GLENDA: Querying RDF Archives with Full SPARQL

Olivier Pelgrin; Ruben Taelman; Luis Galárraga; Katja Hose

doi:10.1007/978-3-031-43458-7_14

GLENDA: Querying RDF Archives with Full SPARQL

Olivier Pelgrin^*, Ruben Taelman, Luis Galárraga, Katja Hose

^*Corresponding author for this work

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

Abstract

The dynamicity of semantic data has propelled the research on RDF Archiving, i.e., the task of storing and making the full history of large RDF datasets accessible. However, existing archiving techniques fail to scale when confronted with very large RDF datasets and support only simple SPARQL queries. In this demonstration, we therefore showcase GLENDA, a system that can run full SPARQL 1.1 compliant queries over large RDF archives. We achieve this through a multi-snapshot change-based storage architecture that we interface using the Comunica query engine. Thanks to this integration we demonstrate that fast SPARQL query processing over multiple versions of a knowledge graph is possible. Moreover, our demonstration provides different statistics about the history of RDF datasets that can be useful for tasks beyond querying and by providing insights about the evolution dynamics of the data.

Original language	English
Title of host publication	The Semantic Web : ESWC 2023 Satellite Events, Proceedings
Editors	Catia Pesquita, Hala Skaf-Molli, Vasilis Efthymiou, Sabrina Kirrane, Axel Ngonga, Diego Collarana, Renato Cerqueira, Mehwish Alam, Cassia Trojahn, Sven Hertling
Number of pages	6
Publisher	Springer Science+Business Media
Publication date	2023
Pages	75-80
ISBN (Print)	978-3-031-43457-0
ISBN (Electronic)	978-3-031-43458-7
DOIs	https://doi.org/10.1007/978-3-031-43458-7_14
Publication status	Published - 2023
Event	20th Extended Semantic Web Conference, ESWC 2023 - Hersonissos, Greece Duration: 28 May 2023 → 1 Jun 2023

Conference

Conference	20th Extended Semantic Web Conference, ESWC 2023
Country/Territory	Greece
City	Hersonissos
Period	28/05/2023 → 01/06/2023

Series	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13998 LNCS
ISSN	0302-9743

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG. 2023.

Keywords

RDF
RDF archives
SPARQL
temporal queries
time-travel queries
versioned queries
versioning

Access to Document

10.1007/978-3-031-43458-7_14

AUB Link

Search for the material in Aalborg University Library's search engine

Cite this

Pelgrin, O., Taelman, R., Galárraga, L., & Hose, K. (2023). GLENDA: Querying RDF Archives with Full SPARQL. In C. Pesquita, H. Skaf-Molli, V. Efthymiou, S. Kirrane, A. Ngonga, D. Collarana, R. Cerqueira, M. Alam, C. Trojahn, & S. Hertling (Eds.), The Semantic Web: ESWC 2023 Satellite Events, Proceedings (pp. 75-80). Springer Science+Business Media. https://doi.org/10.1007/978-3-031-43458-7_14

Pelgrin, Olivier ; Taelman, Ruben ; Galárraga, Luis et al. / GLENDA : Querying RDF Archives with Full SPARQL. The Semantic Web: ESWC 2023 Satellite Events, Proceedings. editor / Catia Pesquita ; Hala Skaf-Molli ; Vasilis Efthymiou ; Sabrina Kirrane ; Axel Ngonga ; Diego Collarana ; Renato Cerqueira ; Mehwish Alam ; Cassia Trojahn ; Sven Hertling. Springer Science+Business Media, 2023. pp. 75-80 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 13998 LNCS).

@inproceedings{ac6a7c497e754df7b87cf805721fada2,

title = "GLENDA: Querying RDF Archives with Full SPARQL",

abstract = "The dynamicity of semantic data has propelled the research on RDF Archiving, i.e., the task of storing and making the full history of large RDF datasets accessible. However, existing archiving techniques fail to scale when confronted with very large RDF datasets and support only simple SPARQL queries. In this demonstration, we therefore showcase GLENDA, a system that can run full SPARQL 1.1 compliant queries over large RDF archives. We achieve this through a multi-snapshot change-based storage architecture that we interface using the Comunica query engine. Thanks to this integration we demonstrate that fast SPARQL query processing over multiple versions of a knowledge graph is possible. Moreover, our demonstration provides different statistics about the history of RDF datasets that can be useful for tasks beyond querying and by providing insights about the evolution dynamics of the data.",

keywords = "RDF, RDF archives, SPARQL, temporal queries, time-travel queries, versioned queries, versioning",

author = "Olivier Pelgrin and Ruben Taelman and Luis Gal{\'a}rraga and Katja Hose",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG. 2023.; 20th Extended Semantic Web Conference, ESWC 2023 ; Conference date: 28-05-2023 Through 01-06-2023",

