Abundant sensor data are now available online from a wealth of sources,which greatly enhance research efforts on the Digital Earth.The combination of distributed sensor networks and expanding citizen-sensing capabilit...Abundant sensor data are now available online from a wealth of sources,which greatly enhance research efforts on the Digital Earth.The combination of distributed sensor networks and expanding citizen-sensing capabilities provides a more synchronized image of earth’s social and physical landscapes.However,it remains difficult for researchers to use such heterogeneous Sensor Webs for scientific applications since data are published by following different standards and protocols and are in arbitrary formats.In this paper,we investigate the core challenges faced when consuming multiple sources for environmental applications using the Linked Data approach.We design and implement a system to achieve better data interoperability and integration by republishing real-world data into linked geo-sensor data.Our contributions include presenting:(1)best practices of re-using and matching the W3C Semantic Sensor Network(SSN)ontology and other popular ontologies for heterogeneous data modeling in the water resources application domain,(2)a newly developed spatial analysis tool for creating links,and(3)a set of RESTful OGC Sensor Observation Service(SOS)like Linked Data APIs.Our results show how a Linked Sensor Web can be built and used within the integrated water resource decision support application domain.展开更多
文摘Abundant sensor data are now available online from a wealth of sources,which greatly enhance research efforts on the Digital Earth.The combination of distributed sensor networks and expanding citizen-sensing capabilities provides a more synchronized image of earth’s social and physical landscapes.However,it remains difficult for researchers to use such heterogeneous Sensor Webs for scientific applications since data are published by following different standards and protocols and are in arbitrary formats.In this paper,we investigate the core challenges faced when consuming multiple sources for environmental applications using the Linked Data approach.We design and implement a system to achieve better data interoperability and integration by republishing real-world data into linked geo-sensor data.Our contributions include presenting:(1)best practices of re-using and matching the W3C Semantic Sensor Network(SSN)ontology and other popular ontologies for heterogeneous data modeling in the water resources application domain,(2)a newly developed spatial analysis tool for creating links,and(3)a set of RESTful OGC Sensor Observation Service(SOS)like Linked Data APIs.Our results show how a Linked Sensor Web can be built and used within the integrated water resource decision support application domain.
