Towards Semantically Enhanced Digital Twins

Kharlamov, Evgeny; Martín-Recuerda, Francisco; Perry, Brandon C.; Cameron, D.; Fjellheim, Roar; Waaler, Arild

doi:10.1109/bigdata.2018.8622503

Cited by 33 publications

(17 citation statements)

References 33 publications

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“…Ontology models allow capturing the digital entities intuitively with standardised ontology languages. Based on ontology, semantic analysis of knowledge enhancement can be conducted to support co-simulation, and several stages of co-simulation are covered with semantic models (Kharlamov et al 2018).…”

Section: Ontology Supporting Co-simulationmentioning

confidence: 99%

Co-simulation of complex engineered systems enabled by a cognitive twin architecture

Chen

et al. 2021

International Journal of Production Research

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Since the complex engineered system involves multi-disciplinary, co-simulation is the key technique to the performance analysis. However, the co-simulation is hindered by heterogeneous sub-systems and ununified environments. In this paper, a Cognitive Twin (CT) to support the co-simulation of the complex engineered system is introduced. It is a generic approach that can be applied in many complex engineered systems such as the aerospace field, automotive system, the Internet of Things, manufacturing systems, etc. CT adopts an ontology model to develop cognition capability based on CT architecture. Then, a unified ontology modelling approach based on GOPPRR (graph, object, point, property, role, relationship) is presented to support an accurate semantic description of the topology between digital entities that use FMI 2.0 as the interconnection standard. Besides, four types of information are included in the ontology model to form the knowledge in co-simulation. Finally, the co-simulation is automatically executed using the cognition capability. Furthermore, a master-slave algorithm is deployed to establish a unified co-simulation environment. The flexibility of CT is evaluated using a gas turbine case. The results demonstrate that the complication in the cosimulation of complex engineered systems is solved by the unified ontology modelling approach and the architecture of CT.

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Section: Ontology Supporting Co-simulationmentioning

confidence: 99%

Co-simulation of complex engineered systems enabled by a cognitive twin architecture

Chen

et al. 2021

International Journal of Production Research

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“…Semantic technologies provide solutions to achieve semantic interoperability in a heterogeneous system [7]. Semantic models enable to capture complex systems in an intuitive fashion, which can be summarized in standardized ontology languages, and come with a wide range of offthe-shelf systems to design, maintain, query, and navigate semantic models [8]. This characteristic makes semantic modelling a promising paradigm to address the challenges that DT development is facing currently.…”

Section: Related Workmentioning

confidence: 99%

Cognitive Twins for Supporting Decision-Makings of Internet of Things Systems

Zheng

Gharaei

et al. 2020

Lecture Notes in Mechanical Engineering

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Cognitive Twins (CT) are proposed as Digital Twins (DT) with augmented semantic capabilities for identifying the dynamics of virtual model evolution, promoting the understanding of interrelationships between virtual models and enhancing the decision-making based on DT. The CT ensures that assets of Internet of Things (IoT) systems are well-managed and concerns beyond technical stakeholders are addressed during IoT system development. In this paper, a Knowledge Graph (KG) centric framework is proposed to develop CT. Based on the framework, a future tool-chain is proposed to develop the CT for the initiatives of H2020 project FACTLOG. Based on the comparison between DT and CT, we infer the CT is a more comprehensive approach to support IoTbased systems development than DT.

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“…Digital twins are the key technology aiming at realizing the mapping of physical systems to digital models in the information space. It makes full use of sensors arranged in each part of the systems to analyze and model physical entity data, forming a multidisciplinary, multiphysicalquantity, multitime-scale, multiprobability simulation process [6]- [8] and reflects the full-life process in different real scenes. Digital twins mainly include three parts, which are a physical entity in the physical space, virtual entity in the artificial space, and connection data and the information between them [9].…”

Section: From Digital Twins To Parallel Systemsmentioning

confidence: 99%

Parallel Societies: A Computing Perspective of Social Digital Twins and Virtual–Real Interactions

Wang

Qin

et al. 2020

IEEE Trans. Comput. Soc. Syst.

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W ELCOME to the first issue of the IEEE TRANS-ACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS (TCSS) of 2020, and Happy New Year to You! We would like to take this opportunity to express our sincere thanks to our editors, reviewers, authors, and readers for your great support and effort devoted to the TCSS, along with our best wish and hope that everyone has a happy, healthy, and fruitful 2020.In this issue, we publish eight regular articles, a brief discussion on parallel societies, and a special issue entitled "Social Sensing and Privacy Computing in Intelligent Social Systems" is published, which includes 16 articles.I would like to share some latest news of the IEEE TCSS with you. In October 2019, we completed our first five-year review cycle (2014-2018) carried out by the Periodicals Review and Advisory Committee (PRAC), and on November 21, I went to a face-to-face review in Boston, MA, USA (see Fig. 1). Our effort on the TCSS is unanimously and highly recognized by the PRAC, and they concluded that we had made a significant progress over the last two years (2017)(2018).

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Towards Semantically Enhanced Digital Twins

Cited by 33 publications

References 33 publications

Co-simulation of complex engineered systems enabled by a cognitive twin architecture

Co-simulation of complex engineered systems enabled by a cognitive twin architecture

Cognitive Twins for Supporting Decision-Makings of Internet of Things Systems

Parallel Societies: A Computing Perspective of Social Digital Twins and Virtual–Real Interactions

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