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
Big Earth Data has experienced a considerable increase in volume in recent years due to improved sensing technologies and improvement of numerical-weather prediction models.The traditional geospatial data analysis wor...Big Earth Data has experienced a considerable increase in volume in recent years due to improved sensing technologies and improvement of numerical-weather prediction models.The traditional geospatial data analysis workflow hinders the use of large volumes of geospatial data due to limited disc space and computing capacity.Geospatial web service technologies bring new opportunities to access large volumes of Big Earth Data via the Internet and to process them at server-side.Four practical examples are presented from the marine,climate,planetary and earth observation science communities to show how the standard interface Web Coverage Service and its processing extension can be integrated into the traditional geospatial data workflow.Web service technologies offer a time-and cost-effective way to access multidimensional data in a user-tailored format and allow for rapid application development or time-series extraction.Data transport is minimised and enhanced processing capabilities are offered.More research is required to investigate web service implementations in an operational mode and large data centres have to become more progressive towards the adoption of geo-data standard interfaces.At the same time,data users have to become aware of the advantages of web services and be trained how to benefit from them most.展开更多
基金the European Community under grant agreement 283610 EarthServer.
文摘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.
基金the European Union’s Horizon 2020 Framework Programme research and innovation agreement[grant number 654367]。
文摘Big Earth Data has experienced a considerable increase in volume in recent years due to improved sensing technologies and improvement of numerical-weather prediction models.The traditional geospatial data analysis workflow hinders the use of large volumes of geospatial data due to limited disc space and computing capacity.Geospatial web service technologies bring new opportunities to access large volumes of Big Earth Data via the Internet and to process them at server-side.Four practical examples are presented from the marine,climate,planetary and earth observation science communities to show how the standard interface Web Coverage Service and its processing extension can be integrated into the traditional geospatial data workflow.Web service technologies offer a time-and cost-effective way to access multidimensional data in a user-tailored format and allow for rapid application development or time-series extraction.Data transport is minimised and enhanced processing capabilities are offered.More research is required to investigate web service implementations in an operational mode and large data centres have to become more progressive towards the adoption of geo-data standard interfaces.At the same time,data users have to become aware of the advantages of web services and be trained how to benefit from them most.
