随着商业和科学研究领域中数据密集型应用越来越广泛,提供透明地访问分布式的、异构的数据源将成为这种应用的关键。提出一种基于网格数据仲裁服务(Grid Data Mediation Service,GDMS)的数据集成系统,它能够把网格中的分布式的、异构的...随着商业和科学研究领域中数据密集型应用越来越广泛,提供透明地访问分布式的、异构的数据源将成为这种应用的关键。提出一种基于网格数据仲裁服务(Grid Data Mediation Service,GDMS)的数据集成系统,它能够把网格中的分布式的、异构的数据源表示成一个逻辑上虚拟的数据源,并设计出了一种灵活的映射模式来描述构建虚拟数据源的过程。展开更多
Ontology-based semantic information integration resolve the schema-level heterogeneity and part of data level heterogeneity between distributed data sources. But it is ubiquitous that schema semantics of information i...Ontology-based semantic information integration resolve the schema-level heterogeneity and part of data level heterogeneity between distributed data sources. But it is ubiquitous that schema semantics of information is identical while the interpretation of it varies with different context, and ontology-based semantic information integration can not resolve this context heterogeneity. By introducing context representation and context mediation to ontology based information integration, the attribute-level context heterogeneity can be detected and reconciled automatically, and hence a complete solution for semantic heterogeneity is formed. Through a concrete example, the context representation and the process in which the attribute-level context heterogeneity is reconciled during query processing are presented. This resolution can make up the deficiency of schema mapping based semantic information integration. With the architecture proposed in this paper the semantic heterogeneity solution is adaptive and extensive.展开更多
文摘随着商业和科学研究领域中数据密集型应用越来越广泛,提供透明地访问分布式的、异构的数据源将成为这种应用的关键。提出一种基于网格数据仲裁服务(Grid Data Mediation Service,GDMS)的数据集成系统,它能够把网格中的分布式的、异构的数据源表示成一个逻辑上虚拟的数据源,并设计出了一种灵活的映射模式来描述构建虚拟数据源的过程。
基金The National Natural Science Foundation of China (No.50305007)the Scientific Research Project of Hubei Provincial Department of Education (No.D200618003)
文摘Ontology-based semantic information integration resolve the schema-level heterogeneity and part of data level heterogeneity between distributed data sources. But it is ubiquitous that schema semantics of information is identical while the interpretation of it varies with different context, and ontology-based semantic information integration can not resolve this context heterogeneity. By introducing context representation and context mediation to ontology based information integration, the attribute-level context heterogeneity can be detected and reconciled automatically, and hence a complete solution for semantic heterogeneity is formed. Through a concrete example, the context representation and the process in which the attribute-level context heterogeneity is reconciled during query processing are presented. This resolution can make up the deficiency of schema mapping based semantic information integration. With the architecture proposed in this paper the semantic heterogeneity solution is adaptive and extensive.
