Relationalization of provenance data in complex RDF reification nodes
Electronic Commerce Research
Scalable reconstruction of RDF-archived relational databases
Proceedings of the Fifth Workshop on Semantic Web Information Management
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The widespread deployment of Resource Description Framework has resulted in the emergence of a new data storage paradigm, the RDF Graph Model, which, in turn, requires a rich suite of modeling and visualization tools to aid with data management. This paper presents R2D (RDF-to-Database), an effort whose goal is to enable reusability of relational tools on RDF data. R2D aims to transform RDF data, at run-time, into an equivalent normalized relational schema, thereby bridging the gap between RDF and RDBMS concepts and making the abundance of existing relational tools available to RDF Stores. The work in this paper extends our earlier work by including the ability to map blank nodes, which are used to represent complex relationships between entities, and to perform pattern matching and aggregation functions on data. The R2D system architecture and mapping constructs, with particular emphasis on blank node handling, are presented along with descriptions of the algorithms comprising R2D. Performance graphs and screen-shots of a relational visualization tool that uses R2D to access RDF data are presented as evidence of the feasibility of our research.