新型城镇化的建设和管理经常涉及到多源异构时空数据的集成和协同应用,其中基础地理数据因具有数据描述信息可被快速识别,有些数据如实时感知数据等,因没有描述信息而难以被识别,使得数据无法及时共享应用。因此,本文分析了不同新型城...新型城镇化的建设和管理经常涉及到多源异构时空数据的集成和协同应用,其中基础地理数据因具有数据描述信息可被快速识别,有些数据如实时感知数据等,因没有描述信息而难以被识别,使得数据无法及时共享应用。因此,本文分析了不同新型城镇化途径下时空数据共享应用需求,总结了时空数据的时间属性、空间属性和内容属性在共享应用中的作用,并从其可共享性快速识别的角度出发,以时空数据的时间、空间和内容等属性为主要内容设计了一个轻量级的时空数据共享信息描述框架(description framework of spatial data sharing information,DFSDSI)实现多标准时空本体数据共享特征的统一表达,从而为城镇多源异构时空数据可共享性的快速识别提供判断依据。展开更多
Currently,ocean data portals are being developed around the world based on Geographic Information Systems(GIS) as a source of ocean data and information.However,given the relatively high temporal frequency and the int...Currently,ocean data portals are being developed around the world based on Geographic Information Systems(GIS) as a source of ocean data and information.However,given the relatively high temporal frequency and the intrinsic spatial nature of ocean data and information,no current GIS software is adequate to deal effectively and efficiently with spatiotemporal data.Furthermore,while existing ocean data portals are generally designed to meet the basic needs of a broad range of users,they are sometimes very complicated for general audiences,especially for those without training in GIS.In this paper,a new technical architecture for an ocean data integration and service system is put forward that consists of four layers:the operation layer,the extract,transform,and load(ETL) layer,the data warehouse layer,and the presentation layer.The integration technology based on the XML,ontology,and spatiotemporal data organization scheme for the data warehouse layer is then discussed.In addition,the ocean observing data service technology realized in the presentation layer is also discussed in detail,including the development of the web portal and ocean data sharing platform.The application on the Taiwan Strait shows that the technology studied in this paper can facilitate sharing,access,and use of ocean observation data.The paper is based on an ongoing research project for the development of an ocean observing information system for the Taiwan Strait that will facilitate the prevention of ocean disasters.展开更多
We present dynamic mode decomposition (DMD) for studying the hairpin vortices generated by hemisphere protuberance measured by two-dimensional (2D) time-resolved (TR) particle image velocimetry (PIV) in a water channe...We present dynamic mode decomposition (DMD) for studying the hairpin vortices generated by hemisphere protuberance measured by two-dimensional (2D) time-resolved (TR) particle image velocimetry (PIV) in a water channel. The hairpins dynamic information is extracted by identifying their dominant frequencies and associated spatial structures. For this quasi-periodic data system, the resulting main Dynamic modes illustrate the different spatial structures associated with the wake vortex region and the near-wall region. By comparisons with proper orthogonal decomposition (POD), it can be concluded that the dynamic mode concentrates on a certain frequency component more effectively than the mode determined by POD. During the analysis, DMD has proven itself a robust and reliable algorithm to extract spatial-temporal coherent structures.展开更多
文摘新型城镇化的建设和管理经常涉及到多源异构时空数据的集成和协同应用,其中基础地理数据因具有数据描述信息可被快速识别,有些数据如实时感知数据等,因没有描述信息而难以被识别,使得数据无法及时共享应用。因此,本文分析了不同新型城镇化途径下时空数据共享应用需求,总结了时空数据的时间属性、空间属性和内容属性在共享应用中的作用,并从其可共享性快速识别的角度出发,以时空数据的时间、空间和内容等属性为主要内容设计了一个轻量级的时空数据共享信息描述框架(description framework of spatial data sharing information,DFSDSI)实现多标准时空本体数据共享特征的统一表达,从而为城镇多源异构时空数据可共享性的快速识别提供判断依据。
基金Supported by National High Technology Research and Development Program of China (863 Program) (Nos. 2009AA12Z225,2009AA12Z208)the National Natural Science Foundation of China (No. 61074132)
文摘Currently,ocean data portals are being developed around the world based on Geographic Information Systems(GIS) as a source of ocean data and information.However,given the relatively high temporal frequency and the intrinsic spatial nature of ocean data and information,no current GIS software is adequate to deal effectively and efficiently with spatiotemporal data.Furthermore,while existing ocean data portals are generally designed to meet the basic needs of a broad range of users,they are sometimes very complicated for general audiences,especially for those without training in GIS.In this paper,a new technical architecture for an ocean data integration and service system is put forward that consists of four layers:the operation layer,the extract,transform,and load(ETL) layer,the data warehouse layer,and the presentation layer.The integration technology based on the XML,ontology,and spatiotemporal data organization scheme for the data warehouse layer is then discussed.In addition,the ocean observing data service technology realized in the presentation layer is also discussed in detail,including the development of the web portal and ocean data sharing platform.The application on the Taiwan Strait shows that the technology studied in this paper can facilitate sharing,access,and use of ocean observation data.The paper is based on an ongoing research project for the development of an ocean observing information system for the Taiwan Strait that will facilitate the prevention of ocean disasters.
基金supported by the National Natural Science Foundation of China (Grant Nos. 10832001 and 10872145)the State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences
文摘We present dynamic mode decomposition (DMD) for studying the hairpin vortices generated by hemisphere protuberance measured by two-dimensional (2D) time-resolved (TR) particle image velocimetry (PIV) in a water channel. The hairpins dynamic information is extracted by identifying their dominant frequencies and associated spatial structures. For this quasi-periodic data system, the resulting main Dynamic modes illustrate the different spatial structures associated with the wake vortex region and the near-wall region. By comparisons with proper orthogonal decomposition (POD), it can be concluded that the dynamic mode concentrates on a certain frequency component more effectively than the mode determined by POD. During the analysis, DMD has proven itself a robust and reliable algorithm to extract spatial-temporal coherent structures.
