Data-Driven Process Control and Exception Handling in Process Management Systems

Stefanie Rinderle; Manfred Reichert

doi:10.1007/11767138_19

Data-Driven Process Control and Exception Handling in Process Management Systems

Stefanie Rinderle, Manfred Reichert

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

34 Citations (Scopus)

1 Downloads (Pure)

Abstract

Business processes are often characterized by high variability and dynamics, which cannot be always captured in contemporary process management systems (PMS). Adaptive PMS have emerged in recent years, but do not completely solve this problem. In particular, users are not adequately supported in dealing with real–world exceptions. Exception handling usually requires manual interactions and necessary process adaptations have to be defined at the control flow level. Altogether, only experienced users are able to cope with these tasks. As an alternative, changes on process data (elements) can be more easily accomplished, and a more data–driven view on (adaptive) PMS can help to bridge the gap between real–world processes and computerized ones. In this paper we present an approach for data–driven process control allowing for the automated expansion and adaptation of task nets during runtime. By integrating and exploiting context information this approach further enables automated exception handling at a high level and in a user–friendly way. Altogether, the presented work provides an added value to current adaptive PMS.

Original language	English
Title of host publication	Advanced Information Systems Engineering
Subtitle of host publication	18th International Conference, CAiSE 2006, Luxembourg, Luxembourg, June 5-9, 2006, Proceedings
Editors	Eric Dubois, Klaus Pohl
Place of Publication	Berlin, Heidelberg, New York
Publisher	Springer
Pages	273-287
Number of pages	15
ISBN (Electronic)	978-3-540-34653-1
ISBN (Print)	978-3-540-34652-4
DOIs	https://doi.org/10.1007/11767138_19
Publication status	Published - Jun 2006
Event	18th International Conference on Advanced Information Systems Engineering, CAiSE 2006 - Luxembourg, Luxembourg Duration: 5 Jun 2006 → 9 Jun 2006 Conference number: 18

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	4001
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	18th International Conference on Advanced Information Systems Engineering, CAiSE 2006
Abbreviated title	CAiSE
Country/Territory	Luxembourg
City	Luxembourg
Period	5/06/06 → 9/06/06

Keywords

SCS-Services
n/a OA procedure

Access to Document

10.1007/11767138_19

Cite this

Rinderle, S., & Reichert, M. (2006). Data-Driven Process Control and Exception Handling in Process Management Systems. In E. Dubois, & K. Pohl (Eds.), Advanced Information Systems Engineering: 18th International Conference, CAiSE 2006, Luxembourg, Luxembourg, June 5-9, 2006, Proceedings (pp. 273-287). (Lecture Notes in Computer Science; Vol. 4001). Springer. https://doi.org/10.1007/11767138_19

Rinderle, Stefanie ; Reichert, Manfred. / Data-Driven Process Control and Exception Handling in Process Management Systems. Advanced Information Systems Engineering: 18th International Conference, CAiSE 2006, Luxembourg, Luxembourg, June 5-9, 2006, Proceedings. editor / Eric Dubois ; Klaus Pohl. Berlin, Heidelberg, New York : Springer, 2006. pp. 273-287 (Lecture Notes in Computer Science).

@inproceedings{960c05f303a34abf8d662d1da92804af,

title = "Data-Driven Process Control and Exception Handling in Process Management Systems",

abstract = "Business processes are often characterized by high variability and dynamics, which cannot be always captured in contemporary process management systems (PMS). Adaptive PMS have emerged in recent years, but do not completely solve this problem. In particular, users are not adequately supported in dealing with real–world exceptions. Exception handling usually requires manual interactions and necessary process adaptations have to be defined at the control flow level. Altogether, only experienced users are able to cope with these tasks. As an alternative, changes on process data (elements) can be more easily accomplished, and a more data–driven view on (adaptive) PMS can help to bridge the gap between real–world processes and computerized ones. In this paper we present an approach for data–driven process control allowing for the automated expansion and adaptation of task nets during runtime. By integrating and exploiting context information this approach further enables automated exception handling at a high level and in a user–friendly way. Altogether, the presented work provides an added value to current adaptive PMS.",

keywords = "SCS-Services, n/a OA procedure",

author = "Stefanie Rinderle and Manfred Reichert",

year = "2006",

month = jun,

doi = "10.1007/11767138_19",

language = "English",

isbn = "978-3-540-34652-4",

series = "Lecture Notes in Computer Science",

publisher = "Springer",

pages = "273--287",

editor = "Eric Dubois and Klaus Pohl",

booktitle = "Advanced Information Systems Engineering",

address = "Germany",

note = "18th International Conference on Advanced Information Systems Engineering, CAiSE 2006, CAiSE ; Conference date: 05-06-2006 Through 09-06-2006",

