A case-based reasoning approach for task-driven spatial–temporally aware geospatial data discovery through geoportals

ABSTRACT

There is a critical need to develop a means for fast, task-driven discovery of geospatial data found in geoportals. Existing geoportals, however, only provide metadata-based means for discovery, with little support for task-driven discovery, especially when considering spatial–temporal awareness. To address this gap, this paper presents a Case-Based Reasoning-supported Geospatial Data Discovery (CBR-GDD) method and implementation that accesses geospatial data by tasks. The advantages of the CBR-GDD approach is that it builds an analogue reasoning process that provides an internal mechanism bridging tasks and geospatial data with spatial–temporal awareness, thus providing solutions based on past tasks. The CBR-GDD approach includes a set of algorithms that were successfully implemented via three components as an extension of geoportals: ontology-enhanced knowledge base, similarity assessment model, and case retrieval nets. A set of experiments and case studies validate the CBR-GDD approach and application, and demonstrate its efficiency.     

The framework of a geospatial semantic web-based spatial decision support system for Digital Earth

Abstract

While significant progress has been made to implement the Digital Earth vision, current implementation only makes it easy to integrate and share spatial data from distributed sources and has limited capabilities to integrate data and models for simulating social and physical processes. To achieve effectiveness of decision-making using Digital Earth for understanding the Earth and its systems, new infrastructures that provide capabilities of computational simulation are needed. This paper proposed a framework of geospatial semantic web-based interoperable spatial decision support systems (SDSSs) to expand capabilities of the currently implemented infrastructure of Digital Earth. Main technologies applied in the framework such as heterogeneous ontology integration, ontology-based catalog service, and web service composition were introduced. We proposed a partition-refinement algorithm for ontology matching and integration, and an algorithm for web service discovery and composition. The proposed interoperable SDSS enables decision-makers to reuse and integrate geospatial data and geoprocessing resources from heterogeneous sources across the Internet. Based on the proposed framework, a prototype to assist in protective boundary delimitation for Lunan Stone Forest conservation was implemented to demonstrate how ontology-based web services and the services-oriented architecture can contribute to the development of interoperable SDSSs in support of Digital Earth for decision-making.     

An algebraic approach to automated geospatial information fusion

This paper presents a new technique for information fusion. Unlike most previous work on information fusion, this paper explores the use of instance‐level (extensional) information within the fusion process. This paper proposes an algorithm that can be used automatically to infer the schema‐level structure necessary for information fusion from instance‐level information. The approach is illustrated using the example of geospatial land‐cover data. The method is then extended to operate under uncertainty, such as in cases where the data are inaccurate or imprecise. The paper describes the implementation of the fusion method within a software prototype. Finally, the paper discusses several key topics for future research, including applications of this work to spatial‐data mining and the semantic web.     

Ontologies of geographic information

This article explores the notion of a system of ontologies specifically designed for the needs of an information science. A framework for geographic information ontologies is outlined that focuses on geographic information constructs rather than on the direct representation of real-world entities or on linguistic terms. The framework takes the form of a generative hierarchy anchored by the notion of intentionality at one end and of a spatiotemporal field of potentially relevant information at the other. Two theoretical notions are used in the generation of the hierarchy. The first is the principle of semantic contraction, whereby, starting from a level of geographic information constructs specified so as to reflect user intentionality, semantically coherent domains of properties are removed over several steps until only the rudiments of a spatiotemporal information system are left. The second notion is that of object of discourse, which allows entities to be represented as the composites of geographic information constructs at the higher levels of the hierarchy, explicitly reflecting the connections between the purpose, function, appropriate internal constitution, and ensuing categorization of the entities represented. The framework's main contribution is thus twofold: first, it allows the notions of user purpose and object function to be directly built into geographic representations; second, it proposes a hierarchy of ontological levels that are linked by systematic semantic relations. Further, the framework presents an integrated view of object and field representations. It may also provide a novel perspective on a number of issues of ongoing interest in geographic information science.     

