Jean Vincent Fonou Dombeu

Combining Ontology Development Methodologies and Semantic Web Platforms for E-government Domain Ontology Development

One of the key challenges in electronic government (e-government) is the development of systems that can be easily integrated and interoperated to provide seamless services delivery to citizens. In recent years, Semantic Web technologies based on ontology have emerged as promising solutions to the above engineering problems. However, current research practicing semantic development in e-government does not focus on the application of available methodologies and platforms for developing government domain ontologies. Furthermore, only a few of these researches provide detailed guidelines for developing semantic ontology models from a government service domain. This research presents a case study combining an ontology building methodology and two state-of-the-art Semantic Web platforms namely Protege and Java Jena ontology API for semantic ontology development in e-government. Firstly, a framework adopted from the Uschold and King ontology building methodology is employed to build a domain ontology describing the semantic content of a government service domain. Thereafter, UML is used to semi-formally represent the domain ontology. Finally, Protege and Jena API are employed to create the Web Ontology Language (OWL) and Resource Description Framework (RDF) representations of the domain ontology respectively to enable its computer processing. The study aims at: (1) providing egovernment developers, particularly those from the developing world with detailed guidelines for practicing semantic content development in their e-government projects and (2), strengthening the adoption of semantic technologies in e-government. The study would also be of interest to novice Semantic Web developers who might used it as a starting point for further investigations.

Semantic-Driven e-Government: Application of Uschold and King Ontology Building Methodology for Semantic Ontology Models Development

ABSTRACT Electronic government (e-government) has been one of the most active areas of ontology development during the past six years. In e-government, ontologies are being used to describe and specify e-government services (e-services) because they enable easy composition, matching, mapping and merging of various e-government services. More importantly, they also facilitate the semantic integration and interoperability of e-government services. However, it is still unclear in the current literature how an existing ontology building methodology can be applied to develop semantic ontology models in a government service domain. In this paper the Uschold and King ontology building methodology is applied to develop semantic ontology models in a government service domain. Firstly, the Uschold and King methodology is presented, discussed and applied to build a government domain ontology. Secondly, the domain ontology is evaluated for semantic consistency using its semi-formal representation in Description Logic. Thirdly, an alignment of the domain ontology with the Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE) upper level ontology is drawn to allow its wider visibility and facilitate its integration with existing metadata standard. Finally, the domain ontology is formally written in Web Ontology Language (OWL) to enable its automatic processing by computers. The study aims to provide direction for the application of existing ontology building methodologies in the Semantic Web development processes of e-government domain specific ontology models; which would enable their repeatability in other e-government projects and strengthen the adoption of semantic technologies in e-government. The research would be of interest to e-government system developers as well as the Semantic Web community, as the framework and techniques employed to develop the semantic ontology models might be repeated in other domains of knowledge to build ontologies.

Quantitative metadata on e-government ontologies in the oeGov repository

Ontologies play an important role in Semantic Web (SW) applications. However, it is costly and time consuming to build new ontologies de novo. One solution is to reuse existing ontologies when developing SW applications. To this end, TopGuadrant has launched the oeGov ontology repository to store and share a number of e-government ontologies of the US government. However, at present, the oeGov repository does not provide quantitative metadata on these ontologies to give an idea of their scales or sizes. This study uses online ontology documentation tools to iteratively gather quantitative metadata including the number of classes, properties and instances of the e-government ontologies in the oeGov repository. The analysis of these metadata revealed that only the 3 top level ontologies in the oeGov architecture are complete ontologies; the majority of the constituents of the oeGov are instances or datasets of the top level ontologies. These quantitative metadata further revealed that the bigger top level ontology in the oeGov is the government ontology (gov) with 151 classes, 72 properties and 24 instances, follows by the geopolitical ontology (geopolitical) with 11 classes, 101 properties and 312 instances. This metadata information may be useful for understanding the basic characteristics of these ontologies for their reuse in the e-government community.

An empirical analysis of semantic web mechanisms for storage and query of ontologies in relational databases

Different platforms and mechanisms have been developed to store and query ontologies in relational databases (RDB). However, very little have been done to identify and discuss the mechanisms used. In this paper, two of the most popular open-source ontology storage platforms namely Sesame and Jena are used to identify the mechanisms used to store ontologies in RDB. Two ontologies are loaded in the repositories and the data within the repositories are analyzed to identify the mechanism(s). The experiments shows that (1) Sesame uses two mechanisms namely vertical partitioning and normalized triple store mechanisms, (2) Jena uses one specific mechanism namely normalized triple store to store ontologies, (3) in Sesame, every ontology has its own database schema, and (4) in Jena, all ontologies have the same database schema.

Development of a data model for semantic exploitation of municipality records in South Africa

A number of South African municipalities have embraced the use of advanced information technology to improve their services to citizens. However, this is not a common practice across the country; there are still municipalities within South Africa who have not automated their information systems for better service delivery to the public. This study develops a data model that can be applied by municipalities across South Africa as the basis for automating their information systems for service delivery. A combination of qualitative and quantitative methods is used. Preliminary data is collected using: (1) literature review, (2) observation at a selected local Municipality and (3) online related resources at two additional municipalities. The collected data is analysed and a generic conceptual municipality data model is drawn. Finally, the data model is further implemented in Oracle to create a test database for future Semantic Web processing.