Database Perspective Research Articles

Impact of Semantic Heterogeneity on Federating Databases

The difficult problems in the design of systems which facilitate interoperation and mediation among information sources and their consumers arise from the presence of semantic heterogeneity among the schemas and ontologies supporting the different services. The purpose of this paper is to develop a taxonomy of semantic heterogeneity, and to describe, taking the perspective of text databases, the conditions under which autonomy-respecting interoperation of different kinds are likely to be feasible. The main conclusion is that interoperation can be based on structured database technology only if the participating organizations communicate among themselves, otherwise the considerations underlying text databases dominate the technology used.

Clustering and knowledge discovery in spatial databases

In the past decades, clustering has been widely used in areas such as pattern recognition, data analysis, and image processing. Recently, clustering has been recognized as a useful method for knowledge discovery in spatial databases. To efficiently detect clusters from large spatial databases with a limited amount of available memory, special database techniques have been developed. In this article, we present a survey of these methods from a database perspective.

Data mining techniques

Data mining, or knowledge discovery in databases, has been popularly recognized as an important research issue with broad applications. We provide a comprehensive survey, in database perspective, on the data mining techniques developed recently. Several major kinds of data mining methods, including generalization, characterization, classification, clustering, association, evolution, pattern matching, data visualization, and meta-rule guided mining, will be reviewed. Techniques for mining knowledge in different kinds of databases, including relational, transaction, object-oriented, spatial, and active databases, as well as global information systems, will be examined. Potential data mining applications and some research issues will also be discussed.

Automatic Processes in Database Building and Subsequent Automatic Abstractions

One of the difficulties in building an effective system for spatial and attribute generalization is the predominance of the conventionally based generalization paradigm. This is exemplified by numerous attempts at reproducing rules derived from manual environments and re-building them in a GIS or CIS. What is often lacking is an understanding of what generalization achieves in its various forms. There is no doubt that the representation issue in generalization is of critical importance, since it is through the representation that we communicate visually. However, with access to databases and high-level programming tools, the quality, consistency, and reliability of the information warrants far greater emphasis than has been given in the past. Re-addressing generalization from a database perspective shifts the focus in model development from cartographic representation issues to geographic information. However, doing so places demands on operational mapping organizations for database building, data classification, and subsequent feature coding.

Automatic Processes in Database Building and Subsequent Automatic Abstractions

One of the difficulties in building an effective system for spatial and attribute generalization is the predominance of the conventionally based generalization paradigm. This is exemplified by numerous attempts at reproducing rules derived from manual environments and re-building them in a GIS or CIS. What is often lacking is an understanding of what generalization achieves in its various forms. There is no doubt that the representation issue in generalization is of critical importance, since it is through the representation that we communicate visually. However, with access to databases and high-level programming tools, the quality, consistency, and reliability of the information warrants far greater emphasis than has been given in the past. Re-addressing generalization from a database perspective shifts the focus in model development from cartographic representation issues to geographic information. However, doing so places demands on operational mapping organizations for database building, data classification, and subsequent feature coding. Recently, techniques have been developed to automatically classify, code, and build databases. Since the impediment to generalization has rested partially in establishing a logical database, the approach discussed in this chapter is to identify techniques that allow users to create the database automatically, without having to code the features interactively. Three different data sets being used for experimentation include hydrography, transportation networks, and land-cover. The models differ somewhat, given the nature of the object categories. Hydrographic and transportation-network features can be classified and coded using a rule base and graph theory, while land cover can be handled using classification and aggregation hierarchies. The objective of this research is to load unclassified categories of features, derive a series of classifications automatically, build a database automatically, and subsequently generalize the data using the derived database to any smaller scale of representation. The objective of this chapter is to present the methodologies required to achieve the research goals and to illustrate the results.

