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矿产预测基础数据库的数据检查
引用本文:左仁广 汪新庆 夏庆霖. 矿产预测基础数据库的数据检查[J]. 地质通报, 2006, 25(4): 528-532.
作者姓名:左仁广 汪新庆 夏庆霖
作者单位:[1]中国地质大学地质过程与矿产资源国家重点实验室,湖北武汉430074 [2]中国地质大学资源学院,湖北武汉430074
基金项目:<全国重要成矿区带资源评价基础数据库管理系统>项目,<矿产资源调查评价综合与社会化服务>项目
摘    要:21世纪的矿产资源预测评价是在GIS平台下,通过建立地质、物探、化探、遥感等信息的空间数据库,并对各数据库进行空间分析和信息转换、提取,最终圈定综合异常的。这项工作的前提是具有高质量的空间数据库。要提高空间数据库的质量,确保入库数据的正确性和完备性是关键,因此数据检查是一个不可回避的难题。矿产预测评价基础空间数据库具有数据量庞大、数据结构复杂、数据类型多样等特点,因此,提出通过元数据技术检查和控制数据的完备性和时效性,通过数据字典技术确保数据的属性精度,借助质量规则控制数据的逻辑一致性和位置精度的数据检查策略,并运用到全国重要成矿区带的基础空间数据库数据检查中.取得了良好的效果。

关 键 词:矿产预测评价 元数据 数据字典 质量规则
文章编号:1671-2552(2006)04-0528-05
收稿时间:2005-03-07
修稿时间:2006-01-13

Data check on the basic mineral resources prediction database
ZUO Ren-guang, WANG Xin-qing, XIA Qing-lin. Data check on the basic mineral resources prediction database[J]. Geological Bulletin of China, 2006, 25(4): 528-532.
Authors:ZUO Ren-guang  WANG Xin-qing  XIA Qing-lin
Affiliation:1. State Key Laboratory of Geological Processes and Mineral Resources, China University of Geoscienees, Wuhan 430074, Hubei, China; 2. School of Earth Resources, China University of Geoscienees, Wuhan 430074, Hubei, China
Abstract:The mineral resources prediction and assessment in the 21st century are conducted with the support of the geography information system (GIS) and by building various spatial information databases such as geological, geophysical, geochemical and remote sensing spatial databases, performing spatial analysis and information conversion and extraction for these databases and finally outlining integrated anomalies. The premise of this work is to build high-quality spatial databases and the key to this is raising the quality of the spatial databases and ensuring the correctness and integrity of the data in the databases. So it is an inevitable problem to check data. The basic mineral resources prediction and evaluation database is characterized by a huge data capacity, complex structure and multiple types of data. The authors suggest that: the metadata check can effectively control the integrity and time limitation of the data, the data dictionary technique can ensure the attribute accuracy; and the quantity rules can control the logic consistency and position accuracies of the data. At last, the data check is a good tactic, which has been proved by checking the basic spatial databases for nationwide important metallogenic provinces and belts.
Keywords:mineral resources prediction and assessment   metadata   data dictionary   quantity rule
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