Good enough practices in scientific computing

PLoS Computational Biology

Volumn 13, Issue 6, 2017, Pages

  Wilson, Greg ^a   Bryan, Jennifer ^b   Cranston, Karen ^c   Kitzes, Justin ^d   Nederbragt, Lex ^e   Teal, Tracy K ^f  

^a The Software Carpentry Foundation   (United States)

^b UNIVERSITY OF BRITISH COLUMBIA   (Canada)

^c DUKE UNIVERSITY   (United States)

^d UNIVERSITY OF CALIFORNIA   (United States)

^e UNIVERSITY OF OSLO   (Norway)

^f Data Carpentry   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; CONTROL SYSTEM; DATA ANALYSIS; DATA PROCESSING; INFORMATION PROCESSING; MATHEMATICAL COMPUTING; MEDICAL RESEARCH; SCIENTIFIC COMPUTING; SOFTWARE; TEAMWORK; WRITING; COMPUTER ANALYSIS; COMPUTER SECURITY; DOCUMENTATION; MEASUREMENT ACCURACY; PRACTICE GUIDELINE; RESEARCH; SCIENCE; STANDARDS;

COMPUTER SECURITY; COMPUTING METHODOLOGIES; DATA ACCURACY; DOCUMENTATION; GUIDELINES AS TOPIC; RESEARCH; SCIENCE; SOFTWARE;

EID: 85021716403     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1005510     Document Type: Article

References (20)

1. Wilson G, Aruliah DA, Brown CT, Hong NPC, Davis M, Guy RT, et al. Best Practices for Scientific Computing. PLoS Biol. 2014;12(1):e1001745. doi: 10.1371/journal.pbio.1001745 24415924
2. Gentzkow M, Shapiro JM. Code and Data for the Social Sciences: A Practitioner's Guide; 2014. https://web.stanford.edu/~gentzkow/research/CodeAndData.pdf.
3. Noble WS, A Quick Guide to Organizing Computational Biology Projects. PLoS Comput Biol. 2009;5(7). doi: 10.1371/journal.pcbi.1000424 19649301
4. Brown CT. How to grow a sustainable software development process; 2015. http://ivory.idyll.org/blog/2015-growing-sustainable-software-development-process.html.
5. Wickham H, Tidy Data. Journal of Statistical Software. 2014;59(1):1–23. doi: 10.18637/jss.v059.i10
6. Kitzes J. Reproducible Workflows; 2016. http://datasci.kitzes.com/lessons/python/reproducible_workflow.html.
7. Sandve GK, Nekrutenko A, Taylor J, Hovig E, Ten Simple Rules for Reproducible Computational Research. PLoS Comput Biol. 2013;9(10). doi: 10.1371/journal.pcbi.1003285 24204232
8. Hart EM, Barmby P, LeBauer D, Michonneau F, Mount S, Mulrooney P, et al. Ten simple rules for digital data storage. PLoS Comput Biol. 2016; doi: 10.1371/journal.pcbi.1005097 27764088
9. U. of Illinois Library. File Formats and Organization. http://www.library.illinois.edu/sc/services/data_management/file_formats.html.
10. White EP, Baldridge E, Brym ZT, Locey KJ, McGlinn DJ, Supp SR, Nine Simple Ways to Make It Easier to (Re)use Your Data. Ideas in Ecology and Evolution. 2013;6(2).
11. Wickes E. Comment on "Metadata"; 2015. https://github.com/swcarpentry/good-enough-practices-in-scientific-computing/issues/3#issuecomment-157410442.
12. Hunt A, Thomas D, The Pragmatic Programmer. Addison-Wesley; 1999.
13. Martin Robert C, Clean Code: A Handbook of Agile Software Craftsmanship. Addison-Wesley; 2008.
14. McConnell Steve, Code Complete: A Practical Handbook of Software Construction. Microsoft Press; 2004.
15. Miller GA, The Magical Number Seven, Plus or Minus Two: Some Limits on Our Capacity for Processing Information. Psychological Review. 1956;63(2):81–97 13310704
16. Steinmacher I, Graciotto Silva M, Gerosa M, Redmiles DF, A Systematic Literature Review on the Barriers Faced by Newcomers to Open Source Software Projects. Information and Software Technology. 2015;59(C). doi: 10.1016/j.infsof.2014.11.001
17. St Laurent AM, Understanding Open Source and Free Software Licensing. O'Reilly Media; 2004. http://www.oreilly.com/openbook/osfreesoft/book/.
18. Gawande A, The Checklist Manifesto: How to Get Things Right. Picador; 2011.
19. Raj A. From over-reproducibility to a reproducibility wish-list; 2016. http://rajlaboratory.blogspot.ca/2016/03/from-over-reproducibility-to.html.
20. Petre M, Wilson G. Code Review For and By Scientists. In: Katz D, editor. Proc. WSSSPE 2014; 2014.