Content Data Model: Technical Summary

Abstract

Due to the increasing complexity and number of modern systems, the Air Force faces an ever-growing number of paper-based technical orders. The Air Force Human Resources Laboratory has conducted research and development (R&D) of automated technical information systems. This research investigated technologies for the storage, distribution, and presentation of technical information. Benefits of this research will include improvement in the performance of maintenance personnel and reduction in the cost of maintaining Air Force technical information. One of the products of this R&D includes a technology which provides the Air Force with an economical way of storing and presenting technical data. The Content Data Model (CDM) is a specification for a data base which is intended to store all of the technical information for a weapon system. At this time, the CDM stores only maintenance and operational information. This paper presents: (a) a description of the work involved in the development of the CDM, (b) a detailed description of CDM, (c) efforts to demonstrate and validate the CDM, and (d) the development of a draft specification for the preparation and delivery of technical data in CDM format. Keywords: Computer-aided acquisition and logistics support system (CALS). (kr)

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1990
Accession Number
ADA222376

Entities

People

  • David R. Gunning
  • Eric Freese
  • Mark Earl
  • Ronald Shroder
  • Walter Werts

Tags

Communities of Interest

  • Air Platforms
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Aerospace Industry
  • Air Force
  • Assembly
  • Bodies
  • Computer Programming
  • Computer Programs
  • Computer-Aided Design
  • Computers
  • Control Systems
  • Databases
  • Department Of Defense
  • Maintenance
  • Maintenance Personnel
  • Materials
  • Relational Databases
  • Test Equipment
  • United States

Fields of Study

  • Engineering

Readers

  • Business Analytics
  • Software Engineering.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.