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NSF Supports Development of New Nationwide Data Storage Network

By National Science Foundation | June 11, 2018

Alex Szalay, professor of astronomy and computer science at Johns Hopkins University (JHU), leads the Big Data revolution at the university as the director of the Institute for Data Intensive Engineering and Science. He is shown in the Data-Scope, a resource for computationally-intensive computing at JHU. (Credit: Johns Hopkins University)

The National Science Foundation (NSF) is announcing a $1.8 million grant for the initial development of a data storage network over the next two years. A collaborative team will combine their expertise, facilities and research challenges to develop the Open Storage Network (OSN). OSN will enable academic researchers across the nation to work with and share their data more efficiently than ever before.

“We are excited to support OSN to help meet the needs of researchers in today’s era of data-driven discovery and innovation,” said Erwin Gianchandani, acting assistant director of the Computer and Information Science and Engineering Directorate at NSF. “The OSN team and their supporting collaborators will build a community to multiply the impact of previous and current NSF investments and anchor comprehensive data infrastructure that will be vital to the future of our nation’s scientific and engineering enterprise.”

The project, led by Alex Szalay of Johns Hopkins University, leverages key data storage partners throughout the U.S. These partners include the National Data Service and members representing each of the four NSF-funded Big Data Regional Innovation Hubs (BD Hubs): the West BD Hub at the San Diego Supercomputer Center (SDSC), the Midwest BD Hub at the National Center for Supercomputer Applications (NCSA), the Southern BD Hub at the Renaissance Computing Institute (RENCI), and the Northeast BD Hub at the Massachusetts Green High Performance Computing Center (MGHPCC) and Pittsburgh Supercomputing Center (PSC).

NSF’s investment in OSN builds on a seed grant by Schmidt Futures — a philanthropic initiative founded by former Google Chairman Eric Schmidt –to enable the data transfer systems for the new network. These systems are designed to be low-cost, high-throughput, large-capacity, and capable of matching the speed of a 100-gigabit network connection with only a small number of nodes. This configuration will help to ensure that OSN can eventually be deployed in many universities across the U.S. to leverage prior investments and establish sustainable management for the overall storage network.

“We are excited to support Professor Szalay’s promising work designing and testing these impressive storage devices, and want many such open-design petabyte units to be assembled and deployed in and for universities,” said Stuart Feldman, chief scientist at Schmidt Futures. “We applaud NSF’s investment in the Open Storage Network as a key step toward enabling research requiring truly massive amounts of data.”

OSN builds on NSF’s longstanding leadership and investments in data science. The new storage network aligns with one of the 10 Big Ideas for Future NSF Investments Harnessing the Data Revolution (HDR). HDR offers a profound opportunity to use data to transform and advance discovery and innovation across all fields of science and engineering. In particular, OSN will help address the HDR goals to build data infrastructure for research and advance fundamental data-centric research and data-driven domain discoveries.

The user experience is an important component of OSN. The new storage network will be piloted by researchers at participating institutions to ensure that it is easy to use, has adequate performance, can be efficiently accessed from various parts of the internet, employs good security and privacy policies, is highly reliable, and has a long duration for data preservation. Additional software and service layers will be added to OSN as it is developed. NSF is also funding a project led by Ian Foster at the University of Chicago to explore the use of Globus services, which are already widely used for data management with OSN.

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