Efficient OLAP operations for RDF analytics

Author

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

Author_Institution

INRIA, France

fYear

2015

fDate

13-17 April 2015

Firstpage

71

Lastpage

76

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.

Keywords

SQL; data analysis; data mining; data models; graph theory; semantic Web; OLAP operation; RDF analytical query; RDF analytics; RDF data; SPARQL 1.1; analytical schemas; cube transformation; data model; dedicated query languages; heterogeneous graph; information extraction; semantic Web; semantic-rich RDF graph; view-based rewriting algorithm; Blogs; Cities and towns; Context; Data warehouses; Q measurement; Resource description framework; Semantics;

fLanguage

English

Publisher

ieee

Conference_Titel

Data Engineering Workshops (ICDEW), 2015 31st IEEE International Conference on

Conference_Location

Seoul

Type

conf

DOI

10.1109/ICDEW.2015.7129548

Filename

7129548