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Capturing Domain-Imposed Requirements Based on Basic Research Findings

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Business Process Management

Part of the book series: Studies in Computational Intelligence ((SCI,volume 444))

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Abstract

The current means of obtaining domain-imposed requirements through users or domain experts are often suboptimal especially for the relatively new area of interest. This paper suggests the use of basic research findings as the more objective source and proposes an approach that translates research findings into a UML model based on which the domain-imposed requirements can be extracted. By using business project management as the domain of interest, it outlines the steps in the said approach and describes the use of the resulting domain model during the requirement specification for a Project Management Information System that caters specially to the needs of business projects. Theoretically, the same method can be applied to the other areas of management and an enterprise domain model could be developed in a similar way. Given equity access to all software developers, it is envisaged that meeting standard domain-imposed requirements would become a pre-requisite for competing enterprise systems in the future.

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Authors and Affiliations

  1. Open University Malaysia / Université de La Rochelle, Jalan Tun Ismail, 50480, Kuala Lumpur, Malaysia

    Siaw Ming Wong

  2. Laboratoire d’Informatique, Image et Interaction, Université de La Rochelle, La Rochelle, France

    Jean-Yves Lafaye

  3. College of Computer Studies, AMA International University, Salmabad, Bahrain

    Patrice Boursier

Authors
  1. Siaw Ming Wong
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  2. Jean-Yves Lafaye
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  3. Patrice Boursier
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Correspondence to Siaw Ming Wong .

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Editors and Affiliations

  1. , Department of Financial and Management, University of the Aegean, Fostini Street 31, Chios, 82100, Greece

    Michael Glykas

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Wong, S.M., Lafaye, JY., Boursier, P. (2013). Capturing Domain-Imposed Requirements Based on Basic Research Findings. In: Glykas, M. (eds) Business Process Management. Studies in Computational Intelligence, vol 444. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28409-0_14

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  • DOI: https://doi.org/10.1007/978-3-642-28409-0_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28408-3

  • Online ISBN: 978-3-642-28409-0

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