Answering provenance-aware queries on RDF data cubes under memory budgets

Luis Galárraga; Kim Ahlstrøm; Katja Hose; Torben Bach Pedersen

doi:10.1007/978-3-030-00671-6_32

Answering provenance-aware queries on RDF data cubes under memory budgets

Luis Galárraga^*, Kim Ahlstrøm, Katja Hose, Torben Bach Pedersen

^*Kontaktforfatter

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

8 Citationer (Scopus)

Abstract

The steadily-growing popularity of semantic data on the Web and the support for aggregation queries in SPARQL 1.1 have propelled the interest in Online Analytical Processing (OLAP) and data cubes in RDF. Query processing in such settings is challenging because SPARQL OLAP queries usually contain many triple patterns with grouping and aggregation. Moreover, one important factor of query answering on Web data is its provenance, i.e., metadata about its origin. Some applications in data analytics and access control require to augment the data with provenance metadata and run queries that impose constraints on this provenance. This task is called provenance-aware query answering. In this paper, we investigate the benefit of caching some parts of an RDF cube augmented with provenance information when answering provenance-aware SPARQL queries. We propose provenance-aware caching (PAC), a caching approach based on a provenance-aware partitioning of RDF graphs, and a benefit model for RDF cubes and SPARQL queries with aggregation. Our results on real and synthetic data show that PAC outperforms significantly the LRU strategy (least recently used) and the Jena TDB native caching in terms of hit-rate and response time.

Originalsprog	Engelsk
Titel	The Semantic Web – ISWC 2018 - 17th International Semantic Web Conference, 2018, Proceedings
Redaktører	Mari Carmen Suárez-Figueroa, Valentina Presutti, Lucie-Aimee Kaffee, Elena Simperl, Marta Sabou, Denny Vrandecic, Irene Celino, Kalina Bontcheva
Antal sider	19
Forlag	Springer
Publikationsdato	1 jan. 2018
Sider	547-565
ISBN (Trykt)	9783030006709
DOI	https://doi.org/10.1007/978-3-030-00671-6_32
Status	Udgivet - 1 jan. 2018
Begivenhed	17th International Semantic Web Conference, ISWC 2018 - Monterey, USA Varighed: 8 okt. 2018 → 12 okt. 2018

Konference

Konference	17th International Semantic Web Conference, ISWC 2018
Land/Område	USA
By	Monterey
Periode	08/10/2018 → 12/10/2018

Navn	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Vol/bind	11136 LNCS
ISSN	0302-9743

Adgang til dokumentet

10.1007/978-3-030-00671-6_32

https://hal.inria.fr/hal-01931333/document

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http://www.scopus.com/inward/record.url?scp=85054795155&partnerID=8YFLogxK

Unleashing the Potential of Open Data
Hose, K.
01/01/2017 → 31/12/2021
Projekter: Projekt › Forskning
QWeb: Querying the Web of Data Easily and Efficiently
Hose, K., Montoya, G., Prado, L. A. G. D., Rouces, J., Mathiassen, K. A. M., Zervakis, E. & Setty, V.
01/02/2015 → 31/10/2019
Projekter: Projekt › Forskning

Citationsformater

Galárraga, L., Ahlstrøm, K., Hose, K., & Pedersen, T. B. (2018). Answering provenance-aware queries on RDF data cubes under memory budgets. I M. C. Suárez-Figueroa, V. Presutti, L-A. Kaffee, E. Simperl, M. Sabou, D. Vrandecic, I. Celino, & K. Bontcheva (red.), The Semantic Web – ISWC 2018 - 17th International Semantic Web Conference, 2018, Proceedings (s. 547-565). Springer. https://doi.org/10.1007/978-3-030-00671-6_32

Galárraga, Luis ; Ahlstrøm, Kim ; Hose, Katja et al. / Answering provenance-aware queries on RDF data cubes under memory budgets. The Semantic Web – ISWC 2018 - 17th International Semantic Web Conference, 2018, Proceedings. red. / Mari Carmen Suárez-Figueroa ; Valentina Presutti ; Lucie-Aimee Kaffee ; Elena Simperl ; Marta Sabou ; Denny Vrandecic ; Irene Celino ; Kalina Bontcheva. Springer, 2018. s. 547-565 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bind 11136 LNCS).

@inproceedings{7d8b1146803c4e8bb91f9a9c5b93d058,

title = "Answering provenance-aware queries on RDF data cubes under memory budgets",

abstract = "The steadily-growing popularity of semantic data on the Web and the support for aggregation queries in SPARQL 1.1 have propelled the interest in Online Analytical Processing (OLAP) and data cubes in RDF. Query processing in such settings is challenging because SPARQL OLAP queries usually contain many triple patterns with grouping and aggregation. Moreover, one important factor of query answering on Web data is its provenance, i.e., metadata about its origin. Some applications in data analytics and access control require to augment the data with provenance metadata and run queries that impose constraints on this provenance. This task is called provenance-aware query answering. In this paper, we investigate the benefit of caching some parts of an RDF cube augmented with provenance information when answering provenance-aware SPARQL queries. We propose provenance-aware caching (PAC), a caching approach based on a provenance-aware partitioning of RDF graphs, and a benefit model for RDF cubes and SPARQL queries with aggregation. Our results on real and synthetic data show that PAC outperforms significantly the LRU strategy (least recently used) and the Jena TDB native caching in terms of hit-rate and response time.",

author = "Luis Gal{\'a}rraga and Kim Ahlstr{\o}m and Katja Hose and Pedersen, {Torben Bach}",

year = "2018",

month = jan,

day = "1",

doi = "10.1007/978-3-030-00671-6_32",

language = "English",

isbn = "9783030006709",

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

publisher = "Springer",

pages = "547--565",

editor = "Su{\'a}rez-Figueroa, {Mari Carmen} and Valentina Presutti and Lucie-Aimee Kaffee and Elena Simperl and Marta Sabou and Denny Vrandecic and Irene Celino and Kalina Bontcheva",

booktitle = "The Semantic Web – ISWC 2018 - 17th International Semantic Web Conference, 2018, Proceedings",

address = "Germany",

note = "17th International Semantic Web Conference, ISWC 2018 ; Conference date: 08-10-2018 Through 12-10-2018",

