The Center for Network and Storage-Enabled Collaborative Computational Science seeks to address the challenges of extracting scientific results collaboratively from large, distributed or diverse data.
Many scientific disciplines are rapidly increasing the size, variety and complexity of data they must work with. As the data grows, scientists are challenged to manage, share and analyze that data and become diverted from a focus on their scientific research to data-access and data-management concerns. Even more problematic is determining how to support many scientists sharing and accessing this ever increasing amount of data.
The Center is working to respond to those challenges broadly. Included in the Center is the NSF-funded OSiRIS project, a collaborative, multi-university venture led by MICDE faculty, and hosted by ARC-TS. The following questions illustrate some of the focus areas the Center is exploring:
- What are the best practices for collaboratively working on large, potentially diverse or distributed, datasets?
- What tools, technologies and techniques are most effective at addressing the challenges faced by such researchers?
- How should data best be stored, organized, indexed and made accessible to improve the ability of scientists to jointly work with one another, especially across the dimensions of time and space?
The Center supports its members and the broader scientific community in sharing expertise, knowledge and practical methods that can better enable scientific discovery for groups of scientists working together on “big, distributed or diverse data”.