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Overview

Since early 2025 several federal research datasets have been altered or deleted in response to White House executive orders. These actions have raised concerns about the accessibility and integrity of government data. For example, in February, several datasets from the US Census Bureau suddenly became unavailable, and others from the CDC were removed and then later restored. In this presentation, we will explore the latest developments in data censorship and the current efforts to rescue and preserve government datasets. You’ll learn about the organizations that have worked to preserve data, alternative sources of government data, and how you can get involved to protect valuable public information.

Learning Objectives

By the end of this workshop, participants will be able to: 

  • Describe the impact of recent executive orders on government data accessibility and integrity
  • Identify key organizations involved in preserving government data
  • Implement a workflow to preserve public-access government datasets

Instructors

Ariel Deardorff is the Director of Data Science & Open Scholarship at the UCSF Library. An expert in data management and research data publishing, Ariel has led the Library’s involvement with several data infrastructure and policy projects.

Yea-Hung is a Data Science Instructor at the UCSF Library. In that role, he provides support to the UCSF community on R and quantitative methods.

Accessibility

UCSF welcomes everyone, including people with disabilities, to our events and classes. To request a reasonable accommodation for this class, please contact Ariel Deardorff by emailing ariel.deardorff@ucsf.edu as soon as possible.

Event Details


UCSF promotes the exchange of diverse ideas and perspectives, acknowledging that the views and opinions of our guest speakers on campus are their own and may not reflect the perspective of the University. We embrace free speech in the pursuit of greater understanding, consistent with our obligations as a public university under the First Amendment.