• 제목/요약/키워드: Ontology Engineering

검색결과 681건 처리시간 0.031초

Using the METHONTOLOGY Approach to a Graduation Screen Ontology Development: An Experiential Investigation of the METHONTOLOGY Framework

  • Park, Jin-Soo;Sung, Ki-Moon;Moon, Se-Won
    • Asia pacific journal of information systems
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    • 제20권2호
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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.

A Study on Enhancement of Learning Outcomes through Building of Learning Ontologies (학습 온톨로지 생성을 통한 학습 성과 강화에 관한 연구)

  • Kim, Jung-Min;Chung, Hyun-Sook
    • Journal of Engineering Education Research
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    • 제11권2호
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    • pp.15-24
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    • 2008
  • Teaching is communication between instructor and students. The learning outcomes can be enhanced by active learning of students. However, there are many obstacles to effective learning below, such as lecture notes authored by instructor, passive student participation, and paper-based homework. In this paper, we propose an effective method for enhancing learning effect through constructing learner ontologies in which knowledge discovered by students is conceptualized and organized. The learning ontology is composed of a teacher ontology and many learner ontologies. The learning ontology is used in discussion, visual presentation, and knowledge sharing between instructor and students. We used the learning ontology in two lectures in practice and learned that the learning ontology enhances learning effect through analysis of feedbacks of students.

Ontology-based Cohort DB Search Simulation (온톨로지 기반 대용량 코호트 DB 검색 시뮬레이션)

  • Song, Joo-Hyung;Hwang, Jae-min;Choi, Jeongseok;Kang, Sanggil
    • Journal of the Korea Society for Simulation
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    • 제25권1호
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    • pp.29-34
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    • 2016
  • Many researchers have used cohort DB (database) to predict the occurrence of disease or to keep track of disease spread. Cohort DB is Big Data which has simply stored disease and health information as separated DB table sets. To measure the relations between health information, It is necessary to reconstruct cohort DB which follows research purpose. In this paper, XML descriptor, editor has been used to construct ontology-based Big Data cohort DB. Also, we have developed ontology based cohort DB search system to check results of relations between health information. XML editor has used 7 layered Ontology development 101 and OWL API to change cohort DB into ontology-based. Ontology-based cohort DB system can measure the relation of disease and health information and can be used effectively when semantic relations are found. We have developed ontology-based cohort DB search system which can measure the relations between disease and health information. And it is very effective when searched results are semantic relations.

Ontology Semantic Mapping based Data Integration of CAD and PDM System (온톨로지 의미 매핑 기반 CAD 및 PDM 시스템 정보 통합)

  • Lee Min-Jung;Jung Won-Cheol;Lee Jae-Hyun;Suh Hyo-Won
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 한국정밀공학회 2005년도 춘계학술대회 논문집
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    • pp.181-186
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    • 2005
  • In collaborative environment, it is necessary that the participants in collaboration should share the same understanding about the semantics of terms. For example, they should know that 'Part' and 'Item' are different word-expressions for the same meaning. In this paper, we consider sharing between CAD and PDM data. In order to handle such problems in information sharing, an information system needs to automatically recognize that the terms have the same semantics. Serving this purpose, the semantic mapping logic and the ontology based mapper system is described in this paper. In the semantic mapping logic topic, we introduce our logic that consists of four modules: Character Matching, Instance Reasoning, definition comparing and Similarity Checking. In the ontology based mapper, we introduce the system architecture and the mapping procedure.

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Study of Performance Test Methods for RFID Devices Using Ontology Concept (온톨로지 기법을 이용한 RFID 장비성능 측정체계 및 방법)

  • Kwon, Hyun-Soo;Chang, Yoon-Seok
    • Journal of The Institute of Information and Telecommunication Facilities Engineering
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    • 제8권3호
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    • pp.144-151
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    • 2009
  • In this paper, we consider various international and local standards and applied ontology concepts which are used in Semantic Web, to make more structured test methods/procedure. Based on the ontology concept, we classify test method as three categories (i.e., conformance test, interoperability test and performance test), and make test structures for each category. We believe that this research provides test methods which reflect various standards as well as the guidelines for users to construct RFID device software more structurally.

