New NIH data sharing policy

The New NIH Data 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.”

Francis S. Collins, M.D., Ph.D., Director, National Institutes of Health

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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 requesting $500,000 or more 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 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 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 Plan (Plan); and (2) compliance with the approved Plan. The Plan should contain details about the software or tools needed to analyze the data, when and where the raw data will be published and any special considerations for accessing or distributing that data. When submitting a funding application from 2023, the NIH will ask for a 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 results in the generation of scientific data. Currently, in the U.S., NIH funds around 300,000 researchers and 2,500 institutions annually. Investigators are going to be held accountable for the data sharing after they have been awarded a grant. If they do not follow through and share their data, they may not receive additional funding.

Regarding the timeline of data sharing, the new guidelines ask that data “should be made available as soon as practicable,” without specifying a specific time frame. This decision was taken because different disciplines have different standards of timeline for publishing, with many factors involved, such as embargoes on data. Of course, data sharing should occur in a timely fashion, and having an electronic lab notebook where all the records are stored and categorized is a big help to streamline the data sharing process.

As expressed in NIH’s view, all data should be considered for data sharing.

“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.”

New NIH data sharing policy gears

There will be some exceptions if certain factors (i.e., ethical, legal, or technical) may necessitate limiting 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 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 Sharing Plan

This new data 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 the new policy, especially given that most laboratories don’t have dedicated data managers. 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.https://www.scinote.net/lmplementing-an-eln-how-to-get-your-team-on-board/

Learn more about the data management policies of the future.

Get your whitepaper on NIH 2023 and European commission policies for free:

Document preview research data management guide

The role of ELNs, lab digitalization and the associated benefits

Even prior to the new NIH data 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), the 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 sharing plan, there are:

  • Unique Persistent Identifiers (UPI)
  • Long-Term Sustainability
  • Metadata
  • Curation and Quality Assurance
  • Free and Easy Access
  • Broad and Measured Reuse
  • Clear Use Guidance
  • Security and Integrity
  • Confidentiality
  • Common Format
  • Provenance
  • 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.

New NIH guidelines teamwork

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 on 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 sharing policy with the help of an electronic lab notebook will not only 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 want to know more about ELNs and how to transition to a digital lab notebook, contact us, and a SciNote specialist will be able to answer your questions.

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You can also read all our testimonials from academia and industry, showing the time-saving and efficiency advantages of using an ELN.

By Dr Arianna Ferrini, biomedical scientist and medical writer