A Novel Approach for Generating SPARQL Queries from RDF Graphs

TL;DR

This paper presents a new method to generate SPARQL queries from user keywords by transforming ontologies into RDF graphs stored in Neo4j, enabling efficient querying and language translation.

Contribution

It introduces a novel approach combining ontology transformation, RDF graph storage in Neo4j, and query language translation between SPARQL and Cypher for flexible RDF data querying.

Findings

The system effectively generates SPARQL queries from keywords.

The approach is adaptable to various RDF graph databases.

Evaluation shows the tool is comprehensive and efficient.

Abstract

This work is done as part of a research master's thesis project. The goal is to generate SPARQL queries based on user-supplied keywords to query RDF graphs. To do this, we first transformed the input ontology into an RDF graph that reflects the semantics represented in the ontology. Subsequently, we stored this RDF graph in the Neo4j graphical database to ensure efficient and persistent management of RDF data. At the time of the interrogation, we studied the different possible and desired interpretations of the request originally made by the user. We have also proposed to carry out a sort of transformation between the two query languages SPARQL and Cypher, which is specific to Neo4j. This allows us to implement the architecture of our system over a wide variety of BD-RDFs providing their query languages, without changing any of the other components of the system. Finally, we tested and evaluated our tool using different test bases, and it turned out that our tool is comprehensive, effective, and powerful enough.