| Abstract [eng] |
In the modern world it is necessary to save a larger amount of data in order to meet the needs. More difficult systems are created in order to save and process the data. However, a big challenge for ordinary systems is to control and appropriately offer for consumers such huge amounts of data. In order to process information quicker, mechanisms are created to systemize the data, and using ontologies to describe them according to the semantic meaning. But the amount of ontologies are also growing, and at the same time data interpretation processes are getting slow. Therefore, the question arises how and where to save ontologies and how to integrate the data with the information which is in relational data bases in order the processes to become quicker. In the research semantic storage opportunities of Oracle data bases management systems are analysed. The methods of semantic data storage, semantic and relational data integration are patterned. The method of the semantic data storage solves semantic data storage tasks such as the creation of semantic patterns and rules, RDF storage in Oracle data bases management systems. The method of the semantic and relational data integration solves different storage data integration tasks. Thus, integrated SQL and SPARQL queries patterns are created which let us manipulate SQL queries language and semantic and relational data at the same time. There is also created the prototype of semantic data administrative tool by using a semantic data storage method. The prototype gives for a consumer a convenient connection to administrate semantic data. |
