Improving geospatial query performance of an interoperable geographic situation‐awareness system for disaster response

Disaster response operations require fast and coordinated actions based on real‐time disaster situation information. Although crowdsourced geospatial data applications have been demonstrated to be valuable tools for gathering real‐time disaster situation information, they only provide limited utility for disaster response coordination because of the lack of semantic compatibility and interoperability. To help overcome the semantic incompatibility and heterogeneity problems, we use Geospatial Semantic Web (GSW) technologies. We then combine GSW technologies with Web Feature Service requests to access multiple servers. However, a GSW‐based geographic information system often has poor performance due to the complex geometric computations required. The objective of this research is to explore how to use optimization techniques to improve the performance of an interoperable geographic situation‐awareness system (IGSAS) based on GSW technologies for disaster response. We conducted experiments to evaluate various client‐side optimization techniques for improving the performance of an IGSAS prototype for flood disaster response in New Haven, Connecticut. Our experimental results show that the developed prototype can greatly reduce the runtime costs of geospatial semantic queries through on‐the‐fly spatial indexing, tile‐based rendering, efficient algorithms for spatial join, and caching, especially for those spatial‐join geospatial queries that involve a large number of spatial features and heavy geometric computation.     

空间服务语义模式的地理信息服务发现

如何从大规模地理信息服务集合中快速且准确地发现目标服务是地理信息服务应用中的一个关键问题。当前基于关键字的服务发现方式缺乏语义支持,搜索效率低。本文在WSMO/WSML框架下,提出了一种基于空间服务语义模式的服务发现方法,将地理信息从语法模式转换为语义模式,明确表达空间数据中隐含的知识,有效克服数据源之间的语义异构。该方法能够显著提高地理信息服务发现的查全率和查准率。     

A parallel approach for improving Geo-SPARQL query performance

Geospatial Semantic Web promises better retrieval geospatial information for Digital Earth systems by explicitly representing the semantics of data through ontologies. It also promotes sharing and reuse of geospatial data by encoding it in Semantic Web languages, such as RDF, to form geospatial knowledge base. For many applications, rapid retrieval of spatial data from the knowledge base is critical. However, spatial data retrieval using the standard Semantic Web query language – Geo-SPARQL – can be very inefficient because the data in the knowledge base are no longer indexed to support efficient spatial queries. While recent research has been devoted to improving query performance on general knowledge base, it is still challenging to support efficient query of the spatial data with complex topological relationships. This research introduces a query strategy to improve the query performance of geospatial knowledge base by creating spatial indexing on-the-fly to prune the search space for spatial queries and by parallelizing the spatial join computations within the queries. We focus on improving the performance of Geo-SPARQL queries on knowledge bases encoded in RDF. Our initial experiments show that the proposed strategy can greatly reduce the runtime costs of Geo-SPARQL query through on-the-fly spatial indexing and parallel execution.     

Approaches to Semantic Similarity Measurement for Geo-Spatial Data: A Survey

Semantic similarity is central for the functioning of semantically enabled processing of geospatial data. It is used to measure the degree of potential semantic interoperability between data or different geographic information systems (GIS). Similarity is essential for dealing with vague data queries, vague concepts or natural language and is the basis for semantic information retrieval and integration. The choice of similarity measurement influences strongly the conceptual design and the functionality of a GIS. The goal of this article is to provide a survey presentation on theories of semantic similarity measurement and review how these approaches – originally developed as psychological models to explain human similarity judgment – can be used in geographic information science. According to their knowledge representation and notion of similarity we classify existing similarity measures in geometric, feature, network, alignment and transformational models. The article reviews each of these models and outlines its notion of similarity and metric properties. Afterwards, we evaluate the semantic similarity models with respect to the requirements for semantic similarity measurement between geospatial data. The article concludes by comparing the similarity measures and giving general advice how to choose an appropriate semantic similarity measure. Advantages and disadvantages point to their suitability for different tasks.     