}

Galárraga, L, Ahlstrøm, K, Hose, K & Pedersen, TB 2018, Answering provenance-aware queries on RDF data cubes under memory budgets. i MC Suárez-Figueroa, V Presutti, L-A Kaffee, E Simperl, M Sabou, D Vrandecic, I Celino & K Bontcheva (red), The Semantic Web – ISWC 2018 - 17th International Semantic Web Conference, 2018, Proceedings. Springer, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), bind 11136 LNCS, s. 547-565, 17th International Semantic Web Conference, ISWC 2018, Monterey, USA, 08/10/2018. https://doi.org/10.1007/978-3-030-00671-6_32

Answering provenance-aware queries on RDF data cubes under memory budgets. / Galárraga, Luis; Ahlstrøm, Kim; Hose, Katja et al.
The Semantic Web – ISWC 2018 - 17th International Semantic Web Conference, 2018, Proceedings. red. / Mari Carmen Suárez-Figueroa; Valentina Presutti; Lucie-Aimee Kaffee; Elena Simperl; Marta Sabou; Denny Vrandecic; Irene Celino; Kalina Bontcheva. Springer, 2018. s. 547-565 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bind 11136 LNCS).

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

TY - GEN

T1 - Answering provenance-aware queries on RDF data cubes under memory budgets

AU - Galárraga, Luis

AU - Ahlstrøm, Kim

AU - Hose, Katja

AU - Pedersen, Torben Bach

PY - 2018/1/1

Y1 - 2018/1/1

N2 - The steadily-growing popularity of semantic data on the Web and the support for aggregation queries in SPARQL 1.1 have propelled the interest in Online Analytical Processing (OLAP) and data cubes in RDF. Query processing in such settings is challenging because SPARQL OLAP queries usually contain many triple patterns with grouping and aggregation. Moreover, one important factor of query answering on Web data is its provenance, i.e., metadata about its origin. Some applications in data analytics and access control require to augment the data with provenance metadata and run queries that impose constraints on this provenance. This task is called provenance-aware query answering. In this paper, we investigate the benefit of caching some parts of an RDF cube augmented with provenance information when answering provenance-aware SPARQL queries. We propose provenance-aware caching (PAC), a caching approach based on a provenance-aware partitioning of RDF graphs, and a benefit model for RDF cubes and SPARQL queries with aggregation. Our results on real and synthetic data show that PAC outperforms significantly the LRU strategy (least recently used) and the Jena TDB native caching in terms of hit-rate and response time.

AB - The steadily-growing popularity of semantic data on the Web and the support for aggregation queries in SPARQL 1.1 have propelled the interest in Online Analytical Processing (OLAP) and data cubes in RDF. Query processing in such settings is challenging because SPARQL OLAP queries usually contain many triple patterns with grouping and aggregation. Moreover, one important factor of query answering on Web data is its provenance, i.e., metadata about its origin. Some applications in data analytics and access control require to augment the data with provenance metadata and run queries that impose constraints on this provenance. This task is called provenance-aware query answering. In this paper, we investigate the benefit of caching some parts of an RDF cube augmented with provenance information when answering provenance-aware SPARQL queries. We propose provenance-aware caching (PAC), a caching approach based on a provenance-aware partitioning of RDF graphs, and a benefit model for RDF cubes and SPARQL queries with aggregation. Our results on real and synthetic data show that PAC outperforms significantly the LRU strategy (least recently used) and the Jena TDB native caching in terms of hit-rate and response time.

UR - http://www.scopus.com/inward/record.url?scp=85054795155&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-00671-6_32

DO - 10.1007/978-3-030-00671-6_32

M3 - Article in proceeding

AN - SCOPUS:85054795155

SN - 9783030006709

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

SP - 547

EP - 565

BT - The Semantic Web – ISWC 2018 - 17th International Semantic Web Conference, 2018, Proceedings

A2 - Suárez-Figueroa, Mari Carmen

A2 - Presutti, Valentina

A2 - Kaffee, Lucie-Aimee

A2 - Simperl, Elena

A2 - Sabou, Marta

A2 - Vrandecic, Denny

A2 - Celino, Irene

A2 - Bontcheva, Kalina

PB - Springer

T2 - 17th International Semantic Web Conference, ISWC 2018

Y2 - 8 October 2018 through 12 October 2018

ER -

Galárraga L, Ahlstrøm K, Hose K , Pedersen TB. Answering provenance-aware queries on RDF data cubes under memory budgets. I Suárez-Figueroa MC, Presutti V, Kaffee L-A, Simperl E, Sabou M, Vrandecic D, Celino I, Bontcheva K, red., The Semantic Web – ISWC 2018 - 17th International Semantic Web Conference, 2018, Proceedings. Springer. 2018. s. 547-565. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bind 11136 LNCS). doi: 10.1007/978-3-030-00671-6_32

Answering provenance-aware queries on RDF data cubes under memory budgets

Abstract

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Unleashing the Potential of Open Data

QWeb: Querying the Web of Data Easily and Efficiently

Citationsformater