Towards Next Generation Business Process Model Repositories – A Technical Perspective on Loading and Processing of Process Models

Business process management repositories manage large collections of process models ranging in the thousands. Additionally, they provide management functions like e.g. mining, querying, merging and variants management for process models. However, most current business process management repositories are built on top of relation database management systems (RDBMS) although this leads to performance issues. These issues result from the relational algebra, the mismatch between relational tables and object oriented programming (impedance mismatch) as well as new technological developments in the last 30 years as e.g. more and cheap disk and memory space, clusters and clouds. The goal of this paper is to present current paradigms to overcome the performance problems inherent in RDBMS. Therefore, we have to fuse research about data modeling along database technologies as well as algorithm design and parallelization for the technology paradigms occurring nowadays. Based on these research streams we have shown how the performance of business process management repositories could be improved in terms of loading performance of processes (from e.g. a disk) and the computation of management techniques resulting in even faster application of such a technique. Exemplarily, applications of the compiled paradigms are presented to show their applicability

SUPPORTING ENTERPRISE TRANSFORMATION USING A UNIVERSAL MODEL ANALYSIS APPROACH

Enterprise Architecture Management has been proposed to help organizations in their efforts to flexibly adapt to rapidly changing market environments. Enterprise architectures are described by means of conceptual models depicting, e.g., an enterprise?s business processes, its organisational structure, or the data the enterprise needs to manage. Such models are stored in large repositories. Using these repositories to support enterprise transformation processes often requires detecting structural patterns containing particular labels within the model graphs. As an example, consider the case of mergers and acquisitions. Respective patterns could represent specific model fragments that occur frequently within the process models of the merging companies. This paper introduces an approach to analyse conceptual models at a structural and semantic level. In terms of structure, the approach is able to detect patterns within the model graphs. In terms of semantics, the approach is able to detect previously standardized model labels. Its core contribution to enterprise architecture management and transformation is two-fold. First, it is able to analyse conceptual models created in arbitrary modelling languages. Second, it supports a wide variety of pattern-based analysis tasks related to managing change in organisations. The approach is applied in a merger and acquisition scenario to demonstrate its applicability

Using a Generic Model Query Approach to Allow for Process Model Compliance Checking – An Algorithmic Perspective

Increased regulation forces financial companies to assure their business processes’ compliance with legal and company-internal rules. In this paper, we introduce a model-driven business process compliance checking approach. It allows for defining compliance rules and identifying their occurrences in process models based on a graph theory-based approach. We outline the challenges to be met in the conceptualization of the approach and especially its implementation through suitable algorithms. Furthermore, we present an according modeling tool and evaluate the approach against related work

SUPPORTING TERMINOLOGICAL STANDARDIZATION IN CONCEPTUAL MODELS - A PLUGIN FOR A META-MODELLING TOOL

Today´s enterprises are accumulating huge repositories of conceptual models, such as data models, organisational charts and most notably business process models. Those models often grow heterogeneously with the company and are thus often terminologically divers and complex. This terminological diversity originates from the fact that natural language allows an issu to be described in a large variety of ways especially when many modellers are involved. This diversity can become a pitfall when conceptual models are subject to model analysis techniqus, which require terminologically comparable model elements. Therefore, it is essential to ensure model quality by enforcing naming conventions. This paper introduces a prototype, which intends to resolve all associated issus of terminological standardisation already during the modelling phase or ex-post based on existing models. The modeller is guided through the standardization process by providing an automated list of all correct phrase propositions according to his entered phrase. In this approach, naming conventions can easily be defined and enforced. This leads to terminologically unambiguous conceptual models, which are easier to understand and ready for further analysis purposes

Identifying Business Process Activity Mappings by Optimizing Behavioral Similarity

This paper describes an approach designed to create a mapping between corresponding activities from two business processes that is geared towards handling noisy similarity values for the labels describing these activities. This is achieved by formulating an optimization problem – maximize the behavioral similarity of the processes as a whole – whose target value depends on the mapping. Thereby, the mapping is created not only with respect to label similarities but also with respect to the overall control flow structure, which avoids some mistakes resulting from erroneous label similarities. A preliminary evaluation demonstrates the improvement

