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Additive Manufacturing Benchmark 2022 Schema

This resource is the implementation in XML Schema [1] of a data model that describes the Additive Manufacturing Benchmark 2022 series data. It provides a robust set of metadata for the build processes and their resulting specimens and for measurements made on these in the context of the AM Bench 2022 project.The schema was designed to support typical science questions which users of a database with metadata about the AM Bench results might wish to pose. The metadata include identifiers assigned to build products, derived specimens, and measurements; links to relevant journal publications, documents, and illustrations; provenance of specimens such as source materials and details of the build process; measurement geometry, instruments and other configurations used in measurements; and access information to raw and processed data as well as analysis descriptions of these datasets.This data model is an abstraction of these metadata, designed using the concepts of inheritance, normalization, and reusability of an object oriented language for ease of extensibility and maintenance. It is simple to incorporate new metadata as needed.A CDCS [2] database at NIST was filled with metadata provided by the contributors to the AM Bench project. They entered values for the metadata fields for an AM Bench measurement, specimen or build process in tabular spreadsheets. These entries were translated to XML documents compliant with the schema using a set of python scripts. The generated XML documents were loaded into the database with a persistent identifier (PID) assigned by the database.[1] https://www.w3.org/XML/Schema[2] https://www.nist.gov/itl/ssd/information-systems-group/configurable-dat…

About this Dataset

Updated: 2024-02-22
Metadata Last Updated: 2023-09-12 00:00:00
Date Created: N/A
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Dataset Owner: N/A

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Table representation of structured data
Title Additive Manufacturing Benchmark 2022 Schema
Description This resource is the implementation in XML Schema [1] of a data model that describes the Additive Manufacturing Benchmark 2022 series data. It provides a robust set of metadata for the build processes and their resulting specimens and for measurements made on these in the context of the AM Bench 2022 project.The schema was designed to support typical science questions which users of a database with metadata about the AM Bench results might wish to pose. The metadata include identifiers assigned to build products, derived specimens, and measurements; links to relevant journal publications, documents, and illustrations; provenance of specimens such as source materials and details of the build process; measurement geometry, instruments and other configurations used in measurements; and access information to raw and processed data as well as analysis descriptions of these datasets.This data model is an abstraction of these metadata, designed using the concepts of inheritance, normalization, and reusability of an object oriented language for ease of extensibility and maintenance. It is simple to incorporate new metadata as needed.A CDCS [2] database at NIST was filled with metadata provided by the contributors to the AM Bench project. They entered values for the metadata fields for an AM Bench measurement, specimen or build process in tabular spreadsheets. These entries were translated to XML documents compliant with the schema using a set of python scripts. The generated XML documents were loaded into the database with a persistent identifier (PID) assigned by the database.[1] https://www.w3.org/XML/Schema[2] https://www.nist.gov/itl/ssd/information-systems-group/configurable-data-curation-system-cdcs/about-cdcs
Modified 2023-09-12 00:00:00
Publisher Name National Institute of Standards and Technology
Contact mailto:[email protected]
Keywords data model , additive manufacturing , build plate , material composition , laser absorptivity , radiography , mechanical testing
{
    "identifier": "ark:\/88434\/mds2-2933",
    "accessLevel": "public",
    "contactPoint": {
        "hasEmail": "mailto:[email protected]",
        "fn": "Lyle E. Levine"
    },
    "programCode": [
        "006:045"
    ],
    "landingPage": "",
    "title": "Additive Manufacturing Benchmark 2022 Schema",
    "description": "This resource is the implementation in XML Schema [1] of a data model that describes the Additive Manufacturing Benchmark 2022 series data. It provides a robust set of metadata for the build processes and their resulting specimens and for measurements made on these in the context of the AM Bench 2022 project.The schema was designed to support typical science questions which users of a database with metadata about the AM Bench results might wish to pose. The metadata include identifiers assigned to build products, derived specimens, and measurements; links to relevant journal publications, documents, and illustrations; provenance of specimens such as source materials and details of the build process; measurement geometry, instruments and other configurations used in measurements; and access information to raw and processed data as well as analysis descriptions of these datasets.This data model is an abstraction of these metadata, designed using the concepts of inheritance, normalization, and reusability of an object oriented language for ease of extensibility and maintenance. It is simple to incorporate new metadata as needed.A CDCS [2] database at NIST was filled with metadata provided by the contributors to the AM Bench project. They entered values for the metadata fields for an AM Bench measurement, specimen or build process in tabular spreadsheets. These entries were translated to XML documents compliant with the schema using a set of python scripts. The generated XML documents were loaded into the database with a persistent identifier (PID) assigned by the database.[1] https:\/\/www.w3.org\/XML\/Schema[2] https:\/\/www.nist.gov\/itl\/ssd\/information-systems-group\/configurable-data-curation-system-cdcs\/about-cdcs",
    "language": [
        "en"
    ],
    "distribution": [
        {
            "accessURL": "https:\/\/ambench2022.nist.gov\/",
            "title": "AM Bench 2022 Metadata Catalog"
        },
        {
            "downloadURL": "https:\/\/data.nist.gov\/od\/ds\/mds2-2933\/AMMeasurement.xsd",
            "format": "xsd",
            "description": "The schema for the metadata describing characterization measurements conducted in the AMBench 2022 project.",
            "mediaType": "text\/xml",
            "title": "AMMeasurement.xsd"
        },
        {
            "downloadURL": "https:\/\/data.nist.gov\/od\/ds\/mds2-2933\/AMBuild.xsd",
            "format": "xsd",
            "description": "The schema for the metadata describing samples and build processes used in the AM Bench 2022 project.",
            "mediaType": "text\/xml",
            "title": "AMBuild.xsd"
        },
        {
            "downloadURL": "https:\/\/data.nist.gov\/od\/ds\/mds2-2933\/AMReference.xsd",
            "format": "xsd",
            "description": "The schema  which contains a generic resource type 'AMResource' in the AM Bench project such as samples and measurements.  AMResource is the ultimate base type for other more explicit AM Bench documents. ",
            "mediaType": "text\/xml",
            "title": "AMReference.xsd"
        },
        {
            "downloadURL": "https:\/\/data.nist.gov\/od\/ds\/mds2-2933\/AMDocs.xsd",
            "format": "xsd",
            "description": "The schema which contains a root element for an AM Bench XML document. It wraps the more specific AM Bench resource documents including specimens and measurements.",
            "mediaType": "text\/xml",
            "title": "AMDocs.xsd"
        },
        {
            "downloadURL": "https:\/\/data.nist.gov\/od\/ds\/mds2-2933\/2933_README.txt",
            "format": "Plain text",
            "description": "Description of the data files included in this data record",
            "mediaType": "text\/plain",
            "title": "README file"
        }
    ],
    "bureauCode": [
        "006:55"
    ],
    "modified": "2023-09-12 00:00:00",
    "publisher": {
        "@type": "org:Organization",
        "name": "National Institute of Standards and Technology"
    },
    "theme": [
        "Materials:Materials characterization",
        "Materials:Modeling and computational material science",
        "Materials:Metals",
        "Materials:Polymers",
        "Manufacturing:Additive manufacturing"
    ],
    "keyword": [
        "data model",
        "additive manufacturing",
        "build plate",
        "material composition",
        "laser absorptivity",
        "radiography",
        "mechanical testing"
    ]
}

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