Abstract
Workflow technology has become a standard solution for managing increasingly complex business processes. Successful business process management depends on effective workflow modeling and analysis. One of the important aspects of workflow analysis is the data-flow perspective because, given a syntactically correct process sequence, errors can still occur during workflow execution due to incorrect data-flow specifications. However, there have been only scant treatments of the data-flow perspective in the literature and no formal methodologies are available for systematically discovering data-flow errors in a workflow model. As an indication of this research gap, existing commercial workflow management systems do not provide tools for data-flow analysis at design time. In this paper, we provide a data-flow perspective for detecting data-flow anomalies such as missing data, redundant data, and potential data conflicts. Our data-flow framework includes two basic components: data-flow specification and data-flow analysis; these components add more analytical rigor to business process management.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 374-391 |
| Number of pages | 18 |
| Journal | Information Systems Research |
| Volume | 17 |
| Issue number | 4 |
| DOIs | |
| State | Published - Dec 2006 |
Keywords
- Data-flow anomalies
- Data-flow specification
- Data-flow verification
- Dependency analysis
- Process data diagram
- Workflow modeling
ASJC Scopus subject areas
- Management Information Systems
- Information Systems
- Computer Networks and Communications
- Information Systems and Management
- Library and Information Sciences