Navigating in Process Model Repositories and Enterprise Process Information

Although process-aware information systems have been adopted in enterprises for many years, they still do not properly link the business processes they implement with related enterprise process information (e.g., guidelines, checklists, templates, and e-mails). On one hand, process management technology is used to design, implement, enact, and monitor processes. On the other, enterprise process information is spread over various sources like shared drives, databases, and enterprise information systems. As a consequence, users often manually link process information with particular process objects (e.g., using process portals). What is needed instead, however is an integrated access to both processes and related enterprise process information. This paper establishes such a link by introducing an integrated navigation space for process model collections and related enterprise process information. In particular, this navigation space allows process participants to flexibly navigate within process model collections, single process models, and related process information. In turn, this enables advanced end-user support for process repositories

Enabling a User-Friendly Visualization of Business Process Models

Abstract. Enterprises are facing increasingly complex business pro-cesses. Engineering processes in the automotive domain, for example, may comprise hundreds or thousands of process tasks. In such a scenario, existing modeling notations do not always allow for a user-friendly pro-cess visualization. In turn, this hampers the comprehensibility of business processes, especially for non-experienced process participants. This paper tackles this challenge by suggesting alternative ways of visualizing large and complex process models. A controlled experiment with 22 subjects provides first insights into how users perceive these approaches. Key words: process visualization, user experiment, visual design

On Maintaining Semantic Networks: Challenges, Algorithms, Use Cases

PURPOSE: Knowledge workers are confronted with a massive load of data from heterogeneous sources, making it difficult for them to discover information relevant in the context of their daily tasks. As a particular challenge, enterprise information needs to be aligned with business processes. In previous work, the authors introduced the Semantic Network (SN) approach for bridging this gap, i.e., for discovering explicit relations between enterprise information and business processes. What has been neglected so far, however, is SN maintenance, which is required to keep an SN consistent, complete, and up-to-date. The paper tackles this issue and extends the SN approach with methods and algorithms for enabling SN maintenance. DESIGN/METHODOLOGY/APPROACH: The paper illustrates an approach for SN maintenance. Specifically, the authors show how an SN evolves over time, classify properties of objects and relations captured in an SN, and show how these properties can be maintained. An empirical evaluation, which is based on synthetic and real-world data, investigates the performance, scalability and practicability of the proposed algorithms. FINDINGS: The authors prove the feasibility of the introduced algorithms in terms of runtime performance with a proof-of-concept implementation. Further, a real-world case from the automotive domain confirms the applicability of the SN maintenance approach. ORIGINALITY/VALUE: As opposed to existing work, the presented approach allows for the automated and consistent maintenance of SNs. Furthermore, the applicability of the presented SN maintenance approach is validated in the context of a real-world scenario as well as two business cases

Navigating in Complex Process Model Collections

The increasing adoption of process-aware information systems (PAIS) has led to the emergence of large process model collections. In the automotive and healthcare domains, for example, such collections may comprise hundreds or thousands of process models, each consisting of numerous process elements (e.g., process tasks or data objects). In existing modeling environments, process models are presented to users in a rather static manner; i.e., as image maps not allowing for any context-specific user interactions. As process participants have different needs and thus require specific presentations of available process information, such static approaches are usually not sufficient to assist them in their daily work. For example, a business manager only requires an abstract overview of a process model collection, whereas a knowledge worker (e.g., a requirements engineer) needs detailed information on specific process tasks. In general, a more flexible navigation and visualization approach is needed, which allows process participants to flexibly interact with process model collections in order to navigate from a standard (i.e., default) visualization of a process model collection to a context-specific one. With the Process Navigation and Visualization (ProNaVis) framework, this thesis provides such a flexible navigation approach for large and complex process model collections. Specifically, ProNaVis enables the flexible navigation within process model collections along three navigation dimensions. First, the geographic dimension allows zooming in and out of the process models. Second, the semantic dimension may be utilized to increase or decrease the level of detail. Third, the view dimension allows switching between different visualizations. All three navigation dimensions have been addressed in an isolated fashion in existing navigation approaches so far, but only ProNaVis provides an integrated support for all three dimensions. The concepts developed in this thesis were validated using various methods. First, they were implemented in the process navigation tool Compass, which has been used by several departments of an automotive OEM (Original Equipment Manufacturer). Second, ProNaVis concepts were evaluated in two experiments, investigating both navigation and visualization aspects. Third, the developed concepts were successfully applied to process-oriented information logistics (POIL). Experimental as well as empirical results have provided evidence that ProNaVis will enable a much more flexible navigation in process model repositories compared to existing approaches

Process-Oriented Information Logistics: Aligning Process Information with Business Processes

During the last decade, research in the field of business process management (BPM) has focused on the design, modeling, execution, monitoring, and optimization of business processes. What has been neglected, however, is the provision of knowledge workers and decision makers with needed information when performing knowledge-intensive business processes such as product engineering, customer support, or strategic management. Today, knowledge workers and decision makers are confronted with a massive load of data, making it difficult for them to discover the information relevant for performing their tasks. Particularly challenging in this context is the alignment of process-related information (process information for short), such as e-mails, office files, forms, checklists, guidelines, and best practices, with business processes and their tasks. In practice, process information is not only stored in large, distributed and heterogeneous sources, but usually managed separately from business processes. For example, shared drives, databases, enterprise portals, and enterprise information systems are used to store process information. In turn, business processes are managed using advanced process management technology. As a consequence, process information and business processes often need to be manually linked; i.e., process information is hard-wired to business processes, e.g., in enterprise portals associating specific process information with process tasks. This approach often fails due to high maintenance efforts and missing support for the individual demands of knowledge workers and decision makers. In response to this problem, this thesis introduces process-oriented information logistics(POIL) as new paradigm for delivering the right process information, in the right format and quality, at the right place and the right point in time, to the right people. In particular, POIL allows for the process-oriented, context-aware (i.e., personalized) delivery of process information to process participants. The goal is to no longer manually hard-wire process information to business processes, but to automatically identify and deliver relevant process information to knowledge workers and decision makers. The core component of POIL is a semantic information network (SIN), which comprises homogeneous information objects (e.g., e-mails, offce files, guidelines), process objects (e.g., tasks, events, roles), and relationships between them. In particular, a SIN allows discovering objects linked with each other in different ways, e.g., objects addressing the same topic or needed when performing a particular process task. The SIN not only enables an integrated formal representation of process information and business processes, but also allows determining the relevance of process information for a given work context based on novel techniques and algorithms. Note that this becomes crucial in order to achieve the aforementioned overall goal of this thesis

