One of the main topics within research activities is the management of research data. Large amounts of data acquired by heterogeneous scientific devices, sensor systems, measuring equipment, and experimental setups have to be processed and ideally be managed by Findable, Accessible, Interoperable, and Reusable (FAIR) data management approaches in order to preserve their intrinsic value to researchers throughout the entire data lifecycle. The symbiosis of heterogeneous measuring devices, FAIR principles, and digital twin technologies is considered to be ideally suited to realize the foundation of reliable, sustainable, and open research data management. This paper contributes a novel architectural approach for gathering and managing research data aligned with the FAIR principles. A reference implementation as well as a subsequent proof of concept is given, leveraging the utilization of digital twins to overcome common data management issues at equipment-intense research institutes. To facilitate implementation, a top-level knowledge graph has been developed to convey metadata from research devices along with the produced data. In addition, a reactive digital twin implementation of a specific measurement device was devised to facilitate reconfigurability and minimized design effort.

No abstract

No abstract

Due to the growing environmental and geopolitical challenges nowadays, which are causing supply chain complications, industry and society are facing significant new objections. As a complement and extension to the technology-driven premises of Industry 4.0, the value-driven Industry 5.0 focuses on society and the environment. Human centricity, sustainability, and resilience should become a more integral part of both industrial and societal revolutions. One of the enabler technologies for both is the Digital Twin (DT). In order to make DTs intelligent, they must become active, online, goal-seeking, and anticipatory. To meet these requirements, the characteristics of Multi-Agent Systems (MASs) can be employed. This paper contributes to the bilateral emergence of the two industrial paradigms and establishes an approach for the provision of Intelligent Digital Twins (IDTs) within the Internet of Digital Twins (IoDT). Initially, a DT reference model aligned with already established Industry 4.0 reference models enriched with the goals of Industry 5.0 is developed, followed by an outline of how IDTs can be realized with the characteristics of MAS. The work is substantiated by an architectural design for IDTs choreographing marketplace-oriented production processes with a subsequent prototypical implementation, followed by a proof of concept.