A $500,000 prize purse, rewarding data sharing and reuse in biomedical research, is a new, innovative strategy for supporting the research community.
I should note that when we started to receive comments on what was to become the NIH DMS Policy, one thing in particular stood out to us. Many commentors told us it would be helpful to have clear information on how to protect the privacy and respect the autonomy of participants when sharing data. Now, we all know that cliffhangers build anticipation, so without further delay, I want to share with you some of the tools NIH has been working on to answer that call.
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I am very pleased to announce the availability of a new website on Scientific Data Sharing. Whether you are involved in an NIH-funded project and want to understand which sharing policies apply to your research and how to comply, or you are a researcher looking to access scientific data from NIH-affiliated repositories, this site is for you.
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If you’re working on NIH-funded research, you probably know the new NIH Data Management and Sharing (DMS) Policy goes into effect January 25, 2023. Don’t worry — there are several resources in the works to help you prepare! In April we are launching a new NIH Scientific Data Sharing website, a one-stop shop for all the information you need to know about NIH sharing policies.
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Dr. Lyric Jorgenson provides an update on what NIH is doing to make our data management and sharing efforts a success on the one-year mark prior to the Data Management and Sharing (DMS) Policy’s effective date.
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NIH continues to work with the research community to ensure we address resource needs associated with the NIH Data Management and Sharing Policy. Today the NIH Office of Science Policy is releasing a new set of FAQs on questions we have heard over the past year, and are also seeking public comment on a new resource for researchers that promotes responsible management and sharing of American Indian/Alaska Native (AI/AN) participant data.
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NIH is committed to ensuring that study participants are equal partners in research and have input into how their data and biospecimens are collected and used in the future. At the heart of any research effort lies the need for transparent and clear conversations between researchers and prospective participants about mutual goals and expectations regarding sharing practices.
To assist in facilitating this dialogue, NIH has been working with stakeholders to identify informed consent language “best practices” capable of effectively describing how data and biospecimens will be stored and shared for future research. From these conversations, NIH has developed a new resource that we are seeking the community’s feedback on. The resource describes points to consider when addressing this issue, and provides sample consent language that researchers can tailor based on their own unique study needs…read on for more…
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Common Data Elements (CDEs) are a type of health data standard that is commonly used and reused in both clinical and research settings. CDEs provide a way to standardize data collection—ensuring that data are collected consistently, and otherwise-avoidable variability is minimized.
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Common Data Elements foster rigor, facilitate data sharing, and allow multiple datasets to be integrated. They also help make data more FAIR (Findable, Accessible, Interoperable, and Reusable). Many different CDEs are currently in use and can vary across research disciplines, so we would encourage researchers check out databases like the NIH CDE Repository for examples, tools, and other related resources. Through a recently released Request for Information (NOT-LM-21-005), we seek your thoughts on how you use CDEs, potential challenges to their adoption, and how NIH might facilitate and incentivize their use to help us plan future CDE-related efforts.
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Today, nearly twenty years after the publication of the Final NIH Statement on Sharing Research Data in 2003, we have released a Final NIH Policy for Data Management and Sharing. This represents the agency’s continued commitment to share and make broadly available the results of publicly funded biomedical research. We hope it will be a critical step in moving towards a culture change, in which data management and sharing is seen as integral to the conduct of research. Responsible data management and sharing is good for science; it maximizes availability of data to the best and brightest minds, underlies reproducibility, honors the participation of human participants by ensuring their data is both protected and fully utilized, and provides an element of transparency to ensure public trust and accountability.
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