Auflistung nach Autor:in "Dumas, Marlon"
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- ZeitschriftenartikelBlockchain Support for Collaborative Business Processes(Informatik Spektrum: Vol. 42, No. 3, 2019) Di Ciccio, Claudio; · Cecconi, Alessio; Dumas, Marlon; Garcia-Bañuelos, Luciano; López-Pintado, Orlenys; Mendling, Qinghua Lu Jan; Ponomarev, Alexander; Tran, An Binh; Weber, IngoBlockchain technology provides basic building blocks to support the execution of collaborative business processes involving mutually untrusted parties in a decentralized environment. Several research proposals have demonstrated the feasibility of designing blockchain-based collaborative business processes using a high-level notation, such as the Business Process Model and Notation (BPMN), and thereon automatically generating the code artifacts required to execute these processes on a blockchain platform. In this paper, we present the conceptual foundations of model-driven approaches for blockchain-based collaborative process execution and we compare two concrete approaches, namely Caterpillar and Lorikeet.
- ZeitschriftenartikelBusiness Process Privacy Analysis in Pleak (Extended Abstract)(Informatik Spektrum: Vol. 42, No. 5, 2019) Toots, Aivo; Tuuling, Reedik; Yerokhin, Maksym; Dumas, Marlon; García-Bañuelos, Luciano; Laud, Peeter; Matulevičius, Raimundas; Pankova, Alisa; Pettai, Martin; Pullonen, Pille; Tom, Jake
- ZeitschriftenartikelCriteria and Heuristics for Business Process Model Decomposition(Business & Information Systems Engineering: Vol. 58, No. 1, 2016) Milani, Fredrik; Dumas, Marlon; Matulevičius, Raimundas; Ahmed, Naved; Kasela, SilvaIt is generally agreed that large process models should be decomposed into sub-processes in order to enhance understandability and maintainability. Accordingly, a number of process decomposition criteria and heuristics have been proposed in the literature. This paper presents a review of the field revealing distinct classes of criteria and heuristics. The study raises the question of how different decomposition heuristics affect process model understandability and maintainability. To address this question, an experiment is conducted where two different heuristics, one based on breakpoints and the other on data objects, were used to decompose a flat process model. The results of the experiment show that, although there are minor differences, the heuristics cause very similar results in regard to understandability and maintainability as measured by various process model metrics.
- ZeitschriftenartikelOpportunities and Challenges for Process Mining in Organizations: Results of a Delphi Study(Business & Information Systems Engineering: Vol. 63, No. 5, 2021) Martin, Niels; Fischer, Dominik A.; Kerpedzhiev, Georgi D.; Goel, Kanika; Leemans, Sander J. J.; Röglinger, Maximilian; van der Aalst, Wil M. P.; Dumas, Marlon; La Rosa, Marcello; Wynn, Moe T.Process mining is an active research domain and has been applied to understand and improve business processes. While significant research has been conducted on the development and improvement of algorithms, evidence on the application of process mining in organizations has been far more limited. In particular, there is limited understanding of the opportunities and challenges of using process mining in organizations. Such an understanding has the potential to guide research by highlighting barriers for process mining adoption and, thus, can contribute to successful process mining initiatives in practice. In this respect, the paper provides a holistic view of opportunities and challenges for process mining in organizations identified in a Delphi study with 40 international experts from academia and industry. Besides proposing a set of 30 opportunities and 32 challenges, the paper conveys insights into the comparative relevance of individual items, as well as differences in the perceived relevance between academics and practitioners. Therefore, the study contributes to the future development of process mining, both as a research field and regarding its application in organizations.
- ZeitschriftenartikelRobotic Process Mining: Vision and Challenges(Business & Information Systems Engineering: Vol. 63, No. 3, 2021) Leno, Volodymyr; Polyvyanyy, Artem; Dumas, Marlon; La Rosa, Marcello; Maggi, Fabrizio MariaRobotic process automation (RPA) is an emerging technology that allows organizations automating repetitive clerical tasks by executing scripts that encode sequences of fine-grained interactions with Web and desktop applications. Examples of clerical tasks include opening a file, selecting a field in a Web form or a cell in a spreadsheet, and copy-pasting data across fields or cells. Given that RPA canÿautomate a wide range of routines, thisÿraises the question of which routines should be automated in the first place. This paper presents a vision towards a family of techniques, termed robotic process mining (RPM), aimed at filling this gap. The core idea of RPM is that repetitive routines amenable for automation can be discovered from logs of interactions between workers and Web and desktop applications, also known as user interactions (UI) logs. The paper defines a set of basic concepts underpinning RPM and presents a pipeline of processing steps that would allow an RPM tool to generate RPA scripts from UI logs. The paper also discusses research challenges to realize the envisioned pipeline. (**encoding or data invalid**)
- ZeitschriftenartikelSemantics and Analysis of DMN Decision Tables.(EMISA Forum: Vol. 37, No. 1, 2017) Calvanese, Diego; Dumas, Marlon; Laurson, Ülari; Maggi, Fabrizio Maria; Montali, Marco; Teinemaa, Irene
- ZeitschriftenartikelUtility-aware Event Log Anonymization for Privacy-Preserving Process Mining(EMISA Forum: Vol. 41, No. 1, 2021) Elkoumy, Gamal; Pankova, Alisa; Dumas, Marlon