• Title/Summary/Keyword: Ontology Development Tools

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A Study on the Development of Ontology Management Tool (온톨로지 저작 도구 개발에 관한 연구)

  • Kim, Won-Pil;Kim, Jeong-Ho
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.45 no.6
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    • pp.187-193
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    • 2008
  • Nowadays, the study on e semantic web has been actively progressing for processing the web data semantically. For actualizing the semantic web environment, the core task is to build the ontology that defines the concepts and relations between concepts about the all things. Many ontology languages such as OWL, RDF(S), DAML+OIL were developed for building the ontology. And the many ontology tools were also implemented based on them. Although, many language and tools were researched, the practical use of the ontology tools is limited to the experts and researchers about the ontology because of the difficulty of the vocabulary, weak understanding about the ontology theory and the difficulty of the use of the ontology tools. And there are no studies on the reuse of constructed huge ontology. Therefore, in our study we design and implement the OWL ontology management tool that both the ontology experts and general users who want to build the ontologies are able to construct the ontology easily In this paper, we introduce the main modules used in our tool and features of our tool.

A Study on Ontology Modeling for Weapon Parts Development Information (무기체계 부품국산화 정보의 온톨로지 구축방안 연구)

  • Jang, Woo Hyuk
    • Journal of Korea Multimedia Society
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    • v.18 no.7
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    • pp.873-885
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    • 2015
  • Today, It is difficult to search the various and numerous information efficiently. For this reason, Semantic Web emerged to provide searching services more easily through the structuring of a variety of unstructured format data and the definition of meaningful relationships between information. Especially, definition of relationship and meaning among resources is significant to share and infer related information. Ontology modeling plays just that role. Weapon parts development information is unstructured and dispersed all over. There are many difficulties in finding desired information, leading to getting improper outcomes. In this paper, we present an intuitive ontology model with weapon parts development information including the multi-dimensional information analysis and expansion of the relevant information. This study build up a ontology model through creating class and hierarchy about parts information and defining the properties of classes with Ontology Development 101[1] procedures using Protégé tools. The ontology model provides users with a platform on which search of needed information can be easy and efficient.

Ontology Construction Process and System (온톨로지 구축 프로세스와 시스템)

  • Lee, In-K.;Seo, Suk-T.;Jeong, Hye-C.;Hwang, Do-Sam;Kwon, Soon-H.
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.6
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    • pp.721-729
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    • 2006
  • Numbers of research on ontology construction and its application are being done for knowledge and information processing using computers. But, the current ontology development methods and ontology construction tools are using in restricted field on propose. Therefore, proper ontology development processes and ontology construction tools on ontology characteristic are needed. In this paper, we propose ontology construction process(OntoProcess) that non-experts in specific field are able to construct ontology through conceptualization of knowledge and formalization of concepts from language resource. Beside, some problems may be occurred while numbers of people are working together to construct ontology: i)duplicated concept definition in conceptualization process of knowledge and ii)decreasing efficiency of ontology construction by short understanding about formal language and tool operation in formalization process. To solve the problems, we propose an ontology construction process for multiple developers (OntoProcess) using meta ontology. We develop an ontology construction system(OntoCS) based on proposed processes, and we show the efficiency of proposed processes and system from ontology construction experiment.

Development of Ontology for Thai Country Songs

  • Thunyaluk, Jaitiang;Malee, Kabmala;Wirapong, Chansanam
    • Journal of Information Science Theory and Practice
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    • v.11 no.1
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    • pp.79-88
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    • 2023
  • This study aimed to develop an ontology for Thai country songs by using the seven steps of an ontology development process. Hozo-Ontology Editor software and Ontology Application Management Framework were tools used in this study. Nine classes of ontology were identified: song, singer, emotion, author, language used, language type, song style, original, and content, and it was found that the song class had a relationship with all of the other classes. The developed ontology was evaluated by seeking opinions from experts in the field of Thai country songs, who agreed that the ontology was highly effective. Additionally, the evaluation employed the knowledge retrieval concept, and the precision, recall, and overall effectiveness were measured, with a precision of 92.59%, a recall of 86.21%, and an overall effectiveness (F-measure) of 89.28%. These results indicate that the developed ontology is highly effective in describing the scope of knowledge of Thai country songs.

