A Scalable Architecture for Visual Data Exploration

Abstract

Intelligence analysts in the areas of defense and homeland security are now faced with the difficult problem of discerning the relevant details amidst massive data stores. We propose a component-based visualization architecture that is built specifically to encourage the flexible exploration of geospatial event databases. The proposed system is designed to deploy on a variety of display layouts, from a single laptop screen to a multi-monitor tiled-display. By utilizing a combination of parallel coordinates, principal components plots and other data views, analysts may reduce the dimensionality of a dataset to their most salient features. Of particular value to our target applications are understanding correlations between data layers both within single views and across multiple views. Our proposed system aims to address the limited scalability associated with coordinated multiple views (CMVs) through the implementation of an efficient core application which is meant to be extended by the end-user rather than a programmer.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2009
Accession Number
ADA623684

Entities

People

  • Alex Godwin
  • Denise Royle
  • Jonathan Decker
  • Mark Livingston

Organizations

  • United States Naval Research Laboratory

Tags

DTIC Thesaurus Topics

  • Beta Testing
  • Computer Programming
  • Computer Programs
  • Data Analysis
  • Data Sets
  • Digital Information
  • Electronic Mail
  • Factor Analysis
  • Information Operations
  • Information Science
  • Language
  • Military Research
  • Object Oriented Programming
  • Predictive Analytics
  • Puerto Rico
  • Scripting Languages
  • Visualizations

Fields of Study

  • Computer science

Readers

  • Geospatial Intelligence and Artificial Intelligence Analytics
  • Software Engineering.
  • Systems Analysis and Design