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  <titleInfo>
    <title>Proceedings of the 2019 conference on Big Data from Space (BIDS' 2019)</title>
    <subTitle>: turning data into insights : 19-21 February 2019, Munich (Germany)</subTitle>
  </titleInfo>
  <name type="personal">
    <namePart>Soille, Pierre</namePart>
  </name>
  <name type="personal">
    <namePart>Loekken, Sveinung</namePart>
  </name>
  <name type="personal">
    <namePart>Albani, Sergio</namePart>
  </name>
  <name type="corporate">
    <namePart>Comisión Europea</namePart>
    <namePart>Centro Común de Investigación</namePart>
  </name>
  <name type="corporate">
    <namePart>SatCen</namePart>
  </name>
  <name type="corporate">
    <namePart>Esa, European Space Agency</namePart>
  </name>
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  <genre authority="marc">technical report</genre>
  <genre authority="marc">conference publication</genre>
  <originInfo>
    <place>
      <placeTerm type="code" authority="marccountry">eu</placeTerm>
    </place>
    <place>
      <placeTerm type="text">Luxemburgo</placeTerm>
    </place>
    <publisher>Oficina de Publicaciones</publisher>
    <dateIssued>2019</dateIssued>
    <edition>4th edition</edition>
    <issuance>monographic</issuance>
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  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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    <extent>xii, 312 p. : il. col.; 1 documento PDF</extent>
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  <abstract>This 4th edition of the Big Data from Space conference is directed towards 'Turning Data into Insights'. Indeed, while the first editions of the conference concentrated on technologies and platforms capable of sustaining the sharp increase of data streams originating from space sensors, the development of efficient and effective methodologies and algorithms capable of extracting insights from these data is gradually becoming the main challenge. In this context, artificial intelligence and machine learning techniques have started to play a key role as illustrated by numerous papers of this conference edition. Methodological developments are motivated by the pressing need to extract information on large areas and/or over long time series to better understand the dynamics of the processes that are shaping our planet and indeed our universe in the case of data collected by telescopes. The topic of analysis ready data has also emerged since the last edition and is closely linked with the development of new data cube representations. Big data from space is also introducing some new legal challenges and the need for further developments of standards and interoperable interfaces between the growing number of platforms hosting multi-petabyte scale data co-located with processing capabilities. All these topics as well as other generic key aspects of big data are mirrored in dedicated sections of these proceedings.</abstract>
  <targetAudience authority="marctarget">specialized</targetAudience>
  <note type="statement of responsibility">/ edited by P. Soille, S. Loekken and S. Albani</note>
  <note>Includes bibliographical references.</note>
  <note>Reutilización autorizada, con indicación de la fuente bibliográfica. La política relativa a la reutilización de los documentos de la Comisión Europea fue establecida por la Decisión 2011/833/UE (DO L 330 de 14.12.2011, p. 39). Cualquier uso o reproducción de fotografías u otro material que no esté sujeto a los derechos de autor de la Unión Europea requerirá la autorización de sus titulares ; Unión Europea.</note>
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  <subject>
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  <subject>
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  <subject>
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    <topic>sistema de gestión de bases de datos</topic>
  </subject>
  <subject>
    <topic>base de datos</topic>
  </subject>
  <subject>
    <topic>Sistema de Información Geográfica</topic>
  </subject>
  <subject>
    <topic>Agencia Espacial Europea</topic>
  </subject>
  <subject>
    <topic>Centro de Satélites de la Unión Europea</topic>
  </subject>
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      <title>Proceedings</title>
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      <namePart>Big Data from Space (BIDS' 2019) (2019 : Munich, Germany).</namePart>
    </name>
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  <identifier type="isbn">978-92-76-00034-1</identifier>
  <identifier type="issn">1831-9424</identifier>
  <identifier type="uri">http://publications.jrc.ec.europa.eu/repository/bitstream/JRC115761/procbids19.pdf</identifier>
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