SparqLog: A System for Efficient Evaluation of SPARQL 1.1 Queries via Datalog [Experiment, Analysis and Benchmark]

TL;DR

SparqLog introduces a system that efficiently evaluates SPARQL 1.1 queries using Datalog, aiming to bridge the gap between Semantic Web and Database approaches for knowledge graph querying.

Contribution

The paper presents SparqLog, a novel system that enables efficient SPARQL 1.1 query evaluation through Datalog, fostering interoperability between SW and DB technologies.

Findings

Demonstrates improved query evaluation performance

Provides a unified framework for SPARQL and Datalog

Benchmarks showing efficiency gains

Abstract

Over the past decade, Knowledge Graphs have received enormous interest both from industry and from academia. Research in this area has been driven, above all, by the Database (DB) community and the Semantic Web (SW) community. However, there still remains a certain divide between approaches coming from these two communities. For instance, while languages such as SQL or Datalog are widely used in the DB area, a different set of languages such as SPARQL and OWL is used in the SW area. Interoperability between such technologies is still a challenge. The goal of this work is to present a uniform and consistent framework meeting important requirements from both, the SW and DB field.