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        "author": "Thurston Sexton",
        "author_email": "thurston.sexton@nist.gov",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Manufacturing",
            "Intended Audience :: Science/Research",
            "License :: Public Domain",
            "Programming Language :: Python :: 3",
            "Topic :: Scientific/Engineering :: Information Analysis"
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        "description": "## Purpose\n\nThis application was designed to help manufacturers \"tag\" their\nmaintenance work-order data according to [the methods being researched](https://www.researchgate.net/project/Knowledge-Extraction-and-Application-for-Smart-Manufacturing) by the Knowledge Extraction and Applications project at the NIST Engineering Laboratory. The goal of this\napplication is to give understanding to data sets that previously were\ntoo unstructured or filled with jargon to analyze. The current build is\nin very early alpha, so please be patient in using this application. If\nyou have any questions, please do not hesitate to contact us (see [Who\nare we?](#who-are-we). )\n\n### Why?\n\nThere is often a large amount of maintenance data *already* available\nfor use in Smart Manufacturing systems, but in a currently-unusable\nform: service tickets and maintenance work orders (MWOs). **Nestor** is\na toolkit for using Natural Language Processing (NLP) with efficient\nuser-interaction to perform structured data extraction with minimal\nannotation time-cost.\n\n### Features\n\n\n-   Ranks concepts to be annotated by importance, to save you time\n-   Suggests term unification by similarity, for you to quickly review\n-   Basic concept relationships builder, to assist assembling problem\n    code and taxonomy definitions\n-   Strucutred data output as tags, whether in readable (comma-sep) or\n    computation-friendly (sparse-mat) form.\n\n### What's Inside?\n\nDocumentation is contained in the /docs subdirectory, and are hosted as\nwebpages and\n[PDF](https://media.readthedocs.org/pdf/nestor/latest/nestor.pdf)\navailable at [readthedocs.io](https://nestor.readthedocs.io/en/latest/)\n.\n\nCurrent:\n\n-   Tagging Tool: Human-in-the-loop Annotation Interface (pyqt)\n-   Unstructured data processing toolkit (sklearn-style)\n-   Vizualization tools for tagged MWOs-style data (under development)\n\nPlanned/underway:\n\n-   KPI creation and visualization suite\n-   Machine-assisted functional taxonomy generation\n-   Quantitative skill assement and training suggestion engine\n-   Graph Database creation assistance and query tool\n\n### Pre-requisites\n\nThis package was built as compatible with Anaconda python distribution.\nSee our [default requirements file](https://github.com/usnistgov/nestor/blob/master/requirements/defaults.txt) for a complete list of major dependencies, along with the requirements to run our [experimental dashboard](https://github.com/usnistgov/nestor/blob/master/requirements/dash.txt) or to [compile our documentation locally](https://github.com/usnistgov/nestor/blob/master/requirements/docs.txt)\n\n\n## Who are we?\n\n\nThis toolkit is a part of the Knowledge Extraction and Application for\nSmart Manufacturing (KEA) project, within the Systems Integration\nDivision at NIST.\n\n### Points of Contact\n\n-   [Michael Brundage](https://www.nist.gov/people/michael-p-brundage)\n    Principal Investigator\n-   [Thurston Sexton](https://www.nist.gov/people/thurston-sexton) Nestor Technical Lead\n\n### Contributors:\nName             |   GitHub Handle\n---              |   ---\nThurston Sexton  |   [@tbsexton](https://github.com/tbsexton)\nSascha Moccozet  |   [@saschaMoccozet](https://github.com/saschaMoccozet)\nMichael Brundage |   [@MichaelPBrundage](https://github.com/MichaelPBrundage)\nMadhusudanan N.  |   [@msngit](https://github.com/msngit)\nEmily Hastings   |   [@emhastings](https://github.com/emhastings)\nLela Bones       |   [@lelatbones](https://github.com/lelatbones)\n\n### Why KEA?\n\nThe KEA project seeks to better frame data collection and transformation\nsystems within smart manufacturing as *collaborations* between human\nexperts and the machines they partner with, to more efficiently utilize\nthe digital and human resources available to manufacturers. Kea (*nestor\nnotabilis*) on the other hand, are the world's only alpine parrots,\nfinding their home on the southern Island of NZ. Known for their\nintelligence and ability to solve puzzles through the use of tools, they\nwill often work together to reach their goals, which is especially\nimportant in their harsh, mountainous habitat.",
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        "name": "nist-nestor",
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        "summary": "Quantifying tacit human knowledge for Smart Manufacturing Maintenance,                        for maintnenance-based investigatory analysis",
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