Article

SPLENDID: SPARQL endpoint federation exploiting VOID descriptions

Authors:

Olaf Görlitz and

Steffen StaabAuthors Info & Claims

COLD'11: Proceedings of the Second International Conference on Consuming Linked Data - Volume 782

October 2011

Pages 13 - 24

Published: 23 October 2011 Publication History

Abstract

In order to leverage the full potential of the Semantic Web it is necessary to transparently query distributed RDF data sources in the same way as it has been possible with federated databases for ages. However, there are significant differences between the Web of (linked) Data and the traditional database approaches. Hence, it is not straightforward to adapt successful database techniques for RDF federation. Reasons are the missing cooperation between SPARQL end-points and the need for detailed data statistics for estimating the costs of query execution plans. We have implemented SPLENDID, a query optimization strategy for federating SPARQL endpoints based on statistical data obtained from voiD descriptions.

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Cited By

Yuan YMa DWen ZZhang ZWang G(2021)Subgraph matching over graph federationProceedings of the VLDB Endowment10.14778/3494124.349412915:3(437-450)Online publication date: 1-Nov-2021
https://dl.acm.org/doi/10.14778/3494124.3494129
Cheng SHartig O(2020)FedQPLProceedings of the 22nd International Conference on Information Integration and Web-based Applications & Services10.1145/3428757.3429120(436-445)Online publication date: 30-Nov-2020
https://dl.acm.org/doi/10.1145/3428757.3429120
Mountantonakis MTzitzikas Y(2019)Large-scale Semantic Integration of Linked DataACM Computing Surveys10.1145/334555152:5(1-40)Online publication date: 13-Sep-2019
https://dl.acm.org/doi/10.1145/3345551
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Index Terms

SPLENDID: SPARQL endpoint federation exploiting VOID descriptions
1. Information systems
  1. Data management systems
    1. Database management system engines
      1. Database query processing
  2. Information retrieval
    1. Information retrieval query processing
2. Theory of computation
  1. Theory and algorithms for application domains
    1. Database theory
      1. Database query processing and optimization (theory)

Index terms have been assigned to the content through auto-classification.

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Information & Contributors

Information

Published In

cover image Guide Proceedings

COLD'11: Proceedings of the Second International Conference on Consuming Linked Data - Volume 782

October 2011

142 pages

Editors:
Olaf Hartig
Humboldt-Universität zu Berlin, Institut für Informatik, Berlin, Germany
,
Andreas Harth
Karlsruhe Institute of Technology, Institute AIFB, Karlsruhe, Germany
,
Juan Sequeda
University of Texas at Austin, Department of Computer Sciences, Austin, TX

Publisher

CEUR-WS.org

Aachen, Germany

Publication History

Published: 23 October 2011

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Cited By

Yuan YMa DWen ZZhang ZWang G(2021)Subgraph matching over graph federationProceedings of the VLDB Endowment10.14778/3494124.349412915:3(437-450)Online publication date: 1-Nov-2021
https://dl.acm.org/doi/10.14778/3494124.3494129
Cheng SHartig O(2020)FedQPLProceedings of the 22nd International Conference on Information Integration and Web-based Applications & Services10.1145/3428757.3429120(436-445)Online publication date: 30-Nov-2020
https://dl.acm.org/doi/10.1145/3428757.3429120
Mountantonakis MTzitzikas Y(2019)Large-scale Semantic Integration of Linked DataACM Computing Surveys10.1145/334555152:5(1-40)Online publication date: 13-Sep-2019
https://dl.acm.org/doi/10.1145/3345551
Sorrentino CGiallonardo EZimeo EHung CPapadopoulos G(2019)Topic-based indexing of federated datasetsProceedings of the 34th ACM/SIGAPP Symposium on Applied Computing10.1145/3297280.3297387(1090-1098)Online publication date: 8-Apr-2019
https://dl.acm.org/doi/10.1145/3297280.3297387
Siow ETiropanis THall W(2018)Analytics for the Internet of ThingsACM Computing Surveys10.1145/320494751:4(1-36)Online publication date: 25-Jul-2018
https://dl.acm.org/doi/10.1145/3204947
Wylot MHauswirth MCudré-Mauroux PSakr S(2018)RDF Data Storage and Query Processing SchemesACM Computing Surveys10.1145/317785051:4(1-36)Online publication date: 6-Sep-2018
https://dl.acm.org/doi/10.1145/3177850
Oguz DYin SErgenç BHameurlain ADikenelli O(2017)Extended Adaptive Join Operator with Bind-Bloom Join for Federated SPARQL QueriesInternational Journal of Data Warehousing and Mining10.4018/IJDWM.201707010313:3(47-72)Online publication date: 1-Jul-2017
https://dl.acm.org/doi/10.4018/IJDWM.2017070103
Chun SJung JSeo SRo WLee K(2017)An adaptive plan-based approach to integrating semantic streams with remote RDF dataJournal of Information Science10.1177/016555151667027843:6(852-865)Online publication date: 1-Dec-2017
https://dl.acm.org/doi/10.1177/0165551516670278
Adamou Ad'Aquin MAllocca CMotta E(2017)Supporting virtual integration of Linked Data with just-in-time query recompilationProceedings of the 13th International Conference on Semantic Systems10.1145/3132218.3132227(112-119)Online publication date: 11-Sep-2017
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Galkin MEndris KAcosta MCollarana DVidal MAuer S(2017)SMJoinProceedings of the 13th International Conference on Semantic Systems10.1145/3132218.3132220(104-111)Online publication date: 11-Sep-2017
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