Abstract
Toward a Better Data Management Plan: The Impact of DMPs on Grant Funded Research Practices
Highlights
Introduction and BackgroundIn our data-centric era, research data have become valuable resources for encouraging research reproducibility, supporting information equity, accelerating science, and amplifying the impact of research (Vision 2010)
Acknowledging the value of research data, federal funding agencies increasingly require that data management plans (DMPs) be included in grant proposals to support good data stewardship practices and to promote data sharing and reuse (Holdren 2013)
The DMP requirement from funding agencies is a commitment to the idea that strong data management planning can help ensure that published research data adheres to community standards like the FAIR Data Principles (Wilkinson et al, 2016)
Summary
Introduction and BackgroundIn our data-centric era, research data have become valuable resources for encouraging research reproducibility, supporting information equity, accelerating science, and amplifying the impact of research (Vision 2010). Acknowledging the value of research data, federal funding agencies increasingly require that data management plans (DMPs) be included in grant proposals to support good data stewardship practices and to promote data sharing and reuse (Holdren 2013). In response to these trends, academic libraries are seeing increased demand to provide research data services (Tenopir et al 2017; Bryant, Lavoie, and Malpas 2017; Tenopir, Sandusky, Allard, and Birch 2014). The FAIR principles support the idea that data must be carefully structured and described in order to be Findable, Accessible, Interoperable, and Reusable
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