Using D3 to Visualize Lexical Link Analysis (LLA) and ADS-B Data
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Authors
Halpin, Quinn
Zhao, Ying
Kendall, Anthony
Subjects
Advisors
Date of Issue
2017
Date
2017
Publisher
AAAI
Language
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.
Type
Article
Description
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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Department
Organization
Naval Postgraduate School (U.S.)
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NPS Report Number
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Funder
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.