User Assistance For Business Process Model Decomposition

Petri nets are a suitable language for modeling business processes with complex flow structures. Processes with a number of alternative, concurrent or sequential flow structures on the same process abstraction level may result in complex processes. Such complex and poorly unstructured processes are particularly difficult for users to understand. Process decomposition can significantly improve the comprehensibility and consistency of process models and enables faster reuse of process models. To maintain homogenous process decomposition demands a significant amount of modeling experience. In this paper, we will present our approach for (semi-)automatic detection of nonuniformly specified process element names on the same process decomposition level. Our detection system validates process element names regarding reasonable hierarchical specifications. The aim of our approach is to (semi-)automatically highlight nonuniformly specified process elements in order to improve process model consistency. The approach is based upon an OWL-based description of Petri nets.

[1]  Nicola Guarino,et al.  Ontologies and Knowledge Bases. Towards a Terminological Clarification , 1995 .

[2]  Dekang Lin,et al.  An Information-Theoretic Definition of Similarity , 1998, ICML.

[3]  Sheila A. McIlraith,et al.  Adapting BPEL4WS for the Semantic Web: The Bottom-Up Approach to Web Service Interoperation , 2003, SEMWEB.

[4]  Alexander Budanitsky,et al.  Lexical Semantic Relatedness and Its Application in Natural Language Processing , 1999 .

[5]  C. A. R. Hoare Theories of Programming: Top-Down and Bottom-Up and Meeting in the Middle , 1999, World Congress on Formal Methods.

[6]  David G. Stork,et al.  Token-Controlled Place Refinement in Hierarchical Petri Nets with Application to Active Document Workflow , 2002, ICATPN.

[7]  August-Wilhelm Scheer,et al.  ARIS Architecture and Reference Models for Business Process Management , 2000, Business Process Management.

[8]  Marc Ehrig,et al.  Measuring Similarity between Semantic Business Process Models , 2007, APCCM.

[9]  Philip Resnik,et al.  Using Information Content to Evaluate Semantic Similarity in a Taxonomy , 1995, IJCAI.

[10]  Eva Blomqvist Fully Automatic Construction of Enterprise Ontologies Using Design Patterns: Initial Method and First Experiences , 2005, OTM Conferences.

[11]  Karl W. Wagner,et al.  The ARIS Toolset , 2002 .

[12]  Martha Palmer,et al.  Verb Semantics and Lexical Selection , 1994, ACL.

[13]  Kurt Jensen,et al.  An Introduction to the Theoretical Aspects of Coloured Petri Nets , 1993, REX School/Symposium.

[14]  Peter Huber,et al.  Hierarchies in coloured Petri nets , 1991, Applications and Theory of Petri Nets.

[15]  Andreas Oberweis,et al.  Ontology Based Business Process Description , 2005, EMOI-INTEROP.

[16]  Andreas Oberweis,et al.  Rule-based Autocompletion of Business Process Models , 2007, CAiSE Forum.

[17]  Mounira Harzallah,et al.  A Tree-Based Similarity for Evaluating Concept Proximities in an Ontology , 2006, Data Science and Classification.

[18]  Ted Pedersen,et al.  WordNet::Similarity - Measuring the Relatedness of Concepts , 2004, NAACL.

[19]  Christiane Fellbaum,et al.  Book Reviews: WordNet: An Electronic Lexical Database , 1999, CL.

[20]  Wolfgang Reisig,et al.  Lectures on Petri Nets I: Basic Models , 1996, Lecture Notes in Computer Science.

[21]  Georg Lausen,et al.  Modeling and Analysis of the Behavior of Information Systems , 1988, IEEE Trans. Software Eng..

[22]  Wil M. P. van der Aalst,et al.  The Application of Petri Nets to Workflow Management , 1998, J. Circuits Syst. Comput..

[23]  Roy Rada,et al.  Development and application of a metric on semantic nets , 1989, IEEE Trans. Syst. Man Cybern..

[24]  L. Stein,et al.  OWL Web Ontology Language - Reference , 2004 .