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Lusail: A System for Querying Linked Data at Scale

Summary: Lusail: scalable federated SPARQL for geo-distributed RDF graphs. Instance-aware query rewriting pushes computation to local endpoints, exposes parallelism, and enables runtime scheduling to boost scalability; demonstrates orders-of-magnitude speedups over state-of-the-art systems. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h585eab8bff1c05eb
Venue
VLDB
Year
2018
Pagerank
4.9793485e-05
Overall Rank
12,256 | 17.60%
DOI
10.1145/3164135.3164144

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

BibTeX Citation

@article{abdelaziz_vldb18,
        title = {{Lusail: A System for Querying Linked Data at Scale}},
        author = {Abdelaziz, Ibrahim and Mansour, Essam and Ouzzani, Mourad and Aboulnaga, Ashraf and Kalnis, Panos},
        journal = {PVLDB},
        series = {{VLDB} '18},
        volume = {11},
        number = {4},
        pages = {485--498},
        doi = {10.1145/3164135.3164144},
        url = {https://doi.org/10.1145/3164135.3164144},
        year = {2018}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
8,432 A Demonstration of MAGiQ: Matrix Algebra Approach for Solving RDF Graph Queries 2018 VLDB 5.3350162e-05
10,213 A Universal Question-Answering Platform for Knowledge Graphs 2023 SIGMOD 5.0596605e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 10 of 10 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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