Abstract
Business processes are designed with the assumption that the data used by the process is an accurate reflection of reality. However, this assumption does not always hold, and situations of data inaccuracy might occur which bear substantial consequences to the process and to business goals. Until now, data inaccuracy has mainly been addressed in the area of business process management as a possible exception at runtime, to be resolved through exception handling mechanisms [?9]. Design-time analysis of potential data inaccuracy has been mostly overlooked so far. In this paper we describe a research agenda for developing a method for supporting process modelers in designing more robust processes with respect to data inaccuracy.
| Original language | English |
|---|---|
| Journal | CEUR Workshop Proceedings |
| Volume | 1603 |
| State | Published - 2016 |
| Event | CAiSE 2016 Doctoral Consortium, CAiSE-DC 2016, co-located with 28th International Conference on Advanced Information Systems Engineering, CAiSE 2016 - Ljubljana, Slovenia Duration: 13 Jun 2016 → 17 Jun 2016 |
Keywords
- Business process modelling
- Data in business processes
- Data inaccuracy
- Formal analysis
ASJC Scopus subject areas
- General Computer Science