TY - GEN
T1 - ProMiSE
T2 - Research Projects Exhibition Papers Presented at the 35th International Conference on Advanced Information Systems Engineering, CAiSE-RPE 2023
AU - Zimmermann, Lisa
AU - Völzer, Hagen
AU - Weber, Barbara
A2 - Zerbato, Francesca
A2 - Font, Jaime
A2 - Arcega, Lorena
A2 - Reyes-Román, José-Fabián
A2 - Giachetti, Giovanni
PY - 2023
Y1 - 2023
N2 - In the past decade, process mining has gained momentum in academia and the industry, as it supports organizations in deriving insights from event data recorded from process executions. The increasing adoption of process mining in practice entails supporting process analysts in their work. Indeed, their analysis includes many exploratory tasks that require them to rely on their experience to interpret the data and steer the analysis. This knowledge-intensive nature of process mining can be challenging for less experienced analysts and calls for methodological and operational guidance tailored to their needs. In this paper, we present ProMiSE, a project funded by the Swiss National Science Foundation that embraces this novel direction in process mining research. The first goal of the project is to improve our understanding of how analysts work in practice, i.e., the process of process mining. Then, methodological guidance and software-based support are developed to assist novice analysts during their analysis. The results obtained in the first two years of ProMiSE have helped to build a solid empirical basis on process mining, laying the foundation for the development of user-centered support, which we will realize in the coming years with the help of our project partners and international collaborators.
AB - In the past decade, process mining has gained momentum in academia and the industry, as it supports organizations in deriving insights from event data recorded from process executions. The increasing adoption of process mining in practice entails supporting process analysts in their work. Indeed, their analysis includes many exploratory tasks that require them to rely on their experience to interpret the data and steer the analysis. This knowledge-intensive nature of process mining can be challenging for less experienced analysts and calls for methodological and operational guidance tailored to their needs. In this paper, we present ProMiSE, a project funded by the Swiss National Science Foundation that embraces this novel direction in process mining research. The first goal of the project is to improve our understanding of how analysts work in practice, i.e., the process of process mining. Then, methodological guidance and software-based support are developed to assist novice analysts during their analysis. The results obtained in the first two years of ProMiSE have helped to build a solid empirical basis on process mining, laying the foundation for the development of user-centered support, which we will realize in the coming years with the help of our project partners and international collaborators.
KW - Process Mining Guidance
KW - Process of Process Mining
KW - Software Support
KW - User Behavior Analysis
UR - https://www.scopus.com/pages/publications/85163490602
M3 - Conference contribution
T3 - CEUR Workshop Proceedings
SP - 60
EP - 67
BT - CAiSE-RPE 2023 : CAiSE 2023 Research Projects Exhibition
PB - CEUR-WS.org
Y2 - 12 June 2023 through 16 June 2023
ER -