Constraint-based Query Distribution Framework for an Integrated Global Schema

Distributed heterogeneous data sources need to be queried uniformly using global schema. Query on global schema is reformulated so that it can be executed on local data sources. Constraints in global schema and mappings are used for source selection, query optimization,and querying partitioned and replicated data sources. The provided system is all XML-based which poses query in XML form, transforms, and integrates local results in an XML document. Contributions include the use of constraints in our existing global schema which help in source selection and query optimization, and a global query distribution framework for querying distributed heterogeneous data sources.Comment: The Proceedings of the 13th INMIC 2009), Dec. 14-15, 2009, Islamabad, Pakistan. Pages 1 - 6 Print ISBN: 978-1-4244-4872-2 INSPEC Accession Number: 11072575 Date of Current Version : 15 January 201

Schema architecture and their relationships to transaction processing in distributed database systems

We discuss the different types of schema architectures which could be supported by distributed database systems, making a clear distinction between logical, physical, and federated distribution. We elaborate on the additional mapping information required in architecture based on logical distribution in order to support retrieval as well as update operations. We illustrate the problems in schema integration and data integration in multidatabase systems and discuss their impact on query processing. Finally, we discuss different issues relevant to the cooperation (or noncooperation) of local database systems in a heterogeneous multidatabase system and their relationship to the schema architecture and transaction processing

Differential Privacy for Relational Algebra: Improving the Sensitivity Bounds via Constraint Systems

Differential privacy is a modern approach in privacy-preserving data analysis to control the amount of information that can be inferred about an individual by querying a database. The most common techniques are based on the introduction of probabilistic noise, often defined as a Laplacian parametric on the sensitivity of the query. In order to maximize the utility of the query, it is crucial to estimate the sensitivity as precisely as possible. In this paper we consider relational algebra, the classical language for queries in relational databases, and we propose a method for computing a bound on the sensitivity of queries in an intuitive and compositional way. We use constraint-based techniques to accumulate the information on the possible values for attributes provided by the various components of the query, thus making it possible to compute tight bounds on the sensitivity.Comment: In Proceedings QAPL 2012, arXiv:1207.055

Coherent Integration of Databases by Abductive Logic Programming

We introduce an abductive method for a coherent integration of independent data-sources. The idea is to compute a list of data-facts that should be inserted to the amalgamated database or retracted from it in order to restore its consistency. This method is implemented by an abductive solver, called Asystem, that applies SLDNFA-resolution on a meta-theory that relates different, possibly contradicting, input databases. We also give a pure model-theoretic analysis of the possible ways to `recover' consistent data from an inconsistent database in terms of those models of the database that exhibit as minimal inconsistent information as reasonably possible. This allows us to characterize the `recovered databases' in terms of the `preferred' (i.e., most consistent) models of the theory. The outcome is an abductive-based application that is sound and complete with respect to a corresponding model-based, preferential semantics, and -- to the best of our knowledge -- is more expressive (thus more general) than any other implementation of coherent integration of databases