DLS - Renée Miller

Renée Miller
University of Toronto

​Big Data Curation
 

​Abstract: Big data has been described as large, dynamic or highly heterogeneous data that requires new forms of processing to enable enhanced decision making and insight discovery. Many of these new forms of processing can be described as data curation —that is, the care of data to ensure it maintains its value over time. In this talk, I describe our experience in curating several open data sets. I overview how we have adapted some of the traditional solutions for aligning data and creating semantics to account for the three Vs of big data — volume, velocity and variety.

​Biography: Renée J. Miller received BS degrees in Mathematics and in Cognitive Science from the Massachusetts Institute of Technology. She received her MS and PhD degrees in Computer Science from the University of Wisconsin in Madison, WI. She received the Presidential Early Career Award for Scientists and Engineers (PECASE), the highest honour bestowed by the United States government on outstanding scientists and engineers beginning their careers. She received the National Science Foundation Early Career Award (formerly, the Presidential Young Investigator Award) for her work on data integration.

She is a Fellow of the ACM, the President of the VLDB Endowment, and the Program Chair for ACM SIGMOD 2011 in Athens, Greece. Her research interests are in the efficient, effective use of large volumes of complex, heterogeneous data. This interest spans data integration, data exchange, knowledge curation and data sharing. She is a Professor and the Bell Canada Chair of Information Systems at the University of Toronto. In 2011, she was elected to the Fellowship of the Royal Society of Canada (FRSC), Canada's national academy.