Verification of Quantitative Temporal Compliance Requirements in Process Descriptions Over Event Logs

Marisol Barrientos; Karolin Winter; Juergen Mangler; Stefanie Rinderle-Ma

doi:10.1007/978-3-031-34560-9_25

Verification of Quantitative Temporal Compliance Requirements in Process Descriptions Over Event Logs

Marisol Barrientos, Karolin Winter, Juergen Mangler, Stefanie Rinderle-Ma

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

3 Citations (Scopus)

3 Downloads (Pure)

Abstract

Process compliance verification ensures that processes adhere to a set of given regulatory requirements which are typically assumed to be available in a formalized way using, e.g., LTL. However, formalized requirements are rarely available in practice, but rather embedded in regulatory documents such as the GDPR, requiring extraction and formalization by experts. Due to the vast amount and frequent changes in regulatory documents, it is almost impossible to keep formalized requirements up to date in a manual way. Therefore, this paper presents an approach towards compliance verification between natural language text and event logs without the need for requirements formalization. This enables humans to cope with an increasingly complex environment. The approach focuses on quantitative temporal requirements (QTCR) and consists of multiple steps. First, we identify clauses with temporal expressions from process descriptions. Second, we generate a set of QTCR by mapping the retrieved clauses to event log activities. Finally, in the third step, we verify that the event log is compliant with the QTCR. The approach is evaluated based on process descriptions and synthesized event logs. For the latter, we implement time shifting as a concept for simulating real-life logs with varying temporal challenges.

Original language	English
Title of host publication	Advanced Information Systems Engineering
Subtitle of host publication	35th International Conference, CAiSE 2023, Zaragoza, Spain, June 12–16, 2023, Proceedings
Editors	Marta Indulska, Iris Reinhartz-Berger, Carlos Cetina, Oscar Pastor
Pages	417-433
Number of pages	17
ISBN (Electronic)	978-3-031-34560-9
DOIs	https://doi.org/10.1007/978-3-031-34560-9_25
Publication status	Published - 2023
Externally published	Yes
Event	35th International Conference on Advanced Information Systems Engineering, CAiSE 2023 - Zaragoza, Spain Duration: 12 Jun 2023 → 16 Jun 2023 https://caise23.svit.usj.es/

Publication series

Name	Lecture Notes in Computer Science (LNCS)
Publisher	Springer
Volume	13901
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	35th International Conference on Advanced Information Systems Engineering, CAiSE 2023
Abbreviated title	CAiSE 2023
Country/Territory	Spain
City	Zaragoza
Period	12/06/23 → 16/06/23
Internet address	https://caise23.svit.usj.es/

