A temporal-contextual analysis of urban dynamics using location-based data

The dynamics of urban activities in Jerusalem were studied by analyzing a large-scale semantically rich movement dataset. The semantic enrichment process was based on coupling movement trajectories sampled by GPS loggers with contextual data derived from trajectory-based digital activity dairies. Although the utility of such procedures in generating trajectory-specific semantic data was noted before, their application stays limited. In this paper, we promote the utilization of these procedures by demonstrating that they are not only feasible but also important for mobility studies. We discuss the characteristics of the semantic enrichment process and the manner by which it was applied within the large-scale analysis of urban dynamics. This application uncovered a time- and context-dependent array of centers in Jerusalem, resulting in a semantically rich characterization of urban dynamics. Such characterization provides otherwise unobtainable insights crucial for urban analysis. Wider implications for movement studies may be derived, as this application demonstrates how diary-based enrichment approaches hold the potential to advance bridging the semantic gap in mobility research.     

A RESTful proxy and data model for linked sensor data

Abstract

The vision of a Digital Earth calls for more dynamic information systems, new sources of information, and stronger capabilities for their integration. Sensor networks have been identified as a major information source for the Digital Earth, while Semantic Web technologies have been proposed to facilitate integration. So far, sensor data are stored and published using the Observations & Measurements standard of the Open Geospatial Consortium (OGC) as data model. With the advent of Volunteered Geographic Information and the Semantic Sensor Web, work on an ontological model gained importance within Sensor Web Enablement (SWE). In contrast to data models, an ontological approach abstracts from implementation details by focusing on modeling the physical world from the perspective of a particular domain. Ontologies restrict the interpretation of vocabularies toward their intended meaning. The ongoing paradigm shift to Linked Sensor Data complements this attempt. Two questions have to be addressed: (1) how to refer to changing and frequently updated data sets using Uniform Resource Identifiers, and (2) how to establish meaningful links between those data sets, that is, observations, sensors, features of interest, and observed properties? In this paper, we present a Linked Data model and a RESTful proxy for OGC's Sensor Observation Service to improve integration and inter-linkage of observation data for the Digital Earth.     

不动产登记数据的建筑分层分户三维建模关键技术

随着实景三维建设的不断推进,城市管理向立体化、精细化和数字化发展,建筑分层分户三维模型能够承载更详细精准的属性信息,并能叠加倾斜三维模型进行场景渲染,可以更好地服务于城市不动产三维管理、数字赋能社会治理等工作。本文以“萧山区数字赋能社会治理”项目建设为背景,探索和实现了基于不动产登记数据的建筑分层分户三维建模关键技术,形成了从全空间多源异构数据归集至城市全域建筑分层分户三维模型建设的一整套生产技术流程,为城市不动产三维管理、数字赋能社会治理等提供了有效的技术支撑和数据基础。     

FME在地理信息系统互操作上的应用研究

介绍了GIS互操作技术,对FME平台体系结构和语义转换技术进行了分析,并概括了FME平台的特性和优势。     

Semantic Web and service computation in GIScience applications: a perspective and prospective

Semantic Web and Web services have been two prominent themes in the computer science and IT mainstream for more than a decade. While both of these themes have been evolving, some geographers and GIScientists have been trying to introduce and adopt such new technologies into GIScience research and development. This paper reviews the state-of-the-art and the main constraints of semantic Web and Web services technologies and their applications in GIScience. Unless some fundamental problems within both semantic Web and Web services can be resolved, such technologies will be difficult to match the needs in the GIScience community. Besides logics, more sciences and theories have to be introduced into this research front in order to break through the long-term bottleneck in semantic Web and service computation in general.     

Computing the semantic similarity of geographic terms using volunteered lexical definitions

Volunteered geographic information (VGI) is generated by heterogenous ‘information communities’ that co-operate to produce reusable units of geographic knowledge. A consensual lexicon is a key factor to enable this open production model. Lexical definitions help demarcate the boundaries of terms, forming a thin semantic ground on which knowledge can travel. In VGI, lexical definitions often appear to be inconsistent, circular, noisy and highly idiosyncratic. Computing the semantic similarity of these ‘volunteered lexical definitions’ has a wide range of applications in GIScience, including information retrieval, data mining and information integration. This article describes a knowledge-based approach to quantify the semantic similarity of lexical definitions. Grounded in the recursive intuition that similar terms are described using similar terms, the approach relies on paraphrase-detection techniques and the lexical database WordNet. The cognitive plausibility of the approach is evaluated in the context of the OpenStreetMap (OSM) Semantic Network, obtaining high correlation with human judgements. Guidelines are provided for the practical usage of the approach.     

形态本体及其在地理空间数据发现中的应用研究

地理空间数据语义异构是实现数据关联、数据智能推荐和精确发现的主要瓶颈。地理空间数据本体被认为是解决地理空间数据语义异构的有效方法。形态特征是地理空间数据(除时空、要素内容外)的重要特征,是地理空间数据本体的重要研究内容。本文首先在系统分析地理空间数据形态特征的基础上,提出地理空间数据形态特征的概念体系。然后,建立地理空间数据形态本体模型,提出形态信息的本体表示方法,并构建地理空间数据形态本体。最后,基于形态本体的本体库,利用Jena本体推理技术,开发地理空间数据语义检索原型系统,并将形态本体应用于国家地球系统科学数据共享平台的元数据检索中。实验结果表明,地理空间数据形态本体可以有效地解决数据形态特征的语义异构,提高数据发现的查全率和查准率。本文的研究方法和成果对解决其他领域数据的语义异构,有重要的参考意义。