Ten simple rules for maximizing the recommendations of the NIH data management and sharing plan

Sara Gonzales; Matthew B. Carson; Kristi Holmes

doi:10.1371/journal.pcbi.1010397

Ten simple rules for maximizing the recommendations of the NIH data management and sharing plan

Sara Gonzales^*, Matthew B. Carson, Kristi Holmes

^*Corresponding author for this work

Preventive Medicine

Research output: Contribution to journal › Article › peer-review

16 Scopus citations

Abstract

AU The:National Pleaseconfirmthatallheadinglevelsarerepresentedcorrectly Institutes of Health (NIH) Policy for Data Management : and Sharing (DMS Policy) recognizes the NIH’s role as a key steward of United States biomedical research and information and seeks to enhance that stewardship through systematic recommendations for the preservation and sharing of research data generated by funded projects. The policy is effective as of January 2023. The recommendations include a requirement for the submission of a Data Management and Sharing Plan (DMSP) with funding applications, and while no strict template was provided, the NIH has released supplemental draft guidance on elements to consider when developing a plan. This article provides 10 key recommendations for creating a DMSP that is both maximally compliant and effective.

Original language	English (US)
Article number	e1010397
Journal	PLoS computational biology
Volume	18
Issue number	8
DOIs	https://doi.org/10.1371/journal.pcbi.1010397
State	Published - Aug 2022

Funding

Funding:Thispublicationwassupported,inpart, bytheNationalInstitutesofHealth’sNational CenterforAdvancingTranslationalSciences,Grant Number UL1TR001422. https://www.nih.gov/. The fundershadnoroleinstudydesign,datacollection andanalysis,decisiontopublish,orpreparationof themanuscript. This publication was supported, in part, by the National Institutes of Health’s National Center for Advancing Translational Sciences, Grant Number UL1TR001422. https://www.nih.gov/. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We are grateful to many collaborators for ongoing and influential discussions about research data management and sharing. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

ASJC Scopus subject areas

Genetics
Ecology, Evolution, Behavior and Systematics
Cellular and Molecular Neuroscience
Molecular Biology
Ecology
Computational Theory and Mathematics
Modeling and Simulation

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Ten simple rules for maximizing the recommendations of the NIH data management and sharing plan

Abstract

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ASJC Scopus subject areas

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