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This article presents a novel user‐oriented interface for generalised informetric analysis and demonstrates how informetric calculations can easily and declaratively be specified through advanced data modelling techniques. The interface is declarative and at a high level. Therefore it is easy to use, flexible and extensible. It enables end users to perform basic informetric ad hoc calculations easily and often with much less effort than in contemporary online retrieval systems. It also provides several fruitful generalisations of typical informetric measurements like impact factors. These are based on substituting traditional foci of analysis, for instance journals, by other object types, such as authors, organisations or countries. In the interface, bibliographic data are modelled as complex objects (non‐first normal form relations) and terminological and citation networks involving transitive relationships are modelled as binary relations for deductive processing. The interface is flexible, because it makes it easy to switch focus between various object types for informetric calculations, e.g. from authors to institutions. Moreover, it is demonstrated that all informetric data can easily be broken down by criteria that foster advanced analysis, e.g. by years or content‐bearing attributes. Such modelling allows flexible data aggregation along many dimensions. These salient features emerge from the query interface‘s general data restructuring and aggregation capabilities combined with transitive processing capabilities. The features are illustrated by means of sample queries and results in the article.

To provide a selective bibliography for researchers and practitioners interested in database modeling of engineering information with sources which can help them develop engineering information systems.

Identifies the requirements for engineering information modeling and then investigates how current database models satisfy these requirements at two levels: conceptual data models and logical database models.

Presents the relationships among the conceptual data models and the logical database models for engineering information modeling viewed from database conceptual design.

Currently few papers provide comprehensive discussions about how current engineering information modeling can be supported by database technologies. This paper fills this gap. The contribution of the paper is to identify the direction of database study viewed from engineering applications and provide a guidance of information modeling for engineering design, manufacturing, and production management.

Expert database system (EDS), which is still in its infancy, is developed and demonstrated for a business function by coupling expert systems (ES) and database systems.

An EDS for inventory management (EDSIM) using the fifth generation artificial intelligence (AI) language, Prolog, is developed. The convergence of logic programming and database techniques is focused in achieving the objective. EDSIM development is based on modular design and integration of several intelligent modules, with own knowledge base and shared dynamic database.

EDSIM developed demonstrates the peculiarities of such an EDS over a system developed using conventional procedural language. It shows that development of such systems has great deployment potential in the next generation enterprise systems where embedded intelligence is inevitable.

Though no attempt is made to demonstrate distributed processing and interaction among various intelligent autonomous modules, an initiative in that direction definitely can kindle reengineering of today's enterprise system.

The language chosen for the development of EDSIM is Turbo Prolog™ and can be easily converted to a program in Visual Prolog™ which is the newer version of Turbo Prolog™. The advantage of such a conversion is that it will enable web readiness of the EDS there by facilitating e‐business in the web environment.

The benefits of the application of EDS, by the integration of ES and database systems in a fifth generation AI language, Prolog, paves way for capturing developments in AI and databases, simultaneously. This technology demonstrator has the potential to bring in an optimal mix of the above technologies in achieving major milestones while reengineering enterprise systems.

The residential construction industry has a major share in Canada's GDP. In spite of huge spending and technical advances in the residential construction sector, the current permit approval process still adheres to traditional manual permit approval process. Consequently, this has contributed to project delays and increased monetary costs to the stakeholders associated with the process. The research presented in this paper seeks to explore key issues related to the current housing development permit approval process.

This paper describes a proposed methodology for the automation of the residential construction development permit approval process. The proposed methodology has been incorporated into a computer system that integrates a knowledge‐based expert system (KBES), database management system (DBMS), and computer‐aided design (CAD). Various concepts related to the database structures, system architecture, process flow and user interfaces are introduced and described in the context of the development permit approval process.

This paper presents a knowledge‐based prototype for the development permit approval process that can be customized as per the needs of various cities. A case study is also presented in order to demonstrate the effectiveness of the proposed method and to illustrate the implementation of the research.

