TY - JOUR A1 - Yousfi, Alaaeddine A1 - Weske, Mathias T1 - Discovering commute patterns via process mining JF - Knowledge and Information Systems N2 - Ubiquitous computing has proven its relevance and efficiency in improving the user experience across a myriad of situations. It is now the ineluctable solution to keep pace with the ever-changing environments in which current systems operate. Despite the achievements of ubiquitous computing, this discipline is still overlooked in business process management. This is surprising, since many of today’s challenges, in this domain, can be addressed by methods and techniques from ubiquitous computing, for instance user context and dynamic aspects of resource locations. This paper takes a first step to integrate methods and techniques from ubiquitous computing in business process management. To do so, we propose discovering commute patterns via process mining. Through our proposition, we can deduce the users’ significant locations, routes, travel times and travel modes. This information can be a stepping-stone toward helping the business process management community embrace the latest achievements in ubiquitous computing, mainly in location-based service. To corroborate our claims, a user study was conducted. The significant places, routes, travel modes and commuting times of our test subjects were inferred with high accuracies. All in all, ubiquitous computing can enrich the processes with new capabilities that go beyond what has been established in business process management so far. KW - Commute pattern KW - Commute process KW - Process mining KW - Ubiquitous computing KW - Location-based services Y1 - 2019 U6 - https://doi.org/10.1007/s10115-018-1255-1 SN - 0219-1377 SN - 0219-3116 VL - 60 IS - 2 SP - 691 EP - 713 PB - Springer CY - London ER - TY - JOUR A1 - Baier, Thomas A1 - Di Ciccio, Claudio A1 - Mendling, Jan A1 - Weske, Mathias T1 - Matching events and activities by integrating behavioral aspects and label analysis JF - Software and systems modeling N2 - Nowadays, business processes are increasingly supported by IT services that produce massive amounts of event data during the execution of a process. These event data can be used to analyze the process using process mining techniques to discover the real process, measure conformance to a given process model, or to enhance existing models with performance information. Mapping the produced events to activities of a given process model is essential for conformance checking, annotation and understanding of process mining results. In order to accomplish this mapping with low manual effort, we developed a semi-automatic approach that maps events to activities using insights from behavioral analysis and label analysis. The approach extracts Declare constraints from both the log and the model to build matching constraints to efficiently reduce the number of possible mappings. These mappings are further reduced using techniques from natural language processing, which allow for a matching based on labels and external knowledge sources. The evaluation with synthetic and real-life data demonstrates the effectiveness of the approach and its robustness toward non-conforming execution logs. KW - Process mining KW - Event mapping KW - Business process intelligence KW - Constraint satisfaction KW - Declare KW - Natural language processing Y1 - 2018 U6 - https://doi.org/10.1007/s10270-017-0603-z SN - 1619-1366 SN - 1619-1374 VL - 17 IS - 2 SP - 573 EP - 598 PB - Springer CY - Heidelberg ER - TY - JOUR A1 - Mendling, Jan A1 - Weber, Ingo A1 - van der Aalst, Wil A1 - Brocke, Jan Vom A1 - Cabanillas, Cristina A1 - Daniel, Florian A1 - Debois, Soren A1 - Di Ciccio, Claudio A1 - Dumas, Marlon A1 - Dustdar, Schahram A1 - Gal, Avigdor A1 - Garcia-Banuelos, Luciano A1 - Governatori, Guido A1 - Hull, Richard A1 - La Rosa, Marcello A1 - Leopold, Henrik A1 - Leymann, Frank A1 - Recker, Jan A1 - Reichert, Manfred A1 - Reijers, Hajo A. A1 - Rinderle-Ma, Stefanie A1 - Solti, Andreas A1 - Rosemann, Michael A1 - Schulte, Stefan A1 - Singh, Munindar P. A1 - Slaats, Tijs A1 - Staples, Mark A1 - Weber, Barbara A1 - Weidlich, Matthias A1 - Weske, Mathias A1 - Xu, Xiwei A1 - Zhu, Liming T1 - Blockchains for Business Process Management BT - Challenges and Opportunities JF - ACM Transactions on Management Information Systems N2 - Blockchain technology offers a sizable promise to rethink the way interorganizational business processes are managed because of its potential to realize execution without a central party serving as a single point of trust (and failure). To stimulate research on this promise and the limits thereof, in this article, we outline the challenges and opportunities of blockchain for business process management (BPM). We first reflect how blockchains could be used in the context of the established BPM lifecycle and second how they might become