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fair-data

Guide researchers in applying FAIR data principles to research data.

6|2|Updated Jun 11, 2026
Search Tags:#data management#metadata#data sharing#research data#FAIR data
One-click install
npx skills add https://github.com/pradyumnasagar/open-research-skills --skill fair-data
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: fair-data
Source: https://github.com/pradyumnasagar/open-research-skills/tree/main/skills/open-science/fair-data
Command: npx skills add https://github.com/pradyumnasagar/open-research-skills --skill fair-data

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill helps researchers ensure their data is FAIR (Findable, Accessible, Interoperable, and Reusable), adhering to best practices for data management and sharing.

Core Features & Use Cases

  • FAIR Data Principles: Guides users through the FAIR principles for data management.
  • Repository Selection: Assists in choosing the appropriate data repository.
  • Metadata Writing: Provides templates and guidance for writing machine-readable metadata.
  • License Application: Recommends open licenses for data sharing.
  • Data Linking: Ensures data is linked to publications and code.
  • Use Case: For a researcher preparing a data management plan and looking to share their data in a FAIR manner.

Quick Start

Use the fair-data skill to check your data against the FAIR principles and ensure it is properly managed and shared.

Frequently Asked Questions about fair-data

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
What are FAIR data principles for research data management?▼

FAIR data principles provide guidelines to make research data Findable, Accessible, Interoperable, and Reusable. They help researchers apply best practices for data management and sharing to improve data reuse.

How do I write machine-readable metadata for my research data?▼

You can write machine-readable metadata using provided templates and guidance. This Skill helps structure your metadata to ensure your research data adheres to FAIR principles and is properly documented for discovery.

How do I choose the right repository for sharing research data?▼

Select an appropriate data repository by evaluating your specific data types and sharing requirements. This Skill assists researchers in repository selection to ensure data meets FAIR compliance standards.

What open licenses should I apply to research data for sharing?▼

Applying open licenses to research data is recommended to enable proper sharing. This Skill recommends appropriate open licenses to ensure your data remains accessible and reusable under clear terms.

Do I need prior knowledge of data types and repositories to make data FAIR?▼

Yes, making data FAIR requires existing knowledge of your data types and repositories. This Skill provides the guiding framework for metadata creation and license application, but expects you to understand your data context.

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