Studies Of Construction And Storage Of Fuzzy OWL Ontologies Supported By Databases

The Semantic Web is an extension of the current web in which the web information can be given well-defined semantic meaning, and thus enabling better cooperation between computers and people. In order to recognize the web resources by computers in an intelligent and automatic way, we should construct ontologies and use ontology description languages to represent ontologies. OWL is a standard for expressing ontologies in the Semantic Web building on data description language RDF and RDFS (or simply RDF(S)). OWL together with RDF(S) forms the foundation of current Semantic Web description languages.Classical ontologies have limitations when dealing with fuzzy knowledge and data information that play an important role in many web applications, so the significant research efforts in the Semantic Web community are recently directed toward the fuzzy extensions to ontologies, which is in accordance with the case in databases that the fuzzy database models are developed for representing and processing the fuzzy data in many real-world applications.As two important techniques of representing and processing the fuzzy information in web, there exist strong relationships between the fuzzy database models and the fuzzy ontologies. On the one hand, from the view of construction, the fuzzy database models in the database area can be used as the dominant source for acquiring the existing knowledge for fuzzy ontologies development. On the other hand, from the view of storage, the fuzzy information in Semantic Web can be managed more effectively by taking advantage of storing and processing fuzzy data of fuzzy relational models (i.e., fuzzy relational databases). In fact, the construction and the storage of fuzzy ontologies are two significant issues in fuzzy ontologies management. Currently, less research has been done in the storage of fuzzy ontologies and the construction of fuzzy ontologies from the structured fuzzy data.In order to represent and deal with large amounts of fuzzy knowledge, and realize the management of fuzzy Semantic Web ontologies, the fuzzy extensions of the data level and the ontology level languages of Semantic Web are firstly investigated. On this basis, the management of fuzzy OWL ontologies supported by databases is investigated in detail so as to form a comprehensive theoretical framework of representation, construction, and storage of fuzzy OWL ontologies. The main contributions of this paper include:(1) The fuzzy RDFS(f-RDF(S)) and fuzzy OWL (f-OWL) are proposed. Firstly, based on the mechanism of RDF data type, a method of representing the fuzzy data type is proposed, which can solve the problems of representing and processing the fuzzy data type information. The f-RDF(S) is hereby presented, and the semantics of f-RDF(S) is also given. Then, based on f-RDF(S), the OWL is extended to f-OWL, and the syntax and semantics of f-OWL are given. The f-OWL lays the language foundation of describing the fuzzy OWL ontologies. On this basis, the formal definition of fuzzy OWL ontologies is given.(2) The construction method of fuzzy OWL ontologies based on fuzzy EER models is presented. Firstly, the formal definition of fuzzy EER models is given, and then from the view of fuzzy description logics, the feasibility of constructing fuzzy OWL ontologies from fuzzy EER models is discussed. On this basis, the steps of constructing fuzzy OWL ontologies using fuzzy EER models is given, and the transformation rules and the algorithm of fuzzy EER models to fuzzy OWL ontologies are given.(3) The construction method of fuzzy OWL ontologies based on fuzzy relational databases is presented. Firstly, the formal definition of fuzzy relational databases is given, and then from the view of fuzzy description logics, the feasibility of constructing fuzzy OWL ontologies from fuzzy relational databases is discussed. On this basis, the steps of constructing the fuzzy OWL ontologies using the fuzzy relational databases, including the semantic recognition of fuzzy relational models, the transformation rules, and the algorithm are given. Then, the generation of fuzzy OWL ontologies instances using the data of fuzzy relational databases is developed in detail. The correctness of construction method of fuzzy OWL ontologies is proved.(4) The storage method of fuzzy OWL ontologies in fuzzy relational databases is proposed. Firstly, by analyzing the storage approaches of ontologies, the storage schema of fuzzy OWL ontologies is given, which can satisfy the storage demand of fuzzy OWL ontologies. On this basis, the storage methods of fuzzy OWL ontologies structure and fuzzy data of different types in the fuzzy relational databases are proposed, which achieve reasonable and efficient storage. The correctness of storage method of fuzzy OWL ontologies is proved.