IDEAS home Printed from https://ideas.repec.org/a/spr/infsem/vyid10.1007_s10257-016-0321-z.html
   My bibliography  Save this article

An automatic model-to-model mapping and transformation methodology to serve model-based systems engineering

Author

Listed:
  • Tiexin Wang

    (University de Toulouse - Mines Albi)

  • Sebastien Truptil

    (University de Toulouse - Mines Albi)

  • Frederick Benaben

    (University de Toulouse - Mines Albi)

Abstract

With enterprise collaboration becoming increasingly frequent, the ability of an enterprise to cooperate with others has become one of the core factors in gaining competitive advantage. This trend has led to an urgent requirement to improve cooperation ability. To this end, model-based systems engineering is being adapted so that it can be used to represent and simulate the working processes of enterprises. Model-to-model mappings and transformations, as important aspects in model-based systems engineering, have become two of the key factors in improving the cooperation capabilities of enterprises. However, the foundations for achieving automatic model-to-model transformation have not yet been built. Normally, model transformation rules are built on the basis of model mappings, and model mappings concern semantic or syntactic representations. One of the difficulties in achieving model-to-model mappings and transformations lies in detecting the semantics and semantic relations that are conveyed in different models. This paper presents an automatic model-to-model mapping and transformation methodology, which applies semantic and syntactic checking measurements to detect the meanings and relations between different models automatically. Both of the semantic and syntactic checking measurements are combined into a refined meta-model based model transformation process. To evaluate the performance of this methodology, we demonstrate its applicability with a realistic example.

Suggested Citation

  • Tiexin Wang & Sebastien Truptil & Frederick Benaben, 0. "An automatic model-to-model mapping and transformation methodology to serve model-based systems engineering," Information Systems and e-Business Management, Springer, vol. 0, pages 1-54.
  • Handle: RePEc:spr:infsem:v::y::i::d:10.1007_s10257-016-0321-z
    DOI: 10.1007/s10257-016-0321-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10257-016-0321-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10257-016-0321-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Daniel Abril & Guillermo Navarro-Arribas & Vicenç Torra, 2012. "Choquet integral for record linkage," Annals of Operations Research, Springer, vol. 195(1), pages 97-110, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tiexin Wang & Sebastien Truptil & Frederick Benaben, 2017. "An automatic model-to-model mapping and transformation methodology to serve model-based systems engineering," Information Systems and e-Business Management, Springer, vol. 15(2), pages 323-376, May.
    2. Nikolaos Vesyropoulos & Christos K. Georgiadis & Panagiotis Katsaros, 2018. "Ensuring business and service requirements in enterprise mashups," Information Systems and e-Business Management, Springer, vol. 16(1), pages 205-242, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Torra, Vicenç, 2023. "The transport problem for non-additive measures," European Journal of Operational Research, Elsevier, vol. 311(2), pages 679-689.
    2. Tiexin Wang & Sebastien Truptil & Frederick Benaben, 2017. "An automatic model-to-model mapping and transformation methodology to serve model-based systems engineering," Information Systems and e-Business Management, Springer, vol. 15(2), pages 323-376, May.
    3. David Koloseni & Tove Helldin & Vicenç Torra, 2020. "AHP-Like Matrices and Structures—Absolute and Relative Preferences," Mathematics, MDPI, vol. 8(5), pages 1-12, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:infsem:v::y::i::d:10.1007_s10257-016-0321-z. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.