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A grid portal for solving geoscience problems using distributed knowledge discovery services

机译:一个使用分布式知识发现服务解决地球科学问题的网格门户

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This paper describes our research effort to employ Grid technologies to enable the development of geoscience applications by integrating workflow technologies with data mining resources and a portal framework in unique work environment called MOSE. Using MOSE, a user can easily compose and execute geo-workflows for analyzing and managing natural disasters such as landslides, earthquakes, floods, wildfires, etc. MOSE is designed to be applicable both for the implementation of response strategies when emergencies occur and for disaster prevention. It takes advantage of the standardized resource access and workflow support for loosely coupled software components provided by web/grid services technologies. The integration of workflows with data mining services significantly improves data analysis. Geospatial data management and mining are critical areas of modern-day geosciences research. An important challenge for geospatial information mining is the distributed nature of the data. MOSE provides knowledge discovery services based on the WEKA data mining library and novel distributed data mining algorithms for spatial data analysis. A P2P bio-inspired algorithm for distributed spatial clustering as an example of distributed knowledge discovery service for intensive data analysis is presented. A real case application for the analysis of landslide hazard areas in the Campania Region near the Samo area shows the advantages of using the portal.
机译:本文介绍了我们的研究工作,即通过将工作流技术与数据挖掘资源和门户框架集成到称为MOSE的独特工作环境中,利用网格技术来实现地球科学应用程序的开发。使用MOSE,用户可以轻松地编写和执行地理工作流程,以分析和管理自然灾害,例如滑坡,地震,洪水,野火等。MOSE旨在既适用于紧急情况下的响应策略实施,也适用于灾害预防。它利用标准的资源访问和工作流支持来支持由Web /网格服务技术提供的松散耦合的软件组件。工作流与数据挖掘服务的集成大大改善了数据分析。地理空间数据管理和挖掘是现代地球科学研究的关键领域。地理空间信息挖掘的一个重要挑战是数据的分布式性质。 MOSE提供基于WEKA数据挖掘库和新颖的分布式数据挖掘算法的知识发现服务,用于空间数据分析。提出了一种用于分布式空间聚类的P2P生物启发算法,作为用于密集数据分析的分布式知识发现服务的示例。在萨摩地区附近的坎帕尼亚地区,一个实际案例分析滑坡灾害区域显示了使用该门户的优势。

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