🟠Newsletter - June 2025

Research Data Management at Universities: Storage Solutions

Research Data Management at Universities: Storage Solutions

Disclaimer The views and thoughts expressed here are my own in my professional capacity as a Data Steward and Research Data Manager. They do not reflect the official opinions or positions of my employer, the Novo Nordisk Foundation Center for Stem Cell Medicine – reNEW.

Introduction

Universities worldwide serve as hubs for cutting-edge research across various disciplines. The data generated through these initiatives is often vast and complex, ranging from social sciences survey data to high-resolution imaging and genomic sequencing in the biomedical sciences.

Proper research data management (RDM) is essential for:

• Ensuring the accuracy and replicability of research findings

• Maintaining data security and integrity

• Supporting accessibility and long-term preservation

• Meeting institutional, legal, and funding compliance requirements

As research projects grow in scale and complexity, universities face mounting challenges in providing sustainable, equitable, and technically robust storage solutions.

The Unique Challenges of University Research Data

Universities must support a highly diverse research environment, each area having unique data management requirements.

Key challenges include:

• Multidisciplinarity

  • Universities must serve many disciplines simultaneously, generating different types, volumes, and data formats.

• Varying Data Lifespans

  • Some datasets are used briefly and discarded, while others—such as longitudinal studies—require preservation for years or decades.

• Collaborative Endeavors

  • Research often involves collaborations across departments, institutions, and countries, demanding reliable, secure, and accessible sharing mechanisms.

• Compliance and Ethical Considerations

  • Storage solutions must adhere to strict ethical and legal standards, especially for sensitive data such as medical research involving human subjects.

Storage Solutions for Research Data Management

To address these challenges, universities typically adopt various storage strategies tailored to academic research needs.

Standard storage solutions include:

On-Premise Storage Systems

• Institutional data centers that offer direct, high-speed access for researchers.

• Especially beneficial for data-intensive analysis that cannot rely on internet connections.

• Greater institutional control over security and compliance.

Cloud Storage Solutions

• Platforms such as AWS S3, Google Cloud Storage, or Microsoft Azure Blob Storage.

• Provide scalability, flexibility, and pay-as-you-go pricing models.

• Enable easy global collaboration and sharing.

Hybrid Solutions

• Combine on-premise and cloud storage to balance flexibility, cost, and security.

• Keep sensitive or high-speed-access data in-house while using cloud capacity for scalable needs.

Data Repositories

• Curated institutional or domain-specific repositories that ensure metadata-rich, discoverable, and shareable data.

• Support compliance with open science mandates and FAIR data principles.

Secure Storage for Sensitive Data

• Systems with advanced encryption, fine-grained access controls, and detailed auditing.

• Necessary for handling personal, clinical, or otherwise highly sensitive data in compliance with data protection laws.

Data Archiving

• Long-term preservation solutions with lower costs and slower retrieval speeds.

• Ideal for data that is infrequently accessed but must be retained for reproducibility, compliance, or future research questions.

Local Challenge: UCPH IT Storage Costs

Important Context Within the University of Copenhagen environment, a recent development has significant implications for RDM planning.

University of Copenhagen (UCPH) IT has begun charging research groups directly for storage. However, their current model provides only tiered "active" storage options without a true Tier 3 cold storage solution for archival needs.

Key concerns include:

• Cost Equity

  • Without a low-cost archival tier, researchers needing to preserve large datasets face high, recurring costs.

  • Shifts infrastructure costs onto individual research projects, potentially creating inequities between groups with different funding levels.

• Lack of Archival Storage

  • Tier 3 cold storage solutions are standard at many institutions for affordable preservation of infrequently accessed data.

  • Without this option, all data is forced into higher-cost active storage tiers, regardless of access frequency.

• Impact on Research Sustainability and Quality

  • Researchers may be forced to delete valuable datasets to manage budgets.

  • Longitudinal studies, reproducibility efforts, and open data commitments are undermined if preservation becomes too expensive.

Recommendations and Considerations

As data generation continues to grow, universities—including UCPH—must prioritize the development of sustainable, equitable, and technically robust storage strategies.

Key recommendations include:

• Develop Tiered Storage Models

  • Include true Tier 3 cold storage solutions with significantly reduced costs for archival data.

  • Align pricing with actual usage and access patterns to support fairness and sustainability.

• Invest in Institutional Infrastructure

  • Treat storage as core research infrastructure requiring shared, strategic, and centrally supported investment.

  • Avoid pushing unpredictable or excessive costs onto individual research groups.

• Enable FAIR and Open Science Practices

  • Ensure storage solutions support metadata standards, access controls, and long-term preservation required for FAIR compliance.

  • Facilitate responsible, secure data sharing in line with open science policies.

• Engage the Research Community

  • Involve researchers in the planning and governance of storage services to ensure solutions meet diverse disciplinary needs.

  • Maintain transparency in cost models, service levels, and planning processes.

The Road Ahead: Building Better RDM Infrastructure

Research data management is not an administrative add-on—it is essential to modern research's integrity, impact, and sustainability.

As universities embrace interdisciplinary, collaborative, and open science practices, storage solutions must evolve to match. By investing in tiered, flexible, and equitable infrastructure, institutions can empower researchers to preserve, share, and leverage data effectively, ethically, and sustainably for the benefit of science and society.