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Ontology Mapping and Rule-Based Inference for Learning Resource Integration

  • Jetinai, Kotchakorn;Arch-int, Ngamnij;Arch-int, Somjit
    • Journal of information and communication convergence engineering
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    • 제14권2호
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    • pp.97-105
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    • 2016
  • With the increasing demand for interoperability among existing learning resource systems in order to enable the sharing of learning resources, such resources need to be annotated with ontologies that use different metadata standards. These different ontologies must be reconciled through ontology mediation, so as to cope with information heterogeneity problems, such as semantic and structural conflicts. In this paper, we propose an ontology-mapping technique using Semantic Web Rule Language (SWRL) to generate semantic mapping rules that integrate learning resources from different systems and that cope with semantic and structural conflicts. Reasoning rules are defined to support a semantic search for heterogeneous learning resources, which are deduced by rule-based inference. Experimental results demonstrate that the proposed approach enables the integration of learning resources originating from multiple sources and helps users to search across heterogeneous learning resource systems.

Semantic Mapping of Terms Based on Their Ontological Definitions and Similarities (온톨로지 기반의 용어 정의 비교 및 유사도를 고려한 의미 매핑)

  • Jung W.C.;Lee J.H.;Suh H.W.
    • Korean Journal of Computational Design and Engineering
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    • 제11권3호
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    • pp.211-222
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    • 2006
  • In collaborative environment, it is necessary that the participants in collaboration should share the same understanding about the semantics of terms. For example, they should know that 'COMPONENT' and 'ITEM' are different word-expressions for the same meaning. In order to handle such problems in information sharing, an information system needs to automatically recognize that the terms have the same semantics. So we develop an algorithm mapping two terms based on their ontological definitions and their similarities. The proposed algorithm consists of four steps: the character matching, the inferencing, the definition comparing and the similarity checking. In the similarity checking step, we consider relation similarity and hierarchical similarity. The algorithm is very primitive, but it shows the possibility of semi-automatic mapping using ontology. In addition, we design a mapping procedure for a mapping system, called SOM (semantic ontology mapper).

A Comparison of Bio and Medical Ontologies (생물학과 의학 온톨로지 비교 분석)

  • Yu, Jeong-Youn;Eom, Dong-Myung;Lee, Kyu-Chul
    • Korean Journal of Oriental Medicine
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    • 제12권2호통권17호
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    • pp.31-45
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    • 2006
  • Bioinformatics and medical informatics have moved to make its knowledge more systematically and computationally using ontology. These ontologies help querying ring and analyzing data and used to develop application in biomedical. However, no research about ontology of oriental medical exists. Thus, to maximize the power of transitional knowledge, it is necessary to construct the ontology for oriental medical. This paper compares the ontologies of bio and medic by an objective point of view to guide the construction of oriental medic ontologies.

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Concept of Ontology based Knowledge Management System (온톨로지 기반 지식관리 시스템의 구성)

  • 박성범;박홍석;이규봉
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 한국정밀공학회 2003년도 춘계학술대회 논문집
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    • pp.1253-1256
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    • 2003
  • These days, companies have to process enormous information and knowledge to satisfy desire of customers. The mere storage of them is no longer a significant problem because of the immense progress information technology has made during the past years and decades. It is important to deliver the right piece of information to the right person at the right time. Consequently, Knowledge management which supports the exchange of relevant information within company organization structure is of special interest for current enterprises. To solve this problem, a concept of the Knowledge management system is introduced in this paper based on the ontology technology. An ontology can describe all relevant information about documents, products, organizational structures or the users, their interests and experiences and be understood by everybody.

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A Method of Applying Ontology for Product Information Search (제품 정보의 검색에 온톨로지 활용 방법)

  • 최무라;유상봉
    • Korean Journal of Computational Design and Engineering
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    • 제6권4호
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    • pp.229-235
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    • 2001
  • As the networks (i.e., intranet and internet) proliferate all over the world, it is inevitable to move some (or all) of the enterprise activities into virtual spaces. Differently from business data, product data have complex semantics and thus are not properly exchanged among different application programs. Even though some neutral formats of product data have been developed by standard organizations, exchanging them among various application programs still needs the comprehensive understanding of the complex semantics. Recently, it is widely recognized that capturing more knowledge is the next step to overcome the current difficulties on sharing product data. In this paper, we utilize the ontology concept in order to facilitate information search far product data in the internet environment. A prototype of search system implemented using the ontology for automobile product data is presented.

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