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Writing a Data Management and Sharing Plan for NIH Online
Overview:
Have you heard of the new NIH Data Management and Sharing Policy but want to learn more about how to comply? Want some more guidance on writing your Data Management and Sharing Plan (DMS plan)? In this hands-on workshop we will quickly introduce the new policy and then work through each section of the DMS plan so you understand what to write and can start drafting your own plan. We will also cover how to locate DMS plan templates and sample plans, and highlight resources for learning more.
Learning Objectives
By the end of this session you should be able to:
- Locate example DMS plans and templates
- Draft an NIH-compliant data management and sharing plan (DMS plan) for your research
- Identify resources for understanding discipline-specific requirements and getting help
Instructors
Ariel Deardorff is the Data Services Librarian at UCSF, and member of the Library's Data Science Initiative team. Ariel teaches courses on data management, open science and reproducibility. For questions about this course or other courses email ariel.deardorff@ucsf.edu or visit the Data Science Initiative Website
Wasila Dahdul is the Data Curation Librarian in the Digital Scholarship Services department at UC Irvine Libraries. She provides instruction and support for research data management, open access data publishing, and helping researchers meet funder or publisher data sharing requirements. She can be reached at wdahdul@uci.edu.
About UC Love Data Week
This workshop is part of UC Love Data Week, a week-long offering of workshops focusing on using data to build a better future through data management, security, sharing, and preservation. All members of the University of California community are welcome to attend. Make sure to register with your UC campus email. A Zoom link will be emailed to registered participants before the workshop starts.
Related LibGuide: Reproducible Data Management by Ariel Deardorff
- Date:
- Monday, Feb 13 2023
- Time:
- 1:00pm - 2:00pm
- 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 > Data Management Data Science