The Open Storage Network will enable researchers to manage big data more efficiently than ever before.
The South Big Data Hub announced it has been selected as one of four regional big data hubs to be awarded $1.8 million grant from the National Science Foundation for the development of a data storage network to take place over the next two years.
A collaborative team will be put together and combine their expertise and resources to develop the Open Storage Network. The network will allow academics from across the country to work with each other and share their data quickly and easily.
The project is being led by Alex Szalay of Johns Hopkins University and with the assistance of data storage partners across the United States including the National Data Service and members representing each of the four NSF-funded Big Data Regional Innovation Hubs (BD Hubs): the South Big Data Hub at the Renaissance Computing Institute (RENCI) and the Georgia Institute of Technology, the West Big Data Hub at the San Diego Supercomputer Center (SDSC), the Midwest Big Data Hub at the National Center for Supercomputer Applications (NCSA), and the Northeast Big Data Hub at the Massachusetts Green High Performance Computing Center (MGHPCC) and Pittsburgh Supercomputing Center (PSC).
“There are hundreds of issues to solve before we have a “datanet” as efficient and cooperatively well organized as the internet,” Christine Kirkpatrick, executive director of the National Data Service and co-chair of the Big Data Hubs’ Data Sharing and Cyberinfrastructure Working Group said. “But just as there are many complexities to solve in the long-term, these solutions can be facilitated by the simplest of additions – here the establishment of a connected storage network. Sharing, reproducibility, replication, and data management all fundamentally rely on a place to store data.”
The data transfer systems for the new network are designed to match the speed of a 100-gigabit connection while being low-cost, large capacity and high bandwidth while utilizing a small number of nodes.