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.

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

The development of the Internet in recent years has made it possible and useful to access many different information systems anywhere in the world to obtain information. While there is much research on the integration of heterogeneous information systems, most commercial systems stop short of the actual integration of available data. Data fusion is the process of fusing multiple records representing the same real-world object into a single, consistent, and clean representation.This article places data fusion into the greater context of data integration, precisely defines the goals of data fusion, namely, complete, concise, and consistent data, and highlights the challenges of data fusion, namely, uncertain and conflicting data values. We give an overview and classification of different ways of fusing data and present several techniques based on standard and advanced operators of the relational algebra and SQL. Finally, the article features a comprehensive survey of data integration systems from academia and industry, showing if and how data fusion is performed in each.

Data fusion

Federated Database Systems for Managing Distributed, Heterogeneous, and Autonomous Databases

Large organizations need to exchange information among many separately developed systems. In order for this exchange to be useful, the individual systems must agree on the meaning of their exchanged data. That is, the organization must ensure semantic interoperability. This paper provides a theory of semantic values as a unit of exchange that facilitates semantic interoperability betweeen heterogeneous information systems. We show how semantic values can either be stored explicitly or be defined by environments. A system architecture is presented that allows autonomous components to share semantic values. The key component in this architecture is called the context mediator, whose job is to identify and construct the semantic values being sent, to determine when the exchange is meaningful, and to convert the semantic values to the form required by the receiver.Our theory is then applied to the relational model. We provide an interpretation of standard SQL queries in which context conversions and manipulations are transparent to the user. We also introduce an extension of SQL, called Context-SQL (C-SQL), in which the context of a semantic value can be explicitly accessed and updated. Finally, we describe the implementation of a prototype context mediator for a relational C-SQL system.

/pdf/using-semantic-values-to-facilitate-interoperability-among-3qqp303is6.pdf

Using semantic values to facilitate interoperability among heterogeneous information systems

Due to the proliferation of database applications, the integration of existing databases into a distributed or federated system is one of the major challenges in responding to enterprises' information requirements. Some proposed integration techniques aim at providing database administrators (DBAs) with a view definition language they can use to build the desired integrated schema. These techniques leave to the DBA the responsibility of appropriately restructuring schema elements from existing local schemas and of solving inter-schema conflicts. This paper investigates the assertion-based approach, in which the DBA's action is limited to pointing out corresponding elements in the schemas and to defining the nature of the correspondence in between. This methodology is capable of: ensuring better integration by taking into account additional semantic information (assertions about links); automatically solving structural conflicts; building the integrated schema without requiring conforming of initial schemas; applying integration rules to a variety of data models; and performing view as well as database integration. This paper presents the basic ideas underlying our approach and focuses on resolution of structural conflicts.

/pdf/model-independent-assertions-for-integration-of-ot9rqvceg2.pdf

Model independent assertions for integration of heterogeneous schemas

Mermaid is a system that allows the user of multiple databases stored under various relational DBMSs running on different machines to manipulate the data using a common language, either ARIEL or SQL. It makes the complexity of this distributed, heterogeneous data processing transparent to the user. In this paper, we describe the architecture, system control, user interface, language and schema translation, query optimization, and network operation of the Mermaid system. Future research issues are also addressed.

Mermaid&#8212;A front-end to distributed heterogeneous databases

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Mermaid—A front-end to distributed heterogeneous databases

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Mermaid&#8212;A front-end to distributed heterogeneous databases

Mermaid—A front-end to distributed heterogeneous databases