Efficient management and storage of a multiversion OWL 2 DL domain ontology

Abstract

Ontology is the chief technology to model domain knowledge and fix its heterogeneity. Knowledge evolution is unavoidable in all fields, and ontology should reflect such an evolution while preserving its consistency. The access to an ontology evolution history is also a crucial need. Thereby, ontology versions should be stored efficiently. To address these requirements, some works focused only on managing ontology inconsistency. To this end, they adopted an a posteriori approach that checks inconsistency after its occurrence. Others have mainly focused on some ontology versioning aspects other than the storage and the consistency preservation issues. Specifically, the state of the art storage strategies perform well some typical queries at the cost of a high storage space. Strategies with low space overhead lose the main specificity of ontology: the knowledge semantics modelling. So, it is useful to address all these shortcomings. This paper presents an approach that allows generating consistent OWL 2 DL ontology versions in a priori way. It also proposes an efficient storage strategy that preserves the semantics aspect of ontology and performs well typical queries with a low storage space. A protégé plug‐in is developed to show the feasibility of the main ideas presented in this paper.

Ontology Versioning Driven by Instance Evolution in the τOWL Framework

“…In (Bayoudhi et al, 2019), the authors have proposed an approach and a Protégé plug-in for versioning of OWL 2 DL ontologies, while applying an a priori consistency management technique (i.e., checking ontology consistency before applying ontology changes) and storing ontology versions in a temporal object-oriented database whose (temporal) schema is based on both the direct model-theoretic semantics for OWL 2 (W3C, 2012c) and on the proposal of Zhang et al (2015) dealing with the storage of OWL 2 ontologies in object-oriented databases. However, the approach of Bayoudhi et al (2019) does not support implicit schema changes triggered by non-conservative instance updates (not taken into account in this approach). Bürger et al (2020) have proposed an approach implemented in a system prototype for the detection of occurrences of semantic editing patterns, defined as graph transformation rules, between two versions of an OWL ontology.…”

“…In (Bayoudhi et al, 2020), the authors have surveyed (among others) approaches for ontology versioning while focusing on three research topics: (i) ontology versions pertinence, like in (Sassi et al, 2016), (ii) ontology versions relationship, like in (Allocca et al, 2009b) and (Díaz et al, 2011), and (iii) ontology versions storage and querying, like in (Grandi, 2013), (Grandi, 2016), (Meimaris, 2018), (Bayoudhi et al, 2019), and (Taelman et al, 2019).…”

A systematic review on time-constrained ontology evolution in predictive maintenance

“…While ontology evolution is considered the process through which an ontology is modified over time, ontology versioning is a stronger version of this process by annotating which modifications occurred and when are properly described and stored, with the possibility of accessing previous states. According to Bayoudhi et al (2019), there are two main approaches to ontology versioning: naïve strategies, which store all ontology versions independently-which may lead to overheads in storage; and change-based approaches, which store a reference accepted version of an ontology as the base point, storing the incremental modifications that must be applied to the reference ontology on runtime-which may lead to overheads in processing time. In an alternate version of this, Timestamp-based approaches opt by tagging each axiom with a time interval stating their validity.…”

“…For ease of reading, the entries presented in Table 8 have been grouped into categories of similar actions, even if in some studies they may be named differently. It should be noted that in some cases, such as Bayoudhi et al (2019), specify only that axioms can be either added or removed, but not do not specify types of axioms. As such, it is assumed that the approach is agnostic enough to support any type of axiom.…”

“…On the topic of ontology versioning, the authors in Bayoudhi et al (2019) propose a strategy for efficient retrieval of knowledge from past versions of an ontology, while keeping consistency in the evolution events. While many previous works have focused on the idea of consistency checking a posteriori, here it is assessed a priori with the aim of reducing both processing time and storage space.…”