Umeå University's logo

umu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • vancouver
  • 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
  • rtf
Ontology-based data federation
Faculty of Computer Science, Free University of Bozen-Bolzano, Bolzano, Italy.
Faculty of Computer Science, Free University of Bozen-Bolzano, Bolzano, Italy.
Faculty of Computer Science, Free University of Bozen-Bolzano, Bolzano, Italy.
Department of Information Science and Media Studies, University of Bergen, Norway; Department of Informatics, University of Oslo, Norway; Ontopic S.r.l., Bolzano, Italy.
Show others and affiliations
2022 (English)In: Proceedings of the 11th International Joint Conference on Knowledge Graphs: IJCKG 2022 / [ed] Alessandro Artale; Diego Calvanese; Haofen Wang; Xiaowang Zhang, Association for Computing Machinery (ACM), 2022, p. 10-19Conference paper, Published paper (Refereed)
Abstract [en]

Ontology-based data access (OBDA) is a well-established approach to information management which facilitates the access to a (single) relational data source through the mediation of a high-level ontology, and the use of a declarative mapping linking the data layer to the ontology. We formally introduce here the notion of ontology-based data federation (OBDF) to denote a framework that combines OBDA with a data federation layer where multiple, possibly heterogeneous sources are virtually exposed as a single relational database. We discuss opportunities and challenges of OBDF, and provide techniques to deliver efficient query answering in an OBDF setting. Such techniques are validated through an extensive experimental evaluation based on the Berlin SPARQL Benchmark.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2022. p. 10-19
Keywords [en]
Data federation, OBDA, Query optimization
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:umu:diva-205345DOI: 10.1145/3579051.3579070Scopus ID: 2-s2.0-85148543827ISBN: 9781450399876 (electronic)OAI: oai:DiVA.org:umu-205345DiVA, id: diva2:1748435
Conference
11th International Joint Conference on Knowledge Graphs, IJCKG 2022, Virtual event, China, October 27-28, 2022
Funder
EU, Horizon 2020, 863410Available from: 2023-04-03 Created: 2023-04-03 Last updated: 2023-04-03Bibliographically approved

Open Access in DiVA

fulltext(1514 kB)130 downloads
File information
File name FULLTEXT01.pdfFile size 1514 kBChecksum SHA-512
aecbb75282e9b38bf8d891f7b93997cfa04a40c9225fea802edf90bd29e597eec7c557383560e01853e962016b58b76217fcda3e570a54c596d737b4b88c658a
Type fulltextMimetype application/pdf

Other links

Publisher's full textScopus

Authority records

Calvanese, Diego

Search in DiVA

By author/editor
Calvanese, Diego
By organisation
Department of Computing Science
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 130 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 339 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • vancouver
  • 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
  • rtf