Conference paper Embargoed Access

Knowledge management system for big data in a smart electricity grid context

Eugénia Vinagre; Tiago Pinto; Gil Pinheiro; Zita Vale; Carlos Ramos; Juan Manuel Corchado


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  <identifier identifierType="DOI">10.5281/zenodo.1209898</identifier>
  <creators>
    <creator>
      <creatorName>Eugénia Vinagre</creatorName>
      <affiliation>Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development</affiliation>
    </creator>
    <creator>
      <creatorName>Tiago Pinto</creatorName>
      <affiliation>BISITE Research Centre</affiliation>
    </creator>
    <creator>
      <creatorName>Gil Pinheiro</creatorName>
      <affiliation>Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development</affiliation>
    </creator>
    <creator>
      <creatorName>Zita Vale</creatorName>
      <affiliation>Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development</affiliation>
    </creator>
    <creator>
      <creatorName>Carlos Ramos</creatorName>
      <affiliation>Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development</affiliation>
    </creator>
    <creator>
      <creatorName>Juan Manuel Corchado</creatorName>
      <affiliation>BISITE Research Centre</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Knowledge management system for big data in a smart electricity grid context</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2018</publicationYear>
  <subjects>
    <subject>Big Data,</subject>
    <subject>Data Analytics,</subject>
    <subject>Knowledge management,</subject>
    <subject>Smart grids</subject>
  </subjects>
  <dates>
    <date dateType="Available">2020-06-09</date>
    <date dateType="Accepted">2018-06-09</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="Text">Conference paper</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/1209898</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.1209897</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/embargoedAccess">Embargoed Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;We have been witnessing a real explosion of information, due in large part to&lt;br&gt;
the development in Information and Knowledge Technologies (ICTs). As information is&lt;br&gt;
the raw material for the discovery of knowledge, there has been a rapid growth, both in&lt;br&gt;
the scientific community and in ICT itself, in the study of the Big Data phenomenon&lt;br&gt;
(Kaisler et al., 2014). The concept of Smart Grids (SG) has emerged as a way of&lt;br&gt;
rethinking how to produce and consume energy imposed by economic, political and&lt;br&gt;
ecological issues (Lund, 2014). To become a reality, SGs must be supported by intelligent&lt;br&gt;
and autonomous IT systems to make the right decisions in real time. Knowledge needed&lt;br&gt;
for real-time decision-making can only be achieved if SGs are equipped with systems&lt;br&gt;
capable of efficiently managing all the surrounding information. Thus, this paper&lt;br&gt;
proposes a system for the management of information in the context of SG to enable the&lt;br&gt;
monitoring, in real time, of the events that occur in the ecosystem and to predict following&lt;br&gt;
events.&lt;/p&gt;</description>
    <description descriptionType="Other">This work has received funding from the European Union's Horizon 2020 research and
innovation programme under the Marie Sklodowska-Curie grant agreement No 641794
(project DREAM-GO) and from FEDER Funds through COMPETE program and from
National Funds through FCT under the project UID/EEA/00760/2013.</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>Fundação para a Ciência e a Tecnologia</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100001871</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/FCT/5876/147448/">147448</awardNumber>
      <awardTitle>Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development</awardTitle>
    </fundingReference>
  </fundingReferences>
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