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Improving Analysis of Large Multidimensional Data through Parallel Processing & Explorative Visualization

Award Information
Agency: Department of Defense
Branch: Missile Defense Agency
Contract: HQ0147-19-C-7058
Agency Tracking Number: B18C-001-0022
Amount: $99,998.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: MDA18-T001
Solicitation Number: 18.C
Timeline
Solicitation Year: 2018
Award Year: 2019
Award Start Date (Proposal Award Date): 2019-03-26
Award End Date (Contract End Date): 2019-09-25
Small Business Information
4141 Colonel Glenn Highway, Suite 140, Beavercreek, OH, 45431
DUNS: 153927827
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Whit Matthews
 Principal Investigator
 (757) 230-2225
 wmatthews@fti-net.com
Business Contact
 Timothy Kellett
Phone: (805) 685-6672
Email: tkellett@fti-net.com
Research Institution
 Old Dominion University Research Foundation
 Michael Ludwick Michael Ludwick
 4111 Monarch Way, Suite 204
Norfolk, VA, 23508
 (757) 683-4293
 Nonprofit college or university
Abstract
Using a combination of parallel processing and explorative visualization, a new and exciting solution for high-performance visual analysis of large multidimensional data is proposed. Steady volume flows are selected to demonstrate the strategy, methodology, techniques, and functionalities. Virtual Reality (VR) and Augmented Reality (AR) platforms will be adopted to unleash the power of explorative visualization. The proposed paradigm is well-suited for visual analysis of vast amounts of vector data, while it can be easily extended for scalar data visualization and information visualization. This project is part of a wider opportunity to establish more effective approaches for visualization of advanced data analytics. Our focus is on developing a solution with the following capabilities: • A scalable and flexible multi-threaded parallel processing system that can perform multiple terabytes worth of data processing tasks such as data parsing, pre-processing, organizing, data flagging, compressing, and reformatting • A data analysis environment using an off-the-shelf big data analytics engine that offers both explorative and predictive analytics capabilities to uncover hidden data relationships and patterns • A wide variety of visualization techniques to carry out algorithm-oriented scientific data visualizations and information visualizations. • A proposed cloud-based commercialization approach that meets all current DOD cybersecurity requirements. Approved for Public Release | 19-MDA-9932 (21 Feb 19)

* Information listed above is at the time of submission. *

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