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DLUBM: A benchmark for distributed linked data knowledge base systems

Publication date
2017-10-21
Document type
Conference paper
Author
Keppmann, Felix Leif
Maleshkova, Maria 
Harth, Andreas
Organisational unit
Karlsruhe Institute of Technology
DOI
10.1007/978-3-319-69459-7_29
URI
https://openhsu.ub.hsu-hh.de/handle/10.24405/15239
Scopus ID
2-s2.0-85032694919
ISBN
9783319694580
ISSN
0302-9743
E-ISSN
1611-3349
Conference
Confederated International Conferences: CoopIS, C&TC, and ODBASE 2017, Rhodes, Greece, October 23-27, 2017
Series or journal
Lecture Notes in Computer Science
Periodical volume
10574
Book title
On the Move to Meaningful Internet Systems. OTM 2017 Conferences Confederated International Conferences: CoopIS, C&TC, and ODBASE 2017, Rhodes, Greece, October 23-27, 2017, Proceedings
Volume (part of multivolume book)
2
First page
427
Last page
444
Peer-reviewed
✅
Part of the university bibliography
Nein
  • Additional Information
Keyword
Distributed benchmarking
DLUBM
Linked Data
Linked Data benchmarking
LUBM
Abstract
Linked Data is becoming a stable technology alternative and is no longer only an innovation trend. More and more companies are looking into adapting Linked Data as part of the new data economy. Driven by the growing availability of data sources, solutions are constantly being newly developed or improved in order to support the necessity for data exchange both in web and enterprise settings. Unfortunately, currently the choice whether to use Linked Data is more an educated guess than a fact-based decision. Therefore, the provisioning of open benchmarking tools and reports, which allow developers to assess the fitness of existing solutions, is key for pushing the development of better Linked Data-based approaches and solutions. To this end we introduce a novel Linked Data benchmark – Distributed LUBM, which enables the reproducible creation and deployment of distributed interlinked LUBM datasets. We provide a system architecture for distributed Linked Data benchmark environments, accompanied by guiding design requirements. We instantiate the architecture with the actual DLUBM implementation and evaluate a Linked Data query engine via DLUBM.
Version
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