Keywords: Domain Modeling, Large Language Model, Process Mining, UML
Astract: Large Language Models (LLMs) have opened new opportunities in modeling in general, and conceptual modeling in particular. With their advanced reasoning capabilities, accessible through natural language interfaces, LLMs enable humans to deepen their understanding of different application domains and enhance their modeling skills. However, the open-ended nature of these interfaces results in diverse interaction behaviors, which may also affect the perceived usefulness of LLM-assisted conceptual modeling. Existing works focus on various quality metrics of LLM outcomes, yet limited attention is given to how users interact with LLMs for such modeling tasks. To address this gap, we present the design and findings of an empirical study conducted with information systems students. After labeling the interactions according to their intentions (e.g., Create Model, Discuss, or Present), and representing them as an event log, we applied process mining techniques to discover process models. These models vividly capture the interaction behaviors and reveal recurrent patterns. We explored the differences in interacting with two LLMs (GPT 4.0 and Code Llama) for two modeling tasks (use case and domain modeling) across three application domains. Additionally, we analyzed user perceptions regarding the usefulness and ease of use of LLM-assisted conceptual modeling.

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Keywords: BIM, simulation, data model, metamodel, compliance checking
Astract: Making sure that Building Information Modelling (BIM) models comply with building codes and contractual requirements is typically a time-consuming and overhead-heavy task. For this reason, there is a push for its automation. However, there are significant challenges to overcome. For example, most technical guidelines and contractual requirements are formulated in a natural language and would need to be translated into a formal representation for digital processing. Furthermore, there is no formal mechanism that enables the declaration, enforcement, and verification of compliance to those in a BIM model. In this work, we present a fundamental approach that makes the last three possible at any level of granularity, i.e., throughout the building’s entire life cycle.

Keywords: business capability, conceptual model, data valuation, Data value, reference ontology
Astract: Despite its recognition as primary asset, enterprises struggle to determine data value due to fragmented and impractical approaches. This paper develops a reference ontology for Data Valuation Business Capabilities (DVBC) leveraging the systematic approach for building ontologies, ArchiMate and integrating scientific insights with ex-ante expert interview validation. Comprising twelve groupings and 66 components, anchored in established ontologies and assessed against (non)-functional requirements, the ontology shapes the fragmented data valuation landscape into a structuring frame for enterprises. While advancing value modelling in information systems research, the ontology faces limitations like detailed process modelling deficiency, ex-post validation potential, and modelling language boundaries.

Keywords: domain models
Astract: Humanity has long since used models in different shapes and forms to understand, redesign, communicate about, and shape, the world around us; including many different social, economic, biological, chemical, physical, and digital aspects. This has resulted in a wide range of modeling practices. When the models as used in such modeling practices have a key role to play in the activities in which these modeling practices are ‘embedded’, the need emerges to consider the effectiveness and efficiency of such processes, and speak about modeling capabilities. In the latter situation, it becomes relevant to develop a thorough understanding of the artifacts involved in the modeling practices/capabilities. One field in which models play (an increasingly) important role is the field of system development (including software engineering, information systems engineering, and enterprise design management). In this context, we come across notions, such as views, diagrams, programs, animations, specifications, etc. The aim of this paper is to take a fundamental look at these notions. In doing so, we will argue that these notions should actually be seen as specific kinds of models, albeit for fundamentally different purposes.

Keywords: BPMN, Facade Maintenance, System Dynamics
Astract: Business process modeling and system dynamics are different approaches that are used in the design and management of organizations. Both approaches are concerned with the processes in, and around, organizations with the aim to identify, design and understand their behavior as well as potential improvements. At the same time, these approaches differ considerably in their methodological focus. While business process modeling specifically takes the (control flow of) business processes as its primary focus, system dynamics takes the analysis of complex and multi-faceted systems as its core focus. More explicitly combining both approaches has the potential to better model and analyze (by way of simulation) complex business processes, while specifically also including more relevant facets from the environment of these business processes. Furthermore, the inherent ability for simulation of system dynamics models, can be used to simulate the behavior of processes over time, while also putting business processes in a broader multi-faceted context. In this paper, we report on initial results on making such a more explicit combination of business process modeling and system dynamics. In doing so, we also provide a step-by-step guide on how to use BPMN based models and system dynamics models together to model and analyze complex business processes, while illustrating this in terms of a case study on the maintenance of building facades.

Keywords: Process Models, Transformer models, Multimodal Evidence, Process Representation
Astract: Stakeholders can struggle to understand and engage with process models due to a mismatch between the technical language used and their own domain-specific jargon and personal communication styles. The paper explores the application of transformer-based architectures to enhance the representation of process models and additional multimodal process data by tailoring them to the language of stakeholders. We present an approach that personalizes process model representations through two types of paraphrasers: one that aligns with domain-specific jargon and another that adapts to individual stakeholder styles. We developed a golden dataset from process model-stakeholder interaction simulation and a silver dataset using large language models to train and validate our approach. Initial findings suggest that these methods could enhance stakeholder engagement and contribute to better teaching of process mining and procedural thinking.

Keywords: Textbook, Conceptual Modeling, Ontology-Guided Modeling

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Keywords: data strategy, data management, semiotic triangle
Astract: It appears that, in an increasingly digital world, data is becoming more and more important for organizations. In several real-world cases in the Netherlands, we have seen that organizations struggle with issues such as: a) What data do we have? b) Which data do we need for value creation? c) Which strategic choices do we make around using data? d) Which strategic choices do we make around managing data as an asset? And e) Which skills do our people need in light of the previous items? The context for these organizations is different, but the challenges are the same. Our position is that the use of models can help to get to grips with the complexity of the aforementioned challenges. In this paper we explore a) the relationship between data and models, and b) a framework that connects data management as a means to care for data as an asset, and data as a means to achieve strategic objectives of the organization. In developing the latter, we follow a design science approach; we explore cases to understand challenges and requirements for such a framework as well as show how the framework helped to solve the challenges in these organizations.