Environmental modelling often requires a long iterative process of sourcing, reformatting, analyzing, and introducing various types of data into the model. Much of the data to be analyzed are geospatial data igital terrain models (DTM), river basin boundaries, snow cover from satellite imagery, etc. nd so the modelling workflow typically involves the use of multiple desktop GIS and remote sensing software packages, with limited compatibility among them. Recent advances in service-oriented architectures (SOA) are allowing users to migrate from dedicated desktop solutions to on-line, loosely coupled, and standards-based services which accept source data, process them, and pass results as basic parameters to other intermediate services and/or then to the main model, which also may be made available on-line. This contribution presents a service-oriented application that addresses the issues of data accessibility and service interoperability for environmental models. Key model capabilities are implemented as geospatial services, which are combined to form complex services, and may be reused in other similar contexts. This work was carried out under the auspices of the AWARE project funded by the European programme Global Monitoring for Environment and Security (GMES). We show results of the service-oriented application applied to alpine runoff models, including the use of geospatial services facilitating discovery, access, processing and visualization of geospatial data in a distributed manner.

Our ability to inform conservation and management of species is fundamentally limited by the availability of relevant biogeographic data, use of statistically robust predictive models, and presentation of results to decision makers. Despite the ubiquity of presence-only models, where available, survey effort should be included in the modeling process to limit spatial bias. The biogeographic archive therefore should be able to store and serve related spatial information such as lines of survey effort or polygons of the study area, best accomplished through geospatial web services such as the Open Geospatial Consortium (OGC) Web Feature Service (WFS). Ideally data could then be easily fetched by modelers into a scientific workflow, providing a visually intuitive, modular, reusable canvas for linking analytical processes without the need to code. Species distribution model results should be easily accessible to decision makers, such as through a web-based spatial decision support system (SDSS). With these principles in mind, we describe our progress to date serving marine animal biogeographic data from OBIS-SEAMAP ( http://seamap.env.duke.edu), and consuming the data for predictive environmental modeling of cetaceans. Using geospatial web services to automate the scientific workflow process, marine mammal observations from OBIS-SEAMAP are used to sample through date-synchronous remotely sensed satellite data for building multivariate habitat models using a variety of statistical techniques (GLM, GAM, and CART). We developed custom scientific workflows using ESRI Model Builder, ArcGIS geoprocessor, R statistical package, Python scripting language, PostGIS geodatabase, and UMN MapServer. These model outputs are then passed to an SDSS with spatial summary capability. Custom products will be open-source and freely available. In the future, we hope to integrate technologies such as OGC WCS, OPeNDAP, and Kepler. The principles and lessons described here can be broadly applied to serving biogeographic data, species distribution modeling, and decision support within the ecological informatics community.

Great interest currently exists for developing ecosystem models to forecast how ecosystem services may change under alternative land use and climate futures. Ecosystem services are diverse and include supporting services or functions (e.g., primary production, nutrient cycling), provisioning services (e.g., wildlife, groundwater), regulating services (e.g., water purification, floodwater retention), and even cultural services (e.g., ecotourism, cultural heritage). Hence, the knowledge base necessary to quantify ecosystem services is broad and derived from many diverse scientific disciplines. Building the required interdisciplinary models is especially challenging as modelers from different locations and times may develop the disciplinary models needed for ecosystem simulations, and these models must be identified and made accessible to the interdisciplinary simulation. Additional difficulties include inconsistent data structures, formats, and metadata required by geospatial models as well as limitations on computing, storage, and connectivity. Traditional standalone and closed network systems cannot fully support sharing and integrating interdisciplinary geospatial models from variant sources. To address this need, we developed an approach to openly share and access geospatial computational models using distributed Geographic Information System (GIS) techniques and open geospatial standards. We included a means to share computational models compliant with Open Geospatial Consortium (OGC) Web Processing Services (WPS) standard to ensure modelers have an efficient and simplified means to publish new models. To demonstrate our approach, we developed five disciplinary models that can be integrated and shared to simulate a few of the ecosystem services (e.g., water storage, waterfowl breeding) that are provided by wetlands in the Prairie Pothole Region (PPR) of North America.

It is difficult to realize the Web-oriented geo-data sharing, because geoscience features a wide range of more than a dozen specialized areas. This paper studies the principal structure of geo-data sharing network platform taking into consideration of these features.Designed geo-data sharing platform is composed of 5 parts, which includes website portal, data sharing business tier, core service tier, data sources management tier and network foundation. Thirteen function modules are organized in this architecture efficiently.The development of metadata theories and their application techniques provide a solution to mass data sharing in web. In this platform, metadata management and services modules (MMS) serve as the infrastructure. They are designed and built based on RDF/XML models recommended by W3C. The foundation hierarchy includes 3 tiers, i.e., application tier, RDF/XML resource management tier, and data resources tier. RDF/XML, served as a middle tier, plays an important role in MMS. As a typical data of geoscience, geospatial data can be published via this platform. Its prototype is researched and developed by means of 7 selected metadata ports and WebGIS technologies.The running environment of Web-oriented geo-data sharing platform is built up with support of Web server and several application servers. Research and experiment showed that Apache + Tomcat + ArcIMS server can work well in the system structure physical deployment.

