ONTOLOGY-DRIVEN CONCEPTUAL MODEL AND DOMAIN ONTOLOGY FOR EGYPTIAN E-GOVERNMENT | ||||
International Journal of Intelligent Computing and Information Sciences | ||||
Volume 23, Issue 2, June 2023, Page 116-132 PDF (607.89 K) | ||||
Document Type: Original Article | ||||
DOI: 10.21608/ijicis.2023.176123.1230 | ||||
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Authors | ||||
Shaimaa Moustafa Haridy ![]() ![]() ![]() ![]() | ||||
1IS, FCIS, Ain Shams University, Cairo, Egypt | ||||
2Vice Dean for Postgraduate Studies & Research, Faculty of Computer and Information Sciences, Ain Shams University | ||||
3Department of Information Systems, Faculty of Computer and Information Sciences, Ain Shams University, Cairo, 11566, Egypt | ||||
4Department of information Systems, Faculty of Computers and Information Sciences, Ain Shams University, Cairo, Egypt | ||||
Abstract | ||||
In recent years, online services have received considerable attention worldwide. One crucial online service during the coronavirus disease (COVID-19) pandemic was e-governance. In which governments provides various services to their citizens using information and communication technology. However, the residents of Arab countries have faced numerous of obstacles and have not received the full benefits of e-governance. One of the main reasons is the absence of integration and information sharing. Therefore, in this study, a novel domain ontology for the Egyptian e-government has been proposed. The developed ontology can be used to solve a variety of interoperability problems. The development process starts with building ontology-driven conceptual model using OntoUML. It is one of the most used ontology-driven conceptual modeling languages. The proposed model is then converted to a computable web ontology via the Web Ontology Language. The resulted ontology is evaluated by the OntoMetrics quality metrics. Results are compared with the metrics collected from 20 e-government ontologies and proved that the proposed ontology has better understandability measurements. | ||||
Keywords | ||||
Artificial intelligence; digital government (e-government); ontology-driven conceptual modeling; ontology engineering; semantic web | ||||
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