HDTQ: Managing RDF Datasets in Compressed Space

Javier David Fernandez Garcia; Miguel A. Martínez-Prieto; Axel Polleres; Julian Reindorf

doi:10.1007/978-3-319-93417-4_13

HDTQ: Managing RDF Datasets in Compressed Space

Javier David Fernandez Garcia, Miguel A. Martínez-Prieto, Axel Polleres, Julian Reindorf

Data, Process and Knowledge Management (Polleres)

Publikation: Beitrag in Buch/Konferenzband › Beitrag in Konferenzband

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Abstract

HDT (Header-Dictionary-Triples) is a compressed representation of RDF data that supports retrieval features without prior decompression. Yet, RDF datasets often contain additional graph information, such as the origin, version or validity time of a triple. Traditional HDT is not capable of handling this additional parameter(s). This work introduces HDTQ (HDT Quads), an extension of HDT that is able to represent quadruples (or quads) while still being highly compact and queryable. Two HDTQ-based approaches are introduced: Annotated Triples and Annotated Graphs, and their performance is compared to the leading open-source RDF stores on the market. Results show that HDTQ achieves the best compression rates and is a competitive alternative to well-established systems.

Originalsprache	Englisch
Titel des Sammelwerks	The Semantic Web. Proceedings of ESWC 2018
Herausgeber*innen	Springer International Publishing
Erscheinungsort	Cham
Verlag	Springer International Publishing
Seiten	191-208
ISBN (Print)	978-3-319-93417-4
DOIs	https://doi.org/10.1007/978-3-319-93417-4_13
Publikationsstatus	Veröffentlicht - 2018

Österreichische Systematik der Wissenschaftszweige (ÖFOS)

102001 Artificial Intelligence
502050 Wirtschaftsinformatik
102015 Informationssysteme

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10.1007/978-3-319-93417-4_13Lizenz: Nicht angegeben

HDTQAkzeptiertes Autor*inn*enmanuskript, 846 KBLizenz: Sonstige

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Katalog der Universitätsbibliothek

Cyber-Physical Social Systems for City-wide Infrastructures
Cecconi, A., Di Ciccio, C., Fernandez Garcia, J. D., Mendling, J. & Polleres, A.
1/10/17 → 31/03/20
Projekt: Forschungsförderung
SPECIAL
Kirrane, S., Drozd, O., Fernandez Garcia, J. D., Havur, G., Polleres, A. & Spiekermann-Hoff, S.
1/01/17 → 31/12/19
Projekt: Forschungsförderung

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title = "HDTQ: Managing RDF Datasets in Compressed Space",

abstract = "HDT (Header-Dictionary-Triples) is a compressed representation of RDF data that supports retrieval features without prior decompression. Yet, RDF datasets often contain additional graph information, such as the origin, version or validity time of a triple. Traditional HDT is not capable of handling this additional parameter(s). This work introduces HDTQ (HDT Quads), an extension of HDT that is able to represent quadruples (or quads) while still being highly compact and queryable. Two HDTQ-based approaches are introduced: Annotated Triples and Annotated Graphs, and their performance is compared to the leading open-source RDF stores on the market. Results show that HDTQ achieves the best compression rates and is a competitive alternative to well-established systems.",

author = "{Fernandez Garcia}, {Javier David} and Mart{\'i}nez-Prieto, {Miguel A.} and Axel Polleres and Julian Reindorf",

year = "2018",

doi = "10.1007/978-3-319-93417-4_13",

language = "English",

isbn = "978-3-319-93417-4",

pages = "191--208",

editor = "{Springer International Publishing}",

booktitle = "The Semantic Web. Proceedings of ESWC 2018",

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TY - GEN

T1 - HDTQ: Managing RDF Datasets in Compressed Space

AU - Fernandez Garcia, Javier David

AU - Martínez-Prieto, Miguel A.

AU - Polleres, Axel

AU - Reindorf, Julian

PY - 2018

Y1 - 2018

N2 - HDT (Header-Dictionary-Triples) is a compressed representation of RDF data that supports retrieval features without prior decompression. Yet, RDF datasets often contain additional graph information, such as the origin, version or validity time of a triple. Traditional HDT is not capable of handling this additional parameter(s). This work introduces HDTQ (HDT Quads), an extension of HDT that is able to represent quadruples (or quads) while still being highly compact and queryable. Two HDTQ-based approaches are introduced: Annotated Triples and Annotated Graphs, and their performance is compared to the leading open-source RDF stores on the market. Results show that HDTQ achieves the best compression rates and is a competitive alternative to well-established systems.

AB - HDT (Header-Dictionary-Triples) is a compressed representation of RDF data that supports retrieval features without prior decompression. Yet, RDF datasets often contain additional graph information, such as the origin, version or validity time of a triple. Traditional HDT is not capable of handling this additional parameter(s). This work introduces HDTQ (HDT Quads), an extension of HDT that is able to represent quadruples (or quads) while still being highly compact and queryable. Two HDTQ-based approaches are introduced: Annotated Triples and Annotated Graphs, and their performance is compared to the leading open-source RDF stores on the market. Results show that HDTQ achieves the best compression rates and is a competitive alternative to well-established systems.

U2 - 10.1007/978-3-319-93417-4_13

DO - 10.1007/978-3-319-93417-4_13

M3 - Contribution to conference proceedings

SN - 978-3-319-93417-4

SP - 191

EP - 208

BT - The Semantic Web. Proceedings of ESWC 2018

A2 - Springer International Publishing, null

PB - Springer International Publishing

CY - Cham

ER -

HDTQ: Managing RDF Datasets in Compressed Space

Abstract

Österreichische Systematik der Wissenschaftszweige (ÖFOS)

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Projekte

Cyber-Physical Social Systems for City-wide Infrastructures

SPECIAL

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