Flexible Databases Supporting Imprecision and Uncertainty [electronic resource] / edited by Gloria Bordogna, Giuseppe Psaila.

Database Models and Query Languages -- Flexible Query Languages for Relational Databases: An Overview -- Vacuity-Oriented Generalized Yes/No Queries Addressed to Possibilistic Databases -- On the Applicability of Extended Possibilistic Truth Values in Flexible Database Modelling and Querying -- Preference based Quality Assessment and Presentation of Query Results -- Modeling Fuzzy Information in the EER and Nested Relational Database Models -- Database Integration -- Querying Contradictory Databases by Taking into Account Their Reliability and Their Number -- Database Integrations in Distributed Enterprise Information Systems: A Database Model with Imprecise Information and Query Processing -- Integrating Data Doubtfully -- Semistructured Data Management -- An Overview of Imperfection Representation in Semistructured Data -- A Synopsis based Approach for XML Fast Approximate Querying -- Spatial Databases -- Maximum Entropy Inference for Geographical Information Systems -- Storage and Manipulation of Vague Spatial Objects Using Existing GIS Functionality -- Spatial SQL with Customizable Soft Selection Conditions.

This volume collects selected contributions on the application of heterogeneous methods for managing uncertainty and imprecision in databases. It contains both survey chapters on classic topics such as "flexible querying in databases", and up to date ontributions on "database models to represent imperfect data". Further, it includes specific contributions on uncertainty management in database integration, and in representing and querying semistructured and spatial data. These topics are of particular relevance nowadays with the diffusion of the internet since, most of the time, applications require information spread across several information sources and their integration may result in inconsistent information. Semistructured information querying often calls for the application of approximate matching techniques, and spatial information is often incomplete and imprecise. Reading this volume can serve as a guide to students for having a panoramic view of the methods to manage uncertainty and imprecision in databases proposed so far, to researchers to focus on the most up to date research trends, and to practitioners for having examples in which current databases incorporate flexible functionalities for the management of uncertainty and imprecision.

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