The Temporal Vadalog System: Temporal Datalog-based Reasoning

TL;DR

This paper introduces Temporal Vadalog, a reasoning system based on temporal Datalog, designed to handle ontological reasoning with temporal logic, supporting features like time series and ensuring practical deployment with efficient architecture.

Contribution

The paper presents a novel, production-ready temporal Datalog reasoner that moves beyond chase-based methods, incorporating modern data pipeline architecture and advanced features.

Findings

Supports time series data processing

Guarantees termination with infinite time intervals

Demonstrates efficient reasoning through extensive experiments

Abstract

In the wake of the recent resurgence of the Datalog language of databases, together with its extensions for ontological reasoning settings, this work aims to bridge the gap between the theoretical studies of DatalogMTL (Datalog extended with metric temporal logic) and the development of production-ready reasoning systems. In particular, we lay out the functional and architectural desiderata of a modern reasoner and propose our system, Temporal Vadalog. Leveraging the vast amount of experience from the database community, we go beyond the typical chase-based implementations of reasoners, and propose a set of novel techniques and a system that adopts a modern data pipeline architecture. We discuss crucial architectural choices, such as how to guarantee termination when infinitely many time intervals are possibly generated, how to merge intervals, and how to sustain a limited memory footprint. We discuss advanced features of the system, such as the support for time series, and present an extensive experimental evaluation. This paper is a substantially extended version of "The Temporal Vadalog System" as presented at RuleML+RR '22. Under consideration in Theory and Practice of Logic Programming (TPLP).