Event box
Time to Get Organized! Records and Information Management Basics Online
Class Overview
As many of us start to think about returning to the office and cleaning out spaces that potentially sat empty for two years, it is a good time to pause and ask yourself what you can actually throw out and what you need to keep. Can you toss that grant information, job applicant's resumé, or old files, or do they need to be retained? What about all of your digital files that have built up in OneDrive, Box, Outlook, etc? This class will help you answer those questions. Together we will cover the basics of records and information management including:
- What is and is not a "record"
- How long you should keep important documents
- How to store your documents
- How to properly dispose of your documents
Got questions about specific kinds of records? We will have plenty of time at the end for you to ask our experts.
Class Instructors
Brenda Gee – Administrative Director – Communications, Records, and Policy in the Office of the Executive Vice Chancellor and Provost.
Brenda is responsible for the development and management of the UCSF Records and Information Management Program. Implementation includes providing advice, information, and training, regarding records management.
Carolyn Tuft – Assistant Director - Business Intelligence
Carolyn Tuft is a Sr Project Manager on the Real Estate team. Her focus is records and information management. She works with teams moving to open plan workspaces to help them reduce their paper records while insuring records and information are accessible when needed and managed in a compliant manner.
Polina Ilieva - Associate University Librarian for Collections
Related LibGuide: Reproducible Data Management by Ariel Deardorff
- Date:
- Thursday, Feb 3 2022
- Time:
- 10:30am - 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:
- Archives and Special Collections Data Science > Data Management Data Science