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Sep

21

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DataFlash: Spotlight on NIH Office of Data Science and Strategy’s Generalist Repository Ecosystem Initiative (GREI)

Posted by on September 21st, 2023 Posted in: Blog, Data Science, Training & Education


What is the Generalist Repository Ecosystem Initiative (GREI)?

The long-term vision for the Generalist Repository Ecosystem Initiative (GREI) is to develop collaborative approaches for data management and sharing through inclusion of the generalist repositories in the NIH data ecosystem. GREI’s primary mission is to establish a common set of cohesive and consistent capabilities, services, metrics, and social infrastructure across various generalist repositories. Ultimately GREI hopes to better enable the search and discovery of NIH-funded data.

What is a generalist repository and how does it differ from a specialized repository?

To be compliant with NIH’s Data Management and Sharing Policy, research funded by NIH must be deposited into an open access repository. In most cases, researchers get to decide which repository to deposit their data. “Generalist” and “specialized” are the terms used to describe the two different types of repositories.

Specialized repositories, also known subject-specific, domain-specific, and discipline-specific repositories, accept data about a specific research topic (e.g. sleep studies). Additionally, specialized repositories typically only accept specific types of structured data and/or software, which are outlined in each respective specialized repository’s user guidelines.

Generalist repositories, also known as cross-discipline repositories, have a broader subject scope and also tend to be more flexible with the types and formats of data that can be deposited.

Does it make a difference which repository data is submitted to?

There are benefits and disadvantages of both types of repositories. For highly-specialized research, depositing data in a relevant specialized repository could make it more likely that your data is discovered and reused by fellow researchers working in your same specialty. However, broader audiences may not be aware of particular topic-specific repository, so they may not be able to discover your data as easily. Of note, there is emerging guidance that depositing data in a generalist repository may make your data more easily findable by a wider range of researchers working in a variety of disciplines (1).

Since the selection of a repository has a direct impact how data is able to be found, accessed, and reused, the NIH has outlined detailed guidance on how to evaluate and select an appropriate data repository.

Visit the following sites for a list of NIH-supported domain-specific repositories and NIH-supported generalist repositories.

GREI Learning Opportunities & Resources

More than one year into the initiative, GREI has launched a number of training sessions and webinars on research data management and sharing, metadata best practices, and open science frameworks. Sessions are also hosted by awardees and range from introductory sessions (e.g. overviews on NIH’s Data Management and Sharing Policy) to more specialized workshops (e.g. data cleaning with open source software).

Below is a list of upcoming scheduled trainings:

Tracking and Reporting Funded Research Plans and Outcomes
Tuesday, October 3, 2023 from 7:00 a.m. – 8:00 a.m. PT
For More Information and to Register Click Here

Research Data Onboarding: Procedures for Research Consistency
Wednesday, October 4, 2023 from 9:00 a.m. – 10 a.m. PT
For More Information and to Register Click Here

Securely Managing and Publishing Sensitive Data
Wednesday, November 15, 2023 from 9:00 a.m. – 10:00 a.m. PT
For More Information and to Register Click Here

Click here for a full list of GREI webinars and awardee hosted trainings.

 

Reference:

  1. Contaxis, N., Clark, J., Dellureficio, A., Gonzales, S., Mannheimer, S., Oxley, P. R., Ratajeski, M. A., Surkis, A., Yarnell, A. M., Yee, M., & Holmes, K. (2022). Ten simple rules for improving research data discovery. PLoS computational biology18(2), e1009768. https://doi.org/10.1371/journal.pcbi.1009768

Image of the author ABOUT Carolann Curry
Carolann Curry is the Outreach & Data Coordinator for NNLM Region 5.

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Developed resources reported in this program are supported by the National Library of Medicine (NLM), National Institutes of Health (NIH) under cooperative agreement number UG4LM012343 with the University of Washington.

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