JOURNAL ARTICLE

Learning from open source software projects to improve scientific review

Satrajit GhoshArno KleinBrian AvantsK. Jarrod Millman

Year: 2012 Journal:   Frontiers in Computational Neuroscience Vol: 6 Pages: 18-18   Publisher: Frontiers Media

Abstract

Peer-reviewed publications are the primary mechanism for sharing scientific results. The current peer-review process is, however, fraught with many problems that undermine the pace, validity, and credibility of science. We highlight five salient problems: (1) reviewers are expected to have comprehensive expertise; (2) reviewers do not have sufficient access to methods and materials to evaluate a study; (3) reviewers are neither identified nor acknowledged; (4) there is no measure of the quality of a review; and (5) reviews take a lot of time, and once submitted cannot evolve. We propose that these problems can be resolved by making the following changes to the review process. Distributing reviews to many reviewers would allow each reviewer to focus on portions of the article that reflect the reviewer's specialty or area of interest and place less of a burden on any one reviewer. Providing reviewers materials and methods to perform comprehensive evaluation would facilitate transparency, greater scrutiny, and replication of results. Acknowledging reviewers makes it possible to quantitatively assess reviewer contributions, which could be used to establish the impact of the reviewer in the scientific community. Quantifying review quality could help establish the importance of individual reviews and reviewers as well as the submitted article. Finally, we recommend expediting post-publication reviews and allowing for the dialog to continue and flourish in a dynamic and interactive manner. We argue that these solutions can be implemented by adapting existing features from open-source software management and social networking technologies. We propose a model of an open, interactive review system that quantifies the significance of articles, the quality of reviews, and the reputation of reviewers.

Keywords:
Computer science Transparency (behavior) Scrutiny Process (computing) Pace Credibility Quality (philosophy) Data science Dialog box Social media Salient World Wide Web Political science

Metrics

27
Cited By
4.15
FWCI (Field Weighted Citation Impact)
16
Refs
0.94
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Wikis in Education and Collaboration
Social Sciences →  Social Sciences →  Communication
Software Engineering Research
Physical Sciences →  Computer Science →  Information Systems
Open Source Software Innovations
Physical Sciences →  Computer Science →  Computer Science Applications
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