Geospatial Information Categories Mapping in a Cross-lingual Environment: A Case Study of “Surface Water” Categories in Chinese and American Topographic Maps

Xi Kuai,Yu Liu,Shen Hang,Lin Li,Zhijun Zhang,Heng Luo

doi:10.3390/ijgi5060090

Xi Kuai, Yu Liu + Show 4 more

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https://doi.org/10.3390/ijgi5060090

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Abstract

The need for integrating geospatial information (GI) data from various heterogeneous sources has seen increased importance for geographic information system (GIS) interoperability. Using domain ontologies to clarify and integrate the semantics of data is considered as a crucial step for successful semantic integration in the GI domain. Nevertheless, mechanisms are still needed to facilitate semantic mapping between GI ontologies described in different natural languages. This research establishes a formal ontology model for cross-lingual geospatial information ontology mapping. By first extracting semantic primitives from a free-text definition of categories in two GI classification standards with different natural languages, an ontology-driven approach is used, and a formal ontology model is established to formally represent these semantic primitives into semantic statements, in which the spatial-related properties and relations are considered as crucial statements for the representation and identification of the semantics of the GI categories. Then, an algorithm is proposed to compare these semantic statements in a cross-lingual environment. We further design a similarity calculation algorithm based on the proposed formal ontology model to distance the semantic similarities and identify the mapping relationships between categories. In particular, we work with two GI classification standards for Chinese and American topographic maps. The experimental results demonstrate the feasibility and reliability of the proposed model for cross-lingual geospatial information ontology mapping.

Highlights

The vision of a “Digital Earth” articulated by US Vice President Al Gore [1,2,3] has contributed significantly to the growth in global geospatial information (GI) on physical and social environments
This is because all the semantic statements used to represent the semantic meaning of these two concepts are correspondingly matched, and all the mapping relationships between them are “exact match”
The presented research focuses on the determination of semantic mapping relationships between categories in different GI ontologies with natural language barriers

Summary

Introduction

The vision of a “Digital Earth” articulated by US Vice President Al Gore [1,2,3] has contributed significantly to the growth in global geospatial information (GI) on physical and social environments. A data integration process is not as simple as joining several systems because any effort at information sharing runs into the problem of semantic heterogeneity [7]. Semantic heterogeneity occurs when enabling interoperability across geographic information systems (GIS) [8,9,10,11] because GIS are often designed to address data from highly distributed, multidisciplinary, and cross-lingual data sources with different application demands [12]. Domain ontologies are built as a mediator to exchange information in such a way that the precise meaning of the data (i.e., semantics) is readily retrievable beyond simple keyword matching via knowledge representation languages and reasoning [7,13,14,15]. Ontology engineering has been regarded as an effective means of providing seamless connection between component GIS at the semantic level [8,12,16]

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