Automatic search of geospatial features for disaster and emergency management

Although the fast development of OGC (Open Geospatial Consortium) WFS (Web Feature Service) technologies has undoubtedly improved the sharing and synchronization of feature-level geospatial information across diverse resources, literature shows that there are still apparent limitations in the current implementation of OGC WFSs. Currently, the implementation of OGC WFSs only emphasizes syntactic data interoperability via standard interfaces and cannot resolve semantic heterogeneity problems in geospatial data sharing. To help emergency responders and disaster managers find new ways of efficiently searching for needed geospatial information at the feature level, this paper aims to propose a framework for automatic search of geospatial features using Geospatial Semantic Web technologies and natural language interfaces. We focus on two major tasks: (1) intelligent geospatial feature retrieval using Geospatial Semantic Web technologies; (2) a natural language interface to a geospatial knowledge base and web feature services over the Semantic Web. Based on the proposed framework we implemented a prototype. Results show that it is practical to directly discover desirable geospatial features from multiple semantically heterogeneous sources using Geospatial Semantic Web technologies and natural language interfaces.     

The Space Package: Tight Integration between Space and Semantics

Interpretation of spatial features often requires combined reasoning over geometry and semantics. We introduce the Space package, an open source SWI‐Prolog extension that provides spatial indexing capabilities. Together with the existing semantic web reasoning capabilities of SWI‐Prolog, this allows efficient integration of spatial and semantic queries and provides an infrastructure for declarative programming with space and semantics. There are few systems that provide indexing and reasoning facilities for both spatial and semantic data. A common solution is to combine separate semantic reasoning and geospatial services. Such loose coupling has the disadvantage that each service cannot make use of the statistics of the other. This makes optimization of such a service‐oriented architecture hard. The SWI‐Prolog Space and Semantic web packages provide a native Prolog interface to both spatial and semantic indexing and reasoning, which makes it easy to write combined query optimizers. Another advantage of the Space package is that it allows declarative logic programming, which means in practice that you say what you want to compute instead of how to compute it. The actual indexing machinery is encapsulated inside Prolog predicates. In this article we describe the interface of the Space package, compare its functionality to alternative software libraries, and show how to work with it using three example applications. These example illustrations include reasoning over movement patterns, dynamically loading geospatial linked data off the semantic web, and setting up a simple KML server.     

Building the World Wide Hypermap (WWH) with a RESTful architecture

The hypermap concept was introduced in 1992 as a way to hyperlink geospatial features to text, multimedia or other geospatial features. Since then, the concept has been used in several applications, although it has been found to have some limitations. On the other hand, Spatial Data Infrastructures (SDIs) adopt diverse and heterogeneous service oriented architectures (SOAs). They are developed by different standard bodies and are generally disconnected from mass market web solutions. This work expands the hypermap concept to overcome its limitations and harmonise it with geospatial resource oriented architecture (ROA), connecting it to the semantic web and generalising it to the World Wide Hypermap (WWH) as a tool for building a single ‘Digital Earth’. Global identifiers, dynamic links, link purposes and resource management capabilities are introduced as a solution that orchestrates data, metadata and data access services in a homogeneous way. This is achieved by providing a set of rules using the current Internet paradigm formalised in the REpresentational State Transfer (REST) architecture and combining it with existing Open Geospatial Consortium (OGC) and International Organization for Standardization (ISO) standards. A reference implementation is also presented and the strategies needed to implement the WWH, which mainly consist in a set of additions to current Geographic Information System (GIS) products and a RESTful server that mediates between the Internet and the local GIS applications.     

Putting meaning into NETMAR – the open service network for marine environmental data

The open service network for marine environmental data (NETMAR) project uses semantic web technologies in its pilot system which aims to allow users to search, download and integrate satellite, in situ and model data from open ocean and coastal areas. The semantic web is an extension of the fundamental ideas of the World Wide Web, building a web of data through annotation of metadata and data with hyperlinked resources. Within the framework of the NETMAR project, an interconnected semantic web resource was developed to aid in data and web service discovery and to validate Open Geospatial Consortium Web Processing Service orchestration. A second semantic resource was developed to support interoperability of coastal web atlases across jurisdictional boundaries. This paper outlines the approach taken to producing the resource registry used within the NETMAR project and demonstrates the use of these semantic resources to support user interactions with systems. Such interconnected semantic resources allow the increased ability to share and disseminate data through the facilitation of interoperability between data providers. The formal representation of geospatial knowledge to advance geospatial interoperability is a growing research area. Tools and methods such as those outlined in this paper have the potential to support these efforts.     

