OSTrails: Advancing FAIR and Reproducible Science in Big Data Environments through EOSC Science Clusters

The OSTrails project advances Open Science by making FAIR and reproducible research a reality in data-intensive domains. It does so by integrating community-driven tools, workflows, and services that reduce the burden on researchers while increasing the quality and reusability of scientific outputs. 

How OSTrails Supports the Data Lifecycle

1. Planning
• Machine-actionable Data Management Plans (maDMPs) help researchers define clear, funder-aligned data strategies from the start.
• Automates linking of datasets, publications, and software for traceability.
2. Collection
• Offers domain-specific templates and guidance to capture structured, FAIR-compliant metadata at the point of data generation.
3. Processing
• Integrates with scientific workflows and notebooks (e.g., Jupyter, Galaxy) to capture processing steps and ensure reproducibility.
• Tracks provenance automatically, minimizing manual effort.
4. Analysis
• Facilitates re-use and sharing of analytical workflows across teams and disciplines.
• Links datasets to analysis steps, software versions, and parameters—building a chain of trust.
5. Preservation
• Ensures outputs (data, software, notebooks) are stored in trusted repositories with proper versioning and metadata.
• Supports long-term access and automated metadata enrichment.
6. Sharing
• Simplifies open publication via persistent identifiers (DOIs), licensing recommendations, and repository integration.
• Encourages proper crediting and boosts impact through visibility.
7. Reuse
• Assesses and enhances the FAIRness of research outputs using customizable indicators.
• Encourages composability: your work becomes part of others’ research, not just a citation.

Why It Matters
Researchers today face increasing demands for transparency, compliance, and impact. OSTrails meets these needs by:

• Reducing admin overhead
• Enabling reproducibility by design
• Promoting trust and visibility in Open Science

OSTrails doesn’t ask researchers to do more—it helps them do what they already do, better and faster.