Title: DLUBM: A benchmark for distributed linked data knowledge base systems
Authors: Keppmann, Felix Leif
Maleshkova, Maria 
Harth, Andreas
Language: eng
Keywords: Distributed benchmarking;DLUBM;Linked Data;Linked Data benchmarking;LUBM
Issue Date: 21-Oct-2017
Publisher: Springer
Document Type: Conference Object
Journal / Series / Working Paper (HSU): Lecture Notes in Computer Science
Volume: 10574
Page Start: 427
Page End: 444
Published in (Book): 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
Number: 2
Publisher Place: Berlin
Conference: Confederated International Conferences: CoopIS, C&TC, and ODBASE 2017, Rhodes, Greece, October 23-27, 2017
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.
Organization Units (connected with the publication): Karlsruhe Institute of Technology
ISBN: 9783319694580
ISSN: 03029743
Publisher DOI: 10.1007/978-3-319-69459-7_29
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