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Report . 2023
License: CC BY
Data sources: Datacite
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Generalist Repository Ecosystem Initiative (GREI) Workshop Summary Report

Authors: Ana Van Gulick; Nicole Pfeiffer; Sara Gonzales; Gabriela Regan; Jessica Herzog; David Scherer; Mark Hahnel; +3 Authors

Generalist Repository Ecosystem Initiative (GREI) Workshop Summary Report

Abstract

Summary report of Virtual Generalist Repository Ecosystem Initiative (GREI) Workshop held January 24 & 25, 2023. Workshop recordings and slides available at: https://doi.org/10.5281/zenodo.7714262 The NIH Virtual Generalist Repository Ecosystem Initiative (GREI) Workshop was held on January 24 and 25, 2023. The online event was presented by the seven generalist repositories that are awardees of the GREI program: Dataverse, Dryad, Figshare, Mendeley Data, Open Science Framework, Vivli, and Zenodo, and was sponsored by the NIH Office of Data Science Strategy. The workshop occurred just at the time when the new NIH Data Management and Sharing Policy went into effect, which will likely be a significant turning point that advances the sharing of NIH-funded research data. This policy will hopefully continue to drive a shift in the culture of data management and sharing and increase the frequency of both data sharing and reuse as well as help make open data more FAIR and trackable. The GREI workshop built on a previous ODSS-funded workshop in February 2020, the NIH Workshop on the Role of Generalist and Institutional Repositories to Enhance Data Discoverability and Reuse, at which the term “coopetition” was coined to describe collaboration (cooperate + competition) among repositories, which is a key objective of GREI. The GREI program has a mission to “establish a common set of cohesive and consistent capabilities, services, metrics, and social infrastructure across various generalist repositories and to raise general awareness and help researchers to adopt FAIR principles to better share and reuse data.” The goals of the GREI Workshop were to explore NIH data sharing use cases for generalist repositories within the larger data sharing landscape and research community, address the potential impact of FAIR data sharing and data reuse for scientific discovery, provide guidance on generalist repository best practices, and gather community feedback on needs for generalist repository infrastructure and training. The workshop was targeted at NIH-funded researchers, both intramural and extramural, and those supporting NIH-funded researchers and data sharing at academic institutions and libraries as well as other stakeholders at NIH and institutions. Each day of the workshop featured a keynote speaker with talks that explored the data repository landscape and the value and impact of data sharing and a panel session with presentations and discussion from leaders in open data from the research community, academic institutions, and NIH offices and institutes. Each day concluded with an interactive training session: the first on using generalist repositories to share data including selecting a data repository for specific use cases and generalist repository best practices and the second on discovering, tracking, and reusing data in generalist repositories.

Keywords

NIH data, data sharing, open science, generalist repository, open data, data management, data repository

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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