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A web services framework for distributed model management

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  • Therani Madhusudan

    (University of Arizona)

Abstract

Distributed model management aims to support the wide-spread sharing and usage of decision support models. Web services is a promising technology for supporting distributed model management activities such as model creation and delivery, model composition, model execution and model maintenance to fulfill dynamic decision-support and problem solving requests. We propose a web services based framework for model management (called MM-WS) to support various activities of the model management life cycle. The framework is based on the recently proposed Integrated Service Planning and Execution (ISP & E) approach for web services integration. We discuss encoding of domain knowledge (as individual models) and utilize the MM-WS framework to interleave synthesis of composite models with their execution. A prototypical implementation with an example is used to illustrate the utility of the framework to enable distributed model management and knowledge integration. Benefits and issues of using the framework to support model-based decision-making in organizational contexts are outlined.

Suggested Citation

  • Therani Madhusudan, 2007. "A web services framework for distributed model management," Information Systems Frontiers, Springer, vol. 9(1), pages 9-27, March.
    • Handle: RePEc:spr:infosf:v:9:y:2007:i:1:d:10.1007_s10796-006-9015-2
    DOI: 10.1007/s10796-006-9015-2
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    2. David Schuff & Karen Corral & Robert D. St. Louis & Greg Schymik, 0. "Enabling self-service BI: A methodology and a case study for a model management warehouse," Information Systems Frontiers, Springer, vol. 0, pages 1-14.
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    4. J. Leon Zhao & Mohan Tanniru & Liang-Jie Zhang, 2007. "Services computing as the foundation of enterprise agility: Overview of recent advances and introduction to the special issue," Information Systems Frontiers, Springer, vol. 9(1), pages 1-8, March.
    5. 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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