An evaluation of ontology matching techniques on geospatial ontologies

Standardization is one of the pillars of interoperability. In this context, efforts promoted by the Open Geospatial Consortium, such as CityGML (Technical University, Berlin), a standard for exchanging three-dimensional models or urban city objects, are welcomed. However, information from other domains of interest (e.g. energy efficiency or building information modeling) is needed for tasks such as land planning, large-scale flooding analysis, or demand/supply energy simulations. CityGML allows extension in order to integrate information from other domains, but the development process is expensive because there is no way to perform it automatically. The discovery of correspondences between CityGML concepts and other domains concepts poses a significant challenge.

Ontology matching is the research field emerged from the Semantic Web to address automatic ontology integration. Using the ontology underlying CityGML and the ontologies which model other domains of interest, ontology matching would be able to find the correspondences that would permit the integration in a more automatic manner than it is done now.

In this paper, we evaluate if ontology matching techniques allow performing an automatic integration of geospatial information modeled from different viewpoints. In order to achieve this, an evaluation methodology was designed, and it was applied to the discovery of relationships between CityGML and ontologies coming from the building information modeling and Geospatial Semantic Web domains. The methodology and the results of the evaluation are presented. The best results have been achieved using string-based techniques, while matching systems give the worst precision and recall. Only in a few cases the values are over 50%, which shows the limitations when these techniques are applied to ontologies with a partial overlap.     

本体在不动产登记中的应用研究--以榆中县为例

不动产登记项目是我国各地开展的工作,本文从整个工作流程出发,利用本体建立了不动产登记知识模型,探讨了工作技术路线中的知识概念及关系等,并分析了模型的建立价值,为后期我国后续的一系列项目提供参考。     

基于地理语义的空间关系查询和推理

地理空间中的地物,根据其本体类型具有不同的地理语义特征。受到地理语义的影响,人们在描述几何特征和关系相似的物体之间的空间关系时,所用的词汇是不同的。目前,人们在空间关系的自然语言查询方面的研究主要集中在空间关系描述、空间关系自然语言形式化表达、空间关系自然语言查询语句的转换,以及空间关系自然语言查询的查询接口等方面,没有考虑到地理本体的语义差异,这会使得空间关系的自然语言查询不能符合人类语言和认知的习惯。本文依据一些学者在空间关系的自然语言描述的形式化(主要是线和线、线和面等形状的空间地物之间的关系)研究的基础上,针对不同地理本体类型的空间地物和空间关系自然语言描述词汇之间对应的语义关系有所不同的特点,总结了自然语言词汇在描述空间关系时的对应规则,提出不同特征类型地物和描述词汇之间的规则库设计方法,并设计部分空间地物的规则实例。最后,结合空间关系判断函数,设计具体查询系统实践举例证明。     

基于本体的基础地理信息分类层次研究

本体源于哲学,近年来在人工智能和计算机科学领域得到广泛应用,主要用于知识的表达、共享及重用.将本体引入地理信息科学领域,对于实现地理信息知识的表达、共享及重用具有重要意义.基于此,本文从本体的含义与结构出发,在分析现有基础地理信息分类基础上,详细阐述了基于本体的地理要素分类方法,结合领域专家所建立的分类体系,提出了基于本体的基础地理信息分类,并实现了基本的基础地理信息分类体系.     

地理数据空间本体构建及其在数据检索中的应用

随着新地理信息时代的来临,地理数据已经呈现出爆炸式增长的趋势。如何在海量的地理数据中准确、及时地找到人们所需要的数据,并把相关联的数据智能地推荐给用户,成为亟待解决的一大难题。针对传统以关键词、主题词等字符串匹配为核心的数据发现方法存在的查不全、查不准的问题,本文通过对地理空间中的概念、属性、关系、规则,以及相应实例的详细表达,初步提出了地理空间本体构建框架,并在此基础上构建了较为完整的地理数据空间本体,以实现地理数据的智能关联,最后在地球系统科学数据共享平台中进行应用实践。结果表明,引入地理数据空间本体后,检索的结果在数据的查全和查准方面显著提高,而且还能智能推荐相关联的数据信息。本文构建的地理数据空间本体对于大数据时代背景下地理数据的精确发现和共享有重要意义。