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Semantic Monitoring and Compensation in Socio-technical Processes

  • Yingzhi Gou
  • Aditya Ghose
  • Chee-Fon Chang
  • Hoa Khanh Dam
  • Andrew Miller
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8823)

Abstract

Socio-technical processes are becoming increasingly important, with the growing recognition of the computational limits of full automation, the growth in popularity of crowd sourcing, the complexity and openness of modern organizations etc. A key challenge in managing socio-technical processes is dealing with the flexible, and sometimes dynamic, nature of the execution of human-mediated tasks. It is well-recognized that human execution does not always conform to predetermined coordination models, and is often error-prone. This paper addresses the problem of semantically monitoring the execution of socio-technical processes to check for non-conformance, and the problem of recovering from (or compensating for) non-conformance. This paper proposes a semantic solution to the problem, by leveraging semantically annotated process models to detect non-conformance, and using the same semantic annotations to identify compensatory human-mediated tasks.

Keywords

Business Process Compensation Point Business Process Management Normative Trace Semantic Annotation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Yingzhi Gou
    • 1
  • Aditya Ghose
    • 1
    • 2
  • Chee-Fon Chang
    • 1
  • Hoa Khanh Dam
    • 2
  • Andrew Miller
    • 1
  1. 1.Centre for Oncology Informatics, Illawarra Health & Medical Research InstituteUniversity of WollongongAustralia
  2. 2.Decision Systems Lab., School of Computer Science and Software EngineeringUniversity of WollongongAustralia

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