WMO:an ontology for the semantic enrichment of wetland monitoring data  

作　　者：Xin Xiao Hui Lin Chaoyang Fang 

机构地区：[1]School of Geography and Environment&Key Laboratory of Poyang Lake Wetland and Watershed Research,Ministry of Education,Jiangxi Normal University,Nanchang,People's Republic of China

出　　处：《International Journal of Digital Earth》2023年第1期2189-2211,共23页国际数字地球学报（英文）

基　　金：supported by National Natural Science Foundation of China[grant no U1811464];Graduate Inno-vation Fund Project of the Education Department of Jiangxi Province[grant no YC2022 B076]。

摘　　要：Rich observation data generated by ubiquitous sensors are vital for wetland monitoring,spanning from the prediction of natural disasters to emergency response.Such sensors use different data acquisition and description methods and,if combined,could provide a comprehensive description of the wetland.Unfortunately,these data remain hidden in isolated silos,and their variety makes integration and interoperability a significant challenge.In this work,we develop a semantic model for wetland monitoring data using an agile and modular approach,namely,wetland monitoring ontology(WMO),which containsfive modules:wetland ecosystem,monitoring indicator,monitoring context,geospatial context,and temporal context.The proposed ontology supports the semantic interoperability and integration of wetland monitoring data from multiple sources,domains,modes,and spatiotemporal scales.We also provide two real-world use cases to validate the WMO and demonstrate the WMO’s usability and reusability.

关 键 词：ONTOLOGY knowledge graph wetland monitoring semantic interoperability spatiotemporal data 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]