On 26th January 2022, Prof. Balbir Barn from LDTRC delivered a keynote talk on “Digital Twin: Current Practice and Future (Sociotechnical) Prospects” at the MDENET Symposium 2022. Digital Twin research and activity is prevalent such that Digital Twins are acquiring silver bullet status. In the United Kingdom in particular, Digital Twin features as a key strand in future-proofing UK infrastructure such as that described in the UK Innovation Strategy. Notably, Digital Twins (DT) have a family resemblance to computational modelling and computer simulation more generally. The talk outlined the importance of the role of DT, their key characteristics, the types of digital twin and their underpinning enabling technologies.
Characteristics prevalent in descriptions of DTs include aspects such as self-adaption, self-regulation, self-monitoring, and self-diagnosing. Types of DTs include the notion of Digital Models, Digital Blueprints, Digital Shadows and of course, pure-play Digital Twins. Applications of DTs are currently dominated by use cases such as anomaly detection, physical infrastructure modelling, predictive maintenance and cyber-physical systems. But there is now also scope for the use of DTs in sociotechnical settings. Sociotechnical DTs are a deprecated form of DT (Shadow, Blueprint, Model), but nonetheless, generate specific challenges that arise from a gap that emerges between the social requirements and the technical machinery of digital twins. Challenges include the lack of appropriate sociotechnical design methods, problems arising from a so-called abstraction gap and various epistemological concerns. The latter are compounded when Machine Learning is utilised. A route to ameliorating the sociotechnical gap is proposed and discussed within a future notion of an Environment Digital Twin. In particular, attention is given to the role of model driven engineering practices and lessons from historical practice from software engineering.
Full programme is: MDENet-Annual-Symposium-Program2022