StarBench: Benchmarking RDF-star Triplestores

Ghadeer Abuoda*, Christian Aebeloe, Daniele Dell'Aglio, Arthur Keen, Katja Hose

*Kontaktforfatter

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

83 Downloads (Pure)

Abstract

RDF-star has rapidly gained popularity as a way to annotate RDF statements while avoiding the disadvantages of reification. Hence, a number of triplestores supporting this new standard have become available.
Yet, it is difficult to assess the performance of these systems and to which degree they support RDF-star
and the corresponding SPARQL-star query language. Hence, in this paper, we propose StarBench, a
benchmark for testing SPARQL-star support and runtime performance. We ran StarBench on a number
of state-of-the-art triplestores with RDF-star and SPARQL-star support and share our findings. Based on
these findings, we highlight existing challenges and research opportunities.
OriginalsprogEngelsk
TitelJoint Proceedings of the QuWeDa and MEPDaW 2023: 7th Workshop on Storing, Querying and Benchmarking Knowledge Graphs and 9th Workshop on Managing the Evolution and Preservation of the Data Web co-located with 22nd International Semantic Web Conference (ISWC 2023)
Antal sider16
ForlagCEUR Workshop Proceedings
Publikationsdato2023
StatusUdgivet - 2023
BegivenhedQuWeDa 2023: 7th Workshop on Storing, Querying and Benchmarking Knowledge Graphs - Athen, Grækenland
Varighed: 6 nov. 202310 nov. 2023

Konference

KonferenceQuWeDa 2023: 7th Workshop on Storing, Querying and Benchmarking Knowledge Graphs
Land/OmrådeGrækenland
ByAthen
Periode06/11/202310/11/2023
NavnCEUR Workshop Proceedings
Vol/bind3565
ISSN1613-0073

Fingeraftryk

Dyk ned i forskningsemnerne om 'StarBench: Benchmarking RDF-star Triplestores'. Sammen danner de et unikt fingeraftryk.

Citationsformater