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An Ontology-Based Approach for Supporting Business-IT Alignment

In: Complex Intelligent Systems and Their Applications

Author

Listed:
  • Csaba Veres

    (University of Bergen)

  • Jennifer Sampson

    (Statoil)

  • Karl Cox

    (University of Brighton)

  • Steven Bleistein

    (Enterprise Analysts Pty Ltd)

  • June Verner

    (University of New South Wales)

Abstract

Summary B-SCP (Business Strategy, Context, and Process) is a promising framework addressing alignment of IT with business strategy from a requirements engineering perspective. The B-SCP approach combines goal and context modeling, and business processes, into a generic modeling framework that deconstructs these to IT requirements and context. However, a problem with the B-SCP framework is that it is difficult to track dependencies between requirements in a project of realistic complexity. To address this we discuss how the RDF (Resource Description Framework) data model with OWL (Web Ontology Language) semantics will greatly benefit an implementation using B-SCP. Our contribution is to extend B-SCP by describing an ontology data structure for representing the requirements and the complex rules which map them together. The benefit in our approach is that it provides a comprehensive way to validate the decomposition of the requirements. Seven–Eleven Japan is used as an exemplar to demonstrate improved productivity and consistency of B-SCP.

Suggested Citation

  • Csaba Veres & Jennifer Sampson & Karl Cox & Steven Bleistein & June Verner, 2010. "An Ontology-Based Approach for Supporting Business-IT Alignment," Springer Optimization and Its Applications, in: Fatos Xhafa & Leonard Barolli & Petraq J. Papajorgji (ed.), Complex Intelligent Systems and Their Applications, chapter 0, pages 21-42, Springer.
    • Handle: RePEc:spr:spochp:978-1-4419-1636-5_2
    DOI: 10.1007/978-1-4419-1636-5_2
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    Cited by:

    1. R. B. K. Brown & G. Beydoun & G. Low & W. Tibben & R. Zamani & F. García-Sánchez & R. Martinez-Bejar, 2016. "Computationally efficient ontology selection in software requirement planning," Information Systems Frontiers, Springer, vol. 18(2), pages 349-358, April.

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