Semantic Language and Tools for Reporting Human Factors Incidents

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.