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Model-based approaches for interoperability of next generation enterprise information systems: state of the art and future challenges

  • Gregory Zacharewicz
  • Saikou Diallo
  • Yves Ducq
  • Carlos Agostinho
  • Ricardo Jardim-Goncalves
  • Hassan Bazoun
  • Zhongjie Wang
  • Guy Doumeingts
Original Article

Abstract

Enterprise businesses are more than ever challenged by competitors that frequently refine and tailor their offers to clients. In this context, enterprise information systems (EIS) are especially important because: (1) they remain one of the last levers to increase the performance and competitiveness of the enterprise, (2) we operate in a business world where the product itself has reached a limit of performance and quality due to uniform capacity of industrial tools in a globalized economy and (3) the EIS can increase the product value thanks to additional digital services (built on data associated to the product) in order to meet and fit better client’s needs. However, the use of EISs reaches a limit in collaborative environments because enterprises management methods diverge and EISs are mainly inflexible resource packages that are not built with an interoperability objective. Consequently, we need to make EISs interoperable in order to achieve the needed gains competitiveness and performance. This paper contribution can be summarized as follows: (1) it relates existing work and it examines barriers that, at the moment, are preventing further improvements due to current methodological and technological limits, and (2) it proposes a conceptual framework and five challenges that model based approaches must overcome to achieve interoperability between EIS in the near and long term.

Keywords

Enterprise information Model-based interoperability Model-driven engineering/architecture Service systems Simulation Semantic approach Social networks 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Gregory Zacharewicz
    • 1
  • Saikou Diallo
    • 2
  • Yves Ducq
    • 2
  • Carlos Agostinho
    • 3
  • Ricardo Jardim-Goncalves
    • 3
  • Hassan Bazoun
    • 4
  • Zhongjie Wang
    • 5
  • Guy Doumeingts
    • 6
  1. 1.CNRS IMS, UMR 5218University of BordeauxTalenceFrance
  2. 2.VMASCOld Dominion UniversitySuffolkUSA
  3. 3.Centre of Technology and Systems, CTSUNINOVACaparicaPortugal
  4. 4.Hardis/Hardis ConseilSaint HerblainFrance
  5. 5.Harbin Institute of TechnologyHarbinChina
  6. 6.Interop VlabBrusselsBelgium

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