Materials Ontology Design and Development (MODD)

Award Information
Agency:
Department of Defense
Branch
Office of the Secretary of Defense
Amount:
$150,000.00
Award Year:
2014
Program:
SBIR
Phase:
Phase I
Contract:
FA8650-14-M-5002
Award Id:
n/a
Agency Tracking Number:
O133-C02-1106
Solicitation Year:
2013
Solicitation Topic Code:
OSD13-C02
Solicitation Number:
2013.3
Small Business Information
1235 South Clark Street, Suite 400, Arlington, VA, 22202-
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
036593457
Principal Investigator:
Tim Hawes
Sr. Software Engineer I
(703) 414-5032
timothy.hawes@dac.us
Business Contact:
Dana Ho
Contracts Manager
(703) 414-5016
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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