Materials Ontology Design and Development (MODD)

Award Information
Agency: Department of Defense
Branch: Office of the Secretary of Defense
Contract: FA8650-14-M-5002
Agency Tracking Number: O133-C02-1106
Amount: $150,000.00
Phase: Phase I
Program: SBIR
Awards Year: 2014
Solitcitation Year: 2013
Solitcitation Topic Code: OSD13-C02
Solitcitation Number: 2013.3
Small Business Information
DECISIVE ANALYTICS Corporation
1235 South Clark Street, Suite 400, Arlington, VA, 22202-
Duns: 036593457
Hubzone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Tim Hawes
 Sr. Software Engineer I
 (703) 414-5032
 timothy.hawes@dac.us
Business Contact
 Dana Ho
Title: Contracts Manager
Phone: (703) 414-5016
Email: dana.ho@dac.us
Research Institution
N/A
Abstract
Semantically Linked Data is widely seen as a revolutionary approach for maximizing the usefulness of existing and future information. In the materials domain, semantically linked materials data holds considerable promise with the ability to facilitate materials research and product development, improve communication, and open up avenues for new types of materials informatics. But realizing the promise of Linked Data, requires establishing a meaningful vocabulary through which to describe concepts in the materials domain. The Materials Ontology Design and Development (MODD) effort is aimed at developing an ontology to realize the goals of linked data within the materials domain. As a direct result of Phase I research, the MODD ontology will link knowledge from a variety of existing materials databases. Additionally, because unstructured text, e.g. journal articles, contain large amounts of the available materials data MODD includes a relation extraction capability which can automatically structure this knowledge according to the ontology. Finally, because terminological variabilityin the vocabulary and in the datathreatens to hinder the utility of this project, we include automated capabilities for identifying and eliminating these types of variation. Combining these three capabilities, MODD will advance the state-of-the-art in materials information management with semantically linked materials data.

* information listed above is at the time of submission.

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