RDF-TX: A Fast, User-Friendly System for Querying the History of RDF Knowledge Bases

Abstract

Knowledge bases that summarize web information in RDF triples deliver many benefits, including providing access to encyclopedic knowledge via SPARQL queries and end-user interfaces. As the real world evolves, the knowledge base is updated and the evolution history of entities and their properties becomes of great interest to users. Thus, users need query tools of comparable power and usability to explore such evolution histories or flash-back to the past. An integrated system that supports user-friendly queries and efficient query evaluation on the history of knowledge bases is required. In this paper, we introduce (i) SPARQL T , a temporal extension of SPARQL that expresses powerful structured queries on temporal RDF graphs, (ii) an efficient in-memory query engine that takes advantage of compressed multiversion B+ trees to achieve fast evaluation of SPARQL T queries, and (iii) a query optimizer that improves selectivity estimation of temporal queries and generates efficient join orders using the statistics of temporal RDF graphs. The performance and scalability of our system are validated by extensive experiments on real world datasets, which shows significant performance improvement comparing with other approaches.