Ten simple rules for making training materials FAIR

Area of Science:

• Computational Biology
• Bioinformatics Training
• Scientific Education

Background:

• Modern biology heavily relies on computational tools, yet formal training for biologists is often insufficient.
• Growing demand for computational biology skills necessitates effective training programs and accessible course materials.

Discussion:

• Existing training materials are frequently scattered and difficult to locate online.
• The Findable, Accessible, Interoperable and Reusable (FAIR) principles offer a framework to address the discoverability of digital scientific assets.
• Adapting FAIR principles can systematically enhance the accessibility and reusability of bioinformatics educational resources.

Key Insights:

• Implementing FAIR principles makes computational biology training materials more discoverable.
• Reusing and adapting existing materials reduces the need to create new content from scratch.
• Systematic application of FAIR guidelines improves the efficiency of educational resource management.

Outlook:

• Wider adoption of FAIR principles in scientific education can foster a more collaborative and efficient learning environment.
• Standardized approaches to resource sharing will accelerate the integration of computational skills in biology.
• Future training initiatives can leverage FAIR-compliant repositories for seamless access to bioinformatics educational content.