Result description
EOSC Matchmaker aggregates and enriches metadata from the project’s repositories in a Metadata Warehouse, enabling the discovery of datasets and linking them with analytics tools in a format that orchestration services can process for execution.
The service supports several phases of the research data lifecycle:
- Data discovery: AI-based discovery of data to accelerate the identification and collection of data to be used in the research.
- Data processing and analysis: To match datasets with the most appropriate tools for processing and analysis tasks.
- Data Preservation: To identify gaps in the FAIRness of datasets for adequate long-term preservation, overall improving the metadata needed for preservation.
- Data sharing and Re-Use: To facilitate faster discovery of newly deposited datasets.
Problem addressed
EOSC Matchmaker enhances research workflows by intelligently connecting datasets with suitable analytical tools.
It aggregates and enriches metadata from diverse repositories, enabling AI-driven discovery, automated pairing of data and tools, and seamless execution through orchestration services.
By supporting all key phases of the research data lifecycle, from planning to sharing, it accelerates data-driven science, improves metadata quality, and promotes FAIR and reusable research outputs.