A new wave of technology is shifting the paradigm of research data access, moving beyond simple sharing to a secure, controlled model of ‘data visiting’. This approach, pioneered by projects like RAISE and now evolving with RAISE Suite, promises to unlock a wealth of previously inaccessible data while safeguarding privacy and intellectual property.

For years, researchers have faced a dilemma: the immense value of sharing data versus the legitimate concerns around security, control, and attribution. Simply posting datasets online opens the door to misuse, unauthorized access, and a loss of recognition for the original data creators. This hesitancy has created a significant bottleneck in scientific progress.

The Rise of ‘Data Visiting’

The RAISE project (Research Analysis Identifier SystEm) tackles this challenge head-on with a novel approach: ‘data visiting’. Instead of downloading sensitive datasets, researchers execute their analytical algorithms within a secure, trusted environment hosted by the data provider. This means the data never leaves its original location, maintaining control and compliance with regulations like GDPR.

“It’s a fundamental shift in thinking,” explains Evdokimos Konstantinidis of the Aristotle University of Thessaloniki, coordinating the RAISE project. “We’re not just sharing data; we’re enabling access to data for analysis, while preserving its integrity and the rights of its owners.”

How Does it Work? The Technology Behind the Trust

At the heart of RAISE is a robust technological infrastructure. The platform generates a persistent Research Analysis Identifier (RAID), similar to a DOI, for every data processing step. This creates a complete and auditable trail, ensuring reproducibility, traceability, and accountability. Every interaction with the data is logged, providing a clear record of who accessed what and when.

This system addresses a critical issue in modern research: the ‘reproducibility crisis’. A 2023 study published in Nature highlighted that over 50% of published research findings are difficult or impossible to reproduce. RAISE’s RAID system directly combats this by providing a verifiable record of the entire analytical process.

From RAISE to RAISE Suite: Automating FAIR Data Principles

The success of RAISE has paved the way for RAISE Suite, a new EU-funded project building on its foundations. RAISE Suite aims to automate the creation of FAIR (Findable, Accessible, Interoperable, and Reusable) datasets, a cornerstone of open science.

Currently, making data FAIR is often a manual and time-consuming process. RAISE Suite will introduce machine-actionable data management plans, streamlining the entire data lifecycle – from collection to processing and sharing. This automation will significantly reduce the burden on researchers, allowing them to focus on their core work.

Real-World Applications: Beyond Academia

The implications extend far beyond academic research. Consider the pharmaceutical industry, where patient data is highly sensitive. RAISE-like technologies allow researchers to collaborate on drug discovery without compromising patient privacy. Similarly, in the financial sector, secure data ‘visiting’ can facilitate fraud detection and risk assessment while adhering to strict regulatory requirements.

Early adopters of RAISE services include both public and private organizations, demonstrating the broad appeal of this secure data access model. A spin-off company leveraging RAISE’s blockchain and AI technologies is already emerging, signaling the potential for commercial applications.

Future Trends: The Data Clean Room and Federated Learning

The trend towards secure data access is converging with other emerging technologies. ‘Data clean rooms’ – secure environments where multiple parties can analyze combined datasets without revealing the underlying raw data – are gaining traction. These clean rooms often leverage technologies similar to RAISE, providing a controlled space for collaborative analysis.

Federated learning, another promising approach, takes this a step further. Instead of bringing the data to the algorithm, federated learning brings the algorithm to the data. Models are trained across decentralized datasets, without the need to share the data itself. Combining federated learning with RAISE’s secure execution environment could unlock even greater potential for collaborative research.

FAQ: Secure Data Access Explained

• What is ‘data visiting’? It’s a secure method of accessing data for analysis without downloading it, keeping the data under the control of the provider.
• What is a RAID? A Research Analysis Identifier, a unique identifier that tracks every step of the data processing, ensuring reproducibility.
• Is this approach compliant with GDPR? Yes, by keeping the data within the provider’s infrastructure, it helps organizations meet GDPR requirements.
• Who can benefit from this technology? Researchers, healthcare providers, financial institutions, and any organization dealing with sensitive data.

The future of research data access is not about open access at all costs, but about responsible access. Technologies like RAISE and RAISE Suite are paving the way for a new era of collaboration, innovation, and trust in the world of data.

Want to learn more about EU-funded projects driving innovation? Contact the editorial team to suggest a ‘Project of the Month’.