An ecosystem for producing and sharing metadata within the web of FAIR Data

Area of Science:

• Data Science
• Information Science
• Research Data Management

Background:

• Descriptive metadata is crucial for research data reporting, discovery, and mobilization.
• Data producers face challenges in organizing, documenting, and ensuring metadata interoperability for data sharing.
• Existing tools often lack user-friendliness and require extensive training for data managers.

Purpose of the Study:

• To develop a user-friendly tool for managing research data metadata.
• To facilitate data organization, documentation, and sharing in compliance with FAIR principles.
• To assist data producers in meeting data management plan requirements.

Main Methods:

• Development of Maggot (Metadata Aggregation on Data Storage), a web-based tool.
• Implementation of high-level metadata management for local data catalogs.
• Integration of metadata crosswalk functionality for repository compatibility and third-party data collection.

Main Results:

• Maggot enables efficient generation and attachment of high-level metadata to datasets.
• The tool supports seamless data sharing in collaborative environments and aligns with data management plans.
• Metadata crosswalks facilitate conversion to repository-specific schemas and export for external applications.

Conclusions:

• Maggot streamlines high-level metadata collection using selected schemas and standards.
• The tool enhances data accessibility through metadata, supporting publicly funded project requirements.
• Maggot promotes effective local data management for FAIR data sharing and contributes to the EOSC FAIR Web of Data.