Call for White Papers on Data Science Curriculum for Public Service

May 22, 2019
Data Science Call for White Papers

A Call for White Papers on Data Science Curriculum for Public Service

The Best Submissions Will Receive $10,000.

  • Letters of intent due June 15, 2019
  • Two-page proposal submissions due June 30, 2019
  • Finalists selection on July 15, 2019
  • White paper submissions due September 15, 2019  

Data have transformed the way in which Americans work and play – but there are still huge deficiencies in the way in which American government uses data to make decisions.  We need your ideas about how to improve the way in which public policy professionals are trained – and will award three $10,000 prizes for the best white papers.  Our goal is to build the basis for evidence-based policy both by developing data science curricula that improve the competence of public service professionals to make use of their own data to solve public problems and by identifying the technical ways to do so.  

If you are interested in writing a white paper on one of the three following topics please submit a two page summary of your proposed approach to DataScience@naspaa.org  by June 30, 2019 in one or more of the following areas:

1.  What are the elements of successful approaches for establishing and maintaining a secure facility to access confidential government data? 

2. What are the elements of successful curricula or pedagogical models that both develop capacity to solve public policy problems and leave explicit space for local experimentation and modification?

3. How should success be evaluated? What are the elements of an evidence-based paradigm for assessing the value of technical and curricular approaches?

Finalists will be selected by July 15, 2019, and asked to develop a white paper of 3,000-5,000 words by September 15, 2019.   Each white paper should sketch a design, briefly summarize existing examples or prototypes and provide a list of questions for further discussion.    The white papers will be highlighted at the NASPAA national meetings in October, and provide a basis for developing a national approach.

Please email us at DataScience@naspaa.org if you have any questions.

This work is generously supported by Overdeck Family Foundation and Schmidt Futures.

 

Context

There is a new opportunity to change the way in which evidence can inform policy.  There is widespread interest across the federal government in using data for evidence.  The U.S. government established a Commission on Evidence-Based Policy making(1), established a secure research facility(2), launched a Federal Data Strategy(3) and passed the Foundations for Evidence-Based Policymaking Act of 2018(4).   State and local government agencies, and their professional associations, are both leading and participating in new programs. New data science programs are being designed for graduate and undergraduate students(5, 6). Public policy schools are also interested in building data science capacity into their curricula through establishing data science tracks in their master’s programs that could also serve as stand-alone certificates. Philanthropic foundations have supported a variety of successful pilots that can be used to inform the design of more sustained and scalable investments.

While these existing efforts are promising, they lack an overarching institutional structure that will ensure that training is disseminated broadly across the country, and that both professionals in the public sector and new entrants have appropriate skills and a shared familiarity with key structures. 

We hope the white papers will provide new ideas to design a data analytics curriculum that can build on recent successes, develop a sustainability model, and produce products that have demonstrable value to stakeholders.  The stand-alone white papers should lay out the key competencies that should be incorporated in a data science for public policy certificate or track, and to build an institutional structure across the country that could disseminate this training.

View NASPAA Webinar Slide Deck with NYU (May 8, 2019)

References

1.           Commission on Evidence-based Policy, “The Promise of Evidence-Based Policymaking” (Washington DC, 2017), (available at www.cep.gov).

2.           Government Computer News Staff, Data mashups at government scale: The Census Bureau ADRF. GCN Mag. (2018).

3.           Office of Management and Budget, Federal Data Strategy (2019), (available at https://strategy.data.gov).

4.           N. Hart, T. Shaw, Congress Provides New Foundation for Evidence-Based Policymaking (2018), (available at https://bipartisanpolicy.org/blog/congress-provides-new-foundation-for-…).

5.           E. National Academies of Sciences  and Medicine, Envisioning the Data Science Discipline: The Undergraduate Perspective: Interim Report (The National Academies Press, Washington, DC, 2018; https://www.nap.edu/catalog/24886/envisioning-the-data-science-discipli…).

6.           National Research Council, Training Students to Extract Value from Big Data: Summary of a Workshop (The National Academies Press, Washington, DC, 2015; https://www.nap.edu/catalog/18981/training-students-to-extract-value-fr…).

7.           National Association of State Workforce Agencies, “Evidence-Building Capacity in State Workforce Agencies” (2017).