Matching INSPIRE Quality of Service Requirements with Hybrid Clouds

A lot of effort has been invested in Spatial Data Infrastructures (SDIs) during the last decade regarding interoperable standards for services and data. But still the scalability and performance of SDI services is reported to be crucial especially if they are accessed concurrently by a high number of users. Furthermore, laws and provisions such as the INSPIRE directive specify challenging requirements regarding the performance, availability and scalability of SDI services. This article presents a Hybrid Cloud architecture for matching INSPIRE‐related Quality of Service (QoS) requirements, without investing in rarely used hardware in advance, by occupying external third‐party resources on a pay‐as‐you‐go basis. The presented Hybrid Cloud is a composition of a local IT‐infrastructure (Private Cloud) and the computational resources of third‐party vendors (Public Cloud). The local infrastructure is laid out to handle the average main load of a service and in lasting peak times additional resources of external providers are allocated and integrated on demand into the local infrastructure to provide sufficient service quality automatically. A proof‐of‐concept implementation of the proposed Hybrid Cloud approach is evaluated and benchmarked with respect to INSPIRE‐related QoS requirements.     

Evaluation and Monitoring of Service Quality: Discussing Ways to Meet INSPIRE Requirements

Service oriented architectures (SOA) are widely used nowadays. As the name implies such architectures rely on services. Germany developed a marine‐specific service oriented data infrastructure (MDI‐DE – Marine Dateninfrastruktur Deutschland) from 2010 to 2013. The services in MDI‐DE can contribute to fulfilling reporting commitments for various European and national legislation. The services of MDI‐DE (just like other services affected, for instance, by INSPIRE) have to meet specific requirements regarding performance, availability and conformity (quality of service, QoS). Although SOA is an important field in scientific research there are very few publications and studies available on QoS, especially regarding INSPIRE requirements. The services of MDI‐DE were analyzed using various existing tools. Their usefulness to reflect where either the aspect's performance, availability or conformity needs improvement was partly verified. Due to varying results and the neglect of some services for various reasons it can be stated that the more tools are used, the more conclusive the outcome. Furthermore, service quality was not coherent when measured with different tools. This means that measuring QoS in terms of INSPIRE will be very difficult to do in the future and there is the danger that people will choose the tools with which their services perform best.     

Feature Definitions in Feature Catalogues

Abstract

First, an overview of the main terms used in the paper is presented, such as feature catalogue, object, feature, and so on. Then INSPIRE (INfrastructure for SPatial InfoRmation in Europe) Directive, STOKIS (Slu?beni topografski i kartografski informacijski sustav RH), ATKIS (Amtliches topographisch-kartographisches Informationssystem) and FACC (Feature and Attribute Coding Catalogue) are explained. The main section of the paper refers to the problem of defining features in feature catalogues. Adequate solutions to this problem are offered on the basis of conducted research. An overall acceptable model for feature definition is offered. The importance of the proposed model for defining features is explained on the feature ‘avenue of trees’. The research results are applicable in countries attempting to create their first feature catalogues with the aim of developing a topographic information system, or in those wanting to produce a new edition of their existing feature catalogue. Since the suggested model is included, it can be used for the future development of the INSPIRE feature.     

Intelligent services for discovery of complex geospatial features from remote sensing imagery

Remote sensing imagery has been commonly used by intelligence analysts to discover geospatial features, including complex ones. The overwhelming volume of routine image acquisition requires automated methods or systems for feature discovery instead of manual image interpretation. The methods of extraction of elementary ground features such as buildings and roads from remote sensing imagery have been studied extensively. The discovery of complex geospatial features, however, is still rather understudied. A complex feature, such as a Weapon of Mass Destruction (WMD) proliferation facility, is spatially composed of elementary features (e.g., buildings for hosting fuel concentration machines, cooling towers, transportation roads, and fences). Such spatial semantics, together with thematic semantics of feature types, can be used to discover complex geospatial features. This paper proposes a workflow-based approach for discovery of complex geospatial features that uses geospatial semantics and services. The elementary features extracted from imagery are archived in distributed Web Feature Services (WFSs) and discoverable from a catalogue service. Using spatial semantics among elementary features and thematic semantics among feature types, workflow-based service chains can be constructed to locate semantically-related complex features in imagery. The workflows are reusable and can provide on-demand discovery of complex features in a distributed environment.     

