院报 ›› 2019, Vol. 36 ›› Issue (10): 34-38.DOI: 10.11988/ckyyb.20190877

• 堤防工程信息化管理 • 上一篇    下一篇

堤防工程数据标准化研究

罗登昌1,2, 韩旭1,2, 于起超3, 马丹璇1,2   

  1. 1.长江勘测规划设计研究有限责任公司,武汉 430010;
    2.长江岩土工程总公司(武汉),武汉 430010;
    3.中南设计集团(武汉)工程技术研究院有限公司,武汉 430071
  • 收稿日期:2019-07-23 出版日期:2019-10-01 发布日期:2019-10-21
  • 作者简介:罗登昌(1988-),男,湖北武汉人,工程师,硕士,主要从事水利地质信息化方面的研究工作。E-mail:615567329@qq.com
  • 基金资助:
    国家重点研发计划项目(2017YFC1502601)

4Standardization of Dyke Engineering Data

LUO Deng-chang1,2, HAN Xu1,2, YU Qi-chao3, MA Dan-xuan1,2   

  1. 1.Changjiang Institute of Survey, Planning, Design and Research, Wuhan 430010, China;
    2.ChangjiangGeotechnical Engineering Corporation, Wuhan 430010, China;
    3.Zhongnan Design Group (Wuhan)Engineering Technology Research Institute Co., Ltd., Wuhan 430071, China
  • Received:2019-07-23 Online:2019-10-01 Published:2019-10-21

摘要: 为了实现堤防工程信息化,促使堤防工程数据高效的收集、有序的存储、快速准确的分析与利用,需确定堤防工程数据标准,明确不同类型数据标准化方案。从堤防工程涉及的工程、水文气象、人文经济、地理、地质、物探、险情及监测数据8个方面出发,调查了国内外数据标准化研究现状,并在此基础上提出堤防数据标准化包含的3部分内容:结构化数据标准化、非结构化数据标准化、数据入库与清洗。结果表明:通过数据分类、数据编码及表设计3个步骤的操作,可对结构化数据进行标准化;利用Java Script对象表示法(Java Script Object Notation,JSON)描述文档的关键信息,将带有文档属性的JSON连同文档一起存入数据库,可实现非结构化数据标准化;通过统一接入和动态配置的数据接入和清洗方法,提高了堤防工程数据标准化过程的效率。研究成果可为进一步提高堤防工程数据标准化程度提供参考。

关键词: 堤防工程, 数据标准化, 数据入库与清洗, Java Script对象表示法, 水利信息化

Abstract: The standards of dyke engineering data should be determined and the standardization schemes of different types of data should be defined in an aim to enhance effective data collection, orderly storage, and rapid and accurate analysis and utilization. In this paper, the status quo of data standardization research in China and abroad are investigated in eight aspects, namely, engineering data, hydrometeorological data, humanistic and economic data, geographic data, geological data, geophysical data, danger data, and monitoring data involved in dyke engineering. The standardization of dyke engineering data should include three contents: structured data, unstructured data, data warehousing and cleaning. Structured data can be standardized through data classification, data coding, and table design; unstructured data can be standardized via describing key information of documents by Java Script Object Notation(JSON) storing the documents together with JSON in the database; the efficiency of data standardization can be improved by uniform data warehousing and dynamic cleaning.

Key words: dyke engineering, data standardization, data warehousing and cleaning, JSON, water conservancy informatization

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