Keywords: Conceptual modeling, Customer journey map, Modeling costs, Multi-method research approach, Pain points
Astract: Conceptual models offer numerous benefits but require significant investments, requiring modelers to strive to balance costs and benefits. Understanding the modeling process and the frustrations experienced by modelers can provide valuable insights for this assessment. While research acknowledges certain instances of modelers’ dissatisfaction, its scope often limits detailed examination. This study seeks to identify and analyze the main pain points associated with domain modeling through a five-phase empirical study using a multi-method approach. We identified 71 pain points, synthesized them to 41, and prioritized 16 as the most significant and prevalent in domain modeling. We then refined, documented, and exemplified the prioritized pain points, analyzed their potential causes, and discussed their practical implications. Our findings provide valuable insights for improving modelers’ experiences and optimizing the modeling process.

Keywords: Business capability, Data valuation, Data value, Taxonomy
Astract: In our data-centric society, the imperative to determine the value of data has risen. Therefore, this paper presents a taxonomy for a data valuation business capability. Utilizing an initial taxonomy version, which originated from a systematic literature review, this paper validates and extends the taxonomy, culminating in four layers, twelve dimensions, and 59 characteristics. The taxonomy validation was accomplished by conducting semi-structured expert interviews with eleven subject matter experts, followed by a cluster analysis of the interviews, leading to a taxonomy heatmap including practical extensions. This paper's implications are manifold. Firstly, the taxonomy promotes a common understanding of data valuation within an enterprise. Secondly, the taxonomy aids in categorizing, assessing, and optimizing data valuation endeavors. Thirdly, it lays the groundwork for potential data valuation standards and toolkits. Lastly, it strengthens theoretical assumptions by grounding them in practical insights and offers an interdisciplinary research agenda following the taxonomy dimensions and characteristics.

Keywords: Domain Modeling, Large Language Models, Tree of thoughts
Astract: Domain modeling is typically an iterative process where modeling experts interact with domain experts to complete and refine the model. Recently, we have seen several attempts to assist, or even replace, the modeler with a Large Language Model (LLM). Several LLM prompting strategies have been attempted, but with limited success. In this paper, we advocate for the adoption of a Tree-of-Thoughts (ToT) strategy to overcome the limitations of current approaches based on simpler prompting strategies. With a ToT strategy, we can decompose the modeling process into several sub-steps using for each step a specialized set of generators and evaluators prompts to optimize the quality of the LLM output. As part of our adaptation, we provide a Domain-Specific Language (DSL) to facilitate the formalization of the ToT process for domain modeling. Our approach is implemented as part of an open source tool available on GitHub.

Keywords: Enterprise Architecture, Architectural Coordination, Digital Twins
Astract: Digital Twins (DTs) carry the promise of supporting better decision-making, monitoring, and learning in relation to the twinned entity, by integrating novel technologies, including digital models, symbolic and sub-symbolic artificial intelligence, as well as advanced optimisation, simulation, and visualisation techniques. However, delivering such a promise requires considerable investments, which can only valorise in the long run, as DTs tend to be ‘data hungry’, in need of ample sensors, actuators and serious computing power. Yet, most current approaches to DT development focus on isolated scenarios, which not only limits the understanding of the value of DTs, but also their broader implications. The introduction of DTs, generally, also entails a wider digital transformation in an (inter-)organisational context, while such transformations need to be properly managed. We also observe that, since DTs are fundamentally a class of (highly advanced) information systems, this inevitably makes them an integral part of an enterprise’s broader (inter-organisational) portfolio of information systems. In line with this, we argue that, in order to (also) improve the socio-economical sustainability of DT solutions, their development, deployment and evolution need to be subject to architectural coordination within the broader frame of enterprise architecture management (EAM). From this perspective, we discuss some potential directions of research in (enterprise) architectural coordination of DT development, in order to help address some crucial challenges of socio-economically sustainable development and evolution of DTs as part of a broader portfolio of information systems.

Keywords: Process Patterns, Teaching Modelling