Publication:
Using D3 to Visualize Lexical Link Analysis (LLA) and ADS-B Data

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Authors
Halpin, Quinn
Zhao, Ying
Kendall, Anthony
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Date of Issue
2017
Date
2017
Publisher
AAAI
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Abstract
The objective of this research is to create effective visualization tools to display Big Data, meaning data incomprehensible to the mind in raw form, in order to extract high-value information from Deep Analytics. This paper examines visualizations tested on Lexical Link Analysis (LLA) and Automatic Dependent Surveillance-Broadcast (ADS-B) data sets.One challenge that shaped this project is satisfying users’needs for Smart Data because the definition of high-value information varies by user and by data set. To address this challenge, a variety of tools and visualization strategies were implemented for the same data set to analyze the strengths and weaknesses of each design. These visualizations were created with D3.js, a JavaScript visualization library. The preliminary finding of this research is that force-directed visualizations are currently the best visualization for LLA results.
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Article
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The article of record as published may be found at http://www.aaai.org/ocs/index.php/FSS/FSS17/paper/viewFile/16008/15314
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Naval Postgraduate School (U.S.)
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Format
4 p.
Citation
Halpin, Quinn, Ying Zhao, and Anthony Kendall. "Using D3 to Visualize Lexical Link Analysis (LLA) and ADS-B Data." 2017 AAAI Fall Symposium Series. 2017.
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