Generalist Repository Selection Flowchart
Tuesday, February 24, 2026
The repository selection flow chart is a product of the Generalist Repository Ecosystem Initiative (GREI)
Tuesday, February 24, 2026
The repository selection flow chart is a product of the Generalist Repository Ecosystem Initiative (GREI)
Friday, April 10, 2026
David N. Kennedy, Ph.D., will present "From Observation to Knowledge: Harnessing Reproducible Practices to Accelerate Science" from 12:00 p.m.–1:00 p.m. EDT.
Reproducible research practices are essential for transforming raw scientific observations into robust, actionable knowledge. This talk explores how advances in infrastructure, developed by ReproNim and the community, empower researchers to better share, reuse, and build upon scientific data.
I will highlight our interactions with collaborative platforms like OpenNeuro, to make versioned and re-executable computation accessible at scale. In addition, the ENIGMA Parkinson’s Disease project will serve as an example highlighting harmonization and query across dozens of research sites, and how public and private metadata stores (so-called ReproLakes and ReproPonds) can be integrated to support FAIR (Findable, Accessible, Interoperable, Reusable) and reproducible analyses.
Attendees will gain insights into the technical and cultural challenges of reproducible science, get practical examples of solutions in action, with the hope that this can support advancing data sharing and reuse within their own research programs. Together, we can accelerate the transition from scientific observation to reliable knowledge by harnessing the power of reproducible practices.
Dr. Kennedy is a Professor of Psychiatry and Radiology at the University of Massachusetts Chan Medical School. He is Director of the Division of Neuroinformatics at the Child and Adolescent Neurodevelopment Initiative (CANDI). He has extensive expertise in the development of image analysis techniques and was a co-founder of the Center for Morphometric Analysis (CMA) at the Massachusetts General Hospital in 1988. His career has seen participation in the advent of such technologies as MRI-based morphometric analysis (1989), functional MRI (1991) and diffusion tensor pathway analysis (1998). He has long standing experience with the development of neuroinformatics resources (such as the NeuroImaging Tools and Resources Collaboratory (NITRC)) and reproducibility initiatives (such as ReproNim: A Center for Reproducible Neuroimaging Computation). In addition, he was a founding editor of the journal Neuroinformatics that debuted in 2003.
The seminar is open to the public and registration is required each month. Individuals who need interpreting services and/or other reasonable accommodations to participate in this event should contact Allison Hurst at 301-670-4990. Requests should be made at least five days in advance of the event.
The National Institutes of Health (NIH) Office of Data Science Strategy hosts this seminar series to highlight examples of data sharing and reuse on the second Friday of each month at noon ET. The monthly series highlights researchers who have taken existing data and found clever ways to reuse the data or generate new findings. A different NIH institute or center will also share its data science activities each month.
Friday, March 20, 2026
By: Dr. Susan Gregurick, Associate Director of Data Science, NIH
Welcome to the March 2026 Director’s Corner! We’re back for the new year to share updates from the NIH Office of Data Science Strategy (ODSS). This month, we’re spotlighting the ODSS collaborations with the NIH Institutes, Centers, and Offices in fiscal year 2025. We capture these collaborations in PDF documents sent to ICO directors. The PDF documents serve as a great way to disseminate information about the impact of ODSS collaborations, with detailed graphics and funding highlights.
To compile the PDF documents, the ODSS gathers relevant information such as funding trends, strategic goal trends, funding highlights, collaboration outputs, and funding outputs across ODSS’s NIH portfolio of partners to ensure accuracy and completeness of the data. We gather this information by reviewing co-funded projects and goals from the past fiscal year.
Each highlight opens with a summary of ODSS funding for the IC in the previous fiscal year. The opening notes funding trends from previous years and ties funding into the larger set of NIH Data Science strategic goals. For example, a PDF document might note that an ICO and ODSS have consistently collaborated to support workforce development or develop analytic tools and data infrastructure. This section also includes graphs and charts to show funding trends, the number of funded projects by goal area, and funding distributions. These are great opportunities to highlight how ICO/ODSS collaborations tie into NIH strategic goals.
Next, the PDF documents show co-funding highlights between the ICO and ODSS from the previous year. Here, we note specific projects funded by ODSS and completed by the ICO. These might be technologies, training programs, data infrastructures, or many other biomedical and research initiatives. Each project is also tied to a specific goal area within the NIH Data Science strategic goals. Finally, a graphic shows collaboration outputs, noting the number of publications, patents, clinical trials, RAS-supported data resources, ChIRP users, Coursera users, and STRIDES accounts from the previous fiscal year.
ODSS is grateful for the partnerships and collaboration with the NIH Institutes, Centers, and Offices that make these highlights possible and illustrate our combined impact in data science, reminding me of a famous African proverb, "If you want to go fast, go alone. If you want to go far, go together."
Check out the highlights at https://datascience.nih.gov/nih-ic-end-of-year-letters.
Stay tuned for more updates from ODSS, and let’s continue working together to transform data into discovery.
Friday, March 13, 2026
Derek Caetano-Anollés, Ph.D., will present "Sequence Read Archive: Leveraging this petabyte-scale database to drive biomedical discovery" from 12:00 p.m.–1:00 p.m. EST.
The Sequence Read Archive (SRA) is the largest publicly available repository of high-throughput sequencing data. With big data come big challenges, and that includes keeping the SRA sustainable while making sure that data is findable, accessible, interoperable and reusable. Following a brief introduction to the SRA and the expanse of data it holds, we will share best practices for accessing SRA data for your analyses and the various formats you may encounter. Finally, we will describe the SRA Lite file format, which is faster to download with the added advantage of shrinking the overall footprint of SRA. We will demonstrate the use of SRA Lite format in NCBI RNA-seq pipelines and related analyses, and offer appropriate NCBI resources to learn more and engage with us.
The seminar is open to the public and registration is required each month. Individuals who need interpreting services and/or other reasonable accommodations to participate in this event should contact Allison Hurst at 301-670-4990. Requests should be made at least five days in advance of the event.
The National Institutes of Health (NIH) Office of Data Science Strategy hosts this seminar series to highlight examples of data sharing and reuse on the second Friday of each month at noon ET. The monthly series highlights researchers who have taken existing data and found clever ways to reuse the data or generate new findings. A different NIH institute or center will also share its data science activities each month.