Knowledge Discovery in the I-METL Application

Abstract

The Installation Mission Essential Task List (I-METL) is a software system designed to support the modeling and analysis of garrison capabilities, tenant functions, and installation resources. From a system analyst's point of view, the main focus of the I-METL application is that of collecting, sharing, and managing structured data. As the stored data accumulates in size, quality, and richness, stakeholders begin to realize the potential for harvesting new business intelligence from the data store. To this end, a myriad of tools and methods (commonly referred to as Knowledge Discovery from Database KDD methods) are available, depending on the kind of intelligence pursued. This research investigated KDD methods that can directly benefit I-METL stakeholders. One goal of this effort was to provide a means for stakeholders to gain an increased understanding of the existing data and data relationships. Another goal was to foster the discovery of new and hidden relationships from the dataset. Methods that will assist with data exploration and cognition also were researched. The two disparate methodologies investigated produced positive results for the KDD process and offer many potential benefits in a real-world deployment scenario. The prototype software developed validated these results and provided insights into future research possibilities.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2004
Accession Number
ADA429327

Entities

People

  • Todd R. Littell

Organizations

  • Engineer Research and Development Center

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Artificial Intelligence Computing
  • Computer Programming
  • Computer Programs
  • Data Analysis
  • Data Visualization
  • Databases
  • Graphical User Interface
  • Inference Engines
  • Information Systems
  • Language
  • Lessons Learned
  • Personnel Management
  • Relational Database Management Systems
  • Relational Databases
  • Two Dimensional
  • User Interface
  • Web Browsers

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence
  • Distributed Systems and Data Platform Development
  • Software Engineering.