Live Query - Visualized Process Analysis

Business process management (BPM) becomes continuously challenging through a steadily increasing number and even more complex processes. For enabling an effective and efficient control of business processes, (semi-)automatic approaches are necessary as a supporting means. However, these approaches are often hardly applicable in practice since they lack a broad applicability or an acceptable ease of use. This work aims to close this gap by providing an approach that supports a widely applicable, (semi-)automatic analysis of business process models and makes the analysis comprehensible using a graphical visualization

The Need for Compliance Verification in Collaborative Business Processes

Compliance constrains processes to adhere to rules, standards, laws and regulations. Non-compliance subjects enterprises to litigation and financial fines. Collaborative business processes cross organizational and regional borders implying that internal and cross regional regulations must be complied with. To protect customs’ data, European enterprises must comply with the EU data privacy regulation (general data protection regulation - GDPR) and each member state’s data protection laws. An example of non-compliance with GDPR is Facebook, it is accused for breaching subscriber trust. Compliance verification is thus essential to deploy and implement collaborative business process systems. It ensures that processes are checked for conformance to compliance requirements throughout their life cycle. In this paper we take a proactive approach aiming to discuss the need for design time preventative compliance verification as opposed to after effect runtime detective approach. We use a real-world case to show how compliance needs to be analyzed and show the benefits of applying compliance check at the process design stag

The Need for Compliance Verification in Collaborative Business Processes

Compliance constrains processes to adhere to rules, standards, laws and regulations. Non-compliance subjects enterprises to litigation and financial fines. Collaborative business processes cross organizational and regional borders implying that internal and cross regional regulations must be complied with. To protect customs’ data, European enterprises must comply with the EU data privacy regulation (general data protection regulation - GDPR) and each member state’s data protection laws. An example of non-compliance with GDPR is Facebook, it is accused for breaching subscriber trust. Compliance verification is thus essential to deploy and implement collaborative business process systems. It ensures that processes are checked for conformance to compliance requirements throughout their life cycle. In this paper we take a proactive approach aiming to discuss the need for design time preventative compliance verification as opposed to after effect runtime detective approach. We use a real-world case to show how compliance needs to be analyzed and show the benefits of applying compliance check at the process design stag

Verifying for Compliance to Data Constraints in Collaborative Business Processes.

Production processes are nowadays fragmented across different companies and organized in global collaborative networks. This is the result of the first wave of globalization that, among the various factors, was enabled by the diffusion of Internet-based Information and Communication Technologies (ICTs) at the beginning of the years 2000. The recent wave of new technologies possibly leading to the fourth industrial revolution – the so-called Industry 4.0 – is further multiplying opportunities. Accessing global customers opens great opportunities for organizations, including small and medium enterprises (SMEs), but it requires the ability to adapt to different requirements and conditions, volatile demand patterns and fast-changing technologies. Regardless of the industrial sector, the processes used in an organization must be compliant to rules, standards, laws and regulations. Non-compliance subjects enterprises to litigation and financial fines. Thus, compliance verification is a major concern, not only to keep pace with changing regulations but also to address the rising concerns of security, product and service quality and data privacy. The software, in particular process automation, used must be designed accordingly. In relation to process management, we propose a new way to pro-actively check the compliance of current running business processes using Descriptive Logic and Linear Temporal Logic to describe the constraints related to data. Related algorithms are presented to detect the potential violations

Collection and Elicitation of Business Process Compliance Patterns with Focus on Data Aspects

Business process compliance is one of the prevalent challenges for companies. Despite an abundance of research proposals, companies still struggle with manual compliance checks and the understanding of compliance violations in the light of missing root-cause explanations. Moreover, approaches have merely focused on the control flow perspective in compliance checking, neglecting other aspects such as the data perspective. This paper aims at analyzing the gap between existing academic work and compliance demands from practice with a focus on the data aspects. The latter emerges from a small set of regulatory documents from different domains. Patterns are assumed as the right level of abstraction for compliance specification due to their independence of (technical) implementation in (process-aware) information systems, potential for reuse, and understandability. A systematic literature review collects and assesses existing compliance patterns. A first analysis of ten regulatory documents from different domains specifically reveals data-oriented compliance constraints that are not yet reflected by existing compliance patterns. Accordingly, data-related compliance patterns are specified

Design principles for ensuring compliance in business processes

In this thesis, we evaluate the complexity and understandability of compliance languages. First, to calculate the complexity, we apply established software metrics and interpret the results with respect to the languages’ expressiveness. Second, to investigate the languages’ understandability, we use a cognitive model of the human problem-solving process and analyze how efficiently users perform a compliance modeling task. Our results have theoretical and practical implications that give directions for the development of compliance languages, and rule-based languages in general.Diese Arbeit beurteilt die Komplexität und Verständlichkeit von Compliance-Sprachen. Zur Messung der Komplexität wenden wir etablierte Software-Metriken an und interpretieren die Ergebnisse in Hinblick auf die Aussagekraft der Sprachen. Zur Untersuchung der Verständlichkeit verwenden wir ein kognitives Modell und analysieren, wie effizient eine Compliance-Sprache zur Lösung eines Modellierungsproblems eingesetzt wird. Unsere Ergebnisse haben theoretische und praktische Implikationen für die Entwicklung von Compliance-Sprachen und anderen regelbasierten Sprachen

Rule-based Monitoring Framework for Business Process Compliance

Business processes compliance monitoring can be viewed as a task of detecting and reacting to the compliance of running business processes with compliance rules, which are the semantic constraints originated from norms, standards, and laws, etc. Normally, compliance rules not only refer to normal process perspectives, like control ow, data ow, and time, but also perspectives of data aggregation as well as their mixtures. Such characteristics as well as potentially high number of concurrently running process instances, post challenges for processes compliance monitoring from the aspects of specification and monitoring efficiency. In this work, we address these challenges by proposing a compliance monitoring framework (bpCMon), including an event-based compliance language (ECL) and event reaction system (ERS), wherein ECL is a formal language enabling specifying compliance rules of multi-perspective, and ERS is a powerful rule-based system enriched with events indexing structure, and fully supports the monitoring for compliance rules in ECL. Experiments on a real life datasets indicate the applicability of bpCMon, and the comparisons with three related works over benchmarks demonstrate the efficiency of bpCMon