Project Name:

Federated Data Usage Platform

Contractor: NORC at the University of Chicago

Lessons Learned

The expectation is the DUP will operate as a shared service. Therefore, to guide critical design decisions and recommendations, it is important to have early discussions. Receiving early guidance and feedback ensures efficient and productive dashboard development.

Feedback from the federal user interviews indicate that many potential platform users are interested in learning more about individual data users, their needs, and how they use agency-level data. This information is critical in platform development.

Based on our completed interviews to date with federal agencies (both statistical and non-statistical), NORC has compiled the following lessons learned for the period April – June 2024:

  1. While usage metrics and data sources vary across federal agencies, almost all agencies rely on data usage measures to inform decision-making.
  2. Many agencies expressed a desire for cross-agency collaboration to expand research initiatives and potentially combine data products.
  3. Agencies expressed a need for a DUP to account for diverse needs which vary by agency and agency type as well as diverse audiences which may be served by a data usage platform.
  • Non-federal interview participants expressed that a useful feature of the data usage platform is to orient users to relevant data based on topics of interest. Many non-federal interview participants were interested in viewing data by topic rather than by agency.
  • Academic researchers and students were interested in citation trends within academic publications, while non-academic researchers and other non-federal interview participants were not interested in publication data.
  • Data journalists noted an interest in using a data usage platform to explore how data have been used and who has used specific data products in their publications to generate ideas for additional reporting.

Disclaimer: America’s DataHub Consortium (ADC), a public-private partnership, implements research opportunities that support the strategic objectives of the National Center for Science and Engineering Statistics (NCSES) within the U.S. National Science Foundation (NSF). These results document research funded through ADC and is being shared to inform interested parties of ongoing activities and to encourage further discussion. Any opinions, findings, conclusions, or recommendations expressed above do not necessarily reflect the views of NCSES or NSF. Please send questions to ncsesweb@nsf.gov.