A uniform metadata representation is introduced for heterogeneous databases, multi media information and other information sources. Some features about metadata are analyzed. The limitation of existing metadata model...A uniform metadata representation is introduced for heterogeneous databases, multi media information and other information sources. Some features about metadata are analyzed. The limitation of existing metadata model is compared with the new one. The metadata model is described in XML which is fit for metadata denotation and exchange. The well structured data, semi structured data and those exterior file data without structure are described in the metadata model. The model provides feasibility and extensibility for constructing uniform metadata model of data warehouse.展开更多
Remote sensing data acquisition is one of the most essential processes in the field of Earth observation.However,traditional methods to acquire data do not satisfy the requirements of current applications because larg...Remote sensing data acquisition is one of the most essential processes in the field of Earth observation.However,traditional methods to acquire data do not satisfy the requirements of current applications because large-scale data processing is required.To address this issue,this paper proposes a data acquisition framework that carries out remote sensing metadata planning and then realizes the online acquisition of large amounts of data.Firstly,this paper establishes a unified metadata cataloging model and realizes the catalog of metadata in a local database.Secondly,a coverage calculation model is presented,which can show users the data coverage information in a selected geographical region under the data requirements of a specific application.Finally,according to the data retrieval results and the coverage calcula-tion,a machine-to-machine interface is provided to acquire target remote sensing data.Experiments were conducted to verify the availability and practicality of the proposed frame-work,and the results show the strengths and powerful capabilities of our framework by overcoming deficiencies in traditional methods.It also achieved the online automatic acquisi-tion of large-scale heterogeneous remote sensing data,which can provide guidance for remote sensing data acquisition strategies.展开更多
Metadata is data about data,which is generated mainly for resources organization and description,facilitating finding,identifying,selecting and obtaining information.With the advancement of technologies,the acquisitio...Metadata is data about data,which is generated mainly for resources organization and description,facilitating finding,identifying,selecting and obtaining information.With the advancement of technologies,the acquisition of metadata has gradually become a critical step in data modeling and function operation,which leads to the formation of its methodological commons.A series of general operations has been developed to achieve structured description,semantic encoding and machine-understandable information,including entity definition,relation description,object analysis,attribute extraction,ontology modeling,data cleaning,disambiguation,alignment,mapping,relating,enriching,importing,exporting,service implementation,registry and discovery,monitoring etc.Those operations are not only necessary elements in semantic technologies(including linked data)and knowledge graph technology,but has also developed into the common operation and primary strategy in building independent and knowledge-based information systems.In this paper,a series of metadata-related methods are collectively referred to as'metadata methodological commons',which has a lot of best practices reflected in the various standard specifications of the Semantic Web.In the future construction of a multi-modal metaverse based on Web 3.0,it shall play an important role,for example,in building digital twins through adopting knowledge models,or supporting the modeling of the entire virtual world,etc.Manual-based description and coding obviously cannot adapted to the UGC(User Generated Contents)and AIGC(AI Generated Contents)-based content production in the metaverse era.The automatic processing of semantic formalization must be considered as a sure way to adapt metadata methodological commons to meet the future needs of Al era.展开更多
An ever-increasing number of sensor resources are being exposed via the World Wide Web to become part of the Digital Earth.Discovery,selection and use of these sensors and their observations require a robust sensor in...An ever-increasing number of sensor resources are being exposed via the World Wide Web to become part of the Digital Earth.Discovery,selection and use of these sensors and their observations require a robust sensor information model,but the consistent description of sensor metadata is a complex and difficult task.Currently,the only available robust model is SensorML,which is intentionally designed in a very generic way.Due to this genericness,interoperability can hardly be achieved without the definition of application profiles that further constrain the use and expressiveness of the root language.So far,such SensorML profiles have only been developed up to a limited extent.This work describes a new approach for defining sensor metadata,the Starfish Fungus Language(StarFL)model.This language follows a more restrictive approach and incorporates concepts from the recently published Semantic Sensor Network Ontology to overcome the key issues users are experiencing with SensorML.StarFL defines a restricted vocabulary and model for sensor metadata to achieve a high level of interoperability and a straightforward reusability of sensor descriptions.展开更多
