| Ontology based on description logics is a kind of knowledge representation language and the ontology layer has been mature in the semantic web structure with the ontology language OWL becoming the standard of W3C, however there are variety of application problems in the ontology engineering with the increasing practical applications, such as it is not easy to maintain and use large ontology and the time is needed in the semantic web, but it is not effectively to solve these problems by only ontology. Rule is another important kind of knowledge representation, and combining the ontology and rules can make up for each other's ability of expression. Datalog rule and ontology share the same logical basis, and there are technologies which can support the combination of both, however thre are lots of semantic differences between ontology and non-monotonic rules (answer set programming), effective combination of both in the semantic level is a key to the development of semantic web. In this dissertation, we contribute the following research works:(1) Modularization based on the ontology and Datalog rule is introduced to logistic ontology to solve the problem of the maintainability and usability of large logistic ontology. The definition of ontology module and the division principles for the logistic problem domain are proposed, and then rule and procedures are defined to link the ontology modules to represent knowledge in different context. Considering that inconsistency may occur during linking the modules, constraints are used to guarantee the accuracy of links between modules. With the method proposed in this dissertation,the logistic system based on ontology and rule is optimized. The experiments show that the logistic ontology modularization restricts the reasoning in an acceptable scope as while as the complexity of reasoning, resource usage and the response time of the system are reduced. Meanwhile, the ontology modularization enhances the maintenance and reusability of ontology modules.(2) Interval-gap-based theory is proposed to extend OWL-Time to represent the situation of a single event with gap-intervals. The extension represents the concept and temporal relation in Interval-gap-based theory and the rationality of this representation is verified by the representation of transport event in logistics. The reasoner for the extension is built by extending the primitives, rules and the operation on inference model in Jena, and the experiment on the reasoner not only verify the correctness of the reasoner, but also ensure the correctness of temporal knowledge represented in ontology and rules. With the method in this dissertation the problem of interval-gap-based temporal knowledge representation and reasoning is solved.(3) We present a new approach to characterizing the semantics for the integration of rules and first-order logic in general, and description logics in particular, based on a circumscription characterization of answer set programming, introduced earlier by Lin and Zhou. We show that both Rosati's semantics based on NM-models and Lukasiewicz's answer set semantics can be characterized by circumscription, and the difference between the two can be seen as a matter of circumscription policies. This approach leads to a number of new insights. First, we rebut a criticism on Lukasiewicz's semantics for its inability to reason for negative consequences. Second, our approach leads to a spectrum of possible semantics based on different circumscription policies, and shows a clear picture of how they are related. Finally, we show that the idea of this dissertation can be applied to first-order general stable models.In summary, the problem of the maintainability and usability of large logistic ontology and the specification of temporal information are solved based on the ontology and Datalog Rules, and the semantics for the integration of ontology and rules based on answer set programming is studied to make up for each other's ability of expression.
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