Inconsistency Handling in DatalogMTL
Meghyn Bienvenu, Camille Bourgaux, Atefe Khodadaditaghanaki
TL;DR
The paper addresses how to manage inconsistencies in DatalogMTL by introducing three repair notions (s, p, i) and corresponding inconsistency-tolerant semantics (brave, CQA, intersection). It formalizes time-interval handling, defines normal form and interval-based comparisons, and extends the semantics to temporal data, with substantial data-complexity results. It establishes that $s$-repairs/conflicts enjoy favorable properties and tractability in many fragments, while $p$- and $i$-variants can exhibit non-existence, infinitude, or higher complexity, though bounded-interval and propositional cases yield tractable outcomes in several settings. The findings lay groundwork for practical inconsistency handling in temporal databases and suggest directions for future work, including extensions to negation and SMT-based implementations for real-world data.
Abstract
In this paper, we explore the issue of inconsistency handling in DatalogMTL, an extension of Datalog with metric temporal operators. Since facts are associated with time intervals, there are different manners to restore consistency when they contradict the rules, such as removing facts or modifying their time intervals. Our first contribution is the definition of relevant notions of conflicts (minimal explanations for inconsistency) and repairs (possible ways of restoring consistency) for this setting and the study of the properties of these notions and the associated inconsistency-tolerant semantics. Our second contribution is a data complexity analysis of the tasks of generating a single conflict / repair and query entailment under repair-based semantics.