The vision of a Digital Earth calls for more dynamic information systems,new sources of information,and stronger capabilities for their integration.Sensor networks have been identified as a major information source fo...The vision of a Digital Earth calls for more dynamic information systems,new sources of information,and stronger capabilities for their integration.Sensor networks have been identified as a major information source for the Digital Earth,while Semantic Web technologies have been proposed to facilitate integration.So far,sensor data are stored and published using the Observations&Measurements standard of the Open Geospatial Consortium(OGC)as data model.With the advent of Volunteered Geographic Information and the Semantic Sensor Web,work on an ontological model gained importance within Sensor Web Enablement(SWE).In contrast to data models,an ontological approach abstracts from implementation details by focusing on modeling the physical world from the perspective of a particular domain.Ontologies restrict the interpretation of vocabularies toward their intended meaning.The ongoing paradigm shift to Linked Sensor Data complements this attempt.Two questions have to be addressed:(1)how to refer to changing and frequently updated data sets using Uniform Resource Identifiers,and(2)how to establish meaningful links between those data sets,that is,observations,sensors,features of interest,and observed properties?In this paper,we present a Linked Data model and a RESTful proxy for OGC’s Sensor Observation Service to improve integration and inter-linkage of observation data for the Digital Earth.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
基金The presented work is developed within the 528 North semantics community,and partly funded by the European projects UncertWeb(FP7-248488)ENVISION(FP7-249170)the GENESIS project(an Integrated Project,contract number 223996).
文摘The vision of a Digital Earth calls for more dynamic information systems,new sources of information,and stronger capabilities for their integration.Sensor networks have been identified as a major information source for the Digital Earth,while Semantic Web technologies have been proposed to facilitate integration.So far,sensor data are stored and published using the Observations&Measurements standard of the Open Geospatial Consortium(OGC)as data model.With the advent of Volunteered Geographic Information and the Semantic Sensor Web,work on an ontological model gained importance within Sensor Web Enablement(SWE).In contrast to data models,an ontological approach abstracts from implementation details by focusing on modeling the physical world from the perspective of a particular domain.Ontologies restrict the interpretation of vocabularies toward their intended meaning.The ongoing paradigm shift to Linked Sensor Data complements this attempt.Two questions have to be addressed:(1)how to refer to changing and frequently updated data sets using Uniform Resource Identifiers,and(2)how to establish meaningful links between those data sets,that is,observations,sensors,features of interest,and observed properties?In this paper,we present a Linked Data model and a RESTful proxy for OGC’s Sensor Observation Service to improve integration and inter-linkage of observation data for the Digital Earth.
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.
