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Safeguarding Public Data: Rescuing Federal Research Datasets Online

Overview

Since early 2025 several federal research datasets have been altered or deleted in response to executive orders from the White House. These actions have raised significant 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 presentation, participants will be able to: 

  1. Describe the impact of recent executive orders on government data accessibility and integrity

  2. Identify key organizations involved in preserving government data

  3. 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 Chen 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 presentation, please contact Ariel Deardorff by emailing ariel.deardorff@ucsf.edu as soon as possible.

Related LibGuide: Population Health and Health Services Research Datasets by Ariel Deardorff

Date:
Tuesday, May 13 2025
Time:
11:00am - 12:00pm
Time Zone:
Pacific Time - US & Canada (change)
Campus:
Online
Online:
This is an online event. Event URL will be sent via registration email.
Categories:
  Data Science     Scholarly Communication  

Registration is required. There are 78 seats available.

Event Organizer

Profile photo of Yea-Hung Chen
Yea-Hung Chen
Profile photo of Ariel Deardorff
Ariel Deardorff

Director of Data Science and Open Scholarship

ariel.deardorff@ucsf.edu