The National Institutes of Health is facing significant challenges when it comes to accessing, managing, analyzing, integrating and making use of the huge amounts of data generated by the biomedical research community.

To get a better handle on the data produced by researchers, NIH has developed its first strategic plan to help the agency keep pace with the rapid changes in biomedical data science.

“Our nation and the world stand at a unique moment of opportunity in biomedical research, and data science is an integral contributor,” states the plan. “Understanding basic biological mechanisms through NIH-funded research depends upon vast amounts of data and has propelled biomedicine into the sphere of ‘Big Data’ along with other sectors of the national and global economies.”

In particular, NIH’s data science plan seeks to address the following challenges:

  • Growing costs of managing data diminish the agency’s ability to enable scientists to generate data for understanding biology and improving health.
  • The current data-resource ecosystem is siloed and is not optimally integrated or interconnected.
  • Datasets exist in many different formats and are often not easily shared, findable or interoperable.
  • Currently, no general system exists to transform or harden innovative algorithms and tools created by academic scientists into enterprise-ready resources that meet industry standards of ease of use and efficiency of operation.

“Because of these issues, NIH has adopted a unified vision, and a corporate strategy for attaining that vision, that will best serve the biomedical research enterprise in the coming decades,” states the plan. “This document, the NIH Strategic Plan for Data Science describes NIH’s overarching goals, strategic objectives, and implementation tactics for modernizing the NIH-funded biomedical data-resource ecosystem.”

Also See: NIH launches ‘Data Commons’ program to aid researchers

Specifically, the plan has five overarching goals:

  • Create a highly efficient and effective biomedical research data infrastructure.
  • Promote modernization of the data-resources ecosystem.
  • Support the development and dissemination of advanced data management, analytics and visualization tools.
  • Enhance workforce development for biomedical data science.
  • Enact appropriate policies to promote stewardship and sustainability.

To achieve these goals, NIH plans to hire a chief data strategist to guide the development and implementation of the agency’s data science activities and to serve as the lead for implementing the strategic plan.

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