SQL to SPARQL conversion for direct RDF querying

With the advances in native storage means of RDF data and associated querying capabilities using SPARQL, there is a need to let SQL users benefit from such capabilities for interoperability objectives and without any conversion of the RDF data into relational data. In this sense, this work present S...

Descripción completa

Detalles Bibliográficos
Autores: Abatal, Ahmed, Alaoui, Khadija, Bahaj, Mohamed, Alaoui, Larbi
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2019
País:España
Institución:Universitat Pompeu Fabra
Repositorio:Repositorio Digital de la UPF
OAI Identifier:oai:repositori.upf.edu:10230/59129
Acceso en línea:http://hdl.handle.net/10230/59129
http://dx.doi.org/10.14569/IJACSA.2019.0101180
Access Level:acceso abierto
Palabra clave:Description Framework (RDF)
Struc-tured Query Language (SQL)
Simple Protocol and RDF Query Language (SPARQL)
schema mapping
query conversion
Allegrograph
id ES_6b87f7f2ebc8440ed6b66d5eedc59fb8
oai_identifier_str oai:repositori.upf.edu:10230/59129
network_acronym_str ES
network_name_str España
repository_id_str
spelling SQL to SPARQL conversion for direct RDF queryingAbatal, AhmedAlaoui, KhadijaBahaj, MohamedAlaoui, LarbiDescription Framework (RDF)Struc-tured Query Language (SQL)Simple Protocol and RDF Query Language (SPARQL)schema mappingquery conversionAllegrographWith the advances in native storage means of RDF data and associated querying capabilities using SPARQL, there is a need to let SQL users benefit from such capabilities for interoperability objectives and without any conversion of the RDF data into relational data. In this sense, this work present SQL2SPARQL4RDF an automatic conversion algorithm of SQL queries into SPARQL queries for querying RDF data, which extends the previously established algorithm with relevant SQL elements such as queries with INSERT, DELETE, GROUP BY and HAVING clauses. SQL users are provided with a relational schema of their RDF data against which they can formulate their SQL queries that are then converted into SPARQL equivalent ones with respect to the provided schema. This avoids the birding of translating instances and data replication and thus saving load-ing times and guaranteeing fast execution especially in the case of massive amounts of data. In addition, the automatic mapping framework developed by the java programming language, and implement many new mapping functionalities. Furthermore, to test and validate the efficiency of the mapping approach and adding a module for automatic execution and evaluation of the various obtained SPARQL queries on Allegrograph.SAI Organization202420242019info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/59129http://dx.doi.org/10.14569/IJACSA.2019.0101180reponame:Repositorio Digital de la UPFinstname:Universitat Pompeu FabraInglésInternational Journal of Advanced Computer Science and Applications(IJACSA). 2019;10(11):599-604.This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:repositori.upf.edu:10230/591292026-06-12T07:21:37Z
dc.title.none.fl_str_mv SQL to SPARQL conversion for direct RDF querying
title SQL to SPARQL conversion for direct RDF querying
spellingShingle SQL to SPARQL conversion for direct RDF querying
Abatal, Ahmed
Description Framework (RDF)
Struc-tured Query Language (SQL)
Simple Protocol and RDF Query Language (SPARQL)
schema mapping
query conversion
Allegrograph
title_short SQL to SPARQL conversion for direct RDF querying
title_full SQL to SPARQL conversion for direct RDF querying
title_fullStr SQL to SPARQL conversion for direct RDF querying
title_full_unstemmed SQL to SPARQL conversion for direct RDF querying
title_sort SQL to SPARQL conversion for direct RDF querying
dc.creator.none.fl_str_mv Abatal, Ahmed
Alaoui, Khadija
Bahaj, Mohamed
Alaoui, Larbi
author Abatal, Ahmed
author_facet Abatal, Ahmed
Alaoui, Khadija
Bahaj, Mohamed
Alaoui, Larbi
author_role author
author2 Alaoui, Khadija
Bahaj, Mohamed
Alaoui, Larbi
author2_role author
author
author
dc.subject.none.fl_str_mv Description Framework (RDF)
Struc-tured Query Language (SQL)
Simple Protocol and RDF Query Language (SPARQL)
schema mapping
query conversion
Allegrograph
topic Description Framework (RDF)
Struc-tured Query Language (SQL)
Simple Protocol and RDF Query Language (SPARQL)
schema mapping
query conversion
Allegrograph
description With the advances in native storage means of RDF data and associated querying capabilities using SPARQL, there is a need to let SQL users benefit from such capabilities for interoperability objectives and without any conversion of the RDF data into relational data. In this sense, this work present SQL2SPARQL4RDF an automatic conversion algorithm of SQL queries into SPARQL queries for querying RDF data, which extends the previously established algorithm with relevant SQL elements such as queries with INSERT, DELETE, GROUP BY and HAVING clauses. SQL users are provided with a relational schema of their RDF data against which they can formulate their SQL queries that are then converted into SPARQL equivalent ones with respect to the provided schema. This avoids the birding of translating instances and data replication and thus saving load-ing times and guaranteeing fast execution especially in the case of massive amounts of data. In addition, the automatic mapping framework developed by the java programming language, and implement many new mapping functionalities. Furthermore, to test and validate the efficiency of the mapping approach and adding a module for automatic execution and evaluation of the various obtained SPARQL queries on Allegrograph.
publishDate 2019
dc.date.none.fl_str_mv 2019
2024
2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10230/59129
http://dx.doi.org/10.14569/IJACSA.2019.0101180
url http://hdl.handle.net/10230/59129
http://dx.doi.org/10.14569/IJACSA.2019.0101180
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv International Journal of Advanced Computer Science and Applications(IJACSA). 2019;10(11):599-604.
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv SAI Organization
publisher.none.fl_str_mv SAI Organization
dc.source.none.fl_str_mv reponame:Repositorio Digital de la UPF
instname:Universitat Pompeu Fabra
instname_str Universitat Pompeu Fabra
reponame_str Repositorio Digital de la UPF
collection Repositorio Digital de la UPF
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869410203137474560
score 15,81155

Similares en LA Referencia