## 2 Related Works and Gap Analysis
The standard is strongly related to previous standards developed to manage information through the product life cycle at the various engineering process phases, as discussed in [35] and shown in Figure 1.  
In Figure 2, we show a representative picture of the main engineering process phases, which groups the main activities described in Clause B.2 of the ISO/IEC 81346 standard to define the development of one single object over its entire life cycle [34]. This represents the baseline we use to construct the engineering process model presented in this paper. Figure 1: Scope of IEC standards supporting the product life cycle. Figure 2: Main engineering process phases of ISO/IEC 81346 standard. The idea of using this standard as a reference for constructing an SOA-based framework has already been introduced in [36] to be able to present all of the different types of objects and relations that are expected to be present in a future Internet of Things (IoT) or Industrial Internet of Things (IIoT) network in a useful engineering tool or set of tools. The concept of displaying different aspects of the same objects appears to be a useful solution. An approach to the multistakeholder management of the life cycle has been proposed with collaborative product development [37]. Nevertheless, this approach and other models, such as RAMI 4.0 and IEC81346, present different limitations in the coverage of EP phases, which, e.g., are limited only to the initial phases of the EP (typically functional design, development, and partial deployment) and do not cover commissioning, operation and management, maintenance, retirement, etc. The ontology that we propose covers the entire EP and allows us to describe the complexity of an extensive system or SoS (e.g., a manufacturing plant), the role of the system constituent components and their relations (e.g., the plant machines and their role in the production process), and provides a basic common understanding of the system layout (e.g., the manufacturing plant). Moreover, the advantage of using an ontology is the possibility of sharing a knowledge base that improves the interoperability between different digitalisation and automation solutions, adopted by different stakeholders, with various roles in the IoT value chain, guided by a variety of interests, objectives, etc. Currently, a critical necessity that characterises the Industry 4.0 paradigm is the digitalisation of highly interconnected processes that share valuable information for improving efficiency and increasing the flexibility of production systems [38]. However, from this perspective, a new dimension emerges because the Industry 4.0 paradigm foresees the aggregation of stakeholders in ecosystems (e.g., a factory, an airport, and a transportation system), and this type of aggregation requires data sharing among different engineering processes and phases with their specific automation levels and different stakeholders, which are typically geographically distributed [39]. Sharing these data enables the optimisation of productivity, raw material yield, energy and environmental footprint, operational and production costs, etc., which is the basic motivation for automation. Several reference architectures and models have been conceived to improve the digitalisation level of manufacturing by combining concepts [40], methodologies, and technologies taken from the IoT [41], cyber-physical systems (CPSs) [42; 43], cloud computing [44; 45], big data analytics (BDA) [46], and information and communications technology (ICT) [47]. Some examples are the smart manufacturing ecosystem developed by NIST [48], the industrial internet reference architecture (IIRA) [49], the IBM Industry 4.0 Architecture [50], and the reference architecture model industries 4.0 (RAMI 4.0), one of the most eminent emerging architectures [16] that intends to drive the manufacturing industry in the direction of a more connected and integrated development model for EP automation [51]. However, according to the shortfall analysis conducted by [PERSON] et al.