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Data Management Resources

Writing Informed Consent Language for Data Sharing

Data sharing is something that should be considered at the impetus of a project, especially when working with human subject data. Informed consent should be developed in a way that allows for secondary use of data, without compromising the ethicality and integrity of the data. Here are some resources to help you develop informed consent for data sharing. 

Research Data & Digital Scholarship Data Sharing Services

The Research Data & Digital Scholarship team offers services to assist you with data sharing, such as:  

  • identifying a repository for depositing your data
  • preparing data for deposit
  • developing documentation
  • depositing qualitative, qualitative, and mixed methods data
  • applying appropriate licenses for future use

NIH Repositories

If you are applying for an NIH grant, be sure to check out the Repositories for Sharing Scientific Data page. It has a searchable list of NIH-supported repositories and information about generalist repositories.

Looking for an appropriate repository according to the NIH Data Management and Sharing Policy policy preferences? Follow our NIH Data Management and Sharing Policy Repository Decision Tree

Data Lifecycle Template Screenshot

Data Sharing Methods Comparison Table

This table provides pros, cons, and examples of different data sharing methods. If you have questions about which method is right for you, please reach out to us.

Method Pros Cons Examples
Institutional data repository
  • Built-in funding means it will continue to be supported
  • Metrics available
  • Local assistance from data professionals on your campus
  • Less likely to accept sensitive data
  • Not all institutions have an institutional repository
Disciplinary repository
  • Developed specifically for people in your field
  • Citations can likely be tracked, depending on service
  • Metrics may be available
  • May go under and stop hosting data
  • May cost money to deposit
  • May or may not provide long term preservation
Generalist repository
  • Great for interdisciplinary scholarship
  • Citation can likely be tracked, depending on service
  • Use is probably measured
  • May cost a fee to deposit
  • Company may change its terms of service
  • Company may go out of business and stop hosting data
  • May or may not provide long term preservation
  • Zenodo- a repository for all types of data but popular with STEM fields
  • Harvard Dataverse- a Harvard supported repository for anyone to deposit data into
  • Open Science Framework (OSF)- has a strong workflow support option so you can use OSF throughout the lifetime of the project, not just at the conclusion
Governmental repository
  • Good repository documentation and supporting information 
  • Will likely continue to be supported
  • Citations can likely be tracked
  • Repositories do not yet exist for all types of data
  • May or may not be prepared for long term preservation
  • May only accept data from research funded by the specific granting agency
Journal publisher - supplemental material/supporting information
  • Data is connected to the publication it supports
  • Citations can be tracked
  • Publishers often strongly suggest relying on a data repository
  • Publisher may decide to discontinue hosting data
  • PLOS One - Supporting Information Policy

Research Data Engineer

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Lauren Phegley
she/her

Lauren Phegley holds consultations on data management, DMPTool, writing Data Management Plans (DMPs), and data sharing.

Schedule: Tuesdays from 10-11am EST (Zoom or in-person) and Fridays from 11-12pm EST (Zoom only).

Head of Research Data Services

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Lynda Kellam
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Head of Research Data Services

See schedule button for current dates and times. Appointments available in person and on zoom.

Subjects: Data & GIS