Automatic Processes in Database Building and Subsequent Automatic Abstractions

One of the difficulties in building an effective system for spatial and attribute generalization is the predominance of the conventionally based generalization paradigm. This is exemplified by numerous attempts at reproducing rules derived from manual environments and re-building them in a GIS or CIS. What is often lacking is an understanding of what generalization achieves in its various forms. There is no doubt that the representation issue in generalization is of critical importance, since it is through the representation that we communicate visually. However, with access to databases and high-level programming tools, the quality, consistency, and reliability of the information warrants far greater emphasis than has been given in the past. Re-addressing generalization from a database perspective shifts the focus in model development from cartographic representation issues to geographic information. However, doing so places demands on operational mapping organizations for database building, data classification, and subsequent feature coding.

Integrating the world wide web and database technology

The recent popularity of the World Wide Web (WWW, or the Web) has created a massive increase in both the supply and demand of Web-based technologies. However, the HyperText Markup Language (HTML) used to construct the Web has limitations that challenge information content providers who want to supply current, up-to-date information with minimal administrative overhead. A powerful, extensible solution to many of these challenges is the use of a database as a back end, or data source, for Web applications. Combining the Web with a database maximizes the strengths of its components. From the Web perspective, this combination offers user friendliness, cross-platform compatibility, and high-speed prototyping capabilities. From the database perspective, it offers relational data manipulation, high-speed search capabilities, and industrial-grade data input and retrieval. This paper describes experiences of application developers working at NCR, formerly AT&T Global Information Solutions. It also analyzes the strengths and weaknesses of the Web/database combination and seeks to prove that this combination is a viable alternative for providing database-oriented solutions.

DATABASE SUPPORTED COOPERATIVE PROBLEM SOLVING

Cooperative problem solving can be viewed as a complex activity requiring harmonious and dynamic interaction between active agents and passive agents. This problem is currently being addressed by the research community at various levels of abstraction. Broadly, this paper analyzes the problem of cooperative problem solving from a database perspective and argues that recent advances in database technology facilitate development of a viable solution to the above problem. Specifically, in this paper, we first analyze the problem of cooperative problem solving to identify its underlying key characteristics. Based upon our analysis, we partition the problem space into classes along a spectrum and indicate the level of cooperation required. We propose near-term as well as long-term solutions for cooperative problem solving that progressively enhances the functionality of database systems by synthesizing appropriate abstractions and techniques. Furthermore, we identify problems, such as agent capability modeling that require further research to address the most general form of cooperative problem solving.

Locating patient data among multiple heterogeneous medical databases

The general problem of connecting heterogeneous databases is well understood. The paper considers the problem from the perspective of medical databases where particular information can be expected to be fragmented over a number of separate databases and where the types of queries would generally be patient-centred. Several different options for structuring data are considered and analysed in terms of their effect on performance. An architecture is proposed and its implementation described briefly. The approach has been used to connect together Ingres and Oracle databases.

A Database Perspective of the Transition from Single-use (Ancillary-based) Systems to Integrated Models Supporting Clinical Care and Research in a MUMPS-based System

The Composite Health Care System (CHCS), a MUMPS-based hospital information system (HIS), has evolved from the Decentralized Hospital Computer Program (DHCP) installed within VA Hospitals. The authors explore the evolution of an ancillary-based system toward an integrated model with a look at its current state and possible future. The history and relationships between orders of different types tie specific patient-related data into a logical and temporal model. Diagrams demonstrate how the database structure has evolved to support clinical needs for integration. It is suggested that a fully integrated model is capable of meeting traditional HIS needs.

Semantic Modeling of Internal Controls in Database Design

:The paper attempts to model internal controls in an organization from a database perspective. It provides a three-level architecture to integrate data, process, and control level Abstractions. A semantic formalism based on this architecture is presented.

The relationship between CAD and software development support—a database perspective

Much attention is currently being given to the development of environments of tools to help throughout the software development life cycle, with data shared through a central database. Similarly, CAD systems are promoted within VLSI chip design, architectural design and related areas as providing equivalent advantages. This paper provides a detailed comparison of these fields from a data modelling perspective. A database schema used to model component VLSI designs is described and discussed, showing how the same schema can be used with minimum changes to model the design of software components. The paper also examines the data modelling facilities of a prototype IPSE and shows how the existing schema can be fully supported in this environment.