Detecting system-level behavior leading to dynamic bottlenecks

Toosinezhad, Z., Fahland, D., Köroglu, Ö., & Van Der Aalst, W. M. P. (2020). Detecting system-level behavior leading to dynamic bottlenecks. In B. van Dongen, M. Montali, & M. T. Wynn (Eds.), Proceedings – 2020 2nd International Conference on Process Mining, ICPM 2020 (pp. 17-24). [9230102] Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICPM49681.2020.00014 Abstract Dynamic Read More …

Defining meaningful local process models

Brunings, M., Fahland, D., & van Dongen, B. (2020). Defining meaningful local process models. In W. van der Aalst, R. Bergenthum, & J. Carmona (Eds.), ATAED 2020 Algorithms & Theories for the Analysis of Event Data 2020: Proceedings of the International Workshop on Algorithms & Theories for the Analysis of Event Data 2020: Satellite event Read More …

Mining process model descriptions of daily life through event abstraction

Tax, N., Sidorova, N., Haakma, R., & van der Aalst, W. M. P. (2018). Mining process model descriptions of daily life through event abstraction. In S. Kapoor, R. Bhatia, & Y. Bi (Eds.), Intelligent Systems and Applications: Extended and Selected Results from the SAI Intelligent Systems Conference (IntelliSys) 2016 (pp. 83-104). (Studies in Computational Intelligence; Read More …

Event abstraction for process mining using supervised learning techniques

Tax, N., Sidorova, N., Haakma, R., & van der Aalst, W. M. P. (2018). Event abstraction for process mining using supervised learning techniques. In Y. Bi, S. Kapoor, & R. Bhatia (Eds.), Proceedings of the SAI Intelligent Systems Conference (IntelliSys 2016), 21-22 September 2016, London, United Kingdom (pp. 251-269). (Lecture Notes in Networks and Systems; Read More …

Data Minimisation as Privacy and Trust Instrument in Business Processes

Zaman, R., Hassani, M., & van Dongen, B. F. (Accepted/In press). Data Minimisation as Privacy and Trust Instrument in Business Processes. In Business Process Management Workshops (BPM 2020) Springer. Abstract Data is vital for almost all sorts of business processes and workflows. However, the possession of personal data of other beings bear consequences. Data is Read More …

Facilitating GDPR compliance: the H2020 BPR4GDPR approach

Lioudakis, G. V., Koukovini, M. N., Papagiannakopoulou, E. I., Dellas, N., Kalaboukas, K., de Carvalho, R. M., Hassani, M., Bracciale, L., Bianchi, G., Juan-Verdejo, A., Alexakis, S., Gaudino, F., Cascone, D., & Barracano, P. (2020). Facilitating GDPR compliance: the H2020 BPR4GDPR approach. In I. O. Pappas, I. O. Pappas, P. Mikalef, L. Jaccheri, J. Krogstie, Read More …

On Enabling GDPR Compliance in Business Processes Through Data-Driven Solutions

Zaman, R., & Hassani, M. (2020). On Enabling GDPR Compliance in Business Processes Through Data-Driven Solutions. SN Computer Science, 1(4), 1-15. [210]. https://doi.org/10.1007/s42979-020-00215-x Abstract The collection and long-term retention of excessive data enables organisations to process data for insights in non-primary processes. The discovery of insights is promoted to be useful both for organisations and Read More …

Predicting Business Process Bottlenecks In Online Events Streams Under Concept Drifts

Spenrath, Y., & Hassani, M. (2020). Predicting Business Process Bottlenecks In Online Events Streams Under Concept Drifts. In M. Steglich, C. Muller, G. Neumann, & M. Walther (Eds.), Proceedings of European Council for Modelling and Simulation (ECMS) 2020 (pp. 190-196). (Proceedings European Council for Modelling and Simulation; Vol. 34, No. 1). European Council for Modeling Read More …

