CC* Planning: NC Regional Science DMZ

依赖大数据和大数据传输的科学方法需要独特的网络基础设施，称为科学DMZ，以支持快速简便的数据传输和数据访问。通常情况下，这些复杂的科学DMZ的好处已经累积到大型，资源充足的“研究密集型”机构，这加剧了大型和小型机构之间已经越来越大的差距，特别是往往资源较少的少数服务机构。这也使得那些以教学使命为主的小型机构更难扩大现有的研究，让学生接触科学方法或合作，包括那些可能依赖大数据的方法。通过杜克大学、北卡罗来纳州中央大学、戴维森学院和MCNC之间的合作，（NC的区域研究和教育网络提供商），该项目计划创建一个共享的科学DMZ（sS-DMZ），作为北卡罗来纳州研究和教育网络的一项服务，以便较小的-资源充足的机构不必承担所有的设立和维持费用，而是可以将其资源用于当地的基础设施、科学研究人员和争取新的研究赠款。该项目与区域高等教育机构合作，1）建立社区信任和共同的治理责任，以扩大参与sS DMZ计划，2）设计方法来构建操作sS-DMZ的技术解决方案。由此产生的建议也将告知在美国其他研究和教育网络中建立sSDMZ的可行性，作为一种降低总体成本的方法，同时增加对大数据科学的访问。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Scientific approaches relying on big data and on large data transfers require unique cyberinfrastructure, called Science DMZs, to support fast and easy data transfers and access of data. Typically, the benefits of these complicated Science DMZs have accrued to large, well-resourced “Research-Intensive” institutions, which compounds an already growing disparity between large and small institutions, especially often-lesser-resourced minority serving institutions. This also makes it much more difficult for smaller institutions with a primarily instructional mission to expand existing research and expose students to scientific approaches or collaborations, including those that may rely on big data.Through a partnership between Duke University, North Carolina Central University, Davidson College, and MCNC (NC’s regional research and education network provider), this project plans the creation of a shared Science DMZ (sS-DMZ) as a service of the North Carolina Research and Education Network so that lesser-resourced institutions do not have to bear all setup and maintenance costs and can instead commit their resources to local infrastructure, their scientific researchers and pursuit of new research grants. This project works with regional higher-ed institutions to 1) establish community trust and shared governance responsibility necessary to expand participation in a sS DMZ program and 2) architect the approach to build the technical solution of operating a sS-DMZ. The resulting proposal will also inform the feasibility of a sSDMZ in other Research and Education Networks in the United States as an approach to reduce overall costs while increasing access to Big Data science.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.