{"title":"NOAA的综合观测和数据管理以及战略组合工具","authors":"M. Yapur, L. E. Miller","doi":"10.1109/OCEANS.2008.5151991","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":113677,"journal":{"name":"OCEANS 2008","volume":"97 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"NOAA's integrated observations and data management and strategic portfolio tools\",\"authors\":\"M. Yapur, L. E. Miller\",\"doi\":\"10.1109/OCEANS.2008.5151991\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":113677,\"journal\":{\"name\":\"OCEANS 2008\",\"volume\":\"97 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"OCEANS 2008\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/OCEANS.2008.5151991\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"OCEANS 2008","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/OCEANS.2008.5151991","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
NOAA's integrated observations and data management and strategic portfolio tools
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.