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Science Engagement

 

 

 

 

 

 

 

 

 

 

 

 

 

The ESnet Science Engagement team's mission is to ensure that science collaborations at every scale, in every domain, have the information and tools they need to achieve maximum benefit from global networks through the creation of scalable, community-driven strategies and approaches. Our team endeavors to make sure scientific progress is completely unconstrained by the physical location of instruments, people, computational resources, or data.  

Our Motivation

The Department of Energy Office of Science together with several other government agencies like the National Science Foundation (NSF) invest over $10B annually to support transformational research and operate world-class facilities throughout the United States.  Computer networks are the essential “circulatory system” for this investment.  The importance of networking increases every year, due to the revolution in experimental instruments and increased computational output that is transforming many scientific disciplines.

DOE and the NSF have made significant investments in network capabilities, campus architectures, and critical software to support and accelerate data-intensive science workflows.  NSF’s visionary CC-NIE program has been a milestone in this regard.  Today, a small number of large collaborations (for example, tthose associated with the Large Hadron Collider) are adept at exploiting networks in the service of discovery. However, the majority of scientific collaborations still struggle with using these resources.  The resulting “capability gap” represents a significant and unnecessary drain on the productivity of US science. 

In response to this challenge, ESnet created the Science Engagement Team, charged with assuring that collaborations can maximize their use of global networks to accelerate science discovery.

The work of this team cannot be fully successful without partners at the national and global scale. This is because 80% of data flows on the ESnet network terminate at a university or facility outside the DOE complex.  This pattern is likely the result of DOE and NSF funding models, which enable thousands of university-based scientists to use DOE facilities (beamlines, genome sequencers, supercomputers) for their research.  

Our Approach

Since 2007, ESnet has actively engaged the various science communities it serves through a formal requirements review process. The process has ensured that ESnet’s capacity, capabilities, and services can support the increased data demands of science over time. Building on the success of the requirements program, ESnet's Science Engagement Strategy has three pillars:  

Partnerships:  ESnet is building partnerships on two fronts.  First, we are working with complementary  providers that “complete” the end-to-end workflow picture. These include: partner networks such as Internet2, regional networks, campus networks, and international networks and software providers like Globus, which provides user-friendly data transfer and data sharing tools for scientists.  Second, ESnet is partnering with organizations that can help scale our efforts and maximize impact.

Education/Consulting:  ESnet is working both with its partner organizations and directly with science collaborations to deliver educational and training opportunities through workshops and webinars, as well as 1:1 consulting for data mobility strategies including Science DMZ, perfSONAR and DTN deployments. 

Knowledgebase: ESnet is developing new communications tools (website, handouts, etc) that are geared towards scientists and non-network experts who rely on networks. ESnet also actively manages, updates and  

How can we help?

Our team has significant experience in working with science collaborations to develop proactive solutions to data mobility issues.  If you are interested in speaking with one of our network engineering experts to discuss your challenges, please contact our team at   .

 

Collaborations at every scale, in every domain, will have the information and tools they need to achieve maximum benefit from global networks through the creation of SCALABLE, community-driven strategies and approaches.
Scientific progress is completely unconstrained by the physical location of instruments, people, computational resources, or data.  

 

 

 

 

 

 

 

 

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