Workshop: Taking Data Science to America's Emerging Workforce

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.