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AGINFRA PLUS D7.2 - Big Data Analysis and Visualisation

Neveu, Pascal; Boizet, Alice


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  <identifier identifierType="DOI">10.5281/zenodo.1304190</identifier>
  <creators>
    <creator>
      <creatorName>Neveu, Pascal</creatorName>
      <givenName>Pascal</givenName>
      <familyName>Neveu</familyName>
      <affiliation>INRA</affiliation>
    </creator>
    <creator>
      <creatorName>Boizet, Alice</creatorName>
      <givenName>Alice</givenName>
      <familyName>Boizet</familyName>
      <affiliation>INRA</affiliation>
    </creator>
  </creators>
  <titles>
    <title>AGINFRA PLUS D7.2 - Big Data Analysis and Visualisation</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2017</publicationYear>
  <subjects>
    <subject>software deliverable; Virtual Research Environment; Food Security Community; High-throughput phenotyping; phenomics community; Visualization features</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2017-12-22</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="Text">Project deliverable</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/1304190</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.1304189</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/aginfra</relatedIdentifier>
  </relatedIdentifiers>
  <version>1.0 | Final</version>
  <rightsList>
    <rights rightsURI="http://creativecommons.org/licenses/by-nc/4.0/legalcode">Creative Commons Attribution Non Commercial 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;D7.2 &amp;ndash; Big Data Analysis and Visualization is a software deliverable. It presents the VRE (Virtual Research Environment) that has been set up on the D4Science platform to support the Food Security Community use case, which is High-throughput phenotyping. This document presents the different features which will be implemented in this VRE in order to meet the phenomics researchers&amp;rsquo; needs.&lt;/p&gt;

&lt;p&gt;The Food Security VRE already provides standard collaboration features such as file sharing and message posting but it is also planned to add new features to fit the phenomics community needs. For instance, the user will have access to high-throughput phenotyping platforms data through web services and will be able to run analytics workflows on this data. Visualization features will be deployed such as pair scatter plots on phenotypic traits or spatial representation of different plant varieties. The user will also&lt;br&gt;
have access to several ontologies used in phenomics.&lt;/p&gt;

&lt;p&gt;While the work on the VRE is proceeding, a group of representative persons of the plant community will test the VRE features and their expectations will be collected. This will help to improve deployed features or to deploy new ones.&lt;/p&gt;

&lt;p&gt;The deliverable has been created on the public space of the AGINFRA+ Wiki and is accessible through the following link:&lt;/p&gt;

&lt;p&gt;https://support.d4science.org/projects/aginfraplus_wiki/wiki/D72_-_Big_Data_Analysis_and_Visualisation&lt;/p&gt;</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/731001/">731001</awardNumber>
      <awardTitle>Accelerating user-driven e-infrastructure innovation in Food  Agriculture</awardTitle>
    </fundingReference>
  </fundingReferences>
</resource>
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