Digital Twins of Socio-Technical Ecosystems to Drive Societal Change Show others and affiliations
2024 (English) In: ACM/IEEE 27TH INTERNATIONAL CONFERENCE ON MODEL DRIVEN ENGINEERING LANGUAGES AND SYSTEMS: COMPANION PROCEEDINGS, MODELS 2024, ASSOC COMPUTING MACHINERY , 2024, p. 275-286Conference paper, Published paper (Refereed)
Abstract [en]
While the engineering of digital twins (DTs) of cyber-physical systems already faces a number of challenges, DTs of socio-technical systems are made even more complex by human and social factors, and a comprehensive representation of their internal relations is currently lacking. DTs for socio-technical systems could open up new ways of achieving common societal goals by i) providing an understanding of complex interactions and processes, and by ii) facilitating the design of and participation in collective actions. In this context, dynamic adaptation and motivational strategies would be required to swiftly address sub-optimal system behavior. To enable the model-driven engineering of DTs responding to such requirements, we propose a conceptual model of socio-technical systems and discuss it with use-case scenarios. The presented approach supports our vision of future DT-based model-driven interventions, empowering citizens and stakeholders in driving societal change and increasing community resilience.
Place, publisher, year, edition, pages ASSOC COMPUTING MACHINERY , 2024. p. 275-286
Keywords [en]
Digital Twin, Modeling, Socio-Technical System, Model-Driven Engineering, System Engineering
National Category
Mechanical Engineering
Identifiers URN: urn:nbn:se:mdh:diva-69428 DOI: 10.1145/3652620.3686248 ISI: 001351589800046 ISBN: 979-8-4007-0622-6 (print) OAI: oai:DiVA.org:mdh-69428 DiVA, id: diva2:1920096
Conference ACM/IEEE 27th International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings (MODELS), SEP 22-27, 2024, Linz, AUSTRIA
2024-12-102024-12-102024-12-10 Bibliographically approved