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NOAA's integrated observations and data management and strategic portfolio tools

机译:NOAA的综合观察和数据管理和战略组合工具

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摘要

The National Oceanic and Atmospheric Administration is developing tools to support the analysis and acquisition of architectures for integrated observations and data management strategic portfolios. One of these tools is the ldquoCasaNOSA analysis toolrdquo (CASRT), a desktop software tool that retrieves and matches observing requirements and capabilities, and uses a variety of algorithms to measure the degree of fit or performance between systems and requirements at the attribute level. This tool pulls data from the database of NOAA observing and data management requirements and capabilities that NESDIS' Office of Systems Development has compiled over the last five years. NOAA's operational and science-oriented programs have more than 800 mission-critical observing requirements. NOAA operates over 80 different land, sea, and space-based observing systems, and also obtains data from a wide range of public and private sector sources. NOAA's observing requirements and capabilities are defined in terms of key attributes such as geographic coverage, horizontal or vertical resolution, measurement accuracy, and re-visit frequency. The NOAA database of requirements and capabilities resides in an open source, Web-based repository system and is managed through a suite of collaborative tools. Results from these CASRT gap analyses will be used for investment portfolio analysis, decision support, statistical analysis, and enterprise architecture modeling.
机译:国家海洋和大气管理局正在开发工具,以支持综合观察和数据管理战略组合的分析和收购架构。其中一个工具是LDQuocasAnsa分析ToolRDQUO(CASRT),一个桌面软件工具,可检索和匹配观察要求和功能,并使用各种算法来测量属性级别的系统和要求之间的适合度或性能。该工具从Nesa的观察和数据管理要求和能力数据库中拉动数据,即在过去五年中编制了NESDIS的系统开发办公室。 NOAA的运营和科学为导向的计划有超过800个关键任务观测要求。 NOAA经营80多个不同的土地,海洋和基于空间的观察系统,也可以获得来自各种公共和私营部门来源的数据。 NOAA的观察要求和功能是根据关键属性(如地理覆盖,水平或垂直分辨率,测量精度和重新访问频率)定义的。 NOAA的要求和功能数据库驻留在开源,基于Web的存储库系统中,并通过一套协作工具管理。这些Casrt差距分析的结果将用于投资组合分析,决策支持,统计分析和企业架构建模。

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  • 来源
    《OCEANS》|2008年||共6页
  • 会议地点
  • 作者

    Yapur M.; Miller E.;

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  • 原文格式 PDF
  • 正文语种
  • 中图分类 P75-53;
  • 关键词

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