A survey of RDF management technologies and benchmark datasets

Zhengyu Pan; Tao Zhu; Hong Liu; Huansheng Ning

doi:10.1007/s12652-018-0876-2

A survey of RDF management technologies and benchmark datasets

Zhengyu Pan
, Tao Zhu
, Hong Liu
, Huansheng Ning^*

^*Corresponding author for this work

Software Engineering Institute

Research output: Contribution to journal › Article › peer-review

21 Scopus citations

Abstract

With the fast development of semantic web and some other areas, the amount of resource description framework (RDF) data has increased significantly. How to efficiently manage these masses of RDF data has become a challenging task, and has attracted many scholars to research. This paper introduces the state-of-the-art of the RDF storage and query technologies according to some classification criteria. In addition, several prevailing benchmark datasets are introduced and compared. Finally, research challenges and opportunities in future are discussed.

Original language	English
Pages (from-to)	1693-1704
Number of pages	12
Journal	Journal of Ambient Intelligence and Humanized Computing
Volume	9
Issue number	5
DOIs	https://doi.org/10.1007/s12652-018-0876-2
State	Published - 1 Oct 2018

Keywords

RDF
RDF benchmark dataset
RDF management
SPARQL
Semantic web

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10.1007/s12652-018-0876-2

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abstract = "With the fast development of semantic web and some other areas, the amount of resource description framework (RDF) data has increased significantly. How to efficiently manage these masses of RDF data has become a challenging task, and has attracted many scholars to research. This paper introduces the state-of-the-art of the RDF storage and query technologies according to some classification criteria. In addition, several prevailing benchmark datasets are introduced and compared. Finally, research challenges and opportunities in future are discussed.",

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author = "Zhengyu Pan and Tao Zhu and Hong Liu and Huansheng Ning",

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AU - Zhu, Tao

AU - Liu, Hong

AU - Ning, Huansheng

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N2 - With the fast development of semantic web and some other areas, the amount of resource description framework (RDF) data has increased significantly. How to efficiently manage these masses of RDF data has become a challenging task, and has attracted many scholars to research. This paper introduces the state-of-the-art of the RDF storage and query technologies according to some classification criteria. In addition, several prevailing benchmark datasets are introduced and compared. Finally, research challenges and opportunities in future are discussed.

AB - With the fast development of semantic web and some other areas, the amount of resource description framework (RDF) data has increased significantly. How to efficiently manage these masses of RDF data has become a challenging task, and has attracted many scholars to research. This paper introduces the state-of-the-art of the RDF storage and query technologies according to some classification criteria. In addition, several prevailing benchmark datasets are introduced and compared. Finally, research challenges and opportunities in future are discussed.

KW - RDF

KW - RDF benchmark dataset

KW - RDF management

KW - SPARQL

KW - Semantic web

UR - https://www.scopus.com/pages/publications/85049573222

U2 - 10.1007/s12652-018-0876-2

DO - 10.1007/s12652-018-0876-2

M3 - 文章

AN - SCOPUS:85049573222

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JO - Journal of Ambient Intelligence and Humanized Computing

JF - Journal of Ambient Intelligence and Humanized Computing

IS - 5

ER -

A survey of RDF management technologies and benchmark datasets

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Keywords

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