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SCALEUS-FD: A FAIR Data Tool for Biomedical Applications.

Arnaldo Pereira¹, Rui Pedro Lopes², José Luís Oliveira¹

¹DETI/IEETA, University of Aveiro, Aveiro, Portugal.

Biomed Research International

|September 10, 2020

Summary

This summary is machine-generated.

This study presents SCALEUS-FD, a FAIR Data extension for Semantic Web tools, enabling seamless integration of legacy data into the FAIR Data ecosystem for better data sharing and reuse.

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Area of Science:

Computer Science
Data Science
Bioinformatics

Background:

The Semantic Web and Linked Data facilitate managing distributed, heterogeneous scientific data.
FAIR Data principles (Findable, Accessible, Interoperable, Reusable) are crucial for effective data stewardship.
Transforming legacy systems into the FAIR Data ecosystem is essential for maximizing data potential.

Purpose of the Study:

To introduce SCALEUS-FD, a FAIR Data extension for a legacy Semantic Web tool.
To enable smooth transformation of legacy solutions into the FAIR Data ecosystem.
To support data integration, semantic annotation, and enrichment within FAIR principles.

Main Methods:

Developed SCALEUS-FD as a FAIR Data extension of an existing Semantic Web tool.
Implemented core functionalities based on Semantic Web and Linked Data principles.
Provided a FAIR REST API for machine-to-machine interoperability.
Evaluated the tool's 'FAIRness' using a set of metrics.
Demonstrated the application in the rare diseases domain.

Main Results:

SCALEUS-FD successfully extends a legacy Semantic Web tool with FAIR Data capabilities.
The tool offers a FAIR REST API for automated data operations.
Evaluation metrics confirmed the 'FAIRness' of the implemented solution.
An application scenario in rare diseases showcased its practical utility.

Conclusions:

SCALEUS-FD facilitates the integration of legacy data into the FAIR Data ecosystem.
The solution enhances data findability, accessibility, interoperability, and reusability.
This work contributes to advancing FAIR Data adoption in scientific research, particularly in specialized domains like rare diseases.