A conceptual framework for supporting deep exploration of business process behavior

Arava Tsoury; Pnina Soffer; Iris Reinhartz-Berger

doi:10.1007/978-3-030-00847-5_6

A conceptual framework for supporting deep exploration of business process behavior

Arava Tsoury, Pnina Soffer, Iris Reinhartz-Berger

Department of Information Systems

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

Abstract

Process mining serves for gaining insights into business process behavior based on event logs. These techniques are typically limited to addressing data included in the log. Recent studies suggest extracting data-rich event logs from databases or transaction logs. However, these event logs are at a very fine granularity level, substituting business-level activities by low-level database operations, and challenging data-aware process mining. To address this gap, we propose an approach that enables a broad and deep exploration of process behavior, using a conceptual framework based on three sources: the event log that holds information regarding the business-level activities, the (relational) database that stores the current values of data elements, and the transaction (redo) log that captures historical data operations performed on the database as a result of business process activities. Nine types of operations define how to map subsets of elements among the three sources in order to support human analysts in exploring and understanding the reasons of observed process behavior. A preliminary evaluation analyzes the outcomes for four useful scenarios.

Original language	English
Title of host publication	Conceptual Modeling - 37th International Conference, ER 2018, Proceedings
Editors	Zhanhuai Li, Juan C. Trujillo, Xiaoyong Du, Mong Li Lee, Karen C. Davis, Tok Wang Ling, Guoliang Li
Publisher	Springer Verlag
Pages	58-71
Number of pages	14
ISBN (Print)	9783030008468
DOIs	https://doi.org/10.1007/978-3-030-00847-5_6
State	Published - 2018
Event	37th International Conference on Conceptual Modeling, ER 2018 - Xi'an, China Duration: 22 Oct 2018 → 25 Oct 2018

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11157 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	37th International Conference on Conceptual Modeling, ER 2018
Country/Territory	China
City	Xi'an
Period	22/10/18 → 25/10/18

Bibliographical note

Publisher Copyright:
© Springer Nature Switzerland AG 2018.

Keywords

Business process
Data-aware
Database
Event log
Process mining
Transaction log

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-030-00847-5_6

Cite this

Tsoury, A., Soffer, P., & Reinhartz-Berger, I. (2018). A conceptual framework for supporting deep exploration of business process behavior. In Z. Li, J. C. Trujillo, X. Du, M. L. Lee, K. C. Davis, T. W. Ling, & G. Li (Eds.), Conceptual Modeling - 37th International Conference, ER 2018, Proceedings (pp. 58-71). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11157 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-00847-5_6

Tsoury, Arava ; Soffer, Pnina ; Reinhartz-Berger, Iris. / A conceptual framework for supporting deep exploration of business process behavior. Conceptual Modeling - 37th International Conference, ER 2018, Proceedings. editor / Zhanhuai Li ; Juan C. Trujillo ; Xiaoyong Du ; Mong Li Lee ; Karen C. Davis ; Tok Wang Ling ; Guoliang Li. Springer Verlag, 2018. pp. 58-71 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Process mining serves for gaining insights into business process behavior based on event logs. These techniques are typically limited to addressing data included in the log. Recent studies suggest extracting data-rich event logs from databases or transaction logs. However, these event logs are at a very fine granularity level, substituting business-level activities by low-level database operations, and challenging data-aware process mining. To address this gap, we propose an approach that enables a broad and deep exploration of process behavior, using a conceptual framework based on three sources: the event log that holds information regarding the business-level activities, the (relational) database that stores the current values of data elements, and the transaction (redo) log that captures historical data operations performed on the database as a result of business process activities. Nine types of operations define how to map subsets of elements among the three sources in order to support human analysts in exploring and understanding the reasons of observed process behavior. A preliminary evaluation analyzes the outcomes for four useful scenarios.",

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author = "Arava Tsoury and Pnina Soffer and Iris Reinhartz-Berger",

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year = "2018",

doi = "10.1007/978-3-030-00847-5_6",

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Tsoury, A, Soffer, P & Reinhartz-Berger, I 2018, A conceptual framework for supporting deep exploration of business process behavior. in Z Li, JC Trujillo, X Du, ML Lee, KC Davis, TW Ling & G Li (eds), Conceptual Modeling - 37th International Conference, ER 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11157 LNCS, Springer Verlag, pp. 58-71, 37th International Conference on Conceptual Modeling, ER 2018, Xi'an, China, 22/10/18. https://doi.org/10.1007/978-3-030-00847-5_6

A conceptual framework for supporting deep exploration of business process behavior. / Tsoury, Arava; Soffer, Pnina ; Reinhartz-Berger, Iris.
Conceptual Modeling - 37th International Conference, ER 2018, Proceedings. ed. / Zhanhuai Li; Juan C. Trujillo; Xiaoyong Du; Mong Li Lee; Karen C. Davis; Tok Wang Ling; Guoliang Li. Springer Verlag, 2018. p. 58-71 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11157 LNCS).

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

TY - GEN

T1 - A conceptual framework for supporting deep exploration of business process behavior

AU - Tsoury, Arava

AU - Soffer, Pnina

AU - Reinhartz-Berger, Iris

N1 - Publisher Copyright: © Springer Nature Switzerland AG 2018.

PY - 2018

Y1 - 2018

N2 - Process mining serves for gaining insights into business process behavior based on event logs. These techniques are typically limited to addressing data included in the log. Recent studies suggest extracting data-rich event logs from databases or transaction logs. However, these event logs are at a very fine granularity level, substituting business-level activities by low-level database operations, and challenging data-aware process mining. To address this gap, we propose an approach that enables a broad and deep exploration of process behavior, using a conceptual framework based on three sources: the event log that holds information regarding the business-level activities, the (relational) database that stores the current values of data elements, and the transaction (redo) log that captures historical data operations performed on the database as a result of business process activities. Nine types of operations define how to map subsets of elements among the three sources in order to support human analysts in exploring and understanding the reasons of observed process behavior. A preliminary evaluation analyzes the outcomes for four useful scenarios.

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Conceptual Modeling - 37th International Conference, ER 2018, Proceedings

A2 - Li, Zhanhuai

A2 - Trujillo, Juan C.

A2 - Du, Xiaoyong

A2 - Lee, Mong Li

A2 - Davis, Karen C.

A2 - Ling, Tok Wang

A2 - Li, Guoliang

PB - Springer Verlag

T2 - 37th International Conference on Conceptual Modeling, ER 2018

Y2 - 22 October 2018 through 25 October 2018

ER -

Tsoury A, Soffer P , Reinhartz-Berger I. A conceptual framework for supporting deep exploration of business process behavior. In Li Z, Trujillo JC, Du X, Lee ML, Davis KC, Ling TW, Li G, editors, Conceptual Modeling - 37th International Conference, ER 2018, Proceedings. Springer Verlag. 2018. p. 58-71. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-00847-5_6

A conceptual framework for supporting deep exploration of business process behavior

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this