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Planetary Defense Mitigation Gateway: A One-Stop Gateway for Pertinent PD-Related Contents

Authors :
Ishan Shams
Yun Li
Jingchao Yang
Manzhu Yu
Chaowei Yang
Myra Bambacus
Ruthan Lewis
Joseph A. Nuth
Luke Oman
Ronald Leung
Bernard D. Seery
Catherine Plesko
Kevin C. Greenaugh
Megan B. Syal
Source :
Data, Vol 4, Iss 2, p 47 (2019)
Publication Year :
2019
Publisher :
MDPI AG, 2019.

Abstract

Planetary Defense (PD) has become a critical effort of protecting our home planet by discovering potentially hazardous objects (PHOs), simulating the potential impact, and mitigating the threats. Due to the lack of structured architecture and framework, pertinent information about detecting and mitigating near earth object (NEO) threats are still dispersed throughout numerous organizations. Scattered and unorganized information can have a significant impact at the time of crisis, resulting in inefficient processes, and decisions made on incomplete data. This PD Mitigation Gateway (pd.cloud.gmu.edu) is developed and embedded within a framework to integrate the dispersed, diverse information residing at different organizations across the world. The gateway offers a home to pertinent PD-related contents and knowledge produced by the NEO mitigation team and the community through (1) a state-of-the-art smart-search discovery engine based on PD knowledge base; (2) a document archiving and understanding mechanism for managing and utilizing the results produced by the PD science community; (3) an evolving PD knowledge base accumulated from existing literature, using natural language processing and machine learning; and (4) a 4D visualization tool that allows the viewers to analyze near-Earth approaches in a three-dimensional environment using dynamic, adjustable PHO parameters to mimic point-of-impact asteroid deflections via space vehicles and particle system simulations. Along with the benefit of accessing dispersed data from a single port, this framework is built to advance discovery, collaboration, innovation, and education across the PD field-of-study, and ultimately decision support.

Details

Language :
English
ISSN :
23065729
Volume :
4
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Data
Publication Type :
Academic Journal
Accession number :
edsdoj.4037f01636e24cc79398e8bd349c2f55
Document Type :
article
Full Text :
https://doi.org/10.3390/data4020047