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The Sensitive Data Research Environment (SDRE) project is an initiative at the ¾ÅÐãÖ±²¥ that focuses on developing a secure, scalable, and high-performance digital infrastructure. This platform supports research activities involving sensitive data, including information governed by legislation, regulatory frameworks and contractual obligations, across various academic disciplines.

Why build the SDRE? 

Many U of A researchers work with sensitive information that demands strict confidentiality and robust security. In the past, individual research groups often created separate computer systems to manage this data safely and comply with the regulations of data owners. While these decentralized systems served their immediate purpose, they presented several challenges:

• Duplication of security assessments, governance frameworks, and operational efforts.
• Increased complexity in onboarding and offboarding research projects over time.
• Higher operational costs and management overhead resulting from the accumulation of diverse hardware.

The SDRE, inspired by national Advanced Research Computing (ARC) platforms but with a specialized focus on security and sensitive information, will significantly enhance the university's capacity for this type of research. This well-secured and efficiently managed environment will empower our researchers, giving you the confidence to launch large-scale projects with greater agility. Ultimately, this will accelerate the translation of research into impactful outcomes, all while meeting the increasingly stringent security expectations of research funding agencies. 

Who is the SDRE for?

The SDRE is primarily designed to support sensitive data research projects, but it is also built to be inclusive:

• Researchers with sensitive data: If your research involves data governed by legislation, regulatory frameworks, or contractual obligations, the SDRE provides the secure environment you need. This includes data classified as restricted, confidential, or protected under ¾ÅÐãÖ±²¥ UAPPOL policies, aligning with Government of Canada guidelines on sensitive technology research and national security.
• Researchers with non-sensitive data: Even if your data isn't sensitive, but you could benefit from the SDRE's powerful resources, you'll be able to access the environment. This is contingent on adhering to the requirements that maintain the system's ability to handle data with sensitivities, ensuring full utilization of the system and supporting research initiatives across campus.
• Researchers with contributed systems: The SDRE is capable of hosting additional computing resources that researchers might bring to campus. These contributions effectively expand the system's size, allowing researchers to utilize more resources and share their contributions with others. The types of resources that can be added will be carefully controlled. 

Sensitive data and security measures

The SDRE itself incorporates robust security measures:

• Physical security: Housed in a physically secured data center with strict access controls and monitoring.
• Cybersecurity: Undergoes regular cybersecurity evaluations.
• Data protection: Implements a high-performance storage system to mitigate data loss.
• Comprehensive data governance: A detailed framework is being developed, outlining policies and procedures for managing, handling, and protecting data, including controlled access, usage rules, quality standards, and measures for data security and privacy.

System specifications

The SDRE will be equipped with a fast, future-ready high-performance computing cluster. Specifications built for research using AI and deep learning, inference and visualization, as well as data-driven research projects, will be available.

Data transfer and management

Globus integration is available for the SDRE implementation to facilitate data transfer and sharing. Planning for Globus integration is underway. Instructions on how to deploy and use Globus will be developed as part of the SDRE project.

The system will also have high-speed access, with ongoing investigations into required bandwidth and network optimization between SDRE and other research data storage services. While SDRE focuses on computation with active project data, the Research Data Storage Service (RDSS) is available and a Research Data Management system is in development for data archiving.

Implementation 

Resource allocation

A resource allocation model is a set of parameters that determine who has access to what resources and under what conditions. The Research Technology Steering Committee (RTSC) will set an initial allocation model. As the project progresses, the allocation model will evolve to suit the needs of our researchers. 

SDRE pilot period

IST will work with pilot groups of researchers to refine the SDRE. 

We are seeking researchers whose projects meet the following criteria:

• can be completed in a short period of time (1-5 days).
• has all the necessary components available to begin participating in this testing phase upon application
• It is not, in any way, “critical” or “essential,” as this is part of a testing phase, and so computing resources to complete any portion of the projects used in these environments cannot be guaranteed.
• has people available as part of the project who are already familiar with Linux-based command-line environments and how to use SLURM, a job scheduling software.

Researchers selected to participate in the testing phase will be asked to provide feedback to help refine the SDRE platform before a broad rollout.

To be considered for the pilot period, by 11:59 p.m. on October 1, 2025. IST will contact researchers who meet the eligibility criteria with the next steps. Questions about the pilot or eligibility can be directed to research.support@ualberta.ca.