CC* Planning: NC Regional Science DMZ

依赖于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，这些复杂的科学dmz的好处已经累积到大型的、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日益扩大的差距，特别是通常资源较少的少数民族服务机构。这也使得以教学为主要任务的小型机构更难扩展现有研究，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或合作。通过杜克大学、北卡罗来纳中央大学、戴维森学院和MCNC（北卡罗来纳的区域研究和教育网络提供商）之间的合作，该项目计划创建一个共享的科学非军事区（sS-DMZ），作为北卡罗来纳研究和教育网络的服务，这样资源较少的机构就不必承担所有的设置和维护成本，而是可以将资源投入到当地的基础设施中。他们的科研人员和对新研究经费的追求。该项目与区域高等教育机构合作，1)建立社区信任和共享管理责任，这是扩大参与sS-DMZ计划所必需的，2)构建构建操作sS-DMZ的技术解决方案的方法。由此产生的提案还将为在美国其他研究和教育网络中建立sSDMZ的可行性提供信息，以降低总体成本，同时增加对大数据科学的访问。该奖项反映了美国国家科学基金会的法定使命，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.