Workshop: Taking Data Science to America's Emerging Workforce

本次研讨会将探索创新方法，通过利用土地赠与机构及其合作推广系统的网络，为全国数据科学劳动力的发展做出贡献。数据科学在社会各个领域（包括商业、政府、教育和研究）的快速增长和重要性，将改变就业的未来。这种转变将创造一个不断变化的工作组合，要求各级求职者获得新的技能，这将是参与这个新的工作世界所必不可少的。技能差距将在那些尚未随时获得教育和其他相关社区资源的社会阶层中最为明显-特别是在美国各地的农村地区和小城镇。研讨会将研究是否可以利用，扩大和/或增强现有的土地出让机构结构，特别是农村地区和小城镇的土地出让机构，以提供数据科学教育和培训，从而获得高薪工作，这些工作可能是本地的或远程访问的。虽然数据科学是一个可能提供许多新就业机会的领域，但它要求劳动力在适当的领域接受良好的培训，以充分利用这些机会。 将数据科学带到美国新兴劳动力研讨会将汇集来自广泛背景和广泛组织的个人-横跨学术界，工业界，政府和土地赠与系统。它将应对挑战，探索机遇，制定建议，并提出在全国范围内建立数据科学实践社区的具体后续步骤。该讲习班得到了计算机和信息科学与工程局、教育和人力资源局本科教育司、以及美国国家科学基金会数学和物理科学理事会（MPS/DMS）数学科学部。本次研讨会讨论了两个紧迫的问题，（1）增加美国数据科学专业人员的队伍，（2）将新兴的数据科学领域及其所代表的职业机会带到农村地区。该研讨会将解决一些问题，包括：-扩大土地赠与机构的合作推广系统的任务和范围，以包括数据科学教育，研究和应用;利用该系统将数据科学革命的好处分布在我们社会的全部范围内;解决任何学术和校园协调挑战，以及联邦，州，县一级的问题。- 合作扩展系统的发展，以适应数据科学教育，培训，研究和应用。资助新的努力将涉及哪些内容;需要解决哪些治理问题，以及未来的想法或模型，包括将数据科学教育工作与相关领域的校园研究联系起来;-可以为数据科学和数据分析部署的基础广泛的教育计划类型。是否有结合学士学位，2年制学位（社区学院），和合作推广认证的方法，应该探索？教育新一代进入劳动力市场的数据科学家，而不是重新培训被现代技术取代的工人？- 鼓励和促进在当地社区进行咨询和签订合同的自营职业办法;- 利用国家在数据科学教育，数据科学研究和远程教育方面的努力，包括联邦机构，州一级计划，非政府组织和私人基金会的努力，NSF大数据中心，和其他NSF劳动力发展计划;-制定国家战略和计划的下一步，以扩大合作推广系统的任务和范围，包括数据科学及其应用。谁需要参与？应如何协调和利用这些努力？该奖项反映了NSF的法定使命，并被认为是值得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的支持。

This workshop will explore innovative approaches for contributing to the development of a data science workforce across the country by leveraging the network of Land-grant Institutions and their Cooperative Extension System. The rapid growth and importance of data science in all sectors of society--across business, government, education, and research--is poised to transform the future of jobs. This transformation will create a changing mix of jobs, requiring job seekers at every level to acquire new skills that will be essential for participating in this new world of jobs. The skills gap will be most pronounced in those segments of society that do not already have ready access to educational and other associated community resources--especially in rural areas and small towns across America. The workshop will examine whether the existing land grant institution structure can be leveraged, augmented, and/or enhanced to provide, especially those in rural areas and small towns, access to data science education and training and, consequently, access to the well-paying jobs that could follow, which may be locally-based or remotely accessible. While data science is a field that can potentially deliver many new job opportunities, it requires that the workforce to be well-trained in the appropriate areas to make best use of such opportunities. The Taking Data Science to America's Emerging Workforce workshop will bring together individuals from a broad range of backgrounds and a broad range of organizations--across academia, industry, government, and the land-grant system. It will address challenges, explore opportunities, develop recommendations, and propose concrete next steps for establishing data science communities of practice across the nation. The workshop is supported by the Computer and Information Science and Engineering Directorate (CISE); the Division of Undergraduate Education of the Education and Human Resources Directorate (EHR/DUE); and, the Division of Mathematical Science of the Mathematical and Physical Sciences Directorate (MPS/DMS) of the National Science Foundation.This workshop addresses two pressing issues, (1) increasing the ranks of data science professionals in the US, and (2) taking the newly emerged field of data science, and the career opportunities that it represents, to the rural sector. The workshop will address a number of issues including:--Broadening the mandate and reach of the Cooperative Extension System of land-grant institutions to include data science education, research, and applications; utilizing this system to distribute the benefits of the data science revolution across the full reach of our society; addressing any academic and campus coordination challenges, and issues at the federal, state, county levels in doing so. --Evolution of the Cooperative Extension System to accommodate data science education, training, research, and applications. What would be involved in funding new efforts; what governance concerns would need to be addressed and what are ideas or models for the future, including linking data science education efforts to campus research in related areas;--The types of broad-based education programs that could be deployed for data science and data analytics. Are there combinations of Bachelor's, 2-year degree (Community Colleges), and Cooperative Extension certification approaches that should be explored? --Educating a new generation of data scientists entering the workforce versus retraining workers who are being displaced by modern technologies?--Establishing local communities of interest with linkages across wide geographic areas;--Encouraging and facilitating self-employment approaches to consulting and contracting in local communities;--Leveraging national efforts in data science education, data science research, and distance education, including efforts at federal agencies, state-level programs, non-governmental organizations, and private foundations, the NSF Big Data Hubs, and other NSF workforce development programs;--Developing next steps in a national strategy and plan to broaden the mandate and reach of the Cooperative Extension system to include data science and its applications. Who needs to be involved? How should these efforts be coordinated and leveraged?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.