RENCI Named as Collaborating Institution for $3 Million Cyberinfrastructure Center of Excellence Pilot

Project will create a model for advising NSF’s largest scientific facilities

The National Science Foundation today named the Renaissance Computing Institute (RENCI) of the University of North Carolina at Chapel Hill as a collaborating institution on a $3 million pilot project to create a model and strategic plan for a Cyberinfrastructure Center of Excellence (CI CoE). The goal of the effort is to establish a reservoir of expertise on best cyberinfrastructure practices for the nation’s largest research facilities.

NSF supports more than 20 large facilities devoted to advancing research in a range of scientific domains, from the far reaches of the universe to the intricacies of Earth’s ecosystems. These facilities, which include telescopes, research vessels and other large research assets funded under the Major Research Equipment and Facilities Construction portion of the NSF budget, can cost hundreds of millions of dollars, take a decade or more to build and typically operate for many years.

Designed to collect and analyze enormous amounts of data, these facilities are often at the leading edge of scientific and computing infrastructure. The new pilot project aims to create a central body for advising large facilities on cyberinfrastructure needs and tools.  

“In the past, each large facility has built its own cyberinfrastructure backbone,” said RENCI research scientist Anirban Mandal, who will serve as co-Principal Investigator on the pilot. “In doing so, they have acquired a significant amount of expertise, but what has been missed is an opportunity to share their experiences, solutions and innovations with other large facilities. This pilot addresses that problem by forming a strategic plan and model for an exchange platform and a knowledge base for large facility cyberinfrastructure, both for existing facilities and new ones to come.”

The $3 million award is supported by NSF’s Office of Advanced Cyberinfrastructure and will be distributed over two years. The University of Southern California will serve as lead institution with Ewa Deelman, Research Director and Research Professor at USC’s Information Sciences Institute, serving as Principal Investigator. Collaborating institutions include RENCI, the University of Utah, Indiana University and the University of Notre Dame. RENCI will receive $440,000 for its contributions to the project from 2018-2020.

The project aims to create a repository for lessons learned and current tools relevant to data management systems, data processing facilities, software tools and other elements of the cyberinfrastructure systems that support large science facilities. It will also provide a forum for discussion among large facility personnel and the broader academic community, as well as address training and workforce development needs to help large facility planners and operators cultivate their in-house expertise.

“RENCI’s role is focused on the cyberinfrastructure side of things,” said Mandal. “We will first gain knowledge about what infrastructures are out there in existing facilities, then look at how we can build templates for future facilities and give consultation and advice on what has, or has not, worked well in the past.”

Collaborators will focus on developing a model for the CI CoE during the first year and implement a pilot for CI CoE in the second year. They will use the National Ecological Observatory Network, which collects data for insights on changes in U.S. ecosystems, as a test case for initial information gathering before broadening the effort to encompass other large facilities in a potential future CI CoE.

“The expertise built using the CI CoE pilot will be applicable to a host of NSF projects that include distributed cyberinfrastructure,” said Mandal. “Its broader impact comes from all the scientists who depend on this cyberinfrastructure; if you make the cyberinfrastructure better for these large facilities, it will help the scientists to do their work more effectively.”