What if you could predict domestic abuse two years in advance? Or understand the brain’s intricate physical structure, connection by microscopic connection?

What if we needed new ways to think about privacy and how personal information is used today? And what if existing data — the vast mountains generated by modern science, by government and business, and by our every digital move — offered a promise of discovery as exciting as that beyond new scientific frontiers, but only if we know how to understand it?

Across Harvard, faculty members, students, and researchers are examining those questions, engaging the world’s latest information revolution, the one in “big data.” Big data is an offspring of the computer revolution, which has blessed scientists with ever-more powerful computers and analytic tools, has transformed the way we communicate and interact, and has turned each cellphone-equipped one of us into a walking treasure trove of information.

In some ways, “big data” is just what it sounds like. It’s the massive amounts of information generated and gathered by modern technology. It is what we’d traditionally consider scientific data, only in vast quantities just recently collectible through innovative sensors, sampling techniques, microchip arrays, DNA analysis, satellite instruments, chemical screening, and the like. It’s data pouring in from the genome, the proteome, the microbiome. It’s climate data, screening data for promising drug candidates. It’s data on health, both of a person and of the population.

In addition to traditional scientific sources, though, big data is almost everything else now too. New analytical techniques are transforming our ideas of what data is, enabling scientists to analyze for the first time less-traditional forms of information. Our digitally augmented lives, for example, generate an avalanche of it each day, in tweets and posts, in web browser histories and credit card purchases, in GPS-marked cellphone calls, in fitness trackers, and ATM transactions.

Nathan Eagle, adjunct assistant professor at the Harvard T.H. Chan School of Public Health, calls it our “data exhaust” and says that with proper analysis it can be used to improve health. Karim Lakhani, Lumry Family Associate Professor of Business Administration at Harvard Business School (HBS), says it’s potential gold to businesses, so he teaches two classes on what it is and how to use it. Jonathan Zittrain, the George Bemis Professor of International Law at Harvard Law School and Harvard Kennedy School, believes that big data — and the algorithms developed to make sense of it — are both exciting and potentially worrisome at the same time, and that thought should be given to who uses it and how. Isaac Kohane, Lawrence J. Henderson Professor of Pediatrics and chair of Harvard Medical School’s (HMS) new Department of Biomedical Informatics, says big data is not just potentially disruptive to the hidebound medical establishment, it’s also potentially lifesaving to its patients.

That’s just a snapshot of the many big-data projects across the University, as researchers increasingly seek out or create from scratch large new data sets and plumb their depths for fresh insights that illuminate the world. Faculty, fellows, students, and staff are figuring out how to manage and understand such data, building places to store it, and finding new, sometimes startling ways to apply it. Students are taking an array of courses across the University, in computational science, computer science, statistics, and bioinformatics, among others, in order to hone their big data skills. Read the entire story here