NIH launches Data Commons pilot
The pilot will test ways to store, access and share biomedical data and associated tools in the cloud so that they are findable, accessible, interoperable and reusable.
The National Institutes of Health has launched its NIH Data Commons Pilot Phase, a project to test ways to store, access and share biomedical data and associated tools in the cloud so that they are findable, accessible, interoperable and reusable (FAIR).
During the four-year pilot phase, researchers will be working with three high-value datasets to determine what policies, processes and architectures they need to accelerate new biomedical discoveries.
“Harvesting the wealth of information in biomedical data will advance our understanding of human health and disease,” said NIH Director Dr. Francis S. Collins. “However, poor data accessibility is a major barrier to translating data into understanding. The NIH Data Commons Pilot Phase is an important effort to remove that barrier.”
The NIH Data Commons will be a community-controlled cloud infrastructure to support collective uses of computing, storage and data for biomedical research by NIH and its academic and industry collaborators.
To start developing the capabilities needed to make the Data Commons a reality, NIH made 12 awards, totaling $9 million, for projects that will help make data transparent and interoperable, safeguard patient data and encourage community buy-in for standards. The 12 awardees will form the core of an NIH Data Commons Pilot Phase Consortium -- a group of data scientists, IT engineers, cloud service providers and biomedical researchers. This consortium will develop processes for FAIR data management and create a roadmap for building the Data Commons.
NIH also will be working with MITRE Corp. to assure cost-effective cloud-based computing and storage for scientific data; analyses related to usage, cost, and comparative business models; and other considerations to assure long-term viability of NIH data science efforts.
The pilot phase also will inform future data management models based on how frequently particular data sets are used, who uses them and whether or how end-users could contribute to the costs of sustaining the resource.
The pilot is expected to span fiscal years 2017-2020, with an estimated total budget of approximately $55.5 million, pending available funds, NIH said.