工业时序大数据质量管理

丁小欧; 王宏志; 于晟健

doi:10.11959/j.issn.2096-0271.2019047

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工业时序大数据质量管理

专题：大数据整理 | 更新时间：2024-06-03

- 工业时序大数据质量管理
- Data quality management of industrial temporal big data
- 大数据 2019年5卷第6期页码：2019047-1
- 作者机构：
- 作者简介：
  
  [ "丁小欧（1993- ），女，哈尔滨工业大学海量数据计算研究中心博士生，主要研究方向为时序数据挖掘与分析、数据清洗、数据质量管理等" ]
  [ "王宏志（1978- ），男，博士，哈尔滨工业大学海量数据计算研究中心教授、博士生导师，主要研究方向为数据库管理系统、大数据管理与分析、数据治理等" ]
  [ "于晟健（1997- ），男，哈尔滨工业大学海量数据计算研究中心硕士生，主要研究方向为时序数据分析、异常检测、时序数据清洗等" ]
- 基金信息：
  
  国家重点研发计划基金资助项目;The National Key Research and Development Program of China(2018YFB1004700);国家自然科学基金资助项目;The National Natural Science Foundation of China(U1509216);国家自然科学基金资助项目;The National Natural Science Foundation of China(U1866602);国家自然科学基金资助项目;The National Natural Science Foundation of China(61602129)
- DOI：10.11959/j.issn.2096-0271.2019047
  中图分类号： TP311
- 网络首发：2019-11，
  
  纸质出版：2019-11-15
- 稿件说明：
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丁小欧, 王宏志, 于晟健. 工业时序大数据质量管理[J]. 大数据, 2019,5(6):2019047-1.

Xiaoou DING, Hongzhi WANG, Shengjian YU. Data quality management of industrial temporal big data[J]. Big Data Research, 2019, 5(6): 2019047-1.
丁小欧, 王宏志, 于晟健. 工业时序大数据质量管理[J]. 大数据, 2019,5(6):2019047-1. DOI： 10.11959/j.issn.2096-0271.2019047.

Xiaoou DING, Hongzhi WANG, Shengjian YU. Data quality management of industrial temporal big data[J]. Big Data Research, 2019, 5(6): 2019047-1. DOI： 10.11959/j.issn.2096-0271.2019047.

摘要

工业大数据已经成为我国制造业转型升级的重要战略资源，工业大数据分析问题正引起重视和关注。时序数据作为工业大数据中一种重要的数据形式，存在大量的数据质量问题，需要设计数据清洗方法对其进行检测和有效处理。介绍了工业时序大数据的特点及工业数据质量管理的难点，并对工业时序大数据质量管理的研究现状加以分析、总结，最后，提出了时序大数据质量管理方法和系统性能的提升方向。

Abstract

Industrial big data has become an important strategic resource for the transformation and upgrading of China’s manufacturing industry

and industrial big data analysis is attracting more and more attention.As an important data form of industrial big data

time series have a lot of quality problems

which is necessary to be detected and handled effectively by designing data cleaning methods.The characteristics of industrial time series big data and the difficulties of industrial data quality management were introduced.Then

the recent developments in the area of that was analyzed and summarized.At last

the quality management method of temporal big data and the improvement direction of system performance were put forward.

关键词

Keywords

references

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