Using Berlin SPARQL benchmark to evaluate virtual SPARQL endpoints over relational databases
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F24%3A10488753" target="_blank" >RIV/00216208:11320/24:10488753 - isvavai.cz</a>
Result on the web
<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=11Q1Z_~.Cl" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=11Q1Z_~.Cl</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.datak.2024.102309" target="_blank" >10.1016/j.datak.2024.102309</a>
Alternative languages
Result language
angličtina
Original language name
Using Berlin SPARQL benchmark to evaluate virtual SPARQL endpoints over relational databases
Original language description
The RDF is a popular and well-documented format for publishing structured data on the web. It enables data to be consumed without the knowledge of how the data is internally stored. There are already several native RDF storage solutions that provide a SPARQL endpoint. However, native RDF stores are not widely adopted. It is still more common to store data in a relational database. One of the useful features of native RDF storage solutions is providing a SPARQL endpoint, a web service to query RDF data with SPARQL. To provide this feature also on top of prevalent relational databases, solutions for virtual SPARQL endpoints on top of a relational database have appeared. To benchmark these solutions, a state-of-the-art tool, the Berlin SPARQL Benchmark (BSBM), is used. However, BSBM was designed primarily to benchmark native RDF stores. It can also be used to benchmark solutions for virtual SPARQL endpoints. However, since BSBM was not designed for virtual SPARQL endpoints, each implementation uses that tool differently for evaluation. As a result, the evaluation is not consistent and therefore hardly comparable. In this paper, we demonstrate how this well-defined benchmarking tool for SPARQL endpoints can be used to evaluate virtual endpoints over relational databases, perform the evaluation on the available implementations, and provide instructions on how to repeat the same evaluation in the future.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA23-07781S" target="_blank" >GA23-07781S: Self-Adapting Management of Multi-Model Databases</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Data and Knowledge Engineering
ISSN
0169-023X
e-ISSN
1872-6933
Volume of the periodical
152
Issue of the periodical within the volume
July 2024
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
18
Pages from-to
102309
UT code for WoS article
001240762500001
EID of the result in the Scopus database
2-s2.0-85192684755