## 1 Introduction  
The challenge posed by digital transformation necessitates fundamental shifts in the conceptualization of assets. The current Industry 5.0 paradigm introduces a landscape where the fusion of digital and physical features of assets with human elements reaches an unprecedented level of interaction, resulting in increasingly complex systems of systems (SoSoS) [1, 2, 3]. Achieving interoperability among all entities involved in this context becomes a global challenge, requiring not only technological advancements but also a mature vision for defining key entities such as assets, processes, and human involvement. A noteworthy concern in addressing interoperability lies in the efficient integration of comprehensive data and information within each asset [4, 5, 6]. Frequently, asset data are scattered across diverse locations, including information systems, applications, edge devices, and cloud platforms. This dispersion limits direct accessibility, coherence, and seamless interaction with human stakeholders, exacerbating the issue of information silos. Digital assets encompass more than raw data; they integrate critical components such as data, models, and services, forming the foundation of digital twins [7]. As digitalization advances from its early focus on data collection and standalone models, the emphasis has shifted towards managing these models effectively. This evolution is critical, as models act as enablers of innovative services that enhance asset value and improve decision-making processes. The feasibility of overseeing and coordinating all models representing an asset as a management entity is now achievable [8]. This aligns with the broader adoption of model-based systems engineering (MBSE) in systems engineering [5]. MBSE supports technologies such as digital twins, Building Information Modeling (BIM), and the Asset Administration Shell (AAS), facilitating a structured approach to digitalization. While technology and platform design are vital to digitalization, there is a growing need to prioritize assets as the central focus [8]. The rapid development of IoT technology offers a practical entry point by bridging the physical and digital worlds. IoT networks enable processes like asset digitization and the digitalization of asset management, as illustrated by frameworks such as the Industrial Internet Reference Architecture (IIRA) and RAMI 4.0 [4; 9; 10]. IoT sensor networks, as key components of the physical asset layer, allow for real-time data acquisition and processing. Designing IoT networks typically begins with identifying and describing the assets to be monitored. However, this initial representation often falls short of addressing the complexities required for advanced digitalization, particularly in supporting predictive processes and strategic decision-making. Maintenance digitalization, a vital subset of asset digitalization, leverages IoT platforms and Prognostics and Health Management (PHM) methods to gather real-time data on asset conditions. This continuous influx of data supports proactive maintenance strategies, reducing unplanned downtime and extending asset lifespans [1; 11; 12; 13; 14]. This shift from reactive to dynamic Intelligent Asset Management underscores the importance of aligning IoT technology with the specific needs of assets. Holistic solutions that improve decision-making and operational outcomes unlock greater value, reduce costs, and accelerate digital transformation initiatives. As digitalization strategies evolve, IoT remains a foundational technology for modern asset management systems. Technologies like Building Information Modeling (BIM) [15; 16; 17] or Augmented Reality (AR) [18; 19; 20] play key roles in maintenance, offering practical benefits such as enhanced reliability and reduced costs. Despite advancements in data accessibility and processing, the maturity of leveraging digitalization outputs in decision-making remains low. Many organizations continue to rely on traditional practices, limiting the potential of emerging capabilities.