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Journal ArticleDOI

Federated database systems for managing distributed, heterogeneous, and autonomous databases

Amit P. Sheth, +1 more
- 01 Sep 1990 - 
- Vol. 22, Iss: 3, pp 183-236
TLDR
In this paper, the authors define a reference architecture for distributed database management systems from system and schema viewpoints and show how various FDBS architectures can be developed, and define a methodology for developing one of the popular architectures of an FDBS.
Abstract
A federated database system (FDBS) is a collection of cooperating database systems that are autonomous and possibly heterogeneous. In this paper, we define a reference architecture for distributed database management systems from system and schema viewpoints and show how various FDBS architectures can be developed. We then define a methodology for developing one of the popular architectures of an FDBS. Finally, we discuss critical issues related to developing and operating an FDBS.

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Citations
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An Experiment in Integrating Large Biomedical Knowledge Resources with RDF: Application to Associating Genotype and Phenotype Information

TL;DR: This paper demonstrates how the Resource Description Framework (RDF) can be used to represent and integrate these resources and support complex queries over the unified resource, and illustrates the effectiveness by answering a real-world biomedical query linking a specific molecular function, glycosyltransferase, to the disorder congenital muscular dystrophy.
Proceedings Article

Diversity with Cooperation in Database Schemata: Semantic Relativism.

TL;DR: This work first analyzes diversity within an information system, where cooperation is made possible by the use of external schemata; semantic relativism of the model of the database schema is the key f,ictor.
Proceedings Article

Joins for Hybrid Warehouses: Exploiting Massive Parallelism in Hadoop and Enterprise Data Warehouses

TL;DR: It is shown that it is actually better to do most data processing on the HDFS side, provided that it can leverage a sophisticated execution engine for joins on the Hadoop side, and a new zigzag join algorithm is described that is a robust join algorithm for hybrid warehouses which performs well in almost all cases.
Journal ArticleDOI

Virtual integration of sensor observation data

TL;DR: This paper discusses the design, implementation and evaluation of a framework that enables the virtual integration of heterogeneous observation data sources through a Sensor Observation Service (SOS) standard interface, using a well-known Mediator/Wrapper virtual data integration architecture.
References
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Book

The entity-relationship model: toward a unified view of data

TL;DR: A data model, called the entity-relationship model, is proposed that incorporates some of the important semantic information about the real world and can be used as a basis for unification of different views of data: the network model, the relational model, and the entity set model.
Book

Fundamentals of Database Systems

TL;DR: Fundamentals of Database Systems combines clear explanations of theory and design, broad coverage of models and real systems, and excellent examples with up-to-date introductions to modern database technologies.
Book

An Introduction to Database Systems

C. J. Date
TL;DR: Readers of this book will gain a strong working knowledge of the overall structure, concepts, and objectives of database systems and will become familiar with the theoretical principles underlying the construction of such systems.
Book

Principles of Distributed Database Systems

TL;DR: This third edition of a classic textbook can be used to teach at the senior undergraduate and graduate levels and concentrates on fundamental theories as well as techniques and algorithms in distributed data management.
Journal ArticleDOI

A comparative analysis of methodologies for database schema integration

TL;DR: The aim of the paper is to provide first a unifying framework for the problem of schema integration, then a comparative review of the work done thus far in this area, providing a basis for identifying strengths and weaknesses of individual methodologies, as well as general guidelines for future improvements and extensions.
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