A Configurable Semantic-Based Transformation Method towards Conceptual Models
Conceptual models are built to depict and analyze complex systems. They are made of concepts and relationships among these concepts. In a particular domain, conceptual models are helpful for different stakeholders to reach a clear and unified view of domain problems. However, the process of building...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2020/6718087 |
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| _version_ | 1832546898586632192 |
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| author | Tiexin Wang Jingwen Cao Chuanqi Tao Zhibin Yang Yi Wu Bohan Li |
| author_facet | Tiexin Wang Jingwen Cao Chuanqi Tao Zhibin Yang Yi Wu Bohan Li |
| author_sort | Tiexin Wang |
| collection | DOAJ |
| description | Conceptual models are built to depict and analyze complex systems. They are made of concepts and relationships among these concepts. In a particular domain, conceptual models are helpful for different stakeholders to reach a clear and unified view of domain problems. However, the process of building conceptual models is time-consuming, tedious, and expertise required. To improve the efficiency of the building process, this paper proposes a configurable semantic-based (semi-) automatic conceptual model transformation methodology (SbACMT) that tries to reuse existing conceptual models to generate new models. SbACMT contains three parts: (i) a configurable semantic relatedness computing method building on the structured linguistic knowledge base “ConceptNet” (SRCM-CNet), (ii) a specific meta-model, which follows the Ecore standard, defines the rules of applying SRCM-CNet to different conceptual models to automatically detect transformation mappings, and (iii) a multistep matching and transformation process that employs SRCM-CNet. A case study is carried out to detail the working mechanism of SbACMT. Furthermore, through a systematically analysis of this case study, we validate the performance of SbACMT. We prove that SbACMT can support the automatic transformation process of conceptual models (e.g., class diagrams). The scalability of SbACMT can be improved by adapting the meta-model and predefined syntax transformation rules. |
| format | Article |
| id | doaj-art-b41a9124d9604df59ca4c05deb88b869 |
| institution | Kabale University |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-b41a9124d9604df59ca4c05deb88b8692025-02-03T06:46:39ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2020-01-01202010.1155/2020/67180876718087A Configurable Semantic-Based Transformation Method towards Conceptual ModelsTiexin Wang0Jingwen Cao1Chuanqi Tao2Zhibin Yang3Yi Wu4Bohan Li5College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaCollege of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaCollege of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaCollege of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaCollege of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaCollege of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaConceptual models are built to depict and analyze complex systems. They are made of concepts and relationships among these concepts. In a particular domain, conceptual models are helpful for different stakeholders to reach a clear and unified view of domain problems. However, the process of building conceptual models is time-consuming, tedious, and expertise required. To improve the efficiency of the building process, this paper proposes a configurable semantic-based (semi-) automatic conceptual model transformation methodology (SbACMT) that tries to reuse existing conceptual models to generate new models. SbACMT contains three parts: (i) a configurable semantic relatedness computing method building on the structured linguistic knowledge base “ConceptNet” (SRCM-CNet), (ii) a specific meta-model, which follows the Ecore standard, defines the rules of applying SRCM-CNet to different conceptual models to automatically detect transformation mappings, and (iii) a multistep matching and transformation process that employs SRCM-CNet. A case study is carried out to detail the working mechanism of SbACMT. Furthermore, through a systematically analysis of this case study, we validate the performance of SbACMT. We prove that SbACMT can support the automatic transformation process of conceptual models (e.g., class diagrams). The scalability of SbACMT can be improved by adapting the meta-model and predefined syntax transformation rules.http://dx.doi.org/10.1155/2020/6718087 |
| spellingShingle | Tiexin Wang Jingwen Cao Chuanqi Tao Zhibin Yang Yi Wu Bohan Li A Configurable Semantic-Based Transformation Method towards Conceptual Models Discrete Dynamics in Nature and Society |
| title | A Configurable Semantic-Based Transformation Method towards Conceptual Models |
| title_full | A Configurable Semantic-Based Transformation Method towards Conceptual Models |
| title_fullStr | A Configurable Semantic-Based Transformation Method towards Conceptual Models |
| title_full_unstemmed | A Configurable Semantic-Based Transformation Method towards Conceptual Models |
| title_short | A Configurable Semantic-Based Transformation Method towards Conceptual Models |
| title_sort | configurable semantic based transformation method towards conceptual models |
| url | http://dx.doi.org/10.1155/2020/6718087 |
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