• Asia pacific journal of information systems
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• v.20 no.2
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• pp.125-155
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• 2010

Ontologies have been adopted in various business and scientific communities as a key component of the Semantic Web. Despite the increasing importance of ontologies, ontology developers still perceive construction tasks as a challenge. A clearly defined and well-structured methodology can reduce the time required to develop an ontology and increase the probability of success of a project. However, no reliable knowledge-engineering methodology for ontology development currently exists; every methodology has been tailored toward the development of a particular ontology. In this study, we developed a Graduation Screen Ontology (GSO). The graduation screen domain was chosen for the several reasons. First, the graduation screen process is a complicated task requiring a complex reasoning process. Second, GSO may be reused for other universities because the graduation screen process is similar for most universities. Finally, GSO can be built within a given period because the size of the selected domain is reasonable. No standard ontology development methodology exists; thus, one of the existing ontology development methodologies had to be chosen. The most important considerations for selecting the ontology development methodology of GSO included whether it can be applied to a new domain; whether it covers a broader set of development tasks; and whether it gives sufficient explanation of each development task. We evaluated various ontology development methodologies based on the evaluation framework proposed by G$\acute{o}$mez-P$\acute{e}$rez et al. We concluded that METHONTOLOGY was the most applicable to the building of GSO for this study. METHONTOLOGY was derived from the experience of developing Chemical Ontology at the Polytechnic University of Madrid by Fern$\acute{a}$ndez-L$\acute{o}$pez et al. and is regarded as the most mature ontology development methodology. METHONTOLOGY describes a very detailed approach for building an ontology under a centralized development environment at the conceptual level. This methodology consists of three broad processes, with each process containing specific sub-processes: management (scheduling, control, and quality assurance); development (specification, conceptualization, formalization, implementation, and maintenance); and support process (knowledge acquisition, evaluation, documentation, configuration management, and integration). An ontology development language and ontology development tool for GSO construction also had to be selected. We adopted OWL-DL as the ontology development language. OWL was selected because of its computational quality of consistency in checking and classification, which is crucial in developing coherent and useful ontological models for very complex domains. In addition, Protege-OWL was chosen for an ontology development tool because it is supported by METHONTOLOGY and is widely used because of its platform-independent characteristics. Based on the GSO development experience of the researchers, some issues relating to the METHONTOLOGY, OWL-DL, and Prot$\acute{e}$g$\acute{e}$-OWL were identified. We focused on presenting drawbacks of METHONTOLOGY and discussing how each weakness could be addressed. First, METHONTOLOGY insists that domain experts who do not have ontology construction experience can easily build ontologies. However, it is still difficult for these domain experts to develop a sophisticated ontology, especially if they have insufficient background knowledge related to the ontology. Second, METHONTOLOGY does not include a development stage called the "feasibility study." This pre-development stage helps developers ensure not only that a planned ontology is necessary and sufficiently valuable to begin an ontology building project, but also to determine whether the project will be successful. Third, METHONTOLOGY excludes an explanation on the use and integration of existing ontologies. If an additional stage for considering reuse is introduced, developers might share benefits of reuse. Fourth, METHONTOLOGY fails to address the importance of collaboration. This methodology needs to explain the allocation of specific tasks to different developer groups, and how to combine these tasks once specific given jobs are completed. Fifth, METHONTOLOGY fails to suggest the methods and techniques applied in the conceptualization stage sufficiently. Introducing methods of concept extraction from multiple informal sources or methods of identifying relations may enhance the quality of ontologies. Sixth, METHONTOLOGY does not provide an evaluation process to confirm whether WebODE perfectly transforms a conceptual ontology into a formal ontology. It also does not guarantee whether the outcomes of the conceptualization stage are completely reflected in the implementation stage. Seventh, METHONTOLOGY needs to add criteria for user evaluation of the actual use of the constructed ontology under user environments. Eighth, although METHONTOLOGY allows continual knowledge acquisition while working on the ontology development process, consistent updates can be difficult for developers. Ninth, METHONTOLOGY demands that developers complete various documents during the conceptualization stage; thus, it can be considered a heavy methodology. Adopting an agile methodology will result in reinforcing active communication among developers and reducing the burden of documentation completion. Finally, this study concludes with contributions and practical implications. No previous research has addressed issues related to METHONTOLOGY from empirical experiences; this study is an initial attempt. In addition, several lessons learned from the development experience are discussed. This study also affords some insights for ontology methodology researchers who want to design a more advanced ontology development methodology.

• Journal of Information Science Theory and Practice
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• v.11 no.1
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• pp.61-78
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• 2023

Ontological knowledge modelling of epic texts, though being an established research arena backed by concrete multilingual and multicultural works, still suffers from two key shortcomings. Firstly, all epic ontological models developed till date have been designed following ad-hoc methodologies, most often combining existing general purpose ontology development methodologies. Secondly, none of the ad-hoc methodologies consider the potential reuse of existing epic ontological models for enrichment, if available. This paper presents, as a unified solution to the above shortcomings, the design and development of GOMME - the first dedicated methodology for iterative ontological modelling of epics, potentially extensible to works in different research arenas of digital humanities in general. GOMME is grounded in transdisciplinary foundations of canonical norms for epics, knowledge modelling best practices, application satisfiability norms, and cognitive generative questions. It is also the first methodology (in epic modelling but also in general) to be flexible enough to integrate, in practice, the options of knowledge modelling via reuse or from scratch. The feasibility of GOMME is validated via a first brief implementation of ontological modelling of the Indian epic Mahabharata by reusing an existing ontology. The preliminary results are promising, with the GOMME-produced model being both ontologically thorough and competent performance-wise.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.609-610
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• 2006

