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This is the second in a series of articles on the changes to the NIH Data Management and Sharing policies that will come into effect for NIH grant applications starting January 2023. See our first article for a general overview.

If you’re preparing to apply for an NIH grant, having a plan to manage and share your data just turned up on your to-do list. Currently, only grants of $500,000 or more are required to have a data management plan. Effective January 25, 2023, ALL grant applications or renewals that generate scientific data must include a detailed plan related to managing and storing data through the duration of the funded period, including plans for data dissemination. NIH just released a list of activity codes for grants that will be subject to the new policy last week. Where do you start? What should be included in this plan? We’ll provide some answers and resources to guide you here. 

All data management plans should incorporate the FAIR (Findable, Accessible, Interoperable, Reusable) principles to ensure optimal research data stewardship. Beyond following FAIR guidelines, what are the specific elements that must be included in a data management plan?  Here’s an outline of things to include and think through:

Who will be responsible for the data?

  • Usually, data is owned by the institution awarded the grant and the principal investigator is responsible for data collection and management.
  • If there are others responsible, this should be documented in the plan.

What types of data will be generated and where will they come from? Create a descriptive list of all the data that will be collected during the research process, as well as an estimate of how much data will be generated. Further things to consider include:

  • Why is it desirable to share this data and how could it be re-used? All data that is required to replicate results should be shared.
  • Are there any risks to disclosing this data? If any data cannot be shared due to legal, ethical, or technical reasons, exceptions for sharing can be written into the plan. However, all data must be managed.
  • At what point in the research process should data be shared? Will it be in a usable format at that time?
  • If you’re using data from other sources, include the source and any conditions for using it, also what relationship it may have to the original data generated during the research.

What formats and standards will be used for your data?

  • Non-proprietary file formats (.csv or .txt or XML or PDF, for example) are preferred. This ensures they will be readable in the future and is important for preservation.
  • Consider using a directory structure with a formalized naming convention and version control to better organize your data. Learn more about file management naming conventions from Cornell.

What formats and standards will be used for your metadata? Metadata describes your data and makes it findable. 

What will be the methods for archiving and sharing the data?

  • Where will the data be stored during the research process and how will it be backed up and secured (is encryption required)? Find tips on our data storage and security page. 
  • How will the data be made accessible after the research is complete? Find some options on our data repositories page. Cornell has considerations for selecting a repository site on their Sharing and archiving data page.
  • Determine the rights for sharing. A CC0 or CC-BY license is recommended when possible, but there may be commercial or intellectual property limitations for your research. Learn more about data licensing and protection in this guide from Cornell and about GW’s policies for sharing data.
  • Will any tools and software be needed to work with the data and metadata? How will those be provided?
  • How long should the data be preserved and made available? It may not be necessary or practical to preserve all the data in perpetuity. Making plans for how long it should be available is important to selecting a repository site.

Additional Resources:

If you have questions about creating data management plans or need further resources or information for guidance, contact Sara Hoover, Metadata and Scholarly Publishing Librarian at shoover@gwu.edu.

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With the 2023 NIH Data Management and Sharing Policy going into effect on January 25, 2023, there’s no better time to explore data management resources! This post explores resources that can help you with your data management needs.

What is data management? 

Data management involves the process of collecting or producing, cleaning and analyzing, preserving, and sharing data from a research project. Data management takes place throughout the entire research life cycle, from deciding on consistent file naming conventions to depositing the data in a repository for long-term archiving. 

Why Data Management?

Data management is vital for transparency (showing your work promotes reproducibility of work), compliance (funding organizations and journals often require making data available), and personal and organizational benefit (using data within your own lab is easier with proper management).

I Think It’s FAIR to Say…

Understanding data management best practices is important to make well-informed decisions when selecting data management resources and tools. The FAIR Principles, first published in 2016, provide a set of guidelines for data management. FAIR stands for Findable, Accessible, Interoperable, and Reusable. You can learn more about the FAIR Principles on our Data Management Guide. Another great resource to help guide your data management is Cornell University’s Research Data Management Service Group’s Comprehensive Data Management Planning and Services Best Practices which provides extensive information related to best practices for: 

Broad Data Management Resources

Himmelfarb’s Data Management Guide provides a wealth of information and resources related to data management. In addition to some basic information about data management, you’ll find information about NIH and NSF funder requirements. Data management plans (DMPs) are also covered in detail. The documentation and metadata page explains what metadata is, what should be included in your metadata, metadata schemas, controlled vocabularies, file naming conventions, and electronic lab notebooks. The data storage and security page includes data storage, storage formats, creating a backup plan, and data security. You’ll also learn about data sharing, including GW’s policy on regulated information, and data repositories.

I might need to make a plan for this… 

Creating a data management plan (DMP) is often part of the grant writing process required by funding institutions. A comprehensive data management plan should address:

  • Data Collection: Must be reliable and valid.
  • Data Storage: Appropriate amount of data so research can be reproduced.
  • Data Analysis: Interpretation of data from which conclusions can be derived.
  • Data Protection: Ensuring sensitive data is safe and secure, preventing tampering or loss of data.
  • Data Ownership: Addresses legal rights associated with data.
  • Data Retention: Addresses how long data should be kept and proper disposal of sensitive data.
  • Data Reporting: Publication of data.
  • Data Sharing: Addresses what data can be shared with others and how.

When it comes to creating a DMP, there are a number of tools available to help! The DMPTool is a free, open-source tool that helps researchers create DMPs that comply with funder requirements. DMPTool also provides links to funder websites, and best practices resources to help guide your data management efforts. Since GW is affiliated with DMPTool, GW users can create a personalized dashboard that allows them to see and organize the DMPs created through the tool. From the DMPTool’s website, simply click “sign in” and use Option 1 to search for George Washington University. Then log in with your GW UserID and password and create your data management plan! 

The Framework for Creating a Data Management Plan, created by ICPSR, is a great outline that will help you create a DMP for your grant application. The framework includes a list of elements to be included, explains why each element is important and provides examples for each element. Michener’s article Ten Simple Rules for Creating a Good Data Management Plan is another great starting point to gain an understanding of the principles and practices of creating a DMP and ensuring your data are safe and shareable. For more DMP resources and to see examples and templates, check out the Data Management Plan page of the data management guide.

What’s Next?

Stay tuned for future posts on best practices for writing a data management plan, data storage, file naming conventions, creating “readme” metadata, and other data management topics. In the meantime, check out the lists of GW resources and additional resources below to learn more!

Additional GW Resources:

Additional Data Management Resources:

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Starting in January of 2023, NIH will put into effect a new Data Management and Sharing Policy for grant applications due on or after the 25th of that month. This will replace the existing policy which has been in place since 2003. The purpose of the new policy is to ensure that the data from NIH funded research is accessible and transparent, both to enable validation of research results and to make the data available for reuse. To see specifically what has changed, this NIH web page outlines the current and new policies side by side.

In order to help researchers prepare for the new policy, the NIH has a new website on data sharing. The website is meant to help researchers determine which policies apply to their projects and provide tools and resources to aid compliance. Below is a video which introduces the new website and how it can be used:

NIH will also present two webinars on the policy, starting with: 

GW’s Himmelfarb and Gelman Libraries are preparing to assist researchers with questions about compliance. At Himmelfarb, you can contact Sara Hoover (shoover@gwu.edu), Metadata and Scholarly Publishing Librarian, and Paul Levett (prlevett@gwu.edu), Reference and Instructional Librarian.  At Gelman you can contact Megan Potterbusch (mpotterbusch@gwu.edu), Data Services Librarian. 

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