Data Observer—a guide to data that can help to inform evidence-based policymaking

Joachim Wagner
{"title":"Data Observer—a guide to data that can help to inform evidence-based policymaking","authors":"Joachim Wagner","doi":"10.1007/s11943-024-00341-5","DOIUrl":null,"url":null,"abstract":"<div><p>For many attempts to inform evidence-based policymaking (or policy-makers in general) researchers have to rely on already available (instead of newly collected) data. These data have to be reliable, accessible (at best, without high hurdles, and with low or no fees to be paid) and findable. One way that helps to find suitable data that are easily accessible (and hopefully reliable) is to look at the contributions published in the <i>Data Observer</i> series described in this paper.</p></div>","PeriodicalId":100134,"journal":{"name":"AStA Wirtschafts- und Sozialstatistisches Archiv","volume":"18 2","pages":"279 - 287"},"PeriodicalIF":0.0000,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"AStA Wirtschafts- und Sozialstatistisches Archiv","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s11943-024-00341-5","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

For many attempts to inform evidence-based policymaking (or policy-makers in general) researchers have to rely on already available (instead of newly collected) data. These data have to be reliable, accessible (at best, without high hurdles, and with low or no fees to be paid) and findable. One way that helps to find suitable data that are easily accessible (and hopefully reliable) is to look at the contributions published in the Data Observer series described in this paper.

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
数据观察员--有助于循证决策的数据指南
在为循证决策(或一般决策者)提供信息的许多尝试中,研究人员必须依靠已有的(而不是新收集的)数据。这些数据必须可靠、可获取(最多是没有高门槛、低费用或无费用)、可查找。找到易于获取(希望可靠)的合适数据的一个方法是查看本文所述的《数据观察家》系列所发表的文章。
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
Vorwort der Herausgeber Connecting algorithmic fairness to quality dimensions in machine learning in official statistics and survey production Automated Bayesian variable selection methods for binary regression models with missing covariate data Fairness als Qualitätskriterium im Maschinellen Lernen – Rekonstruktion des philosophischen Konzepts und Implikationen für die Nutzung außergesetzlicher Merkmale bei qualifizierten Mietspiegeln Interview mit Walter Krämer
×
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