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Big Data Analytics for Earth Sciences:the EarthServer approach 被引量:3
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作者 Peter Baumann Paolo Mazzetti +34 位作者 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 《International Journal of Digital Earth》 SCIE EI CSCD 2016年第1期3-29,共27页
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 Anal... 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. 展开更多
关键词 big data Big Data Analytics array databases Earth Sciences INTEROPERABILITY STANDARDS
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