SOA-enabled compliance management: Instrumenting, assessing, and analyzing service-based business processes

Facilitating compliance management, that is, assisting a company's management in conforming to laws, regulations, standards, contracts, and policies, is a hot but non-trivial task. The service-oriented architecture (SOA) has evolved traditional, manual business practices into modern, service-based IT practices that ease part of the problem: the systematic definition and execution of business processes. This, in turn, facilitates the online monitoring of system behaviors and the enforcement of allowed behaviors-all ingredients that can be used to assist compliance management on the fly during process execution. In this paper, instead of focusing on monitoring and runtime enforcement of rules or constraints, we strive for an alternative approach to compliance management in SOAs that aims at assessing and improving compliance. We propose two ingredients: (i) a model and tool to design compliant service-based processes and to instrument them in order to generate evidence of how they are executed and (ii) a reporting and analysis suite to create awareness of a company's compliance state and to enable understanding why and where compliance violations have occurred. Together, these ingredients result in an approach that is close to how the real stakeholders-compliance experts and auditors-actually assess the state of compliance in practice and that is less intrusive than enforcing compliance. © 2013 Springer-Verlag London

Research in Business Process Management: A bibliometric analysis

It contains several growing subtopics such as process mining, process flexibility and process compliance. BPM is also highly relevant for numerous related fields, such as Business Intelligence, ERP systems or Knowledge Management. The growing number of publications and the variety of topics in BPM make it useful to apply bibliometric methods on this scientific field. With bibliometric methods, topical clusters, essential authors and the relationships between them can be discovered. In this work, the BibTechMon software from the Austrian Institute of Technology is utilized to perform the bibliometric analyses. As a novelty for the work with BibTechMon, data from Google Scholar is used as the basis of the analyses. The nature of Google Scholar data differs significantly from the data of other scientific databases. These differences lead to changes on how the bibliometric analyses can be performed. After these changes have been assessed, several bibliometric analyses in the BPM field and related fields are performed. As a result of these analyses, diverse topical clusters in BPM and its related fields could be discovered. Additionally, important authors for each cluster and for the BPM field as a whole were determined. In order to evaluate the results of the bibliometric analyses, I conducted an interview on BPM with Professor Reichert, who is an active researcher in the field. Subsequently, his statements are compared with the results of the bibliometric analyses and the match between the bibliometric analyses and his statements is assessed

Discovering Process Reference Models from Process Variants Using Clustering Techniques

In today's dynamic business world, success of an enterprise increasingly depends on its ability to react to changes in a quick and flexible way. In response to this need, process-aware information systems (PAIS) emerged, which support the modeling, orchestration and monitoring of business processes and services respectively. Recently, a new generation of flexible PAIS was introduced, which additionally allows for dynamic process and service changes. This, in turn, has led to large number of process and service variants derived from the same model, but differs in structures due to the applied changes. This paper provides a sophisticated approach which fosters learning from past process changes and allows for determining such process variants. As a result we obtain a generic process model for which the average distances between this model and the process variants becomes minimal. By adopting this generic process model in the PAIS, need for future process configuration and adaptation will decrease. The mining method proposed has been implemented in a powerful proof-of-concept prototype and further validated by a comparison between other process mining algorithms

Automatic Synthesis and Verification of Industrial Commissioning Processes

The topic of this doctoral dissertation is the verification and synthesis of processes, i.e., work-flows. Verification is the check if a given process model fulfills all necessary properties. Synthesis is the automatic generation of a process model from a set of properties. The running example of the thesis and the use case for the evaluation is the commissioning of vehicles in the automobile production

Information Security in Business Intelligence based on Cloud: A Survey of Key Issues and the Premises of a Proposal

International audienceMore sophisticated inter-organizational interactions have generated changes in the way in which organizations make business. Advanced forms of collaborations, such as Business Process as a Service (BPaaS), allow different partners to leverage business intelligence within organizations. However, although it presents powerfull economical and technical benefits, it also arrises some pitfalls about data security, especially when it is mediated by the cloud. In this article, current aspects which have been tackled in the literature related to data risks and accountability are presented. In addition, some open issues are also presented from the analysis of the existing methodologies and techniques proposed in the literature. A final point is made by proposing an approach, which aims at preventive, detective and corrective accountability and data risk management, based on usage control policies and model driven engineering

Exploring Business Process Deviance with Declare

See töö tutvustab äriprotsessi hälbe kaevandust, mis kuulub protsessi\n\rkaevandamise gruppi ja annab ülevaate mitme hälbivaga kaevandamise lähenemisviisidest.\n\rKeskendutakse ka hälbiva kaevandamise kasutamise diskrimineerivatele mustritele, mis kuulub kontserni järjestikumustrite kaevandustehnoloogiatega samasse gruppi. Selles töös vaadeldakse uute diskrimineerivate mustrite kaevandamise algoritmi, mis põhineb Declare keelel. Rakendati plug-in lähenemisviisi protsessi kaevandamise näitajaga ProMile. Kirjeldatakse kogu protsessi kuni klassifitseerimiseni. Töö lõpus hinnati algoritmi tõhusust ja eksperimente erinevates variatsioonides.This thesis introduces business process deviance mining, which belongs to the group\n\rof process mining, and gives an overview on multiple deviance mining approaches. After that\n\rwe focus on deviance mining using discriminative patterns, which belongs to the group of\n\rsequential patterns mining techniques. In this work we propose new discriminative pattern\n\rmining algorithm based on the Declare language. We implemented the approach as a plug-in\n\rof the Process Mining tool ProM. We describe the whole proposed approach from the labelling\n\rof the event logs until building the classifier and classifying the test logs. In the end of the\n\rthesis we evaluate the effectiveness of our proposed algorithm on variety of experiments on\n\revent logs

Process mining of test processes : a case study

Process mining techniques attempt to extract non-trivial and useful information from event logs. For example, there are many process mining techniques to automatically discover a process model describing the causal dependencies between activities. Moreover, using conformance checking it is possible to investigate and quantify deviations between the real process and the modeled process. Several successful case studies have been reported in literature, all demonstrating the applicability of process mining. However, these case studies refer to rather structured administrative processes. In this paper, we investigate the applicability of process mining to less structured processes. We report on a case study where the ProM framework has been applied to the test processes of ASML (the leading manufacturer of wafer scanners in the world). This case study provides many interesting insights. On the one hand, process mining is also applicable to the less structured processes of ASML. On the other hand, the case study also shows the need for alternative mining approaches able to better visualize processes and provide more insights