Design of an ontological knowledge structure for a query language for multiple data sources

In a command and control system which uses different kinds of sensors attached to various platforms, it is important to know which sensor data to use and which recognition algorithm to apply to that data when searching for a certain object type in a certain area at a certain point or interval in time. In this work an ontological knowledge structure, implemented as a knowledge base, is used to model apriori knowledge about the objects of interest, the sensors, the sensor platforms, the recognition algorithms used for searching in the sensor data, as well as external conditions. All these aspects have an impact on which sensor and algorithm is the most appropriate to use. A rule manager has been implemented. It is used for editing the rules describing how the sensors and algorithms are affected by the different conditions. Also implemented is an algorithm that uses the ontological knowledge base and the rules created in the rule manager for making actual decisions on which sensors and algorithms are the most appropriate given a complete set of input parameters (e.g. object to search for, area of interest, timestamp, existing conditions, etc).