Jena: implementing the semantic web recommendations
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Scalable semantic web data management using vertical partitioning
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Hexastore: sextuple indexing for semantic web data management
Proceedings of the VLDB Endowment
Column-store support for RDF data management: not all swans are white
Proceedings of the VLDB Endowment
An Experimental Comparison of RDF Data Management Approaches in a SPARQL Benchmark Scenario
ISWC '08 Proceedings of the 7th International Conference on The Semantic Web
Scalable indexing of RDF graphs for efficient join processing
Proceedings of the 18th ACM conference on Information and knowledge management
The RDF-3X engine for scalable management of RDF data
The VLDB Journal — The International Journal on Very Large Data Bases
YARS2: a federated repository for querying graph structured data from the web
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
Database foundations for scalable RDF processing
RW'11 Proceedings of the 7th international conference on Reasoning web: semantic technologies for the web of data
Database techniques for linked data management
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
FoXtrot: Distributed structural and value XML filtering
ACM Transactions on the Web (TWEB)
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The Semantic Web, which represents a web of knowledge, offers new opportunities to search for knowledge and information. To harvest such search power requires robust and scalable data repositories that can store RDF data and support efficient evaluation of SPARQL queries. Most of the existing RDF storage techniques rely on relation model and relational database technologies for these tasks. They either keep the RDF data as triples, or decompose it into multiple relations. The mis-match between the graph model of the RDF data and the rigid 2D tables of relational model jeopardizes the scalability of such repositories and frequently renders a repository inefficient for some types of data and queries. We propose to decompose RDF graph into a forest of semantically correlated XML trees, store them in an XML repository and rewrite SPARQL queries into XPath/XQuery queries to be evaluated in the XML repository. In this paper, we discuss the basic idea of RDF-to-XML decomposition and the criteria of such decomposition in term of correctness, redundancy and query efficiency, then propose two RDF-to-XML decomposition algorithms based on these criteria. Our experimental evaluation results illustrate that our approach is capable of improving both the storage efficiency and query processing efficiency compared to the existing RDF techniques.