## 1 Introduction  
Sociotechnical systems (STSs) generally assume system-of-systems (SoS) incorporating humans and technology, with three essential characteristics: emergence (the system as a whole is not a simple sum of its components), non-determinism (the system does not always produce the same output as the response to the same input), and subjective behavior (the quality and usability assessments rely solely on the system stakeholders), demanding joint optimization equally respecting technical excellence and inherent diversity of human activities [1, 2]. They strongly depend on a sustainable equilibrium between the nondeterministic social context ingredients: social structures, roles, and rights, and the designers' Holy Grail, the deterministic nature of the underlying technical system. Concerning maturity, the relevant social concepts are more mature than the supportive technologies, causing the digital transformation of sociotechnical systems to be a reengineering instead of an engineering endeavor. Following the maturation dimension of STS design principles, in [3], the authors point out a still dominant linear approach to organizational transitions, with clearly defined current and future states, rather than keeping up with a nondeterministic and continuously evolving nature of the future state. Concerning the STS theory, the extent to which an organizational system adheres to the knowledge management (KM) drivers determines its ability to mitigate the inherent non-linear social uncertainty while incorporating linear and deterministic technological innovations [4]. Consequently, engineering or reengineering of STSs represents a wicked problem usually perceived as difficult to define, to select the appropriate resolving methodology, to achieve a definitive successful solution, or even to assess the solution's appropriateness without at least one previous unsuccessful solving attempt [5,6]. The relations between the STS's functions and human-task allocation determine the importance of requirements elicitation, specification, and modeling activities [7,8]. On the other hand, the nature of information flow across the STS architecture demands mitigation of the inherent information architecture (IA) duality (social and technology-related) [9]. In keeping the STSs' resilience at a maximum level, adaptive strategies in a varying context and possibly unpredictable human behavior open a challenging approach to the dynamic game theory application [10]. According to [11], agent-based modeling and simulation (ABMS) is a valuable tool for assessing complex STSs and is becoming increasingly advanced through integrating data-driven capabilities. The inherent dichotomy of sociotechnical systems is augmented by segregating humans from social context and introducing the observer-based (human, social, and technology) approach, mitigating the complexity emerging from biological, organizational, and technology systems interactions through structural coupling that forms the human-social-technology (HST) recursive trichotomy [12]. Each observer possesses the evaluation criteria that ensure the preservation of its internal logic in potentially disruptive context (codes), rules and criteria guiding the application of codes while architecting and operating the observer system to mitigate the context-related influences (programs), and mechanisms that enable the observer-system to distinguish itself from the contemporary context (medium/form distinction). Assuming humans are psychical systems with inherent biological autopoiesis (producing and maintaining itself by creating its parts), in [12], the authors perceive the technology as an autopoietic system and leave the inherent nature of the social dimension intact. The concept of transpoiesis in social systems theory emerges from the need to maintain strategic coherence within decentralized organizations. The STSs fulfill the proclaimed missions in the broader social and technology context, raising the importance of context management foundations.