This paper introduces a methodology for construction of ontology-based product knowledge Map. For CPC(Collaborative Product Commerce) environment, engineering application of ontology has been studied . However, there are no generic and comprehensive methodologies for ontology construction yet because of such problems: dependency on experience of ontologist and domain experts and insufficiency of detail stages or rules. To solve those problems, we propose a methodology to construct ontology from engineering documents in semi-automatic. We use middle-out strategy and term's axioms, sub-definitions, to build ontology map. 5-turple ontology structure, semantic network and First order logic (FOL) are used for ontology definition in this study.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.11a
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• pp.591-594
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• 2004

Existing methodologies and practical ontology development experiences have explored a broad spectrum of knowledge management challenges. Each has its own characteristics and evaluates only a subset of specific domain. However, there is still no one 'correct' way or methodology for developing ontologies. In this paper, we described a methodology for domain driven ontology development, covering the whole lifecycle from the formalization of domain to the evolution of ontologies.

• Journal of Information Technology Services
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• v.9 no.2
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• pp.193-203
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• 2010

Service-Oriented Architecture (SOA) is a new trend for the design of application architecture to enhance the degree of share and reuse with the concept of service. It comes from the current situation where the business environments are changing rapidly and therefore competitions are getting bitter. To cope with such business challenges, business (and/or applications) architecture needs considerably flexibility and reusability, and that's why SOA is accepted as one of the most effective framework for the business applications in these days. In this paper we propose an analysis and design methodology for the applications of SOA. To implement the proposed methodology, the service ontology needs to be defined first, and the tasks such as service profiling, workflow design and service orchestration need to be followed. To validate the expected effects on flexibility and reusability, the proposed methodology was compared with CBD (Component Based Development).

• Journal of KIISE:Software and Applications
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• v.34 no.12
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• pp.1021-1036
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• 2007

As the requirement of Semantic Web and knowledge management has been rising, ontology developments have been carried out actively. Ontology is now at the point that systematic developing standardization should be made up like the developing a large scale software. Yet, It has not been made to optimize and standardize ontology development methodologies. In this study, to compare ontology development methodologies, METHONTOLOGY, CommonKADS, OTK in foreign countries and EOE in Korea are selected. The evaluating method is to introduce CMM-I version 1.1 framework. Ontology development methodologies have been evaluated in process areas that introduce for CMM-I maturity level 2 and 3. The purpose of this study is to find matured process and weak process in ontology development methodology on the view of process maturity, and suggests the areas to be Improved in it. The result of this study can be applied as basic data to establish and improve ontology development methodology.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.1
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• pp.119-128
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• 2013

The spotlight is thrown on the ubiquitous technology these days, and diverse management technologies are proposed to efficiently manage the networks in the ubiquitous environment. Because each network has its unique management technology, the integrated management of complex networks is a very difficult challenge. In this paper, an integrated network management methodology is proposed to ensure the efficient management of different networks using ontology. Although the proposed integrated network management methodology is quite simple, the definition of this methodology is essential for the integrated network management. Using the $Prot\acute{e}g\acute{e}$ to Ontology development, the terms for the integrated network management were defined, along with the OWL and relevant rules, and several methods were implemented according to the proposed methodology. The process in this paper is considered essential for the network expansion and multiple network management.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.256-264
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• 2001

A methodology of ontology design and a computer system supporting ontology design are needed. Our research goals include development of a methodology for ontology design and a its support environment. Although several systems for building ontologies have been implemented, they do not consider ontological theory very much. We discuss how to apply the \"role-concept\" and \"relationship\" in our environment, named Hozo, for creating and using ontologies. We present the architecture, functionalities of its modules, its interface and the some experiences on the design and use of ontologies.

• Journal of the Korean Society for information Management
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• v.27 no.3
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• pp.35-51
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• 2010

Emerging Web 2.0 services such as Twitter, Blogs, and Wikis alongside the poorlystructured and immeasurable growth of information requires an enhanced information organization approach. Ontology has received much attention over the last 10 years as an emerging approach for enhancing information organization. However, there is little penetration into current systems. The purpose of this study is to propose ontology implementation and methodology. To achieve the goal of this study, limitations of traditional information organization approaches are addressed and emerging information organization approaches are presented. Two ontology data models, RDF/OW and Topic Maps, are compared and then ontology development processes and methodology with topic maps based medical information retrieval system are addressed. The comparison of two data models allows users to choose the right model for ontology development.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.3
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• pp.275-283
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• 2005

Ontologies are the core components of the Semantic Web and knowledge-based systems. But it is difficult to find useful ontologies in actual domains. In order to build useful domain ontology, the conceptualization of the domain knowledge by knowledge experts of the specific domain and the specification of conceptualized knowledge with formal languages by ontology designers are required. In addition, structured and detailed guidelines and methods should be provided to be shared by the development team members. However, existing ontology building methodologies define and describe the skeletal structure of the whole building process at the top-layer. We build a useful academic ontology that is based on the conceptual knowledge structure in the domain of philosophy, and propose a detailed methodology to build a text ontology based on Topic Maps. Our methodology consists of two phases, ontology modelling and ontology implementation. We implement a philosophy knowledge portal to support retrieving and navigating of the philosophy knowledge.