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- full type Paper assertion.
- full type Resource assertion.
- full type MediaObject assertion.
- full description "Although all the technical components supporting fully orchestrated Digital Twins (DT) currently exist, what remains missing is a conceptual clarification and analysis of a more generalized concept of a DT that is made FAIR, that is, universally machine actionable. This methodological overview is a first step toward this clarification. We present a review of previously developed semantic artifacts and how they may be used to compose a higher-order data model referred to here as a FAIR Digital Twin (FDT). We propose an architectural design to compose, store and reuse FDTs supporting data intensive research, with emphasis on privacy by design and their use in GDPR compliant open science." assertion.
- full dateCreated "2023-01-11 08:09:52.086059+00:00" assertion.
- full name "FAIR Digital Twins for Data-Intensive Research" assertion.
- full contentUrl "https://www.frontiersin.org/articles/10.3389/fdata.2022.883341/full" assertion.
- full creator 0000-0002-1784-2920 assertion.
- full dateModified "2023-01-11 08:09:53.313682+00:00" assertion.
- full license no-permission assertion.
- full sdDatePublished "2023-01-11 08:09:52.086059+00:00" assertion.
- full keywords "digital twin" assertion.
- full author 0000-0002-1784-2920 assertion.