jHound: Large-Scale Profiling of Open JSON Data

M. Möller, Nicolas Berton, Meike Klettke, Stefanie Scherzinger, U. Störl
{"title":"jHound: Large-Scale Profiling of Open JSON Data","authors":"M. Möller, Nicolas Berton, Meike Klettke, Stefanie Scherzinger, U. Störl","doi":"10.18420/btw2019-44","DOIUrl":null,"url":null,"abstract":"We present jHound, a tool for profiling large collections of JSON data, and apply it to thousands of data sets holding open government data. jHound reports key characteristics of JSON documents, such as their nesting depth. As we show, jHound can help detect structural outliers, and most importantly, badly encoded documents: jHound can pinpoint certain cases of documents that use string-typed values where other native JSON datatypes would have been a better match. Moreover, we can detect certain cases of maladaptively structured JSON documents, which obviously do not comply with good data modeling practices. By interactively exploring particular example documents, we hope to inspire discussions in the community about what makes a good JSON encoding.","PeriodicalId":421643,"journal":{"name":"Datenbanksysteme für Business, Technologie und Web","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Datenbanksysteme für Business, Technologie und Web","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18420/btw2019-44","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

Abstract

We present jHound, a tool for profiling large collections of JSON data, and apply it to thousands of data sets holding open government data. jHound reports key characteristics of JSON documents, such as their nesting depth. As we show, jHound can help detect structural outliers, and most importantly, badly encoded documents: jHound can pinpoint certain cases of documents that use string-typed values where other native JSON datatypes would have been a better match. Moreover, we can detect certain cases of maladaptively structured JSON documents, which obviously do not comply with good data modeling practices. By interactively exploring particular example documents, we hope to inspire discussions in the community about what makes a good JSON encoding.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
jHound:开放JSON数据的大规模分析
我们介绍了jHound,这是一个分析大型JSON数据集的工具,并将其应用于数千个包含开放政府数据的数据集。jHound报告JSON文档的关键特征,比如嵌套深度。正如我们所展示的,jHound可以帮助检测结构异常值,最重要的是,可以检测编码错误的文档:jHound可以精确地指出某些使用字符串类型值的文档,而其他本地JSON数据类型可以更好地匹配这些值。此外,我们可以检测到结构不适应的JSON文档的某些情况,这些文档显然不符合良好的数据建模实践。通过交互式地探索特定的示例文档,我们希望激发社区中关于什么是好的JSON编码的讨论。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
SportsTables: A new Corpus for Semantic Type Detection Accelerating Large Table Scan using Processing-In-Memory Technology The InsightsNet Climate Change Corpus (ICCC) On the State of German (Abstractive) Text Summarization The Easiest Way of Turning your Relational Database into a Blockchain - and the Cost of Doing So
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1