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Learning from open source software projects to improve scientific review
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 comprehen...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2012
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3328792/ https://www.ncbi.nlm.nih.gov/pubmed/22529798 http://dx.doi.org/10.3389/fncom.2012.00018 |
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author | Ghosh, Satrajit S. Klein, Arno Avants, Brian Millman, K. Jarrod |
author_facet | Ghosh, Satrajit S. Klein, Arno Avants, Brian Millman, K. Jarrod |
author_sort | Ghosh, Satrajit S. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-3328792 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-33287922012-04-23 Learning from open source software projects to improve scientific review Ghosh, Satrajit S. Klein, Arno Avants, Brian Millman, K. Jarrod Front Comput Neurosci Neuroscience 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. Frontiers Media S.A. 2012-04-18 /pmc/articles/PMC3328792/ /pubmed/22529798 http://dx.doi.org/10.3389/fncom.2012.00018 Text en Copyright © 2012 Ghosh, Klein, Avants and Millman. http://www.frontiersin.org/licenseagreement This is an open-access article distributed under the terms of the Creative Commons Attribution Non Commercial License, which permits non-commercial use, distribution, and reproduction in other forums, provided the original authors and source are credited. |
spellingShingle | Neuroscience Ghosh, Satrajit S. Klein, Arno Avants, Brian Millman, K. Jarrod Learning from open source software projects to improve scientific review |
title | Learning from open source software projects to improve scientific review |
title_full | Learning from open source software projects to improve scientific review |
title_fullStr | Learning from open source software projects to improve scientific review |
title_full_unstemmed | Learning from open source software projects to improve scientific review |
title_short | Learning from open source software projects to improve scientific review |
title_sort | learning from open source software projects to improve scientific review |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3328792/ https://www.ncbi.nlm.nih.gov/pubmed/22529798 http://dx.doi.org/10.3389/fncom.2012.00018 |
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