Why did my Consumer Shop? Learning an Efficient Distance Metric for Retailer Transaction Data

Spenrath, Y., Hassani, M., van Dongen, B. F., & Tariq, H. Why did my Consumer Shop? Learning an Efficient Distance Metric for Retailer Transaction Data. In Y. Dong, D. Mladenic, & C. Saunders (Eds.), Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track – European Conference, ECML PKDD 2020, Proceedings (pp. Read More …

An innovative online process mining framework for supporting incremental GDPR compliance of business processes

Zaman, R., Cuzzocrea, A., & Hassani, M. (2019). An innovative online process mining framework for supporting incremental GDPR compliance of business processes. In C. Baru, J. Huan, L. Khan, X. T. Hu, R. Ak, Y. Tian, R. Barga, C. Zaniolo, K. Lee, & Y. F. Ye (Eds.), 2019 IEEE International Conference on Big Data, Big Read More …

Detection of batch activities from event logs

Martin, N., Pufahl, L., & Mannhardt, F. (2021). Detection of batch activities from event logs. Information Systems, 95, [101642]. https://doi.org/10.1016/j.is.2020.101642 Abstract Organizations carry out a variety of business processes in order to serve their clients. Usually supported by information technology and systems, process execution data is logged in an event log. Process mining uses this Read More …

Designing a Privacy Dashboard for a Smart Manufacturing Environment

Mannhardt, F., Oliveira, M., & Petersen, S. A. (2020). Designing a Privacy Dashboard for a Smart Manufacturing Environment. In I. O. Pappas, I. O. Pappas, P. Mikalef, L. Jaccheri, J. Krogstie, Y. K. Dwivedi, & M. Mäntymäki (Eds.), Digital Transformation for a Sustainable Society in the 21st Century – I3E 2019 IFIP WG 6.11 International Read More …

Event abstraction in process mining: literature review and taxonomy

van Zelst, S. J., Mannhardt, F., de Leoni, M., & Koschmider, A. (2020). Event abstraction in process mining: literature review and taxonomy. Granular Computing, XX(XX). https://doi.org/10.1007/s41066-020-00226-2 Abstract The execution of processes in companies generates traces of event data, stored in the underlying information system(s), capturing the actual execution of the process. Analyzing event data, i.e., Read More …

Extensions to the bupaR Ecosystem: An Overview

Janssenswillen, G., Mannhardt, F., Creemers, M., Depaire, B., Jans, M., Jooken, L., Martin, N., & Van Houdt, G. (2020). Extensions to the bupaR Ecosystem: An Overview. In Proceedings of the ICPM Doctoral Consortium and Tool Demonstration Track 2020 co-located with the 2nd International Conference on Process Mining (ICPM 2020) (pp. 43-46). (CEUR Workshop Proceedings; Vol. Read More …

MINING E-MAIL CONVERSATIONS TO ENRICH EVENT LOGS: AN EXPLORATORY CASE STUDY OF A HIRING PROCESS IN A NORWEGIAN MUNICIPALITY

Goday-Verdaguer , A., Mannhardt, F., & Torvatn, H. Y. (2020). MINING E-MAIL CONVERSATIONS TO ENRICH EVENT LOGS: AN EXPLORATORY CASE STUDY OF A HIRING PROCESS IN A NORWEGIAN MUNICIPALITY. In Proceedings of the NOKOBIT conference 24-25th of November 2020 (Vol. 28) https://ojs.bibsys.no/index.php/Nokobit/article/view/867 Abstract Process improvement is an important challenge for the public sector, which struggles Read More …

Quantifying the Re-identification Risk of Event Logs for Process Mining: Empiricial Evaluation Paper

Nuñez von Voigt, S., Fahrenkrog-Petersen, S. A., Janssen, D., Koschmider, A., Tschorsch, F., Mannhardt, F., Landsiedel, O., & Weidlich, M. (2020). Quantifying the Re-identification Risk of Event Logs for Process Mining: Empiricial Evaluation Paper. In S. Dustdar, E. Yu, V. Pant, C. Salinesi, & D. Rieu (Eds.), Advanced Information Systems Engineering – 32nd International Conference, Read More …

