Workshop: Satisfying NIH data sharing and management requirements with Terra and AnVIL

  • Register
    • Regular Member - $15
    • Early Career Member - $8
    • Resident/Clinical Fellow Member - $8
    • Postdoctoral Fellow Member - $8
    • Graduate Student Member - $8
    • Undergraduate Student Member - $8
    • Emeritus Member - $8
    • Life Member - $15
    • Trainee Member - $8
    • Nonmember - $30

    Continue

As biomedical data grow at an exciting pace, the ability to share them in a way that is Findable, Accessible, Interoperable, and Reusable (FAIR) has never been more important. Recognizing this need for better data practices, the National Institutes of Health (NIH) has released a new policy (NOT-OD-21-013) that requires researchers generating NIH-funded data to create a strategy and budget for data management and sharing. This plan must include the selection of a public data repository that implements desirable characteristics like unique identifiers, metadata, free and easy sharing, security, and quality assurance. Terra, an open-source bioinformatics ecosystem that includes a repository, a Data Oversight Use System (DUOS), and an analysis platform, is an ideal solution for researchers needing to comply with this new NIH policy and is already being implemented as an approved data-sharing repository by the NHGRI's Genomic Data Science Analysis, Visualization, and Informatics Lab-Space (AnVIL, NOT-HG-19-024). 

In this interactive workshop, participants will learn about key data-sharing practices and take a journey through the Terra ecosystem to explore the features that meet NIH’s desirable characteristics. Participants will view and engage in two vignettes that discern how Terra and AnVIL can satisfy the data needs of both a large consortium and an individual research lab. In the consortium vignette, the AnVIL team will use hands-on activities to show how they are harnessing Terra features for data sharing, management, and reproducible analysis in ways that already meet NIH’s standards. In the individual lab vignette, participants can upload and share their own mock data set and metadata. Regardless of their use case, participants will walk away with the skills and confidence to include Terra/AnVIL in their data management plan. 

By the end of the workshop, participants will learn how to: 

1. Find and use Terra/AnVIL features that comply with NIH policy requirements

2. Upload data to Terra/AnVIL

3. Make data findable and accessible to promote scientific reproducibility

Stephen Mosher

Dr. Stephen Mosher is a Research Scientist at Johns Hopkins University. He received his Masters degree from the University of Toronto in Canada and his doctorate from the University of Tübingen in Germany. Today, Dr. Mosher serves as a program manager on the AnVIL Project (https://anvilproject.org) and the Genomic Data Science Community Network (https://www.gdscn.org).

Elena Ghanaim

Elena Ghanaim is the Policy Advisor for Data Science and Sharing within the Office of Genomic Data Science (OGDS) at the National Human Genome Research Institute (NHGRI). She spearheads NHGRI’s scientific data sharing policy development, oversight, and implementation. 

Ava Hoffman

Dr. Ava Hoffman is a Senior Staff Scientist at Fred Hutchinson Cancer Center where she is a member of the Fred Hutch Data Science Lab. She helps lead and develop outreach resources for the AnVIL Project (https://anvilproject.org) and the Genomic Data Science Community Network (https://www.gdscn.org). Her background is in genetics of non-model organisms and data science consulting for industry.

Anton Kovalsky

Dr. Anton Kovalsky is a Science Writer at the Broad Institute of MIT and Harvard. In this role, he authors and edits material for technical documentation, blog posts, how-to guides and workshop presentations. 

Frederick Tan

Frederick Tan is on the Bioinformatics Research Faculty at Carnegie Institution, Department of Embryology, and an Adjunct Assistant Professor at Johns Hopkins University, Department of Biology. He and his collaborators research mechanisms to effectively train and support diverse populations in genomic data science.

Key:

Complete
Failed
Available
Locked
Live Workshop Online Event
09/14/2023 at 12:00 PM (EDT)  |  Recorded On: 09/18/2023
09/14/2023 at 12:00 PM (EDT)  |  Recorded On: 09/18/2023
You must register to access.