A Tiered Model for Data Management, Curation, and Sharing Support in Grant Proposals and Budgets

Recent trends in research funder policies and guidelines increasingly point to requirements for more detailed plans for data management, curation, and sharing with an emphasis on including allowable costs in grant budgets to support these activities as well. As a result, libraries and other collabor...

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Veröffentlicht in:Journal of escience librarianship 2023-11, Vol.12 (2)
1. Verfasser: Johnson, Andrew
Format: Artikel
Sprache:eng
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Zusammenfassung:Recent trends in research funder policies and guidelines increasingly point to requirements for more detailed plans for data management, curation, and sharing with an emphasis on including allowable costs in grant budgets to support these activities as well. As a result, libraries and other collaborating units at academic institutions have an opportunity to develop streamlined models that allow researchers to incorporate institutional resources for data management, curation, and sharing into their grant proposals along with costs to support these resources. While the current literature contains examples and discussions of general funding approaches to activities like data curation and long-term preservation, little has been written on formal models or strategies for incorporating data management and curation support into the grant proposal and budget process itself. This article describes the development and implementation of a tiered grant support model at the University of Colorado Boulder that provides three levels of services, infrastructure, and expertise to researchers who are looking to incorporate support and costs for data management, curation, and sharing into their grant proposals. The article also presents lessons learned since the soft launch of the grant support model as well as key challenges that have emerged. This model may serve as an example for other institutions to use or adapt to continue to help researchers meet funder requirements while simultaneously increasing the visibility of existing data management and curation resources and identifying potential new revenue or cost recovery streams.
ISSN:2161-3974
2161-3974
DOI:10.7191/jeslib.702