地理空间数据的形态本体及其在数据发现中的应用

Kai Sun, Yunqiang Zhu, Peng Pan, Kan Luo, Dongxu Wang, Zhiwei Hou
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引用次数: 1

摘要

地理空间数据的语义异构性是实现关联数据、智能推荐和准确发现数据的主要瓶颈。本体理论是解决数据语义异构的有效途径。形态特征是数据语义异质性研究的重要内容。本文主要研究地理空间数据的形态特征,分析地理空间数据的概念、属性和关系,提出地理空间数据的概念体系。在此基础上,建立了地理空间数据的形态本体模型,定义了形态信息的形式化表示方法。最后,本文构建了形态本体,并将其应用于地球系统科学数据共享基础设施的元数据检索。验证实验表明,地理空间数据的形态学本体能够有效地解决数据的语义异构问题,显著提高数据发现结果的查全率和查全率。本文的研究方法和成果对解决其他领域数据语义异构问题具有重要的参考价值。
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Morphology-Ontology of geospatial data and its application in data discovery
Semantic heterogeneity of geospatial data is the main bottleneck for implementing linked data, intelligent recommendation and accurate discovery of data. The ontology theory is an effective way to solve the semantic heterogeneity of data. Morphological Characteristics is the important research content of Semantic heterogeneity of data. This paper mainly studies morphological characteristics of geospatial data, analyzes its concept, attribute, and relation, and puts forward its concepts system. On this basis, this paper builds the model of Morphology-Ontology of geospatial data and defines the method of formalization representation of morphological information. In the last part, this paper constructs Morphology-Ontology and applies it to the retrieval of metadata of the Data Sharing Infrastructure of Earth System Science. Verification tests show that Morphology-Ontology of geospatial data can solve the semantic heterogeneity of data effectively and improve the precision and recall of the result of data discovery significantly. The research methods and results of this paper are of great reference value to solve the semantic heterogeneity of data in other fields.
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