Research on process mining focuses on the development of tools and techniques for the data-driven analysis of organizational processes. Process mining achieves this by analyzing event logs, which consist of events recorded during the execution of a process. Naturally, the insightfulness and correctness of any results obtained using process mining strongly depend on the characteristics of the event data used as input. Therefore, it is crucial to consider how well event data used in a process mining scenario actually resembles the real process that is under investigation. In this context, it is particularly important to consider what is actually recorded, how this recording occurs, and in which form the recorded data is represented, since such factors influence the completeness, correctness, and usability of the data at hand.

Recognizing this, the goal of this special issue is to dive deeply into the factors that influence the event data used in process mining, the impact that quality issues have on analysis results, and solutions to mitigate the impact of such issues. Therefore, we invite original contributions that specifically focus on the event data used in process mining, welcoming both investigative and solution-oriented submissions.

Investigative papers focus on gaining or providing insights into the event data used in process mining, aiming to understand, capture, or analyze the existing (mis)match between event data and real-world processes. Investigative papers may be concerned with topics such as (but not restricted to):

• Assessing the representativeness and quality of event data with respect to a real-world process
• Investigating the presence of data quality and data integration issues in real-world scenarios
• The data-extraction pipeline used to obtain event logs
• The impact of data quality issues on process mining results
• The impact and consideration of exogenous factors (such as weather, resource involvement in other processes, etc.) during process analysis

Solution-oriented papers focus on improving the current situation by considering how event data can be recorded in a better manner, resolving quality issues in event logs, or mitigating the impact that such issues have on obtained process mining results. Solution-oriented papers may be concerned with topics such as (but not restricted to):

• Object-centric representations of event data and associated analysis techniques
• The incorporation of additional data sources into process mining
• Inferring hidden factors that influence processes, e.g., missing activities or process inter-dependencies
• Mitigating the impact of data quality and data integration issues on process mining results
• Process mining in the presence of data uncertainty
• Data abstraction and augmentation techniques

This special issue is intended to provide practitioners and researchers with a venue to present insights, innovations, and solutions in information systems engineering. We welcome both behavioral and design-oriented work but submitted papers must have a strong empirical basis/component to be eligible for this special issue. BISE provides a forum for information systems engineering research with a strong empirical component and a venue for publishing empirical results relevant to both researchers and practitioners. In addition to the open call for papers, authors of conference papers are encouraged to submit extended versions of their work. To comply with the goals of a journal publication, we are asking to revise and substantially extend the original conference papers. Some possible extensions can be adding additional data gathered through case studies or experiments, additional empirical validation, systematic comparisons with other approaches, or a sound theoretical foundation. Revised papers should explicitly explain how they extend the original conference papers.

Submission Guidelines
Please submit papers by 1 July 2024 at the latest via the journal’s online submission system (http://www.editorialmanager.com/buis/). Please observe the instructions regarding the format and size of contributions to Business & Information Systems Engineering (BISE). Papers should adhere to the submission general BISE author guidelines (https://www.bise-journal.com/?page_id=18).

All papers will be reviewed anonymously (double-blind process) by at least two referees with regard to relevance, originality, and research quality. In addition to the editors of the journal, including those of this special issue, distinguished international scholars will be involved in the review process.

Schedule

• Deadline for submission: 1 Jul 2024
• Notification of the authors, 1st round: 1 Sep 2024
• Completion Revision 1: 1 Nov 2024
• Notification of the authors, 2nd round: 16 Dec 2024
• Completion Revision 2: 22 Jan 2024

Special Issue Editors

• Adela del Río Ortega, University of Seville
• Iris Beerepoot, Utrecht University
• Han van der Aa, University of Mannheim
• Joerg Evermann, Memorial University of Newfoundland