Context-aware Process Management for the Software Engineering Domain

Historically, software development projects are challenged with problems concerning budgets, deadlines and the quality of the produced software. Such problems have various causes like the high number of unplanned activities and the operational dynamics present in this domain. Most activities are knowledge-intensive and require collaboration of various actors. Additionally, the produced software is intangible and therefore difficult to measure. Thus, software producers are often insufficiently aware of the state of their source code, while suitable software quality measures are often applied too late in the project lifecycle, if at all. Software development processes are used by the majority of software companies to ensure the quality and reproducibility of their development endeavors. Typically, these processes are abstractly defined utilizing process models. However, they still need to be interpreted by individuals and be manually executed, resulting in governance and compliance issues. The environment is sufficiently dynamic that unforeseen situations can occur due to various events, leading to potential aberrations and process governance issues. Furthermore, as process models are implemented manually without automation support, they impose additional work for the executing humans. Their advantages often remain hidden as aligning the planned process with reality is cumbersome. In response to these problems, this thesis contributes the Context-aware Process Management (CPM) framework. The latter enables holistic and automated support for software engineering projects and their processes. In particular, it provides concepts for extending process management technology to support software engineering process models in their entirety. Furthermore, CPM contributes an approach to integrate the enactment of the process models better with the real-world process by introducing a set of contextual extensions. Various events occurring in the course of the projects can be utilized to improve process support and activities outside the realm of the process models can be covered. That way, the continuously growing divide between the plan and reality that often occurs in software engineering projects can be avoided. Finally, the CPM framework comprises facilities to better connect the software engineering process with other important aspects and areas of software engineering projects. This includes automated process-oriented support for software quality management or software engineering knowledge management. The CPM framework has been validated by a prototypical implementation, various sophisticated scenarios, and its practical application at two software companies

Integration heterogener Produktdaten in verteilten, komplexen Entwicklungsprozessen

Moderne Produkte, wie etwa Automobile oder Maschinen, werden infolge der zunehmenden Digitalisierung komplexer. Neben mechanischen Bauteilen umfassen sie zahlreiche mechatronische,elektronische und elektrische Bauteile. Um unterschiedliche Kundenbedürfnisse, länderspezifische Charakteristika oder gesetzliche Anforderungen bedienen zu können, muss für diese Produkte eine hohe Variabilität ermöglicht werden. Die Produktentwicklung erfolgt üblicherweise system- und komponentenorientiert und wird mit Methoden des Concurrent Engineering realisiert. Unterschiedliche Anforderungen und Aufgaben der Produktentwickler führen zu einer autonomen, heterogenen IT-Systemlandschaft, die sowohl aus etablierten Informationssystemen, etwa Produktdatenmanagement-Systemen, aber auch aus fachbereichsspezifischen Lösungen besteht. Während zwischen den etablierten Informationssystemen häufig Austauschschnittstellen existieren, erfolgt der Abgleich von Produktdaten aus diesen Systemen mit fachbereichsspezifischen Lösungen häufig manuell oder gar nicht. Zusätzlich ist die IT-Systemlandschaft der Produktentwicklung einem ständigem Wandel unterworfen, so dass Austauschschnittstellen kontinuierlich angepasst und erweitert werden müssen. Während die unabhängige Entwicklung von Systemen und Komponenten die Entwicklungszeit reduziert, wird es zu verschiedenen Zeitpunkten während der Produktentwicklung notwendig,die autonomen, heterogenen Produktdaten zu synchronisieren. Fehlerhafte und inkonsistente Produktdaten in späten Entwicklungsphasen führen zu erheblichen Kosten, so dass die Kontrolle der Vollständigkeit und Konsistenz von Produktdaten möglichst früh sichergestellt werden sollte, um eine hohe Produktqualität zu gewährleisten. Gegenstand dieser Arbeit ist das PROactive Consistency for E/E product Data management(PROCEED)-Framework, das die Integration autonomer, heterogener Produktdaten ermöglicht. PROCEED unterstützt den gesamten Lebenszyklus der Integration von Produktdaten, beginnend mit der initialen Integration, über die Steuerung und Überwachung des Integrationsprozesses sowie die Unterstützung von Schema- und Datenänderungen. Um die strukturelle Heterogenität von Produktdaten zu überwinden, werden Informationssysteme in sog. Produktontologien abstrahiert. Die Produktontologien werden anschließend mit Hilfe von Abbildungsregeln und -aktionen in eine gemeinsame Sicht überführt. Auf Basis dieses Modells werden Qualitätsmetriken der Integration, wie z.B. die Konsistenz und Vollständigkeit definiert. Zusätzlich wird das dynamische Verhalten bei Änderungen von Schema und Daten der Produktontologien erläutert. Schließlich wir das PROCEED-Rahmenwerk prototypisch realisiert und in einer Fallstudie angewandt