An extension of the method that was used for building and using the network-based knowledge system SUPER is proposed to fully utilize the benefits of this approach in the domain of diagnosing distributed dynamically evolving processes. In the scope of distributed sensor networks, several issues are addressed concerning problems dealing with software architectures, strategies, and properties for efficient sensor data management: (1) how to build links efficiently between the elements of each network-based knowledge base, (2) how to maintain consistency of the whole structure and manage the constraints of domain dependent variables corresponding to sensor data, (3) how to manage and update efficiently the database at run time in order to maintain its consistency and to satisfy a high level of response time performances, and (4) how to propagate the solutions given by a qualitative knowledge base into a knowledge base utilizing sensor data whenever the sensors are out of order. The answers given are based on extending and generalizing the principles that have been defined for SUPER.