Tackling Complexity: Process Reconstruction and Graph Transformation for Financial Audits

A key objective of implementing business intelligence tools and methods is to analyze voluminous data and to derive information that would otherwise not be available. Although the overall significance of business intelligence has increased with the general growth of processed and available data it is almost absent in the auditing industry. Public accountants face the challenge to provide an opinion on financial statements that are based on the data produced by the automated processing of countless business transactions in ERP systems. Methods for mining and reconstructing financially relevant process instances can be used as a data analysis tool in the specific context of auditing. In this article we introduce and evaluate an algorithm that effectively reduces the complexity of mined process instances. The presented methods provide a part of the foundation for implementing automated analysis and audit procedures that can assist auditors to perform more efficient and effective audits

Systemizing Colour for Conceptual Modeling

Colour is used in many conceptual models and is discussed intensively since MOODY has published his ‘Physics of Notation’. Yet, choosing the right colour for a construct is difficult but crucial. Using a colour for a certain construct which is not appropriate can lead to visual stress as well as too much or too little emphasis on that construct. The aim of this paper is to give a systematization of colour for conceptual modeling by reviewing theories of colour vision, colour harmony and visual attention. Based on this review we provide colour combinations for different conceptual modeling colour scenarios

Process Mining Handbook

This is an open access book. This book comprises all the single courses given as part of the First Summer School on Process Mining, PMSS 2022, which was held in Aachen, Germany, during July 4-8, 2022. This volume contains 17 chapters organized into the following topical sections: Introduction; process discovery; conformance checking; data preprocessing; process enhancement and monitoring; assorted process mining topics; industrial perspective and applications; and closing

A systematic investigation of risk management and process mining ontologies

Διπλωματική εργασία--Πανεπιστήμιο Μακεδονίας, Θεσσαλονίκη, 2019.This study proposes and examines the ‘’Risk – Process’’ ontology with respect to and in comparison with the Process mining methodology. The ontology consists of Process elements (Process Mining, Business Process Management and Business Process Intelligence) and Risk elements (Governance, Risk Management & Compliance, Internal Audit and Enterprise Risk Management). A two-fold literature review is executed, focusing firstly on the six key elements of the ‘’Risk - Process’’ ontology, and secondly at the “Risk” components of the ontology. Moving on, as an original contribution, the popularity and the coherence of the aforementioned elements in internet searches from 2004 to 2018 is presented and forecasted with the use of the Google Trends tool. As a last step, a statistical analysis of the time series obtained through Google Trends is performed, in order to find relation, correlations, statistical significance and predictors with respect to Process minin

Workflow Behavior Auditing for Mission Centric Collaboration

Successful mission-centric collaboration depends on situational awareness in an increasingly complex mission environment. To support timely and reliable high level mission decisions, auditing tools need real-time data for effective assessment and optimization of mission behaviors. In the context of a battle rhythm, mission health can be measured from workflow generated activities. Though battle rhythm collaboration is dynamic and global, a potential enabling technology for workflow behavior auditing exists in process mining. However, process mining is not adequate to provide mission situational awareness in the battle rhythm environment since event logs may contain dynamic mission states, noise and timestamp inaccuracy. Therefore, we address a few key near-term issues. In sequences of activities parsed from network traffic streams, we identify mission state changes in the workflow shift detection algorithm. In segments of unstructured event logs that contain both noise and relevant workflow data, we extract and rank workflow instances for the process analyst. When confronted with timestamp inaccuracy in event logs from semi automated, distributed workflows, we develop the flower chain network and discovery algorithm to improve behavioral conformance. For long term adoption of process mining in mission centric collaboration, we develop and demonstrate an experimental framework for logging uncertainty testing. We show that it is highly feasible to employ process mining techniques in environments with dynamic mission states and logging uncertainty. Future workflow behavior auditing technology will benefit from continued algorithmic development, new data sources and system prototypes to propel next generation mission situational awareness, giving commanders new tools to assess and optimize workflows, computer systems and missions in the battle space environment

Software Engineering and Petri Nets

This booklet contains the proceedings of the Workshop on Software Engineering and Petri Nets (SEPN), held on June 26, 2000. The workshop was held in conjunction with the 21st International Conference on Application and Theory of Petri Nets (ICATPN-2000), organised by the CPN group of the Department of Computer Science, University of Aarhus, Denmark. The SEPN workshop papers are available in electronic form via the web page:http://www.daimi.au.dk/pn2000/proceeding

Obstructions in Security-Aware Business Processes

This Open Access book explores the dilemma-like stalemate between security and regulatory compliance in business processes on the one hand and business continuity and governance on the other. The growing number of regulations, e.g., on information security, data protection, or privacy, implemented in increasingly digitized businesses can have an obstructive effect on the automated execution of business processes. Such security-related obstructions can particularly occur when an access control-based implementation of regulations blocks the execution of business processes. By handling obstructions, security in business processes is supposed to be improved. For this, the book presents a framework that allows the comprehensive analysis, detection, and handling of obstructions in a security-sensitive way. Thereby, methods based on common organizational security policies, process models, and logs are proposed. The Petri net-based modeling and related semantic and language-based research, as well as the analysis of event data and machine learning methods finally lead to the development of algorithms and experiments that can detect and resolve obstructions and are reproducible with the provided software