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AODB and CDMM Modeling – Comparative Case-Study

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Intelligent Information and Database Systems (ACIIDS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10752))

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Abstract

The paper is focused on comparison of two different approaches to graph modeling. A case study, which was chosen as a common background for the comparison, is an example of modeling problems characteristic for bioinformatics. First the OMG Semantics of Business Vocabulary and Rules (SBVR) standard was used to define the domain. The Association-Oriented Database (AODB) metamodel based approach was applied to show how the appropriate domain-specific model can be created in a graph modeling language dedicated to data modeling. In contrast, the Context-Driven Meta-Modeling (CDMM) approach, illustrates how to construct a domain-specific modeling language to model the case-study as a domain. The AODB is used as a General-Purpose Modeling Language (GPML) while the CDMM is applied as a Domain-Specific Modeling Language (DSML). Both approaches constitute alternatives for MOF based languages known from OMG standards.

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Authors and Affiliations

  1. Wrocław University of Science and Technology, Wyb. Wyspiańskiego 27, 50-370, Wrocław, Poland

    Marek Krótkiewicz

  2. Cracow University of Technology, Warszawska 24, 31-155, Kraków, Poland

    Piotr Zabawa

Authors
  1. Marek Krótkiewicz
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  2. Piotr Zabawa
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Correspondence to Marek Krótkiewicz .

Editor information

Editors and Affiliations

  1. Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Quang Binh University, Dong Hoi City, Vietnam

    Duong Hung Hoang

  3. National University of Kaohsiung, Kaohsiung, Taiwan

    Tzung-Pei Hong

  4. Rutgers University, Piscataway, New Jersey, USA

    Hoang Pham

  5. Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

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Krótkiewicz, M., Zabawa, P. (2018). AODB and CDMM Modeling – Comparative Case-Study. In: Nguyen, N., Hoang, D., Hong, TP., Pham, H., Trawiński, B. (eds) Intelligent Information and Database Systems. ACIIDS 2018. Lecture Notes in Computer Science(), vol 10752. Springer, Cham. https://doi.org/10.1007/978-3-319-75420-8_6

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  • DOI: https://doi.org/10.1007/978-3-319-75420-8_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-75419-2

  • Online ISBN: 978-3-319-75420-8

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