The Center for Network and Storage Enabled Collaborative Computational Science held its first symposium at the University of Michigan May 18-19, 2017, exploring the themes the Center was founded on. The Center seeks to address the challenges of extracting scientific results collaboratively from large, distributed or diverse data.
The Challenge: 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 those 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 seeking to address:
- 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?
This symposium was intended to bring together those interested in these questions to share experiences and best practices, and to discuss both challenges and possible solutions that enable scientists to work together on “big, distributed or diverse data”.
MORE INFORMATION: Event details and a complete list of speakers and slides are available at: https://indico.