The NIH Makes a Big Push for Big Data

Scientists will tell you that the single greatest hindrance to their research is time. And with the growing collection of data amassing globally, their schedules haven’t gotten any freer.

In fact, the National Institutes of Health said the growth of their biomedical databases had resulted in data scientists spending 80 percent of their time collecting and organizing data rather than analyzing it. By 2025, genomic information alone is expected to “equal or exceed” the quantity of data currently produced by data giants YouTube and Twitter, the agency said.

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That’s great news for advancing personal medicine, but it’s a mammoth task for researchers to sort.

For this reason, NIH recently announced its first “Strategic Plan for Data Science,” which will weave its existing data science efforts into a larger data ecosystem and shape how the agency manages its biomedical data. The agency hopes this will allow researchers to spend less time processing data and more time analyzing it.

“Accessible, well-organized, secure, and efficiently operated data resources are critical to modern scientific inquiry. By maximizing the value of data generated through NIH-funded efforts, the pace of biomedical discoveries and medical breakthroughs for better health outcomes can be substantially accelerated,” the agency said in a statement.

Most biomedical data is highly scattered and exists in a wide variety of formats that complicates researchers’ ability to use research data generated by their peers, creating the need for extensive data cleaning.

The new plan has a number of goals to address these issues, including: supporting an efficient biomedical research data infrastructure; promoting the modernization of the data ecosystem; promoting advanced data management, analytics, and visualization technologies; supporting workforce development; and creating policies that make these steps sustainable.

The plan will also ensure that all data-science activities and products supported by the agency continue to adhere to the FAIR principles, meaning that data is Findable, Accessible, Interoperable, and Reusable.

Following the announcement, Robert Alpern, MD, dean of the Yale School of Medicine, said this was an “important area” and that he was pleased that NIH was “dealing with this as a high priority.”

In its effort to modernize the way it stores, processes, and publishes biomedical data, the agency also said it would hire its first chief data strategist to oversee the plan.

The data chief will be involved with data intensive research initiatives such as the All of Us program—which aims to gather data from 1 million people in the US to accelerate research and improve health—the BRAIN Initiative, the Cancer Moonshot, and the Opioid Initiative. The data head will also serve as NIH’s advocate and representative in global data science efforts.

The basics of the data strategy are already underway, but the NIH said it expects to begin implementation in the next 12 months, while continuing, “to seek community input” throughout the implementation. It also noted that the plan would likely require “frequent course corrections” as technology and data needs evolve.

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