Geospatial data ontology: the semantic foundation of geospatial data integration and sharing
Geospatial data ontology: the semantic foundation of geospatial data integration and sharing
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DOI：
10.1080/20964471.2019.1661662
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发表时间：
2019-07
期刊：
影响因子：
4
通讯作者：
Kai Sun;Yunqiang Zhu;Peng Pan;Zhiwei Hou;Dongxu Wang;Weirong Li;Jia Song
中科院分区：
文献类型：
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作者：
Kai Sun;Yunqiang Zhu;Peng Pan;Zhiwei Hou;Dongxu Wang;Weirong Li;Jia Song
地理空间数据的有效集成和广泛共享是促进地理信息科学研究和应用的重要和基本前提。然而，地理空间数据的语义异构性是一个主要问题，显着阻碍地理空间数据集成和共享。本体被认为是一种很有前途的方式来解决语义问题，通过提供一个形式化的表示的地理实体和它们之间的关系，在机器可以理解的方式。基于本体的地理空间数据集成与共享已成为研究的热点。然而，缺乏一个专门的本体，将提供一个统一的描述地理空间数据。本文针对地理空间数据的特点，提出了一个统一的地理空间数据本体框架GeoDataOnt，为地理空间数据的集成与共享奠定语义基础。首先，我们提供了一个地理空间数据的特征层次结构。接下来，我们分析了地理空间数据的每个特征的语义问题。随后，我们提出了GeoDataOnt的总体框架，针对这些问题，根据地理空间数据的特点。然后将GeoDataOnt划分为多个模块，并对每个模块进行了详细的设计和实现。GeoDataOnt的主要限制和挑战，并讨论了GeoDataOnt的广泛应用。
ABSTRACT Effective integration and wide sharing of geospatial data is an important and basic premise to facilitate the research and applications of geographic information science. However, the semantic heterogeneity of geospatial data is a major problem that significantly hinders geospatial data integration and sharing. Ontologies are regarded as a promising way to solve semantic problems by providing a formalized representation of geographic entities and relationships between them in a manner understandable to machines. Thus, many efforts have been made to explore ontology-based geospatial data integration and sharing. However, there is a lack of a specialized ontology that would provide a unified description for geospatial data. In this paper, with a focus on the characteristics of geospatial data, we propose a unified framework for geospatial data ontology, denoted GeoDataOnt, to establish a semantic foundation for geospatial data integration and sharing. First, we provide a characteristics hierarchy of geospatial data. Next, we analyze the semantic problems for each characteristic of geospatial data. Subsequently, we propose the general framework of GeoDataOnt, targeting these problems according to the characteristics of geospatial data. GeoDataOnt is then divided into multiple modules, and we show a detailed design and implementation for each module. Key limitations and challenges of GeoDataOnt are identified, and broad applications of GeoDataOnt are discussed.