The National Institutes of Health (NIH) is looking to improve its data management and sharing challenges with the new NIH Policy on Data Management and Sharing that will become effective on Jan. 25, 2023.
The new policy will replace the 2003 NIH Data Sharing Policy still in effect. Susan Gregurick, associate director for data science and director of the Office of Data Science Strategy at NIH explained that data management and data sharing is “something that’s on everybody’s mind at NIH and in the community.”
“We, of course, want to align with our NIH Data Management and Sharing policy,” Gregurick said on March 31 during a GovernmentCIO Media and Research event. “Everybody is thinking about it. We’re coordinating across all of our 27 institutes and centers to provide resources and guidance to the community.”
Gregurick said NIH’s Office of Extramural Research will launch a website in late April with resources for researchers on how to develop a data management plan, repositories to share data in, and navigate the complexities of data and policies for different programs.
She also said NIH is currently preparing its data repositories for new training on data management and data sharing for the community, including an April 6 webinar with the data curation network on how researchers can develop data management plans.
The new data policy will be helpful because NIH “is a broad community with many different expectations,” Gregurick said.
“The overall goal is to provide a modernized, integrated biomedical data ecosystem and that sounds super easy, but actually, it’s really not,” she said. “It’s quite challenging because of the diversity of science across NIH and a diversity of needs and capabilities. An overall one-size-fits-all strategy is very, very challenging.”
“Some of the problem is just that data in the biomedical space is very heterogeneous, and at some point, we’re going to have to embrace this,” she added. “We’ve spent an enormous amount of time and energy on efforts in harmonization, and creating new datasets that are more AI-ready, and these have been successful, but it just sometimes feels like it’s a never-ending and hard-to-win strategy.”
Gregurick went on to say she believes NIH needs to start to embrace the fact that data is going to come in heterogeneous forms, and accept that it’s “very hard to keep pace in a harmonization-driven world.”