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Full Description
This Festschrift volume, published in honour of Peter Buneman, contains contributions written by some of his colleagues, former students, and friends. In celebration of his distinguished career a colloquium was held in Edinburgh, Scotland, 27-29 October, 2013. The articles presented herein belong to some of the many areas of Peter's research interests.
Contents
Models for Data-Centric Workflows.- Relational Databases and Bell's Theorem.- High-Level Rules for Integration and Analysis of Data: New Challenges.- A New Framework for Designing Schema Mappings.- User Trust and Judgments in a Curated Database with Explicit Provenance.- An Abstract, Reusable, and Extensible Programming Language Design Architecture.- A Discussion on Pricing Relational Data.- Tractable Reasoning in Description Logics with Functionality Constraints.- Toward a Theory of Self-explaining Computation.- To Show or Not to Show in Workflow Provenance.- Provenance-Directed Chase and Backchase.- Data Quality Problems beyond Consistency and Deduplication.- Hitting Buneman Circles.- Looking at the World Thru Colored Glasses.- Static Analysis and Query Answering for Incomplete Data Trees with Constraints.- Using SQL for Efficient Generation and Querying of Provenance Information.- Bounds and Algorithms for Joins via Fractional Edge Covers.- Incremental Data Fusion Based on Provenance Information.- Provenance for Linked Data.- First-Order Provenance Games.- Querying an Integrated Complex-Object Dataflow Database.- Types, Functional Programming and Atomic Transactions in Hardware Design.- Record Polymorphism: Its Development and Applications.- A Calculus of Chemical Systems.- Schemaless Semistructured Data Revisited - Reinventing Peter Buneman's Deterministic Semistructured Data Model.- Provenance Propagation in Complex Queries.- Well-Defined NRC Queries Can Be Typed.- Nine Years with Peter Buneman.- Modal Logic for Preference Based on Reasons.- The Dichotomous Intensional Expressive Power of the Nested Relational Calculus with Powerset.- Provenance in a Modifiable Data Set.