Harmonisation requirements and capabilities towards a European spatial data infrastructure (ESDI): the HUMBOLDT protected areas scenario

Abstract

The HUMBOLDT project has the aim of implementing a Framework for harmonisation of data and services in the geoinformation domain, under the Infrastructure for Spatial Information in Europe (INSPIRE) Directive and in the context of the Global Monitoring for Environment and Security (GMES) Initiative. The two-pronged approach of HUMBOLDT comprises a technical side of software framework development and an application side of scenario testing and validation. Among the HUMBOLDT Application Scenarios designed to demonstrate the capabilities of the Framework there is the one covering Protected Areas themes and use cases. It aims to transform geoinformation, managed by park authorities, into a seamless flow that combines multiple information sources from different governance levels (European, national, regional), and exploits this newly combined information for the purposes of planning, management and tourism promotion. The Scenario constitutes a step further towards the integration of monitoring systems envisaged in the view of Digital Earth. Protected Areas Scenario creates an examples of the use of the HUMBOLDT tools in Desktop and Web GIS environment, together with setting up a server environment exploiting HUMBOLDT harmonisation framework as taking into account user requirements and needs and providing benefits for making the road to ESDI establishment easier.     

地理空间信息服务质量评价的概念与方法

本文在综合商业服务质量评价模型与软件质量评价模型的基础上,对地理空间信息服务质量评价的一般过程与方法进行了分析。首先,对地理空间信息服务的质量评价的基本概念与内涵进行了分析;其次,对服务执行质量评价与服务实体质量评价进行了比较;然后,对原子地理空间信息服务质量评价中的度量方法进行了探讨;最后,提出了5个地理空间信息服务的基本组合模型,并对几个关键质量要素的组合算法进行了分析。     

空间信息服务质量评价

随着信息技术在测绘领域的广泛应用和信息化测绘的广泛实践,测绘不再只是提供地图或地图数据,而是提供包括空间数据在内的空间信息服务.首先提出空间信息服务质量是由空间数据质量、信息可达度以及信息交互质量三个质量指标决定的,其中每一个质量指标又包括若干下级质量指标,以此构成一个地理信息服务质量的指标树.在构建空间信息服务质量指...     

基于Agent的空间信息服务组合研究

首先简要介绍了空间信息服务的研究现状,然后分析了空间信息服务组合的3种主要形式。总结了Agent技术实现聚合式空间信息服务组合的优势,指出Agent的自主性、交互性等特性是解决开放环境下空间信息服务的发现、选择以及组合问题的最佳途径之一。详细设计了基于Agent的空间信息服务模型,阐述了服务发现、服务组合、用户交互3部分的结构和功能,引入词频向量的方法解决服务发现和匹配问题,最后构造了一个基于Agent的空间信息服务组合的用例。     

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。     

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。     

一种基于软件网络的重要服务发现方法

与已有的侧重于服务内容的方法不同,本文根据服务组合的历史记录,提出了一种依据服务间依赖关系发现重要服务,以及其他可与之进行组合的服务的方法。在对ProgrammableWeb真实数据的实验结果表明,发现的重要Web API在Mashup中出现率达95%,且在分析给定Web API集的可组合性方面,成功率高达98%。     

基于上下文感知的地理信息服务发现与匹配技术研究

如何在网络上寻找到最适合的地理信息服务,即服务的发现与匹配技术的需求变得越来越迫切。本文结合普适思想提出了基于上下文感知的地理信息服务多级发现与匹配框架．包括基本描述、服务功能、约束条件、空间上下文4级匹配过程,并详细分析了空间上下文的建模与推理、地理信息相似性等关键技术,最终通过一个原型系统验证了该框架及关键技术的可行性。     

多级应急响应地理信息服务平台的应用技术

提出一个支持多级分布、服务级联的信息服务综合架构和集成机制,并应用于应急响应地理信息服务平台的设计,探讨了应急响应地理数据虚拟化、分布式异构环境下应急响应地理信息数据/功能服务技术、多级应急地理信息目录服务构建技术等,为构建有效的多级应急响应地理信息服务平台提供技术支撑。     

基于OWL-S的地理信息服务描述和发现

本文建立了地理数据类型本体和地理服务类型本体,提出了基于OWL-S地理理信息服务发现方法。其核心思想是用OWL-S进行服务描述和发布,通过对服务语义描述中的输入、输出、服务分类进行分级匹配实现服务的自动发现。