WMO:an ontology for the semantic enrichment of wetland monitoring data
作者机构：School of Geography and Environment&Key Laboratory of Poyang Lake Wetland and Watershed ResearchMinistry of EducationJiangxi Normal UniversityNanchangPeople's Republic of China
出 版 物：《International Journal of Digital Earth》 (国际数字地球学报（英文）)
年 卷 期：2023年第16卷第1期
页 面：2189-2211页
核心收录：
学科分类：08[工学] 080203[工学-机械设计及理论] 0802[工学-机械工程]
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]
主 题：Ontology knowledge graph wetland monitoring semantic interoperability spatiotemporal data
摘 要：Rich observation data generated by ubiquitous sensors are vital for wetland monitoring,spanning from the prediction of natural disasters to emergency *** sensors use different data acquisition and description methods and,if combined,could provide a comprehensive description of the ***,these data remain hidden in isolated silos,and their variety makes integration and interoperability a significant *** 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 *** proposed ontology supports the semantic interoperability and integration of wetland monitoring data from multiple sources,domains,modes,and spatiotemporal *** also provide two real-world use cases to validate the WMO and demonstrate the WMO’s usability and reusability.
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