NIH Data Management and Sharing Requirements - Roundup of Training Resources

One of NLM's prominent messages this year at MLA-22 was about preparing for the Data Management & Sharing Plan Requirements that go into effect January 2023.

NLM / NIH are seeking to strike a balance between data access vs. data protection / privacy.  We know there will be more innovation when the data is shared widely, but it needs to be balanced with keeping personal data secure. 

Patti Brennan gave the example of the current waste water studies tracking community rates of Covid-19.  Those samples contain personal DNA along with viral DNA of Covid/SARS-Cov-2.  How do we separate and secure the personal DNA data from the viral DNA data and make that available and useable by other researchers?  

Librarians in attendance asked NIH to provide templates or prototypes as examples of data management set plans.  They said they would provide guidelines, but not templates, because every data management plan will be different according to the data produced.

Key Points:

• You don't have to be a statistician to [help a researcher] write a data plan.  
• It's more thinking about how the data will be managed and shared.  
• A DMSP is designed to be 2 pages or less. [Now--Doesn't that make it seem do-able?]

I am not a Data Librarian, and I'm still wrapping my head around how I can apply this in my health care setting, but wanted to set it down here for those who want to  ...

Learn More:

Data Clearinghouse https://sharing.nih.gov

    

    > The Data Clearninghouse is where you'll find the "meat and potatoes" of what will be required in January 2023, including more info on the following:

    

Data Management & Sharing Policy (DMSP)

• About
• Overview
• Research Covered Under DMSP
• Planning & Budgeting for DM&S
• Writing a DM&S Plan
• Budgeting for DM&S
• Data Management
• FAIR Principles
• Length of Time to Maintain Data
• Metadata and Other Associated Documentation
• Naming Conventions
• Common Data Elements
• Data Storage Format
• Data Security

• Sharing Scientific Data
• Data Sharing Approaches
• Selecting a Data Repository
• Repositories for Sharing Scientific Data

Classes & Webinars to learn more:

Common Data Elements: Standardizing Data Collection

Making data Findable, Accessible, Interoperable and Reusable (FAIR) starts well before
data collection. Designing studies with common data elements (CDEs) can enable data sharing
and reuse, and librarians and other information professionals can assist researchers in the use of CDEs.
Whether you are a research data librarian or assist researchers in finding sources, this one-hour,
self-paced course from the National Library of Medicine can help you understand how you can
support the use of common data elements (CDEs) in creating FAIR data.

Objectives

After completing this course, you will be able to: 

• Explain what we mean by making data Findable, Accessible, Interoperable and Reusable (FAIR) 
• Define and describe Common Data Elements (CDEs) 
• Interpret the roles for librarians related to CDEs, and identify repositories that would be relevant to these roles
• Describe the National Library of Medicine’s role in supporting CDEs 

The course modules include: 

• Why the Need for Common Data Elements? (10 minutes) 
• FAIR Data (15 minutes) 
• Common Data Elements (CDEs) (20 minutes) 
• NLM and Common Data Elements (15 minutes) 

NIH Data Management and Sharing Requirements Series

The webinar series introduces the basics of data management and the new requirements for data management and sharing that will be in place beginning in 2023. The introduction will then be followed by three webinars providing “practitioner perspectives” – i.e., data librarians sharing their opportunities, barriers, methods, and successes as they work toward improving data management practices at their institutions.

Objectives

Upon attendance, attendees will be able to:

1. Describe basic best practices in data management
2. Advise researchers on steps to adhere to the NIH DMSP requirement
3. Create a plan for outreach at their own institution

The Sessions:

• Introduction to the NIH Data Management and Sharing Plan (Session 1)
• NIH Data Management and Sharing Session 2. Practitioner Perspectives: Internal Outreach and Policy
• NIH Data Management and Sharing (Session 3). Practitioner Perspectives: Education
• NIH Data Management and Sharing Session 4. Practitioner Perspectives: Infrastructure
• NIH Data Management and Sharing Session 5. Policy Recap and Q&A (May 24, 2022)

Changing the Culture of Data Management and Sharing: A Workshop from The National Academies of Sciences, Engineering, Medicine

This two-day virtual workshop will explore challenges and opportunities for researchers, institutions, and funders in establishing effective data management and sharing practices. Workshop presentations and discussions may examine strategies, resources, and promising practices for developing and evaluating data management and sharing plans. Participants may also discuss how researchers can effectively share scientific data over the course of the data life cycle.

Potential topics include:

• Overarching strategies for managing and sharing data
• Assessing the value of shared data
• Monitoring and evaluating data management and sharing practices
• Educational and resource needs for responsible data sharing