@inproceedings{9400dbee7fed4e43ba4bdd7346d9b50c,
title = "Incorporating data inaccuracy considerations in process models",
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. Design-time analysis of potential data inaccuracy has been mostly overlooked so far. In this paper we propose a conceptual framework for incorporating data inaccuracy considerations in process models to support an analysis of data inaccuracy at design time and empirically evaluate its usability by process designers.",
keywords = "Business process management, Business process modeling, Data inaccuracy",
author = "Yotam Evron and Pnina Soffer and Anna Zamansky",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 18th International Conference on Business Process Modeling, Development and Support, BPMDS 2017 and 22nd International Conference on Evaluation and Modeling Methods for Systems Analysis and Development, EMMSAD 2017 held at Conference on Advanced Informa... ; Conference date: 12-06-2017 Through 13-06-2017",
year = "2017",
doi = "https://doi.org/10.1007/978-3-319-59466-8_19",
language = "American English",
isbn = "9783319594651",
series = "Lecture Notes in Business Information Processing",
publisher = "Springer Verlag",
pages = "305--318",
editor = "Jens Gulden and Selmin Nurcan and Iris Reinhartz-Berger and Palash Bera and Wided Guedria",
booktitle = "Enterprise, Business-Process and Information Systems Modeling - 18th International Conference, BPMDS 2017, 22nd International Conference, EMMSAD 2017 Held at CAiSE 2017, Proceedings",
address = "Germany",
}