Accomplishment of Multimedia Ontology for the Tunisian Archaeology Field

Haifa, Degachi; Yengui, Ameni; Néji, Mahmoud

doi:10.1007/978-981-15-5859-7_5

Cited by 1 publication

(2 citation statements)

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“…In the previous step, we have defined the two main classes: The T1-Archaeological-Entity class aims to define the different archaeological entities involved in the Tunisian archaeological field. This class includes two subclasses a) T11-Site, and b) T12-Monument [2].…”

Section: Subclasses Stepmentioning

confidence: 99%

“…Based on these hypotheses, we have defined a methodology to develop an ontology that consists of six steps [2]- [4]:1) filtering of data step, 2) Validation of the Classes step, 3) Subclasses step, 4) properties step, 5) axioms step, and 6) Population step. In addition, Despite the important progress in the methodology of creating ontology, most methods existing in the literature define only the positive axioms [5]- [7] .…”

Section: Introductionmentioning

confidence: 99%

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MOTunAr Ontology: Creation and Axioms Impacts

Haifa¹,

Yengui²,

Néji³

2022

ESIJ

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Due to its potential for supporting heterogeneous and various data, ontologies are used in serval domains, notably the archaeological one. In this paper, we want to present a multimedia ontology that designs the different entities involved in the Tunisian archaeological field. On another hand, the task of creating ontology is error-prone. The quality of ontology should be sequentially evaluated based on various criteria (e.g., coherence, consciences, interoperability, etc.). Axioms present the guarantor to satisfy high quality for a developed ontology. Therefore, we detail in this work a hybrid approach that guarantees the quality of the generated ontology. This approach combines the corrective method that defines the positive axioms, and the constructive method that defines all relevant axioms based on the elimination of model and integrity constraints. The generated ontology is evaluated with the Pellet reasoner and OOPS! Online service.

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Section: Subclasses Stepmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%