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Integrated model-driven dashboard development

Author

Listed:
  • Themis Palpanas

    (University of Trento)

  • Pawan Chowdhary

    (IBM T.J. Watson Research Center)

  • George Mihaila

    (IBM T.J. Watson Research Center)

  • Florian Pinel

    (IBM T.J. Watson Research Center)

Abstract

Business performance modeling and model-driven business transformation are two research directions that are attracting much attention lately. In this study, we propose an approach for dashboard development that is model-driven and can be integrated with the business performance models. We adopt the business performance modeling framework, and we extend it in order to capture the reporting aspect of the business operation. We describe models that can effectively represent all the elements necessary for the business performance reporting process, and the interactions among them. We demonstrate how all these models can be combined and automatically generate the final solution. We further extend the proposed framework with mechanisms that can detect changes in the models and incrementally update the deployed solutions. Finally, we discuss our experience from the application of our technique in a real-world scenario. This case study shows that our technique can be efficiently applied to and handle changes in the underlying business models, delivering significant benefits in terms of both development time and flexibility.

Suggested Citation

  • Themis Palpanas & Pawan Chowdhary & George Mihaila & Florian Pinel, 2007. "Integrated model-driven dashboard development," Information Systems Frontiers, Springer, vol. 9(2), pages 195-208, July.
  • Handle: RePEc:spr:infosf:v:9:y:2007:i:2:d:10.1007_s10796-007-9032-9
    DOI: 10.1007/s10796-007-9032-9
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    Cited by:

    1. Tom Butler & Damien McGovern, 2012. "A conceptual model and IS framework for the design and adoption of environmental compliance management systems," Information Systems Frontiers, Springer, vol. 14(2), pages 221-235, April.
    2. Chulhwan Chris Bang, 2015. "Information systems frontiers: Keyword analysis and classification," Information Systems Frontiers, Springer, vol. 17(1), pages 217-237, February.

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