Semantic Integration of Heterogeneous Databases of Same Domain Using Ontology
Heterogeneous database integration is the study of integrating data from multiple databases. Integrating the heterogeneous database of the same domain has three main challenges that make the heterogeneity problem difficult to solve. The three problems are Semantic, Syntactic and Structural Heterogen...
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Veröffentlicht in: | IEEE access 2020, Vol.8, p.77903-77919 |
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description | Heterogeneous database integration is the study of integrating data from multiple databases. Integrating the heterogeneous database of the same domain has three main challenges that make the heterogeneity problem difficult to solve. The three problems are Semantic, Syntactic and Structural Heterogeneity. Conventional heterogeneous database integration schemes, like De-duplication Techniques, Data Warehouse, and Information Retrieval (IR) Search technique lack the capability to solve the integration of databases completely. The only reason is they cannot deal with Semantic heterogeneity problems efficiently. The semantic Web ontology model is experimented and discussed in the article, which is based on the query execution model. The ontology modeling is divided into two phases, initially to translate the database rules according to ontology rules to find an abstract ontology model. Secondly, to extend the abstract ontology model according to the databases. The method facilitates to apply similarly SPQRAL queries to search the data in the databases. Therefore, the Jena API is used to retrieve semantically similar records. The experiment is based on the two heterogeneous Universities Library Databases. The results show the effectiveness and scalability of the methodology. |
doi_str_mv | 10.1109/ACCESS.2020.2988685 |
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Integrating the heterogeneous database of the same domain has three main challenges that make the heterogeneity problem difficult to solve. The three problems are Semantic, Syntactic and Structural Heterogeneity. Conventional heterogeneous database integration schemes, like De-duplication Techniques, Data Warehouse, and Information Retrieval (IR) Search technique lack the capability to solve the integration of databases completely. The only reason is they cannot deal with Semantic heterogeneity problems efficiently. The semantic Web ontology model is experimented and discussed in the article, which is based on the query execution model. The ontology modeling is divided into two phases, initially to translate the database rules according to ontology rules to find an abstract ontology model. Secondly, to extend the abstract ontology model according to the databases. The method facilitates to apply similarly SPQRAL queries to search the data in the databases. 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Integrating the heterogeneous database of the same domain has three main challenges that make the heterogeneity problem difficult to solve. The three problems are Semantic, Syntactic and Structural Heterogeneity. Conventional heterogeneous database integration schemes, like De-duplication Techniques, Data Warehouse, and Information Retrieval (IR) Search technique lack the capability to solve the integration of databases completely. The only reason is they cannot deal with Semantic heterogeneity problems efficiently. The semantic Web ontology model is experimented and discussed in the article, which is based on the query execution model. The ontology modeling is divided into two phases, initially to translate the database rules according to ontology rules to find an abstract ontology model. Secondly, to extend the abstract ontology model according to the databases. The method facilitates to apply similarly SPQRAL queries to search the data in the databases. Therefore, the Jena API is used to retrieve semantically similar records. The experiment is based on the two heterogeneous Universities Library Databases. The results show the effectiveness and scalability of the methodology.</description><subject>Data models</subject><subject>Data search</subject><subject>Data warehouses</subject><subject>Domains</subject><subject>Heterogeneity</subject><subject>Information retrieval</subject><subject>Library Databases</subject><subject>Ontologies</subject><subject>Ontology</subject><subject>Ontology modelling</subject><subject>Relational databases</subject><subject>Resource description framework</subject><subject>Semantic Integration</subject><subject>Semantic Web</subject><subject>Semantics</subject><issn>2169-3536</issn><issn>2169-3536</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><sourceid>DOA</sourceid><recordid>eNpNUctOw0AMjBBIIOgX9BKJc4v3lWSPKDxaqYhD4bxyNk6UqsnCbnro37MlqMIXW_bM2NYkyZzBkjHQD49l-bzdLjlwWHJdFFmhLpIbzjK9EEpkl__q62QWwg5iFLGl8pvkbUs9DmNn0_UwUutx7NyQuiZd0UjetTSQO4T0CUesMFA4jbbYU_rkeuyG9DN0Q5u-D6Pbu_Z4l1w1uA80-8u3yefL80e5WmzeX9fl42ZhJRTjQgsGOXDNSfJ4RYVcKZSEOrMKG4FWyjqnqm5yZklZpUAha6ocVIVMR8Rtsp50a4c78-W7Hv3ROOzMb8P51qCPT-3JYCUJtCCNDCRw1NTUIkNpha1FnamodT9pfXn3faAwmp07-CGeb7hUEjQXCiJKTCjrXQiemvNWBuZkg5lsMCcbzJ8NkTWfWB0RnRkacs5ULn4A3ReDUg</recordid><startdate>2020</startdate><enddate>2020</enddate><creator>Asfand-E-Yar, Muhammad</creator><creator>Ali, Ramis</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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subjects | Data models Data search Data warehouses Domains Heterogeneity Information retrieval Library Databases Ontologies Ontology Ontology modelling Relational databases Resource description framework Semantic Integration Semantic Web Semantics |
title | Semantic Integration of Heterogeneous Databases of Same Domain Using Ontology |
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