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Title: Safeguards Knowledge Management & Retention at U.S. National Laboratories.

Abstract

In 2017, four U.S. National Laboratories collaborated on behalf of DOE/NNSA to explore the safeguards knowledge retention problem, identify possible approaches, and develop a strategy to address it. The one-year effort consisted of four primary tasks. First, the project sought to identify critical safeguards information at risk of loss. Second, a survey and workshop were conducted to assess nine U.S. National Laboratories' efforts to determine current safeguards knowledge retention practices and challenges, and identify best practices. Third, specific tools were developed to identify and predict critical safeguards knowledge gaps and how best to recruit in order to fill those gaps. Finally, based on findings from the first three tasks and research on other organizational approaches to address similar issues, a strategy was developed on potential knowledge retention methods, customized HR policies, and best practices that could be implemented across the National Laboratory Complex.

Authors:
 [1];  [2];  [2];  [2];  [2];  [3];  [4];  [4];  [4]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  2. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  3. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  4. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1398239
Report Number(s):
SAND2017-10508
657378
DOE Contract Number:
AC04-94AL85000
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL PROTECTION; 96 KNOWLEDGE MANAGEMENT AND PRESERVATION

Citation Formats

Haddal, Risa, Jones, Rebecca, Bersell, Bridget, Frazar, Sarah, Burbank, Roberta, Stevens, Rebecca, Cain, Ron, Kirk, Bernadette, and Morell, Sean. Safeguards Knowledge Management & Retention at U.S. National Laboratories.. United States: N. p., 2017. Web. doi:10.2172/1398239.
Haddal, Risa, Jones, Rebecca, Bersell, Bridget, Frazar, Sarah, Burbank, Roberta, Stevens, Rebecca, Cain, Ron, Kirk, Bernadette, & Morell, Sean. Safeguards Knowledge Management & Retention at U.S. National Laboratories.. United States. doi:10.2172/1398239.
Haddal, Risa, Jones, Rebecca, Bersell, Bridget, Frazar, Sarah, Burbank, Roberta, Stevens, Rebecca, Cain, Ron, Kirk, Bernadette, and Morell, Sean. Fri . "Safeguards Knowledge Management & Retention at U.S. National Laboratories.". United States. doi:10.2172/1398239. https://www.osti.gov/servlets/purl/1398239.
@article{osti_1398239,
title = {Safeguards Knowledge Management & Retention at U.S. National Laboratories.},
author = {Haddal, Risa and Jones, Rebecca and Bersell, Bridget and Frazar, Sarah and Burbank, Roberta and Stevens, Rebecca and Cain, Ron and Kirk, Bernadette and Morell, Sean},
abstractNote = {In 2017, four U.S. National Laboratories collaborated on behalf of DOE/NNSA to explore the safeguards knowledge retention problem, identify possible approaches, and develop a strategy to address it. The one-year effort consisted of four primary tasks. First, the project sought to identify critical safeguards information at risk of loss. Second, a survey and workshop were conducted to assess nine U.S. National Laboratories' efforts to determine current safeguards knowledge retention practices and challenges, and identify best practices. Third, specific tools were developed to identify and predict critical safeguards knowledge gaps and how best to recruit in order to fill those gaps. Finally, based on findings from the first three tasks and research on other organizational approaches to address similar issues, a strategy was developed on potential knowledge retention methods, customized HR policies, and best practices that could be implemented across the National Laboratory Complex.},
doi = {10.2172/1398239},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Fri Sep 01 00:00:00 EDT 2017},
month = {Fri Sep 01 00:00:00 EDT 2017}
}

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