}

Rinderle, S & Reichert, M 2006, Data-Driven Process Control and Exception Handling in Process Management Systems. in E Dubois & K Pohl (eds), Advanced Information Systems Engineering: 18th International Conference, CAiSE 2006, Luxembourg, Luxembourg, June 5-9, 2006, Proceedings. Lecture Notes in Computer Science, vol. 4001, Springer, Berlin, Heidelberg, New York, pp. 273-287, 18th International Conference on Advanced Information Systems Engineering, CAiSE 2006, Luxembourg, Luxembourg, 5/06/06. https://doi.org/10.1007/11767138_19

Data-Driven Process Control and Exception Handling in Process Management Systems. / Rinderle, Stefanie; Reichert, Manfred.
Advanced Information Systems Engineering: 18th International Conference, CAiSE 2006, Luxembourg, Luxembourg, June 5-9, 2006, Proceedings. ed. / Eric Dubois; Klaus Pohl. Berlin, Heidelberg, New York: Springer, 2006. p. 273-287 (Lecture Notes in Computer Science; Vol. 4001).

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

TY - GEN

T1 - Data-Driven Process Control and Exception Handling in Process Management Systems

AU - Rinderle, Stefanie

AU - Reichert, Manfred

N1 - Conference code: 18

PY - 2006/6

Y1 - 2006/6

N2 - Business processes are often characterized by high variability and dynamics, which cannot be always captured in contemporary process management systems (PMS). Adaptive PMS have emerged in recent years, but do not completely solve this problem. In particular, users are not adequately supported in dealing with real–world exceptions. Exception handling usually requires manual interactions and necessary process adaptations have to be defined at the control flow level. Altogether, only experienced users are able to cope with these tasks. As an alternative, changes on process data (elements) can be more easily accomplished, and a more data–driven view on (adaptive) PMS can help to bridge the gap between real–world processes and computerized ones. In this paper we present an approach for data–driven process control allowing for the automated expansion and adaptation of task nets during runtime. By integrating and exploiting context information this approach further enables automated exception handling at a high level and in a user–friendly way. Altogether, the presented work provides an added value to current adaptive PMS.

AB - Business processes are often characterized by high variability and dynamics, which cannot be always captured in contemporary process management systems (PMS). Adaptive PMS have emerged in recent years, but do not completely solve this problem. In particular, users are not adequately supported in dealing with real–world exceptions. Exception handling usually requires manual interactions and necessary process adaptations have to be defined at the control flow level. Altogether, only experienced users are able to cope with these tasks. As an alternative, changes on process data (elements) can be more easily accomplished, and a more data–driven view on (adaptive) PMS can help to bridge the gap between real–world processes and computerized ones. In this paper we present an approach for data–driven process control allowing for the automated expansion and adaptation of task nets during runtime. By integrating and exploiting context information this approach further enables automated exception handling at a high level and in a user–friendly way. Altogether, the presented work provides an added value to current adaptive PMS.

KW - SCS-Services

KW - n/a OA procedure

U2 - 10.1007/11767138_19

DO - 10.1007/11767138_19

M3 - Conference contribution

SN - 978-3-540-34652-4

T3 - Lecture Notes in Computer Science

SP - 273

EP - 287

BT - Advanced Information Systems Engineering

A2 - Dubois, Eric

A2 - Pohl, Klaus

PB - Springer

CY - Berlin, Heidelberg, New York

T2 - 18th International Conference on Advanced Information Systems Engineering, CAiSE 2006

Y2 - 5 June 2006 through 9 June 2006

ER -

Rinderle S, Reichert M. Data-Driven Process Control and Exception Handling in Process Management Systems. In Dubois E, Pohl K, editors, Advanced Information Systems Engineering: 18th International Conference, CAiSE 2006, Luxembourg, Luxembourg, June 5-9, 2006, Proceedings. Berlin, Heidelberg, New York: Springer. 2006. p. 273-287. (Lecture Notes in Computer Science). doi: 10.1007/11767138_19

Data-Driven Process Control and Exception Handling in Process Management Systems

Abstract

Publication series

Conference

Keywords

Access to Document

Fingerprint

Cite this