Recommendations for enhancing the usability and understandability of process mining in healthcare

Martin, N., De Weerdt, J., Fernández-Llatas, C., Gal, A., Gatta, R., Ibáñez, G., Johnson, O., Mannhardt, F., Marco-Ruiz, L., Mertens, S., Munoz-Gama, J., Seoane, F., Vanthienen, J., Wynn, M. T., Boilève, D. B., Bergs, J., Joosten-Melis, M., Schretlen, S., & Acker, B. V. (2020). Recommendations for enhancing the usability and understandability of process mining in Read More …

The Internet of Things Meets Business Process Management: A Manifesto

Janiesch, C., Koschmider, A., Mecella, M., Weber, B., Burattin, A., Di Ciccio, C., Fortino, G., Gal, A., Kannengiesser, U., Leotta, F., Mannhardt, F., Marrella, A., Mendling, J., Oberweis, A., Reichert, M., Rinderle-ma, S., Serral, E., Song, W., Su, J., Torres, V., Weidlich, M., Weske, M., Zhang, L. (2020). The Internet of Things Meets Business Process Read More …

A trust and privacy framework for smart manufacturing environments

Mannhardt, F., Petersen, S. A., & Oliveira, M. F. (2019). A trust and privacy framework for smart manufacturing environments. Journal of Ambient Intelligence and Smart Environments, 11(3), 201-219. https://doi.org/10.3233/AIS-190521 Abstract Operators in industrial manufacturing environments are under pressure to cope with the ever increasing flexibility and complexity of work. Transitioning towards data-driven smart manufacturing environments Read More …

Detailed Performance Diagnosis Based on Production Timestamps: A Case Study

de Man, J. C., & Mannhardt, F. (2019). Detailed Performance Diagnosis Based on Production Timestamps: A Case Study. In F. Ameri, K. E. Stecke, G. von Cieminski, & D. Kiritsis (Eds.), Advances in Production Management Systems. Production Management for the Factory of the Future – IFIP WG 5.7 International Conference, APMS 2019, Proceedings (pp. 708-715). Read More …

ELPaaS: Event log privacy as a service

Bauer, M., Fahrenkrog-Petersen, S. A., Koschmider, A., Mannhardt, F., van der Aa, H., & Weidlich, M. (2019). ELPaaS: Event log privacy as a service. In B. Depaire, J. de Smedt, & M. Dumas (Eds.), BPMT 2019 BPM 2019 Dissertation Award, Doctoral Consortium, and Demonstration Track: Proceedings of the Dissertation Award, Doctoral Consortium, and Demonstration Track Read More …

Estimating the impact of incidents on process delay

Mannhardt, F., Arnesen, P., & Landmark, A. D. (2019). Estimating the impact of incidents on process delay. In Proceedings – 2019 International Conference on Process Mining, ICPM 2019 (pp. 49-56). [8786065] (Proceedings – 2019 International Conference on Process Mining, ICPM 2019). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICPM.2019.00018 Abstract Process mining reveals how processes in Read More …

Mining railway traffic control logs

Mannhardt, F., & Landmark, A. D. (2019). Mining railway traffic control logs. Transportation Research Procedia, 37, 227-234. https://doi.org/10.1016/j.trpro.2018.12.187 Abstract Railway traffic is a set of interrelated processes that are centrally controlled. Despite optimized train schedules, train dispatchers still take ad-hoc decisions on the scheduling of trains in the context of unplanned events. Train orders are Read More …