An Efficient Web Ontology Storage Considering Hierarchical Knowledge for Jena-based Applications

  • Jeong, Dong-Won;Shin, Hee-Young;Baik, Doo-Kwon;Jeong, Young-Sik
    • Journal of Information Processing Systems
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    • v.5 no.1
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    • pp.11-18
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    • 2009
  • As well as providing various APIs for the development of inference engines and storage models, Jena is widely used in the development of systems or tools related with Web ontology management. However, Jena still has several problems with regard to the development of real applications, one of the most important being that its query processing performance is unacceptable. This paper proposes a storage model to improve the query processing performance of the original Jena storage. The proposed storage model semantically classifies OWL elements, and stores an ontology in separately classified tables according to the classification. In particular, the hierarchical knowledge is managed, which can make the processing performance of inferable queries enhanced and stores information. It enhances the query processing performance by using hierarchical knowledge. For this paper an experimental evaluation was conducted, the results of which showed that the proposed storage model provides a improved performance compared with Jena.

Development of Standardized Korean Plant Ontology for International Harmonization of Environmental and Ecological Knowledge Bases (환경·생태 지식베이스의 국제적 조화를 위한 한국형 표준 식물 온톨로지 개발)

  • Eunjeong Ju;Hunjoo Lee
    • Journal of Environmental Health Sciences
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    • v.49 no.4
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    • pp.201-209
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    • 2023
  • Background: To describe domain knowledge consistently and precisely, the establishment of a controlled vocabulary, a so-called ontology, is essential. Internationally, the plant ontology (PO) in the ecology field has been developed for the anatomy and developmental stages of plants in English, Spanish, and Japanese, but there is no Korean version of the PO due to a lack of knowledge on standardization for Korean plants. Objectives: We aimed to establish a Korean plant ontology with core PO architectures. Methods: The latest ontology web language (OWL)-formatted raw version of the PO was collected from the PO consortium site. A formal workflow process and OWL file-handing tools for efficient Korean content development were conducted and executed. Results: The macro- and micro-perspective frameworks of the PO were presented by analyzing the upper model and the internal OWL-leveled physical structure, respectively. We developed and validated Korean knowledge content for a total of 1,957 classes included in the PO and transplanted them into an ontology modeling system. Conclusions: A Korean plant ontology was established for international harmonization through improved compatibility and data exchangeability with multilingual environmental and ecological knowledge bases.

Bio-Ontology Generation Using Object-Oriented Ontology Manager (객체지향 온톨로지 관리기를 이용한 바이오 온톨로지 생성)

  • Yang, Kyung-Ah;Yang, Hyung-Jeong;Yang, Jae-Dong
    • The KIPS Transactions:PartB
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    • v.11B no.4
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    • pp.437-448
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    • 2004
  • This paper presents an approach to the development of bio-ontology using the Object-oriented Ontology Manager(OOM). OOM views a term of an ontology as an object which can be an instance or a concept. OOM facilitates the semi-automatic construction of ontologies by an intuitive interface and by inferencing with links among complicated and informative ontology terns. The main advantage of OOM is simple-to-use not compromising expressiveness so that ontologies in a complicated domain such as bioinformatics can be modeled intuitively. The ontologies constructed by OOM are easily exported to ontologies in other ontology languages without semantic loss because the structures of both the ontology by OOM and the ontologies in most of standard ontology languages are analogous. A translator to another standard ontology language is also provided by OOM so that the ontology can be combined with others to be applied to more complicated applications.

