On June 4, the National Institutes of Health (NIH) released its first Strategic Plan for Data Science. The plan outlines steps the agency will take to modernize research data infrastructure and resources and to maximize the value of data generated by NIH-supported research.
Data science challenges for NIH have evolved and grown rapidly since the launch of the Big Data to Knowledge (BD2K) program in 2014. The most pressing challenges include the growing costs of data management, limited interconnectivity and interoperability among data resources, and a lack of generalizable tools to transform, analyze, and otherwise support the usability of data for researchers, institutions, industry, and the public.
The goals of the NIH Strategic Plan for Data Science are to:
- support an efficient, effective data infrastructure by optimizing data storage, security, and interoperability;
- modernize data resources by improving data repositories, supporting storage and sharing of individual data sets, and integrating clinical and observational data;
- develop and disseminate both generalizable and specialized tools for data management, analytics, and visualization;
- enhance workforce development for data science by expanding NIH’s internal data science workforce and supporting expansion of the national research workforce, and by engaging a broader community of experts and the general public in developing best practices; and
- enact policies that promote stewardship and sustainability of data science resources.
As part of the implementation of the strategic plan, the NIH will hire a chief data strategist. For information about the position, see the job announcement.