摘要
随着铁路信息技术的快速发展,行业数据总量和增量呈非线性快速增长趋势,我国铁路已进入大数据时代,在取得一系列重大应用的同时,铁路大数据质量问题也逐渐凸显。阐述铁路大数据质量现状,提出面向狭义、广义、应用层面的铁路数据质量评估方法,深化数据质量优化方法,构建适用于我国铁路数据现状的数据质量评估与优化流程。该研究对促进大数据技术在我国铁路领域的进一步应用具有积极意义。
With the rapid development of railway information technology, both the total amount and increment of data in the industry show a non-linear trend of rapid growth. China＇s railway industry has entered the era of big data. As a series of major applications have been implemented, the problem in the quality of railway big data has also gradually becomes prominent. This paper describes the status quo of railway big data quality and puts forward methods for railway data quality evaluation in narrow, broad and application levels, further improves the method of data quality optimization and builds a data quality assessment and optimization process suitable for the status quo of the railway data in China. It is of positive significance to promoting the further application of big data technology in China＇s railway sector.
作者
赵冰
李平
代明睿
ZHAO Bing;LI Ping;DAI Mingrui(Railway Big Data Research and Application Innovation Center, China Academy of Railway Sciences, Beijing 100081, China)
出处
《中国铁路》
2018年第2期63-67,共5页
China Railway
基金
中国铁路总公司科技研究开发计划项目(Z2016-X003)
关键词
铁路
大数据
数据质量
质量评估
railway
big data
data quality
quality evaluation
作者简介
赵冰（1992-），男，博士。E-mail：zhaobing_0412@163．com
