use infrequent contacts with polar ground stations or data relay satellites. This introduces one to two orbits (1 to 3 hours) of delay into the data acquisition even before the ground processing begins. The NPOESS implementation, termed “SafetyNet,” leverages the global presence of high-bandwidth fiber optic cable. Not only is the solution cheaper than today’s traditional approaches, but the globally distributed network of 15 receptors are also linked to processing centrals via commercial fiber to enable both low data latency and high data availability. Facilitated by the near-instantaneous and near-continuous data availability, ground processing executes efficiently, producing and delivering the first environmental satellite data products less than 4 minutes after they are sensed on orbit, completing more than 60 percent in 10 minutes, and 95 percent of the products in less than half an hour.

Transparency is critical and has several applicable definitions. In one context, the term “transparency” means that users are unaware of, and unconcerned with, the system supporting their data utilization. This includes transparent data interfaces efficiently handling the tasking, processing, storage, formatting, exploitation, delivery, visualization, and decision support systems. An example of transparency is dial tone when you pick up your telephone receiver; another is the link between a computer keyboard and the screen where the character you just typed is displayed. One gives no thought to the complex systems that connect your action to the response—unless they don’t work transparently. This simple concept has significant implications. Beyond simple latency, this implies a relentless focus on total customer