Fereidoon Sadri

On the logical foundations of schema integration and evolution in heterogeneous database systems

Developing a declarative approach to schema integration in the context of heterogeneous database systems is a major goal of this research. We take a first step toward this goal in this paper, by developing a simple logic called SchemaLog which is syntactically higher-order but has a first-order semantics. SchemaLog can provide for a logical integration of multiple relational databases in a federation of database systems. We develop a fixpoint theory as well as a sound and complete proof theory for the definite clause fragment of SchemaLog and show their equivalence to the model-theoretic semantics. We argue that a uniform framework for schema integration as well as schema evolution is both desirable and possible. We illustrate the simplicity and power of SchemaLog with a variety of applications involving database programming (with schema browsing), schema integration, schema evolution, and cooperative query answering.

Modeling Uncertainty in Deductive Databases

Information Source Tracking (IST) method has been developed recently for the modeling and manipulation of uncertain and inaccurate data in relational databases. In this paper we extend the IST method to deductive databases. We show that positive uncertain databases, i.e. IST-based deductive databases with only positive literals in the heads and the bodies of the rules, enjoy a least model/least fixpoint semantics. Query processing in this model is studied next. We extend the top-down and bottom-up evaluation techniques of logic programming and deductive databases to our model. Finally, we study negation for uncertain databases, concentrating on stratified uncertain databases.

Modeling uncertainty in databases

Relational algebra operations were extended to produce, together with answers to queries, information regarding sources that contributed to the answers. The authors previous model is reviewed and the semantic interpretation is presented. It is shown that extended relational algebra operations are precise, that is, they produce exactly the same answers that are expected under the semantic interpretation. Algorithms for computing the reliability of answers to a query are also reviewed and their correctness under the semantic interpretation proposed is proved.<<ETX>>

Reliability of answers to queries in relational databases

The author studies the problem of determining the reliability of answers to queries in a relational database system, where the information in the database comes from various sources with varying degrees of reliability. An extended relational model is proposed in which each tuple in a relation is associated with an information source vector which identifies the information source(s) that contributed to that tuple. The author shows how relational algebra operations can be extended, and implemented using information source vectors, to calculate the vector corresponding to each tuple in the answer to a query, and hence, to identify information source(s) contributing to each tuple in the answer. This also enables the database system to calculate the reliability of each tuple in the answer to a query as a function of the reliability of information sources. >

Non-first normal form universal relations: an application to information retrieval systems

Abstract The relational model has gained wide popularity because it is conceptually simple and provides “physical independence”. Furthermore, the universal relation model provides “logical independence”, while non-first normal form relations further simplify the conceptual view. A number of proposals have been made to apply database techniques to Information Retrieval (DBMIRS); this is principally due to the commonality of functions in Database Management systems and Information Retrieval Systems. The proposals have, most commonly, included attempts to extend the relational model, thus losing some of the inherent simplicity of the relational model. In this paper we propose the use of non-first normal form universal relations to simply the user interface in DBMIRS.

A Data Model for Use with Formatted and Textual Data.

Un modele de donnees regroupe trois composantes: un ensemble dobjets, des operateurs et des lois dintegrite; sa structure peut etre hierarchique, en reseau ou relationnelle. Lapplication a la structure de la recherche documentaire a necessite le plus souvent le recours a une structure relationnelle. A partir dune description des ordres et structures logiques dune recherche documentaire, une analyse algorithmique est faite

Scheduling of page fetches in join operations using B/sub c/-trees

The authors consider B/sub c/-trees in a centralized system with large main memory, and show that in some cases the join operation using B/sub c/-trees out performs other join techniques. The results can be used for estimating the cost of join using B/sub c/-trees and then making a decision regarding the most efficient join technique to be used.<<ETX>>

Recognizing Credible Experts in Inaccurate Databases

While the problem of incomplete data in databases has been extensively studied, a relatively unexplored form of uncertainty in databases, called inaccurate data, demands due attention. Inaccurate data results when data are contributed by various information agents with associated credibility. Though the data itself is total or complete, the reliability of the data now depends on the agents credibility. Several issues of this form of data reliability has been reported recently where the credibility of agents were assumed to be known, static and uniform throughout the database. In this paper we address the issue of credibility maintenance of information agents and take the view that the agent credibility is dynamic and is a function of the database knowledge, the agents performance relative to other agents, and the agents expertise. We present a method to identify agents field of expertise (called the contexts) and use agents context dependent credibility to calculate the reliability of the contextual data.

Aggregate Operations in the Information Source Tracking Method

The Information Source Tracking method, IST, is an approach to the management of uncertain and imprecise data in database systems. In this paper we study the processing of queries involving aggregate operations in the IST method. The problems discussed include producing all possible outcomes of an aggregate query and their probabilities, and determining the probability of a specific outcome. We present algorithms for the evaluation of aggregate queries, and show that some of these problems are intractable.

Trusting an Information Agent

While the common kinds of uncertainties in databases (e.g., null values, disjunction, corrupt/missing data, domain mismatch, etc.) have been extensively studied, a relatively unexplored form of uncertainty in databases, called inaccurate data, demands due attention. Inaccurate data results when data are contributed by various information agents with some known reliability. Though the data itself is total or complete, the reliability of the data now depends on the agent’s reliability. Several issues of this form of data reliability have been reported recently where the reliability of agents were assumed to be known and static. In this paper we address the issue of reliability maintenance of information agents and take the view that the agent reliability is dynamic and is a function of the database knowledge and the agent evidences (facts that are observed to be true or false). We propose a method of quantifying the level of trust (or the agent reliability) that the database system should rest on the agent based on observation, and statistical estimation.