Translational research has been driven by the increasing amount of heterogeneous data sets collected from medical instruments, sensors, patient diagnosis records, genomic and microbiome samples. The recent advancement in information technology greatly accelerates the innovation in translational research by applying in-depth analysis on these data with large scale computing and storage resources. Clinical researchers now heavily rely on such cyberinfrastructure to understand trends, derive correlations, and/or identify anomalies, which are instrumental to accurate diagnosis, precision drug discovery and effective treatment of diseases. In this context, the security of the patient data, the efficient sharing of data, and the processing of data in a regulation compliant fashion are critical. This project addresses the resource limitations and security aspects of data-driven translational research. The project will greatly speed up clinical research activities that rely heavily on the analysis of sensitive data. The resulting software defined security infrastructure can be applied to a wide range of cyberinfrastructure that carries sensitive data. The project will strengthen the collaboration among computer scientists, clinical researchers, IT managers and provides a rare opportunity to address the cyberinfrastructure challenges in a holistic way instead of an ad hoc, incremental manner.
This project designs and deploys a Security and compliant Cyberinfrastructure for Translational Research (SECTOR) that enables sharing and computing on sensitive data sets between private compute clusters, a shared HPC facility and/or a HIPAA compliant cloud. Specifically, it (1) leverages the emerging software defined infrastructure (SDI), blockchain and secure domain name system to extend the boundary of computing on sensitive and private data. This is the first project to bring the agility and resilience of SDI to clinical research activities; (2) designs a framework that enables the deployment of a new workflows with fine grained user and access control that are compliant with the HIPAA (Health Insurance Portability and Accountability Act of 1996) technical safeguard; (3) enables the migration of data computation using streaming based data redirection and processing, requiring very little effort in porting existing scientific applications; (4) designs a portal that exploits the underlying SDI resources to help various stakeholders to express their workflow and simplify the management of healthcare resources.
Dr. Yan Luo, PI, Professor, Dept of Electrical and Computer Engineering, University of Massachusetts Lowell
Dr. Yu Cao, Co-PI, Associate Professor, Dept of Computer Science, University of Massachusetts Lowell
Dr. Peilong Li, Co-PI, Research Assistant Professor, Dept of Electrical and Computer Engineering, University of Massachusetts Lowell
Dr. Jomol P. Mathew, Co-PI, Associate Chief Information Officer at UMass Medical School
Dr. Silvia Corvera, Co-PI, Endowed Chair for Diabetes Research and Professor of Molecular Medicine at UMass Medical School
Start soon. Sept 2017 – 2020
National Science Foundation, Office of Advanced Cyberinfrastructure (OAC)