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Development supporting framework of architectural descriptions using heavy-weight ontologies with fuzzy-semantic similarity

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Abstract

This paper proposes a framework to support the development of architectural descriptions that have DM2-compliance data and are constructed and integrated under considering of the consistency between views as components of the viewpoints with different perspectives of the system. To do so, we developed two heavy-weight ontologies: DM2 Data Dictionary ontology containing whole things of DoDAF DM2 terms such as the definitions, aliases, and mapping relations to DoDAF Models and architectural description ontology expresses all outcomes of efforts to develop the architectural descriptions in a case structure. Based on the ontologies, our framework implements a fuzzy-semantic similarity measure to identify the appropriate views using case-based reasoning to meet the goal as a solution of the architecture to solve a problem. Furthermore, we performed data validation to check the DM2 compliance based on DM2 Data Dictionary ontology. To verify the superiority of our framework, we perform the three kinds of evaluations. First, we evaluate the effectiveness of the fuzzy-semantic similarity measure. Second, we verify the completeness of relationships of the data entities and attributes required to develop the architectural descriptions. Finally, we show the performance of the DM2 Data Dictionary ontology from a DM2 compliance. As a result, the experimental results verified the effectiveness and superiority of the proposed framework.

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Acknowledgments

This research was partially supported by the IT R&D program of MKE/KEIT [No. 10041788, Development of Smart Home Service based on Advanced Context-Awareness] and partially supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the “IT Consilience Creative Program” (IITP-2015-R0346-15-1008) supervised by the IITP (Institute for Information & Communications Technology Promotion).

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Authors and Affiliations

  1. Department of Industrial Engineering, Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, Suwon, 440-746, Korea

    Mye Sohn, Sunghwan Jeong & Taehoon Kim

  2. School of Integrated Technology, Yonsei Institute of Convergence Technology, Yonsei University, 162-1, Songdo-dong, Yeonsu-gu, Incheon, Korea

    Hyun Jung Lee

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  1. Mye Sohn
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  2. Sunghwan Jeong
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Correspondence to Mye Sohn.

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None of the authors of this paper has a financial or personal relationship with other people or organizations that could inappropriately influence or bias the content of the paper.

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Communicated by V. Loia.

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Sohn, M., Jeong, S., Kim, T. et al. Development supporting framework of architectural descriptions using heavy-weight ontologies with fuzzy-semantic similarity. Soft Comput 21, 6105–6119 (2017). https://doi.org/10.1007/s00500-016-2168-0

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