Secure Research Data & Computing


Secure Research Data & Computing

Sensitive, confidential and restricted use data must be secured with care. Assessing whether your data need certain kinds of precautions, and then finding the appropriate secure environment that allows you to perform your research in the most efficient manner can be a challenging task. Our consultants provide front line support for researchers working with sensitive data. We also help researchers work with the Information Security Office to assess and plan for managing highly sensitive data. Contact Research IT consultants ( to connect with our network of experts and to learn more about our services for working with sensitive data. 

Highly Sensitive Compute and Storage

Secure Research Data and Compute (SRDC) platform has been developed for researchers working with highly sensitive (P4) data. This will include high performance computing, computing on virtual machines with desktop environments, and protected storage for both options.

For example, researchers working with protected health information (PHI), other highly sensitive human subjects data, controlled unclassified information (CUI), or other high risk data coming from third parties are strong candidates for SRDC. 

High Performance Computing with Moderately Sensitive Data

Savio, UC Berkeley’s high performance computing cluster may be used for moderately sensitive (P2/P3) data(link is external)(link is external). Savio is suitable for a wide range of research applications, including tightly coupled applications that require a low latency, high bandwidth interconnect, or very fast I/O.

For example, researchers working with de-identified public health or human genetic data are strong candidates for Savio. 

Computing on Virtual Machines with Moderately Sensitive Data

Analytics Environment on Demand (AEoD), a Windows-friendly virtual machine service, may be used for computation over moderately sensitive (P2/P3) data. AEoD is most suitable for researchers needing interactive computing using common software packages (Stata, ArcGIS, RStudio, etc.) in a familiar desktop environment. AEoD virtual machines are scaled to meet computational needs, and are available in different sizes, from 2 - 20 cores, 4 - 256 GB RAM plus performant storage...

For example, researchers performing data analytics or geospatial analysis with moderately sensitive public health information, FERPA(link is external)(link is external) data, or data related to animal research are strong candidates for AEoD.

And, if at this time you are working with open data we can help with publication, sharing, and licensing. Contact Research IT consultants: