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New England Database Society

Friday, February 16, 2007

sponsored by Sun Microsystems

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MauveDB: Managing Uncertain Data using Statistical Models

Amol Deshpande
University of Maryland

Friday, February 16, 2007, 4:00 PM
Volen 101, Brandeis University

(preceded by a wine and cheese reception at 3:00 pm)


Real-world data, especially that generated by distributed measurement infrastructures such as wireless sensor networks, tends to be incomplete, imprecise, and erroneous, and hence rarely usable in its raw form. The traditional approach to dealing with this problem is to first synthesize (filter) such data using a statistical or a probabilistic model, thus resulting in a more robust interpretation of the data. However current database systems do not provide adequate support for statistical modeling of data, especially when those models need to be frequently updated as new data arrives in the system. Hence most scientists and engineers, who depend on models for managing their data, do not use database systems for archival or querying at all; at best, databases serve as persistent raw data stores.

In this talk, I will present our approach to integrating statistical and probabilistic models into database systems, in the context of data management in wireless sensor networks. I will first present a data acquisition approach for wireless sensor networks that demonstrates how models can be used both to provide more meaningful answers to user queries, and to significantly reduce the energy cost of acquiring data from the underlying sensing devices. I will then present our recent work on the "MauveDB" system, which uses an abstraction called "model-based views" to seamlessly integrate models into traditional relational database systems.

Speaker Bio:

Amol Deshpande is an Assistant Professor at the University of Maryland at College Park. He received his PhD from UC Berkeley in 2004. His research interests are in adaptive query processing, sensor network data management, and statistical modeling of data. He is a recipient of the National Science Foundation CAREER award.

Maintained by Dina Goldin dqg AT