A Model Driven Data Mining System for Studying Environmental Impact of Nanomaterials

Award Information
Agency:
Department of Defense
Branch
Army
Amount:
$730,000.00
Award Year:
2012
Program:
SBIR
Phase:
Phase II
Contract:
W912HZ-12-C-0004
Agency Tracking Number:
A2-4784
Solicitation Year:
2010
Solicitation Topic Code:
A10-107
Solicitation Number:
2010.2
Small Business Information
Intelligent Automation, Inc.
MD, Suite 400, Rockville, MD, 20855-2737
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
Y
Duns:
161911532
Principal Investigator:
Kaizhi Tang
Senior Research Scientist
(301) 294-5214
ktang@i-a-i.com
Business Contact:
Mark James
Director
(301) 294-5221
mjames@i-a-i.com
Research Institution:
Stub




Abstract
As more engineered nanomaterials (eNM) are developed for military use, it is crucial to minimize any unintended environmental impacts (NEI) resulting from the application of eNM. To realize this vision, industry and policymakers must base risk management decisions on sound scientific information about the environmental fate of NM; their availability to receptor organisms, including related concepts such as uptake; and any resultant biological effects, e.g. toxicity. Intelligent Automation, Inc. (IAI) is developing a Model driven Data Mining System for studying Environmental Impact of Nanomaterials, NEIMiner, which consists of four components. The NEI modeling framework defines the scope of NEI modeling and the strategy of integrating NEI models to form a layered, comprehensive predictability similar to the Framework for Risk Analysis of Multi-Media Environmental Systems (FRAMES). The data integration layer brings together heterogeneous data sources related to NEI via automatic web services and web scraping technologies. The data management and access layer reuses and extends a popular Content Management System (CMS), Drupal, and consists of modules that model and enable interactions over a complex data structure for NEI related bibliography and characterization data. The model discovery and composition layer provides an analysis capability for NEI data.

* information listed above is at the time of submission.

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