Big data analytics for earth sciences: the earth server approach (Articolo in rivista)

Type
Label
  • Big data analytics for earth sciences: the earth server approach (Articolo in rivista) (literal)
Anno
  • 2015-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1080/17538947.2014.1003106 (literal)
Alternative label
  • Peter Baumann, Paolo Mazzetti, Joachim Ungar, Roberto Barbera, Damiano Barboni, Alan Beccati, Lorenzo Bigagli, Enrico Boldrini, Riccardo Bruno, Antonio Calanducci, Piero Campalani, Oliver Clements, Alex Dumitru, Mike Grant, Pasquale Herzig, George Kakaletris, John Laxton, Panagiota Koltsida, Kinga Lipskoch, Alireza Rezaei Mahdiraji, Simone Mantovani, Vlad Merticariu, Antonio Messina, Dimitar Misev, Stefano Natali, Stefano Nativi, Jelmer Oosthoek, Marco Pappalardo, James Passmore, Angelo Pio Rossi, Francesco Rundo, Marcus Sen, Vittorio Sorbera, Don Sullivan, Mario Torrisi, Leonardo Trovato, Maria Grazia Veratelli & Sebastian Wagner (2015)
    Big data analytics for earth sciences: the earth server approach
    in International journal of digital earth (Online)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Peter Baumann, Paolo Mazzetti, Joachim Ungar, Roberto Barbera, Damiano Barboni, Alan Beccati, Lorenzo Bigagli, Enrico Boldrini, Riccardo Bruno, Antonio Calanducci, Piero Campalani, Oliver Clements, Alex Dumitru, Mike Grant, Pasquale Herzig, George Kakaletris, John Laxton, Panagiota Koltsida, Kinga Lipskoch, Alireza Rezaei Mahdiraji, Simone Mantovani, Vlad Merticariu, Antonio Messina, Dimitar Misev, Stefano Natali, Stefano Nativi, Jelmer Oosthoek, Marco Pappalardo, James Passmore, Angelo Pio Rossi, Francesco Rundo, Marcus Sen, Vittorio Sorbera, Don Sullivan, Mario Torrisi, Leonardo Trovato, Maria Grazia Veratelli & Sebastian Wagner (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://dx.doi.org/10.1080/17538947.2014.1003106 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Jacobs University, Bremen, Germany;CNR-IIA, National Research Council of Italy - Institute of Atmospheric Pollution Research, Florence, Italy; EOX IT Services GmbH, Vienna, Austria; Consorzio COMETA, Catania, Italy; MEEO S.r.l., Ferrara, Italy; Jacobs University, Bremen, Germany;CNR-IIA, National Research Council of Italy - Institute of Atmospheric Pollution Research, Florence, Italy; CNR-IIA, National Research Council of Italy - Institute of Atmospheric Pollution Research, Florence, Italy; Consorzio COMETA, Catania, Italy; Italian National Institute for Nuclear Physics - Division of Catania, Catania, Italy; Jacobs University, Bremen, Germany;Plymouth Marine Laboratory, Plymouth, UK;Jacobs University, Bremen, Germany;Plymouth Marine Laboratory, Plymouth, UK;Fraunhofer IGD, Darmstadt, Germany; Athena Research and Innovation Center in Information Communication & Knowledge Technologies, Athens, Greece; British Geological Survey, Edinburgh, UK; Athena Research and Innovation Center in Information Communication & Knowledge Technologies, Athens, Greece; Jacobs University, Bremen, Germany;Jacobs University, Bremen, Germany;MEEO S.r.l., Ferrara, Italy;Jacobs University, Bremen, Germany;Software Engineering Italia S.r.l., Catania, Italy;Jacobs University, Bremen, Germany;MEEO S.r.l., Ferrara, Italy; CNR-IIA, National Research Council of Italy - Institute of Atmospheric Pollution Research, Florence, Italy;Jacobs University, Bremen, Germany;Software Engineering Italia S.r.l., Catania, Italy;British Geological Survey, Edinburgh, UK;Jacobs University, Bremen, Germany;Consorzio COMETA, Catania, Italy; British Geological Survey, Keyworth, UK; Consorzio COMETA, Catania, Italy; NASA Ames Research Center, CA, USA; Italian National Institute for Nuclear Physics - Division of Catania, Catania, Italy; Software Engineering Italia S.r.l., Catania, Italy; MEEO S.r.l., Ferrara, Italy; Fraunhofer IGD, Darmstadt, Germany (literal)
Titolo
  • Big data analytics for earth sciences: the earth server approach (literal)
Abstract
  • Big Data Analytics is an emerging field since massive storage and computing capabilities have been made available by advanced e-infrastructures. Earth and Environmental sciences are likely to benefit from Big Data Analytics techniques supporting the processing of the large number of Earth Observation datasets currently acquired and generated through observations and simulations. However, Earth Science data and applications present specificities in terms of relevance of the geospatial information, wide heterogeneity of data models and formats, and complexity of processing. Therefore, Big Earth Data Analytics requires specifically tailored techniques and tools. The EarthServer Big Earth Data Analytics engine offers a solution for coverage-type datasets, built around a high performance array database technology, and the adoption and enhancement of standards for service interaction (OGC WCS and WCPS). The EarthServer solution, led by the collection of requirements from scientific communities and international initiatives, provides a holistic approach that ranges from query languages and scalability up to mobile access and visualization. The result is demonstrated and validated through the development of lighthouse applications in the Marine, Geology, Atmospheric, Planetary and Cryospheric science domains. (literal)
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