An Ontological Approach for Querying Distributed Heterogeneous Information Systems Under Critical Operational Environments

In this paper, we propose an information exchange framework suited for operating in time-critical environments where diverse heterogeneous sources may be involved. We utilize a request-response type of communication in order to eliminate the need for local collection of distributed information. We then introduce an ontological knowledge representation with a semantic reasoner that operates on an aggregated view of the knowledge sources to generate a response and a semantic proof. A prototype of the system is demonstrated in two example emergency health care scenarios, where there is low tolerance for inaccuracy and the use of diverse sources is required, not all of which may be known to the individual generating the request. The system is contrasted with conventional machine learning approaches and existing work in semantic data mining (used to infer knowledge in order to provide responses), and is shown to o er theoretical and practical advantages over these conventional techniques.