39 research outputs found

    Evaluation of Functional Data Models for Database Design and Use

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    The problems of design, operation, and maintenance of databases using the three most popular database management systems (Hierarchical, CQDASYL/DBTG, and Relational) are well known. Users wishing to use these systems have to make conscious and often complex mappings between the real-world structures and the data structuring options (data models) provided by these systems. In addition, much of the semantics associated with the data either does not get expressed at all or gets embedded procedurally in application programs in an ad-hoc way. In recent years, a large number of data models (called semantic data models) have been proposed with the aim of simplifying database design and use. However, the lack of usable implementations of these proposals has so far inhibited the widespread use of these concepts. The present work reports on an effort to evaluate and extend one such semantic model by means of an implementation. It is based on the functional data model proposed earlier by Shipman[SHIP81). We call this 'Extended Functional Data Model' (EFDM). EFDM, like Shipman's proposals, is a marriage of three of the advanced modelling concepts found in both database and artificial intelligence research: the concept of entity to represent an object in the real world, the concept of type hierarchy among entity types, and the concept of derived data for modelling procedural knowledge. The functional notation of the model lends itself to high level data manipulation languages. The data selection in these languages is expressed simply as function application. Further, the functional approach makes it possible to incorporate general purpose computation facilities in the data languages without having to embed them in procedural languages. In addition to providing the usual database facilities, the implementation also provides a mechanism to specify multiple user views of the database

    Decision Support Systems: Issues and Challenges; Proceedings of an International Task Force Meeting, June 23-25, 1980

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    This book reports on a three-day meeting on Decision Support Systems held at IIASA. IIASA's interest in sponsoring the meeting was spurred by several factors. First, the term DSS clearly is used in a wide range of contexts; we hoped to develop a deeper understanding of the term and the new field to which it refers. Second, we felt that ongoing work in the DSS field would be enhanced by interaction between professionals who had been working on such systems and people from fields that function as "resource disciplines" for DSS. Finally we wished to bring professionals from several nations together, from the east as well as the west, to share experiences and to assess the viability of the DSS concept in different cultures. The broad objectives set for this meeting were realized in a number of ways. Virtually all the participants testified that they had gained a deeper understanding of DSS, the role it can play in asssisting managers in organizations, and the need for further development in key areas

    Relational multimedia databases.

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    Engineering and Scientific Data Management

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    The application of data management systems to engineering and scientific data is described

    Restructuring mechanism for a codasyl-type data base

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    SIGLELD:D48229/84 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

    The semantic database model as a basis for an automated database design tool

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    Bibliography: p.257-80.The automatic database design system is a design aid for network database creation. It obtains a requirements specification from a user and generates a prototype database. This database is compatible with the Data Definition Language of DMS 1100, the database system on the Univac 1108 at the University of Cape Town. The user interface has been constructed in such a way that a computer-naive user can submit a description of his organisation to the system. Thus it constitutes a powerful database design tool, which should greatly alleviate the designer's tasks of communicating with users, and of creating an initial database definition. The requirements are formulated using the semantic database model, and semantic information in this model is incorporated into the database as integrity constraints. A relation scheme is also generated from the specification. As a result of this research, insight has been gained into the advantages and shortcomings of the semantic database model, and some principles for 'good' data models and database design methodologies have emerged

    Generic functional requirements for a NASA general-purpose data base management system

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    Generic functional requirements for a general-purpose, multi-mission data base management system (DBMS) for application to remotely sensed scientific data bases are detailed. The motivation for utilizing DBMS technology in this environment is explained. The major requirements include: (1) a DBMS for scientific observational data; (2) a multi-mission capability; (3) user-friendly; (4) extensive and integrated information about data; (5) robust languages for defining data structures and formats; (6) scientific data types and structures; (7) flexible physical access mechanisms; (8) ways of representing spatial relationships; (9) a high level nonprocedural interactive query and data manipulation language; (10) data base maintenance utilities; (11) high rate input/output and large data volume storage; and adaptability to a distributed data base and/or data base machine configuration. Detailed functions are specified in a top-down hierarchic fashion. Implementation, performance, and support requirements are also given

    Space station data system analysis/architecture study. Task 2: Options development, DR-5. Volume 3: Programmatic options

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    Task 2 in the Space Station Data System (SSDS) Analysis/Architecture Study is the development of an information base that will support the conduct of trade studies and provide sufficient data to make design/programmatic decisions. This volume identifies the preferred options in the programmatic category and characterizes these options with respect to performance attributes, constraints, costs, and risks. The programmatic category includes methods used to administrate/manage the development, operation and maintenance of the SSDS. The specific areas discussed include standardization/commonality; systems management; and systems development, including hardware procurement, software development and system integration, test and verification
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