R2DB: A System for Querying and Visualizing Weighted RDF Graphs
Songling Liu, Juan Pablo Cedeno, K. Selçuk Candan, Maria Luisa Sapino, Shengyu Huang, Xinsheng Li · 2012
Existing RDF query languages and RDF stores fail to support a large class of knowledge applications which associate utilities or costs on the available knowledge statements. A recent proposal includes (a) a ranked RDF (R2DF) specification to enhance RDF triples with an application specific weights and (b) a SPA Rank QL query language specification, which provides novel primitives on top of the SPARQL language to express top-k queries using traditional query patterns as well as novel flexible path predicates. We introduce and demonstrate R2DB, a database system for querying weighted RDF graphs. R2DB relies on the AR2Q query processing engine, which leverages novel index structures to support efficient ranked path search and includes query optimization strategies based on proximity and sub-result inter-arrival times. In addition to being the first data management system for the R2DF data model, R2DB also provides an innovative features-of-interest (FoI) based method for visualizing large sets of query results (i.e., sub graphs of the data graph).