Implicit Trust in a Data Model

Abstract

As an assessment of databases used to store Maritime Situational Awareness data, the hypothesis is posed that a database built upon a data model, utilizing international standards, recognized and accepted data modelling concepts, best practices, etc. would be more trusted by the community utilizing the data contained within the database. In this work, the validity of this hypothesis was investigated and assessed by decomposing trust into the sub-components: predictability, dependability, faith, reliability, robustness, familiarity, understandability, explication of intention, usefulness, competence, self-confidence, and reputation. An analysis of how these components are expressed in the context of a database system and in particular, how they impact the data model, was performed. The analysis indicates that reliability, understandability, usefulness, familiarity and reputation are the components that capture the concept of trust in a data model. These components were then applied in an analysis of the National Information Exchange Model-Maritime data model, essentially grading the model against the applicable trust components. Results vary from a poor grade on aspects of reliability, to excellent in terms of familiarity and reputation.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2011
Accession Number
ADA595898

Entities

People

  • Anthony W. Isenor
  • Marie-odette St-hilaire
  • Michel Mayrand

Organizations

  • OODA Technologies Inc.

Tags

Communities of Interest

  • C4I
  • Cyber
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Best Practices
  • Computer Program Documentation
  • Computer Program Reliability
  • Computer Programming
  • Computers
  • Data Modeling
  • Database Management Systems
  • Databases
  • Information Exchange
  • Information Systems
  • National Security
  • Relational Database Management Systems
  • Relational Databases
  • Reliability
  • Semantic Models
  • Situational Awareness
  • Web Service

Readers

  • Organizational Psychology.
  • Systems Analysis and Design
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.