Enabling End-to-End Geospatial Data Modeling Workflows via INPort: The Isotope Networks Portal
Enabling End-to-End Geospatial Data Modeling Workflows via INPort: The Isotope Networks Portal
批准号:
0743543
负责人:
Gabriel Bowen
金额:
$83.16万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2008
资助国家:
美国
项目状态:
已结题
起止时间:
2008-08-01 至 2012-07-31
中文摘要
普渡大学获得了一笔拨款,用于开发和部署INPort,这是一个可扩展的基于网络的平台,用于分析和建模有关空间和时间的稳定同位素数据。INPort将通过提供集成的数据查询、数据采集和地理空间建模操作,在数据消费者和数据源之间提供一个透明的接口。它将由与数据和应用管理系统相连接的web-GIS接口组成,该系统将在幕后进行数据识别、获取、处理和模型执行。INPort的主要输出将是空间和时间上明确的环境同位素分布图。INPort软件和产品将为越来越多的研究项目提供服务,这些项目生成或使用时空解析的环境同位素数据来解决生物地球化学、有机生态学和水文学等领域的关键问题,包括这些领域的国家级监测计划。这些项目有望从一系列环境系统中产生大量空间分解的同位素数据,并且将这些数据与现有数据集和辅助空间数据成功和适当地整合将是最大化其科学影响的关键。INPort将促进将这些多样化、异构的数据转化为具有统一、可理解的数据类型的衍生产品,促进广泛的科学家和非科学家的学习和数据访问。
英文摘要
Purdue University is awarded a grant to develop and deploy INPort, an extensible, web-based platform for the analysis and modeling of stable isotope data with respect to space and time. INPort will provide a transparent interface between data consumers and data sources by providing integrated data querying, data acquisition, and geospatial modeling operations. It will consist of web-GIS interface linked to a data and application management system that will conduct data identification, acquisition, and processing and model execution behind the scenes. The primary output of INPort will spatially and temporally explicit maps of environmental isotope distributions. INPort software and products will serve a growing number of research programs that generate or use spatiotemporally-resolved environmental isotope data to address key problems in biogeochemistry, organismal ecology, and hydrology, including national-scale monitoring initiatives in these areas. These programs promise to generate large quantities of spatially resolved isotope data from a range of environmental systems, and successful and appropriate integration of this data with existing data sets and ancillary spatial data will be key to maximizing its scientific impact. INPort will facilitate the transformation of these diverse, heterogeneous data into derived products having a uniform, intelligible data type, facilitating learning and data access by a wide range of scientists and non-scientists.
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会议论文
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