Show simple item record

dc.contributor.authorHasnain, Ali
dc.contributor.authorSaleem, Muhammad
dc.contributor.authorNgomo, Axel-Cyrille Ngonga
dc.contributor.authorRebholz-Schuhmann, Dietrich
dc.date.accessioned2019-02-15T10:01:23Z
dc.date.available2019-02-15T10:01:23Z
dc.date.issued2018
dc.identifier.citationHasnain, Ali, Saleem, Muhammad, Ngomo, Axel-Cyrille Ngonga, & Rebholz-Schuhmann, Dietrich. (2018). Extending LargeRDFBench for multi-source data at scale for SPARQL endpoint federation. Paper presented at the 17th International Semantic Web Conference 2018 (ISWC2018), Monterey, California, USA, 08-12 October, in Studies on the Semantic Web, Volume 36: Emerging Topics in Semantic Technologies. doi: 10.3233/978-1-61499-894-5-203en_IE
dc.identifier.isbn978-1-61499-894-5
dc.identifier.urihttp://hdl.handle.net/10379/14958
dc.description.abstractQuerying the Web of Data is highly motivated by the use of federation approaches mainly SPARQL query federation when the data is available through endpoints. Different benchmarks have been proposed to exploit the full potential of SPARQL query federation approaches in real world scenarios with their limitations in size and complexity. Previously, we introduced LargeRDFBench – a billion-triple benchmark for SPARQL query federation. In this work, we pinpoint some of of the limitation of LargeRDFBench and propose an extension with 8 additional queries. Our evaluation results of the state-of-the-art federation engines revealed interesting insights, when tested on these additional queriesen_IE
dc.description.sponsorshipThis work was supported by the project HOBBIT, which has received funding from the European Union’s H2020 research and innovation action program (GA number 688227). Also, this publication has emanated from research supported in part by a research grant from Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2289, co-funded by the European Regional Development Fund.en_IE
dc.formatapplication/pdfen_IE
dc.language.isoenen_IE
dc.publisherIOS Pressen_IE
dc.relation.ispartofInternational Semantic Web Conference 2018en
dc.subjectLargeRDFBenchen_IE
dc.subjectSPARQL Endpointen_IE
dc.subjectQuery Federationen_IE
dc.titleExtending largeRDFBench for multi-source data at scale for SPARQL endpoint federationen_IE
dc.typeConference Paperen_IE
dc.date.updated2019-01-23T15:56:28Z
dc.identifier.doi10.3233/978-1-61499-894-5-203
dc.local.publishedsourcehttps://dx.doi.org/10.3233/978-1-61499-894-5-203en_IE
dc.local.publisherstatementHasnain, Ali, Saleem, Muhammad, Ngomo, Axel-Cyrille Ngonga, & Rebholz-Schuhmann, Dietrich. (2018). Extending LargeRDFBench for multi-source data at scale for SPARQL endpoint federation. Paper presented at the 17th International Semantic Web Conference 2018 (ISWC2018), Monterey, California, USA, 08-02 October, in Studies on the Semantic Web, Volume 36: Emerging Topics in Semantic Technologies. doi: 10.3233/978-1-61499-894-5-203, with permission from IOS Press at www.iospress.nl The publication is available at IOS Press through https://dx.doi.org/10.3233/978-1-61499-894-5-203en_IE
dc.description.peer-reviewedpeer-reviewed
dc.contributor.funderHorizon 2020en_IE
dc.contributor.funderScience Foundation Irelanden_IE
dc.contributor.funderEuropean Regional Development Funden_IE
dc.internal.rssid15742081
dc.local.contactSyed Muhammad Ali Hasnain, Deri, Ida Business Park, Lower Dangan, Galway. Email: ali.hasnain@nuigalway.ie
dc.local.copyrightcheckedYes
dc.local.versionPUBLISHED
dcterms.projectinfo:eu-repo/grantAgreement/EC/H2020::RIA/688227/EU/Holistic Benchmarking of Big Linked Data/HOBBITen_IE
dcterms.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Centres/12/RC/2289/IE/INSIGHT - Irelands Big Data and Analytics Research Centre/en_IE
nui.item.downloads63


Files in this item

Attribution-NonCommercial-NoDerivs 3.0 Ireland
This item is available under the Attribution-NonCommercial-NoDerivs 3.0 Ireland. No item may be reproduced for commercial purposes. Please refer to the publisher's URL where this is made available, or to notes contained in the item itself. Other terms may apply.

The following license files are associated with this item:

Thumbnail

This item appears in the following Collection(s)

Show simple item record