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

Graph database models can be defined as those in which data structures for the schema and instances are modeled as graphs or generalizations of them, and data manipulation is expressed by graph-oriented operations and type constructors. These models took off in the eighties and early nineties alongside object-oriented models. Their influence gradually died out with the emergence of other database models, in particular geographical, spatial, semistructured, and XML. Recently, the need to manage information with graph-like nature has reestablished the relevance of this area. The main objective of this survey is to present the work that has been conducted in the area of graph database modeling, concentrating on data structures, query languages, and integrity constraints.

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Survey of graph database models

Database management systems will continue to manage large data volumes. Thus, efficient algorithms for accessing and manipulating large sets and sequences will be required to provide acceptable performance. The advent of object-oriented and extensible database systems will not solve this problem. On the contrary, modern data models exacerbate the problem: In order to manipulate large sets of complex objects as efficiently as today's database systems manipulate simple records, query-processing algorithms and software will become more complex, and a solid understanding of algorithm and architectural issues is essential for the designer of database management software. This survey provides a foundation for the design and implementation of query execution facilities in new database management systems. It describes a wide array of practical query evaluation techniques for both relational and postrelational database systems, including iterative execution of complex query evaluation plans, the duality of sort- and hash-based set-matching algorithms, types of parallel query execution and their implementation, and special operators for emerging database application domains.

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Query evaluation techniques for large databases

Alloy is a little language for describing structural properties. It offers a declaration syntax compatible with graphical object models, and a set-based formula syntax powerful enough to express complex constraints and yet amenable to a fully automatic semantic analysis. Its meaning is given by translation to an even smaller (formally defined) kernel. This paper presents the language in its entirety, and explains its motivation, contributions and deficiencies.

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Alloy: a lightweight object modelling notation

Most common database management systems represent information in a simple record-based format. Semantic modeling provides richer data structuring capabilities for database applications. In particular, research in this area has articulated a number of constructs that provide mechanisms for representing structurally complex interrelations among data typically arising in commercial applications. In general terms, semantic modeling complements work on knowledge representation (in artificial intelligence) and on the new generation of database models based on the object-oriented paradigm of programming languages.This paper presents an in-depth discussion of semantic data modeling. It reviews the philosophical motivations of semantic models, including the need for high-level modeling abstractions and the reduction of semantic overloading of data type constructors. It then provides a tutorial introduction to the primary components of semantic models, which are the explicit representation of objects, attributes of and relationships among objects, type constructors for building complex types, ISA relationships, and derived schema components. Next, a survey of the prominent semantic models in the literature is presented. Further, since a broad area of research has developed around semantic modeling, a number of related topics based on these models are discussed, including data languages, graphical interfaces, theoretical investigations, and physical implementation strategies.

Semantic database modeling: survey, applications, and research issues

Semantic data models have emerged from a requirement for more expressive conceptual data models. Current generation data models lack direct support for relationships, data abstraction, inheritance, constraints, unstructured objects, and the dynamic properties of an application. Although the need for data models with richer semantics is widely recognized, no single approach has won general acceptance. This paper describes the generic properties of semantic data models and presents a representative selection of models that have been proposed since the mid-1970s. In addition to explaining the features of the individual models, guidelines are offered for the comparison of models. The paper concludes with a discussion of future directions in the area of conceptual data modeling.

Semantic data models

The Data Model Compiler project represents an effort to automatically produce object-oriented database systems. An analysis of data models of this genre leads to the conclusion that their significant differentiating characteristic is the set of fundamental, or built-in, relationships. This observation has lead to the development of a methodology for the generation of object-oriented data models which revolves around the specification of the basic relationships. Initially, the project focused on the development of a variety of object-oriented models in order to gain an understanding of the problem space. This paper concentrates upon that experience with a brief discussion of future plans. The particular application domains for which models have been constructed include business data processing, mechanical CAD, office information systems, and software performance modelling. The knowledge gained by developing these models served as the basis for the specification of a set of essential relationship characteristics. The plan for generating database software corresponding to a user-specified data model revolves around the definition of the fundamental relationships of the model in terms of the aforementioned characteristics.

The Data Model Compiler: a tool for generating object-oriented database systems

Backend database systems have been proposed as a solution to the problems of overloaded data processing installations. This tutorial examines backend database systems in terms of their basic structure, their potential benefits and drawbacks, and the problems facing developers of such systems. Several prototype systems are described, and research on extensions of the backend concept is discussed. The structure of the hardware and software components of backend database systems is presented in detail. The performance problems encountered in recent prototypes are pointed out and potential solutions indicated.

Backend Database Systems

A metamodel for describing the semantics of object-oriented data models is presented. This metamodel supports the automatic generation of conceptual database design tool software for a variety of data models. Data modeling is viewed as having three levels of abstraction. The physical database, at the lowest level, stores objects and relationships. Specific data models reside at the middle level. A data model consists of object types and relationship types. The metamodel resides at the highest level and is composed of metaobject types and metarelationship types. To illustrate the utility of the metamodel, the representation of the ORION data model is presented. >

Using a metamodel to represent object-oriented data models

The authors address the data allocation problem in a dynamically reconfigurable distributed database system. Following the description of the system model and the consequences of node movement, several dynamic allocation strategies are presented. A distributed candidate-selection algorithm using the data from the accounting system in the database servers is proposed to reduce the number of files and nodes considered in reallocation. The allocation algorithms choose the optimal assignment using heuristic benefit functions and greedy search strategy. The experimental results demonstrate the accuracy and efficiency of the allocation algorithms. >

Fred J. Maryanski

Papers

Semantic data models

The Data Model Compiler: a tool for generating object-oriented database systems

Backend Database Systems

Using a metamodel to represent object-oriented data models

Data allocation in a dynamically reconfigurable environment