Funding

Acknowledgments. Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – EXC-2023 Internet of Production – 390621612. We thank Jan-Gustav Michnia for his initial exploration of the FHE library CONCRETE [8]. We followed an abstract research methodology [21] to structure and organize our research collaborations. Acknowledgements. This research is supported by the Estonian Research Council (PRG1226) and the European Research Council (PIX Project). Acknowledgement. This work has been funded by the following projects: AETHER-US (PID2020-112540RB-C44), ALBA-US (TED2021-130355B-C32) AEI/10.13039/ 501100011033/Unión Europea NextGenerationEU/PRTR, METAMORFOSIS (US-1381375), and COPERNICA (P20-01224). Acknowledgment. This work was supported by the NSF, grant number 1952225 and the German Federal Ministry of Education and Research (BMBF), grant number 16DII133. Acknowledgements. A.G.S. was supported by the Valencian Innovation Agency and Innovation through the OGMIOS project (INNEST/2021/57), the Gen-eralitat Valenciana through the CoMoDiD project (CIPROM/2021/023), and the Spanish State Research Agency through the DELFOS (PDC2021-121243-I00,MICIN/AEI/10.13039/501 100011033) and SREC (PID2021-123824OB-I00) projects, and co-financed with ERDF and the European Union Next Generation EU/PRTR. Work funded by the European Research Council (PIX Project). Acknowledgement. This work has been partly funded by SAP SE in the context of the research project “Building Semantic Models for the Process Mining Pipeline”. Acknowledgments. This work is partially funded by Industrial Doctorates from Gen- Acknowledgements. We thank the anonymous reviewers for their valuable feedback. This work has been partially funded by MUR PRIN project 2017TWRCNB SEDUCE, and the PNRR MUR project VITALITY (ECS00000041) Spoke 2 ASTRA - Advanced Space Technologies and Research Alliance. Acknowledgements. This work was supported in part by Centro para el Desar-rollo Tecnológico Industrial (CDTI) under Grant IDI-20210948 (STRATO, nuevaS herramienTas para la modeRnizAción de sisTemas heredadOs). Acknowledgements. Research supported by MCIN/AEI/10.13039/501100011033 and the “European Union NextGenerationEU/PRTR” under contract PID2021-125438OB-I00. Xabier Garmendia enjoys a grant from the University of the Basque Country - PIF20/236. Acknowledgement. This research was supported by ERDF “CyberSecurity, CyberCrime and Critical Information Infrastructures Center of Excellence” (No. CZ.02.1.01/0.0/0.0/16 019/0000822). Computational resources were supplied by the project “e-Infrastruktura CZ” (e-INFRA CZ LM2018140) supported by the Ministry of Education, Youth and Sports of the Czech Republic. A special thanks to the e-INFRA CZ SensitiveCloud team for their participation in the study. This research was also co-founded by the European Union under Grant Agreement No. 101087529. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Research Executive Agency. Neither the European Union nor the granting authority can be held responsible for them. Our work is supported by the Bavarian Research Foundation (grant no. AZ-1390-19). Acknowledgement. This work was supported by the European Social Fund via ”ICT programme” measure, the European Regional Development Fund, and the programme Mobilitas Pluss (2014-2020.4.01.16-0024). Acknowledgement. This work is supported by National Key Research and Development Program (2020AAA0107800), National Natural Science Foundation of China Acknowledgement. The research leading to these results received funding from French Research Agency through the ANR-19-CE25-0003 KOALA project and from the Norwegian Research Council through the DILUTE project (Grant No. 262854/F20). Acknowledgements. This work is supported by the H2020 projects TAILOR: Foundations of Trustworthy AI - Integrating Reasoning, Learning and Optimization – EC Grant Agreement number 952215 – and SPICE: Social Cohesion, Participation and Inclusion through Cultural Engagement – EC Grant Agreement number 870811, as well as by the Italian PNRR MUR project PE0000013-FAIR. Acknowledgements. This work has been partially funded through the Austrian Acknowledgements. This work has been partly funded by SAP SE in the context of the research project “Building Semantic Models for the Process Mining Pipeline” and by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – project number 277991500. We are grateful to the whole team that worked collaboratively for the success of CAiSE 2023 and its related events. We sincerely thank the General Chairs, Carlos Cetina and Oscar Pastor, the Local Organization Chair, Raul Lapeña; and the Proceedings Chair, Pierluigi Plebani, for facilitating our work as Program Chairs. We are also thankful to Giancarlo Guizzardi, Bran Selic and Pnina Soffer for their inspirational keynote presentations. We further wish to thank: the Forum Chairs, Cristina Cabanillas and Francisca Pérez; the Workshop Chairs, Pnina Soffer and Marcela Ruiz; the Tutorial Chairs, Fabi-ano Dalpiaz and Jelena Zdravkovic; the Panel Chairs, Hajo A. Reijers and Stefanie Rinderle-Ma; the Doctoral Consortium Chairs, Daniel Méndez and Raimundas Matule-vicius; the Journal-first Track Chairs, Jan Mendling and Lola Burgueño; the Publicity Chairs, Jolita Ralyté, Guilherme H. Travassos, Anna Segooa and Anna Kalenkova; the Web and Social Media Chairs, Jorge Echeverria and Africa Domingo; the Sustainability Chairs, Sergio España and Monica Vitali; the Sponsor Chairs, Pedro Valderas and Antonio Ruiz; the Student Chairs, Selmin Nurcan and Estefania Serral; the PhD Award Chairs, John Krogstie and Camille Salinesi; and the Research Project Exhibition Chairs, Giovanni Giachetti, Jaime Font, Lorena Arcega and José Fabián Reyes.

