Schema-Based Mapping Approach for Data Transformation to Enrich Semantic Web

Modern web wants the data to be in Resource Description Framework (RDF) format, a machine-readable form that is easy to share and reuse data without human intervention. However, most of the information is still available in relational form. The existing conventional methods transform the data from R...

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Autores principales:	Senthilselvan Natarajan, Subramaniyaswamy Vairavasundaram, Yuvaraja Teekaraman, Ramya Kuppusamy, Arun Radhakrishnan
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi-Wiley 2021
Materias:	Technology T Telecommunication TK5101-6720
Acceso en línea:	https://doaj.org/article/7d68e0922f314f42ba3f1a307fc02796
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id	oai:doaj.org-article:7d68e0922f314f42ba3f1a307fc02796
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spelling	oai:doaj.org-article:7d68e0922f314f42ba3f1a307fc027962021-11-22T01:10:39ZSchema-Based Mapping Approach for Data Transformation to Enrich Semantic Web1530-867710.1155/2021/8567894https://doaj.org/article/7d68e0922f314f42ba3f1a307fc027962021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/8567894https://doaj.org/toc/1530-8677Modern web wants the data to be in Resource Description Framework (RDF) format, a machine-readable form that is easy to share and reuse data without human intervention. However, most of the information is still available in relational form. The existing conventional methods transform the data from RDB to RDF using instance-level mapping, which has not yielded the expected results because of poor mapping. Hence, in this paper, a novel schema-based RDB-RDF mapping method (relational database to Resource Description Framework) is proposed, which is an improvised version for transforming the relational database into the Resource Description Framework. It provides both data materialization and on-demand mapping. RDB-RDF reduces the data retrieval time for nonprimary key search by using schema-level mapping. The resultant mapped RDF graph presents the relational database in a conceptual schema and maintains the instance triples as data graph. This mechanism is known as data materialization, which suits well for the static dataset. To get the data in a dynamic environment, query translation (on-demand mapping) is best instead of whole data conversion. The proposed approach directly converts the SPARQL query into SQL query using the mapping descriptions available in the proposed system. The mapping description is the key component of this proposed system which is responsible for quick data retrieval and query translation. Join expression introduced in the proposed RDB-RDF mapping method efficiently handles all complex operations with primary and foreign keys. Experimental evaluation is done on the graphics designer database. It is observed from the result that the proposed schema-based RDB-RDF mapping method accomplishes more comprehensible mapping than conventional methods by dissolving structural and operational differences.Senthilselvan NatarajanSubramaniyaswamy VairavasundaramYuvaraja TeekaramanRamya KuppusamyArun RadhakrishnanHindawi-WileyarticleTechnologyTTelecommunicationTK5101-6720ENWireless Communications and Mobile Computing, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Technology T Telecommunication TK5101-6720
spellingShingle	Technology T Telecommunication TK5101-6720 Senthilselvan Natarajan Subramaniyaswamy Vairavasundaram Yuvaraja Teekaraman Ramya Kuppusamy Arun Radhakrishnan Schema-Based Mapping Approach for Data Transformation to Enrich Semantic Web
description	Modern web wants the data to be in Resource Description Framework (RDF) format, a machine-readable form that is easy to share and reuse data without human intervention. However, most of the information is still available in relational form. The existing conventional methods transform the data from RDB to RDF using instance-level mapping, which has not yielded the expected results because of poor mapping. Hence, in this paper, a novel schema-based RDB-RDF mapping method (relational database to Resource Description Framework) is proposed, which is an improvised version for transforming the relational database into the Resource Description Framework. It provides both data materialization and on-demand mapping. RDB-RDF reduces the data retrieval time for nonprimary key search by using schema-level mapping. The resultant mapped RDF graph presents the relational database in a conceptual schema and maintains the instance triples as data graph. This mechanism is known as data materialization, which suits well for the static dataset. To get the data in a dynamic environment, query translation (on-demand mapping) is best instead of whole data conversion. The proposed approach directly converts the SPARQL query into SQL query using the mapping descriptions available in the proposed system. The mapping description is the key component of this proposed system which is responsible for quick data retrieval and query translation. Join expression introduced in the proposed RDB-RDF mapping method efficiently handles all complex operations with primary and foreign keys. Experimental evaluation is done on the graphics designer database. It is observed from the result that the proposed schema-based RDB-RDF mapping method accomplishes more comprehensible mapping than conventional methods by dissolving structural and operational differences.
format	article
author	Senthilselvan Natarajan Subramaniyaswamy Vairavasundaram Yuvaraja Teekaraman Ramya Kuppusamy Arun Radhakrishnan
author_facet	Senthilselvan Natarajan Subramaniyaswamy Vairavasundaram Yuvaraja Teekaraman Ramya Kuppusamy Arun Radhakrishnan
author_sort	Senthilselvan Natarajan
title	Schema-Based Mapping Approach for Data Transformation to Enrich Semantic Web
title_short	Schema-Based Mapping Approach for Data Transformation to Enrich Semantic Web
title_full	Schema-Based Mapping Approach for Data Transformation to Enrich Semantic Web
title_fullStr	Schema-Based Mapping Approach for Data Transformation to Enrich Semantic Web
title_full_unstemmed	Schema-Based Mapping Approach for Data Transformation to Enrich Semantic Web
title_sort	schema-based mapping approach for data transformation to enrich semantic web
publisher	Hindawi-Wiley
publishDate	2021
url	https://doaj.org/article/7d68e0922f314f42ba3f1a307fc02796
work_keys_str_mv	AT senthilselvannatarajan schemabasedmappingapproachfordatatransformationtoenrichsemanticweb AT subramaniyaswamyvairavasundaram schemabasedmappingapproachfordatatransformationtoenrichsemanticweb AT yuvarajateekaraman schemabasedmappingapproachfordatatransformationtoenrichsemanticweb AT ramyakuppusamy schemabasedmappingapproachfordatatransformationtoenrichsemanticweb AT arunradhakrishnan schemabasedmappingapproachfordatatransformationtoenrichsemanticweb
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Schema-Based Mapping Approach for Data Transformation to Enrich Semantic Web

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