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Source Selection for SPARQL Endpoints: Fit for Heterogeneous Federations of RDF Data Sources?
Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0003-4363-0654
Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-1741-2090
2022 (English)In: Proceedings of the QuWeDa 2022: 6th Workshop on Storing, Querying and Benchmarking Knowledge Graphs co-located with 21st International Semantic Web Conference {(ISWC} 2022), CEUR-WS , 2022, Vol. 3279, p. 5-16Conference paper, Published paper (Refereed)
Abstract [en]

To answer queries over a federation of multiple data sources, a preliminary task is source selection; i.e.,identify the federation members that can answer each part of the query and decompose the query into subqueries assigned to each federation member. Existing source selection approaches for federations of RDF data sources have been developed based on the assumption that the federation member are SPARQL endpoints. This paper presents an analytical study that investigates whether these approaches are still effective in the context of federations that are heterogeneous in terms of the types of data access interface. In particular, we identify what information about the data of the federation members is required by the approaches and analyze the possibilities and the effort of obtaining this information via the different types of data access interfaces. We find that almost all existing source selection approaches can be adopted for heterogeneous federations but obtaining the required information may not be practical

Place, publisher, year, edition, pages
CEUR-WS , 2022. Vol. 3279, p. 5-16
Series
CEUR Workshop Proceedings, ISSN 1613-0073 ; 3279
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:liu:diva-198000Scopus ID: 2-s2.0-85142813273OAI: oai:DiVA.org:liu-198000DiVA, id: diva2:1799177
Conference
6th Workshop on Storing, Querying and Benchmarking Knowledge Graphs (QuWeDa), colocated with ISWC 2022, Hangzhou, China, 23-27 October, 2022
Funder
Swedish Research Council, 2019-05655CUGS (National Graduate School in Computer Science)Available from: 2023-09-21 Created: 2023-09-21 Last updated: 2024-08-22Bibliographically approved

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Cheng, SijinHartig, Olaf

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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
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