Case Study

Rapid Secure Research Environment (RSRE) Implementation

Higher Education

We helped a major higher education institution develop a capability for rapidly establishing cloud-based secure research environments

CLIENT’S CHALLENGE

Virginia Tech is a leading research institution in the United States. Some VT researchers work with datasets that contain varying degrees of sensitivity, from non-sensitive data to data that includes Personally Identifiable Information (“PII”) or Protected Health Information (“PHI”). VT researchers need to work with this data while maintaining appropriate protections of the sensitive elements within it. ​

To provide this capability, VT needs a secure environment where researchers can work with diverse and large data sets, collaborate with others on the research, and store the results safely and securely, often permanently.​

OUR APPROACH

Impact Makers managed an agile development effort at VT to create a secure, cloud-based (AWS) platform to enable researchers to request and deploy their own research workspaces, each with dedicated compute and data storage resources, via an intuitive, web-based UI. In addition to storage and compute, workspaces were provisioned with virtual desktops for each workspace user and a customizable set of data analysis tools.​

The solution included automated monitoring, allowing idle resources to be shut down when not in use and easily restarted on demand.​

SKILLS AND TECHNOLOGIES LEVERAGED

Strategic Development - Requirements Analysis - Infrastructure as Code - Amazon Web Services - Cloud Computing - Big Data - Data Privacy

The Results

We Developed the Research Data Infrastructure solution with essential functionality, tested with early adopters and deployed for use by the Virginia Tech community.​

The solution provided:

  • A usable and productive platform for researchers​
  • Elastic and scalable technical infrastructure​
  • Rapid delivery through agile deployment​
  • Simple, easy way to set up a new virtual research environment that has built-in security based on the data classification.​​
  • Zero tolerance for data loss.​​
  • Ability to collaborate with others during the research phase.​​
  • Ability to use a variety of tools to analyze the data without having to install, set up, acquire licenses, etc., for those tools.​​
  • Ability to archive data, but with the ability to access it at a later time, if needed.​​
  • Integration with external data and systems. ​​
  • Fully masked PII within research data.​​
  • Secure access to data by both internal and external resources.​​
  • Storage that is HIPAA and NIH-compliant.​