Developing a standardized but extendable framework to increase the findability of infectious disease datasets

Area of Science:

• Biomedical Informatics
• Open Science
• Data Management

Background:

• Biomedical datasets are growing rapidly, posing challenges for FAIRness (findability, accessibility, interoperability, reusability).
• Existing repositories often lack standardized metadata, hindering data discovery and reuse.
• Infectious disease researchers aim to enhance transparency and reproducibility through open science.

Purpose of the Study:

• To improve the FAIRness of biomedical datasets and computational tools.
• To address the lack of standardized metadata in biomedical data repositories.
• To enable data discovery and accelerate research through data reuse.

Main Methods:

• Evaluated metadata standards across biomedical data repositories.
• Developed a reusable metadata schema based on Schema.org.
• Catalogued nearly 400 datasets and computational tools using the new schema.

Main Results:

• Identified a lack of adherence to single metadata standards like Schema.org in most repositories.
• Created a customized, reusable metadata schema interoperable with community standards.
• Successfully catalogued 400 datasets and tools, improving data discovery and reusability.

Conclusions:

• The developed metadata schema enhances data discovery and reusability for research consortiums.
• This approach facilitates interoperability and customization for specific research contexts.
• Ongoing challenges in FAIRness beyond discoverability require further attention.