Data Complexity and Rewritability of Ontology-Mediated Queries in Metric Temporal Logic under the Event-Based Semantics (Full Version)
Not on the map. Why?
Abstract (arXiv)
We investigate the data complexity of answering queries mediated by metric temporal logic ontologies under the event-based semantics assuming that data instances are finite timed words timestamped with binary fractions. We identify classes of ontology-mediated queries answering which can be done in AC0, NC1, L, NL, P, and coNP for data complexity, provide their rewritings to first-order logic and its extensions with primitive recursion, transitive closure or datalog, and establish lower complexity bounds.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 May 2019.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 1; 2022: 2; 2023: 0; 2024: 0; 2025: 2.
5 papers.
- 2022MeTeoR: Practical Reasoning in Datalog with Metric Temporal Operatorscited by 7
- 2025On Deciding the Data Complexity of Answering Linear Monadic Datalog Queries with LTL Operators(Extended Version)cited by 1
- 2021Query Evaluation in DatalogMTL -- Taming Infinite Query Resultscited by 0
- 2022Seminaive Materialisation in DatalogMTLcited by 0
- 2025Inconsistency Handling in DatalogMTLcited by 0
- 2025Inconsistency Handling in DatalogMTL15 May 2025
- 2025On Deciding the Data Complexity of Answering Linear Monadic Datalog Queries with LTL Operators(Extended Version)23 Jan 2025
- 2022Seminaive Materialisation in DatalogMTL15 Aug 2022
- 2022MeTeoR: Practical Reasoning in Datalog with Metric Temporal Operators12 Jan 2022
- 2021Query Evaluation in DatalogMTL -- Taming Infinite Query Results21 Sep 2021