Introduction

Conceptual domain modeling in the field of the Semantic Web is typically achieved through Description Logic (DL)-based ontology languages such as OWL, guided by normal set theory. However, modeling Imprecise Temporal Expressions (ITEs) linked to unstructured vague time data is currently a challenge. A considerable loss of information occurs owing to the requirement of current domain modeling languages that temporal information be set as definite time-points. This shortcoming can lead to a loss of relevant information in modeling the real-world, especially in application ontologies; hence, there is a call for a more comprehensive ontology language for managing the vague temporal expressions commonly found in real-world narration of domain facts.

As ontologies gradually become pervasive in enterprise applications, efficient representation and communication of fuzzy domain facts are paramount. Consequently, a number of language extensions have been built, inspired by the fuzzy set theory, to aid representing non-crisp or vague facts in ontology models. Despite these advances, there still exists a wide research gap in achieving consistent representation formalisms for managing temporal uncertainties in domain ontologies.

The purpose of this research, therefore, is to bridge this gap by introducing FT-SWRL: A consistent fuzzy-temporal extension that can be used to represent and reason over uncertain-temporal domain knowledge in the semantic web. The proposed extension would deal with the representation of imprecise temporal expressions as fuzzy intervals.

Motivation

The end goal of this research is to enable a consistent representation model for modeling both temporal data and the temporal uncertainties often found in domain facts through extending the Semantic Web Rule Language with fuzzy temporal constructs. For instance, current OWL/SWRL definitions find it difficult to easily and efficiently represent and extract from OWL ontologies, expressions involving approximate temporal assertions such as "around 4 pm", "about 4 hours", "few weeks ago", etc.

This limitation necessitates the development of the FT-SWRL extension aimed at encoding fuzzy-temporal information in SWRL formalism. Furthermore, by modeling such real-world issues that require the representation of time changes and the uncertainties brought about by these changes or temporal relations between events, this study aims to meet the need for handling imprecise temporal expressions in domains like medical, multimedia, market trends analysis, and more.

Scope

Given the enormous task of commuting all fuzzy set theories into an ontology rule language extension, this study adopts a bottom-up approach, commencing with the introduction of fuzziness from SWRL peripherals by extending the existing temporal model. This approach takes advantage of existing tools during implementation and avoids introducing inconsistencies to main ontologies.

This proposal relies mainly on existing standards compatible with SWRL while focusing primarily on providing an extended abstract syntax and semantics for fuzzy temporal representation in SWRL. The result would be a model that allows imprecise temporal facts to be modeled using fuzzy temporal modifiers defined as constructs.

In conclusion, the article presents a breakthrough in fuzzy temporal extensions by defining a complete fuzzification process with the Semantic Web Rule Language (SWRL) and its fuzzy temporal extension largely due to its semantic integration with OWL. This enables efficient domain knowledge assertions into ontologies and allows extraction using the query functionality available as an SQWRL (SWRL query language).