Vincent Y. Lum

DEMOM-A description based media object data model

A description is given of the DEMOM media object data model, which aims at providing a uniform framework for managing different types of media data i.e. images, text, sound or graphics. According to DEMOM, media objects are defined as a class hierarchy of objects, i.e., images, text, sound, and graphics are subtypes of the general type media object. Representation-specific objects are regarded as subordinate types of the corresponding subtype, e.g., a SUN raster image in pixrect format is an instance of the subtype pixrect which is in turn a subtype of image. Using images as an example the authors discuss the media object hierarchy, the corresponding access operations, and implementation issues. Content-oriented search of media data on the basis of predicate calculus is considered as an essential part of DEMOM and hence briefly outlined. Finally, concerns related to the integration of alphanumeric and media objects are also included.<<ETX>>

GRADI, a Graphical Database Interface for a Multimedia DBMS

In this paper we describe the GRAphical Database Interface (GRADI) of a Multimedia Database Management System. As generally true, the user interface is an important part of the system which strongly determines the effectiveness of using it. In order to find an easy and natural way of interacting with the MDBMS system we examined the query specification process used by humans. We found that incremental query specification, predefined joins and an additional ‘all’-operator are important to improve the process of query specification making it considerably easier to use compared to query languages like SQL. The Graphical Database Interface described in this paper incorporates the mentioned capabilities as part of the MDBMS system. We think that the principles are of general use not only for multimedia systems but for any database query interface.

Visual query specification in a multimedia database system

A visual interface for a multimedia database management system (MDBMS) is described. DBMS query languages are linear in syntax. Although natural language interfaces have been found to be useful, natural language is ambiguous and difficult to process. For queries on standard (relational) data, these difficulties can be avoided with the use of a visual, graphical interface to guide the user in specifying the query. For image and other media data which are ambiguous in nature, natural language processing, combined with direct graphical access to the domain knowledge, is used to interpret and evaluate the natural language query. The system fully supports graphical and image input/output in different formats. The combination of visual effect and natural language specification, the support of media data, and the allowance of incremental query specification simplify the process of query specification not only for image or multimedia databases but also for all databases.<<ETX>>

A Chinese query language Chiql: design and evaluation

Chiql, an unconventional Chinese Database Query Language, is specially designed to be easily used by the naive and casual as well as expert users with Chinese background. In order to satisfy the requests of the Chinese user, we first depict the design principles of Chiql. Considering this, the language design and definition are described. Chiql supports restricted natural Chinese expressiveness, procedural query style and relational completeness. This facility renders Chiql simple to use and easy to remember. In order to verify the extent to which these objectives are satisfied by Chiql, we have conducted a series of evaluations to examine the languages expressiveness and ease of use. The result of this experiment is positive and clearly shows that the Chiql language fits the criteria of easy to use, easy to remember and easy to understand.

The processing and improvement of multi-statement queries in Chiql

Chiql is a novel Chinese relational database query language for Chinese users. It supports procedural query style in which users can specify a complex database request in multiple simple statements. This facility renders Chiql simple-to-use and easy-to-remember. However, direct executation of multi-statement Chiql queries (i.e. statement by statement) is often inefficient as potential index-based operations (e.g. join) are by-passed. Furthermore, it often incurs additional database operations, such as scan and projection. To improve this situation, the SMA (Statement Merging Algorithm) is proposed. The goal of SMA is to merge as many dependent statements within a Chiql query as possible to form a more efficient Chiql query. The ability in achieving improved efficiency without sacrificing the simplicity of the language is the major advantage of this algorithm.