为了充分展示全球油气地质综合研究的数据资料，提供数据库对外信息服务的窗口，基于AreGISServer技术、Visualstudio．NET开发平台和ORACLE数据库管理系统，构建了B／s结构的全球油气地质信息共享系统。本系统是WebGIS应用平台，提供了信息发布、地图浏览、图形查询、空间分析、专题制图等功能，以图形、文字、图表等方式展示研究区的基础地理、基础地质、油气地质、资源潜力、投资环境等方面的最新成果，为公众和研究人员提供了高效的信息访问途径，为国家油气资源管理和能源决策提供了可靠的信息支撑，实现了重要信息社会化共享的目标。文章简单介绍了ArcGISServer，重点描述系统框架、数据分类和功能模块，旨在探讨ArcGISServer的网络信息共享系统的设计与实现。

如何高效管理、利用中国东部已有地球科学研究数据是急需解决的问题.在地球化学数据模型研究 基础上,应用关系数据库和WebGIS技术,建立了中国东部地球化学科学数据库（ECGD）.ECGD深度整合WebGIS技术,研究者可利用ECGD基 于Web对地球化学数据进行检索、分析、输出和空间可视化,查询结果可以标注于基于WebGIS的网络地图,生成分类、分级专题图,并对查询结果进行地球 化学图解等专业分析.ECGD是第一个基于Web,集成了数据检索、空间数据可视化和数据分析功能的地球化学科学数据库,为地学工作者提供了一个地球化学 数据管理、共享、获取、交流的协作平台,具有重要的实用价值.

分析了我国油气资源地质调查数据共享及应用服务存在的主要问题,简析了国内外油气大数据研究现状。基于我国油气资源地质调查服务目标和主流大数据建设技术,提出了油气资源地质调查大数据逻辑架构和应用架构,并展望了油气资源调查大数据中心在油气地质调查、盆地协同研究、社会公益服务等方面的应用。

信息化时代不可避免地来临,随着地质数据的数据量的飞速增长,地质数据也正式归类到了大数据中。应势,国土资源部地质信息技术重点实验室建设了地学大数据技术研究实验平台GeoBDA,用以解决地质大数据的存储和管理等问题。

基于大数据、云计算等现代信息技术与理念,结合地质调查工作实际,系统论述了建设地质大数据体系的总体框架和实现的技术途径。提出了地质大数据体系建设的5项任务组成:建设地质数据采集体系,推进地质数据快速规范采集;建设地质大数据汇聚体系,实现地质数据快速有效汇聚;建设地质数据与信息服务产品体系,丰富地质数据与信息社会化服务产品;建设地质数据与信息服务体系,推进地质数据与信息协同服务;建设地质大数据支撑平台("地质云"),提升地质数据与信息服务的能力和水平。论述了5项任务的主要内容及其面临的关键技术问题,并简要提出了建设地质大数据体系对其他相关工作的影响和要求。

信息服务已经成为21世纪各国地质工作的战略重点，基于Internet和信息技术及时有效 地为用户提供综合、客观的地质信息服务已列入了各国地质调查机构的战略计划。完善的信息服务体系是信息服务健康发展的必要条件。本文在明确相关概念的基础 上，分析了现代信息服务的特点，提出了较为完整的地质信息服务体系框架．阐述了体系框架中各组成部分的主要内容和相互关系。

当前世界进入基于大数据进行数 据密集型科学研究的时代,协同操作的数据、信息、系统、空间基础设施对整个地球科学研究和应对巨大社会挑战至关重要。2012年8月在澳大利亚布里斯班召 开的第34届国际地质大会,吸引了世界范围内的行业领军科学家交流讨论了地学信息领域取得的进展、成果和发展趋势。从本届地质大会来看,计算机技术、数据 库技术、网络技术、虚拟技术等现代化的技术深入应用到了地学众多专业领域,地学信息产品服务成为了信息化时代各国为公众提供公益性服务的主流渠道,地学信 息逐步突破孤立的专题、地区、国家的限制,跨专业、跨学科、跨国乃至跨大洲级别的数据共享将逐步达成共识。当前,全球的地学信息科学家都在朝着这同一方向 努力,让地学知识能够快速、便捷、高效的为变化的地球服务。

<p>随着海量分布式地理空间数据的持续增长和地理空间处理服务复杂程度的不断增加,异步地理空间信息服务已经成为当前地理空间信息领域的研究热点。开放地理信息联盟(Open GIS Consortium,OGC)针对地理空间信息服务互操作制定的一系列标准规范大多建立在同步协议之上,适用于较为简单的非实时计算环境,难以满足复杂、动态的异步信息处理需求。本文提出了一种异步网络处理服务实现方法,以网络处理服务(Web processing service,WPS)和网络通知服务(Web notification service,WNS)为核心,扩展了标准的网络处理服务请求,从而支持异步调用。</p>

针对完全虚拟化技术不能快速部署Web集群及自适应动态扩容的问题。本文提出了一种基于Docker容器组建Web集群的设计方案。该方案主要采用了Docker容器引擎打包Web应用环境镜像生成应用容器,并利用Nginx对业务流量进行负载均衡的方法。系统设计完成后,通过Ruby On Rails框架生成的Web应用打印容器IP地址的方式验证集群是否正常工作。实验结果表明,通过Docker容器部署Web集群系统开销小,能有效的满足Web集群的部署和扩容需求。

Docker的核心思想是利用扩展的LXC(Linux Container)方案实现一种轻量级的虚拟化解决方案。Docker主要利用kernel namespace来实现容器的虚拟化隔离性,保证每个虚拟机中服务的运行环境的隔离。Docker的隔离机制降低了内存开销,保证了虚拟化实例密度。本文从Docker的工作原理出发,详细分析了Docker的虚拟化隔离技术和容器隔离方案的实现。