2015/03/10 by Gabriela Montoya, Montoya, Gabriela, Hala Skaf-Molli +7
Computer Science · Decision Sciences · #Advanced Database Systems and Queries #Data Quality and Management #Databases (cs.DB) #FOS: Computer and information sciences #Semantic Web and Ontologies #cs.DB
paper · pdf · doi:10.48550/arxiv.1503.02940
arxiv created 2015/03/10 · openalex publication_date 2015/03/10 · arxiv updated 2015/03/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Low reliability and availability of public SPARQL endpoints prevent real-world applications from exploiting all the potential of these querying infras-tructures. Fragmenting data on servers can improve data availability but degrades performance. Replicating fragments can offer new tradeoff between performance and availability. We propose FEDRA, a framework for querying Linked Data that takes advantage of client-side data replication, and performs a source selection algorithm that aims to reduce the number of selected public SPARQL endpoints, execution time, and intermediate results. FEDRA has been implemented on the state-of-the-art query engines ANAPSID and FedX, and empirically evaluated on a variety of real-world datasets.