DataDeps.jl: Repeatable Data Setup for Reproducible Data Science

Q1 Social Sciences
Lyndon White, R. Togneri, Wei Liu, Bennamoun
{"title":"DataDeps.jl: Repeatable Data Setup for Reproducible Data Science","authors":"Lyndon White, R. Togneri, Wei Liu, Bennamoun","doi":"10.5334/jors.244","DOIUrl":null,"url":null,"abstract":"We present DataDeps.jl: a julia package for the reproducible handling of static datasets to enhance the repeatability of scripts used in the data and computational sciences. It is used to automate the data setup part of running software which accompanies a paper to replicate a result. This step is commonly done manually, which expends time and allows for confusion. This functionality is also useful for other packages which require data to function (e.g. a trained machine learning based model). DataDeps.jl simplifies extending research software by automatically managing the dependencies and makes it easier to run another author’s code, thus enhancing the reproducibility of data science research.","PeriodicalId":37323,"journal":{"name":"Journal of Open Research Software","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Open Research Software","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5334/jors.244","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 3

Abstract

We present DataDeps.jl: a julia package for the reproducible handling of static datasets to enhance the repeatability of scripts used in the data and computational sciences. It is used to automate the data setup part of running software which accompanies a paper to replicate a result. This step is commonly done manually, which expends time and allows for confusion. This functionality is also useful for other packages which require data to function (e.g. a trained machine learning based model). DataDeps.jl simplifies extending research software by automatically managing the dependencies and makes it easier to run another author’s code, thus enhancing the reproducibility of data science research.
DataDeps。可复制数据科学的可重复数据设置
我们介绍DataDeps。Jl:一个Julia包,用于可再现地处理静态数据集,以增强数据和计算科学中使用的脚本的可重复性。它用于自动运行软件的数据设置部分,该软件随论文一起复制结果。这一步通常是手动完成的,这会花费时间并导致混乱。此功能对于其他需要数据才能运行的包也很有用(例如,基于训练有素的机器学习模型)。DataDeps。Jl通过自动管理依赖关系简化了研究软件的扩展,并使运行其他作者的代码变得更容易,从而增强了数据科学研究的可再现性。
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
Journal of Open Research Software
Journal of Open Research Software Social Sciences-Library and Information Sciences
CiteScore
6.50
自引率
0.00%
发文量
7
审稿时长
21 weeks
×
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