Capturing Data Uncertainty in High-Volume Stream Processing

University of Massachusetts, Amherst


The goal of this project is to design and develop a stream processing system that captures data uncertainty from data collection to query processing to final result generation. This project takes a principled approach grounded in probability and statistical theory to support uncertainty as a first-class citizen, and efficiently integrate this approach into high-volume stream processing. The project has two main contributions:

CLARO project web page


Project Members


Sponsors

National Science Foundation

III-COR-small: Capturing Data Uncertainty in High-Volume Stream Processing. Yanlei Diao (PI) and Anna Liu (co-PI). National Science Foundation IIS-0812347. Award abstract.

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Last Updated: June 09, 2010