文章基本信息

标题：Ontology based Semantic Metadata for Imagery and Gridded Data
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作者：CHEN Xu ; ZHU Xinyan ; DU Daosheng 等
期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2008
卷号：XXXVII Part B2
页码：743-748
出版社：Copernicus Publications
摘要：Nowadays, huge volumes of imagery and gridded data are accessible. However they vary in formats and are stored at various organizations leading to problems of data discovery, data interoperability and usability. ISO19115, Content Standard for Digital Geospatial Metadata and some other norms don't provide enough provision for imagery and gridded data. UML and XML schema of metadata also don't provide semantic description of the data content within the dataset. So we provide the additional structure to describe the derivation of imagery and gridded data. This structure is intended to augment the existing metadata standard described in ISO 19115. We focus on identification information, data quality information, spatial representation information, content information, acquisition Information in ISO 19115, we extend these dataset packages, in order to describe the metadata of imagery and gridded data during the cycle of the image product. OWL permits a much richer table of semantics as well as a more flexible definition of classes and their attributes when compared to UML and XML schema. We propose the mapping rule between UML and OWL, summarize the similarities between UML and OWL concepts. Then we explain in detail the conventions we have adopted to translate the metadata UML model for imagery and gridded data into an OWL ontology, including naming conventions, data types, and restriction conditions between the two concepts. Finally, we store imagery and gridded data metadata ontologies and individuals in a semantic registry prototype, to demonstrate how to fully utilizing the semantic information implicitly embedded in metadata
关键词：Satellite Remote Sensing; Interoperability; Metadata; Semantics; Image Understanding; Ontology; Geo-information ; Management