The New NIH Data Management and Sharing Policy 2023 – Why Sharing is Caring
“The extraordinary effort to speed the development of treatments and vaccines in response to the COVID-19 pandemic has put into sharp relief the need for the global science community to share scientific data openly.”
This blog post is part of the Data Management and Sharing series. See also:
7 min read
The National Institute of Health (NIH) has recently issued a new final NIH Policy for Data Management and Sharing. This new policy will come into effect on January 25, 2023, and will replace the 20-years old 2003 NIH Data Sharing Policy currently in effect.
The new policy will require researchers submitting an NIH research application to submit a plan outlining how scientific data from their research will be managed and shared or, if applicable, state why data sharing will not be possible.
In concert with the policy release, the NIH has already provided additional supplementary information on elements of a data management and sharing plan, allowable costs, and selecting a data repository.
Read on to find out more details about the new NIH data management and sharing plan and tips on how to make its implementation a smooth process.
What the new NIH data sharing policy entails and whom it affects
The new data management and sharing policy has been years in the making and includes valuable feedback collected from all stakeholders involved during this time. The two main requirements of the final policy are (1) the submission of a Data Management and Sharing (DMS) plan; and (2) compliance with the approved Plan. The DMS plan should contain details about the software or tools needed to analyze the research data, when and where the scientific data will be published and any special considerations for accessing or distributing that research data. When submitting a funding application from 2023, the NIH will ask for a DMS plan at the time of submission. This is an important message, highlighting how planning and budgeting for data management and sharing need to occur in parallel with the research itself.
The policy applies to all research funded or conducted by NIH that will generate scientific data. Currently, in the U.S., NIH funds around 300,000 researchers and 2,500 institutions annually. Investigators will be held accountable for complying to their proposed data management and sharing plans after they have been awarded a grant.
Regarding the timeline of data sharing, the new guidelines state that “shared scientific data should be made accessible as soon as possible, and no later than the time of an associated publication, or the end of performance period, whichever comes first“. This decision was taken because different disciplines have different standards of timeline for publishing, with many factors involved, such as embargoes on research data. Of course, data sharing should occur in a timely fashion, and having an electronic lab notebook where all scientific data are stored and categorized is a big help to streamline how scientific data are shared.
As expressed in NIH’s view, data sharing is a critical step to further advance scientific discoveries.
“Data sharing promotes many goals of the NIH research endeavor. Data sharing allows scientists to expedite the translation of research results into knowledge, products, and procedures to improve human health. Data should be made as widely and freely available as possible while safeguarding the privacy of participants and protecting confidential and proprietary data.”
There will be some exceptions if certain factors (i.e., ethical, legal, or technical) may necessitate limiting data sharing to some extent, and the NIH Office of Science Policy addresses them in their FAQs section. For example, an exemption could be if the informed consent does not allow or limit the extent of data sharing or if the privacy or safety of research participants would be at risk even with Certificates of Confidentiality in place. Other examples are if an explicit federal or local law prohibits the disclosure or if the data sets cannot be digitized with a reasonable effort. On the other hand, examples of reasons that would generally not be considered justifiable factors to limit scientific data sharing are:
- researchers anticipate the data will not be widely used
- data sets are considered too small
- data are not considered to have a suitable repository
Benefits and drawbacks of the NIH Data Management & Sharing Plan
This new data management and sharing policy will, of course, set a new global standard for biomedical research, and it has been defined as a “seismic shift“. It is also hoped that it could introduce a sort of ripple effect that could induce smaller funding agencies and other industries to implement similar changes. However, some researchers also express doubts about it. Specifically, there are concerns about the amount of extra time the researchers will need to spend to comply with this new data management and sharing policy, especially given that most laboratories don’t have dedicated managers who oversee research data. In this context, digital data management tools like electronic lab notebooks can make a huge difference. Nevertheless, it is clear that, in the long term, this policy will boost the public trust in science, justifying the initial extra effort.
Learn more about the data management policies of the future.
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The role of ELNs, lab digitalization and the associated benefits
Even before the new NIH data management and sharing policy, the agency had already identified the principles of good record keeping, stating that “Records should be legible, clear, timely, thorough, complete, secure, backed-up, and well-organized.” In addition, all entries should be in English. According to the NIH, good records should describe who did the experiment and when, what was done exactly, why (the scientific rationale behind it), what project it was part of, how it was done (including detailed methodology and materials used), research findings and outcomes, and the researcher’s interpretation of them.
Now, among the desirable characteristics for the data repositories to be used in accordance with the NIH data management and sharing plan, there are:
- Unique Persistent Identifiers (UPI)
- Long-Term Sustainability
- Curation and Quality Assurance
- Free and Easy Access
- Broad and Measured Reuse
- Clear Use Guidance
- Security and Integrity
- Common Format
- Retention Policy
These, which resemble the FAIR principles, are all factors that can be ensured by the use of an ELN tailored to the specific needs of the research program. Electronic lab notebooks not only allow easier input of scientific data and experimental outcomes in a uniform format, but they also enable collaborators to share and add more records. Compared to print lab notebooks, ELNs provide advanced features that allow for data integration storage, searchability, and data analysis. Importantly, they can be password protected and meet all other necessary safety requirements. Thanks to their ease of use, flexibility and large capacity to store data, digital lab notebooks’ popularity is rapidly increasing. Hopefully, after the implementation of the 2023 NIH policy, there will be a cultural shift where data sharing becomes the norm, and one can predict that electronic lab notebooks will completely take over their print counterpart.
How data sharing is connected to reproducibility and sustainability
Even before the publication of these new guidelines, it was no news that reproducibility is a big issue in research, especially in the biomedical field. In 2021, one of the largest reproducibility studies ever conducted, an eight-year attempt to replicate high-impact cancer studies as part of the Reproducibility Project: Cancer Biology found that less than half of the assessed experiments stood the test of time. For none of the 193 experiments included in the study the original paper provided enough details to enable the repetition of the experiments. It has been estimated that each year, scientists in the U.S. spend a staggering $28 billion attempting to replicate research findings of basic biomedical research that cannot be successfully reproduced. Data sharing and appropriate record-keeping to enhance reproducibility are particularly important in research involving human subjects (patients or healthy controls).
“Irreproducible studies not only waste taxpayers’ money, but also undermine public trust in science. We want to make sure that we’re making good on the nation’s investment and fostering transparency and accountability in research”.
Dr. Lyric Jorgenson, Acting Associate Director for Science Policy and Acting Director of the NIH Office of Science Policy
In this context, and more so from 2023, using an ELN can help your team tackle the reproducibility of research data by providing a centralized data management system with information that is easy to track, share and ultimately reproduce.
Complying with the new NIH Data Management and Sharing Policy with the help of an electronic lab notebook will improve the reproducibility of your research. It will also make a difference in resources utilization, enhancing the overall sustainability of the life science research ecosystem. Echoing what Dr. Jorgenson from NIH said, taxpayer’s money should not be wasted with the use of unnecessary resources due to poor reproducibility and the need to often repeat experiments. Therefore, improved data recording and data sharing can significantly affect both reproducibility and sustainability. It’s a win-win situation!
If you like this post also check out:
- NIH Data Management and Sharing Policy – 9 tips for preparing your DMS plan [Guide]
- Data management and sharing: Paper vs OneNote vs SciNote [Comparison]
- Implementing SciNote Electronic Lab Notebook in an academic lab [Video]
- Using Data Lineage and Traceability to Optimize Publishing Potential by Technology Networks
- NIH issues a seismic mandate: share data publicly by Nature
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