A Conceptual Workflow for Fine-Grained FAIR Assessment of Genomic Repositories

In this repository we maintain a Python-based framework for automatically assessing the compliance of genomic repositories with the FAIR principles (Findability, Accessibility, Interoperability, and Reusability).

Unlike existing FAIR assessment tools that typically evaluate entire datasets or repositories, this workflow performs fine-grained FAIR assessment at the level of individual digital objects (e.g., studies, series, biosamples, experiments, and files). The framework translates FAIR principles into measurable metrics and executable practical tests that can be applied across heterogeneous genomic repositories.

Supported repositories

The current implementation supports the following repositories:

• ArrayExpress / BioStudies
• Gene Expression Omnibus (GEO)
• GWAS Catalog
• ENCODE (both Biosamples and Experiments)
• Genomic Data Commons (GDC)

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Features

• Automated FAIR assessment
• Fine-grained evaluation of individual digital objects
• Repository-specific metadata extraction
• Keyword-based assessment
• Whole-repository assessment
• Detailed reports for each FAIR principle
• Comparative FAIR scores across repositories

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Repository structure

FAIR/
│
├── fair_metrics/          # FAIR assessment modules
├── metadata/              # Retrieved metadata
├── results/               # Generated assessment reports
│
├── assess.py              # FAIR assessment engine
├── evaluate.py            # Main entry point
├── repositories.py        # Repository-specific functions
├── utils.py               # Utility functions
├── demo.ipynb             # Example notebook
├── requirements.txt
└── README.md

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Installation

Clone the repository

git clone https://github.com/anadrmic/FAIR.git
cd FAIR

Create a virtual environment

python -m venv venv

Activate it

Linux/macOS

source venv/bin/activate

Windows

venv\Scripts\activate

Install the dependencies

pip install -r requirements.txt

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Usage

Run the assessment tool

python evaluate.py

The program interactively asks the user to:

1. Select a genomic repository
2. Choose the assessment mode
3. (Optionally) provide keywords
4. Execute the FAIR assessment

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Assessment modes

Keyword-based assessment

Evaluates only digital objects matching user-provided keywords.

This mode is useful for evaluating FAIRness of domain-specific collections.

Example:

Repository:
ArrayExpress

Keywords:
Parkinson
Homo sapiens

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Whole-repository assessment

Evaluates all available digital objects retrieved from the selected repository.

This mode provides an overall FAIR profile of the repository.

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Output

The assessment generates:

• Overall FAIR scores
• Metric-level scores
• Principle-level reports
• Detailed explanations of each practical test

Results are stored in the results/ directory.

Typical outputs include

scores.txt
Findability.txt
Accessibility.txt
Interoperability.txt
Reusability.txt
fair_principles_scores.png

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Assessment methodology

The workflow follows a three-level assessment:

FAIR Principle
        ↓
Metric
        ↓
Practical Test

Each practical test evaluates one aspect of FAIR compliance and produces a normalized score.

Metric scores are aggregated into FAIR principle scores to produce the final assessment.

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Publications

If you use this software in your research, please cite:

Anna Bernasconi, Ana Drmic A Conceptual Workflow for Fine-Grained FAIR Assessment of Genomic Repositories. (under submission)

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License

This repository is intended for research and educational purposes.

Please check the repository license before redistribution or commercial use.

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Contact

Anna Bernasconi

https://annabernasconi.faculty.polimi.it/

anna.bernasconi@polimi.it