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University of Wisconsin–Madison

New NIH requirement enhances open data sharing

By Natasha Kassulke,, (608) 219-8042

Sharing scientific data can accelerate research discovery, enhance research reproducibility and provide accessibility to unique datasets. As the short time to COVID vaccine development showed the world, sharing of scientific data can also expedite the translation of research results into products and procedures to improve human health.

It’s based on those benefits that the National Institutes of Health (NIH) has issued a new requirement for grantees to ensure sharing of data whenever possible.

“Effective for applications starting Jan. 25, 2023, and after, all NIH-supported researchers producing scientific data will be expected to submit a data management & sharing plan as part of their proposals under the Data Management and Sharing (DMS) Policy,” explains Cameron Cook, chair of Research Data Services (RDS) for the UW–Madison Libraries.

Cook and the RDS team helps connect researchers with data and digital scholarship support on campus. This includes supporting researchers as they share and deposit their data to comply with a funding agency or publisher requirements, including helping create a data management plan as part of their proposals and making their data publicly accessible through the campus repository.

Cook explains that updates to a grantees’ plan will be expected within annual progress reporting (i.e., Research Performance Progress Report) and compliance with the plan is monitored over the course of the funding/reporting intervals and at the end of the grant.

To read more about the forthcoming policy, visit: .

The NIH has a helpful FAQ for the new policy that is continually updated.

Trisha Adamus, a member of RDS team and research data librarian for Ebling Library, explains that the new policy only applies to those applications submitted on or after Jan. 25, 2023. Those grants currently funded are not covered by the policy.

Adamus notes that there are more than 1,000 principal investigators on campus with NIH grants in place.

Some PIs on campus have already embraced open data sharing plans.

In 2016, UW virologist David O’Connor was featured in Nature for his Zika Experimental Science Team’s role in posting raw data in real-time on the amount of Zika virus detected in the blood, saliva and urine of three Indian rhesus macaques. Sharing the data helped research outcomes of other researchers.

Two years ago, the American Family Insurance Data Science Institute posted a collection of COVID-19 resources that demonstrated the contributions data science was making to better understanding the virus. These resources included projections for the virus’ spread and treatment, visualizations, research datasets and code bases, as well as stories about how data scientists are helping the efforts to combat the virus. Semantic Scholar made the COVID-19 Open Research Dataset (CORD-19) accessible online for download and analysis.

Last year, UW graduate student Zheng Yu was named winner of the Wisconsin MRSEC Excellence in Open Science Prize. Yu was working in Bu Wang’s lab at the Grainger Institute for Engineering, when he generated the data as part of his work investigating the relationship between structure and stability in specialized glasses using computer simulations and machine learning. The MRSEC Open Science prize recognizes a researcher or team that has demonstrated an exceptional effort or success in the development and dissemination of data for benefit of the scientific community.

The Department of Radiology has been a leader in data sharing on campus.

“We have been sharing data on,” notes David Harris, research services manager for Radiology. “Our group deals a lot with human subjects data, and our hope is that with the new NIH policy is that UW can move toward repositories where the ongoing sharing burden doesn’t fall to individual groups.”

Dr. Scott Reeder is director of the UW Liver Imaging Research Program, an active NIH-funded group that performs research in technical development and translation of new imaging methods, particularly quantitative imaging biomarkers, to assess liver disease.

“Sharing imaging data – especially quantitative imaging data – is essential to

further major international initiatives in reproducible research” says Reeder. “As new technologies are developed, the ability to re-analyze valuable clinical data can lead to new advances without the need to start clinical trials over from scratch.”

Given the variety of science that NIH supports, the NIH Data Sharing Policy does not require specific ways of documenting, formatting, presenting or transporting data. Applicants are asked to propose the most appropriate means for sharing data according to the specifications of their research project and area of science, in compliance with policies and regulations governing research awards.

DoIT can also support researchers as they pursue options for data storage and sharing.

Those with questions about the policy, data sharing or data management plans, are asked to reach out to Research Data Services (RDS). At the RDS website, one can learn more about the policy,  about DMPTool – a tool that assists with writing and reviewing data management plans, and about the data repositories available to PIs through campus where they can share their data.


NIH Data Management and Sharing Drop-ins Scheduled

Drop in and learn about the forthcoming NIH data sharing requirements. Bring your lunch and your questions. Research Data Services is providing a series of drop-in sessions over the lunch hour through Fall that will provide a brief overview of the new policy requirements, an overview of data management and sharing plans, and touch on repository options for data sharing. Time will be allowed for a discussion to follow attendees’ interests. These sessions are intended to be informal. Drop in and out as needed.

 SMPH, Health Sciences Learning Center 2158 (Noon to 1 p.m.)

  • Oct. 5 and 19
  • Nov. 2, 16 and 30

Steenbock, BioCommons (Noon to 1 p.m.)

  • Oct. 12 and 26
  • Nov. 9