Abstract: In this talk I will present some of the work we are doing as a part of our work with the NSF Northeast Big Data Hub on developing a shared platform to automate the process of licensing and sharing data. Sharing of data sets can provide tremendous mutual benefits for industry, researchers, and nonprofit organizations. A major obstacle is that data often comes with prohibitive restrictions on how it can be used. Beyond open data protocols, many attempts to share relevant data sets between different stakeholders in industry and academia fail or require a large investment to make data sharing possible. We are addressing these challenges by: 1) Creating a licensing model for data that facilitates sharing data that is not necessarily open or free between different organizations, 2) Developing a prototype data sharing software platform, ShareDB that will enforce agreement terms and restrictions for the licenses developed, and (3) Developing and integrating relevant metadata that will accompany the datasets shared under the different licenses, making them easily searchable and interpretable.
Bio: Samuel Madden is a Professor of Electrical Engineering and Computer Science in MIT's Computer Science and Artificial Intelligence Laboratory. His research interests include databases, distributed computing, and networking. Research projects include the C-Store column-oriented database system, the CarTel mobile sensor network system, and the Relational Cloud "database-as-a-service". Madden is a leader in the emerging field of "Big Data", heading the Intel Science and Technology Center (ISTC) for Big Data, a multi-university collaboration on developing new tools for processing massive quantities of data. He also leads BigData@CSAIL, an industry-backed initiative to unite researchers at MIT and leaders from industry to investigate the issues related to systems and algorithms for data that is high rate, massive, or very complex. Madden received his Ph.D. from the University of California at Berkeley in 2003 where he worked on the TinyDB system for data collection from sensor networks. Madden was named one of Technology Review's Top 35 Under 35 in 2005, and is the recipient of several awards, including an NSF CAREER Award in 2004, a Sloan Foundation Fellowship in 2007, best paper awards in VLDB 2004 and 2007, and a best paper award in MobiCom 2006. He also received a a "test of time" award in SIGMOD 2013 (for his work on Acquisitional Query Processing in SIGMOD 2003), and a ten year best paper award in VLDB 2015 (for his work on the C-Store system).