Every day, 2.5 quintillion bytes of data are created. This data comes from digital pictures, videos, posts to social media sites, intelligent sensors, purchase transaction records, cell phone GPS signals to name a few. This is “Big Data.”
There is a great interest both in the commercial and in the research communities around Big Data. It has been predicted that “analyzing Big Data will become a key basis of competition, underpinning new waves of productivity growth, innovation, and consumer surplus,” according to research by McKinsey.
But very few people seem to look at how data can be used specifically for solving social problems. Why is this? What can be done in the international research community to make sure that some of the most brilliant ideas do have an impact also for social issues?
In order to make data’s potential for social good a part of the “Big Data” discussion, I invited a distinguished panel of experts to discuss how Big Data can be used to create Social Capital. The panelists are: Roger Barga (Microsoft Research, group lead eXtreme Computing Group, USA), Laura Haas (IBM Fellow and Director Institute for Massive Data, Analytics and Modeling IBM Research, USA), Alon Halevy (Google Research, Head of the Structured Data Group, USA), and Paul Miller (Consultant, Cloud of Data, UK).
We asked the panelists if they believe it is possible to conduct research for a corporation and/or a research lab, and at the same time make sure that the potential output of our research has also a social impact. Is it possible to dig into Big Data to help people in need? Preventing/predicting natural catastrophes, helping offering services "targeting" to people and structures in social need?
Just a few examples of leveraging current and future data tools and research for social good:
Harvard researchers found that Twitter data could be analysed to track the spread of Cholera on Haiti in a way that proved “substantially faster” than traditional techniques. According to Mathew Ingram’s write-up of the research, “What the Harvard and HealthMap study shows is that analyzing the data from large sets like the tweets around Haiti isn’t just good at tracking patterns or seeing connections after an event has occurred, but can actually be of use to researchers on the ground while those events are underway. [Paul’s emphasis]
As one simple example, a recent Danish Journalism Award was given to a nice visualization of data about which doctors are being sponsored by the medical industry. The ability to communicate this data with the public is certainly part of the Big Data agenda.
One such example in science is Jim Gray and Alex Szalay’s collaboration to build a virtual observatory for astronomy, which leveraged relational database technology. The SDSS Sky Server has since supported hundreds of researchers and resulted in thousands of publications over the years.
Much of our "Smarter Planet" related research is around utilizing more intelligently the large amounts of data coming from instrumenting, observing, and capturing the information about phenomena on planet earth, both natural and man-made.
The full text of the interview can be read at the ODBMS Industry Watch Blog.
Roberto Zicari is Editor of ODBMS.org and professor of Database and Information Systems at Frankfurt University.
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