Process materialization using templates and rules to design flexible process models

Akhil Kumar, Wen Yao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Scopus citations

Abstract

The main idea in this paper is to show how flexible processes can be designed by combining generic process templates and business rules. We instantiate a process by applying rules to specific case data, and running a materialization algorithm. The customized process instance is then executed in an existing workflow engine. We present an architecture and also give an algorithm for process materialization. The rules are written in a logic-based language like Prolog. Our focus is on capturing deeper process knowledge and achieving a holistic approach to robust process design that encompasses control flow, resources and data, as well as makes it easier to accommodate changes to business policy.

Original languageEnglish (US)
Title of host publicationRule Interchange and Applications - International Symposium, RuleML 2009, Proceedings
Pages122-136
Number of pages15
DOIs
StatePublished - Dec 2 2009
EventInternational Symposium on Rule Interchange and Applications, RuleML 2009 - Las Vegas, NV, United States
Duration: Nov 5 2009Nov 7 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5858 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherInternational Symposium on Rule Interchange and Applications, RuleML 2009
CountryUnited States
CityLas Vegas, NV
Period11/5/0911/7/09

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Kumar, A., & Yao, W. (2009). Process materialization using templates and rules to design flexible process models. In Rule Interchange and Applications - International Symposium, RuleML 2009, Proceedings (pp. 122-136). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5858 LNCS). https://doi.org/10.1007/978-3-642-04985-9_13