A capability matching and ontology reasoning method for high precision OGC web service discovery

Finding the right spatially aware web service in a heterogeneous distributed environment using criteria such as service type, version, time, space, and scale has become a challenge in the integration of geospatial information services. A new method for retrieving Open Geospatial Consortium (OGC) Web Service (OWS) that deals with this challenge using page crawling, link detection, service capability matching, and ontology reasoning, is described in this paper. Its major components are distributed OWS, the OWS search engine, the OWS ontology generator, the ontology-based OWS catalog service, and the ontology-based multi-protocol OWS client. Experimental results show that the execution time of this proposed method equals only 0.26 of that of Nutch's method. In addition, the precision is much higher. Moreover, this proposed method can carry out complex OWS reasoning-based queries. It is being used successfully for the Antarctica multi-protocol OWS portal of the Geo-Information Web Service Portal of the Polar.     

基于云计算的三维地理空间信息服务的表达

当前云计算的发展已能支持高性能的地理空间服务,比如在数字城市和电子商务等行业。Apache基金支持下的开源软件框架Hadoop,可以用来构建一个云环境的集群用来存储和处理高性能的地理空间数据。开放地理空间联盟(OGC)的Web三维服务(W3DS)就是这样一个很好的三维的地理空间数据服务标准。在标准的云计算环境下将是一个更好的应用示范。基于此,本文研究了OGC的W3DS服务在云计算环境下的实验结果。实验采用Apache的Hadoop框架作为三维地理空间信息服务实验展示的基础。实验结果对展示高性能的三维地理空间信息提供了有价值的参考。     

Determining Semantic Similarity of Behaviour Using Natural Semantic Metalanguage to Match User Objectives to Available Web Services

Natural Semantic Metalanguage specifies a set of semantic primitives identified by linguists since the 1970s as being present in all analysed languages and not capable of further reduction. In this article, the 63 semantic primitives are used to define the semantics of user objectives and web services in the form of semantic explications, which are then compared to determine whether the web services are likely to be helpful in meeting the user objective. The comparison of the user objectives and web services is a two stage process. Firstly, the content is compared by classifying the semantic primitives from the candidate web service and user objective on the basis of whether the primitives are common or similar. On the basis of these classifications, the percentage match and semantic relationship (subset, superset, overlaps, disjoint, identical) are determined. Secondly, the order of the semantic primitives is compared and the edit distance determined as a measure of semantic similarity. The method is tested using two examples: a comparison of spatial relations and a comparison of a user objective and three geospatial web services. The results show that the method is able to determine which concepts are broadly semantically similar and which are not.     

Requirements for Next Generation Spatial Data Infrastructures-Standardized Web Based Geoprocessing and Web Service Orchestration

Spatial Data Infrastructures (SDI) have been widely accepted to exchange geospatial data among organizations. Today SDIs main focus lies on the provision of geospatial data in the form of distributed spatial web services, the retrieval through catalogues, and visualization in the form of Web Map Services (WMS). The hypothesis presented in this paper takes SDI's one step further by providing a method to process geodata in an Open Geospatial Consortium (OGC) compliant way into information. Two case studies present the potential of standardized geoprocessing services. In addition, this paper addresses the problem of service chaining by providing a system architecture to implement complex geoprocessing models and workflows based on web services using Web Service Orchestration (WSO). The proposed methods utilize spatial standards provided by OGC, the International Organization for Standardization (ISO) and ‘mainstream IT’ standards provided by the World Wide Web Consortium (W3C) and the Organization for the Advancement of Structured Information Standards (OASIS) to establish a generic web service architecture for providing common geoprocessing capabilities (e.g. spatial algorithms, map algebra, etc.) for usage in SDIs.     

