Envisioning food and agricultural data for the future: Engaging communities to identify trusted data
This webinar focused on how to respond to the changing data landscape that affects food and agricultural research. The session explored how to contribute to a community-driven roadmap for improving the accessibility, transparency, and utility of food and agricultural data.
About This Webinar
How can researchers and decision-makers respond to the changing data landscape that affects food and agricultural research? As uncertainty grows about the availability of federally produced data, the research community may need to build new approaches for identifying which alternative data sources are reliable, transparent, and fit for purpose.
This webinar on June 20 addressed the following questions: What could be the role of the user community in signaling which specific food and agricultural research data are trustworthy? And how can future data infrastructures better reflect community assessment of data quality?
What Was Covered
- Why "trusted data" is more than the way data are produced—such as accurate or well-documented—but also whether data are usable, relevant, and timely for the questions researchers and decision-makers need to answer
- The difference between data that are available and data that are fit for purpose
- How researchers are navigating data access challenges through applied research use cases
- How federal agencies are using dashboard tools to track data usage and support research communities
- How the Extension community is building practical, AI-enabled tools like ExtensionBot and MERLIN to support public-facing research and education
- How national initiatives like the National Data Platform are working to develop resilient, community-aligned data infrastructure that meets evolving user needs
Who Attended
The session was designed for researchers, agency staff, Extension professionals, and applied data users working across food and agricultural policy. While recognizing the foundational role of federal statistical agencies, the discussion highlighted how data needs have evolved, particularly around access, granularity, and usability.
Speakers shared examples of researchers and institutions developing new data resources in response to emerging needs. These cases were intended to encourage discussion about collaboration and future investments.