On the Contextualization of Event-Activity Mappings

Koschmider, A., Mannhardt, F., & Heuser, T. (2019). On the Contextualization of Event-Activity Mappings. In F. Daniel, Q. Z. Sheng, & H. Motahari (Eds.), Business Process Management Workshops – BPM 2018 International Workshops, Revised Papers (pp. 445-457). (Lecture Notes in Business Information Processing; Vol. 342). Springer. https://doi.org/10.1007/978-3-030-11641-5_35 Abstract Event log files are used as input Read More …

Privacy-Preserving Process Mining: Differential Privacy for Event Logs

Mannhardt, F., Koschmider, A., Baracaldo, N., Weidlich, M., & Michael, J. (2019). Privacy-Preserving Process Mining: Differential Privacy for Event Logs. Business and Information Systems Engineering, 61(5), 595-614. https://doi.org/10.1007/s12599-019-00613-3 Abstract Privacy regulations for data can be regarded as a major driver for data sovereignty measures. A specific example for this is the case of event data Read More …

User-centered and privacy-driven process mining system design for IoT

Michael, J., Koschmider, A., Mannhardt, F., Baracaldo, N., & Rumpe, B. (2019). User-centered and privacy-driven process mining system design for IoT. In M. Ruiz, & C. Cappiello (Eds.), Information Systems Engineering in Responsible Information Systems – CAiSE Forum 2019, Proceedings (pp. 194-206). (Lecture Notes in Business Information Processing; Vol. 350). Springer. https://doi.org/10.1007/978-3-030-21297-1_17 Abstract Process mining Read More …

A Framework to Navigate the Privacy Trade-offs for Human-Centred Manufacturing

Petersen, S. A., Mannhardt, F., Oliveira, M., & Torvatn, H. (2018). A Framework to Navigate the Privacy Trade-offs for Human-Centred Manufacturing. In Y. Rezgui, H. Afsarmanesh, & L. M. Camarinha-Matos (Eds.), Collaborative Networks of Cognitive Systems – 19th IFIP WG 5.5 Working Conference on Virtual Enterprises, PRO-VE 2018, Proceedings (pp. 85-97). (IFIP Advances in Information Read More …

A taxonomy for combining activity recognition and process discovery in industrial environments

Mannhardt, F., Bovo, R., Oliveira, M. F., & Julier, S. (2018). A taxonomy for combining activity recognition and process discovery in industrial environments. In D. Camacho, P. Novais, A. J. Tallón-Ballesteros, & H. Yin (Eds.), Intelligent Data Engineering and Automated Learning – IDEAL 2018 – 19th International Conference, Proceedings (pp. 84-93). (Lecture Notes in Computer Read More …

Privacy Challenges for Process Mining in Human-Centered Industrial Environments

Mannhardt, F., Petersen, S. A., & Oliveira, M. F. (2018). Privacy Challenges for Process Mining in Human-Centered Industrial Environments. In Proceedings – 2018 International Conference on Intelligent Environments, IE 2018 (pp. 64-71). [8595033] (Proceedings – 2018 International Conference on Intelligent Environments, IE 2018). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/IE.2018.00017 Abstract Operators in industrial manufacturing Read More …

Revealing work practices in hospitals using process mining

Mannhardt, F., & Toussaint, P. J. (2018). Revealing work practices in hospitals using process mining. In G. O. Klein, D. Karlsson, A. Moen, & A. Ugon (Eds.), Building Continents of Knowledge in Oceans of Data: The Future of Co-Created eHealth – Proceedings of MIE 2018 (pp. 281-285). (Studies in Health Technology and Informatics; Vol. 247). Read More …

Connecting databases with process mining: a meta model and toolset

González López de Murillas, E., Reijers, H. A., & van der Aalst, W. M. P. (2019). Connecting databases with process mining: a meta model and toolset. Software and Systems Modeling, 18(2), 1209-1247. https://doi.org/10.1007/s10270-018-0664-7 Abstract Process mining techniques require event logs which, in many cases, are obtained from databases. Obtaining these event logs is not a Read More …

