A guide to backward paper writing for the data sciences

被引:4
|
作者
Zelner, Jon [1 ,2 ]
Broen, Kelly [1 ,2 ]
August, Ella [1 ,3 ]
机构
[1] Univ Michigan, Dept Epidemiol, Sch Publ Hlth, Ann Arbor, MI 48109 USA
[2] Univ Michigan, Ctr Social Epidemiol & Populat Hlth, Sch Publ Hlth, Ann Arbor, MI 48109 USA
[3] Prepublicat Support Serv PREPSS, Ann Arbor, MI 48109 USA
来源
PATTERNS | 2022年 / 3卷 / 03期
关键词
DSML 3: Development/pre-production: Data science output has been rolled out/validated across multiple domains/problems;
D O I
10.1016/j.patter.2021.100423
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this perspective, we outline a set of best practices for the planning, writing, and revision of scientific papers and other forms of professional communication in the data sciences. We propose a backward approach that begins with clearly identifying the scientific and professional goalsmotivating the work, followed by a purposeful mapping from those goals to each section of a paper. This approach is motivated by the conviction that manuscript writing can be more effective, efficient, creative, and even enjoyable-particularly for early-career researchers-when the overarching goals of the paper and its individual components are clearly mapped out.
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页数:7
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