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Compressed and queryable self-indexes for RDF archives
dc.contributor.author | Cerdeira-Pena, Ana | |
dc.contributor.author | Bernardo, Guillermo de | |
dc.contributor.author | Fariña, Antonio | |
dc.contributor.author | Fernández, Javier D. | |
dc.contributor.author | Martínez-Prieto, Miguel A. | |
dc.date.accessioned | 2023-12-20T08:59:32Z | |
dc.date.issued | 2023-08 | |
dc.identifier.citation | A. Cerdeira-Pena, G. de Bernardo, A. Fariña, J. D. Fernández, y M. A. Martínez-Prieto, «Compressed and queryable self-indexes for RDF archives», Knowl Inf Syst, ago. 2023, doi: 10.1007/s10115-023-01967-7. | es_ES |
dc.identifier.issn | 0219-3116 | |
dc.identifier.uri | http://hdl.handle.net/2183/34566 | |
dc.description | This version of the article has been accepted for publication, after peer review and is subject to Knowledge and Information Systems , but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/s10115-023-01967-7 | es_ES |
dc.description.abstract | [Abstract]: RDF compression and querying are consolidated topics in the Web of Data, with a plethora of solutions to efficiently store and query static datasets. However, as RDF data changes along time, it becomes necessary to keep different versions of RDF datasets, in what is called an RDF archive. For large RDF datasets, naive techniques to store these versions lead to significant scalability problems. In this paper, we present v-RDF-SI, one of the first RDF archiving solutions that aim at joining both compression and fast querying. In v-RDF-SI, we extend existing RDF representations based on compact data structures to provide efficient support of version-based queries in compressed space. We present two implementations of v-RDF-SI, named v-RDFCSA and v-HDT, based, respectively, on RDFCSA (an RDF self-index) and HDT (a W3C-supported compressed RDF representation). We experimentally evaluate v-RDF-SI over a public benchmark named BEAR, showing that v-RDF-SI drastically reduces space requirements, being up to 40 times smaller than the baselines provided by BEAR, and 4 times smaller than alternatives based on compact data structures, while yielding significantly faster query times in most cases. On average, the fastest variants of v-RDF-SI outperform the alternatives by almost an order of magnitude. | es_ES |
dc.description.sponsorship | The first three co-authors are members of the CITIC, which, as Research Center accredited by the Galician University System, is funded by Consellería de Cultura, Educación e Universidades from Xunta de Galicia, supported in an 80% through ERDF Funds, ERDF Operational Programme Galicia 2014–2020, and the remaining 20% by Secretaría Xeral de Universidades [Grant ED431G 2019/01]. The Spanish group is also funded by Xunta de Galicia/FEDER-UE [ED431C 2021/53]; by MICINN [Magist: PID2019-105221RB-C41; FLATCity-POC: PDC2021-121239-C31; SIGTRANS: PDC2021-120917-C21; EXTRA-Compact: PID2020-114635RB-I00; PID2019-105221RB-C41]; by MCIU-AEI/FEDER-UE [BIZDEVOPS: RTI2018-098309-B-C32]; and by Xunta de Galicia/Igape/IG240.2020.1.185. | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431C 2021/53 | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431G 2019/01 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Springer Nature | es_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PDC2021-121239-C31/ES/FLATCITY-POC | es_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PDC2021-120917-C21/ES/SIGTRANS | es_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-114635RB-I00/ES/EXPLOTACION ENRIQUECIDA DE TRAYECTORIAS CON ESTRUCTURAS DE DATOS COMPACTAS Y GIS/ | es_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-105221RB-C41/ES/VISUALIZACION Y EXPLORACION BASADA EN FLUJOS Y ANALITICA DE BIG DATA ESPACIAL | es_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-098309-B-C32/ES/BIZDEVOPS-GLOBAL: UN FRAMEWORK TECNOLOGICO Y METODOLOGICO SOSTENIBLE PARA EL DESARROLLO DE SOFTWARE ALINEADO CON EL NEGOCIO EN DEVOPS GLOBAL | es_ES |
dc.relation.uri | https://doi.org/10.1007/s10115-023-01967-7 | es_ES |
dc.rights | © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2023 | es_ES |
dc.subject | RDF | es_ES |
dc.subject | RDF Archiving | es_ES |
dc.subject | RDF compression | es_ES |
dc.subject | Self-index | es_ES |
dc.title | Compressed and queryable self-indexes for RDF archives | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.access | info:eu-repo/semantics/embargoedAccess | es_ES |
dc.date.embargoEndDate | 2024-08-01 | es_ES |
dc.date.embargoLift | 2024-08-01 | |
UDC.journalTitle | Knowledge and Information Systems | es_ES |
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