TY - GEN
T1 - Overcoming the Data Availability Paradox with Managed Digital Twin Instances
AU - Ugbomah, Christopher
AU - Kumi, Sandra
AU - Lomotey, Richard K.
AU - Deters, Ralph
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Digital transformation, IoT, and cloud storage have led to vast data collections that tend to exist in isolated silos, thus limiting their utilization. This leads to the data availability paradox, in which individuals, groups, and organizations possess vast amounts of data but struggle to utilize or share it effectively. The struggle is due to privacy, security, and intellectual property concerns. When this happens, individuals and institutions are unable to take full advantage of the capability of Industry 4.0 and digitalization. This paper proposes using managed Digital Twin Instances (DTI) to overcome this paradox. The fully managed digital twin instances provide well-defined and fully controlled access to models derived from the underlying data sets. Digital twin instances, therefore serve as virtual replicas of real-world systems, entities, or processes, enabling controlled access. A key issue in this approach is the effective hosting and managing large numbers of digital twin instances. The paper introduces a management and hosting framework and its evaluation in the MS Azure cloud environment.
AB - Digital transformation, IoT, and cloud storage have led to vast data collections that tend to exist in isolated silos, thus limiting their utilization. This leads to the data availability paradox, in which individuals, groups, and organizations possess vast amounts of data but struggle to utilize or share it effectively. The struggle is due to privacy, security, and intellectual property concerns. When this happens, individuals and institutions are unable to take full advantage of the capability of Industry 4.0 and digitalization. This paper proposes using managed Digital Twin Instances (DTI) to overcome this paradox. The fully managed digital twin instances provide well-defined and fully controlled access to models derived from the underlying data sets. Digital twin instances, therefore serve as virtual replicas of real-world systems, entities, or processes, enabling controlled access. A key issue in this approach is the effective hosting and managing large numbers of digital twin instances. The paper introduces a management and hosting framework and its evaluation in the MS Azure cloud environment.
UR - http://www.scopus.com/inward/record.url?scp=105002212536&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=105002212536&partnerID=8YFLogxK
U2 - 10.1109/SWC62898.2024.00311
DO - 10.1109/SWC62898.2024.00311
M3 - Conference contribution
AN - SCOPUS:105002212536
T3 - Proceedings - 2024 IEEE Smart World Congress, SWC 2024 - 2024 IEEE Ubiquitous Intelligence and Computing, Autonomous and Trusted Computing, Digital Twin, Metaverse, Privacy Computing and Data Security, Scalable Computing and Communications
SP - 2025
EP - 2032
BT - Proceedings - 2024 IEEE Smart World Congress, SWC 2024 - 2024 IEEE Ubiquitous Intelligence and Computing, Autonomous and Trusted Computing, Digital Twin, Metaverse, Privacy Computing and Data Security, Scalable Computing and Communications
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th IEEE Smart World Congress, SWC 2024
Y2 - 2 December 2024 through 7 December 2024
ER -