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Code sharing in ecology and evolution increases citation rates but remains uncommon.

Authors :
Maitner B
Santos Andrade PE
Lei L
Kass J
Owens HL
Barbosa GCG
Boyle B
Castorena M
Enquist BJ
Feng X
Park DS
Paz A
Pinilla-Buitrago G
Merow C
Wilson A
Source :
Ecology and evolution [Ecol Evol] 2024 Aug 27; Vol. 14 (8), pp. e70030. Date of Electronic Publication: 2024 Aug 27 (Print Publication: 2024).
Publication Year :
2024

Abstract

Biologists increasingly rely on computer code to collect and analyze their data, reinforcing the importance of published code for transparency, reproducibility, training, and a basis for further work. Here, we conduct a literature review estimating temporal trends in code sharing in ecology and evolution publications since 2010, and test for an influence of code sharing on citation rate. We find that code is rarely published (only 6% of papers), with little improvement over time. We also found there may be incentives to publish code: Publications that share code have tended to be low-impact initially, but accumulate citations faster, compensating for this deficit. Studies that additionally meet other Open Science criteria, open-access publication, or data sharing, have still higher citation rates, with publications meeting all three criteria (code sharing, data sharing, and open access publication) tending to have the most citations and highest rate of citation accumulation.<br />Competing Interests: The authors declare no competing interests.<br /> (© 2024 The Author(s). Ecology and Evolution published by John Wiley & Sons Ltd.)

Details

Language :
English
ISSN :
2045-7758
Volume :
14
Issue :
8
Database :
MEDLINE
Journal :
Ecology and evolution
Publication Type :
Academic Journal
Accession number :
39206460
Full Text :
https://doi.org/10.1002/ece3.70030