PDF HTML阅读 XML下载 导出引用 引用提醒 我国城市可持续发展能力评估指标的元数据分析与管理 DOI: 10.5846/stxb201705080841 作者: 作者单位: 中国科学院生态环境研究中心 城市与区域生态国家重点实验室,中国科学院生态环境研究中心 城市与区域生态国家重点实验室 中国科学院大学,中国科学院生态环境研究中心 城市与区域生态国家重点实验室 中国科学院大学,中国科学院生态环境研究中心 城市与区域生态国家重点实验室 中国科学院大学,中国科学院生态环境研究中心 城市与区域生态国家重点实验室 中国科学院大学 作者简介: 通讯作者: 中图分类号: 基金项目: 国家重点研发计划(2016YFC0503605) Metadata analysis and management for an urban sustainable development capability evaluation index in China Author: Affiliation: State Key Laboratory of Urban and Regional Ecology,Research Center for Eco-Environmental science,Chinese Academy of Sciences,State Key Laboratory of Urban and Regional Ecology,Research Center for Eco-Environmental science,Chinese Academy of Sciences,State Key Laboratory of Urban and Regional Ecology,Research Center for Eco-Environmental science,Chinese Academy of Sciences,State Key Laboratory of Urban and Regional Ecology,Research Center for Eco-Environmental science,Chinese Academy of Sciences,State Key Laboratory of Urban and Regional Ecology,Research Center for Eco-Environmental science,Chinese Academy of Sciences Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:在我国大力推动城市可持续发展,推进国家可持续发展实验区建设的同时,采用何种评估方法和数据开展城市可持续发展能力评估是需要重点解决的问题。近年来兴起的元数据理论与技术在解决评估数据质量控制方面被视为是一种行之有效的方法。针对我国现阶段使用的一些城市可持续发展能力评估指标体系的特点,通过深入剖析每一个指标数据的来源、获取手段、适用方法等特征,提出从软件工程学思路研发城市可持续发展能力评估元数据管理系统的具体方法,帮助可持续发展实验区高效获取和管理评估所需数据信息;以"十二五"科技支撑计划项目"城市可持续发展能力评估及信息管理关键技术研究与示范"中所建立的元数据规范,对其所包含的"数据发布日期"、"数据发布形式"、"空间范围"、"时间范围(起始时间、结束时间)"、"统计频率"、"数据安全限制分级"、"数据志说明"、"在线资源链接地址"和"数据统计单位信息(单位名称、联络人、联系电话、单位地址、邮件地址)"共14项为评估数据的关键元数据项,以此追踪对标的评估数据。并通过量化数据质量评分法针对数据质量在运用元数据追踪法前后的评价结果对比发现,被评估指标的数据质量在获得元数据支持时,其数据可靠性、可比性和可持续性方面的评价分值都获得了十分显著的改善。研究认为采用元数据理论在控制和保障城市可持续发展能力评估数据质量方面具有优势作用,开发有针对性的城市可持续发展能力评估元数据管理系统能够有效提高评估数据的综合评价结果。 Abstract:The scientific assessment of urban sustainable development capability has important guiding significance for the urban green development and smart growth. Although China is promoting urban sustainable development and developing sustainable experimental areas, it is vital to identify scientific methods and obtain data to analyze this development. In recent years, metadata has been regarded as an effective method to improve data quality. This study focused on the characteristics of an urban sustainable development analysis index system which is based on a metadata management system using software engineering by analyzing the data source, collection method, and application method etc. The aim of this study was to effectively and efficiently collect useful data from the sustainable development experimental area. According to the metadata standard which was developed by "research and demonstration on urban sustainable development capacity assessment and information management key technologies" in 12th Five-Year science and technology support program, we used fourteen key evaluation metadata items in this standard as benchmarks, including data release date, data release form, spatial range, time range(start time and end time), statistical frequency, data security limit classification, data description, Online resource link address and information of data statistics institution(institution name, contacts, contact number, address and e-mail address). Comparing the results of data quality evaluation before and after using a metadata tracking method through the quantitative data quality scoring method, we found that the data are more reliable, comparable and constant when using metadata. This research shows several advantages in controlling and protecting urban sustainable development analysis data quality when applying the metadata theory. Further, the development of a specific urban sustainable development analysis metadata management system could improve the comprehensive evaluation result of the data. 参考文献 相似文献 引证文献
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