Grant: Discovery Grants Program - Individual

Available information in real-life is often incomplete, imprecise, uncertain, and/or possibly inconsistent. To model the real world, we need the ability to represent and manipulate such data with imperfection. This proposal focuses on uncertainty, i.e., data of limited reliability. Intuitively, a piece of data is uncertain if its truth is not established definitely. Uncertainty could modeled simply be a real value in the unit interval [0,1] or as more complex objects, i.e., a collection of values or symbols. Uncertainty has been studied extensively in artificial intelligence and database research, resulting in significant achievements. In the database self assessment reports in 1991 and 2005, uncertainty has been identified as an important challenge in database research: ""Further research [in uncertainty] is essential as we must learn not only to cope with data of limited reliability, but also do so efficiency, with massive amounts of data."" Our proposal is motivated by this recognition, and stress the need for declarative programming and powerful tools and techniques to support many existing and emerging applications that deal with uncertain data. Our goal is to contribute to theoretical and practical foundations towards the development of a desired database management system (DBMS) with uncertainty, by using, adopting, and extending existing tools, techniques, and results. Recently we have witnessed increased research activities in for building such systems, e.g., Orion (Purdue) and Trio (Stanford), which treat uncertain data as a first-class citizen. What is stressed in our proposal, however, is that such a system has to be made aware of the nature and the kind of uncertainty modeled in the data, captured through the so-called parameters that are carefully selected by a user and includes uncertainty domain and uncertainty combination functions. These parameters will be considered by new query processing and optimization techniques, to be developed in this proposal, in order to carry out the required operations correctly and efficiently. We plan to build our parametric DBMS by extending PostgresSQL -- an object-oriented relational open-source database system.