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The Case for Data Sharing: Generalist Repository Real-World User Stories

Curtin, Lisa

Abstract

These are the presentation slides from Session III of the 2025 MIRL Symposium, focusing on the Generalist Repository Ecosystem Initiative (GREI). This session provided attendees with practical resources and illustrative examples to support open data sharing and compliance with the NIH Data Management and Sharing (DMS) Policy. The presentation outlines the GREI Resource Toolkit for librarians and researchers, which includes: The Generalist Repository Comparison Chart The Generalist Repository Selection Flowchart Best Practices for Data Submission Checklist Guide for including generalist repositories in NIH DMS Plans Additionally, the slides feature real-world user stories from seven generalist repositories (Harvard Dataverse, Dryad, Figshare, Mendeley Data, OSF, Vivli, and Zenodo). These case studies demonstrate the tangible scientific benefits of data sharing, including data harmonization, enhanced reproducibility, support for multimodal datasets, and restricted access capabilities for sensitive health data.

Full text

The Case for Data Sharing: Generalist Repository Real-World User Stories Medical Institutional Repositories in Libraries Symposium Session III: Data November 20, 2025 Lisa Curtin Coordinator for Research Data & Funders, Figshare GREI Year 4 Community Engagement Lead https://datascience.nih.gov/data-ecosystem/generalist-repository-ecosystem-initiative About GREI The mission of the Generalist Repository Ecosystem Initiative (GREI) is to establish a common set of capabilities, services, metrics, and social infrastructure; raise general awareness and facilitate researchers to adopt FAIR principles to better share and reuse data. GREI Resource Toolkit Practical, openly available resources GREI Use Case Catalog: Published seven total use cases for researchers, institutions, and funders to demonstrate practical applications of generalist repositories in an NIH data sharing context. Generalist Repository Selection Flowchart: Designed to guide users through a series of considerations for selecting the right repository for sharing data. GREI Use Case Catalogs in Zenodo doi.org/10.5281/zenodo.11105429 A detailed chart comparing features, limits, and costs to help users select the right repository. This is the most viewed and downloaded item in the GREI Zenodo community. Generalist Repository Comparison Chart: v4 doi.org/10.5281/zenodo.3946719 GREI Resource Toolkit: Generalist Repository Comparison Chart ●Detailed features and services ●Data Storage, Sharing, Access, and Preservation ●Metadata ●Persistent Identifiers and Interoperability ●Usage Statistics and Metrics ●Access Control ●Registries and Certification ●User Support v4 v4 doi.org/10.5281/zenodo.3946719 Guide for Including a Generalist Repository in an NIH Data Management and Sharing (DMS) Plan: Specific guidance and sample text for researchers for each required element of an NIH DMS Plan when a generalist repository is being used. Best Practices for Data Submission in Generalist Repositories: A checklist of best practices for researchers to follow when planning, preparing, submitting, and following up on data submissions to generalist repositories. doi.org/10.5281/zenodo.14278906 doi.org/10.5281/zenodo.14278957 GREI Resource Toolkit Practical, openly available resources GREI Real-World User Stories To demonstrate the real impact of the GREI repositories, each repository has begun collecting stories from real repository users about their experiences sharing and reusing biomedical data in generalist repositories. Through these stories we have learned how researchers have, for example: GREI Real-World User Stories can be found at: https://bit.ly/GREIUserStories Shared complex, multimodal datasets that have been reused by other labs, leading to new discoveries and collaborations. Combined and reused data from separate clinical trials to create new disease models and directly inform national clinical practice guidelines. Published analysis code, software, and workflows, improving reproducibility and accelerating research in computationally intensive fields like multi-omics and biomedical informatics. Sharing the Brain Genomics Superstruct Project (GSP) Researcher: Dr. Buckner, Randy L.(Harvard, MGH, HMS) The Research: The Brain Genomics Superstruct Project Open Access Data Release exposes a carefully vetted collection of neuroimaging, behavior, cognitive, and personality data for over 1,500 human participants. Repository Use: Dr. Buckner chose the Harvard Dataverse Repository due to the General support and excitement over a Harvard open data repository. The reuse dataset identified in this real world user story is is also shared on Harvard Dataverse. Data Sharing and Reuse User Stories “It’s been amazing to watch the field change. When you ask about sharing standards in our field, I think most people — especially if they receive NIH funding — follow them. But more broadly, because foundations…run by the Coalition for Aligning Science all encourage open, transparent data sharing, it has just now become the new standard. And it wasn’t 30 years ago.” https://doi.org/10.5281/zenodo.17081413 Exploring data sharing practices through Dryad: A researcher’s insight Data Sharing and Reuse User Stories "Data sharing becomes extremely important for multi-institution collaborations, as well as training activities we have with scholars from other laboratories.” https://doi.org/10.5281/zenodo.17038533 Researcher: Dr. Troy D. Wood, University at Buffalo The Research: The data benefits researchers studying soybean metabolomics and stress-adaptive phenotypes, and offers valuable examples for mass spectrometry practitioners applying the Kendrick mass defect in complex biological samples. Repository Use: Dr. Wood chose Dryad to host the dataset due to his previous positive experience publishing data on Dryad and the platform’s expert team of curators—“real people who provide hands-on support for every dataset to ensure quality, consistency, and usability.” Open Science in Neuroscience Researcher: Oliver Contier, Max Planck Institute for Human Cognitive and Brain Sciences The Research: The THINGS-data project provides a massive collection of brain and behavioral data to shed light on how we see and distinguish between different objects. Repository Use: The research team chose Figshare as the central repository for THINGS-data due to its flexibility in organizing large, multimodal collections. To further enhance accessibility and meet community standards, THINGS neuroimaging data was shared on OpenNeuro.org, while behavioral data was shared via the Open Science Framework (OSF). Data Sharing and Reuse User Stories “Reusing open data can be particularly beneficial for early-career researchers, helping to minimize risks when resources are limited…and sharing one's own data can increase visibility and help develop valuable technical skills.” https://doi.org/10.5281/zenodo.16970812 Thank you!