More than $23 million in grants from the National Institutes of Health - courtesy of the NIH's Big Data to Knowledge (BD2K) initiative - have launched two Stanford-housed centers of excellence bent on enhancing scientists' capacity to compare, contrast and combine study results in order to draw more accurate conclusions, develop superior medical therapies and understand human behaviors.
Huge volumes of biomedical data - some of it from carefully controlled laboratory studies, increasing amounts of it in the form of electronic health records, and a building torrent of data from wearable sensors - languish in isolated locations and, even when researchers can get their hands on them, are about as comparable as oranges and orangutans. These gigantic banks of data, all too often, go unused or at least underused.
But maybe not for long. “The proliferation of devices monitoring human activity, including mobile phones and an ever-growing array of wearable sensors, is generating unprecedented quantities of data describing human movement, behaviors and health,” says movement-disorders expert Scott Delp, PhD, director of the new National Center for Mobility Data Integration to Insight, also known as the Mobilize Center. “With the insights gained from subjecting these massive amounts of data to state-of-the-art analytical techniques, we hope to enhance mobility across a broad segment of the population," Delp told me.
Directing the second grant recipient, the Center for Expanded Data and Retrieval (or CEDAR), is Stanford's Mark Musen, MD, PhD, a world-class biomedical-computation authority. As I wrote in an online story:
[CEDAR] will address the need to standardize descriptions of diverse biomedical laboratory studies and create metadata templates for detailing the content and context of those studies. Metadata consists of descriptions of how, when and by whom a particular set of data was collected; what the study was about; how the data are formatted; and what previous or subsequent studies along similar lines have been undertaken.
The ultimate goal is to concoct a way to translate the banter of oranges and orangutans, artichokes and aardvarks now residing in a global zoo (or is it a garden?) of diverse databases into one big happy family speaking the same universal language, for the benefit of all.
Previously: NIH associate director for data science on the importance of “data to the biomedicine enterprise”, Miniature wireless device aids pain studies and Stanford bioengineers aim to better understand, treat movement disorders