Big Data Analytics for Earth Sciences: the EarthServer approach
Authors: 
Peter Baumann
Authors: 
Paolo Mazzetti
Authors: 
Joachim Ungar
Authors: 
Roberto Barbera
Authors: 
Damiano Barboni
Authors: 
Oliver Clements
Authors: 
Alex Dumitru
Authors: 
Mike Grant
Authors: 
Pasquale Herzig
Authors: 
George Kakaletris
Authors: 
John Laxton
Authors: 
Panagiota Koltsida
Authors: 
Kinga Lipskoch
Authors: 
Alireza Rezaei Mahdiraji
Authors: 
Simone Mantonavi
Authors: 
Vlad Catalin Merticariu
Authors: 
Antonio Messina
Authors: 
Dimitar Misev
Authors: 
Stefano Natali
Authors: 
Stefano Nativi
Authors: 
Jelmer Oosthoek
Authors: 
Marco Pappalardo
Authors: 
James Passmore
Authors: 
Angelo Pio Rossi
Authors: 
Francesco Rundo
Authors: 
Marcus Sen
Authors: 
Vittorio Sorbera
Authors: 
Don Sullivan
Authors: 
Mario Torrisi
Authors: 
Leonardo Trovato
Authors: 
Maria Grazia Veratelli
Authors: 
Wagner Sebastian
Date published: 
2015
Published In: 
International Journal of Digital Earth
Type: 
Journal Article
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.


Big Data Analytics for Earth Sciences: the EarthServer approach - ResearchGate. Available from: http://www.researchgate.net/publication/273126396_Big_Data_Analytics_for_Earth_Sciences_the_EarthServer_approach [accessed Apr 16, 2015].

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