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- KonferenzbeitragTransforming Object-Centric Process Models into BPMN 2.0 Models in the PHILharmonicFlows Framework(Modellierung 2024, 2024) Breitmayer, Marius; Arnold, Lisa; Pejic, Marko; Reichert, ManfredBusiness processes can be modeled using a plethora of different paradigms including activity-centric (e.g., imperative, declarative), and data-centric processes. The former focus on the process activities to be executed as well as their execution order and constraints, whereas the latter deal with the data required to progress during process execution. Both representations, however, allow describing the same process, but from different viewpoints. Consequently, a transformation between process representations based on the different paradigms yields promising perspectives for enabling a holistic view on both the behavior and the data perspective of a process and fosters a common understanding of different paradigms. This paper presents an approach for transforming object-centric processes (i.e., object lifecycle processes and their interactions) into corresponding activity-centric representations modeled in terms of BPMN 2.0. We present seven transformation rules for mapping an object- to an activity-centric process, illustrated along a running example. We evaluate the approach based on a proof-of-concept implementation that can automatically perform the necessary transformations and has been applied in multiple scenarios. Overall, our approach for transforming object-centric processes into BPMN 2.0 models provides new insights into the relationship between the two paradigms and enables a more flexible and effective way of modeling business processes in general.
- KonferenzbeitragModeling difficulties in creating conceptual data models: Multimodal studies on individual modeling processes(Modellierung 2024, 2024) Rosenthal, Kristina; Strecker, Stefan; Snoeck, MoniqueCombining complementary modes of observation of modelers' modeling processes, we study modeling difficulties encountered by modelers while performing a data modeling task. Using the notion of cognitive breakdowns, we identify and confirm five types of modeling difficulties relating to different aspects of data modeling by analyzing audiovisual protocols of the modelers' modeling processes, recordings of modelers' interactions with the employed modeling software tool and survey data of modelers about their own perceptions of modeling difficulties they encountered.
- KonferenzbeitragModeling Classes of Body Sensor Networks(Modellierung 2024, 2024) Carwehl, Marc; Reisig, WolfgangComputer-embedded systems frequently manifest in diverse variants, featuring slight differences in interfaces and functionalities, yet fundamentally grounded in a shared functional kernel. To address this variability, we propose to employ a schematic model of the functional kernel, from which concrete system instances are derived. This modeling methodology leverages well-established principles from predicate logic and Petri nets, augmented with the dynamic extensions provided by the \textsc{Heraklit} infrastructure. As a practical case study, we explore the realm of Body Sensor Networks (BSNs), a domain increasingly pivotal in the realm of medical diagnosis. Our work showcases the versatility and adaptability of our modeling framework in the context of BSNs, offering insights into its potential applications in the broader landscape of embedded systems and beyond.
- KonferenzbeitragAutomatisierte Generierung fachlicher Prozessmodelle basierend auf natürlichsprachlichen Prozessbeschreibungen(Modellierung 2024, 2024) von Olberg, Pauline; Strey, LukasDie manuelle Erstellung von Prozessmodellen ist eine gängige Tätigkeit im Rahmen der Softwareentwicklung. Die Erstellung der Modelle stellt allerdings eine zeitintensive Aufgabe für IT-Fachkräfte dar. Mit dem Ziel, die Fachkräfte zu entlasten, stellen wir die Methode NL2BPMN und einen Prototyp vor, durch welche natürlichsprachliche sowie fachspezifische Prozessbeschreibungen automatisiert in BPMN-Prozessmodelle transformiert werden können. Die Methode basiert auf Natural Language Processing (NLP) und bedient sich unter anderem dem Part-of-Speech-Tagging sowie dem Dependency Parsing. Ein Bestandteil der Methode ist die Verwendung einer Fachbegriffe-Liste als zusätzlicher Input neben Prozessbeschreibungen, um Fachbegriffe, die aus mehreren Wörtern bestehen, als zusammengehörige Begriffe zu verarbeiten. Ein Vergleich von automatisiert generierten Modellen mit manuell erstellten Modellen zeigt Erfolgsquoten von über 90 \% in allen Bewertungskategorien, sofern eine Fachbegriffe-Liste verwendet wird.
