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 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. Collection Offers domain-specific templates and guidance to capture structured, FAIR-compliant metadata at the point of data generation. Processing Integrates with scientific workflows and notebooks (e.g., Jupyter, Galaxy) to capture processing steps and ensure reproducibility. Tracks provenance automatically, minimizing manual effort. 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. Preservation Ensures outputs (data, software, notebooks) are stored in trusted repositories with proper versioning and metadata. Supports long-term access and automated metadata enrichment. Sharing Simplifies open publication via persistent identifiers (DOIs), licensing recommendations, and repository integration. Encourages proper crediting and boosts impact through visibility. 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 MattersResearchers 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.