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Related Experiment Video

Updated: Sep 21, 2025

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FAIR Digital Twins for Data-Intensive Research.

Erik Schultes^1,2, Marco Roos^1,3, Luiz Olavo Bonino da Silva Santos⁴

¹Leiden Institute for FAIR and Equitable Science, Leiden, Netherlands.

Frontiers in Big Data

|June 1, 2022

Summary

This summary is machine-generated.

This study introduces the FAIR Digital Twin (FDT), a universally machine-actionable concept. It proposes an architecture for composing, storing, and reusing FDTs for data-intensive research within open science frameworks.

Keywords:

FAIR Digital Object FAIR Digital Twin FAIR guiding principles Knowlet augmented reasoning data stewardship machine learning nanopublications

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Area of Science:

Digital Twin technology
Data science
Open science
Information science

Background:

Technical components for Digital Twins (DT) are available.
A conceptual gap exists in generalizing DTs to be FAIR (Findable, Accessible, Interoperable, Reusable) and machine-actionable.
Existing semantic artifacts can be leveraged for this generalization.

Purpose of the Study:

To conceptually clarify and analyze a generalized FAIR Digital Twin (FDT).
To propose a methodological overview and architectural design for FDTs.
To support data-intensive research using privacy-preserving, GDPR-compliant open science principles.

Main Methods:

Review of existing semantic artifacts.
Development of a higher-order data model for FDTs.
Proposal of an architectural design for FDT composition, storage, and reuse.

Main Results:

A conceptual framework for FAIR Digital Twins (FDTs) is presented.
An architectural design is proposed for creating, managing, and utilizing FDTs.
Emphasis is placed on privacy-by-design and GDPR compliance for open science.

Conclusions:

The FAIR Digital Twin (FDT) concept bridges the gap towards universally machine-actionable digital twins.
The proposed architecture facilitates the practical implementation of FDTs in data-intensive research.
This work supports the advancement of GDPR-compliant, privacy-preserving open science initiatives.