Literature DB >> 33816893

Making simulation results reproducible-Survey, guidelines, and examples based on Gradle and Docker.

Wilfried Elmenreich1, Philipp Moll1, Sebastian Theuermann1, Mathias Lux1.   

Abstract

This article addresses two research questions related to reproducibility within the context of research related to computer science. First, a survey on reproducibility addressed to researchers in the academic and private sectors is described and evaluated. The survey indicates a strong need for open and easily accessible results, in particular, reproducing an experiment should not require too much effort. The results of the survey are then used to formulate guidelines for making research results reproducible. In addition, this article explores four approaches based on software tools that could bring forward reproducibility in research results. After a general analysis of tools, three examples are further investigated based on actual research projects which are used to evaluate previously introduced tools. Results indicate that the evaluated tools contribute well to making simulation results reproducible but due to conflicting requirements, none of the presented solutions fulfills all intended goals perfectly.
© 2019 Elmenreich et al.

Entities:  

Keywords:  In-silico research; Reproducibility; Simulation

Year:  2019        PMID: 33816893      PMCID: PMC7924710          DOI: 10.7717/peerj-cs.240

Source DB:  PubMed          Journal:  PeerJ Comput Sci        ISSN: 2376-5992


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7.  Scientific research in the age of omics: the good, the bad, and the sloppy.

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Journal:  J Am Med Inform Assoc       Date:  2012-10-04       Impact factor: 4.497

8.  Data sharing in neuroimaging research.

Authors:  Jean-Baptiste Poline; Janis L Breeze; Satrajit Ghosh; Krzysztof Gorgolewski; Yaroslav O Halchenko; Michael Hanke; Christian Haselgrove; Karl G Helmer; David B Keator; Daniel S Marcus; Russell A Poldrack; Yannick Schwartz; John Ashburner; David N Kennedy
Journal:  Front Neuroinform       Date:  2012-04-05       Impact factor: 4.081

9.  phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data.

Authors:  Paul J McMurdie; Susan Holmes
Journal:  PLoS One       Date:  2013-04-22       Impact factor: 3.240

10.  Git can facilitate greater reproducibility and increased transparency in science.

Authors:  Karthik Ram
Journal:  Source Code Biol Med       Date:  2013-02-28
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