relevant beyond. We conclude our discourse with a summary of seven research directions for investigating the application of blockchain technology in the context of BPM. KW - Blockchain KW - business process management KW - research challenges Y1 - 2018 U6 - https://doi.org/10.1145/3183367 SN - 2158-656X SN - 2158-6578 VL - 9 IS - 1 SP - 1 EP - 16 PB - Association for Computing Machinery CY - New York ER - TY - BOOK A1 - Meyer, Andreas A1 - Smirnov, Sergey A1 - Weske, Mathias T1 - Data in business processes N2 - Process and data are equally important for business process management. Process data is especially relevant in the context of automated business processes, process controlling, and representation of organizations' core assets. One can discover many process modeling languages, each having a specific set of data modeling capabilities and the level of data awareness. The level of data awareness and data modeling capabilities vary significantly from one language to another. This paper evaluates several process modeling languages with respect to the role of data. To find a common ground for comparison, we develop a framework, which systematically organizes process- and data-related aspects of the modeling languages elaborating on the data aspects. Once the framework is in place, we compare twelve process modeling languages against it. We generalize the results of the comparison and identify clusters of similar languages with respect to data awareness. N2 - Prozesse und Daten sind gleichermaßen wichtig für das Geschäftsprozessmanagement. Prozessdaten sind dabei insbesondere im Kontext der Automatisierung von Geschäftsprozessen, dem Prozesscontrolling und der Repräsentation der Vermögensgegenstände von Organisationen relevant. Es existieren viele Prozessmodellierungssprachen, von denen jede die Darstellung von Daten durch eine fest spezifizierte Menge an Modellierungskonstrukten ermöglicht. Allerdings unterscheiden sich diese Darstellungenund damit der Grad der Datenmodellierung stark untereinander. Dieser Report evaluiert verschiedene Prozessmodellierungssprachen bezüglich der Unterstützung von Datenmodellierung. Als einheitliche Grundlage entwickeln wir ein Framework, welches prozess- und datenrelevante Aspekte systematisch organisiert. Die Kriterien legen dabei das Hauptaugenmerk auf die datenrelevanten Aspekte. Nach Einführung des Frameworks vergleichen wir zwölf Prozessmodellierungssprachen gegen dieses. Wir generalisieren die Erkenntnisse aus den Vergleichen und identifizieren Cluster bezüglich des Grades der Datenmodellierung, in welche die einzelnen Sprachen eingeordnet werden. T3 - Technische Berichte des Hasso-Plattner-Instituts für Digital Engineering an der Universität Potsdam - 50 KW - business process modeling KW - process modeling languages KW - data modeling KW - data in business processes Y1 - 2011 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-53046 SN - 978-3-86956-144-8 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - BOOK A1 - Kunze, Matthias A1 - Weske, Mathias T1 - Behavioural Models BT - From Modelling Finite Automata to Analysing Business Processes N2 - This textbook introduces the basis for modelling and analysing discrete dynamic systems, such as computer programmes, soft- and hardware systems, and business processes. The underlying concepts are introduced and concrete modelling techniques are described, such as finite automata, state machines, and Petri nets. The concepts are related to concrete application scenarios, among which business processes play a prominent role. The book consists of three parts, the first of which addresses the foundations of behavioural modelling. After a general introduction to modelling, it introduces transition systems as a basic formalism for representing the behaviour of discrete dynamic systems. This section also discusses causality, a fundamental concept for modelling and reasoning about behaviour. In turn, Part II forms the heart of the book and is devoted to models of behaviour. It details both sequential and concurrent systems and introduces finite automata, state machines and several different types of Petri nets. One chapter is especially devoted to business process models, workflow patterns and BPMN, the industry standard for modelling business processes. Lastly, Part III investigates how the behaviour of systems can be analysed. To this end, it introduces readers to the concept of state spaces. Further chapters cover the comparison of behaviour and the formal analysis and verification of behavioural models. The book was written for students of computer science and software engineering, as well as for programmers and system analysts interested in the behaviour of the systems they work on. It takes readers on a journey from the fundamentals of behavioural modelling to advanced techniques for modelling and analysing sequential and concurrent systems, and