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doi: 10.1145/3507909
handle: 11576/2697869 , 11380/1263161 , 11585/879941
In recent years, digital twins have been pervading different application domains—from manufacturing to healthcare—as an approach for virtualising different kinds of physical entities (things, products, machines). The dominant view developed in the literature so far is about the virtualisation of individual physical assets in a closed-system perspective. In this article, we introduce and explore a broader perspective that we call Web of Digital Twins (WoDT), in which the digital twin paradigm is exploited for the pervasive softwarisation of possibly large-scale interrelated physical realities. A WoDT can be conceived as an open, distributed and dynamic ecosystem of connected digital twins, functioning as an interoperable service-oriented layer for applications running on top, especially smart applications and multiagent systems. The article introduces an abstract model and architecture aimed to capture key aspects of the idea not bound to any specific application domains or implementing technologies and discusses their adoption in engineering real-world systems. To this purpose, two concrete case studies are considered, in the context of healthcare and smart mobility. Finally, the article includes a discussion of a selected set of research directions.
Digital Twins, Web of Things, Semantic Web, Intelligent Systems, Computer Networks and Communications, agents; Digital twins; MAS; web; WoDT;
Digital Twins, Web of Things, Semantic Web, Intelligent Systems, Computer Networks and Communications, agents; Digital twins; MAS; web; WoDT;
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 94 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 1% |
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