An outlook on semantic business process mining and monitoring

  • Authors:
  • A. K. Alves De Medeiros;C. Pedrinaci;W. M. P. van der Aalst;J. Domingue;M. Song;A. Rozinat;B. Norton;L. Cabral

  • Affiliations:
  • Eindhoven University of Technology, Eindhoven, The Netherlands;Knowledge Media Institute, The Open University, Milton Keynes, UK;Eindhoven University of Technology, Eindhoven, The Netherlands;Knowledge Media Institute, The Open University, Milton Keynes, UK;Eindhoven University of Technology, Eindhoven, The Netherlands;Eindhoven University of Technology, Eindhoven, The Netherlands;Knowledge Media Institute, The Open University, Milton Keynes, UK;Knowledge Media Institute, The Open University, Milton Keynes, UK

  • Venue:
  • OTM'07 Proceedings of the 2007 OTM Confederated international conference on On the move to meaningful internet systems - Volume Part II
  • Year:
  • 2007

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Abstract

Semantic Business Process Management (SBPM) has been proposed as an extension of BPM with Semantic Web and Semantic Web Services (SWS) technologies in order to increase and enhance the level of automation that can be achieved within the BPM life-cycle. In a nutshell, SBPM is based on the extensive and exhaustive conceptualization of the BPM domain so as to support reasoning during business processes modelling, composition, execution, and analysis, leading to important enhancements throughout the life-cycle of business processes. An important step of the BPM life-cycle is the analysis of the processes deployed in companies. This analysis provides feedback about how these processes are actually being executed (like common control-flow paths, performance measures, detection of bottlenecks, alert to approaching deadlines, auditing, etc). The use of semantic information can lead to dramatic enhancements in the state-of-the-art in analysis techniques. In this paper we present an outlook on the opportunities and challenges on semantic business process mining and monitoring, thus paving the way for the implementation of the next generation of BPM analysis tools.