Design-time analysis of data inaccuracy awareness at runtime

Yotam Evron; Pnina Soffer; Anna Zamansky

doi:10.1007/978-3-319-74030-0_47

Design-time analysis of data inaccuracy awareness at runtime

Yotam Evron, Pnina Soffer, Anna Zamansky

Department of Information Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Analyzing potential data inaccuracy is an important aspect of business process design that has been mostly overlooked so far. To this end, process models should express the relevant information to support such analysis. In this paper we propose a formal framework for design-time analysis of potential data inaccuracy situations. In particular, we define a property of Data Inaccuracy Awareness which indicates the ability to know at runtime whether data values are accurate representations of real values. We propose an algorithm for analyzing this property at design time based on a process model. A preliminary evaluation of the applicability and scalability of the algorithm using a benchmark collection of process models is reported.

Original language	English
Title of host publication	Business Process Management Workshops - BPM 2017 International Workshops, Revised Papers
Editors	Ernest Teniente, Matthias Weidlich
Publisher	Springer Verlag
Pages	600-612
Number of pages	13
ISBN (Print)	9783319740294
DOIs	https://doi.org/10.1007/978-3-319-74030-0_47
State	Published - 2018
Event	15th International Conference on Business Process Management, BPM 2017 - Barcelona, Spain Duration: 10 Sep 2017 → 15 Sep 2017

Publication series

Name	Lecture Notes in Business Information Processing
Volume	308
ISSN (Print)	1865-1348

Conference

Conference	15th International Conference on Business Process Management, BPM 2017
Country/Territory	Spain
City	Barcelona
Period	10/09/17 → 15/09/17

Bibliographical note

Publisher Copyright:
© Springer International Publishing AG 2018.

Keywords

Business process management
Business process modeling
Data inaccuracy

ASJC Scopus subject areas

Management Information Systems
Control and Systems Engineering
Business and International Management
Information Systems
Modeling and Simulation
Information Systems and Management

Access to Document

10.1007/978-3-319-74030-0_47

Cite this

Evron, Y., Soffer, P., & Zamansky, A. (2018). Design-time analysis of data inaccuracy awareness at runtime. In E. Teniente, & M. Weidlich (Eds.), Business Process Management Workshops - BPM 2017 International Workshops, Revised Papers (pp. 600-612). (Lecture Notes in Business Information Processing; Vol. 308). Springer Verlag. https://doi.org/10.1007/978-3-319-74030-0_47

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Evron, Y , Soffer, P & Zamansky, A 2018, Design-time analysis of data inaccuracy awareness at runtime. in E Teniente & M Weidlich (eds), Business Process Management Workshops - BPM 2017 International Workshops, Revised Papers. Lecture Notes in Business Information Processing, vol. 308, Springer Verlag, pp. 600-612, 15th International Conference on Business Process Management, BPM 2017, Barcelona, Spain, 10/09/17. https://doi.org/10.1007/978-3-319-74030-0_47

Design-time analysis of data inaccuracy awareness at runtime. / Evron, Yotam ; Soffer, Pnina ; Zamansky, Anna.
Business Process Management Workshops - BPM 2017 International Workshops, Revised Papers. ed. / Ernest Teniente; Matthias Weidlich. Springer Verlag, 2018. p. 600-612 (Lecture Notes in Business Information Processing; Vol. 308).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - Analyzing potential data inaccuracy is an important aspect of business process design that has been mostly overlooked so far. To this end, process models should express the relevant information to support such analysis. In this paper we propose a formal framework for design-time analysis of potential data inaccuracy situations. In particular, we define a property of Data Inaccuracy Awareness which indicates the ability to know at runtime whether data values are accurate representations of real values. We propose an algorithm for analyzing this property at design time based on a process model. A preliminary evaluation of the applicability and scalability of the algorithm using a benchmark collection of process models is reported.

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Design-time analysis of data inaccuracy awareness at runtime

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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