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Parameter mapping and data transformation for engineering application integration

Author

Listed:
  • Chengen Wang

    (Northeastern University)

  • Lida Xu

    (Old Dominion University
    Beijing Jiaotong University
    Xian Jiaotong University)

Abstract

Enterprise applications may be classified into management applications used by managerial staffs for making decisions on business operations, and engineering applications used by engineers for solving multidisciplinary design problems. In the literature, enterprise application integration is extensively addressed in the context of management applications, but insufficiently discussed in the engineering disciplines. Practitioners in manufacturing industries have for a long time feel the increasing need of integrating engineering applications, in order to accelerate product development paces and improve design qualities. Integrating engineering applications used in the multiple engineering disciplines has to cope with a number of challenges. This paper focuses on one of the critical issues: parameter mapping and data transformation, which is of pivotal importance to integrating engineering applications. Design parameter mapping provides a consistent approach to data extraction, storage, display and manipulation among different data sources. Data transformation describes the operational logic of parsing input/output files, extracting and transforming data, and maintaining consistency among multiple data sources.

Suggested Citation

  • Chengen Wang & Lida Xu, 2008. "Parameter mapping and data transformation for engineering application integration," Information Systems Frontiers, Springer, vol. 10(5), pages 589-600, November.
  • Handle: RePEc:spr:infosf:v:10:y:2008:i:5:d:10.1007_s10796-008-9112-5
    DOI: 10.1007/s10796-008-9112-5
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    References listed on IDEAS

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    1. Vicens, E. & Alemany, M. E. & Andres, C. & Guarch, J. J., 2001. "A design and application methodology for hierarchical production planning decision support systems in an enterprise integration context," International Journal of Production Economics, Elsevier, vol. 74(1-3), pages 5-20, December.
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    Cited by:

    1. Pan Wang & Ricardo Valerdi & Shangming Zhou & Ling Li, 2015. "Introduction: Advances in IoT research and applications," Information Systems Frontiers, Springer, vol. 17(2), pages 239-241, April.
    2. Ni Li & Minghui Sun & Zhuming Bi & Zeya Su & Chao Wang, 2014. "A new methodology to support group decision-making for IoT-based emergency response systems," Information Systems Frontiers, Springer, vol. 16(5), pages 953-977, November.
    3. Siqing Shan & Cangyan Li & Wei Yao & Jihong Shi & Jie Ren, 2014. "An Empirical Study on Critical Factors Affecting Employee Satisfaction," Systems Research and Behavioral Science, Wiley Blackwell, vol. 31(3), pages 447-460, May.
    4. Chenxia Jin & Fachao Li & Marzana Wilamowska‐Korsak & Ling Li & Liuliu Fu, 2014. "BSP‐GA: A new Genetic Algorithm for System Optimization and Excellent Schema Selection," Systems Research and Behavioral Science, Wiley Blackwell, vol. 31(3), pages 337-352, May.
    5. Ni Li & Xiang Li & Yuzhong Shen & Zhuming Bi & Minghui Sun, 2015. "Risk assessment model based on multi-agent systems for complex product design," Information Systems Frontiers, Springer, vol. 17(2), pages 363-385, April.
    6. 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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