Information Standards and Their Use: Implications for Design Patterns

Abstract

Long before systems engineers began to design computer networks and to integrate databases, there were standards. In fact, the history of standards in fields such as medicine and commerce is measured in centuries. (Bowker and Star, 1999) Later, during the industrial revolution, standards were applied to manufactured goods and we are reminded of the success of such standards when we have a part replaced on our car or when we plug an electrical device into a wall socket. More recently, the worlds of computer systems engineering and standards have become intertwined. When standards and systems engineering meet, systems engineers are faced with two challenges. First and most obviously, computers, networks, computer programs, and the systems built from them are all manufactured goods. And as such, they are subject to standardization in the same way as other manufactured goods. The challenge for computer and software engineers comes when they are asked to participate in standards efforts. Typically, the act of interacting with other engineers from other organizations and collaborating with them in order to produce standards requires a different set of skills than are needed for effective computer programming and systems engineering. This raises a question that is not typically addressed in their education and training: How are effective standards created?

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Document Details

Document Type
Technical Report
Publication Date
Mar 16, 2010
Accession Number
AD1108593

Entities

People

  • Dave Mann
  • Joann Brooks

Organizations

  • MITRE Corporation

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Application Software
  • Artificial Intelligence
  • Central Processing Units
  • Cognitive Science
  • Community Of Practice
  • Computer Languages
  • Computer Programming
  • Computer Programs
  • Computer Science
  • Computers
  • Graphical User Interface
  • Human Machine Interface
  • Information Processing
  • Information Science
  • Information Systems
  • Internet
  • Natural Languages
  • Ontologies
  • Operating Systems
  • Organizational Structure
  • Programming Languages
  • Psychology
  • Systems Engineering

Fields of Study

  • Computer science

Readers

  • Database Systems and Applications
  • Software Engineering
  • Systems Analysis and Design