Keywords

Compliance Verification
Event Logs
Natural Language Text
Process Descriptions
Temporal Compliance Requirements

Access to Document

10.1007/978-3-031-34560-9_25

Cite this

Barrientos, M., Winter, K., Mangler, J., & Rinderle-Ma, S. (2023). Verification of Quantitative Temporal Compliance Requirements in Process Descriptions Over Event Logs. In M. Indulska, I. Reinhartz-Berger, C. Cetina, & O. Pastor (Eds.), Advanced Information Systems Engineering: 35th International Conference, CAiSE 2023, Zaragoza, Spain, June 12–16, 2023, Proceedings (pp. 417-433). (Lecture Notes in Computer Science (LNCS); Vol. 13901). https://doi.org/10.1007/978-3-031-34560-9_25

Barrientos, Marisol ; Winter, Karolin ; Mangler, Juergen et al. / Verification of Quantitative Temporal Compliance Requirements in Process Descriptions Over Event Logs. Advanced Information Systems Engineering: 35th International Conference, CAiSE 2023, Zaragoza, Spain, June 12–16, 2023, Proceedings. editor / Marta Indulska ; Iris Reinhartz-Berger ; Carlos Cetina ; Oscar Pastor. 2023. pp. 417-433 (Lecture Notes in Computer Science (LNCS)).

@inproceedings{d9910aa7cc2c45d0941ea90cb7cdf2cd,

title = "Verification of Quantitative Temporal Compliance Requirements in Process Descriptions Over Event Logs",

abstract = "Process compliance verification ensures that processes adhere to a set of given regulatory requirements which are typically assumed to be available in a formalized way using, e.g., LTL. However, formalized requirements are rarely available in practice, but rather embedded in regulatory documents such as the GDPR, requiring extraction and formalization by experts. Due to the vast amount and frequent changes in regulatory documents, it is almost impossible to keep formalized requirements up to date in a manual way. Therefore, this paper presents an approach towards compliance verification between natural language text and event logs without the need for requirements formalization. This enables humans to cope with an increasingly complex environment. The approach focuses on quantitative temporal requirements (QTCR) and consists of multiple steps. First, we identify clauses with temporal expressions from process descriptions. Second, we generate a set of QTCR by mapping the retrieved clauses to event log activities. Finally, in the third step, we verify that the event log is compliant with the QTCR. The approach is evaluated based on process descriptions and synthesized event logs. For the latter, we implement time shifting as a concept for simulating real-life logs with varying temporal challenges.",

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Barrientos, M, Winter, K, Mangler, J & Rinderle-Ma, S 2023, Verification of Quantitative Temporal Compliance Requirements in Process Descriptions Over Event Logs. in M Indulska, I Reinhartz-Berger, C Cetina & O Pastor (eds), Advanced Information Systems Engineering: 35th International Conference, CAiSE 2023, Zaragoza, Spain, June 12–16, 2023, Proceedings. Lecture Notes in Computer Science (LNCS), vol. 13901, pp. 417-433, 35th International Conference on Advanced Information Systems Engineering, CAiSE 2023, Zaragoza, Spain, 12/06/23. https://doi.org/10.1007/978-3-031-34560-9_25

Verification of Quantitative Temporal Compliance Requirements in Process Descriptions Over Event Logs. / Barrientos, Marisol; Winter, Karolin; Mangler, Juergen et al.
Advanced Information Systems Engineering: 35th International Conference, CAiSE 2023, Zaragoza, Spain, June 12–16, 2023, Proceedings. ed. / Marta Indulska; Iris Reinhartz-Berger; Carlos Cetina; Oscar Pastor. 2023. p. 417-433 (Lecture Notes in Computer Science (LNCS); Vol. 13901).

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

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Barrientos M, Winter K, Mangler J, Rinderle-Ma S. Verification of Quantitative Temporal Compliance Requirements in Process Descriptions Over Event Logs. In Indulska M, Reinhartz-Berger I, Cetina C, Pastor O, editors, Advanced Information Systems Engineering: 35th International Conference, CAiSE 2023, Zaragoza, Spain, June 12–16, 2023, Proceedings. 2023. p. 417-433. (Lecture Notes in Computer Science (LNCS)). doi: 10.1007/978-3-031-34560-9_25

Verification of Quantitative Temporal Compliance Requirements in Process Descriptions Over Event Logs

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