Keywords: Internet of Meaning, HESTIA, Domain-Specific Modeling
Astract: At first glance, the Internet of Things brings about an expectation for users (be it individuals or organizations) to interact with the many Internet-connected “things” in a natural way while also enhancing everyday work and life. The emergence of smart cities, and smart homes, also fuels the need for a broad audience to interact with the Internet of Things in a natural way. In current practice, however, users are confronted with the need to negotiate a complex landscape involving a myriad of protocols, standards, and work-arounds to integrate “legacy” devices, etc. We contend that users should not have to think about their world in terms of specific sensors, actuators, gateways, and protocols but rather in terms of room temperatures, the desire to increase the temperature in the living room, the concern that the plants in the garden are watered on time, etc. This creates a need to bridge this gap by creating a semantically meaningful layer of abstraction on top of the sensors and actuators that make up the “device and protocols oriented” Internet of Things, to create an Internet of Meaning. To this end, this chapter reports on the HESTIA framework, which combines: (1) An abstraction of the implementation details pertaining to, e.g., different protocols, standards, etc. (2) A domain-specific (conceptual) modeling framework in terms of which “things” can be captured in a way that is meaningful to the domain at hand (3) Based on this, a domain-specific language that is understandable by the user, enabling users to define control/behavioral rules in terms that are meaningful to them The presented HESTIA framework will be illustrated in terms of examples in the context of home and garden automation. Though such application contexts seem less challenging and complex than industrial Internet of Things applications, the variety of devices and protocols and distance between users and the technical details are often larger than in the case of industrial Internet of Things.

Keywords: Enterprise Architecture, Architectural Coordination, Digital Twins for Urban Planning, Local Digital Twin
Astract: Digital Twins (DTs) carry the promise of improved decision-making about, as well as monitoring and understanding of, the twinned entity. This makes them an attractive instrument to support the, often complex and multi-faceted, decision-making processes germane to urban planning. DTs require considerable technological investments, as they tend to be data-hungry and computing-intensive. Business-wise, such investments are only meaningful if they really add value to the intended decision-making processes. However, most current DT development approaches primarily focus on the technological potential of DTs within the limited scope of isolated business scenarios, and rarely address trade-offs between costs and benefits towards the business case, let alone the broader implications for IT/IS portfolio management. These broader considerations are crucial in urban planning contexts, which typically involve a broad ecosystem of parties, complex decision-making challenges, and pre-existing technological landscapes. Drawing on the discipline of Enterprise Architecture Management (EAM), this paper argues that architectural coordination of DT development initiatives would enable more effective valorisation of DTs potential, and more effective management of DT-related technology within a broader technological landscape. To this end, the paper discusses the vision for and an initial sketch of a specialisation of EAM for DT development.

Keywords: BERTopic, Data-driven approach, Dynamic Topic Modeling, EMMSAD, IS analysis and design
Astract: Modeling for information systems (IS) analysis and design offers broad insights into the advances and challenges of enterprise, business process, software, and conceptual modeling. In celebration of its 30th edition, this paper presents a data-driven retrospective analysis of studies published at the Exploring Modeling Methods for Systems Analysis and Development (EMMSAD) working conference from 2005 to 2024. EMMSAD has long been a key venue for research on Information Systems (IS) Modeling, covering areas such as conceptual modeling, enterprise modeling, and model-driven engineering, as well as the evaluation of modeling techniques and tools. Using machine learning, specifically Dynamic Topic Modeling (DTM) with BERTopic, this study identifies recurring topics, emerging trends, and shifts in research focus within the IS modeling community. The findings highlight key areas of alignment between IS modeling and the broader modeling landscape, providing insights into the field’s evolution and future research opportunities.

Keywords: Conceptual Models, Domain Models, Modeling, Return on Modeling Efforts, Risk Assessment
Astract: Modelers and organizations often struggle to assess the benefits and drawbacks of modeling activities. This paper proposes addressing this challenge through a risk-oriented lens, leveraging the Common Ontology of ValuE and Risk (COVER) and the Reference Ontology for Security Engineering (ROSE). The proposal focuses on identifying assets at risk throughout the modeling process to clarify: when models mitigate risks and contribute to cost savings (models as risk deterrents), when models introduce risk to other assets (models as risk sources), or when they are vulnerable to risk events themselves (models as assets at risk), potentially generating additional costs. This perspective enables modelers and organizations to evaluate the benefits and costs of modeling practices, aligning investments with organizational goals, while helping researchers identify gaps for enhancing modeling languages, methods, and tools. The proposal is evaluated by analyzing case studies from the literature and interviews with nine professionals and researchers.

Keywords: Process Mining