Agent-as-a-service-based geospatial service aggregation in the cloud: A case study of flood response

An Agent-as-a-Service (AaaS)-based geospatial service aggregation is proposed to build a more efficient, robust and intelligent geospatial service system in the Cloud for flood emergency response. It involves an AaaS infrastructure, encompassing the mechanisms and algorithms for geospatial Web Processing Service (WPS) generation, geoprocessing and aggregation. The method has the following advantages: 1) it allows separately hosted services and data to work together, avoiding transfers of large volumes of spatial data over the network; 2) it enriches geospatial service resources in the distributed environment by utilizing the agent cloning, migration and service regeneration capabilities of the AaaS, solving issues associated with lack of geospatial services to a certain extent; 3) it enables the migration of services to target nodes to finish a task, strengthening decentralization and enhancing the robustness of geospatial service aggregation; and 4) it helps domain experts and authorities solve interdisciplinary emergency issues using various Agent-generated geospatial services.     

Sharing geospatial provenance in a service-oriented environment

One of the earliest investigations of provenance was inspired by applications in GIS in the early 1990’s. Provenance records the processing history of a data product. It provides an information context to help users determine the reliability of data products. Conventional provenance applications in GIS focus on provenance capture, representation, and usage in a stand-alone environment such as a desktop-based GIS software system. They cannot support wide sharing and open access of provenance in a distributed environment. The growth of service-oriented sharing and processing of geospatial data brings some new challenges in provenance-aware applications. One is how to share geospatial provenance in an interoperable way. This paper describes the development of provenance service for geospatial data products using the ebXML Registry Information Model (ebRIM) of a geospatial catalog service, which follows the interface specifications of the OGC Catalogue Services for the Web (CSW). This approach fits well the current service stack of the GIS domain and facilitates the management of geospatial data provenance in an open and distributed environment.     

区块链技术在地学数据共享中的应用可行性分析

地学数据共享是地学研究的重要内容,也是挖掘地学数据、避免地学数据重复采集的重要途径,是现代数据密集型科研范式下地学研究的重要基础,因此,如何打破地学数据“孤岛”、实现不同地学数据便捷获取、保障数据安全、提升和扩展地学数据贡献者权益保护是地学数据共享中急需解决的问题。区块链技术的兴起,为地学数据价值外化途径扩充、提升数据安全和地学数据贡献者权益保护带来了新的可能。在系统梳理地学数据共享现状、存在问题、区块链基本原理、特点、底层架构以及应用现状的基础上,探讨区块链技术在地学数据共享中的应用可行性以及应用场景,阐述区块链技术在地学数据共享中的应用挑战,以期为地学数据共享领域区块链相关研究与应用提供参考。     

Application Feasibility Analysis of Block Chain Technology in Geospatial Data Sharing

Geospatial data sharing as a significant component of geoscience research. It is also an important means to exploit geoscience data and avoid repeated collection of geospatial data. It is an essential foundation for modern data-intensive geoscience research. Therefore, how to break the geospatial data “island” and realize different geoscience data portable access, secure data security, and promote geospatial data author copyright are urgent problems in geospatial data sharing. The rise of blockchain technology has brought new possibilities for the expansion of the value of geospatial data, the enhancement of data security and the improvement of the protection of the rights of stakeholders in geospatial data. Based on the systematic review of the status quo of data sharing, existing problems, basic principles of blockchain, underlying architecture, characteristics and application status, this paper discusses the application feasibility of blockchain technology in geospatial data sharing, and expounds the application challenges of blockchain technology in geospatial data sharing, in order to provide reference for the research and application of blockchain in geospatial data sharing.     

基于Web Services的异构空间信息共享

异构集成技术正日益成为信息资源管理的一个热点技术。以地理信息共享的应用为背景,提出了基于Web Services的异构空间信息共享体系结构。通过引入Web Services技术架构,设计了一个异构空间信息共享系统。该系统可提供各信息源灵活、动态发布自身服务的功能,从而为快速构建异构集成系统提供了性能保证。     

WebGIS中地理空间Metadata管理系统研究与设计

为实现ＷｅｂＧＩＳ中地理空间信息的有效管理和网络共享,结合国际地理空间信息共享的标准规范,对ＷｅｂＧＩＳ中地理空间Ｍｅｔａｄａｔａ的定义、作用、内容、技术实现及其应用进行了详细的研究和设计,提出了与与ＷｅｂＧＩＳ集成的地理空间Ｍｅｔａｄａｔａ管理系统解决方案,并给出了体现具体技术实现的原型系统,为国家空间信息基础设施和数字地球的建设提供了理论基础和技术原型,在当今信息化与数字地球时代,对地理空间信     

Geospatial information infrastructures to address spatial needs in health: Collaboration,challenges and opportunities

Most health-related issues such as public health outbreaks and epidemiological threats are better understood from a spatial–temporal perspective and, clearly demand related geospatial datasets and services so that decision makers may jointly make informed decisions and coordinate response plans. Although current health applications support a kind of geospatial features, these are still disconnected from the wide range of geospatial services and datasets that geospatial information infrastructures may bring into health. In this paper we are questioning the hypothesis whether geospatial information infrastructures, in terms of standards-based geospatial services, technologies, and data models as operational assets already in place, can be exploited by health applications for which the geospatial dimension is of great importance. This may be certainly addressed by defining better collaboration strategies to uncover and promote geospatial assets to the health community. We discuss the value of collaboration, as well as the opportunities that geographic information infrastructures offer to address geospatial challenges in health applications.     

