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Actionable Intelligence | NIST

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</div> <!-- nist-index-ignore-end --> </div> </div> </div> <div class="grid-container margin-top-4"> <div class="grid-row grid-gap-6"> <div class="nist-page__region nist-page__region--content tablet-lg:grid-col-8"> <div class="nist-block gray-box"> <div class="text-long"> <h2>Summary</h2> <p>Much information that could have immediate practical value in the understanding, management, and measurement of socio-technical systems exists as domain-specific text embedded technical documents and information systems. The goal of this project is to discover, characterize, and apply text analysis methodologies that extract relevant information from domain-specific text.</p> </div> </div> <div class="nist-block"> <h2 class="nist-block__title">Description</h2> <div class="text-with-summary"> <p>A large portion of this project involves a collaboration with the Engineering Laboratory鈥檚 (EL) Model-based Enterprise program, specifically with the Knowledge Extraction and Application for Manufacturing Operations project. This collaboration has focused on the analysis of maintenance work order data and the development of an adaptation of Natural Language Processing (NLP) for technical text.</p> <p>We contribute to the NIST effort to provide tools for searching the COVID-19 Open Research Dataset (CORD-19) by reconstructing the dataset鈥檚 contiguous text from its JSON format. We use an Allen AI language model to extract keywords for this effort.</p> <p>We have been developing a methodology for analyzing large collections of privacy notices and have an emerging collaboration with the Federal Judicial Center to classify court dockets. Both of these efforts are focused on developing domain-specific text analyses for low-resource environments.</p> <p>We have contributed to the IARPA TrojAI project by developing a semi-automated methodology for literature reviews and are also investigating a methodology for the development of synthetic data for low-resource domains. This effort is interfacing with the Configurable Data Curation System (CDCS) project which will provide infrastructure for this effort.</p> <p>We are beginning an effort with the University of Maryland/Applied Research Laboratory for Intelligence and Security (ARLIS) to analyze supply-chain related documents to identify potential risks. We will begin by evaluating several text analysis methodologies. We also plan to investigate architectures for supply chain observatories.</p> <p>We also plan to collaborate with the Material Measurement Laboratory to analyze microscopy journal articles to assist with the development of scientific taxonomies.</p> </div> </div> <div class="nist-block"> <h2 class="nist-block__title">Major Accomplishments</h2> <div class="text-long"><ul><li>Played a role in the creation of the聽<a href="https://web.archive.org/web/20231128043114/https://www.nist.gov/el/technical-language-processing-community-interest">Technical Language Processing Community of Interest</a>聽and its kick off workshop.</li> </ul></div> </div> <div class="nist-block"> <div class="usa-accordion " aria-multiselectable="false"> <div class="text-long"> <h2 class="usa-accordion__heading"> <button class="usa-accordion__button" aria-expanded="false" aria-controls="field_project_associated_product"> Associated Product(s) </button> </h2> <div id="field_project_associated_product" class="usa-accordion__content"> <h2 class="nist-block__title">Resources/Demos</h2> <ul><li><a href="https://web.archive.org/web/20231128043114/https://github.com/usnistgov/trojai-literature">TrojAI Literature Review</a></li> <li><a href="https://web.archive.org/web/20231128043114/https://github.com/usnistgov/literature-survey-tools/">Literature Survey Tools</a></li> <li><a href="https://web.archive.org/web/20231128043114/https://www.nist.gov/news-events/news/nist-tools-searching-coronavirus-dataset">NIST Tools for Searching the Coronavirus Dataset</a></li> </ul> </div> </div> </div> </div> <div class="nist-block"> <!-- nist-index-ignore-start --> <div data-elastic-exclude="" class="nist-tags"> <a href="/web/20231128043114/https://www.nist.gov/topic-terms/information-technology" hreflang="en">Information technology</a></div> <!-- nist-index-ignore-end --> </div> </div> <aside class="nist-page__region nist-page__region--sidebar-second tablet-lg:grid-col-4"> <div> <!