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Big Data Analytics for Earth Sciences:the EarthServer approach

International Journal of Digital Earth 2016年第1期9卷 3-29页

作者： 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 Dumitrua,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 Large-Scale Scientific Information Systems Jacobs UniversityBremenGermany Rasdaman GmbH BremenGermany CNR-IIA National Research Council of ItalyInstitute of Atmospheric Pollution ResearchFlorenceItaly EOX IT Services GmbH ViennaAustria Consorzio COMETA CataniaItaly Division of Catania Italian National Institute for Nuclear PhysicsCataniaItaly Department of Physics and Astronomy University of CataniaCataniaItaly MEEO S.r.l. FerraraItaly Plymouth Marine Laboratory PlymouthUK Fraunhofer IGD DarmstadtGermany Athena Research and Innovation Center in Information Communication&Knowledge Technologies AthensGreece British Geological Survey EdinburghUK Software Engineering Italia S.r.l. CataniaItaly British Geological Survey KeyworthUK NASA Ames Research Center Moffett FieldCAUSA

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.

关键词： big data Big Data Analytics array databases Earth Sciences interoperability standards

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