iWarded: A System for Benchmarking Datalog+/- Reasoning (technical report)
Teodoro Baldazzi (Universit\`a Roma Tre), Luigi Bellomarini (Banca, d'Italia), Emanuel Sallinger (University of Oxford, TU Wien), Paolo Atzeni, (Universit\`a Roma Tre)

TL;DR
iWarded is a system designed to generate large, complex, and realistic reasoning scenarios for benchmarking Datalog+/- reasoning systems, addressing the lack of specialized tools for evaluation and comparison.
Contribution
The paper introduces iWarded, a novel system that creates challenging reasoning benchmarks for Datalog+/- systems, supported by new theoretical results for scenario generation.
Findings
iWarded can generate large, complex reasoning benchmarks.
The system effectively supports evaluation of Datalog+/- systems.
It facilitates comparison of reasoning system optimizations.
Abstract
Recent years have seen increasing popularity of logic-based reasoning systems, with research and industrial interest as well as many flourishing applications in the area of Knowledge Graphs. Despite that, one can observe a substantial lack of specific tools able to generate nontrivial reasoning settings and benchmark scenarios. As a consequence, evaluating, analysing and comparing reasoning systems is a complex task, especially when they embody sophisticated optimizations and execution techniques that leverage the theoretical underpinnings of the adopted logic fragment. In this paper, we aim at filling this gap by introducing iWarded, a system that can generate very large, complex, realistic reasoning settings to be used for the benchmarking of logic-based reasoning systems adopting Datalog+/-, a family of extensions of Datalog that has seen a resurgence in the last few years. In…
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Taxonomy
TopicsLogic, Reasoning, and Knowledge · Semantic Web and Ontologies · Advanced Database Systems and Queries
