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Mediators in the Architecture of Future Information Systems

Published: 01 March 1992 Publication History

Abstract

For single databases, primary hindrances for end-user access are the volume of data that is becoming available, the lack of abstraction, and the need to understand the representation of the data. When information is combined from multiple databases, the major concern is the mismatch encountered in information representation and structure. Intelligent and active use of information requires a class of software modules that mediate between the workstation applications and the databases. It is shown that mediation simplifies, abstracts, reduces, merges, and explains data. A mediator is a software module that exploits encoded knowledge about certain sets or subsets of data to create information for a higher layer of applications. A model of information processing and information system components is described. The mediator architecture, including mediator interfaces, sharing of mediator modules, distribution of mediators, and triggers for knowledge maintenance, are discussed.

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Reviews

James Roger Geissman

The author argues for a concept that is intended to help computer users survive the continuing data (not, one notices, knowledge or information) explosion. Because of the data surfeit, we have trouble getting enough knowledge. Selection (reducing the volume) and abstraction are our tools in dealing with this problem. Where abstractions are available for accessing some data, however, they are likely not to match the abstractions available for other data. If we had intelligent assistants, or <__?__Pub Fmt italic>mediators<__?__Pub Fmt /italic> (Wiederhold avoids the AI term <__?__Pub Fmt italic>agent<__?__Pub Fmt /italic>, although he draws attention to the similarity between agents and mediators), we could issue requests such as, “Based on the models used by the best economists, summarize the evolution of world trade over the past five years.” (Isn't that better than SQL__?__) This example task involves making the abstract request concrete through judgment, model selection, database connection, data look-up, model execution, data interpretation and reduction, presentation of results, and probably cooperation among several such assistants, which in turn involves dealing with the abstractions they respond to. Thus is knowledge created from data. The author sees automating such assistants as the solution to the data explosion. In a layered architecture, mediators are intermediate between one or more DBMSs and the applications that need the information. They convert requests into data-specific queries, which they pass downward, and convert data into information and pass it upward. The interface protocol is a form of universal object access language, analogous to the interface SQL provides to databases, but based on useful abstractions, not data dictionary entries. The paper goes on to discuss some implementation issues, such as What language is used for mediator requests__?__ What sort of intelligence do mediators need__?__ How do mediators, which are relatively autonomous, cooperate__?__ Can mediator knowledge be kept up to date through triggering events__?__ and Can mediators learn__?__ The author goes on to imagine (in a sidebar) a world in which<__?__Pub Caret> mediators might be available for rent—knowledge as commodity.

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Published In

cover image Computer
Computer  Volume 25, Issue 3
March 1992
82 pages
ISSN:0018-9162
Issue’s Table of Contents

Publisher

IEEE Computer Society Press

Washington, DC, United States

Publication History

Published: 01 March 1992

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Cited By

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  • (2022)Polystore and Tensor Data Model for Logical Data Independence and Impedance Mismatch in Big Data AnalyticsTransactions on Large-Scale Data- and Knowledge-Centered Systems XLII10.1007/978-3-662-60531-8_3(51-90)Online publication date: 11-Mar-2022
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