地理语义查询关键技术研究

发布时间：2018-01-21 05:12

本文关键词： 地理语义数据 SPARQL GeoSPARQL 地理语义查询地理语义空间索引　出处：《武汉大学》2013年博士论文　论文类型：学位论文

【摘要】：随着语义技术在地理空间领域的应用和发展,地理语义化项目越来越多,地理语义数据也愈加丰富和庞大。为了能够有效地处理和应用地理语义数据,快速、有效、智能化的地理语义查询是十分必要的。 GeoSPARQL规范是地理本体、SPARQL语法空间扩展、推理规则等技术推动下的产物。GeoSPARQL规范是OGC2012年9月发布的一个地理语义查询规范,该规范的目的是提供一个能够广泛使用的地理语义查询使用方案,从而能够对异构的、不兼容的地理语义数据进行一致的表示和查询。GeoSPARQL规范定义了一个与简单要素模型兼容的RDF/OWL本体词表,用于描述地物、地物几何对象以及两者间的关系；一个SPARQL空间扩展函数集,用于规范基于SPARQL语法的地理语义空间查询的谓词构建；一个规则交换格式(RIF,Rule Interchange Format)集,用于地理语义推理查询。为了实现对地理语义数据的快速有效的查询,从而更加有效的处理和应用地理语义数据,本文基于GeoSPARQL规范,在语义相关技术的支持下研究和解决地理语义查询的几个关键问题,即SPARQL语法上的空间查询扩展,高效的数据组织,以及智能化查询。本文主要有如下贡献： 1、在SPARQL语法层上构建和实现了GeoSPARQL规范中的空间算子针对OGC最新的地理语义查询规范GeoSPARQL,基于ARQ的查询和扩展机制,在SPARQL语法层上构建和实现了GeoSPARQL的空间算子,实现地理语义空间关系查询。 2、提出并实现满足GeoSPARQL规范中地理本体的地理语义空间索引在RDF数据组织和传统空间索引的研究基础上,提出地理语义数据模型—空间四元组(GeoQuard)模型；在该模型的基础上,提出和构建了地理语义空间索引结构。 3、提出和实现了一种基于STX语法的流式数据转换方法在地理语义属性推理查询中,针对方法流程中的GML文件到地理本体文件的数据转换问题,提出和实现了一种基于STX语法的流式数据转换方法,实现GML文件到本体文件的快速有效转换。 4、构建和实现了GeoSPARQL的解析层,支持对GeoSPARQL中的本体实例数据以及GeoSPARQL的衍生本体数据的解析和空间可视化。本文的研究内容丰富了语义技术在地理空间领域的研究,一定程度上促进了地理语义查询的研究和应用。
[Abstract]:With the application and development of semantic technology in the field of geospatial, there are more and more geo-semantic projects and geo-semantic data become richer and larger. In order to effectively process and apply geo-semantic data, it is fast. Effective and intelligent geographical semantic query is very necessary. The GeoSPARQL specification is an extension of the geographical ontology Sparql syntax space. The product, GeoSparql, which is driven by reasoning rules and other technologies, is a geographical semantic query specification published by OGC2012 in September. The purpose of this specification is to provide a widely used solution for geo-semantic query usage, so that it can be used for heterogeneous. Incompatibility of geographical semantic data for consistent representation and query. GeoSparql specification defines a simple element model compatible with the RDF/OWL ontology vocabulary used to describe features. Geometric objects of ground objects and the relationship between them; A set of extended functions in SPARQL space, which is used to construct predicates for geo-semantic spatial query based on SPARQL syntax. A rule exchange format called riff Rule Interchange format, which is used for geo-semantic reasoning query. In order to realize the quick and effective query of the geographic semantic data, so as to process and apply the geographic semantic data more effectively, this paper is based on the GeoSPARQL specification. With the support of semantic related technology, several key problems of geographic semantic query are studied and solved, such as spatial query expansion in SPARQL syntax, efficient data organization, and intelligent query. The main contributions of this paper are as follows: 1. The spatial operators in the GeoSPARQL specification are constructed and implemented on the SPARQL syntax layer. Aiming at GeoSPARQL, the latest geosemantic query specification of OGC, the query and extension mechanism based on ARQ is introduced. The spatial operator of GeoSPARQL is constructed and implemented on the SPARQL syntax layer, and the query of geographical semantic spatial relation is realized. 2. A geographical semantic spatial index satisfying GeoSPARQL specification is proposed and implemented. Based on the research of RDF data organization and traditional spatial index, a geo-semantic data model-Spatial Quaternion GeoQuard model is proposed. Based on this model, a geographical semantic spatial index structure is proposed and constructed. 3. A method of streaming data conversion based on STX syntax is proposed and implemented. In order to solve the problem of data conversion from GML files to geographical ontology files in the method flow, a method of streaming data conversion based on STX syntax is proposed and implemented in geographical semantic attribute reasoning query. Realize the fast and effective transformation from GML file to ontology file. 4. Build and implement the parsing layer of GeoSPARQL. Supports parsing and spatial visualization of ontology instance data in GeoSPARQL and derivative ontology data in GeoSPARQL. The research content of this paper enriches the research of semantic technology in the field of geospatial, and to some extent promotes the research and application of geographical semantic query.
【学位授予单位】：武汉大学
【学位级别】：博士
【学位授予年份】：2013
【分类号】：TP391.1;P208

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