SMART-KG: Hybrid Shipping for SPARQL Querying on the Web

Amr Azzam; Javier David Fernandez Garcia; Maribel Acosta; Martin Beno; Axel Polleres

doi:10.1145/3366423.3380177

SMART-KG: Hybrid Shipping for SPARQL Querying on the Web

Amr Azzam, Javier David Fernandez Garcia, Maribel Acosta, Martin Beno, Axel Polleres

Institute for Data, Process and Knowledge Management (AE Polleres)

Publication: Chapter in book/Conference proceeding › Contribution to conference proceedings

Abstract

While Linked Data (LD) provides standards for publishing (RDF) and (SPARQL) querying Knowledge Graphs (KGs) on the Web, serving, accessing and processing such open, decentralized KGs is often practically impossible, as query timeouts on publicly available SPARQL endpoints show. Alternative solutions such as Triple Pattern Fragments (TPF) attempt to tackle the problem of availability by pushing query processing workload to the client side, but suffer from unnecessary transfer of irrelevant data on complex queries with large intermediate results. In this paper we present smart-KG, a novel approach to share the load between servers and clients, while significantly reducing data transfer volume, by combining TPF with shipping compressed KG partitions. Our evaluations show that smart-KG outperforms state-of-the-art client-side solutions and increases server-side availability towards more cost-effective and balanced hosting of open and decentralized KGs.

Original language	English
Title of host publication	Proceedings of The Web Conference 2020
Editors	Association for Computing Machinery
Place of Publication	New York
Pages	984 - 994
DOIs	https://doi.org/10.1145/3366423.3380177
Publication status	Published - 2020

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Cite this

@inproceedings{98349442cd6a4fa8be05467585591b5f,

title = "SMART-KG: Hybrid Shipping for SPARQL Querying on the Web",

abstract = "While Linked Data (LD) provides standards for publishing (RDF) and (SPARQL) querying Knowledge Graphs (KGs) on the Web, serving, accessing and processing such open, decentralized KGs is often practically impossible, as query timeouts on publicly available SPARQL endpoints show. Alternative solutions such as Triple Pattern Fragments (TPF) attempt to tackle the problem of availability by pushing query processing workload to the client side, but suffer from unnecessary transfer of irrelevant data on complex queries with large intermediate results. In this paper we present smart-KG, a novel approach to share the load between servers and clients, while significantly reducing data transfer volume, by combining TPF with shipping compressed KG partitions. Our evaluations show that smart-KG outperforms state-of-the-art client-side solutions and increases server-side availability towards more cost-effective and balanced hosting of open and decentralized KGs.",

author = "Amr Azzam and {Fernandez Garcia}, {Javier David} and Maribel Acosta and Martin Beno and Axel Polleres",

year = "2020",

doi = "10.1145/3366423.3380177",

language = "English",

isbn = "978-1-4503-7023-3",

pages = "984 -- 994",

editor = "{Association for Computing Machinery}",

booktitle = "Proceedings of The Web Conference 2020",

}

TY - GEN

T1 - SMART-KG: Hybrid Shipping for SPARQL Querying on the Web

AU - Azzam, Amr

AU - Fernandez Garcia, Javier David

AU - Acosta, Maribel

AU - Beno, Martin

AU - Polleres, Axel

PY - 2020

Y1 - 2020

N2 - While Linked Data (LD) provides standards for publishing (RDF) and (SPARQL) querying Knowledge Graphs (KGs) on the Web, serving, accessing and processing such open, decentralized KGs is often practically impossible, as query timeouts on publicly available SPARQL endpoints show. Alternative solutions such as Triple Pattern Fragments (TPF) attempt to tackle the problem of availability by pushing query processing workload to the client side, but suffer from unnecessary transfer of irrelevant data on complex queries with large intermediate results. In this paper we present smart-KG, a novel approach to share the load between servers and clients, while significantly reducing data transfer volume, by combining TPF with shipping compressed KG partitions. Our evaluations show that smart-KG outperforms state-of-the-art client-side solutions and increases server-side availability towards more cost-effective and balanced hosting of open and decentralized KGs.

AB - While Linked Data (LD) provides standards for publishing (RDF) and (SPARQL) querying Knowledge Graphs (KGs) on the Web, serving, accessing and processing such open, decentralized KGs is often practically impossible, as query timeouts on publicly available SPARQL endpoints show. Alternative solutions such as Triple Pattern Fragments (TPF) attempt to tackle the problem of availability by pushing query processing workload to the client side, but suffer from unnecessary transfer of irrelevant data on complex queries with large intermediate results. In this paper we present smart-KG, a novel approach to share the load between servers and clients, while significantly reducing data transfer volume, by combining TPF with shipping compressed KG partitions. Our evaluations show that smart-KG outperforms state-of-the-art client-side solutions and increases server-side availability towards more cost-effective and balanced hosting of open and decentralized KGs.

U2 - 10.1145/3366423.3380177

DO - 10.1145/3366423.3380177

M3 - Contribution to conference proceedings

SN - 978-1-4503-7023-3

SP - 984

EP - 994

BT - Proceedings of The Web Conference 2020

A2 - Association for Computing Machinery, null

CY - New York

ER -