Military Communications and Information Technology: A Trusted ...

Chapter 3: Information Technology for Interoperability and Decision...
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not support some of the libraries that were important in the process of ontology
application like e.g. Protégé OWL API. This library has an important plugin which
enables to generate java code form OWL classes which is useful while exploiting
ontologies at run-time.
Figure 5. Reasoning module interface to the Communication Module of ENS
In general, existing implementation of the reasoning engine performs a set
of operations on the ontology, e.g.:
• filling in the domain model with event descriptions,
• extending an ontology with SWRL rules,
• reasoning and classifying knowledge,
• querying an ontology about knowledge contained into the domain model
by using the queries described in Semantic Query-Enhanced Web Rule
Language (SQWRL).
The RM after being invoked creates an object of the OWLModel class on
the basis of event.owl ontology ; creates an object of the MyFactory class to
fill in the ontology with instances; creates an instance of Protégé Pellet Reasoner;
checks consistency of the created OWL model; classifies ontology; loads SWRL rules
and invokes Jess rule engine; creates an SQWRL queries and returns the response.
InsigmaEventOntology service implements Web Method called send-
EventDescription used to invoke reasoning engine. Event description is used
by the RM to infer knowledge. These are the following information (A-Box statements):
kind of event, injured person in the event and result of the event (see
example of simple SOAP request in Fig. 6).
For the reasoning purposes we decided to use Pellet reasoning engine. The reasoner
provides classification that compute complete class hierarchy, consistency
checking (checking possibility for a class to have any instances) and finding the most
specific classes that an individual belongs to.