A Big Data-Theoretic Approach to Quantify Organizational Failure Mechanisms in Probabilistic Risk Assessment: National Science Foundation (NSF) Project #1535167 Final Report

Zahra Mohaghegh; Catherine Lesley Blake; Cheri Ostroff; Justin Pence; Pegah Farshadmanesh; Madeline Morasca; Andrea Roy

A Big Data-Theoretic Approach to Quantify Organizational Failure Mechanisms in Probabilistic Risk Assessment: National Science Foundation (NSF) Project #1535167 Final Report

Zahra Mohaghegh, Catherine Lesley Blake, Cheri Ostroff, Justin Pence, Pegah Farshadmanesh, Madeline Morasca, Andrea Roy

Research output: Book/Report/Conference proceeding › Commissioned report

Original language	English (US)
Publisher	U.S. National Science Foundation
State	Published - 2023

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title = "A Big Data-Theoretic Approach to Quantify Organizational Failure Mechanisms in Probabilistic Risk Assessment: National Science Foundation (NSF) Project #1535167 Final Report",

author = "Zahra Mohaghegh and Blake, {Catherine Lesley} and Cheri Ostroff and Justin Pence and Pegah Farshadmanesh and Madeline Morasca and Andrea Roy",

year = "2023",

language = "English (US)",

publisher = "U.S. National Science Foundation",

}

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T1 - A Big Data-Theoretic Approach to Quantify Organizational Failure Mechanisms in Probabilistic Risk Assessment

T2 - National Science Foundation (NSF) Project #1535167 Final Report

AU - Mohaghegh, Zahra

AU - Blake, Catherine Lesley

AU - Ostroff, Cheri

AU - Pence, Justin

AU - Farshadmanesh, Pegah

AU - Morasca, Madeline

AU - Roy, Andrea

PY - 2023

Y1 - 2023

M3 - Commissioned report

BT - A Big Data-Theoretic Approach to Quantify Organizational Failure Mechanisms in Probabilistic Risk Assessment

PB - U.S. National Science Foundation

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