94 Knowledge engineering 94.1 Databases Database Abstraction Data Models Databases Hierarchical Databases M. Abdelguerfi and Databases. Architecture of a DBMs. Data Integrity and R. Eskicioglu Security. Emerging Trends University of New Orleans 94.2 Rule-Based Expert Systems Problem Selection.Knowledge Acquisition.Knowledge Jay Liebowitz Representation.Knowledge Encoding. Knowledge Testing and George Washington University Evaluation. Implementation and maintenance 94.1 Databases M. Abdelguerfi and R. Eskicioglu In the past, file processing techniques were used to design information systems. These systems usually consist of a set of files and a collection of application programs. Permanent records are stored in the files, and application programs are used to update and query the files. The application programs were in general developed individ- ually to meet the needs of different groups of users. In many cases, this approach leads to a duplication of data among the files of different users. Also, the lack of coordination between files belonging to different users often leads to a lack of data consistency. In addition, changes to the underlying data requirements usually necessitate hajor changes to existing application programs. Among other major problems that arise with the use of file processing techniques are lack of data sharing, reduced programming productivity, and increased program maintenance. Because of their inherent difficulties and lack of flexibility, file processing techniques have lost great deal of their popularity and are being replaced by database management systems(DBMS). A DBMS is designed to efficiently manage a shared pool of interrelated data( database). This includes the existence of features such as a data definition language for the definition of the logical structure of the database database schema), a data manipulation language to query and update the database, a concurrency control mechanism to keep the database consistent when shared by several users, a crash recovery strategy to avoid any loss of information after a system crash, and safety mechanisms against any unauthorized access Database Abstraction A DBMS is expected to provide for data independence, i.e., user requests are made at a logical level without any need for the knowledge of how the data is stored in actual files. This implies that the internal file structure could be modified without any change to the user's perception of the database. To achieve data independence, ne Standards Planning and Requirements Committee(SPARC)of the American National Standards Institute (ANSI)in its 1977 report recommended three levels of database abstraction(see Fig. 94. 1). The lowest level in the abstraction is the internal level. Here, the database is viewed as a collection of files organized according to one of several possible internal data organizations(e.g, B+-tree data organization). In the conceptual level, the database is viewed at an abstract level. The user at this level is shielded from the internal storage details. At the external level, each group of users has their own perception or view of the database. Each view is derived from c 2000 by CRC Press LLC© 2000 by CRC Press LLC 94 Knowledge Engineering 94.1 Databases Database Abstraction • Data Models • Relational Databases • Hierarchical Databases • Network Databases • Architecture of a DBMS • Data Integrity and Security • Emerging Trends 94.2 Rule-Based Expert Systems Problem Selection • Knowledge Acquisition • Knowledge Representation • Knowledge Encoding • Knowledge Testing and Evaluation • Implementation and Maintenance 94.1 Databases M. Abdelguerfi and R. Eskicioglu In the past, file processing techniques were used to design information systems. These systems usually consist of a set of files and a collection of application programs. Permanent records are stored in the files, and application programs are used to update and query the files. The application programs were in general developed individ￾ually to meet the needs of different groups of users. In many cases, this approach leads to a duplication of data among the files of different users. Also, the lack of coordination between files belonging to different users often leads to a lack of data consistency. In addition, changes to the underlying data requirements usually necessitate major changes to existing application programs. Among other major problems that arise with the use of file processing techniques are lack of data sharing, reduced programming productivity, and increased program maintenance. Because of their inherent difficulties and lack of flexibility, file processing techniques have lost a great deal of their popularity and are being replaced by database management systems (DBMS). A DBMS is designed to efficiently manage a shared pool of interrelated data (database). This includes the existence of features such as a data definition language for the definition of the logical structure of the database (database schema), a data manipulation language to query and update the database, a concurrency control mechanism to keep the database consistent when shared by several users, a crash recovery strategy to avoid any loss of information after a system crash, and safety mechanisms against any unauthorized access. Database Abstraction A DBMS is expected to provide for data independence, i.e., user requests are made at a logical level without any need for the knowledge of how the data is stored in actual files. This implies that the internal file structure could be modified without any change to the user’s perception of the database. To achieve data independence, the Standards Planning and Requirements Committee (SPARC) of the American National Standards Institute (ANSI) in its 1977 report recommended three levels of database abstraction (see Fig. 94.1). The lowest level in the abstraction is the internal level. Here, the database is viewed as a collection of files organized according to one of several possible internal data organizations (e.g., B+-tree data organization). In the conceptual level, the database is viewed at an abstract level. The user at this level is shielded from the internal storage details. At the external level, each group of users has their own perception or view of the database. Each view is derived from M. Abdelguerfi and R. Eskicioglu University of New Orleans Jay Liebowitz George Washington University