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Good enough practices in scientific computing

Overview of attention for article published in PLoS Computational Biology, June 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#11 of 4,555)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

blogs
5 blogs
twitter
825 tweeters
facebook
5 Facebook pages
googleplus
4 Google+ users

Readers on

mendeley
468 Mendeley
citeulike
9 CiteULike
Title
Good enough practices in scientific computing
Published in
PLoS Computational Biology, June 2017
DOI 10.1371/journal.pcbi.1005510
Pubmed ID
Authors

Greg Wilson, Jennifer Bryan, Karen Cranston, Justin Kitzes, Lex Nederbragt, Tracy K. Teal, Wilson, Greg, Bryan, Jennifer, Cranston, Karen, Kitzes, Justin, Nederbragt, Lex, Teal, Tracy K.

Abstract

Computers are now essential in all branches of science, but most researchers are never taught the equivalent of basic lab skills for research computing. As a result, data can get lost, analyses can take much longer than necessary, and researchers are limited in how effectively they can work with software and data. Computing workflows need to follow the same practices as lab projects and notebooks, with organized data, documented steps, and the project structured for reproducibility, but researchers new to computing often don't know where to start. This paper presents a set of good computing practices that every researcher can adopt, regardless of their current level of computational skill. These practices, which encompass data management, programming, collaborating with colleagues, organizing projects, tracking work, and writing manuscripts, are drawn from a wide variety of published sources from our daily lives and from our work with volunteer organizations that have delivered workshops to over 11,000 people since 2010.

Twitter Demographics

The data shown below were collected from the profiles of 825 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 468 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 11 2%
United Kingdom 5 1%
Germany 3 <1%
Spain 3 <1%
France 2 <1%
Sweden 2 <1%
Australia 1 <1%
South Africa 1 <1%
Italy 1 <1%
Other 7 1%
Unknown 432 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 136 29%
Researcher 130 28%
Student > Master 47 10%
Student > Bachelor 36 8%
Professor > Associate Professor 27 6%
Other 92 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 130 28%
Biochemistry, Genetics and Molecular Biology 49 10%
Computer Science 47 10%
Environmental Science 36 8%
Unspecified 31 7%
Other 175 37%

Attention Score in Context

This research output has an Altmetric Attention Score of 580. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 May 2018.
All research outputs
#8,178
of 10,782,532 outputs
Outputs from PLoS Computational Biology
#11
of 4,555 outputs
Outputs of similar age
#585
of 260,765 outputs
Outputs of similar age from PLoS Computational Biology
#1
of 156 outputs
Altmetric has tracked 10,782,532 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,555 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.7. This one has done particularly well, scoring higher than 99% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 260,765 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 156 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.