Towards knowledge-based geovisualisation using Semantic Web technologies: a knowledge representation approach coupling ontologies and rules

ABSTRACT

Geovisualisation is a knowledge-intensive art in which both providers and users need to possess a wide range of knowledge. Current syntactic approaches to presenting visualisation information lack semantics on the one hand, and on the other hand are too bespoke. Such limitations impede the transfer, interpretation, and reuse of the geovisualisation knowledge. In this paper, we propose a knowledge-based approach to formally represent geovisualisation knowledge in a semantically-enriched and machine-readable manner using Semantic Web technologies. Specifically, we represent knowledge regarding cartographic scale, data portrayal and geometry source, which are three key aspects of geovisualisation in the contemporary web mapping era, coupling ontologies and semantic rules. The knowledge base enables inference for deriving the corresponding geometries and portrayals for visualisation under different conditions. A prototype system is developed in which geospatial linked data are used as underlying data, and some geovisualisation knowledge is formalised into a knowledge base to visualise the data and provide rich semantics to users. The proposed approach can partially form the foundation for the vision of web of knowledge for geovisualisation.     

基于语义Web的地理服务发现框架

在传统Web服务发现架构中,仅凭接口参数的结构化相似度计算匹配方法远远不能满足复杂地理服务的发现需求。本文结合语义Web知识,设计了地理服务发现框架,框架支持地理服务语义化描述、带有语义信息的服务注册、基于语义推理的服务发现。其中,服务匹配算法是服务发现的关键,本文基于传统的四级匹配算法,提出采用分级匹配思想,并在I/O匹配中利用本体分类树,将本体相似度求解转换为分类树中节点距离求解的方法的地理服务发现匹配算法。实例证明,改进的算法不但能区分匹配等级,而且能区分同一匹配等级之间的相似度大小,能较好地满足地理服务的发现的需求。     

基于GIS服务链的遥感影像分布式融合处理

提出了基于Web服务技术、OGC规范和工作流技术,以实现与平台无关的、具备流程编排能力的地理空间处理服务链框架,用于支持复杂的在线空间处理任务.在该框架基础上实现了一个在线遥感影像融合处理示例.该示例展示了利用OGC WCS、WPS,WSDL,UDDI和BPEL4WS等成熟的标准规范来构建GIS服务链,使得客户应用程序...     

基于多协议的地理信息服务集成

设计了多协议地理信息服务集成框架,探讨解决了其中的关键问题,实现了从不同地理信息服务获取的影像数据、矢量数据和DEM数据的无缝集成。     

A geospatial search engine for discovering multi-format geospatial data across the web

The volume of publically available geospatial data on the web is rapidly increasing due to advances in server-based technologies and the ease at which data can now be created. However, challenges remain with connecting individuals searching for geospatial data with servers and websites where such data exist. The objective of this paper is to present a publically available Geospatial Search Engine (GSE) that utilizes a web crawler built on top of the Google search engine in order to search the web for geospatial data. The crawler seeding mechanism combines search terms entered by users with predefined keywords that identify geospatial data services. A procedure runs daily to update map server layers and metadata, and to eliminate servers that go offline. The GSE supports Web Map Services, ArcGIS services, and websites that have geospatial data for download. We applied the GSE to search for all available geospatial services under these formats and provide search results including the spatial distribution of all obtained services. While enhancements to our GSE and to web crawler technology in general lie ahead, our work represents an important step toward realizing the potential of a publically accessible tool for discovering the global availability of geospatial data.     

Ontology‐supported Querying of Geographical Databases

Querying geographical information systems has been recognized as a difficult task for non‐expert users. Furthermore, user queries are often characterized by semantic aspects not directly managed by traditional spatial databases or GIS. Examples of such semantic geospatial queries are the use of implicit spatial relations between objects, or the reference of domain concepts not explicitly represented in data. To handle such queries, we envisage a system that translates natural language queries into spatial SQL statements on a database, thus improving standard GIS with new semantic capabilities. Within this general objective, the contribution of this article is to introduce a methodology to handle semantic geospatial queries issued over a spatial database. This approach captures semantics from an ontology built upon the spatial database and enriched by domain concepts and properties specifically defined to represent the localization of objects. Some examples of the use of the methodology in the urban domain are presented.