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BEGIN:VEVENT
DTSTART:20250513T180000Z
DTEND:20250513T190000Z
DTSTAMP:20250513T000000Z
SUMMARY:postponed: Safeguarding Public Data: Rescuing Federal Research Datasets
DESCRIPTION:We have to postpone this event due to illness. It will not be 
 held on the scheduled date (5/13). Please register if you'd like to be 
 notified regarding the new date. We hope to make that announcement 
 soon.\n\nOverview\n\nSince 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.\n\nLearning Objectives \n\nBy the end 
 of this presentation\, participants will be able to: \n\n\n	\n	Describe the 
 impact of recent executive orders on government data accessibility and 
 integrity\n	\n	\n	Identify key organizations involved in preserving 
 government data\n	\n	\n	Implement a workflow to preserve public-access 
 government datasets\n	\n\n\nInstructors\n\nAriel 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. 
 \n\nYea-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. \n\nAccessibility\n\nUCSF 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.
LOCATION:Online
ORGANIZER;CN="Ariel Deardorff":MAILTO:ariel.deardorff@ucsf.edu
CATEGORIES:Data Science, Scholarly Communication
CONTACT;CN="Ariel Deardorff":MAILTO:ariel.deardorff@ucsf.edu
STATUS:CONFIRMED
UID:LibCal-14477905
URL:https://calendars.library.ucsf.edu/event/14477905
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