研究大数据集:旗舰会议调查

Yi Wei, Shijun Liu, Jiao Sun, Li-zhen Cui, Li Pan, Lei Wu
{"title":"研究大数据集:旗舰会议调查","authors":"Yi Wei, Shijun Liu, Jiao Sun, Li-zhen Cui, Li Pan, Lei Wu","doi":"10.1109/BigDataCongress.2016.62","DOIUrl":null,"url":null,"abstract":"It is obvious that big data can bring us new opportunities to discover valuable information. Apparently, corresponding big datasets are powerful tools for scholars, which connect theoretical studies to reality. They can help scholars to evaluate their achievements and find new problems. In recent years, there has been a significant growth in research data repositories and registries. However, these infrastructures are fragmented across institutions, countries and research domains. As such, finding research datasets is not a trivial task for many researchers. Thus we investigated 195 papers regarding big data on some notable international conferences in recent 3 years, and also gathered 285 datasets mentioned in them. In this paper, we present and analyze our survey results in terms of the status quo of big data research and datasets from different aspects. In particular, we propose two different taxonomies of big datasets and classify our surveyed datasets into them. In addition, we also give a brief introduction about 7 widely accepted data collections online. Finally, some basic principles for scholars in choosing and using big datasets are given.","PeriodicalId":407471,"journal":{"name":"2016 IEEE International Congress on Big Data (BigData Congress)","volume":"16 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Big Datasets for Research: A Survey on Flagship Conferences\",\"authors\":\"Yi Wei, Shijun Liu, Jiao Sun, Li-zhen Cui, Li Pan, Lei Wu\",\"doi\":\"10.1109/BigDataCongress.2016.62\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"It is obvious that big data can bring us new opportunities to discover valuable information. Apparently, corresponding big datasets are powerful tools for scholars, which connect theoretical studies to reality. They can help scholars to evaluate their achievements and find new problems. In recent years, there has been a significant growth in research data repositories and registries. However, these infrastructures are fragmented across institutions, countries and research domains. As such, finding research datasets is not a trivial task for many researchers. Thus we investigated 195 papers regarding big data on some notable international conferences in recent 3 years, and also gathered 285 datasets mentioned in them. In this paper, we present and analyze our survey results in terms of the status quo of big data research and datasets from different aspects. In particular, we propose two different taxonomies of big datasets and classify our surveyed datasets into them. In addition, we also give a brief introduction about 7 widely accepted data collections online. Finally, some basic principles for scholars in choosing and using big datasets are given.\",\"PeriodicalId\":407471,\"journal\":{\"name\":\"2016 IEEE International Congress on Big Data (BigData Congress)\",\"volume\":\"16 2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE International Congress on Big Data (BigData Congress)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BigDataCongress.2016.62\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Congress on Big Data (BigData Congress)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BigDataCongress.2016.62","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

显然,大数据可以给我们带来发现有价值信息的新机会。显然,相应的大数据集是学者们将理论研究与现实联系起来的有力工具。他们可以帮助学者评估他们的成就和发现新的问题。近年来,研究数据存储库和注册表有了显著的增长。然而,这些基础设施在各个机构、国家和研究领域是分散的。因此,对许多研究人员来说,寻找研究数据集不是一项微不足道的任务。因此,我们调查了近3年来在一些重要的国际会议上发表的195篇关于大数据的论文,并收集了其中提到的285个数据集。在本文中,我们从不同方面的大数据研究现状和数据集来展示和分析我们的调查结果。特别地,我们提出了两种不同的大数据集分类法,并将我们调查的数据集归入其中。此外,我们还简要介绍了网上被广泛接受的7个数据收集。最后,给出了学者选择和使用大数据集的一些基本原则。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Big Datasets for Research: A Survey on Flagship Conferences
It is obvious that big data can bring us new opportunities to discover valuable information. Apparently, corresponding big datasets are powerful tools for scholars, which connect theoretical studies to reality. They can help scholars to evaluate their achievements and find new problems. In recent years, there has been a significant growth in research data repositories and registries. However, these infrastructures are fragmented across institutions, countries and research domains. As such, finding research datasets is not a trivial task for many researchers. Thus we investigated 195 papers regarding big data on some notable international conferences in recent 3 years, and also gathered 285 datasets mentioned in them. In this paper, we present and analyze our survey results in terms of the status quo of big data research and datasets from different aspects. In particular, we propose two different taxonomies of big datasets and classify our surveyed datasets into them. In addition, we also give a brief introduction about 7 widely accepted data collections online. Finally, some basic principles for scholars in choosing and using big datasets are given.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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:604180095
Book学术官方微信