Semantic Language and Tools for Reporting Human Factors Incidents

Award Information
Agency:
National Aeronautics and Space Administration
Branch
n/a
Amount:
$99,758.00
Award Year:
2009
Program:
SBIR
Phase:
Phase I
Contract:
NNX09CE37P
Award Id:
90734
Agency Tracking Number:
084756
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
100 N.E. Loop 410, Suite 520, San Antonio, TX, 78216
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
193786014
Principal Investigator:
DebraSchreckenghost
Principal Investigator
(832) 415-0109
schreck@traclabs.com
Business Contact:
JimAnderson
CEO
(832) 415-4407
janderson@traclabs.com
Research Institute:
n/a
Abstract
Incidents related to impaired human performance in space operations can be caused by environmental conditions, situational challenges, and operational deficiencies. Detecting, reporting, and correlating related incidents are key to preventing future incidents. NASA has made significant progress in standardizing the reporting of aviation incidents by developing electronic forms for reporting incidents. While such forms improve report consistency, incident data are not represented in a way that enables computer-based reasoning across reports (e.g., automatic linking of related reports.) TRACLabs proposes to develop a human factors incident-reporting tool for gathering incident data, documenting data in incident reports, and archiving incident data. We will define an XML-based semantic language for incident reporting to capture information about human factors incidents, including multi-modal data. We will develop software for authoring incident reports using this language, archiving these reports, and searching the archives using incident semantics. This project is innovative in defining an incident reporting language that uses an ontology-based vocabulary. This enables improved tools for gathering incident data, and for authoring and archiving incident reports. The semantic indexing provided by the use of incident reporting language permits more sophisticated search of archives, including automatic identification of prior incidents potentially relevant to the current incident.

* information listed above is at the time of submission.

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