pISA-tree - a data management framework for life science research projects using a standardised directory tree

Area of Science:

• Life Sciences
• Bioinformatics
• Data Management

Background:

• Effective organization of life science research data and metadata is crucial for reproducibility and collaboration.
• Existing data management solutions may lack flexibility or be costly to maintain.
• The need for standardized, FAIR-compliant data handling in multi-partner projects is increasing.

Purpose of the Study:

• To develop a straightforward and flexible data management solution for life science projects.
• To create a system that addresses end-user requirements for practicality and low maintenance.
• To support the principles of Open Science and FAIR data.

Main Methods:

• Development of pISA-tree, a system for on-the-fly creation of a standardized directory tree structure (project/Investigation/Study/Assay) based on the ISA model.
• Implementation of template-based metadata generation at each level for guided submission.
• Complementary R packages, pisar for bioinformatic pipeline integration and ISA-Tab export, and seekr for FAIRDOMHub synchronization.

Main Results:

• pISA-tree enables standardized organization of research data and metadata through an enriched directory tree structure.
• The system facilitates guided metadata submission using templates, improving data consistency.
• Integration with R packages (pisar, seekr) enhances data usability in pipelines and repository synchronization.
• Successful application demonstrated in multi-partner national and international projects.

Conclusions:

• pISA-tree provides a practical, low-maintenance solution for managing life science research data.
• The system promotes Findable, Accessible, Interoperable, and Reusable (FAIR) research practices.
• pISA-tree aligns with Open Science initiatives by enhancing data organization and accessibility.