Geodesic
SRDF QDAG: An Efficient End-to-End RDF Data Management when Graph Exploration Meets Spatial Processing
Computer Science and Information Systems, Tome 20 (2023) no. 4.

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The popularity of RDF has led to the creation of several datasets (e.g., Yago, DBPedia) with different natures (graph, temporal, spatial). Different extensions have also been proposed for SPARQL language to provide appropriate processing. The best known is GeoSparql, that allows the integration of a set of spatial operators. In this paper, we propose new strategies to support such operators within a particular TripleStore, named RDF QDAG, that relies on graph fragmentation and exploration and guarantees a good compromise between scalability and performance. Our proposal covers the different TripleStore components (Storage, evaluation, optimization). We evaluated our proposal using spatial queries with real RDF data, and we also compared performance with the latest version of a popular commercial TripleStore. The first results demonstrate the relevance of our proposal and how to achieve an average gain of performance of 28% by choosing the right evaluation strategies to use. Based on these results, we proposed to extend the RDF QDAG optimizer to dynamically select the evaluation strategy to use depending on the query. Then, we show also that our proposal yields the best strategy for most queries.
Keywords: RDF, Graph Data, Spatial Data, TripleStore, Graph exploration, Optimization 
@article{CSIS_2023_20_4_a4,
     author = {Houssameddine Yousfi and Amin Mesmoudi and Allel Hadjali and Houcine Matallah and Seif-Eddine Benkabou},
     title = {SRDF {QDAG:} {An} {Efficient} {End-to-End} {RDF} {Data} {Management} when {Graph} {Exploration} {Meets} {Spatial} {Processing}},
     journal = {Computer Science and Information Systems},
     publisher = {mathdoc},
     volume = {20},
     number = {4},
     year = {2023},
     url = {http://geodesic.mathdoc.fr/item/CSIS_2023_20_4_a4/}
}
TY  - JOUR
AU  - Houssameddine Yousfi
AU  - Amin Mesmoudi
AU  - Allel Hadjali
AU  - Houcine Matallah
AU  - Seif-Eddine Benkabou
TI  - SRDF QDAG: An Efficient End-to-End RDF Data Management when Graph Exploration Meets Spatial Processing
JO  - Computer Science and Information Systems
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%A Houssameddine Yousfi
%A Amin Mesmoudi
%A Allel Hadjali
%A Houcine Matallah
%A Seif-Eddine Benkabou
%T SRDF QDAG: An Efficient End-to-End RDF Data Management when Graph Exploration Meets Spatial Processing
%J Computer Science and Information Systems
%D 2023
%V 20
%N 4
%I mathdoc
%U http://geodesic.mathdoc.fr/item/CSIS_2023_20_4_a4/
%F CSIS_2023_20_4_a4
Houssameddine Yousfi; Amin Mesmoudi; Allel Hadjali; Houcine Matallah; Seif-Eddine Benkabou. SRDF QDAG: An Efficient End-to-End RDF Data Management when Graph Exploration Meets Spatial Processing. Computer Science and Information Systems, Tome 20 (2023) no. 4. http://geodesic.mathdoc.fr/item/CSIS_2023_20_4_a4/