-- nist-index-ignore-start --> <div class="views-element-container nist-block nist-block--org" data-elastic-exclude=""> <h2 class="nist-block__title">Organizations</h2> <div><div class="js-view-dom-id-cd982cfa412a367b435df71fd5f1541bcca4a4fb98430064ece3f8c551230faf"> <div class="nist-related-orgs"><div class="term-tree-list"> <ul class="term"><li><a href="/web/20231128043114/https://www.nist.gov/nist-organizations/nist-headquarters" class="selected" hreflang="en">NIST Headquarters</a></li><li><ul class="term"><li><a href="/web/20231128043114/https://www.nist.gov/nist-organizations/nist-headquarters/laboratory-programs" class="selected" hreflang="en">Laboratory Programs</a></li><li><ul class="term"><li><a href="/web/20231128043114/https://www.nist.gov/nist-organizations/nist-headquarters/laboratory-programs/information-technology-laboratory" class="selected" hreflang="en">Information Technology Laboratory</a></li><li><ul class="term"><li><a href="/web/20231128043114/https://www.nist.gov/nist-organizations/nist-headquarters/laboratory-programs/information-technology-laboratory/software" class="selected" hreflang="en">Software and Systems Division</a></li><li><ul class="term"><li><a href="/web/20231128043114/https://www.nist.gov/nist-organizations/nist-headquarters/laboratory-programs/information-technology-laboratory-22" class="selected" hreflang="en">Information Systems Group</a></li></ul></li></ul></li></ul></li></ul></li></ul> </div> </div> <div class="nist-related-orgs"></div> <div class="nist-related-orgs"></div> <div class="nist-related-orgs"></div> <div class="nist-related-orgs"></div> </div> </div> </div> <!-- nist-index-ignore-end --> <div class="nist-block nist-block--contact"> <h2 class="nist-block__title">NIST Staff</h2> <div class="nist-field nist-field--label-hidden entity-reference nist-field--no-margin nist-field--link-list"> <div class="nist-field__items"> <div class="nist-field__item"> <a href="/web/20231128043114/https://www.nist.gov/people/alden-dima" rel="bookmark"><span>Alden A. Dima</span> </a> </div> </div> </div> </div> <div class="nist-block"> <h2 class="nist-block__title">Project Status</h2> <div class="nist-badge display-inline-block margin-y-1 nist-badge--blue boolean">Ongoing</div> </div> <div class="nist-block"> <h2 class="nist-block__title">Related Publications</h2> <div class="nist-field nist-field--label-hidden nist-field--link-list entity-reference"> <div class="nist-field__items"> <div class="nist-field__item"><a href="/web/20231128043114/https://www.nist.gov/publications/technical-language-processing-unlocking-maintenance-knowledge" hreflang="en">Technical Language Processing: Unlocking Maintenance Knowledge</a></div> <div class="nist-field__item"><a href="/web/20231128043114/https://www.nist.gov/publications/visual-analytics-approach-diagnosis-heterogeneous-and-multidimensional-machine" hreflang="en">A Visual Analytics Approach for the Diagnosis of Heterogeneous and Multidimensional Machine Maintenance Data</a></div> </div> </div> </div> <div class="nist-block"> <h2 class="nist-block__title">Other Projects</h2> <div class="text-long"><p><strong>Related Projects</strong></p> <ul><li>[Knowledge Extraction and Application for Manufacturing Operations](Knowledge Extraction and Application for Manufacturing Operations)</li> <li><a data-entity-substitution="canonical" data-entity-type="node" data-entity-uuid="675721be-64a5-49fe-97e7-97068a40d389" href="/web/20231128043114/https://www.nist.gov/itl/ssd/information-systems-group/configurable-data-curation-system-cdcs" title="The Configurable Data Curation System (CDCS)">The Configurable Data Curation System</a></li> </ul></div> </div> <h2 class="nist-block__title"> CUSTOMERS/CONTRIBUTORS<br>/COLLABORATORS </h2> <div class="text-long"><p><strong>Internal Collaborators</strong></p> <ul><li>Michael Brundage, NIST/EL</li> <li>Rachael聽Sexton, NIST/EL</li> <li>Michael Sharp, NIST/EL</li> <li>Benjamin Long, NIST/ITL</li> <li>Carelyn Campbell, NIST/MML</li> <li>June Lau, NIST/MML</li> </ul><p><strong>External Collaborators</strong></p> <ul><li>Thomas Hedberg, University of Maryland/Applied Research Laboratory for Intelligence and Security</li> <li>Melinda Hodkiewicz, University of Western Australia</li> <li>Sarah Lukens, GE Digital</li> <li>Xiaoyu Zhang, University of California, Davis</li> <li>Takanori Fujiwara, University of California, Davis</li> <li>Senthil Chandrasegaran, Technische Universiteit Delft (formerly University of California, Davis)</li> <li>Kwan-Liu Ma, University of California, Davis</li> <li>Timothy Lau, Federal Judicial Center</li> </ul></div> </div> </aside> </div> </div> <div class="grid-container"> <div class="nist-page__region nist-page__region--content-bottom"> <div class="nist-block"> <div class="text-italic font-sans-2xs"> Created May 27, 2021, Updated May 25, 2023 </div> </div> </div> </div> </section> </div> <div data-elastic-exclude> <!-- nist-index-ignore-start --> <footer class="nist-footer padding-bottom-4"> <div 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