Towards Practicable Algorithms for Rewriting Graph Queries Beyond DL-Lite

Abstract

Despite the advantages that the virtual knowledge graph paradigm has brought to many application domains, state-of-the-art systems still do not support popular graph database management systems like Neo4j. Their query rewriting algorithms focus on languages like conjunctive queries and their unions, which were developed for relational data and are poorly suited for graph data. Moreover, they also limit the expressiveness of the ontology languages that admit rewritings, restricting them to those that enjoy the so-called FO-rewritability property. Rewritings have thus focused on the DL-Lite family of Description Logics. In this paper, we propose a technique for rewriting a family of navigational queries for a suitably tailored fragment of ELHI. Leveraging navigational features in the target query language, we can include some widely-used axiom shapes not supported by DL-Lite. We implemented a proof-of-concept prototype that rewrites into Cypher queries, and tested it on a real-world cognitive neuroscience use case with promising results.