Kernel Metadata Declaration — on demand

ISO 26324 asks a DOI Registration Agency to produce a Kernel Metadata Declaration for every DOI it issues. Give any DOI: its public record becomes a record in the Smart Scholars DOI Metadata Format 1.0, checked against every rule, and declared as the Kernel XML.

✓ Meets every rule of the format

The record below is complete and every controlled value is a DOI Attribute Value Set 2.3 spelling. The Declaration on the right follows DOIMetadataKernel.xsd element by element.

What the DOI identifies

SMART GRID USING MACHINE LEARNING

10.46243/jst.2023.v8.i06.pp120-123 · JournalArticle — an article in a journal · Digital · Visual · Language · en

Published 2023-08-07

Part of Journal of Science & Technology · ISSN 2456-5660 · vol. 8 · no. 7 · pp. 120–123

Principal agents

P. SREELATHA P. SREELATHA (author → Author)
Longman Publishers (publisher → Publisher)

Also in the record, outside the Kernel: the abstract, the licence, 3 links, 7 references. Source: Crossref (member 25296), registered 2024-02-16, last deposited 2026-09-17.

⬇ Record (JSON) ⬇ Declaration (XML)

System metadata — ISO 26324:2025, Annex B · DOI Handbook 10.1

Each element by the standard's name and the Handbook's (in grey), read off the record.

DOI Name DOI name	10.46243/jst.2023.v8.i06.pp120-123
Referent Type referentType	Creation
Referent Sub-Type referentSubType	JournalArticle — an article in a journal
Referent Name(s) referentName(s)	SMART GRID USING MACHINE LEARNING (PrincipalTitle, en)
Basic Metadata basicMetadata	author: P. SREELATHA P. SREELATHA publisher: Longman Publishers published: 2023-08-07 part of: Journal of Science & Technology · ISSN 2456-5660 · vol. 8 · no. 7 · pp. 120–123 language: en form: Digital · Visual · Language
Referent Identifier(s) alternateIdentifier(s)	none besides the DOI
Registration Authority registrationAuthorityCode	Crossref — issued by Crossref (member 25296); held here as a copy
Created Date issueDate	2024-02-16
relatedIdentifiers	none needed — the descriptive metadata is in this record

The record

{
    "format": "smartscholars-doi-metadata/1.0",
    "doi": "10.46243/jst.2023.v8.i06.pp120-123",
    "referent": "Creation",
    "type": "JournalArticle",
    "structural_type": "Digital",
    "modes": [
        "Visual"
    ],
    "characters": [
        "Language"
    ],
    "titles": [
        {
            "value": "SMART GRID USING MACHINE LEARNING",
            "type": "PrincipalTitle",
            "lang": "en"
        }
    ],
    "identifiers": [
        {
            "type": "DOI",
            "value": "10.46243/jst.2023.v8.i06.pp120-123"
        }
    ],
    "agents": [
        {
            "role": "author",
            "name": {
                "given": "P. SREELATHA",
                "family": "P. SREELATHA"
            },
            "sequence": "first"
        },
        {
            "role": "publisher",
            "name": {
                "org": "Longman Publishers"
            }
        }
    ],
    "dates": {
        "published": "2023-08-07",
        "date_type": "PublicationDate",
        "online": "2023-08-07"
    },
    "language": "en",
    "container": {
        "type": "Journal",
        "titles": [
            {
                "value": "Journal of Science & Technology",
                "type": "PrincipalTitle"
            }
        ],
        "identifiers": [
            {
                "type": "ISSN",
                "value": "2456-5660",
                "medium": "electronic"
            }
        ],
        "volume": "8",
        "issue": "7",
        "pages": {
            "first": "120",
            "last": "123"
        }
    },
    "links": [
        {
            "url": "https://www.jst.org.in/index.php/pub/article/view/737",
            "return_type": "text/html",
            "primary": true
        },
        {
            "url": "https://www.jst.org.in/index.php/pub/article/download/737/663",
            "purpose": "text-mining",
            "return_type": "application/pdf"
        },
        {
            "url": "https://www.jst.org.in/index.php/pub/article/download/737/1784",
            "purpose": "text-mining",
            "return_type": "application/xml"
        }
    ],
    "abstract": {
        "value": "- In today‟s world, wastage of energy has become more frequent which leads to build a system which will take another way to maintain power generation and make proper distribution of energy and that system is called as SMART GRID.In this paper we will be making a Smart Grid which will overcome these issues by using Machine Learning. We will be using solar data power generation prediction by machine learning. This paper will help production or utility company to get knowledge of how much they have generate and distribute. By his paper blackout and energy wastage can be reduced.we developed the application which shows energy generation and user log.",
        "lang": "en"
    },
    "license": {
        "url": "https://creativecommons.org/licenses/by/4.0",
        "start": "2023-08-07",
        "applies_to": "vor"
    },
    "references": [
        {
            "key": "ref1",
            "doi": "10.1109/jproc.2011.2124210",
            "unstructured": "H. Gharaviand, R. Ghafurian, „„Smartgrid: The electric energy system of the future [scanning the issue],’’ Proc. IEEE, vol. 99, no. 6, pp. 917–921, Jun. 2011"
        },
        {
            "key": "ref2",
            "doi": "10.1109/smartgridcomm.2015.7436323",
            "unstructured": "S. Aman, M. Frincu, C. Chelmis, M. Noor, Y. Simmhan, and V. K. Prasanna, „„Prediction models for dynamic demand response: Requirements, challenges, and insights’’. in Proc. IEEE Int. Conf. Smart Grid Commun. (Smart Grid Comm), Nov. 2015, pp. 338–343"
        },
        {
            "key": "ref3",
            "doi": "10.1016/j.rser.2016.01.091",
            "unstructured": "C. Gamarra, J.M. Guerrero, and E. Montero, „„A knowledge discovery in databases approach for industrial microgrid planning,’’ Renew. Sustain. Energy Rev., vol. 60, pp. 615–630, Jul. 2016"
        },
        {
            "key": "ref4",
            "doi": "10.1016/j.bdr.2015.03.003",
            "unstructured": "P.D. Diamantoulakis, V.M. Kapinas, and G.K. Karagiannidis, „„Bigdata analytics for dynamic energy management in smart grids, ‘‘Big Data Res., vol. 2, pp. 94–101, Sep. 2015"
        },
        {
            "key": "ref5",
            "doi": "10.1109/tsg.2014.2368382",
            "unstructured": "V. Madani et al., „„Distribution automation strategies challenges and opportunities in a changing landscape,’’ IEEE Trans. Smart Grid, vol. 6, no. 4, pp. 2157–2165, Jul. 2015"
        },
        {
            "key": "ref6",
            "doi": "10.1109/tsg.2014.2302245",
            "unstructured": "Soliman, H. and Leon-Garcia, “A. Game-theoretic demand-side management with storage devices for the future smart grid”"
        },
        {
            "key": "ref7",
            "doi": "10.3390/en7096142",
            "unstructured": "J. Rodríguez-Molina, M. Martínez-Núñez, J.-F. Martínez, and W. Pérez-Aguiar, „„Business models in the smart grid: Challenges, opportunities and proposals for prosumer profitability,’’ Energies, vol. 7, no. 9, pp. 6142–6171, 2014"
        }
    ],
    "record": {
        "registrant": "Longman Publishers",
        "registered": "2024-02-16",
        "updated": "2026-09-17",
        "issue_number": 1,
        "source": "crossref-api",
        "source_agency": "Crossref (member 25296)"
    }
}

