Efficient OLAP operations for RDF analytics

Elham Akbari Azirani; Francois Goasdoue; Ioana Manolescu; Alexandra Roatis

doi:10.1109/ICDEW.2015.7129548

Efficient OLAP operations for RDF analytics

Elham Akbari Azirani
, Francois Goasdoue
, Ioana Manolescu
, Alexandra Roatis

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

RDF is the leading data model for the Semantic Web, and dedicated query languages such as SPARQL 1.1, featuring in particular aggregation, allow extracting information from RDF graphs. A framework for analytical processing of RDF data was introduced in [1], where analytical schemas and analytical queries (cubes) are fully re-designed for heterogeneous, semantic-rich RDF graphs. In this novel analytical setting, we consider the following optimization problem: how to reuse the materialized result of a given RDF analytical query (cube) in order to compute the answer to another cube. We provide view-based rewriting algorithms for these cube transformations, and demonstrate experimentally their practical interest.

Original language	English
Title of host publication	ICDEW 2015 - 2015 IEEE 31st International Conference on Data Engineering Workshops
Publisher	IEEE Computer Society
Pages	71-76
Number of pages	6
ISBN (Electronic)	9781479984411
DOIs	https://doi.org/10.1109/ICDEW.2015.7129548
Publication status	Published - 19 Jun 2015
Event	2015 31st IEEE International Conference on Data Engineering Workshops, ICDEW 2015 - Seoul, Korea, Republic of Duration: 13 Apr 2015 → 17 Apr 2015

Publication series

Name	Proceedings - International Conference on Data Engineering
Volume	2015-June
ISSN (Print)	1084-4627

Conference

Conference	2015 31st IEEE International Conference on Data Engineering Workshops, ICDEW 2015
Country/Territory	Korea, Republic of
City	Seoul
Period	13/04/15 → 17/04/15

Access to Document

10.1109/ICDEW.2015.7129548

Cite this

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title = "Efficient OLAP operations for RDF analytics",

abstract = "RDF is the leading data model for the Semantic Web, and dedicated query languages such as SPARQL 1.1, featuring in particular aggregation, allow extracting information from RDF graphs. A framework for analytical processing of RDF data was introduced in [1], where analytical schemas and analytical queries (cubes) are fully re-designed for heterogeneous, semantic-rich RDF graphs. In this novel analytical setting, we consider the following optimization problem: how to reuse the materialized result of a given RDF analytical query (cube) in order to compute the answer to another cube. We provide view-based rewriting algorithms for these cube transformations, and demonstrate experimentally their practical interest.",

author = "Azirani, \{Elham Akbari\} and Francois Goasdoue and Ioana Manolescu and Alexandra Roatis",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 2015 31st IEEE International Conference on Data Engineering Workshops, ICDEW 2015 ; Conference date: 13-04-2015 Through 17-04-2015",

year = "2015",

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day = "19",

doi = "10.1109/ICDEW.2015.7129548",

language = "English",

series = "Proceedings - International Conference on Data Engineering",

publisher = "IEEE Computer Society",

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booktitle = "ICDEW 2015 - 2015 IEEE 31st International Conference on Data Engineering Workshops",

}

Azirani, EA, Goasdoue, F, Manolescu, I & Roatis, A 2015, Efficient OLAP operations for RDF analytics. in ICDEW 2015 - 2015 IEEE 31st International Conference on Data Engineering Workshops., 7129548, Proceedings - International Conference on Data Engineering, vol. 2015-June, IEEE Computer Society, pp. 71-76, 2015 31st IEEE International Conference on Data Engineering Workshops, ICDEW 2015, Seoul, Korea, Republic of, 13/04/15. https://doi.org/10.1109/ICDEW.2015.7129548

Efficient OLAP operations for RDF analytics. / Azirani, Elham Akbari; Goasdoue, Francois; Manolescu, Ioana et al.
ICDEW 2015 - 2015 IEEE 31st International Conference on Data Engineering Workshops. IEEE Computer Society, 2015. p. 71-76 7129548 (Proceedings - International Conference on Data Engineering; Vol. 2015-June).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Efficient OLAP operations for RDF analytics

AU - Azirani, Elham Akbari

AU - Goasdoue, Francois

AU - Manolescu, Ioana

AU - Roatis, Alexandra

PY - 2015/6/19

Y1 - 2015/6/19

N2 - RDF is the leading data model for the Semantic Web, and dedicated query languages such as SPARQL 1.1, featuring in particular aggregation, allow extracting information from RDF graphs. A framework for analytical processing of RDF data was introduced in [1], where analytical schemas and analytical queries (cubes) are fully re-designed for heterogeneous, semantic-rich RDF graphs. In this novel analytical setting, we consider the following optimization problem: how to reuse the materialized result of a given RDF analytical query (cube) in order to compute the answer to another cube. We provide view-based rewriting algorithms for these cube transformations, and demonstrate experimentally their practical interest.

AB - RDF is the leading data model for the Semantic Web, and dedicated query languages such as SPARQL 1.1, featuring in particular aggregation, allow extracting information from RDF graphs. A framework for analytical processing of RDF data was introduced in [1], where analytical schemas and analytical queries (cubes) are fully re-designed for heterogeneous, semantic-rich RDF graphs. In this novel analytical setting, we consider the following optimization problem: how to reuse the materialized result of a given RDF analytical query (cube) in order to compute the answer to another cube. We provide view-based rewriting algorithms for these cube transformations, and demonstrate experimentally their practical interest.

U2 - 10.1109/ICDEW.2015.7129548

DO - 10.1109/ICDEW.2015.7129548

M3 - Conference contribution

AN - SCOPUS:84944322602

T3 - Proceedings - International Conference on Data Engineering

SP - 71

EP - 76

BT - ICDEW 2015 - 2015 IEEE 31st International Conference on Data Engineering Workshops

PB - IEEE Computer Society

T2 - 2015 31st IEEE International Conference on Data Engineering Workshops, ICDEW 2015

Y2 - 13 April 2015 through 17 April 2015

ER -

Efficient OLAP operations for RDF analytics

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