Showing papers on "Data warehouse published in 1982"

On the architecture of a system integrating data base management and information retrieval

Abstract: The data model, i.e. data structures and operations needed for a system integrating the management of formated textual data (DBMIRS) are discussed. It is investigated how this data model fits into the ANSI-SPARC three schema architecture for data base management systems. The conclusion is that the DBMIRS should be regarded to be a new external data model. This would require only small changes to the concepts discussed so far for the conceptual and internal level. The advantages of this approach are:- The dichotomy between IRS and DBMS does not further exist.- The main part of the software can be used for IR systems as well as DB systems.- IR research can concentrate on the problems inherent in the retrieval of texts, e.g. automatic indexing, relevance feedback techniques.

A data base management system for image processing

Abstract: The Picture Database Management System (PICDMS) is a new, general solution to the data-processing processing problems of two-dimensional information (such as images and pictures): data definition, manipulation, and management, establishment of relationships among data from different sources, and handling of enormous data volume. An analysis of existing cartographic systems demonstrates the variation and two-dimensional mixing of standard data structures, and their performance in different situations. It conpares data manipulation capabilities among systems, their ability to interrelate variables from different sources, details of data management, and data storage efficiency. PICDMS are designed includes the following unique features: (1) Dynamic stacked-image data structure, (2) A data dictionary for storage of current data formats, (3) Flexible data manipulation capabilities, (4) A simple, easily understood data definition and manipulation language, (5) Automatic adaptation of the data access algorithm for maximum efficiency, (6) An Operations Dictionary for storage of standard operations, security and integrity constraints, and administrative procedures for the local implementation of the system, (7) An automatic file-handling system for security and redundancy control, (8) A resource access protocol to allow resource sharing among users, and (9) Detailed measurements of the time use of each module by each operation to allow performance analysis. The basic components of PICDMS which have been constructed constitute a working system which is already in some ways more powerful than existing software for two-dimensional data processing. It includes the data structure, data dictionary, data manipulation capabilities, data manipulation language, automatic choice among three access methods, access protocols, and performance measurements of the original design. The PICDMS approach to numerous simple and two complex data processing problems is described. For another set of problems it is compared in processing steps to a well-known image-processing system.

Data bases for large energy-economic models

Abstract: The collection, collation and transformation of data into the form required by a large energy-economic model constitutes a significant part of the overall modelling activity. The correct basis for setting up a model data base rests on the separation of the model specification into the four areas of external data transformation, internal data representation, internal data transformation and the mathematical relationships. From this specification, the model may be generated. The internal data base is comprised of a series of tables, covering intersectoral transactions, capital stock transactions, energy sector operating characteristics, consumption patterns and other data. These tables may be compiled direct from source material, or via some research requiring prior data processing. In both cases the process should be fully documented, so that data accuracy is ensured and the data may be updated reliably when new material becomes available. It is recommended that a data coordinating function be established within the modelling group, in order to plan and control data-related activities.