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Article
A framework of enriching business processes life-cycle with tagging information
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
  • Zakaria Maamar, Zayed University
  • Sherif Sakr, University of New South Wales (UNSW) Australia
  • Ahmed Barnawi, King Abdulaziz University
  • Seyed Mehdi Reza Beheshti, University of New South Wales (UNSW) Australia
Document Type
Conference Proceeding
Publication Date
1-1-2015
Abstract

© Springer International Publishing Switzerland 2015. In this demonstration, we present a framework for enriching business processes with tags specialized into social, resource, location, and temporal. Using the framework, business-process engineers and end-users (i.e., executors) provide the tags with the necessary details which are then automatically propagated from one tag to another, when appropriate. At design time phase of a business process, the propagation of relations between tags reflects unidirectional-transfer-offinal-details, unidirectional-transfer-of-partial-details, and bidirectional transfer- of-partial-details while at run-time the propagation of relations reflects strong-trigger, weak-trigger, and meet-in-the-middle trigger. Our provides an elegant mechanism for monitoring business processes which is more user-driven than traditional approaches which heavily rely on log analysis mechanisms.

ISBN
9783319195476
Publisher
Springer Verlag
Disciplines
Keywords
  • Concentration (process),
  • Database systems,
  • Business Process,
  • Design time,
  • End users,
  • Log analysis,
  • Meet-in-the-middle,
  • Runtimes,
  • Traditional approaches,
  • User driven,
  • Life cycle
Scopus ID
84959431785
Indexed in Scopus
Yes
Open Access
No
https://doi.org/10.1007/978-3-319-19548-3_25
Citation Information
Zakaria Maamar, Sherif Sakr, Ahmed Barnawi and Seyed Mehdi Reza Beheshti. "A framework of enriching business processes life-cycle with tagging information" Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 9093 (2015) p. 309 - 313 ISSN: <a href="https://v2.sherpa.ac.uk/id/publication/issn/0302-9743" target="_blank">0302-9743</a>
Available at: http://works.bepress.com/zakaria-maamar/60/