Home | | Database Management Systems | | FUNDAMENTALS OF Database Systems | | Database Management Systems | Enhanced Data Models for Advanced Applications

Chapter: Fundamentals of Database Systems - Advanced Database Models, Systems, and Applications - Enhanced Data Models for Advanced Applications

| Study Material, Lecturing Notes, Assignment, Reference, Wiki description explanation, brief detail |

Enhanced Data Models for Advanced Applications

As the use of database systems has grown, users have demanded additional functionality from these software packages, with the purpose of making it easier to implement more advanced and complex user applications.

Part 11

Advanced Database Models, Systems, and Applications

 

Chapter 26

Enhanced Data Models for Advanced Applications

As the use of database systems has grown, users have demanded  additional  functionality  from  these software packages, with the purpose of  making it easier to implement more advanced and complex user applications. Object-oriented databases and object-relational systems do provide features that allow users to extend their systems by specifying additional abstract data types for each application. However, it is quite useful to identify certain common features for some of these advanced applications and to create models that can represent them. Additionally, specialized storage structures and indexing methods can be implemented to improve the performance of these common features. Then the features can be implemented as abstract data types or class libraries and purchased separately from the basic DBMS software package. The term data blade has been used in Informix and cartridge in Oracle to refer to such optional submodules that can be included in a DBMS package. Users can utilize these features directly if they are suitable for their applications, without having to reinvent, reimplement, and reprogram such common features.

 

This chapter introduces database concepts for some of the common features that are needed by advanced applications and are being used widely. We will cover active rules that are used in active database applications, temporal concepts that are used in temporal database applications, and, briefly, some of the issues involving spatial databases and multimedia databases. We will also discuss deductive databases. It is important to note that each of these topics is very broad, and we give only a brief introduction to each. In fact, each of these areas can serve as the sole topic of a complete book.

 

In Section 26.1 we introduce the topic of active databases, which provide additional functionality for specifying active rules. These rules can be automatically triggered by events that occur, such as database updates or certain times being reached, and can initiate certain actions that have been specified in the rule declaration to occur if certain conditions are met. Many commercial packages include some of the functionality provided by active databases in the form of triggers. Triggers are now part of the SQL-99 and later standards.

 

In Section 26.2 we introduce the concepts of temporal databases, which permit the database system to store a history of changes, and allow users to query both current and past states of the database. Some temporal database models also allow users to store future expected information, such as planned schedules. It is important to note that many database applications are temporal, but they are often implemented without having much temporal support from the DBMS package—that is, the temporal concepts are implemented in the application programs that access the data-base.

 

Section 26.3 gives a brief overview of spatial database concepts. We discuss types of spatial data, different kinds of spatial analyses, operations on spatial data, types of spatial queries, spatial data indexing, spatial data mining, and applications of spatial databases.

 

Section 26.4 is devoted to multimedia database concepts. Multimedia databases provide features that allow users to store and query different types of multimedia information, which includes images (such as pictures and drawings), video clips (such as movies, newsreels, and home videos), audio clips (such as songs, phone messages, and speeches), and documents (such as books and articles). We discuss automatic analysis of images, object recognition in images, and semantic tagging of images,

 

In Section 26.5 we discuss deductive databases,1 an area that is at the intersection of databases, logic, and artificial intelligence or knowledge bases. A deductive data-base system includes capabilities to define (deductive) rules, which can deduce or infer additional information from the facts that are stored in a database. Because part of the theoretical foundation for some deductive database systems is mathematical logic, such rules are often referred to as logic databases. Other types of systems, referred to as expert database systems or knowledge-based systems, also incorporate reasoning and inferencing capabilities; such systems use techniques that were developed in the field of artificial intelligence, including semantic networks, frames, production systems, or rules for capturing domain-specific knowledge. Section 26.6 summarizes the chapter.

 

Readers may choose to peruse the particular topics they are interested in, as the sections in this chapter are practically independent of one another.

 


Study Material, Lecturing Notes, Assignment, Reference, Wiki description explanation, brief detail


Copyright © 2018-2020 BrainKart.com; All Rights Reserved. Developed by Therithal info, Chennai.