Semantic Web-based geospatial knowledge transformation

Earth and space science research and applications typically involve collecting and analyzing large volumes of geospatial data much of which is derived from other existing data by applying a scientific workflow. Such a step-by-step process can be viewed as a process of geospatial knowledge transformation, which often involves hypotheses, inferences and integrations to derive user-specific data products from the knowledge of domain experts. Our research is focused on reducing the transformation effort by providing component inference and integration tools. The Semantic Web envisions a new standardized information infrastructure to enable interoperable machine-to-machine interactions and automatic or semi-automatic service chaining for deriving knowledge over networks. This paper describes a generic framework and implementation of how the Semantic Web proceeds through the life cycle of geospatial knowledge transformation, from geospatial modeling (knowledge formalization), through model instantiation (service chain) to model execution (data product). Our approach relies on semantic integrations. A number of ontologies used to capture domain knowledge are introduced in this paper as the basis of knowledge bases for describing and reasoning geospatial data and services. Also, a semantically enabled geospatial catalog service is described to enable more effective discovery, automation and integration of geospatial data and services.     

地理信息元数据及系统

作为数字地球重要支撑技术之一的地理信息元数据技术随着信息技术的飞速发展显得越来越重要。该文对现有的典型地理信息元数据内容和标准以及实现系统进行了分析和综合比较,然后对地理信息元数据内容与标准的制订、地理信息元数据系统的建设提出了一点思考,希望能够对相关的研究有所启发。     

基于数据挖掘的Web个性化信息推荐系统

基于数据挖掘的Web个性化信息推荐日益成为一个重要的研究课题。文章设计了一个基于数据挖掘的Web个性化信息推荐系统(WPIRS)。在WPIRS中,提出了推荐策略,在推荐策略中考虑针对不同类型的用户采用不同的推荐算法。根据用户是否有新颖信息的需求,WPIRS采用了两种推荐算法。     

空间信息融合与地理编码数据库的开发

空间信息的本质特征是区域空间上的分布性,可以根据行政区划、自然地理区域、坐标系统、地名、地址或数码(邮政编码、电活号码)来识别它们。该文阐述了地理编码数据库在空间信息融合和共享中的作用,提出利用地理编码技术,通过包含在空间信息中的地址定位要素来关联空间与非空间信息资源。最后,对地理编码数据库的体系结构和实现策略进行了探讨。     

Energy-efficient and high-accuracy secure data aggregation in wireless sensor networks

Due to the inherent characteristics of resource-constrained sensors, communication overhead is always a major concern in wireless sensor networks (WSNs). Data aggregation is an essential technique to reduce the communication overhead and prolong network lifetime. Since data aggregation results are usually used to make critical decisions, the accuracy of final aggregation results is very important. Furthermore, as wireless sensor networks are increasing being deployed in security-critical applications, we should take security into consideration as well. Therefore, for such applications, data aggregation protocols must be highly energy efficient and highly accurate while being able to prevent an adversary from stealing private data held by each sensor node. In this paper, we propose an energy-efficient and high-accuracy (EEHA) scheme for secure data aggregation. The main idea of our scheme is that accurate data aggregation is achieved without releasing private sensor readings and without introducing significant overhead on the battery-limited sensors. We conduct extensive simulations to evaluate the performance of EEHA. Our analysis and simulations show that EEHA is more efficient and accurate than the existing scheme.     

Web Service aggregation with string distance ensembles and active probe selection

The adoption of standards for exchanging information across the Web presents both new opportunities and important challenges for data integration and aggregation. Although Web Services simplify the discovery and access of information sources, the problem of semantic heterogeneity remains: how to find semantic correspondences across the data being integrated.In this paper, we explore these issues in the context of Web Services, and propose OATS, a novel algorithm for schema matching that is specifically suited to Web Service data aggregation. We show how probing Web Services with a small set of related queries results in semantically correlated data instances which greatly simplifies the matching process, and demonstrate that the use of an ensemble of string distance metrics in matching data instances performs better than individual metrics. We also show how the choice of probe queries has a dramatic effect on matching accuracy. Motivated by this observation, we describe and evaluate an machine learning approach to selecting probes to maximise accuracy while minimising cost.     

