Using Data and Community Input to Develop Strategies

10:10 AM - 11:55 AM

Balcony A

The development of strategic R&D priorities can be effectively informed through community input and analysis of data to understand the R&D landscape and identify gaps that must be addressed. How do you best engage with stakeholders to understand their current and future resource needs? How can short and long- term R&D investments be guided by analysis of the S&T enterprise through indicators and metrics? Hear from speakers on their strategies using data and community input to coordinate R&D resource investments.


Capt. Sally Hu,

Defense Health Agency:

will speak on improving R&D outcomes of the Military Medical Enterprise through partnerships and technology transfer.

Jack Kaye,


will discuss the way in which Decadal Surveys issued by the National Academies of Science, Engineering, and Medicine have guided NASA’s Earth Science Division (ESD) in developing its plans and programs, focusing on both the first Decadal Survey for Earth Science, released in 2007, as well as the more recent one from later 2017. The ways in which ESD responded to these two very different surveys will be reviewed.

[presenter materials]

Nigel Mouncey,


will discuss stewardship of the Joint Genome Institute (JGI), a US Department of Energy User Facility. He will discuss the approaches the JGI uses to obtain user input and scientific guidance to inform JGI’s strategy and resource plan to ensure JGI remains relevant and valuable to the scientific community.

[presenter materials]

John Veysey,

National Science Board:

will discuss Science and Engineering Indicators (SEI) and how the National Science Board uses it to inform policy-making. He will discuss plans for the forthcoming SEI 2020 report, which will be redesigned to be more useful and responsive to policy-makers.

[presenter materials]

Discussion Questions:

  • How do you and the community deal with situations when the budget assumptions made in the development of “community-based plans” don’t correspond to the ultimate reality?
  • In planning and coordination, how do you balance those things that are more definite (in terms of specificity and concentration in implementation) vs. more diffuse (especially competitive research programs that are spread among large numbers of principal investigators and institutions, and the nature of who is engaged is not obvious ahead of time)?
  • How could planning methods discussed be applicable to S&T domains that historically have not used these methods? What are the benefits? How do you manage public and non-public discourse and information in planning and coordination activities?
  • What are opportunities to better connect S&T Enterprise planning and coordination of resources across S&T domains and capabilities?