- KonferenzbeitragPragmatic Reuse for DSML Development(Modellierung 2024, 2024) Klikovits, Stefan; Buchs, DidierThis is a summary of an article (with the same title) originally published in the International Journal on Software and Systems Modeling (Vol. 20, pages 837–866, (2021)) discussing the lessons learned during the development of a DSL for physical resource flows.
- KonferenzbeitragA flexible operation-based infrastructure for collaborative model-driven engineering(Modellierung 2024, 2024) Herac, Edvin; Marchezan, Luciano; Assunção, Wesley; Haas, Rainer; Egyed, AlexanderCurrent engineering practices to create complex systems rely on highly interdisciplinary teams, potentially globally distributed, working with heterogeneous artifacts. For instance, in a robotics project, collaboration from multiple engineers across different domains such as mechanical, electronic, and software is required. However, achieving proper collaboration to correctly and efficiently develop complex systems is not a trivial activity. The artifacts developed in each domain, usually represented as models, use different structures (e.g., metamodels) and are managed in different tools, but somehow related to each other.
- KonferenzbeitragAdvancing Virtual Coaching in Healthcare: Towards A Unified Terminology and Reference Model(Modellierung 2024, 2024) Gißke, Carola; Weiman, Thure Georg; Schlieter, HannesVirtual coaching applications, designed to facilitate behavior change through adaptive coaching activities, hold promise for personalized interventions, particularly in healthcare. While existing literature explores various aspects of virtual coaches (VCs), there is a lack of comprehensive conceptual analysis, and inconsistent terminology further complicates their understanding. The present paper aims to demonstrate the ongoing work on systematically categorizing and describing the components of VCs and, thereby, creating a reference model reusable for different contexts. Based on a systematic literature review, concepts related to VC interventions will be derived, categorized, and linked to each other, forming a unified framework that could simplify the process of designing VCs and provide the foundation for dedicated building tools in terms of low/no-code platforms. Moreover, the work contributes with a consolidated terminology, and the proposed model may also be used to identify underexplored research areas, enhancing research opportunities in the field.
- KonferenzbeitragModels for Human-Machine Teaming for Shared Decision-Making under Uncertainty(Modellierung 2024, 2024) Bencomo, NellyThere is growing uncertainty about the runtime environment of software systems. Therefore, how the system should behave under different contexts cannot be fully predicted at design time. It is considerations such as these that have led to the development of self-adaptive systems (SAS), which can dynamically and autonomously reconfigure their behavior to respond to hanging external conditions. The use of Machine Learning (ML) and AI has exacerbated the issues by adding more uncertainty sources. The scope of the talk is in the areas of Model-driven Engineering (MDE), Requirements Engineering (RE), software engineering (SE), and the development of techniques to quantify uncertainty to improve decision-making. The explicit reatment of uncertainty by the running system improves its judgment to make decisions supported by evaluating evidence found during runtime, possibly including the human-in-the-loop. The speaker will discuss how quantification of uncertainty can improve requirement elicitation (using simulations, for example). The talk will also cover different approaches to quantifying uncertainty, models@run.time and their role in Human-Machine Teaming.
- KonferenzbeitragModellierung 2024 - Complete Volume(Modellierung 2024, 2024)
- KonferenzbeitragModel-driven Design and Automation of Process Orchestrations in Manufacturing(Modellierung 2024, 2024) Rinderle-Ma, StefanieManufacturing is a domain that spans a broad range of process orchestration scenarios with different requirements regarding the degree of automation and human involvement. Moreover, context is provided in manufacturing orchestrations by a rich set of sensor streams that (externally) influence the process execution and outcome. In this keynote, the model-driven design and automation of different real-world manufacturing scenarios is presented. We explain the arising challenges and how they can be met by existing process technologies. Future research directions and opportunities, in particular, the interplay of process automation and process mining conclude the keynote.
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