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the MIT Big Data Living Lab Project


We now have the ability to collect and acquire digital information at an unprecedented rate across practically all aspects of our life including healthcare, financial transactions, social interactions, education, energy usage, transportation, environmental monitoring and so on.  "Big Data" is about harnessing all of this digital information by combining and analyzing it in completely new ways to make better predictions and ultimately, better decisions.  Over the next decade Big Data has the potential to profoundly change the way we live, work and play.  Big Data also introduces unique challenges when it comes to managing and protecting personal privacy. Big Data privacy issues are complex, introducing a host of ethical, legal, policy and technical questions.  How do we build on Big Data’s potential for good, while maintaining essential privacy protections?  And, how do we design future technologies, policies, and practices to get that balance right for society? 

Our goal with this project is to demonstrate how organizations can leverage data in the future, including how we collect, manage, and use personal information, from setting appropriate policies to demonstrating systems that can implement it in practice.  In terms of integrating, analyzing, and sharing data, MIT faces similar challenges to many organizations across different sectors whether in industry or government.   A Big Data testbed at MIT will allow us to demonstrate how data can be used to better understand and improve our community; collectively explore ways to address technical and privacy challenges; and demonstrate new approaches and solutions emerging from the research community.

A Living Lab
What is a "Living Lab"?  It is a open innovation ecosystem, operating in a specific context, integrating research and innovation processes within a public-private partnership.*  In short, a testbed for research and experimentation.
We propose creating a Big Data Living Lab at MIT to allow the community to access, share, and use data about life on campus.  Why? To explore issues around large-scale data integration, privacy, visualization, and performance, as well as social implications of big data.