Currently, sensor networks consist of isolated systems of sensors that communicate in different formats and are accessed by disparate and proprietary interfaces. These isolated networks are not interoperable; each isolated network of sensors or even each type of sensor within the network usually requires its own software for sensor asset management (i.e., sensor discovery, data retrieval, tasking, etc.). Furthermore, adding a new sensor type to a sensor network often requires significant integration of time and money. Since these isolated networks are usually controlled by different organizations with different operational requirements, it is often difficult or impossible for a user looking to capture and analyze particular types of sensor data on a global, national, state, or even smaller scale.

Sensor data, as with other intelligence, has even higher value when it can be fused with data from multiple sources. High-value sensor data often goes unexploited due to the failure of traditional information management systems to discover, manage, and relate this data. This failure, caused in part by the technological and organizational stovepipes that exist in today’s sensor networks, results in a gap between data and users’ ability to transform data into actionable knowledge.