Research on the construction of smart museum big data model

Zhiming Zhang, Lingling Hu
{"title":"Research on the construction of smart museum big data model","authors":"Zhiming Zhang, Lingling Hu","doi":"10.1117/12.2667467","DOIUrl":null,"url":null,"abstract":"The current situation of Museum data is generally faced with common problems such as scattered data resources, lack of high-quality cataloguing and labeling information, and difficult data management, resulting in the phenomenon of low data utilization. It is suggested that the establishment of a special institution to centrally manage Museum data assets, the unified design of Museum big data model, and the improvement of data analysis capability are the three measures to improve the big data capability. Two big data model design methods from technology to business and from business to technology are described. We study the three key points of building the museum big data model. The comprehensive application of the above measures, design methods and technical points can effectively ensure the continuous improvement of the museum's big data capability.","PeriodicalId":137914,"journal":{"name":"International Conference on Artificial Intelligence, Virtual Reality, and Visualization","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Artificial Intelligence, Virtual Reality, and Visualization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2667467","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The current situation of Museum data is generally faced with common problems such as scattered data resources, lack of high-quality cataloguing and labeling information, and difficult data management, resulting in the phenomenon of low data utilization. It is suggested that the establishment of a special institution to centrally manage Museum data assets, the unified design of Museum big data model, and the improvement of data analysis capability are the three measures to improve the big data capability. Two big data model design methods from technology to business and from business to technology are described. We study the three key points of building the museum big data model. The comprehensive application of the above measures, design methods and technical points can effectively ensure the continuous improvement of the museum's big data capability.
智慧博物馆大数据模型构建研究
博物馆数据的现状普遍面临数据资源分散、缺乏高质量的编目标注信息、数据管理困难等共性问题,导致数据利用率低的现象。建议建立专门机构对博物馆数据资产进行集中管理,统一设计博物馆大数据模型,提高数据分析能力是提高大数据能力的三项措施。介绍了从技术到业务和从业务到技术两种大数据模型设计方法。本文研究了构建博物馆大数据模型的三个关键点。综合运用上述措施、设计方法和技术要点,可以有效保证博物馆大数据能力的持续提升。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信