The Kernel Metadata Declaration

DOIMetadataKernel.xsd · namespace http://www.doi.org/2010/DOISchema · Attribute Value Sets 2.3 · draft — the agency's DOI name is filled in on accreditation

<?xml version="1.0" encoding="UTF-8"?>
<!-- DRAFT declaration: Smart Scholars is not yet a DOI Registration Agency. registrationAgencyDoiName is a marker (10.0/ is no RA's prefix) and is filled in on accreditation. -->
<kernelMetadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.doi.org/2010/DOISchema https://www.doi.org/doi_schemas/DOIMetadataKernel.xsd" xmlns="http://www.doi.org/2010/DOISchema">
  <referentDoiName>10.46243/jst.2023.v8.i06.pp120-123</referentDoiName>
  <primaryReferentType>Creation</primaryReferentType>
  <registrationAgencyDoiName>10.0/smart-scholars-draft</registrationAgencyDoiName>
  <issueDate>2026-10-04</issueDate>
  <issueNumber>1</issueNumber>
  <referentCreation>
    <name primaryLanguage="en">
      <value>SMART GRID USING MACHINE LEARNING</value>
      <type>PrincipalTitle</type>
    </name>
    <identifier>
      <nonUriValue>10.46243/jst.2023.v8.i06.pp120-123</nonUriValue>
      <uri returnType="text/html" doesContentNegotiation="true">https://doi.org/10.46243/jst.2023.v8.i06.pp120-123</uri>
      <type>DOI</type>
    </identifier>
    <identifier>
      <uri returnType="text/html">https://www.jst.org.in/index.php/pub/article/view/737</uri>
      <type>URI</type>
    </identifier>
    <identifier>
      <uri>https://www.jst.org.in/index.php/pub/article/download/737/663</uri>
      <type>URI</type>
    </identifier>
    <identifier>
      <uri returnType="application/xml">https://www.jst.org.in/index.php/pub/article/download/737/1784</uri>
      <type>URI</type>
    </identifier>
    <structuralType>Digital</structuralType>
    <mode>Visual</mode>
    <character>Language</character>
    <type>JournalArticle</type>
    <principalAgent>
      <name>
        <value>P. SREELATHA P. SREELATHA</value>
        <type>PrincipalName</type>
      </name>
      <role>Author</role>
    </principalAgent>
    <principalAgent>
      <name>
        <value>Longman Publishers</value>
        <type>PrincipalName</type>
      </name>
      <role>Publisher</role>
    </principalAgent>
    <linkedCreation>
      <name>
        <value>Journal of Science &amp; Technology</value>
        <type>PrincipalTitle</type>
      </name>
      <identifier>
        <nonUriValue>2456-5660</nonUriValue>
        <type>ISSN</type>
      </identifier>
      <referentCreationRole>Part</referentCreationRole>
      <referentCreationSequenceIdentifier>
        <value>8</value>
        <type>VolumeNumber</type>
      </referentCreationSequenceIdentifier>
      <referentCreationSequenceIdentifier>
        <value>7</value>
        <type>IssueNumber</type>
      </referentCreationSequenceIdentifier>
      <referentCreationSequenceIdentifier>
        <value>120-123</value>
        <type>PageNumber</type>
      </referentCreationSequenceIdentifier>
    </linkedCreation>
    <language>en</language>
    <languageOfReferentContent>
      <language>en</language>
      <languageOfReferentContentType>Original</languageOfReferentContentType>
    </languageOfReferentContent>
    <creationDate>
      <date>2023-08-07</date>
      <creationDateType>PublicationDate</creationDateType>
    </creationDate>
  </referentCreation>
</kernelMetadata>

Kernel Metadata Declaration — on demand

✓ Meets every rule of the format

What the DOI identifies

System metadata — ISO 26324:2025, Annex B · DOI Handbook 10.1

The record

The Kernel Metadata Declaration

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