基于REST面向资源的地理信息服务设计

结合具有表述性状态转移(REST)的Web服务与开放地理空间联盟(OGC)规范,设计一种面向资源的地理信息服务。将OGC规范作为服务接口标准,采用REST技术,以资源形式对外公开,从而实现信息共享和功能互操作。所有资源共享统一界面,在服务器与客户端之间进行状态传输。     

Metadata Community Profiles for the Semantic Web

Metadata is needed to facilitate data sharing among geospatial information communities. Geographic Metadata Standards are available but tend to be general and complex in nature and also are not well suited to overcome semantic heterogeneities across vocabularies of different domains and user communities. Current formalizations of metadata standards are not flexible enough to allow reuse and extension of metadata specifications, in particular for Web based information systems. In order to address this problem we propose a methodology to create community specific metadata profiles for the Semantic Web by reusing metadata specifications and domain vocabularies encoded as resources for the Web. This ensures that these community profiles are semantically compatible so they can be used in Web based information systems. The ISO-19115:2003 geographic metadata standard is the most general standard available and is being used in conjunction with the Web Ontology Language as the expression medium to test the methodology for each one of the possible extensions documented in ISO-19115:2003. It is shown that it is possible to extend and reuse metadata specifications and vocabularies distributed in the Web using the Web Ontology Language, by utilizing the language's flexibility to create restrictions on inherit properties and to make interferences on web distributed resources. Examples from the area of Hydrology are provided to demonstrate the technical details of the approach.     

A logic-based model to support alert correlation in intrusion detection

Managing and supervising security in large networks has become a challenging task, as new threats and flaws are being discovered on a daily basis. This requires an in depth and up-to-date knowledge of the context in which security-related events occur. Several tools have been proposed to support security operators in this task, each of which focuses on some specific aspects of the monitoring. Many alarm fusion and correlation approaches have also been investigated. However, most of these approaches suffer from two major drawbacks. First, they only take advantage of the information found in alerts, which is not sufficient to achieve the goals of alert correlation, that is to say to reduce the overall amount of alerts, while enhancing their semantics. Second, these techniques have been designed on an ad hoc basis and lack a shared data model that would allow them to reason about events in a cooperative way. In this paper, we propose a federative data model for security systems to query and assert knowledge about security incidents and the context in which they occur. This model constitutes a consistent and formal ground to represent information that is required to reason about complementary evidences, in order to confirm or invalidate alerts raised by intrusion detection systems.     

空间信息栅格中的不同数据格式转换研究

空间信息存在数据量大、处理复杂、难以共享等问题。空间信息栅格（SIG）的一个主要任务就是实现一体化、智能化的空间信息获取、存储、组织、分发、融合及互操作,形成空间信息资源共享与集成。通过比较目前主要的几种空间数据格式,在分析了数据转换的主要方法后,提出以MIF文件格式为中间桥梁的思想,通过两两不同的空间数据的相互转换,实现了多种空间数据之间的转换,有效地解决了不同空间数据的共享问题。     

Integrating and customizing heterogeneous e-commerce applications

A broad spectrum of electronic commerce applications is currently available on the Web, providing services in almost any area one can think of. As the number and variety of such applications grow, more business opportunities emerge for providing new services based on the integration and customization of existing applications. (Web shopping malls and support for comparative shopping are just a couple of examples.) Unfortunately, the diversity of applications in each specific domain and the disparity of interfaces, application flows, actor roles in the business transaction, and data formats, renders the integration and manipulation of applications a rather difficult task. In this paper we present the Application Manifold system, aimed at simplifying the intricate task of integration and customization of e-commerce applications. The scope of the work in this paper is limited to web-enabled e-commerce applications. We do not support the integration/customization of proprietary/legacy applications. The wrapping of such applications as web services is complementary to our work. Based on the emerging Web data standard, XML, and application modeling standard, UML, the system offers a novel declarative specification language for describing the integration/customization task, supporting a modular approach where new applications can be added and integrated at will with minimal effort. Then, acting as an application generator, the system generates a full integrated/customized e-commerce application, with the declarativity of the specification allowing for the optimization and verification of the generated application. The integration here deals with the full profile of the given e-commerce applications: the various services offered by the applications, the activities and roles of the different actors participating in the application (e.g., customers, vendors), the application flow, as well as with the data involved in the process. This is in contrast to previous works on Web data integration that focused primarily on querying the data available in the applications, mostly ignoring the additional aspects mentioned above. Received: 30 October 2000 / Accepted 14 March 2001 Published online: 2 August 2001     

Framework for prioritizing geospatial data processing tasks during extreme weather events

In recent years, advanced geospatial technologies have been playing an increasingly important role in supporting critical decision makings in disaster response. One rising challenge to effectively use the growing volume of geospatial data sets is to rapidly process the data and to extract useful information. Unprocessed data are intangible and non-consumable, and often create the so-called “data-rich-but-information-poor” situation. To address this issue, this study proposed a Data Envelopment Analysis (DEA) based information salience framework to prioritize the sequence of the information processing tasks. The proposed model integrates the DEA efficiency score with a linguistic group decision process. For the input variables, computational complexity and intensity are selected to measure the difficulty in information processing. For the outputs, the performance of each processing tasks is evaluated based on the experts’ judgment on how the processing tasks satisfy the needs of decision makers. These needs are characterized by four classic disaster functions. A unique element of our proposed framework is that cone constraints are added to the DEA model based on the experts’ evaluation of the importance of the four disaster functions to model the dynamic information need. The proposed model was validated with a Hurricane Sandy based case study. The results indicate that the proposed framework is capable of prioritizing geospatial data processing tasks in a systematic manner and accelerating information extraction from disaster related geospatial data sets.