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Change management for evolving collaborative business process development is crucial when the business logic, transections and workflow change due to changes in business strategies or organizational and technical environment. During the…
Predictive monitoring of business processes is concerned with the prediction of ongoing cases on a business process. Lately, the popularity of deep learning techniques has propitiated an ever-growing set of approaches focused on predictive…
Business processes underpin a large number of enterprise operations including processing loan applications, managing invoices, and insurance claims. There is a large opportunity for infusing AI to reduce cost or provide better customer…
Process mining methods often analyze processes in terms of the individual end-to-end process runs. Process behavior, however, may materialize as a general state of many involved process components, which can not be captured by looking at…
Over the last decade we have witnessed an increasing use of data processing in embedded systems. Where in the past the data processing was limited (if present at all) to the handling of a small number of "on-off control signals", more…
Predictive analysis in business process monitoring aims at forecasting the future information of a running business process. The prediction is typically made based on the model extracted from historical process execution logs (event logs).…
The aim of process discovery, originating from the area of process mining, is to discover a process model based on business process execution data. A majority of process discovery techniques relies on an event log as an input. An event log…
A common challenge for improving business processes in large organizations is that business people in charge of the operations are lacking a fact-based understanding of the execution details, process variants, and exceptions taking place in…
Process mining enables business owners to discover and analyze their actual processes using event data that are widely available in information systems. Event data contain detailed information which is incredibly valuable for providing…
Most prominent research today addresses compliance with data protection laws through consumer-centric and public-regulatory approaches. We shift this perspective with the Privatech project to focus on corporations and law firms as agents of…
Regulations for privacy protection aim to protect individuals from the unauthorized storage, processing, and transfer of their personal data but oftentimes fail in providing helpful support for understanding these regulations. To better…
As machine learning (ML) components become increasingly integrated into software systems, the emphasis on the ethical or responsible aspects of their use has grown significantly. This includes building ML-based systems that adhere to…
As information becomes increasingly sizable for organizations to maintain the challenge of organizing data still remains. More importantly, the on-going process of analysing incoming data occurs on a continual basis and organizations should…
Financial inclusion depends on providing adjusted services for citizens with disclosed vulnerabilities. At the same time, the financial industry needs to adhere to a strict regulatory framework, which is often in conflict with the desire…
Modern information systems are able to collect event data in the form of event logs. Process mining techniques allow to discover a model from event data, to check the conformance of an event log against a reference model, and to perform…
Popular process models such as the Rational Unified Process or the V-Modell XT are by nature large and complex. Each time that a new release is published software development organizations are confronted with the big challenge of…
Business Process Management (BPM) in the cloud is focused on how to provide Business Process as a Service (BPaaS) and also implementing the Elastic Business Process Management (eBPM). These approaches are finding models, techniques and…
Threat modeling has been successfully applied to model technical threats within information systems. However, a lack of methods focusing on non-technical assets and their representation can be observed in theory and practice. Following the…
Process modeling is usually done using imperative modeling languages like BPMN or EPCs. In order to cope with the complexity of human-centric and flexible business processes several declarative process modeling languages (DPMLs) have been…
Blockchain technology enables the execution of collaborative business processes involving untrusted parties without requiring a central authority. Specifically, a process model comprising tasks performed by multiple parties can be…