TITLE

Development of an e-Government Ontology to Support Risk Analysis

AUTHOR(S)
Onwudike, Onyekachi; Lock, Russell; Phillips, Iain
PUB. DATE
January 2015
SOURCE
Proceedings of the European Conference on e-Government;2015, p45
SOURCE TYPE
Conference Proceeding
DOC. TYPE
Article
ABSTRACT
The complexity of governments is one of the biggest problems citizens face in engaging with them. This complexity is seen in the growing number of departments and services that a government is made up of and the need for citizens to interact with these departments or services independently. This research shows a lack of efficiency in the E-Government domain due to the vertical alignment of services and the need for complex collaboration across the departments, which all too often does not exist. We propose that an ontology could potentially help to foster interactions between departments and services, and thereby manage this complexity more efficiently. Although ontologies exist for different subject domains, the quality and suitability of these ontologies in the government domain at the present time gives rise for concern. Ontologies have the potential to play an important role in the design and development of government services. The key reason behind the development and design of an ontology for the EGovernment domain is to use knowledge that is resident in the domain of governments to reduce risks associated with the delivery, combination and dependencies that exist amongst services so that the resilience of the E-Government domain can be improved throughout government. This paper addresses the issue of identifying and analysing risk in the development and deployment of EGovernment services. Relevant information on risks that may occur with respect to services can be collected, compiled and disseminated which can serve as prediction tools for future governments as well as enable service providers make choices that would enable them fulfil service requirements adequately. The aim of this research is to contribute by constructing an ontology that is aimed at gauging the risks associated with using solutions across departments and even governments. Further, we also document how we have made use of queries to validate this ontology.
ACCESSION #
109455506

 

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