Path discovery by Querying the federation of Relational Database and RDF Graph

TL;DR

This paper introduces a new federated path querying language that extends existing regular path queries to integrate RDF graphs with relational databases, enhancing expressivity while maintaining efficient evaluation.

Contribution

It proposes a federated path querying language that surpasses nested regular expressions and negation-free property paths, enabling complex graph pattern federation with low computational complexity.

Findings

More expressive than existing path query languages

Supports federation of RDF and relational data

Maintains low computational complexity

Abstract

The class of queries for detecting path is an important as those can extract implicit binary relations over the nodes of input graphs. Most of the path querying languages used by the RDF community, like property paths in W3C SPARQL 1.1 and nested regular expressions in nSPARQL are based on the regular expressions. Federated queries allow for combining graph patterns and relational database that enables the evaluations over several heterogeneous data resources within a single query. Federated queries in W3C SPARQL 1.1 currently evaluated over different SPARQL endpoints. In this paper, we present a federated path querying language as an extension of regular path querying language for supporting RDF graph integration with relational database. The federated path querying language is absolutely more expressive than nested regular expressions and negation-free property paths. Its additional expressivity can be used for capturing the conjunction and federation of nested regular path queries. Despite the increase in expressivity, we also show that federated path queries are still enjoy a low computational complexity and can be evaluated efficiently.