X-TOP: Design and Implementation of TopicMaps Platform for Ontology Construction on Legacy Systems (X-TOP: 레거시 시스템상에서 온톨로지 구축을 위한 토픽맵 플랫폼의 설계와 구현)

  • Park, Yeo-Sam;Chang, Ok-Bae;Han, Sung-Kook
    • Journal of KIISE:Computing Practices and Letters
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    • v.14 no.2
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    • pp.130-142
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    • 2008
  • Different from other ontology languages, TopicMap is capable of integrating numerous amount of heterogenous information resources using the locational information without any information transformation. Although many conventional editors have been developed for topic maps, they are standalone-type only for writing XTM documents. As a result, these tools request too much time for handling large-scale data and provoke practical problems to integrate with legacy systems which are mostly based on relational database. In this paper, we model a large-scale topic map structure based on XTM 1.0 into RDB structure to minimize the processing time and build up the ontology in legacy systems. We implement a topic map platform called X-TOP that can enhance the efficiency of ontology construction and provide interoperability between XTM documents and database. Moreover, we can use conventional SQL tools and other application development tools for topic map construction in X-TOP. The X-TOP is implemented to have 3-tier architecture to support flexible user interfaces and diverse DBMS. This paper shows the usability of X-TOP by means of the comparison with conventional tools and the application to healthcare cancer ontology management.

Knowledge Representation Using Fuzzy Ontologies: A Survey

  • V.Manikandabalaji;R.Sivakumar
    • International Journal of Computer Science & Network Security
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    • v.23 no.12
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    • pp.199-203
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    • 2023
  • In recent decades, the growth of communication technology has resulted in an explosion of data-related information. Ontology perception is being used as a growing requirement to integrate data and unique functionalities. Ontologies are not only critical for transforming the traditional web into the semantic web but also for the development of intelligent applications that use semantic enrichment and machine learning to transform data into smart data. To address these unclear facts, several researchers have been focused on expanding ontologies and semantic web technologies. Due to the lack of clear-cut limitations, ontologies would not suffice to deliver uncertain information among domain ideas, conceptual formalism supplied by traditional. To deal with this ambiguity, it is suggested that fuzzy ontologies should be used. It employs Ontology to introduce fuzzy logical policies for ambiguous area concepts such as darkness, heat, thickness, creaminess, and so on in a device-readable and compatible format. This survey efforts to provide a brief and conveniently understandable study of the research directions taken in the domain of ontology to deal with fuzzy information; reconcile various definitions observed in scientific literature, and identify some of the domain's future research-challenging scenarios. This work is hoping that this evaluation can be treasured by fuzzy ontology scholars. This paper concludes by the way of reviewing present research and stating research gaps for buddy researchers.

An Ontology - based Transformation Method from Feature Model to Class Model (온톨로지 기반 Feature 모델에서 Class 모델로의 변환 기법)

  • Kim, Dong-Ri;Song, Chee-Yang;Kang, Dong-Su;Baik, Doo-Kwon
    • Journal of the Korea Society of Computer and Information
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    • v.13 no.5
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    • pp.53-67
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    • 2008
  • At present, for reuse of similar domains between feature model and class model. researches of transformation at the model level and of transformation using ontology between two models are being made. but consistent transformation through metamodel is not made. And the factors of modeling transformation targets are not sufficient, and especially, automatic transformation algorithm and supporting tools are not provided so reuse of domains between models is not activated. This paper proposes a method of transformation from feature model to class model using ontology on the metamodel. For this, it re-establishes the metamodel of feature model, class model, and ontology, and it defines the properties of modelling factors for each metamodel. Based on the properties, it defines the profiles of transformation rules between feature mndel and ontology, and between ontology and class model, using set theory and propositional calculus. For automation of the transformation, it creates transformation algorithm and supporting tools. Using the proposed transformation rules and tools, real application is made through Electronic Approval System. Through this, it is possible to transform from the existing constructed feature model to the class model and to use it again for a different development method. Especially, it is Possible to remove ambiguity of semantic transformation using ontology, and automation of transformation maintains consistence between models.

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