NSF Awards: Two $1 Million Grants to Support Data-Intensive Scientific Research

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Projects aim to improve scientific productivity and protect data from inadvertent errors

 

Lead by the Renaissance Computing Institute (RENCI) of the University of North Carolina at Chapel Hill, two new $1 million awards from the National Science Foundation aim to help researchers take advantage of the latest advances in data science, networking and computation while protecting the integrity of their scientific work:

 

This week NSF announced an award of $999,575 over three years to support Integrity Introspection for Scientific Workflows (IRIS), a project to develop a seamless system to uncover unintentional data errors. While previous work has focused on catching malicious hackers or software bugs, IRIS will be the first to specifically address the detection of unintentional—and often unseen—errors that can be introduced when working with big data. Collaborators include Anirban Mandal (RENCI research scientist, the project’s Principal Investigator), Von Welch at Indiana University Center for Applied Cybersecurity Research and Ewa Deelman of University of Southern California Information Sciences Institute’s Science Automation Technologies.

 

The second project, Delivering a Dynamic Network-centric Platform for Data-driven Science (DyNamo), also uses Pegasus as a platform. In this case, the aim is to help scientists take better advantage of available resources and high performance networks for working with large data sets scattered in facilities around the country. The project, announced in July, provides a total of $1 million over two years. Anirban Mandal is the Principal Investigator. Co-Principal Investigators include Ewa Deelman of the University of Southern California, Michael Zink of the University of Massachusetts at Amherst, Cong Wang of RENCI, and Ivan Rodero of Rutgers.

 

 

Read the Full Press Release

 

Source: RENCI News

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