Managing Uncertain Data

                          Anish Das Sarma
                    Stanford University InfoLab

The recent ubiquity of uncertain data in modern-day applications (such
as data integration, sensor networks, and scientific experiments) has
resulted in a growing need for principled techniques in dealing with
uncertainty. At Stanford, we have been developing Trio: a system for
managing data, uncertainty, and lineage. In the first part of the
talk, I will describe some challenges in managing uncertain data in
Trio, and how lineage helped us overcome them. Lineage allows for a
simple yet expressive model for representing uncertain data, and it
enables efficient query processing.

The next part of the talk covers uncertain data management in the
context of automated data integration. I will describe a
self-configuring data integration system that produces high-quality
answers with no human intervention. The system is based on
probabilistic mediated-schemas and schema-mappings. I will present
results on the relative expressive power of probabilistic mediated
schemas and mappings, give algorithms for creating them, and describe
extensive experimental results.

Finally, I will describe briefly some of my other topics and results,
and my plans for future research.