thus provides them a deep understanding of the concepts and techniques introduced and how they can be applied to concrete application scenarios. Y1 - 2016 SN - 978-3-319-44958-6 PB - Springer CY - Cham ER - TY - BOOK A1 - Weske, Mathias T1 - Business Process Management : Concepts, Languages, Architectures Y1 - 2007 SN - 978-3-540-73521-2 U6 - https://doi.org/10.1007/978-3-540-73522-9 PB - Springer-Verlag Berlin Heidelberg CY - Berlin, Heidelberg ER - TY - JOUR A1 - Pernici, Barbara A1 - Weske, Mathias T1 - Business process management Y1 - 2006 SN - 0169-023X ER - TY - JOUR A1 - Weske, Mathias A1 - van der Aalst, Wil M. P. A1 - Verbeek, H. M. W. T1 - Advances in business process management Y1 - 2004 SN - 0169-023X ER - TY - BOOK A1 - Smirnov, Sergey A1 - Reijers, Hajo A. A1 - Nugteren, Thijs A1 - Weske, Mathias T1 - Business process model abstraction : theory and practice N2 - Business process management aims at capturing, understanding, and improving work in organizations. The central artifacts are process models, which serve different purposes. Detailed process models are used to analyze concrete working procedures, while high-level models show, for instance, handovers between departments. To provide different views on process models, business process model abstraction has emerged. While several approaches have been proposed, a number of abstraction use case that are both relevant for industry and scientifically challenging are yet to be addressed. In this paper we systematically develop, classify, and consolidate different use cases for business process model abstraction. The reported work is based on a study with BPM users in the health insurance sector and validated with a BPM consultancy company and a large BPM vendor. The identified fifteen abstraction use cases reflect the industry demand. The related work on business process model abstraction is evaluated against the use cases, which leads to a research agenda. T3 - Technische Berichte des Hasso-Plattner-Instituts für Digital Engineering an der Universität Potsdam - 35 Y1 - 2010 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-41782 SN - 978-3-86956-054-0 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - BOOK A1 - Herzberg, Nico A1 - Weske, Mathias T1 - Enriching raw events to enable process intelligence : research challenges N2 - Business processes are performed within a company’s daily business. Thereby, valuable data about the process execution is produced. The quantity and quality of this data is very dependent on the process execution environment that reaches from predominantly manual to fullautomated. Process improvement is one essential cornerstone of business process management to ensure companies’ competitiveness and relies on information about the process execution. Especially in manual process environments data directly related to the process execution is rather sparse and incomplete. In this paper, we present an approach that supports the usage and enrichment of process execution data with context data – data that exists orthogonally to business process data – and knowledge from the corresponding process models to provide a high-quality event base for process intelligence subsuming, among others, process monitoring, process analysis, and process mining. Further, we discuss open issues and challenges that are subject to our future work. N2 - Die wertschöpfenden Tätigkeiten in Unternehmen folgen definierten Geschäftsprozessen und werden entsprechend ausgeführt. Dabei werden wertvolle Daten über die Prozessausführung erzeugt. Die Menge und Qualität dieser Daten ist sehr stark von der Prozessausführungsumgebung abhängig, welche überwiegend manuell als auch vollautomatisiert sein kann. Die stetige Verbesserung von Prozessen ist einer der Hauptpfeiler des Business Process Managements, mit der Aufgabe die Wettbewerbsfähigkeit von Unternehmen zu sichern und zu steigern. Um Prozesse zu verbessern muss man diese analysieren und ist auf Daten der Prozessausführung angewiesen. Speziell bei manueller Prozessausführung sind die Daten nur selten direkt zur konkreten Prozessausführung verknüpft. In dieser Arbeit präsentieren wir einen Ansatz zur Verwendung und Anreicherung von Prozessausführungsdaten mit Kontextdaten – Daten die unabhängig zu den Prozessdaten existieren – und Wissen aus den dazugehörigen Prozessmodellen, um ein hochwertige Event- Datenbasis für Process Intelligence Anwendungen, wie zum Beispiel Prozessmonitoring, Prozessanalyse und Process Mining, sicherstellen zu können. Des Weiteren zeigen wir offene Fragestellungen und Herausforderungen auf, welche in Zukunft Gegenstand unserer Forschung sein werden. T3 - Technische Berichte des Hasso-Plattner-Instituts für Digital Engineering an der Universität Potsdam - 73 Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-64012 SN - 978-3-86956-241-4 PB - Universitätsverlag Potsdam CY - Potsdam ER -