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Open Access

τSQWRL: A TSQL2-Like Query Language for Temporal Ontologies Generated from JSON Big Data

Department of Computer Science, Faculty of Economics and Management, University of Sfax, Sfax 3029, Tunisia.
Department of Computer Science and Engineering, University of Bologna, Bologna 40136, Italy.
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Abstract

Temporal ontologies allow to represent not only concepts, their properties, and their relationships, but also time-varying information through explicit versioning of definitions or through the four-dimensional perdurantist view. They are widely used to formally represent temporal data semantics in several applications belonging to different fields (e.g., Semantic Web, expert systems, knowledge bases, big data, and artificial intelligence). They facilitate temporal knowledge representation and discovery, with the support of temporal data querying and reasoning. However, there is no standard or consensual temporal ontology query language. In a previous work, we have proposed an approach named τJOWL (temporal OWL 2 from temporal JSON, where OWL 2 stands for "OWL 2 Web Ontology Language" and JSON stands for "JavaScript Object Notation" ). τJOWL allows (1) to automatically build a temporal OWL 2 ontology of data, following the Closed World Assumption (CWA), from temporal JSON-based big data, and (2) to manage its incremental maintenance accommodating their evolution, in a temporal and multi-schema-version environment. In this paper, we propose a temporal ontology query language for τJOWL, named τSQWRL (temporal SQWRL), designed as a temporal extension of the ontology query language—Semantic Query-enhanced Web Rule Language (SQWRL). The new language has been inspired by the features of the consensual temporal query language TSQL2 (Temporal SQL2), well known in the temporal (relational) database community. The aim of the proposal is to enable and simplify the task of retrieving any desired ontology version or of specifying any (complex) temporal query on time-varying ontologies generated from time-varying big data. Some examples, in the Internet of Healthcare Things (IoHT) domain, are provided to motivate and illustrate our proposal.

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Big Data Mining and Analytics
Pages 288-300

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Cite this article:
Brahmia Z, Grandi F, Bouaziz R. τSQWRL: A TSQL2-Like Query Language for Temporal Ontologies Generated from JSON Big Data. Big Data Mining and Analytics, 2023, 6(3): 288-300. https://doi.org/10.26599/BDMA.2022.9020044

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Received: 26 August 2022
Revised: 15 October 2022
Accepted: 28 October 2022
Published: 07 April 2023
© The author(s) 2023.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).