The objective of this project is to design and develop a data management system that supports query processing on continuous uncertain data by returning a full probability distribution of query output and optimizes such processing for performance. This project includes four thrusts: (1) supporting continuous uncertain data processing using both the traditional relational model and the array model; (2) addressing complex correlation that arises in continuous uncertain data processing using new statistical graphical models; (3) supporting arbitrary user-defined functions, besides standard query operations, by exploring advanced techniques such as Gaussian processes and functional interpolation; and (4) developing a prototype system and evaluating it using real-world applications. Expected results include statistical models and techniques, data storage schemes, query processing and optimization techniques, and a publicly available prototype to fully support query processing on continuous uncertain data.
The results of the project can benefit applications such as severe weather monitoring and computational astrophysics, as well as the broader scientific community. Since applications such as tornado detection may trigger actions based on derived information, the ability to characterize uncertainty of output may result in significant social impacts. This project also integrates research and education with curriculum development and engaging women in research through college outreach and CRA's distributed mentor program. The results of the project are disseminated at the project web site: http://claro.cs.umass.edu.