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Research Data Repository Management with ARC Structure"

Researchers benefit from standardized data management using ARC (Annotated Research Context) structure in GitLab, enabling collaborative research data sharing, automated validation, and long-term data preservation with integrated metadata.

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Overview

Value: Researchers benefit from standardized data management using ARC (Annotated Research Context) structure in GitLab, enabling collaborative research data sharing, automated validation, and long-term data preservation with integrated metadata.

Problem: Research data in TRR341 project lacks standardized structure and management, making collaboration difficult, data validation manual, and long-term preservation uncertain. Researchers need efficient ways to share and validate research data while maintaining quality standards.

Solution: Implement GitLab-based research data repositories using ARC (Annotated Research Context) structure with automated validation, large file support via Git LFS, and collaborative access management for efficient research data lifecycle management.

Who Benefits

Primary

  • TRR341 Researchers
    • Standardized data structure
    • Automated data validation
    • Collaborative data sharing
    • Version control for research data
  • Research Data Managers
    • Centralized data oversight
    • Quality assurance automation
    • Compliance monitoring
    • Access control management

Secondary

  • External Collaborators
    • Structured data access
    • Clear data documentation
    • Transparent data provenance
  • Data Visualization Platform
    • Standardized data input
    • Automated data integration
    • Quality-assured datasets

When to Use

  • Multi-institutional research projects
  • Need for standardized data structure
  • Collaborative research data management
  • Requirements for data validation
  • Long-term data preservation needs

When Not to Use

  • Single researcher projects
  • Unstructured exploratory data
  • Projects without collaboration needs
  • Simple data storage requirements

Process

  1. Create research data repository following ARC structure
  2. Upload research data with proper metadata annotation
  3. Automated CI/CD validation of data structure and metadata
  4. Collaborate with team members through GitLab features
  5. Share validated data repositories with stakeholders
  6. Archive completed research data for long-term preservation

Requirements

People

  • Research Scientists
  • Data Managers
  • GitLab Administrator
  • Validation Script Developers

Data Inputs

  • Research datasets
  • Metadata annotations
  • Documentation files
  • Analysis scripts

Tools & Systems

  • GitLab with CI/CD
  • Git LFS for large files
  • ARC validation tools
  • Object storage (S3)
  • Data visualization platform integration

Policies & Compliance

  • Research data management policies
  • GDPR compliance
  • Institutional data governance
  • Scientific data standards

Risks & Mitigations

  • Invalid data structure preventing collaboration

    • Automated validation in CI/CD
    • Template repositories
    • Training on ARC structure
    • Pre-commit validation hooks

  • Large file storage costs and performance

    • Git LFS with object storage
    • Storage quota management
    • Data lifecycle policies
    • Efficient storage backends

  • Loss of research data

    • Git version control
    • Regular backups
    • Multi-location storage
    • Disaster recovery procedures

Getting Started

To implement this use case, you need GitLab with CI/CD, Git LFS support, ARC validation tools, and integration with research data infrastructure.

  1. Set up GitLab instance with ARC template repositories
  2. Configure Git LFS and object storage for large research files
  3. Implement ARC validation scripts in CI/CD pipeline
  4. Train researchers on ARC structure and GitLab workflows
  5. Integrate with institutional data management systems

Resources

FAQ

What is ARC (Annotated Research Context)?

ARC is a standardized structure for research data repositories that includes proper metadata annotation and follows FAIR principles for data management.

How does validation work?

CI/CD pipelines automatically validate data structure and metadata compliance when changes are pushed to the repository.

Can external partners access the data?

Yes, external collaborators can be granted appropriate access levels while maintaining security and compliance requirements.

Glossary

ARC
Annotated Research Context - standardized structure for research data repositories with metadata
FAIR Principles
Findable, Accessible, Interoperable, Reusable - guidelines for research data management
TRR341
Transregio-Sonderforschungsbereich 341 - collaborative research center
FDR
Forschungsdatenrepository - Research Data Repository in German academic context