year = "2023",

doi = "10.1007/978-3-031-43458-7_14",

language = "English",

isbn = "978-3-031-43457-0",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Science+Business Media",

pages = "75--80",

editor = "Catia Pesquita and Hala Skaf-Molli and Vasilis Efthymiou and Sabrina Kirrane and Axel Ngonga and Diego Collarana and Renato Cerqueira and Mehwish Alam and Cassia Trojahn and Sven Hertling",

booktitle = "The Semantic Web",

address = "United States",

}

Pelgrin, O, Taelman, R, Galárraga, L & Hose, K 2023, GLENDA: Querying RDF Archives with Full SPARQL. in C Pesquita, H Skaf-Molli, V Efthymiou, S Kirrane, A Ngonga, D Collarana, R Cerqueira, M Alam, C Trojahn & S Hertling (eds), The Semantic Web: ESWC 2023 Satellite Events, Proceedings. Springer Science+Business Media, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13998 LNCS, pp. 75-80, 20th Extended Semantic Web Conference, ESWC 2023, Hersonissos, Greece, 28/05/2023. https://doi.org/10.1007/978-3-031-43458-7_14

GLENDA: Querying RDF Archives with Full SPARQL. / Pelgrin, Olivier; Taelman, Ruben; Galárraga, Luis et al.
The Semantic Web: ESWC 2023 Satellite Events, Proceedings. ed. / Catia Pesquita; Hala Skaf-Molli; Vasilis Efthymiou; Sabrina Kirrane; Axel Ngonga; Diego Collarana; Renato Cerqueira; Mehwish Alam; Cassia Trojahn; Sven Hertling. Springer Science+Business Media, 2023. p. 75-80 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 13998 LNCS).

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

TY - GEN

T1 - GLENDA

T2 - 20th Extended Semantic Web Conference, ESWC 2023

AU - Pelgrin, Olivier

AU - Taelman, Ruben

AU - Galárraga, Luis

AU - Hose, Katja

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG. 2023.

PY - 2023

Y1 - 2023

N2 - The dynamicity of semantic data has propelled the research on RDF Archiving, i.e., the task of storing and making the full history of large RDF datasets accessible. However, existing archiving techniques fail to scale when confronted with very large RDF datasets and support only simple SPARQL queries. In this demonstration, we therefore showcase GLENDA, a system that can run full SPARQL 1.1 compliant queries over large RDF archives. We achieve this through a multi-snapshot change-based storage architecture that we interface using the Comunica query engine. Thanks to this integration we demonstrate that fast SPARQL query processing over multiple versions of a knowledge graph is possible. Moreover, our demonstration provides different statistics about the history of RDF datasets that can be useful for tasks beyond querying and by providing insights about the evolution dynamics of the data.

AB - The dynamicity of semantic data has propelled the research on RDF Archiving, i.e., the task of storing and making the full history of large RDF datasets accessible. However, existing archiving techniques fail to scale when confronted with very large RDF datasets and support only simple SPARQL queries. In this demonstration, we therefore showcase GLENDA, a system that can run full SPARQL 1.1 compliant queries over large RDF archives. We achieve this through a multi-snapshot change-based storage architecture that we interface using the Comunica query engine. Thanks to this integration we demonstrate that fast SPARQL query processing over multiple versions of a knowledge graph is possible. Moreover, our demonstration provides different statistics about the history of RDF datasets that can be useful for tasks beyond querying and by providing insights about the evolution dynamics of the data.

KW - RDF

KW - RDF archives

KW - SPARQL

KW - temporal queries

KW - time-travel queries

KW - versioned queries

KW - versioning

UR - http://www.scopus.com/inward/record.url?scp=85175970873&partnerID=8YFLogxK

U2 - 10.1007/978-3-031-43458-7_14

DO - 10.1007/978-3-031-43458-7_14

M3 - Article in proceeding

AN - SCOPUS:85175970873

SN - 978-3-031-43457-0

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 75

EP - 80

BT - The Semantic Web

A2 - Pesquita, Catia

A2 - Skaf-Molli, Hala

A2 - Efthymiou, Vasilis

A2 - Kirrane, Sabrina

A2 - Ngonga, Axel

A2 - Collarana, Diego

A2 - Cerqueira, Renato

A2 - Alam, Mehwish

A2 - Trojahn, Cassia

A2 - Hertling, Sven

PB - Springer Science+Business Media

Y2 - 28 May 2023 through 1 June 2023

ER -

Pelgrin O, Taelman R, Galárraga L, Hose K. GLENDA: Querying RDF Archives with Full SPARQL. In Pesquita C, Skaf-Molli H, Efthymiou V, Kirrane S, Ngonga A, Collarana D, Cerqueira R, Alam M, Trojahn C, Hertling S, editors, The Semantic Web: ESWC 2023 Satellite Events, Proceedings. Springer Science+Business Media. 2023. p. 75-80. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 13998 LNCS). doi: 10.1007/978-3-031-43458-7_14