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机构地区:[1]中国科学院地理科学与资源研究所 资源与环境信息系统国家重点实验室,北京100101 [2]中国科学院研究生院,北京100049
出 处:《科研信息化技术与应用》2012年第2期35-43,共9页E-science Technology & Application
基 金:科技基础性工作重点项目(2007 FY 110300;2011 FY 110400);中国科学院信息化专项项目(INFO-115-C01)
摘 要:综合科学考察是获取区域资源环境本底数据的重要手段。集成综合科学考察所获取的多学科、多尺度、多来源、多时相的科学数据时,如何进行质量控制是一个难题。本研究结合东北亚区域(覆盖中国北方、蒙古、俄罗斯远东和西伯利亚地区)的综合科学考察实践,以数据标准化和信息化为核心,提出和建立一系列的数据集成质量控制技术方法。主要内容包括:(1)建立数据获取和管理标准规范体系,研制数据质量检查及元数据标准等技术规范;(2)基于信息化手段,研发元数据采集和数据规范化入库软件工具;(3)统一构建数据目录,实现综合科学考察数据的集成管理。通过以上研究和实践,既保证了集成这些来之不易的野外科学考察数据资源的质量,又为相关领域科学考察的数据集成质量控制提供了标准化和信息化技术方法借鉴。Integrated scientific expedition is one of important approaches to acquire regional resources and environment background data. Scientific expedition data has many characteristics, such as multi-discipline, multi-scale, multi-sources, multi-temporal and so on. How to control the data quality in the processing of scientific expedition data integration is a key problem. The paper proposed a serial of data quality control approaches for North East Asia area scientific expedition, by utilizing standardization and information technologies. The expedition area covers northern China, Mongolia, and east Siberia area of Russia. Firstly, the scientific expedition data collection and management standards and specification system is designed. Data quality review specification and core metadata standard are proposed in the system. Secondly, a metadata collection and a standardization data integration software tool is designed and developed. Thirdly, all the scientific expedition data from 2008 to 2012 in North East Asia area are integrated in a data warehouse under uniform data classification system, which includes 4 main classes, and 28 sub classes. The research will not only ensure the scientific expedition data integration quality in North East Asia area, but also provide effective data quality control methods for related scientific expedition fields.
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