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Awards

Topic Information Award/Contract Number Proposal Information Company Performance
Period
Award/Contract
Value
Abstract

15.OATS-003
Humanitarian Assistance/Disaster Relief (HA/DR) Social Media Analytics Tools

D15PC00248 DHS SBIR-2015.OATS-15.OATS-003-0001-II
(DHS SBIR-2015.OATS Phase II)
Scanigo: A Social Media Analytics Toolkit

Progeny Systems Corporation
9500 Innovation Drive
Manassas, VA 20110-2210

09/25/2015
to
07/15/2016
$180,191.16

Progeny developed a social media analytics toolkit called Scanigo under an ONR SBIR N121-092. Scanigo provides a methodology and computer aided approach for identifying critical information from social media for disaster responders. Scanigo implements an Ontology-Based Information Extraction (OBIE) methodology that significantly reduces the amount of information presented to the analysts, based on computed relevance, information overload is reduced by orders-of-magnitude while passing relevant information. Scanigo has been in use supporting real-world disaster since 2012 with results of less than 1% reduction of the total data to actionable information, relevant to the domain. The purpose of this Phase II is to significantly improve Scanigo's modularity, adaptability and performance. In addition, to demonstrate utility for use-cases that supports FEMA's emergency response operations. Planned improvements include: additional data sources; componentization; NoSQL database migration; knowledge extraction; ontology learning; ontology management; and cloud deployment. The primary purpose of componentization is to support various integration opportunities that already have a social media monitoring or analysis platform. For example, the OBIE pipeline that reduces social media streams in real-time based on relevance can be integrated into existing data flow architectures. The common theme of the planned improvements is scale. Componentization will allow Scanigo to scale to other integration opportunities. The ontology improvements will allow Scanigo to scale to other domains. Implementing ontology learning and management allows end users to perform their own domain customization, scaling to other domains. And finally, the performance improvements and a cloud deployment will allow Scanigo to scale to a global market.