Process mining for six sigma: a guideline and tool support

Graafmans, T. L. F., Türetken, O., Poppelaars, J. J. G. H., & Fahland, D. (Accepted/In press). Process mining for six sigma: a guideline and tool support. Business & Information Systems Engineering, 63(3), 277-300. https://doi.org/10.1007/s12599-020-00649-w. Abstract Process mining offers a set of techniques for gaining data-based insights into business processes from event logs. The literature acknowledges Read More …

A tour in process mining: from practice to algorithmic challenges

van der Aalst, W., Carmona, J., Chatain, T., & van Dongen, B. (2019). A tour in process mining: from practice to algorithmic challenges. In M. Koutny, L. Pomello, & L. M. Kristensen (Eds.), Transactions on Petri Nets and Other Models of Concurrency XIV (pp. 1-35). (Lecture Notes in Computer Science (including subseries Lecture Notes in Read More …

Guided interaction exploration and performance analysis in artifact-centric process models

van Eck, M. L., Sidorova, N., & van der Aalst, W. M. P. (2019). Guided interaction exploration and performance analysis in artifact-centric process models. Business and Information Systems Engineering, 61(6), 649-663. https://doi.org/10.1007/s12599-018-0546-0 Abstract Artifact-centric process models aim to describe complex processes as a collection of interacting artifacts. Recent development in process mining allow for the Read More …

Case notion discovery and recommendation: automated event log building on databases

de Murillas, E. G. L., Reijers, H. A., & van der Aalst, W. M. P. (Accepted/In press). Case notion discovery and recommendation: automated event log building on databases. Knowledge and Information Systems. https://doi.org/10.1007/s10115-019-01430-6 Abstract Process mining techniques use event logs as input. When analyzing complex databases, these event logs can be built in many ways. Read More …

Evaluating conformance measures in process mining using conformance propositions

Syring, A. F., Tax, N., & van der Aalst, W. M. P. (2019). Evaluating conformance measures in process mining using conformance propositions. In M. Koutny, L. Pomello, & L. M. Kristensen (Eds.), Transactions on Petri Nets and Other Models of Concurrency XIV (pp. 192-221). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Read More …

Overview of efficient clustering methods for high-dimensional big data streams

Hassani, M. (2019). Overview of efficient clustering methods for high-dimensional big data streams. In O. Nasraoui, & C-E. Ben N’Cir (Eds.), Clustering Methods for Big Data Analytics (pp. 25-42). (Unsupervised and Semi-Supervised Learning). Cham: Springer. https://doi.org/10.1007/978-3-319-97864-2_2 Abstract The majority of clustering approaches focused on static data. However, a big variety of recent applications and research Read More …

Using process analytics to improve healthcare processes

Hompes, B., Dixit, P., & Buijs, J. (2019). Using process analytics to improve healthcare processes. In S. Consoli, D. Reforgiato Recupero, & M. Petković (Eds.), Data Science for Healthcare: Methodologies and Applications (pp. 305-325). Cham: Springer. https://doi.org/10.1007/978-3-030-05249-2_12 Abstract Healthcare processes are inherently complex as each patient is unique and medical staff deviate from protocols, often Read More …

Repairing outlier behaviour in event logs

Fani Sani, M., van Zelst, S. J., & van der Aalst, W. M. P. (2018). Repairing outlier behaviour in event logs. In W. Abramowicz, & A. Paschke (Eds.), Business Information Systems – 21st International Conference, BIS 2018, Proceedings (pp. 115-131). (Lecture Notes in Business Information Processing; Vol. 320). Cham: Springer. https://doi.org/10.1007/978-3-319-93931-5_9 Abstract One of the Read More …

Computing alignments of event data and process models

van Zelst, S. J., Bolt, A., & van Dongen, B. F. (2018). Computing alignments of event data and process models. In M. Koutny, L. M. Kristensen, & W. Penczek (Eds.), Transactions on Petri Nets and Other Models of Concurrency XIII (pp. 1-26). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Read More …