HDR DSC: Collaborative Research: Connecting the Dots

对精通数据科学和分析的劳动力的需求很大。雇主希望毕业生能够（1）理解，解释和分析数据，（2）有效地传达数据分析的结果，（3）实践数据的道德使用，以及（4）应用数据科学概念解决与现实世界相关的实际问题。来自求职网站的数据显示，纽约州的需求尤其尖锐。2018年，美国国家科学、工程和医学院发布了一份题为《本科生数据科学：机遇和选择》的报告，呼吁各机构提高毕业生的“数据敏锐度”。虽然数据科学能力的传播在一些学科中得到了强调（例如，计算机科学），但向大学毕业生广泛传授这些技能的工作进展缓慢。该项目的目的是开发和实施一个可扩展的创新计划，称为“连接点”，为攻读本科工程学位的学生提供数据科学能力。连接点（CTD）是纽约州立大学（SUNY）系统的旗舰学校之间的高度合作项目，美国最大的高等教育系统，和纽约城市大学（CUNY）系统。CTD团队的大学在布法罗（UB）与纽约城市学院（CCNY）的目标是（a）加强理解和有效地使用数据的能力，通知来自不同的本科生跨工程学科的决策，同时（B）同时提高区域社区合作伙伴的能力，将数据分析方法纳入其业务或战略规划目标。CTD项目团队将创建的标志性学术数据科学轨道是一个本科证书课程，即纽约数据科学学者计划，该计划可以轻松与任何工程专业集成，并补充本科和研究生级别的现有计算机科学专业。通过新颖的数据科学社区实验室为广泛的社区合作伙伴提供服务，这些实验室作为UB和CCNY校园的“弹出式”夏季设施，学生为社区合作伙伴执行实习项目，这些社区合作伙伴有挑战性的数据科学问题供学生解决，但无法很好地主持传统的实习生。该团队的最终扩展目标是开发一个易于被其他SUNY和CCNY校园采用的程序，这些校园举办4年制工程课程，并在纽约州以外的校园提供类似的学位课程结构。NSF的利用数据革命数据科学团计划专注于在地方，州，国家和国际层面建设利用数据革命的能力，以帮助释放数据的力量，为科学和社会服务。该计划中的项目由NSF的利用数据革命大想法;信息和智能系统部计算机和信息科学与工程局;本科教育部教育和人力资源局;数学科学部数学和物理科学局;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。

There is significant demand for a workforce that is proficient in data science and analytics. Employers seek graduates with an ability to (1) understand, interpret, and analyze data, (2) effectively communicate results that stem from the analysis of data, (3) practice the ethical use of data, and (4) apply data science concepts to solve practical problems with real-world relevance. Data from job search sites indicate that the demand in New York State is particularly acute. A 2018 report from the National Academies of Sciences, Engineering, and Medicine entitled "Data Science for Undergraduates: Opportunities and Options" calls for institutions to advance the so-called "data acumen" of graduates. While the dissemination of data science competencies has been emphasized in some disciplines (e.g., computer science), the broad delivery of these skills to college graduates has been slow to evolve. The aim of this project is to develop and implement a scalable, innovative program, termed "Connecting the Dots", for delivery of data science competencies to students pursuing an undergraduate engineering degree.Connecting the Dots (CTD) is a highly collaborative project between the flagships schools in the State University of New York (SUNY) system, the largest higher education system in the nation, and the City University of New York (CUNY) system. CTD teams the University at Buffalo (UB) with the City College of New York (CCNY) with the goals to (a) strengthen the ability to understand and use data effectively to inform decisions among diverse undergraduate students from across the engineering disciplines, while (b) simultaneously increasing the capacity of regional community partners to incorporate data analytical methods into their business or strategic planning objectives. The signature academic data science track to be created by the CTD project team is an undergraduate certificate program, the New York Data Science Scholars program, that is readily integrated with any engineering major and that complements existing computer science majors at both the undergraduate and graduate level. A broad range of community partners are served via novel Data Science Community Labs, which act as "pop-up" summer facilities on the UB and CCNY campuses wherein students perform internship projects for community partners who have challenging data science problems for students to work on, but are not well-positioned to host a conventional intern. The team's ultimate scaling objective is to develop a program that is easily adopted by other SUNY and CCNY campuses that host 4-year engineering programs and by campuses outside of New York State with similar degree program structures. NSF's Harnessing the Data Revolution Data Science Corps program focuses on building capacity for harnessing the data revolution at the local, state, national, and international levels to help unleash the power of data in the service of science and society. Projects in this program are being jointly funded by the NSF's Harnessing the Data Revolution Big Idea; the Directorate for Computer and Information Science and Engineering, Division of Information and Intelligent Systems; the Directorate for Education and Human Resources, Division of Undergraduate Education; the Directorate for Mathematical and Physical Sciences, Division of Mathematical Sciences; and the Directorate for Social, Behavioral and Economic Sciences, Office of Multidisciplinary Activities and Division of Behavioral and Cognitive Sciences.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.