Big Data Analytics for Earth Sciences: the EarthServer approach

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 Observatio...

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Published in:International journal of digital earth Vol. 9; no. 1; pp. 3 - 29
Main Authors: Baumann, Peter, Mazzetti, Paolo, Ungar, Joachim, Barbera, Roberto, Barboni, Damiano, Beccati, Alan, Bigagli, Lorenzo, Boldrini, Enrico, Bruno, Riccardo, Calanducci, Antonio, Campalani, Piero, Clements, Oliver, Dumitru, Alex, Grant, Mike, Herzig, Pasquale, Kakaletris, George, Laxton, John, Koltsida, Panagiota, Lipskoch, Kinga, Mahdiraji, Alireza Rezaei, Mantovani, Simone, Merticariu, Vlad, Messina, Antonio, Misev, Dimitar, Natali, Stefano, Nativi, Stefano, Oosthoek, Jelmer, Pappalardo, Marco, Passmore, James, Rossi, Angelo Pio, Rundo, Francesco, Sen, Marcus, Sorbera, Vittorio, Sullivan, Don, Torrisi, Mario, Trovato, Leonardo, Veratelli, Maria Grazia, Wagner, Sebastian
Format: Journal Article
Language:English
Published: Abingdon Taylor & Francis 02.01.2016
Taylor & Francis Ltd
Subjects:
Analytics
array databases
Arrays
Big Data
Big Data Analytics
Customer information files
data analysis
data collection
Data management
Earth
Earth science
Earth Sciences
Environmental science
geology
geospatial data processing
Heterogeneity
interoperability
languages
Mathematical models
Point of sale systems
ISSN:1753-8955, 1753-8947, 1753-8955
Online Access:Get full text
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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.
AbstractList 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.
Author Sen, Marcus
Trovato, Leonardo
Natali, Stefano
Barbera, Roberto
Bigagli, Lorenzo
Dumitru, Alex
Herzig, Pasquale
Wagner, Sebastian
Baumann, Peter
Beccati, Alan
Laxton, John
Passmore, James
Rundo, Francesco
Sorbera, Vittorio
Veratelli, Maria Grazia
Lipskoch, Kinga
Oosthoek, Jelmer
Messina, Antonio
Nativi, Stefano
Merticariu, Vlad
Campalani, Piero
Calanducci, Antonio
Mahdiraji, Alireza Rezaei
Grant, Mike
Barboni, Damiano
Mantovani, Simone
Misev, Dimitar
Rossi, Angelo Pio
Bruno, Riccardo
Mazzetti, Paolo
Clements, Oliver
Kakaletris, George
Boldrini, Enrico
Pappalardo, Marco
Koltsida, Panagiota
Torrisi, Mario
Ungar, Joachim
Sullivan, Don
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Snippet Big Data Analytics is an emerging field since massive storage and computing capabilities have been made available by advanced e-infrastructures. Earth and...
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SubjectTerms Analytics
array databases
Arrays
Big Data
Big Data Analytics
Customer information files
data analysis
data collection
Data management
Earth
Earth science
Earth Sciences
Environmental science
geology
geospatial data processing
Heterogeneity
interoperability
languages
Mathematical models
Point of sale systems
Title Big Data Analytics for Earth Sciences: the EarthServer approach
URI https://www.tandfonline.com/doi/abs/10.1080/17538947.2014.1003106
https://www.proquest.com/docview/1767084438
https://www.proquest.com/docview/1787976438
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https://www.proquest.com/docview/1808049037
Volume 9
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