CC* Data Storage: Supporting Big-Data Edge Computing using Hybrid and Cloud-Native Storage Infrastructure

The University of Washington (UW) Information Technology (UW-IT) and the Office of Vice Provost for Research are supported by a Campus Cyberinfrastructure (CC*) award to create a novel central data storage, curation, and sharing platform. The core tenant of this research ecosystem is the development of a scalable, elastic, low-latency data storage framework supporting a wide range of interdisciplinary research, bolstered by advanced high-throughput data science tools, an open-source high-performance data management system, and the expertise of professional storage cyberinfrastructure engineers.

The new cyberinfrastructure empowers researchers to perform scalable, data-intensive analysis across disciplinary and institutional boundaries to inform new discoveries, including materials, particle physics, environmental, medical, and health sciences. The project develops a broad range of data science training programs to provide interdisciplinary research experiences to the trainees and supports data science education and research at partner minority-serving institutions, preparing them for diverse education leadership roles, and simultaneously inspiring enthusiasm for big-data sciences in the broader community.

The project identifies and removes data storage bottlenecks that are common across scientific domains and develops a modern data storage cyberinfrastructure that scales scientific analyses to thousands of processors and petabytes of data locally as well as on top of existing national NSF cyberinfrastructure, while maintaining seamless synchronization with commercial cloud-based storage. The deployment of the 9.6 PB usable new storage infrastructure advances all big data research disciplines by providing scalable low-latency data access and egress across all three local UW campuses (Seattle, Bothell, Tacoma).

The new data storage ecosystem facilitates a research paradigm shift by (1) advancing the development of high-throughput data analytics; (2) encouraging collaborative big-data research through a common data landing path; (3) providing a highly secure yet permissive data management plan, to allow compliant use with regulated research data; and (4) supporting convergent science by bringing together substantially different science and engineering disciplines.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.