Complex Data Manipulation Research Articles

A high-level data manipulation language for hierarchical data structures

In this paper we assert that the hierarchical view of data will continue to be popular for a broad class of applications and users. In particular, some of these applications require complex data manipulation which, heretofore, has been dealt with procedurally. In this light, a nonprocedural language, CONVERT, is proposed as a high-level DBMS interface. CONVERT is meant to provide users with a tool for performing complex data manipulation and query of hierarchical data abstractions, called “Forms”. Included in the paper are a description of the Form data abstraction and the CONVERT language, as well as a complete illustrative sample application.

A high-level data manipulation language for hierarchical data structures

In this paper we assert that the hierarchical view of data will continue to be popular for a broad class of applications and users. In particular, some of these applications require complex data manipulation which, heretofore, has been dealt with procedurally. In this light, a nonprocedural language, CONVERT, is proposed as a high-level DBMS interface. CONVERT is meant to provide users with a tool for performing complex data manipulation and query of hierarchical data abstractions, called “Forms”. Included in the paper are a description of the Form data abstraction and the CONVERT language, as well as a complete illustrative sample application.

Automation in cardiology.

The basic principles of analogue and digital computers are reviewed and their application is described for the beat-to-beat analysis of the electrocardiogram using the AZTEC data reduction programme, for on-line haemodynamic analyses in the cardiac catheterization laboratory, coronary care unit, or postoperative ward, and for the clinical history and physical examination of the patient. The role of the computer in the management of cardiovascular disease is defined and its superiority in the collection and manipulation of complex data is emphasized. Its use in sparing staff the tedium of routine analyses of data will amply repay the initial cost of its installation.