The prototype is application‐independent and may be implemented anywhere in the AutoCAD environment. The research paves the way for the setting of drafting standards for the residential industry.

Prototype provides significant gains in productivity and accuracy over the current practices by minimizing the redundancies involved in the development permit approval process.

The purpose of this research is to study how knowledge‐based systems are applied in an industrial environment. This paper attempts to propose a system, object‐based knowledge integration system (OBKIS) which supports the early stages of product development.

This proposed system characterizes the “dynamic” information exchange capability through its distinct features to include executable tasks within product information script that is being utilized in various functional groups, thereby introducing the action items to be carried out in relevant areas. To achieve the “dynamic” information exchange capability, object technology, which is favorable to the creation of inter‐related modularized data objects, is incorporated into the product information script to facilitate the active information interchange process. The universal extensible markup language (XML) is also adopted to facilitate data exchange between the database and the knowledge base in order to make real time data and knowledge available throughout the enterprise.

Further research on developing the well‐structured XML schema is needed in order to provide a well‐understood syntax and self‐defined mark‐up language to suit particular needs of product data exchange. For verification and measurement, it is suggested that one should evaluate the system in terms of data reliability, transformation accuracy and effectiveness for improving product design process.

The implications of these for information flows and management of product data during product development are discussed. In order to validate the feasibility of the proposed system, a prototype is developed for a local company so as to provide linking between the system design concept and system implementation in a practical environment.

The significance of this research is that a new product data schema for the initial phase of product development is formulated and the proposed system supports invoking various behaviors for the same message and overriding the pre‐defined inherited operation such that a flexible correlation can be formulated in the iterative product design process.

A multimedia computer system is one that can create, import, integrate, store, retrieve, edit, and delete two or more types of media materials in digital form, such as audio, image, full‐motion video, and text information. This paper surveys four possible types of multimedia computer systems: hypermedia, multimedia database, multimedia message, and virtual reality systems. The primary focus is on advanced multimedia systems development projects and theoretical efforts that suggest long‐term trends in this increasingly important area.

With the development of systems and applications, the number of users interacting with databases has increased considerably. The relational database model is still considered as the most used model for data storage and manipulation. However, it does not offer any semantic support for the stored data which can facilitate data access for the users. Indeed, a large number of users are intimidated when retrieving data because they are non-technical or have little technical knowledge. To overcome this problem, researchers are continuously developing new techniques for Natural Language Interfaces to Databases (NLIDB). Nowadays, the usage of existing NLIDBs is not widespread due to their deficiencies in understanding natural language (NL) queries. In this sense, the purpose of this paper is to propose a novel method for an intelligent understanding of NL queries using semantically enriched database sources.

First a reverse engineering process is applied to extract relational database hidden semantics. In the second step, the extracted semantics are enriched further using a domain ontology. After this, all semantics are stored in the same relational database. The phase of processing NL queries uses the stored semantics to generate a semantic tree.

The evaluation part of the work shows the advantages of using a semantically enriched database source to understand NL queries. Additionally, enriching a relational database has given more flexibility to understand contextual and synonymous words that may be used in a NL query.

Existing NLIDBs are not yet a standard option for interfacing a relational database due to their lack for understanding NL queries. Indeed, the techniques used in the literature have their limits. This paper handles those limits by identifying the NL elements by their semantic nature in order to generate a semantic tree. This last is a key solution towards an intelligent understanding of NL queries to relational databases.

Database management systems (DBMS) and information retrieval (IR) systems can both be used as online information systems but they differ in the type of data and the types of retrieval they provide for users. Many previous attempts have been made to couple DBMS and IR systems together, either by integrating the two into a unified framework, or by using a DBMS as an implementation tool for information retrieval functionality. This paper reports on some of these previous attempts and describes a system, retriev, which uses a DBMS to implement an IR system for teaching and research purposes. The implementation of retriev is described in detail and the effects that the current trends in database research will have on the relationship between DBMS and IR systems, are discussed.