文摘A uniform metadata representation is introduced for heterogeneous databases, multi media information and other information sources. Some features about metadata are analyzed. The limitation of existing metadata model is compared with the new one. The metadata model is described in XML which is fit for metadata denotation and exchange. The well structured data, semi structured data and those exterior file data without structure are described in the metadata model. The model provides feasibility and extensibility for constructing uniform metadata model of data warehouse.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences[grant number XDA19020201]。
文摘Remote sensing data acquisition is one of the most essential processes in the field of Earth observation.However,traditional methods to acquire data do not satisfy the requirements of current applications because large-scale data processing is required.To address this issue,this paper proposes a data acquisition framework that carries out remote sensing metadata planning and then realizes the online acquisition of large amounts of data.Firstly,this paper establishes a unified metadata cataloging model and realizes the catalog of metadata in a local database.Secondly,a coverage calculation model is presented,which can show users the data coverage information in a selected geographical region under the data requirements of a specific application.Finally,according to the data retrieval results and the coverage calcula-tion,a machine-to-machine interface is provided to acquire target remote sensing data.Experiments were conducted to verify the availability and practicality of the proposed frame-work,and the results show the strengths and powerful capabilities of our framework by overcoming deficiencies in traditional methods.It also achieved the online automatic acquisi-tion of large-scale heterogeneous remote sensing data,which can provide guidance for remote sensing data acquisition strategies.
基金supported by the National Social Science Foundation(Grant/Award Number:21&ZD334)。
文摘Metadata is data about data,which is generated mainly for resources organization and description,facilitating finding,identifying,selecting and obtaining information.With the advancement of technologies,the acquisition of metadata has gradually become a critical step in data modeling and function operation,which leads to the formation of its methodological commons.A series of general operations has been developed to achieve structured description,semantic encoding and machine-understandable information,including entity definition,relation description,object analysis,attribute extraction,ontology modeling,data cleaning,disambiguation,alignment,mapping,relating,enriching,importing,exporting,service implementation,registry and discovery,monitoring etc.Those operations are not only necessary elements in semantic technologies(including linked data)and knowledge graph technology,but has also developed into the common operation and primary strategy in building independent and knowledge-based information systems.In this paper,a series of metadata-related methods are collectively referred to as'metadata methodological commons',which has a lot of best practices reflected in the various standard specifications of the Semantic Web.In the future construction of a multi-modal metaverse based on Web 3.0,it shall play an important role,for example,in building digital twins through adopting knowledge models,or supporting the modeling of the entire virtual world,etc.Manual-based description and coding obviously cannot adapted to the UGC(User Generated Contents)and AIGC(AI Generated Contents)-based content production in the metaverse era.The automatic processing of semantic formalization must be considered as a sure way to adapt metadata methodological commons to meet the future needs of Al era.
文摘An ever-increasing number of sensor resources are being exposed via the World Wide Web to become part of the Digital Earth.Discovery,selection and use of these sensors and their observations require a robust sensor information model,but the consistent description of sensor metadata is a complex and difficult task.Currently,the only available robust model is SensorML,which is intentionally designed in a very generic way.Due to this genericness,interoperability can hardly be achieved without the definition of application profiles that further constrain the use and expressiveness of the root language.So far,such SensorML profiles have only been developed up to a limited extent.This work describes a new approach for defining sensor metadata,the Starfish Fungus Language(StarFL)model.This language follows a more restrictive approach and incorporates concepts from the recently published Semantic Sensor Network Ontology to overcome the key issues users are experiencing with SensorML.StarFL defines a restricted vocabulary and model for sensor metadata to achieve a high level of interoperability and a straightforward reusability of sensor descriptions.
