Supporting Decentralized SPARQL Queries in an Ad-Hoc Semantic Web Data Sharing System

Jing Zhou, Gregor v. Bochmann, Zhongzhi Shi


Sharing the Semantic Web data encoded in Resource Description Framework (RDF) triples from proprietary datasets scattered around the Internet, calls for efficient support from distributed computing technologies. The highly dynamic ad-hoc settings that would be pervasive for Semantic Web data sharing among personal users in the future, however, pose even more demanding challenges for the enabling technologies. We extend previous work on a hybrid peer-to-peer (P2P) architecture for an ad-hoc Semantic Web data sharing system which better models the data sharing scenario by allowing data to be maintained by its own providers and exhibits satisfactory scalability owing to the adoption of a two-level distributed index and hashing techniques. Additionally, we propose efficient, scalable decentralized processing of SPARQL Protocol and RDF Query Language (SPARQL) queries in such a context and explore optimization techniques that build upon distributed query processing for database systems and relational algebra optimization. The effectiveness and efficiency of the SPARQL query processing mechanism we proposed for a decentralized settings were verified through a series of experiments. We anticipate that our work will become an indispensable, complementary approach to making the Semantic Web a reality by delivering efficient data sharing and reusing in an ad-hoc environment. 


ad-hoc; decentralized SPRQL query processing; hybrid P2P; query optimization; Semantic Web data sharing

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