HOW TO MODEL SERVICE PRODUCTIVITY FOR DATA ENVELOPMENT ANALYSIS? A META-DESIGN APPROACH

The rise of the service economy is increasingly reflected in the IS discipline. Since services depend on a co-creation of value between service providers and customers, productivity measurement needs to account for both points of view. Contrasting this evolution, current productivity management concepts often remain limited to the firm instead of focusing on dyadic relationships. Also, software tools frequently constitute expert systems that are focused on solving an optimization problem based on a linear program, but do not guide users in setting up a suitable productivity model in the first place. To account for this need, we conceptualize a software tool support for setting up productivity models for services. Our concept encompasses an extended Data Envelopment Analysis (DEA) approach as its analytical core, but in addition features various tools that help users to collaboratively define a productivity measurement model. Since the suitability of such a model is contingent on the environment in which it is applied, the proposed concept constitutes a meta-design that is intended to be applicable to a class of productivity management problems. As an outlook we present ideas for further research focusing on the implementation and evaluation of IT artefacts compliant with the proposed meta-design

Effiziente Prozessmodellanalyse mit Algorithmen der Subgraphisomorphie

In der Literatur existiert eine Vielzahl verschiedener Ansätze, um Prozessmodelle strukturell zu analysieren. Ein Unterproblem, das oft in vielen dieser Ansätze auftritt, ist die Identifikation von (häufig auftretenden) Subgraphen innerhalb der Modellgraphen. Um diese Problemstellung zu lösen, können graphentheoretische Algorithmen genutzt werden. Der vorliegende Artikel demonstriert, dass derartige Algorithmen in der Lage sind, große Mengen von Prozessmodellen innerhalb von (Milli-)Sekunden zu analysieren. Sie können folglich als Unterkomponente in bestehende Analyseansätze integriert werden, um (potenziell aufwändigere) Eigenentwicklungen zu ersetzen. Der Vorteil dieser Algorithmen liegt in ihrer breiten, nicht auf konkrete Modellierungssprachen oder Analysezwecke beschränkten Anwendbarkeit

Eine empirische Studie zur strukturellen Komplexität konzeptioneller Modelle – Grundlegung eines effizienten Ansatzes zur strukturellen Modellanalyse

Für die Analyse konzeptioneller Informationsmodelle existiert eine Vielzahl von Verfahren, die für eine bestimmte Modellierungssprache oder Anwendungsdomäne entwickelt wurden und abgegrenzte Analysezwecke unterstützen. Häufig besteht eine Teilaufgabe der Analyseverfahren in der Identifikation struktureller Modellmuster. Für dieses als Subgraphisomorphie bekannte Problem existieren effiziente, allgemein anwendbare Algorithmen, die bestimmte topologische Eigenschaften der zugrundeliegenden Graphen voraussetzen. Dieser Beitrag präsentiert die Ergebnisse der Untersuchung von 3000 Informationsmodellen und demonstriert, dass die meisten dieser Modelle entsprechende Eigenschaften aufweisen. Er präsentiert eine empirische Studie für die Entwicklung einer allgemein anwendbaren Analysemethode, die in viele Spezialentwicklungen integriert werden kann

Eine empirische Studie zur strukturellen Komplexität konzeptioneller Modelle – Grundlegung eines effizienten Ansatzes zur strukturellen Modellanalyse

Für die Analyse konzeptioneller Informationsmodelle existiert eine Vielzahl von Verfahren, die für eine bestimmte Modellierungssprache oder Anwendungsdomäne entwickelt wurden und abgegrenzte Analysezwecke unterstützen. Häufig besteht eine Teilaufgabe der Analyseverfahren in der Identifikation struktureller Modellmuster. Für dieses als Subgraphisomorphie bekannte Problem existieren effiziente, allgemein anwendbare Algorithmen, die bestimmte topologische Eigenschaften der zugrundeliegenden Graphen voraussetzen. Dieser Beitrag präsentiert die Ergebnisse der Untersuchung von 3000 Informationsmodellen und demonstriert, dass die meisten dieser Modelle entsprechende Eigenschaften aufweisen. Er präsentiert eine empirische Studie für die Entwicklung einer allgemein anwendbaren Analysemethode, die in viele Spezialentwicklungen integriert werden kann